diff --git a/stride/core.py b/stride/core.py index 3158d32..09c9cab 100644 --- a/stride/core.py +++ b/stride/core.py @@ -392,7 +392,8 @@ def _dealloc(*args): if nxt.name_idx in prev: input_grad = await _maybe_sum(prev[nxt.name_idx], input_grad) - if not isinstance(input_grad, types.awaitable_types) and nxt.op.runtime_id != runtime.uid: + if not isinstance(input_grad, types.awaitable_types) \ + and hasattr(nxt.op, 'runtime_id') and nxt.op.runtime_id != runtime.uid: input_grad = await runtime.put(input_grad) deallocs.append(input_grad) diff --git a/stride/optimisation/optimisation_loop.py b/stride/optimisation/optimisation_loop.py index 68d8128..eaa8bc7 100644 --- a/stride/optimisation/optimisation_loop.py +++ b/stride/optimisation/optimisation_loop.py @@ -664,11 +664,7 @@ def clear(self, **kwargs): self._current_block = None self.running_id = 0 - load_kwargs = dict(path=self.problem.output_folder, - project_name=self.problem.name, version=0) - load_kwargs.update(kwargs) - - self.remove_file(**load_kwargs) + self.remove_file(**kwargs) def blocks(self, num, *iters, restart=False, restart_id=-1, **kwargs): """ diff --git a/stride/problem/data.py b/stride/problem/data.py index 2f5a676..187945e 100644 --- a/stride/problem/data.py +++ b/stride/problem/data.py @@ -756,6 +756,7 @@ def __set_desc__(self, description, **kwargs): inner = [] for each in description.inner: + each = [e.decode() if isinstance(e, bytes) else e for e in each] inner.append(slice( int(each[0]) if each[0] != 'None' else None, int(each[1]) if each[1] != 'None' else None, diff --git a/stride_examples/tutorials/01_basics.ipynb b/stride_examples/tutorials/01_basics.ipynb index f33345c..01306d9 100644 --- a/stride_examples/tutorials/01_basics.ipynb +++ b/stride_examples/tutorials/01_basics.ipynb @@ -80,7 +80,18 @@ "execution_count": 1, "id": "manual-genius", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "x" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from stride import Scalar\n", "from stride_examples import f, g, h\n", @@ -187,7 +198,18 @@ "execution_count": 2, "id": "psychological-distributor", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "scalar" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from stride import Operator, Scalar\n", "\n", @@ -266,10 +288,11 @@ "output_type": "stream", "text": [ "Updating variable m,\n", - "\t grad before processing in range [-1.050360e+03, -1.050360e+03]\n", - "\t grad after processing in range [-1.050360e+03, -1.050360e+03]\n", - "\t variable range before update [-1.050360e+03, -1.050360e+03]\n", - "\t variable range after update [0.000000e+00, 0.000000e+00]\n" + "\t grad before processing in range [2.627646e-17, 2.627646e-17]\n", + "\t grad after processing in range [1.313823e-19, 1.313823e-19]\n", + "\t variable range before update [2.627646e-17, 2.627646e-17]\n", + "\t taking final update step of 1.000000e+00 [unclipped step of 1.000000e+00]\n", + "\t variable range after update [2.614507e-17, 2.614507e-17]\n" ] }, { @@ -313,35 +336,41 @@ "output_type": "stream", "text": [ "Updating variable m,\n", - "\t grad before processing in range [-1.050360e+03, -1.050360e+03]\n", - "\t grad after processing in range [-1.050360e+03, -1.050360e+03]\n", - "\t variable range before update [0.000000e+00, 0.000000e+00]\n", - "\t variable range after update [1.050360e+03, 1.050360e+03]\n", + "\t grad before processing in range [5.242153e-17, 5.242153e-17]\n", + "\t grad after processing in range [1.307254e-19, 1.307254e-19]\n", + "\t variable range before update [2.614507e-17, 2.614507e-17]\n", + "\t taking final update step of 1.000000e+00 [unclipped step of 1.000000e+00]\n", + "\t variable range after update [2.601435e-17, 2.601435e-17]\n", "Updating variable m,\n", - "\t grad before processing in range [1.050360e+03, 1.050360e+03]\n", - "\t grad after processing in range [1.050360e+03, 1.050360e+03]\n", - "\t variable range before update [1.050360e+03, 1.050360e+03]\n", - "\t variable range after update [0.000000e+00, 0.000000e+00]\n", + "\t grad before processing in range [7.843588e-17, 7.843588e-17]\n", + "\t grad after processing in range [1.300717e-19, 1.300717e-19]\n", + "\t variable range before update [2.601435e-17, 2.601435e-17]\n", + "\t taking final update step of 1.000000e+00 [unclipped step of 1.000000e+00]\n", + "\t variable range after update [2.588428e-17, 2.588428e-17]\n", "Updating variable m,\n", - "\t grad before processing in range [1.050360e+03, 1.050360e+03]\n", - "\t grad after processing in range [1.050360e+03, 1.050360e+03]\n", - "\t variable range before update [0.000000e+00, 0.000000e+00]\n", - "\t variable range after update [-1.050360e+03, -1.050360e+03]\n", + "\t grad before processing in range [1.043202e-16, 1.043202e-16]\n", + "\t grad after processing in range [1.294214e-19, 1.294214e-19]\n", + "\t variable range before update [2.588428e-17, 2.588428e-17]\n", + "\t taking final update step of 1.000000e+00 [unclipped step of 1.000000e+00]\n", + "\t variable range after update [2.575486e-17, 2.575486e-17]\n", "Updating variable m,\n", - "\t grad before processing in range [-1.050360e+03, -1.050360e+03]\n", - "\t grad after processing in range [-1.050360e+03, -1.050360e+03]\n", - "\t variable range before update [-1.050360e+03, -1.050360e+03]\n", - "\t variable range after update [0.000000e+00, 0.000000e+00]\n", + "\t grad before processing in range [1.300750e-16, 1.300750e-16]\n", + "\t grad after processing in range [1.287743e-19, 1.287743e-19]\n", + "\t variable range before update [2.575486e-17, 2.575486e-17]\n", + "\t taking final update step of 1.000000e+00 [unclipped step of 1.000000e+00]\n", + "\t variable range after update [2.562608e-17, 2.562608e-17]\n", "Updating variable m,\n", - "\t grad before processing in range [-1.050360e+03, -1.050360e+03]\n", - "\t grad after processing in range [-1.050360e+03, -1.050360e+03]\n", - "\t variable range before update [0.000000e+00, 0.000000e+00]\n", - "\t variable range after update [1.050360e+03, 1.050360e+03]\n", + "\t grad before processing in range [1.557011e-16, 1.557011e-16]\n", + "\t grad after processing in range [1.281304e-19, 1.281304e-19]\n", + "\t variable range before update [2.562608e-17, 2.562608e-17]\n", + "\t taking final update step of 1.000000e+00 [unclipped step of 1.000000e+00]\n", + "\t variable range after update [2.549795e-17, 2.549795e-17]\n", "Updating variable m,\n", - "\t grad before processing in range [1.050360e+03, 1.050360e+03]\n", - "\t grad after processing in range [1.050360e+03, 1.050360e+03]\n", - "\t variable range before update [1.050360e+03, 1.050360e+03]\n", - "\t variable range after update [0.000000e+00, 0.000000e+00]\n" + "\t grad before processing in range [1.811990e-16, 1.811990e-16]\n", + "\t grad after processing in range [1.274898e-19, 1.274898e-19]\n", + "\t variable range before update [2.549795e-17, 2.549795e-17]\n", + "\t taking final update step of 1.000000e+00 [unclipped step of 1.000000e+00]\n", + "\t variable range after update [2.537046e-17, 2.537046e-17]\n" ] } ], @@ -389,7 +418,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.5" + "version": "3.11.8" } }, "nbformat": 4, diff --git a/stride_examples/tutorials/02_problem_definition.ipynb b/stride_examples/tutorials/02_problem_definition.ipynb index 3fd321d..108a349 100644 --- a/stride_examples/tutorials/02_problem_definition.ipynb +++ b/stride_examples/tutorials/02_problem_definition.ipynb @@ -196,7 +196,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.5" + "version": "3.11.8" } }, "nbformat": 4, diff --git a/stride_examples/tutorials/03_acoustic_modelling.ipynb b/stride_examples/tutorials/03_acoustic_modelling.ipynb index b983e94..f77f73a 100644 --- a/stride_examples/tutorials/03_acoustic_modelling.ipynb +++ b/stride_examples/tutorials/03_acoustic_modelling.ipynb @@ -34,7 +34,7 @@ "outputs": [], "source": [ "from stride import Space, Time, Grid\n", - "%matplotlib widget\n", + "%matplotlib ipympl\n", "\n", "space = Space(shape=(200, 200), extra=(50, 50), absorbing=(40, 40), spacing=0.4e-3)\n", "time = Time(start=0.0e-6, step=0.05e-6, num=2000)\n", @@ -78,21 +78,30 @@ "id": "veterinary-ultimate", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Qt: Session management error: None of the authentication protocols specified are supported\n", + "QApplication: invalid style override 'gtk' passed, ignoring it.\n", + "\tAvailable styles: Windows, Fusion\n" + ] + }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d1d5becf18d246b090b4ef3ff80281ed", + "model_id": "ab98dab4001b4677a04d784453b33c73", "version_major": 2, "version_minor": 0 }, - 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", 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", 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Gqauryz333FO5eRYAAHRkTsFaTU888UQWLVqU2tra7Lrrrsu1V1VVVa4//+ijjxZdHgAAtEsCyGqaOnVqkg8v1dilS5cW+zRdRrOpLwAAdHQtf3NmpebMmZMk2WCDDVrt09TW1HdZ9fX1qa+vrzxvbGzMu+++mz59+lSu9Q8AQPtRLpfz3nvvpV+/fq50upoEkNW0cOHCJEl1dXWrfWpqapIkCxYsaLH94osvzgUXXLD2iwMA4GM1c+bMbL755m1dxjpJAFlNTXfOXbRoUat9mmY3unbt2mL7ueeem7PPPrvyfN68eRkwYEBmzpyZHj16rMVqAYrzt7/9LePGjcsTTzyRZ599Ni+88MIK/1/Zq1evDB48OIMGDVruZ+/evQusHGDl6urq0r9//6y//vptXco6SwBZTSs7vWrpttZO06qpqanMkiytR48eAgiwztprr72y1157VZ4vWbIk06dPz3PPPZe//e1vmTZtWqZNm5apU6dm1qxZmTt3bh5//PE8/vjjyx3rqKOOys0335zOnTsX+RYAVsrp8qtPAFlNQ4YMSZLMmDEjixcvbnEh+vTp05v1BViXlMvlNDQ0ZNGiRS1u9fX1WbBgwUfe6urqsmTJkvTu3Tv19fWZPXt2qzXcddddmT9/vr80AnyCCCCraZdddklVVVUWLlyYSZMmtXgfkIkTJyZJs78EAh1TY2NjFi1alIaGhsr2UZ6vat+mYNBaaFhRmFh2X0NDQ+GfU3V1dfr165fNNtssQ4YMyWmnnSZ8AHzCCCCrqUePHjnooINy11135dprr10ugNx8882pq6tLnz59sv/++7dNkfAJ1NDQkPnz52f+/PmVL82r+6V+db/kr87zxsbGtv7o1lipVEpNTU2qq6srW21tbbp27fqRth49eqRnz54tbrW1tU5rAPiEE0DWwL/927/l7rvvzjXXXJP9998/X/nKV5IkTz31VGVx+ahRo1Z4pSzo6Mrlcm644YacffbZaWxszHrrrZdyuVxpK5fLWbJkSSV0LF68uI0rXnuqqqqabdXV1a0+X1Fb07ZsOKiurm5x3+r2sQ4DgLWhVG76Tc9q+cEPfpDvfve7ST688WD37t0zefLkNDY25rDDDsutt966yr+06+rq0rNnz8ybN88idDqM5557Lttvv31bl9FM01/6a2trK3/hb3q+9OM1ed70hb5z587p1KlT5fFHfd6pU6dmm9kDgI+X72trTgBZC+64445cccUVefzxx9PQ0JAhQ4bklFNOyTe/+c2P9BdD/6DpiBoaGvKtb30rv/zlL9u6lE+MZUNJSyFlZX3WxphP4mu11H/ZfSt73pZ9SqWSkApryPe1NSeAtCP+QcP/aroC09JXT1q8eHFlTUXT42V/ruq+FbUtWbIkjY2NWbJkyXKP27IN1pb2GpC89prVt+wsaUv7VvRYQF01vq+tOWtAgHapVCpV1h/07NmzrctpFxobG1sMJ+VyudK2OtuajG/L1y56/JIlSyrrklZ2nJU9X1tj1vTfEiyrtTDT2uPV7du5c+d06dIlVVVVH+ln08Us1ltvvdTW1qa+vj6LFy/OV77ylXTv3r2tPz5WkQACsI5o+mLQ0n2H6JiWDURrI+i0p4DV3sYsWbIkixcvzuLFiyt/BFj2cWvtrf1s7Zhtpen9rmsX/Lj55ptz7733tnUZrCK/xQBoVdMXsaYvuh/1+ZqM/aQce12p85N87JWFjFXpVy47Y709Gz58eFuXwEcggMBqWNEvqNZ+Ebb0eE3bvW7HqfHjet0VfZkD1lzTOo1lLwawKus61uaYpuelUqnZaVAtnRq1OvvXxjGW3d90yfFlLxW+9PNu3bqla9eubf2fmY9IAOngFi5cmHfeeafZgtxlF+i2tu+j9Gk6V71pW/b5yvavzpiP81jAR7f0F6ClH3/U58Yau6pjm75st8UX/qVrAJoTQDqwH/3oR/nXf/3Xti6jw2npF2drv0BbevxR+hbxGu2tHu955X1b6/9Rn3+UvgDQRADpwMaNG9fWJaxTSqVS5SocLW1NV/RY+uoeLT1uml5e+q9pq7J9nGOaviyubvu6eAxfigGgbQggHdjYsWMzbty4dOnSpXKfhYULF1YeN51CtexVO1Z0RY+10X/ZtnK5vMLTqYo6LapcLmfRokVZtGjRx/5aFKM9BCHHKO4YLZ1v3hTSBVKA4gggHVhtbW0+//nPt3UZa82yC8NXZS3IyrZP4timULfs/tY+v1Vtb+tjrM6iaWt6aFIqLb8wd1UXza6NPk0zqVVVVR/LVlNTk/XWW6+y1dbWCl1AmxFA+MRY+gsEHU9LV4JaV8OUY6zdY6zKXeTL5XJl5rUjuvHGG/P3f//3bV0G0EEIIMAnwtILn2FZTadyrsrWFFqW3RYvXpwFCxZk/vz5LZ622tq2Kv0bGhra9PP5j//4DwEEKIwAAkCbamxsrKyvWnarr69vta3o/uva7EhNTU1qa2uX+9l0UYxOnTpl0aJFGTx4cC6//PK2LhfoQAQQAFpVLpcze/bsvPHGG3n77bfz3nvv5f3332/2c9l9K/pS31Lbqpwi1R517ty5xZukrWxb0/4thYpl91VXV1vjAbRbAggAFTNmzMgFF1yQZ555Jq+//nrefPPNwk8P6tKly8f+JX5N+1ZVVVlvBrCaBBAAKs4+++z88Y9/bLFto402yhZbbJH1118/3bt3b/az6XH37t2b/RX+o37pr6qqso4H4BNOAAGg4thjj81tt93W4qzHW2+9lcbGxgwdOjRbbLFFhg4dmm222SZDhw7NoEGD0qWLXykArFypvDoXz+djUVdXl549e2bevHnp0aNHW5cDdFCLFi3KM888k//v//v/8txzz+X555/PlClTMnPmzFbHVFVVZfDgwdlmm22y884758wzz0yvXr2KKxqgIL6vrTkBpB3xDxpozz744IO88MILlUDS9POFF17I/Pnzm/UdMWJErrnmmjaqFODj4/vamjNfDsAq6datW3bZZZfssssuzfY3Njbm1VdfzfPPP5/vf//7efDBB/PWW2+1UZUAtHcCCABrpFOnThkwYEAGDBiQGTNm5MEHH2zrkgBox1xqBAAAKIwAAgAAFEYAAQAACiOAAAAAhRFAAACAwgggAABAYQQQAACgMAIIAABQGAEEAAAojAACAAAURgABAAAKI4AAAACFEUAAAIDCCCAAAEBhBBAAAKAwAggAAFAYAQQAACiMAAIAABRGAAEAAAojgAAAAIURQAAAgMIIIAAAQGEEEAAAoDACCAAAUBgBBAAAKIwAAgAAFEYAAQAACiOAAAAAhRFAAACAwgggAABAYQQQAACgMAIIAABQGAEEAAAojAACAAAURgABAAAKI4AAAACFEUAAAIDCCCAAAEBhBBAAAKAwAggAAFAYAQQAACiMAAIAABRGAAEAAAojgAAAAIURQAAAgMIIIAAAQGEEEAAAoDACCAAAUBgBBAAAKIwAAgAAFEYAAQAACiOAAAAAhRFAAACAwgggAABAYTp8ACmXy3nwwQczcuTI7L333unVq1eqq6vTr1+/HHPMMbn//vtXOP7hhx/OEUcckb59+6Zr167ZbrvtcuGFF2bhwoUFvQMAAFh3dPgA8pe//CX77LNPLr300kycODEbb7xxPvWpT+W9997LLbfckgMPPDD//u//3uLY66+/Pvvss09uu+221NTUZNttt820adNy3nnnZd999838+fMLfjcAANC+dfgAUi6Xs9VWW+Wqq67KO++8k+effz6TJk3K7Nmzc+655yZJLrrootxxxx3Nxr388ssZMWJElixZkksuuSQzZ87MpEmTMnXq1AwdOjQTJ07MqFGj2uItAQBAu9XhA8iee+6Zv/3tb/nGN76RDTbYoLK/uro6//f//t984QtfSJKMGTOm2bjRo0envr4+hxxySEaOHJlSqZQkGThwYH71q18lSa6++uq8+eabBb0TAABo/zp8AOnRo0e6dOnSavvBBx+cJHnhhRcq+8rlcsaOHZskGTFixHJjhg0blm222SYNDQ259dZb13LFAACw7urwAWRlmhaTd+3atbJvxowZef3115Mkn/nMZ1oc17T/0Ucf/ZgrBACAdYcAsgLlcjk333xzkuZBY+rUqUmSmpqa9OvXr8WxgwYNatYXAABIWj/3iIwZMyZPPPFEqqurc9ZZZ1X2z5kzJ0nSq1evytqPZTWtJ2nq25L6+vrU19dXntfV1a2FqgEAoP0yA9KKSZMm5cwzz0zy4VWwBg8eXGlrOi2rurq61fE1NTVJkgULFrTa5+KLL07Pnj0rW//+/ddG6QAA0G4JIC146aWXcvjhh2fhwoX56le/mm9/+9vN2mtra5MkixYtavUYTTMbS68dWda5556befPmVbaZM2euheoBAKD9cgrWMt54440cfPDBef3113PYYYfluuuuW+40q6bTq+bOnZtyudziaVhNp14tfWnfZdXU1FRmSgAAoCMwA7KUd999NwcffHBefPHF7Lfffrn55ptTVVW1XL8hQ4Yk+XCWY9asWS0ea/r06c36AgAAAkjF+++/n0MPPTSTJ0/OHnvskdtvv73V06cGDBiQTTbZJEny0EMPtdinaf9ee+318RQMAADrIAEkH85kHHHEEXn00Uez/fbb5+67787666/fav9SqZSjjjoqSXLttdcu1z5hwoRMmTIlVVVVGT58+MdWNwAArGs6fABZsmRJvvzlL+cvf/lLBg8enD//+c/p3bv3SseNHDky1dXVuffeezN69OiUy+UkySuvvJJTTz01SXLaaadVZkoAAACL0HPTTTflv/7rv5IknTp1yrHHHttiv0033bRyU8Ik2XLLLTNmzJiccsopGTVqVH784x9no402yuTJk9PQ0JDddtsto0ePLuItAADAOqPDB5ClbwQ4derUVu9cPnDgwOX2nXjiidlqq61y8cUXZ8KECXnuuecyaNCgfOUrX8k555xTuVwvAADwoQ4fQE4++eScfPLJqz1+2LBhuf3229deQQAA8AnW4deAAAAAxRFAAACAwgggAABAYQQQAACgMAIIAABQGAEEAAAojAACAAAURgABAAAKI4AAAACFEUAAAIDCCCAAAEBhBBAAAKAwAggAAFAYAQQAACiMAAIAABRGAAEAAAojgAAAAIURQAAAgMIIIAAAQGEEEAAAoDACCAAAUBgBBAAAKIwAAgAAFEYAAQAACiOAAAAAhRFAAACAwgggAABAYQQQAACgMAIIAABQGAEEAAAojAACAAAURgABAAAKI4AAAACFEUAAAIDCCCAAAEBhBBAAAKAwAggAAFAYAQQAACiMAAIAABRGAAEAAAojgAAAAIURQAAAgMIIIAAAQGEEEAAAoDACCAAAUBgBBAAAKIwAAgAAFEYAAQAACiOAAAAAhRFAAACAwgggAABAYQQQAACgMAIIAABQGAEEAAAojAACAAAURgABAAAKI4AAAACFEUAAAIDCCCAAAEBhBBAAAKAwAggAAFAYAQQAACiMAAIAABRGAAEAAAojgAAAAIURQAAAgMIIIAAAQGEEEAAAoDACCAAAUBgBBAAAKIwAAgAAFEYAAQAACiOAAAAAhRFAAACAwgggAABAYQSQFnz3u99NqVRKqVTKRRdd1Gq/hx9+OEcccUT69u2brl27ZrvttsuFF16YhQsXFlgtAACsOwSQZfztb3/L6NGjV9rv+uuvzz777JPbbrstNTU12XbbbTNt2rScd9552XfffTN//vwCqgUAgHWLALKUcrmcr33ta6mqqsqBBx7Yar+XX345I0aMyJIlS3LJJZdk5syZmTRpUqZOnZqhQ4dm4sSJGTVqVIGVAwDAukEAWcq1116bBx54IOedd1769+/far/Ro0envr4+hxxySEaOHJlSqZQkGThwYH71q18lSa6++uq8+eabhdQNAADrCgHkf7z99ts555xzst122+Wf//mfW+1XLpczduzYJMmIESOWax82bFi22WabNDQ05NZbb/3Y6gUAgHWRAPI//vmf/znvvvturrrqqlRVVbXab8aMGXn99deTJJ/5zGda7NO0/9FHH137hQIAwDpMAEly33335frrr8/xxx+f/fbbb4V9p06dmiSpqalJv379WuwzaNCgZn0BAIAPdWnrAtrawoUL8/Wvfz09e/bMpZdeutL+c+bMSZL06tWrsvZjWRtssEGzvq2pr69PfX195XldXd2qlg0AAOukDj8DctFFF2XatGn5wQ9+kI033nil/Zvu8VFdXd1qn5qamiTJggULVnisiy++OD179qxsK1r4DgAAnwQdOoA03fNj1113zTe+8Y1VGlNbW5skWbRoUat9mmY1unbtusJjnXvuuZk3b15lmzlz5ipWDgAA66YOfQrWP/7jP2bx4sX5+c9/nk6dVi2LNZ1eNXfu3JTL5RZPw2o69aqpb2tqamoqsyUAANARdOgA8sQTT6RUKmX48OHLtc2bNy9J8qMf/Sg//elP079//0ycODFDhgxJ8uEsx6xZs7LZZpstN3b69OlJUukLAAB8qEMHkCRZsmTJCm8Y+P777+f999+vnHo1YMCAbLLJJnnjjTfy0EMP5e///u+XG/PQQw8lSfbaa6+Pp2gAAFhHdeg1IE2nUbW0nXTSSUmSCy+8MOVyOS+//HKSpFQq5aijjkry4Z3TlzVhwoRMmTIlVVVVLc6sAABAR9ahA8jqGjlyZKqrq3Pvvfdm9OjRKZfLSZJXXnklp556apLktNNOyyabbNKWZQIAQLsjgKyGLbfcMmPGjEmnTp0yatSo9O/fP7vuumuGDBmS559/PrvttltGjx7d1mUCAEC7I4CsphNPPDEPPPBADj/88CxYsCDPPfdcBg0alPPPPz8PPvhgunXr1tYlAgBAu9PhF6G35rrrrst11123wj7Dhg3L7bffXkxBAADwCWAGBAAAKIwAAgAAFEYAAQAACiOAAAAAhRFAAACAwgggAABAYQQQAACgMAIIAABQGAEEAAAojAACAAAURgABAAAKI4AAAACFEUAAAIDCrDMBpLGxMW+//XZmzJjR1qUAAACrqd0HkDvvvDMHH3xw1l9//WyyySYZNGhQs/Yf/OAH+epXv5q33367jSoEAABWVbsOIKNGjcoXv/jF3HfffVmyZEmqqqpSLpeb9dl0001z4403ZuzYsW1UJQAAsKrabQD54x//mEsvvTT9+vXLHXfckQ8++CB77LHHcv2OOuqoJMltt91WdIkAAMBH1KWtC2jNz372s5RKpdx8883Ze++9W+23wQYbZMstt8zUqVMLrA4AAFgd7XYG5Iknnkj//v1XGD6a9O3bN6+99loBVQEAAGui3QaQ+vr69OrVa5X6zp8/P507d/54CwIAANZYuw0g/fv3z7Rp09LQ0LDCfvPmzcuUKVMyePDggioDAABWV7sNIH/3d3+XBQsW5Iorrlhhv+9///tZvHhxDj/88IIqAwAAVle7DSDnnHNO1l9//XznO9/JyJEjM2XKlEpbY2Njnn766Zx66qm54oorsuGGG+bMM89sw2oBAIBV0W6vgrXZZpvl1ltvzdFHH53LL788l19+eaWtqqoqSVIul9O7d++MHTs2ffr0aatSAQCAVdRuZ0CSZL/99svkyZNz1llnZeDAgSmXy5Vt0003zTe/+c089dRTGTZsWFuXCgAArIJ2OwPSZNNNN81ll12Wyy67LB988EHmzZuX7t27p0ePHm1dGgAA8BG1+wCytG7duqVbt25tXQYAALCa2vUpWAAAwCdLu58Bueeee3L33Xdn+vTpef/991Mul1vsVyqVct999xVcHQAA8FG02wBSV1eXI488MuPHj281dCytVCoVUBUAALAm2m0AOeecczJu3Lj07t07p59+enbZZZf07dtX0AAAgHVYuw0gt9xyS6qqqjJ+/Phsv/32bV0OAACwFrTbRegffPBBhg4dKnwAAMAnSLsNINtss00WLFjQ1mUAAABrUbsNIGeccUZefPHFjBs3rq1LAQAA1pJ2G0BOOeWUfOtb38rRRx+dn/zkJ3n//ffbuiQAAGANtdtF6ElyySWXZObMmTnrrLNy1llnpW/fvllvvfVa7FsqlfLiiy8WXCEAAPBRtNsA8uabb+aggw7Kc889V7kPyFtvvdVqf5fnBQCA9q/dBpBzzjknzz77bLbaaquMHDkyO++8s/uAAADAOq7dBpC77747tbW1GTduXPr169fW5QAAAGtBu12E/sEHH2SbbbYRPgAA4BOk3QaQHXbYIbNnz27rMgAAgLWo3QaQkSNHZubMmbnpppvauhQAAGAtabcB5Kijjsp//Md/5LTTTsu//Mu/5Nlnn83ChQvbuiwAAGANtNtF6J07d648vvLKK3PllVeusH+pVMrixYs/5qoAAIA10W4DSNO9Pz6u/gAAQPHabQBpbGxs6xIAAIC1rN2uAQEAAD55BBAAAKAwAggAAFCYdrEGZNCgQUmSrbbaKvfee2+zfauqVCrlxRdfXOu1AQAAa0+7CCAvv/xykqS2tna5fauqVCqtxYoAAICPQ7sIIC+99FKSpKqqarl9AADAJ0e7CCADBw5cbt8rr7ySnj17Zqeddlrp+Keffjpz585t8TgAAED70W4Xoe+///75p3/6p1Xqe+aZZ+bAAw/8mCsCAADWVLsNIMlHu7u5O6EDAED7164DyKqaPXt2unbt2tZlAAAAK9Eu1oAkSV1dXebOndtsX319fWbOnNnq7MaCBQsyfvz4TJ48eZXWigAAAG2r3QSQK664It///veb7XvssceyxRZbrNL4ESNGfAxVAQAAa1O7CSC9evXKgAEDKs9nzJiR6urqbLLJJi32L5VK6dq1awYNGpQvfelLOf7444sqFQAAWE3tJoCceeaZOfPMMyvPO3XqlD322CN//etf27AqAABgbWo3AWRZv/71r7Pxxhu3dRkAAMBa1G4DyEknndTWJQAAAGvZJ+IyvAAAwLpBAAEAAAojgAAAAIURQAAAgMIIIAAAQGEEEAAAoDACCAAAUBgBBAAAKIwAAgAAFEYAAQAACiOAAAAAhRFAlrJkyZKMGTMm++23XzbccMPU1tZm4MCBOfLII3Prrbe2OObhhx/OEUcckb59+6Zr167ZbrvtcuGFF2bhwoUFVw8AAO1fl7YuoL2YM2dODj300DzyyCMplUrZeuuts8UWW2TWrFm59dZb06VLlxxxxBHNxlx//fU56aSTsmTJkmy22Wbp379/Jk+enPPOOy+33357xo0bl/XWW6+N3hEAALQ/ZkCSNDY2Zvjw4XnkkUdy9NFHZ8aMGZkyZUoee+yxzJo1KzNnzsw//dM/NRvz8ssvZ8SIEVmyZEkuueSSzJw5M5MmTcrUqVMzdOjQTJw4MaNGjWqjdwQAAO2TAJLk6quvzoMPPpgDDjggN998czbffPNm7Ztvvnn23XffZvtGjx6d+vr6HHLIIRk5cmRKpVKSZODAgfnVr35VOe6bb75ZzJsAAIB1gACS5Mc//nGS5MILL0ynTiv/SMrlcsaOHZskGTFixHLtw4YNyzbbbJOGhoZW144AAEBH1OEDyNSpUzNlypT07t07w4YNy6233prjjz8+n/vc5/LlL38511xzTerr65uNmTFjRl5//fUkyWc+85kWj9u0/9FHH/143wAAAKxDOvwi9McffzxJss022+SEE07I9ddf36z9xhtvzGWXXZa77747AwcOTPJhaEmSmpqa9OvXr8XjDho0qFlfAADADEhlJmPixIm5/vrrc9ppp+Xll1/OwoUL89///d8ZNGhQpkyZkmOOOSaNjY1JPrxiVpL06tWrsvZjWRtssEGzvi2pr69PXV1dsw0AAD7JOnwA+eCDD5IkDQ0N2WeffTJmzJgMHDgwNTU1+dznPpdbbrklpVIpjz/+eP70pz8lSeUeH9XV1a0et6amJkmyYMGCVvtcfPHF6dmzZ2Xr37//2npbAADQLnX4AFJbW1t5fOaZZy7XvtNOO+WAAw5Iktx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", 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", 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", 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\n", " " ], @@ -293,6 +302,7 @@ "\t * log-level=DEBUG\n", "\t * language=openmp\n", "(ShotID 0) Preparing to run state for shot\n", + "(ShotID 0) Selected boundary type sponge_boundary_2\n", "(ShotID 0) Estimated bandwidth for the propagated wavelet 0.260-0.730 MHz\n", "(ShotID 0) Spatial grid spacing (0.400 mm | 5.137 PPW) is below dispersion limit (0.411 mm | 5.000 PPW)\n", "(ShotID 0) Time grid spacing (0.050 μs | 18%) is below OT2 limit (0.120 μs)\n", @@ -301,46 +311,47 @@ "Operator `acoustic_iso_state` instance configuration:\n", "\t * name=acoustic_iso_state\n", "\t * subs={h_x: 0.0004, h_y: 0.0004, dt: 5e-08}\n", - "\t * opt=advanced-fsg\n", - "\t * autotuning=off\n", - "\t * compiler=nvc\n", - "\t * language=openacc\n", - "\t * platform=nvidiaX\n", + "\t * opt=advanced\n", "\t * devicecreate=(p(t, x, y),)\n", - "Operator `acoustic_iso_state` generated in 1.57 s\n", - " * lowering.Clusters: 0.78 s (49.8 %)\n", - " * specializing.Clusters: 0.40 s (25.6 %)\n", - " * lowering.Expressions: 0.39 s (24.9 %)\n", - " * lowering.IET: 0.33 s (21.1 %)\n", - "Flops reduction after symbolic optimization: [99 --> 55]\n", - "Operator `acoustic_iso_state` fetched `/tmp/devito-jitcache-uid1000/379a5c3204c5761233329524198c272903f03482.cpp` in 0.10 s from jit-cache\n", + "Operator `acoustic_iso_state` generated in 4.25 s\n", + " * lowering.Clusters: 2.88 s (68.0 %)\n", + " * specializing.Clusters: 1.87 s (44.1 %)\n", + " * fuse: 1.11 s (26.2 %)\n", + " * lowering.IET: 0.90 s (21.3 %)\n", + "Flops reduction after symbolic optimization: [338 --> 247]\n", + "recompiling for non-existent cache dir (/tmp/devito-codepy-uid1000/e7e5adc/4f841d7864d4098a94494e7e78d99336).\n", + "gcc -march=native -O3 -g -fPIC -Wall -std=c99 -Wno-unused-result -Wno-unused-variable -Wno-unused-but-set-variable -ffast-math -shared -fopenmp /tmp/devito-jitcache-uid1000/e7e5adc4b9e1dae37ab8ee2f21a28895bdd7c812.c -lm -o /tmp/devito-jitcache-uid1000/e7e5adc4b9e1dae37ab8ee2f21a28895bdd7c812.so\n", + "Operator `acoustic_iso_state` jit-compiled `/tmp/devito-jitcache-uid1000/e7e5adc4b9e1dae37ab8ee2f21a28895bdd7c812.c` in 0.56 s with `CustomCompiler`\n", "(ShotID 0) Running state equation for shot\n", - "Operator `acoustic_iso_state` ran in 0.17 s\n", - "Global performance: [OI=2.60, 45.57 GFlops/s, 1.06 GPts/s]\n", + "AutoTuner: could not perform any runs\n", + "Operator `acoustic_iso_state` ran in 0.09 s\n", + "Global performance: [OI=0.01, 88.25 GFlops/s, 2.00 GPts/s]\n", + "Global performance : [0.09 s, 2.07 GPts/s]\n", "Local performance:\n", - " * section0<120> ran in 0.01 s [OI=0.50, 0.01 GFlops/s, 0.00 GPts/s]\n", - " * section1<1999,300,300> ran in 0.03 s [OI=2.60, 355.02 GFlops/s, 8.26 GPts/s]\n", - " * section2<<1999,1,2,2>,<1999,1,2,2>> ran in 0.02 s [OI=5.80, 0.04 GFlops/s, 0.01 GPts/s]\n", - " * section3<<1999,120>,<1999,120,2,2>> ran in 0.02 s [OI=1.32, 0.74 GFlops/s, 0.00 GPts/s]\n", - "Performance[mode=advanced-fsg] arguments: {'deviceid': -1, 'devicerm': 1}\n", + " * section0 ran in 0.04 s [OI=3.25, 104.79 GFlops/s, 2.69 GPts/s]\n", + " * section1 ran in 0.05 s [OI=0.01, 92.40 GFlops/s, 1.85 GPts/s]\n", + " * section2 ran in 0.01 s\n", + " * section3 ran in 0.01 s\n", + "Performance[mode=advanced] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6, 'pthreads': 0}\n", + "(ShotID 0) Completing state equation run for shot\n", "(ShotID 0) Completed state equation run for shot\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "54d98aa977114d62822db33d2363388c", + "model_id": "15852ed6819643eda04fd7e61d9f2bfd", "version_major": 2, "version_minor": 0 }, - "image/png": 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", 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", 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", + "image/png": 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", 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", + "image/png": 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\n", " Figure\n", "
\n", - " \n", + " \n", "
\n", " " ], @@ -495,45 +506,48 @@ "Operator `acoustic_iso_state` instance configuration:\n", "\t * name=acoustic_iso_state\n", "\t * subs={h_x: 0.0004, h_y: 0.0004, dt: 5e-08}\n", - "\t * opt=advanced-fsg\n", + "\t * opt=advanced\n", "\t * devicecreate=(p(t, x, y),)\n", - "Operator `acoustic_iso_state` generated in 2.36 s\n", - " * lowering.Clusters: 1.13 s (48.1 %)\n", - " * specializing.Clusters: 0.70 s (29.8 %)\n", - " * lowering.Expressions: 0.82 s (34.9 %)\n", - "Flops reduction after symbolic optimization: [496 --> 84]\n", - "recompiling for non-existent cache dir (/tmp/devito-codepy-uid1000/a573a74/e0f0e3572984c72ecaead739f69d53d0).\n", - "gcc -march=native -O3 -g -fPIC -Wall -std=c99 -Wno-unused-result -Wno-unused-variable -Wno-unused-but-set-variable -ffast-math -shared -fopenmp /tmp/devito-jitcache-uid1000/a573a746c66470fc4905b3d0d0374e04e3cc01f4.c -lm -o /tmp/devito-jitcache-uid1000/a573a746c66470fc4905b3d0d0374e04e3cc01f4.so\n", - "Operator `acoustic_iso_state` jit-compiled `/tmp/devito-jitcache-uid1000/a573a746c66470fc4905b3d0d0374e04e3cc01f4.c` in 0.44 s with `GNUCompiler`\n", + "Operator `acoustic_iso_state` generated in 7.60 s\n", + " * lowering.Clusters: 5.41 s (71.3 %)\n", + " * specializing.Clusters: 3.58 s (47.2 %)\n", + " * fuse: 2.11 s (27.8 %)\n", + "Flops reduction after symbolic optimization: [2218 --> 372]\n", + "recompiling for non-existent cache dir (/tmp/devito-codepy-uid1000/835fa19/0cd0ca23d703d1bf65fc6b70a5e6de1a).\n", + "gcc -march=native -O3 -g -fPIC -Wall -std=c99 -Wno-unused-result -Wno-unused-variable -Wno-unused-but-set-variable -ffast-math -shared -fopenmp /tmp/devito-jitcache-uid1000/835fa19594b2d9e4c8f52259d5478bf29bbcbf3c.c -lm -o /tmp/devito-jitcache-uid1000/835fa19594b2d9e4c8f52259d5478bf29bbcbf3c.so\n", + "Operator `acoustic_iso_state` jit-compiled `/tmp/devito-jitcache-uid1000/835fa19594b2d9e4c8f52259d5478bf29bbcbf3c.c` in 0.88 s with `CustomCompiler`\n", "(ShotID 0) Using inhomogeneous density\n", "(ShotID 0) Running state equation for shot\n", "AutoTuner: could not perform any runs\n", - "Operator `acoustic_iso_state` ran in 0.16 s\n", - "Global performance: [OI=1.78, 83.08 GFlops/s, 1.13 GPts/s]\n", + "Operator `acoustic_iso_state` ran in 0.22 s\n", + "Global performance: [OI=0.01, 60.41 GFlops/s, 0.82 GPts/s]\n", + "Global performance : [0.22 s, 0.84 GPts/s]\n", "Local performance:\n", - " * section0<120> ran in 0.01 s [OI=0.50, 0.01 GFlops/s, 0.00 GPts/s]\n", - " * section1<<1999,309,309>,<1999,300,300>> ran in 0.15 s [OI=1.79, 89.79 GFlops/s, 1.22 GPts/s]\n", - " * section2<<1999,1,2,2>,<1999,1,2,2>> ran in 0.01 s [OI=5.80, 0.11 GFlops/s, 0.01 GPts/s]\n", - " * section3<<1999,120>,<1999,120,2,2>> ran in 0.01 s [OI=1.32, 3.03 GFlops/s, 0.00 GPts/s]\n", - "Performance[mode=advanced-fsg] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6}\n", + " * multipass0 ran in 0.21 s [OI=0.01, 63.49 GFlops/s, 0.87 GPts/s]\n", + " + section0 ran in 0.08 s [34.94%] \n", + " + section1 ran in 0.14 s [64.97%] \n", + " * section2 ran in 0.01 s\n", + " * section3 ran in 0.01 s\n", + "Performance[mode=advanced] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6, 'pthreads': 0}\n", + "(ShotID 0) Completing state equation run for shot\n", "(ShotID 0) Completed state equation run for shot\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0c38945fae0447f0993d33bbc9ac04cf", + "model_id": "9a64fd395def403e9420eed6c2ed49ee", "version_major": 2, "version_minor": 0 }, - "image/png": 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", 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", + "image/png": 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", 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VqVJFP//8s6pUqaKHHnpISUlJatasWSl/O7AyGYbhuR38bjCZmZkKDg5WZPw0puEFAMBDWLKzlfqPicrIyHD71KzWZ4e0/eEuWQckIuZYmdwXbmxkQAAAAAC4DQsRAgAAeDhXzFrlybNgoXwjAwIAAADAbciAAAAAeDiLDJnJgMBDEIAAAAB4OLpgwZPQBQsAAACA25ABAQAA8HBmw5DZySsrOLs+wIoMCAAAAAC3IQMCAADg4Sz/25xdJ+AKZEAAAAAAuA0ZEAAAAA9ndsE0vM6uD7AiAwIAAADAbciAAAAAeDizUbA5u07AFQhAAAAAPByD0OFJ6IIFAAAAwG3IgAAAAHg4i0wyy+T0OgFXIAMCAAAAwG3IgAAAAHg4i1GwObtOwBXIgAAAAABwGzIgAAAAHs7sgjEgzq4PsCIDAgAAAMBtyIAAAAB4ODIg8CQEIAAAAB7OYphkMZw8Da+T6wOs6IIFAAAAwG3IgAAAAHg4umDBk5ABAQAAAOA2ZEAAAAA8nFleMjv5vbLZqbUBfyADAgAAAMBtyIAAAAB4OMMFs2AZzIIFFyEDAgAAAMBtyIAAAAB4OGbBgichAwIAAADAbciAAAAAeDiz4SWz4eRZsAynVgfYEIAAAAB4OItMsji5Y4tFRCBwDbpgAQAAAHAbMiAAAAAejkHo8CRkQAAAAAC4DRkQAAAAD+eaQeiMAYFrVPgMSEpKikwmU7G27777rkj5zZs3q1+/fqpZs6YCAgLUrFkzTZ06VdnZ2WVwNwAAAED5VuEzIP7+/urUqZPD4ydOnNCRI0fk7++vVq1aFTq2aNEiDR8+XGazWeHh4YqIiNDu3bs1adIkrVy5UuvXr1flypVdfAcAAKCiK5gFy7ljNpxdH2BV4TMgderU0YYNGxxuf/7znyVJffv2VXBwsK1cSkqKRo0aJbPZrFdffVVpaWlKTEzUwYMH1aRJE23btk3jx48vq9sCAABwu+TkZM2ZM0cPPfSQWrZsqUqVKslkMmnatGnXVW9Je5xERUUVq3fLCy+8UKjc+vXrr1nm3Xffva57ARmQqzp//rw+++wzSdIDDzxQ6NiMGTOUk5Ojnj17aty4cbb99evX1/z589WpUye99957ev7551W7dm13NhsAAFQwFnnJXA7WAZk1a5ZmzZrl1HaUpsdJu3btVK9ePbv1Xbx4UTt37pQk24vmKwUFBalFixZ2j9WtW/c67gYSAchVLV++XBcuXFDNmjV155132vYbhqEVK1ZIkkaNGlWkXMeOHRUTE6P9+/crISFBDz/8sNvaDAAAKp7yMgg9NDRUffr0Ufv27dWuXTvNnTtXy5YtK3UbruxxMnbsWJlMJh09elR33HGHrcfJm2++Wajc0qVLHdY5d+5cPfTQQ6pbt666d+9u95zWrVtr/fr1pW43rq7Cd8G6moULF0qS4uLiVKnSH7FaamqqTpw4IUkOx49Y92/ZssXFrQQAACgfJk6cqJUrV+r555/XnXfeqSpVqlxXfVf2ODGZCsalWHucSNJ7772nU6dOFbvOjz76SJI0dOhQeXt7X1f7UDoEIA6cOHFCa9askVS0+9XBgwclSX5+fgoLC7NbPjo6utC5AAAArmKRl0u2slTcHid5eXlKSEgoVp1Hjx7VDz/8IKno8x3chwDEgUWLFslisahJkyZq165doWNnz56VJIWEhNgi8StVq1at0Ln25OTkKDMzs9AGAAAA1/Q4WbRokQzDUIsWLdSyZcurXnvEiBHq3r277r77bk2YMEG7du0q2Q3AIcaAOGDtfmUvOrbOuODr6+uwvJ+fnyTp0qVLDs+ZPn16kdkXAAAASspsmGQ2nDttrrPrKylX9Di52vPd5ZKTk5WcnGz7+YsvvlB8fLwef/xxzZo1i65b14kMiB0///yzkpKSZDKZ9Ne//rXIcX9/f0lSbm6uwzpycnIkSQEBAQ7PmTBhgjIyMmxbWlradbYcAADAua7srWF9xnE1Z/U4sdq+fbv27dsnLy8vDR061O45AQEBGjlypNasWaNjx44pJydH+/bt09NPPy2TyaS33npLzz77bCnvCFYEIHZYByd16dJF9evXL3Lc+mU/d+6cDAczRFj/EKzn2uPn56egoKBCGwAAQEmZ/zcNr7M3SYqIiFBwcLBtmz59ulvuyVk9Tqys2Y9u3bopPDzc7jkdOnTQ/Pnz1a1bN4WFhcnX11cxMTF6/fXX9frrr0uSZs6cWSg7gpIjALmCxWLR4sWLJTlOzzVu3FhSQZbj+PHjds85cuRIoXMBAAA8UVpaWqEeGxMmTHDLdZ3V40SS8vPzbc93w4YNK1V7nnjiCdWrV09ms1mff/55qepAAQKQK6xbt06//vqr/P39dc8999g9JzIyUnXq1JEkbdy40e451v0dOnRwTUMBAAD+x2J4uWSTVKS3hjXr4GrO6nEiSatWrdJvv/2mwMBADRgwoFTt8fb2Vvv27SVJhw4dKlUdKEAAcgVr96u+ffsqODjY7jkmk8n25Z03b16R45s2bdL+/fvl4+Ojvn37uq6xAAAAcm0XrLLizB4n1u5XAwYMuK61SXx8fCQVZFRQegQgl7l06ZKWL18u6dqzI4wbN06+vr5atWqVZsyYYYvMjx49qgcffFCSNHr0aFumBAAAAMXnrB4nWVlZtnVCrnftjz179kiS6tWrd131VHQEIJf57LPPlJWVpZo1a+rOO++86rkNGjTQnDlz5OXlpfHjxysiIkJt2rRR48aNdeDAAbVt21YzZsxwU8sBAEBFZtEfU/E6a7OU8T05q8fJsmXLdPHiRdWtW1fdu3cvdXtWrVql3bt3S5J69OhR6npAAFKItftVXFycKlW69hIpw4YN0w8//KA+ffro0qVL2rt3r6KjozVlyhRt2LBBgYGBrm4yAACAR5s5c6aioqIUFxdX5JgzepxYu18NHTr0mut3xMXFae3atbJY/gi/rCuyW9vXs2dPxvheJ5PhaFQP3C4zM1PBwcGKjJ8mr//N/AAAAMo3S3a2Uv8xURkZGW6fUt/67PBOYjsFVHHu+tKXzufrb222lei+Nm7cqH79+tl+Pn/+vHJyclS5cuVCM1Xt3LlTERERkqQpU6bohRdeUNeuXbV+/foidX744YcaOXKkLBaLwsPDVatWLe3evVt5eXlq27atvvvuO4cvfY8dO6bIyEhZLBbt2rXrqqufSwVrjmRkZCgwMFCNGjWSn5+fkpOTdfr0aUlSu3bt9NVXXyk0NLRYvw/Yx0roAAAAcIq8vDylp6cX2X/x4kVdvHjR9rPZbC52ncOGDVOjRo00ffp0bdq0ydbjZMiQIXr22Wdt0/Xas2jRIlksFrVo0eKawYckxcfHa/369UpKSlJqaqqysrIUEhKi7t27Ky4uTsOHD7cNREfpkQEpR8iAAADgecpDBuTNHR1ckgF5ou2WMrkv3NgYAwIAAADAbeiCBQAA4OEsMskik9PrBFyBAAQAAMDDmQ0vmQ3ndmxxdn2AFd8sAAAAAG5DBgQAAMDDmeUls5PfKzu7PsCKbxYAAAAAtyEDAgAA4OEshkkWw8mD0J1cH2BFBgQAAACA25ABAQAA8HAWF4wBsfCeGi7CNwsAAACA25ABAQAA8HAWw0sWJ6/b4ez6ACsCEAAAAA9nlklmJ69c7uz6ACtCWwAAAABuQwYEAADAw9EFC56EbxYAAAAAtyEDAgAA4OHMcv6YDbNTawP+QAYEAAAAgNuQAQEAAPBwjAGBJ+GbBQAAAMBtyIAAAAB4OLPhJbOTMxbOrg+wIgABAADwcIZMsjh5ELrBQoRwEUJbAAAAAG5DBgQAAMDD0QULnoRvFgAAAAC3IQMCAADg4SyGSRbDuWM2nF0fYEUGBAAAAIDbkAEBAADwcGZ5yezk98rOrg+w4psFAAAAwG3IgAAAAHg4xoDAkxCAAAAAeDiLvGRxcscWZ9cHWPHNAgAAAOA2ZEAAAAA8nNkwyezkLlPOrg+wIgMCAAAAwG3IgAAAAHg4BqHDk5ABAQAAAOA2ZEAAAAA8nGF4yWI4972y4eT6ACu+WQAAAADchgwIAACAhzPLJLOcPAuWk+sDrMiAXMZsNmvOnDnq2rWrQkND5e/vr/r166t///5KSEiwW2bz5s3q16+fatasqYCAADVr1kxTp05Vdna2m1sPAAAqKovxx0B0521lfVe4URGA/M/Zs2f1l7/8RQ8//LB++OEHhYaGKjY2Vnl5eUpISNBHH31UpMyiRYvUuXNnff755/Lz81PTpk116NAhTZo0SV26dNHFixfL4E4AAADKRnJysubMmaOHHnpILVu2VKVKlWQymTRt2rTrqrekL3wXLFggk8l01e2bb75xeL1jx47p4YcfVkREhPz8/BQZGalHHnlEx44du677QAG6YEmyWCzq27evfvzxRw0cOFCzZs1SvXr1bMd//fVXHTlypFCZlJQUjRo1SmazWa+++qrGjh0rk8mko0eP6o477tC2bds0fvx4vfnmm+6+HQAAUMFYXDAIvTT1zZo1S7NmzXJqOxYtWqThw4fLbDYrPDxcERER2r17tyZNmqSVK1dq/fr1qly5st2ytWrVUuPGje0eq1atmt39e/fuVefOnXXmzBkFBwcrNjZWhw8f1nvvvadly5Zpw4YNiomJcdr9VURkQCS999572rBhg2677TYtXbq0UPAhSfXq1VOXLl0K7ZsxY4ZycnLUs2dPjRs3TiZTQT/J+vXra/78+bZ6T5065Z6bAAAAKGOhoaHq06ePXnzxRX399dcaNGjQddV35QvftLQ0JSYm6uDBg2rSpIntha8jvXr10oYNG+xuHTp0KHK+2WzW4MGDdebMGQ0aNEjHjx/Xjh07dOzYMQ0cOFDp6em67777ZLFYruu+KjoCEMkWqU+dOlVeXtf+lRiGoRUrVkiSRo0aVeR4x44dFRMTY+u+BQAA4EoWmVyyldTEiRO1cuVKPf/887rzzjtVpUqV67ovd7/wXb58ufbu3asaNWro/ffft2VWAgMDtWDBAtWoUUM//fQTz3fXqcIHIAcPHtT+/ftVvXp1dezYUQkJCfrrX/+q7t27Ky4uTnPnzlVOTk6hMqmpqTpx4oQkqVOnTnbrte7fsmWLa28AAADgBlQWL3yXL18uSbr33ntVtWrVQseqVq2qwYMHS5KWLl3qlOtVVBU+ANmxY4ckKSYmRg888ID69++vRYsWae3atfrkk0/00EMPqVWrVjp69KitzMGDByVJfn5+CgsLs1tvdHR0oXMBAABcxWyYXLKVJWe88E1KStLQoUPVrVs39e/fXy+88IIOHz7s8Jo//vjjdV0PxVPhAxDrF3vbtm1atGiRRo8erZSUFGVnZ2v16tWKjo7W/v37NWjQIFt/v7Nnz0qSQkJCbKnAK1kHNlnPtScnJ0eZmZmFNgAAADjnhe+uXbu0ePFirVu3TgkJCZoyZYqaNGmil156qci5ubm5Sk1NLVSvo+ulpKQoLy+vZDcEmwofgFy4cEGSlJeXp86dO2vOnDmqX7++/Pz81L17dy1fvlwmk0k7duzQl19+KUm2Kd98fX0d1uvn5ydJunTpksNzpk+fruDgYNsWERHhrNsCAAAViHUWLGdvZel6XviGhITo73//uzZu3KhTp04pOztbO3fu1AMPPCCz2ayJEycWmak0IyPD9rLZ0QxZ1v0Wi4UXx9ehwgcg/v7+tn8/9dRTRY63bNlSt912myTZ5ou2lsnNzXVYr3XcSEBAgMNzJkyYoIyMDNuWlpZW8hsAAABwoSt7a1w5NtZVrueFb//+/fXGG2+oY8eOqlWrlvz8/NSqVSt9+OGHevrppyUVDJjPysoqcr2rXdN6PXvXRPFV+ADk8gjX0ZzOTZs2lVSQbru8zLlz52QY9pcJtUbijiJoqeBLHBQUVGgDAAAoKYucvQr6H7NgRUREFOqxMX36dLfck7Ne+F7phRdekJ+fnzIyMrR27doi17vaNS8PvkpyTRRW4RcibNKkie3fl0e1l7PuN5vNkmRb0CYnJ0fHjx9XeHh4kTLWhQsdLX4DAADgLEYpp829Vp2SlJaWVuglqaPnJWe78oWvvW5YxXnhe6WgoCA1b95ciYmJOnTokG1/cHCwvLy8ZLFYHI7hte738vLixfF1qPAZkNatW9si3itXO7ey7rcGGpGRkapTp44kaePGjXbLWPfbW+QGAADAU1zZW8NdAciVL3ztKe0LXx8fH0lSfn6+bZ+vr68iIyML1evoelFRUbY6UHIVPgAJDAzUXXfdJUn64IMPihw/efKk/vvf/0qSunXrJkkymUwaMGCAJGnevHlFymzatEn79++Xj4+P+vbt66qmAwAASJLzu1/9bytLrnrhazabdeDAAUlSvXr1Ch2z1sMLZteq8AGIJE2aNEne3t5asmRJoSDk3LlzGjFihC5duqTo6Gjb4jOSNG7cOPn6+mrVqlWaMWOGbSzI0aNH9eCDD0qSRo8ebfvDAQAAQPG56oXvvHnzdO7cOXl7e+vWW28tdGzgwIGSpE8//bTQAHVJysrKsi1AeM8995TkVnAFAhAVzHT15ptvyjAMjRgxQvXr11e7du0UHh6u//73vwoNDdWyZcsKzYjQoEEDzZkzR15eXho/frwiIiLUpk0bNW7cWAcOHFDbtm01Y8aMMrwrAABQUXjyNLwzZ85UVFSU4uLiihwrzQvfzMxMDRkyRFu3bi1Ul9ls1pw5c2yzno4aNarION5BgwYpJiZG6enpGjlypC5evCipYNmGkSNHKj09XbGxserfv7/T7r8iIgD5n0cffVTfffed7r77bl28eFE//fSTatWqpccff1y7du1Sq1atipQZNmyYfvjhB/Xp00eXLl3S3r17FR0drSlTpmjDhg0KDAx0/40AAACUkY0bNyo0NNS2LVmyRFLB2meX77986YFz587p6NGjOnnyZJH6SvPC12KxaMmSJerQoYOqVaumNm3aqH379goNDdXDDz+s7Oxs9erVS7NmzSpyPW9vby1dulTVqlXTsmXLFBYWpptvvlnh4eFatmyZqlevrk8++UReXjxCX48KPwvW5Tp37qzOnTuXqEzHjh21cuVKF7UIAADg2lwxZqM09eXl5Sk9Pb3I/osXL9qyCdIfM4sWx7Bhw9SoUSNNnz5dmzZtsr3wHTJkiJ599tlC0+dKBeN7X331VW3atEm7d+/W4cOHdenSJdWoUUO9e/fWsGHDNHjwYIeLG8bGxiopKUkvvviivv76a/3888+qWbOm7r33Xk2aNKnIuBGUnMlwtJAF3C4zM1PBwcGKjJ8mryv+mAAAQPlkyc5W6j8mKiMjw+1Ts1qfHfqtelA+gY4X7CuNvAu5Sug5v0zuCzc2MiAAAAAezuKCdUCcXR9gRQACAADg4cpLFyygOBhBAwAAAMBtyIAAAAB4ODIg8CRkQAAAAAC4DRkQAAAAD0cGBJ6EDAgAAAAAtyEDAgAA4OHIgMCTkAEBAAAA4DZkQAAAADycIecvHGg4tTbgDwQgAAAAHo4uWPAkdMECAAAA4DZkQAAAADwcGRB4EjIgAAAAANyGDAgAAICHIwMCT0IGBAAAAIDbkAEBAADwcGRA4EnIgAAAAABwGzIgAAAAHs4wTDKcnLFwdn2AFQEIAACAh7PI5PSV0J1dH2BFFywAAAAAbkMGBAAAwMMxCB2ehAwIAAAAALchAwIAAODhGIQOT0IGBAAAAIDbkAEBAADwcIwBgSchAwIAAADAbciAAAAAeDjGgMCTEIAAAAB4OMMFXbAIQOAqdMECAAAA4DZkQAAAADycIckwnF8n4ApkQAAAAAC4DRkQAAAAD2eRSSY5eRpeJ9cHWJEBAQAAAOA2ZEAAAAA8HNPwwpOQAQEAAADgNmRAAAAAPJzFMMnk5IyFs9cVAawIQAAAADycYbhgGl7m4YWL0AULAAAAgNsQgEgaMWKETCbTVbfs7Gy7ZTdv3qx+/fqpZs2aCggIULNmzTR16lSH5wMAADibdRC6szfAFQhALtO4cWN16tTJ7ublVfRXtWjRInXu3Fmff/65/Pz81LRpUx06dEiTJk1Sly5ddPHixTK4CwAAgLKRnJysOXPm6KGHHlLLli1VqVIlmUwmTZs27brqLekL319++UXTp09Xz549VadOHfn4+Kh69eq67bbb9P7778tisdgtt379+mu+lH733Xev617AGJBC/vnPf2rEiBHFOjclJUWjRo2S2WzWq6++qrFjx8pkMuno0aO64447tG3bNo0fP15vvvmmaxsNAAAqvPIyDe+sWbM0a9Ysp7Zj0aJFGj58uMxms8LDwxUREaHdu3dr0qRJWrlypdavX6/KlSvbzjebzWrSpInt53r16qlVq1ZKTU3V+vXrtX79ei1ZskQJCQny9/e3e82goCC1aNHC7rG6des69f4qIjIgpTRjxgzl5OSoZ8+eGjdunEymgj/S+vXra/78+ZKk9957T6dOnSrLZgIAALhNaGio+vTpoxdffFFff/21Bg0adF31XfnCNy0tTYmJiTp48KCaNGlie+F7OcMwFBISookTJ+rw4cNKS0vTtm3bdOrUKX3yyScKCAjQqlWrNHHiRIfXbd26tTZs2GB369ev33XdEwhASsUwDK1YsUKSNGrUqCLHO3bsqJiYGOXl5SkhIcHdzQMAABWMxTC5ZCupiRMnauXKlXr++ed15513qkqVKtd1X6V54evt7a0jR45o6tSpio6OLlTfvffeq8mTJ0uS5s+f77ArFlyLAOQy//nPf9S/f39169ZNcXFxmj17tjIyMoqcl5qaqhMnTkiSOnXqZLcu6/4tW7a4rsEAAAA3qNK+8DWZTKpWrZrDenv27ClJOnv2rE6fPu3kVqM4GANymS+//LLQz5988okmT56sjz/+WHfeeadt/8GDByVJfn5+CgsLs1uXNeK2ngsAAOAqN+I6IMV94bt//35t2bJFDz/8cLHqvXzgekBAgMNrjxgxQmlpaapcubJiY2N13333qVWrViW7CdhFBkRSw4YN9fLLLyspKUmZmZnKysrSqlWr1KFDB509e1b9+/fX9u3bbeefPXtWkhQSEmJLBV7JGnlbz7UnJydHmZmZhTYAAICSKghAnD0Nb9nek6te+H766aeSpNjYWAUFBdk9Jzk5WR988IHWrl2rL774QvHx8WrdurWeeOIJmc3mktwG7CAAkfT8889rwoQJ+tOf/qSqVauqSpUquv322/X999+rffv2ysnJ0bPPPms73xo5+/r6OqzTz89PknTp0iWH50yfPl3BwcG2LSIiwkl3BAAA4BxXvizNyclxy3Wd9cL3crt379bbb78tSUUGr0sFGZGRI0dqzZo1OnbsmHJycrRv3z49/fTTMplMeuuttwo9E6J0CECuwtfXV1OnTpVUMC+09cttnbItNzfXYVnrH6ej1J4kTZgwQRkZGbYtLS3NWU0HAAAViCsXIoyIiCj0wnT69OluuSdnvfC1OnfunAYNGqTc3FzdddddeuCBB4qc06FDB82fP1/dunVTWFiYfH19FRMTo9dff12vv/66JGnmzJlKTk4uzS3hfwhAruHPf/6zJMlisejIkSOS/oi2z507J8NBftIarFxtEJSfn5+CgoIKbQAAAOVJWlpaoRemEyZMcMt1nfXC13pe//799csvv6h58+ZauHBhidvzxBNPqF69ejKbzfr8889LXB5/IAC5Bh8fH9u/8/PzJRWsmC4VfJmPHz9ut5w1WLGeCwAA4CqGizZJRV6WWrMOruasF775+fm677779N133ykqKkqrVq266vmOeHt7q3379pKkQ4cOlbg8/kAAcg179uyx/btevXqSpMjISNWpU0eStHHjRrvlrPs7dOjg4hYCAADceJzxwtcwDI0cOVIJCQmqW7euVq9e7XBAe3FYX0xbX0qjdAhAruHf//63JCkmJkbh4eGSCuaXHjBggCRp3rx5Rcps2rRJ+/fvl4+Pj/r27eu+xgIAgArJlWNAyoozXvg+8cQTWrhwoWrUqKFvv/1WDRs2vK42WV9MW19Ko3QqfADy7bffasKECUUGE2VkZOjJJ5/U4sWLJUmTJk0qdHzcuHHy9fXVqlWrNGPGDFtq8OjRo3rwwQclSaNHj7b94QAAAKD4rveF73PPPae3335bVatW1TfffKPmzZtfV3tWrVql3bt3S5J69OhxXXVVdBU+ALlw4YLi4+MVHR2tevXqqX379mrdurVq1aql2bNny2QyafLkyRoyZEihcg0aNNCcOXPk5eWl8ePHKyIiQm3atFHjxo114MABtW3bVjNmzCijuwIAABWKKweBuNjMmTMVFRWluLi4IsdK+8L3tdde08svv6yAgAB98cUXuvnmm4vVlri4OK1du1YWi8W2z7oiu7V9PXv2pIv9dTIZjkb1VBBpaWn6v//7P23evFmHDh3S6dOnZRiG6tatq86dO+uxxx676pds06ZNmj59ujZt2qQLFy4oKipKQ4YM0bPPPmubvaG4MjMzFRwcrMj4afIqYVkAAFA2LNnZSv3HRGVkZLh9Rkvrs0P0gufkVdm5zw6Wi9k6MuKlEt3Xxo0b1a9fP9vP58+fV05OjipXrlxopqqdO3fa1j+bMmWKXnjhBXXt2lXr168vUueHH36okSNHymKxKDw8XLVq1dLu3buVl5entm3b6rvvvlNgYKDt/OPHj6tevXoyDEO1atW66oRA//nPfwoFLyEhIcrIyFBgYKAaNWokPz8/JScn6/Tp05Kkdu3a6auvvlJoaGixfh+wr1JZN6CsRUREaNq0aaUu37FjR61cudKJLQIAAPBMeXl5Sk9PL7L/4sWLunjxou3nkqwmPmzYMDVq1Mj2wnfv3r2Kjo52+MI3NzfXlin57bff9Ntvvzms27rWiFV8fLzWr1+vpKQkpaamKisrSyEhIerevbvi4uI0fPjwQjOkonQqfAakPCEDAgCA5ykPGZAG77smA5I8smQZEKA4KvwYEAAAAADuU+G7YAEAAHg6V0ybW9bT8OLGRQYEAAAAgNuQAQEAAPB0hqlgc3adgAuQAQEAAADgNmRAAAAAPJxhFGzOrhNwBQIQAAAAT+eKlcsJQOAidMECAAAA4DZkQAAAADwc0/DCk5ABAQAAAOA25TID8uuvv+r777/Xhg0bdPToUZ0+fVqXLl1SaGioatasqTZt2qhz585q3769fHx8yrq5AAAAZY8xG/AQ5SYAuXTpkpYsWaK5c+fqxx9/lCQZDqZfWLZsmSQpJCRE999/v0aNGqWWLVu6ra0AAAAASqfMA5D8/Hy98847mjZtmn7//XcZhqHw8HC1b99e7dq1U926dVW9enUFBATozJkzOnPmjPbu3autW7cqKSlJb775pt566y317t1b8fHxatasWVnfEgAAgFsxBgSepMwDkJiYGCUnJ6tevXoaP3684uLiip3NuHDhgj777DMtXrxYX3/9tb7++mvNnTtXw4cPd3GrAQAAAJRGmQcg3t7emjdvnh544AF5e3uXqGxgYKDuv/9+3X///Tp06JBeeuklHT9+3EUtBQAAKKdYBwQepMwDkH379snL6/on42rUqJHef/99WSwWJ7QKAAAAgCuUeQDijODDlfUBAACUf6b/bc6uE3C+Mg9AAAAAcJ3oggUPUu4DkHPnzik5OVnnz593OC2vJHXp0sWNrQIAAABQGuU2AFm7dq2ee+45bd269Zrnmkwm5efnu6FVAAAA5RAZEHiQchmAfPXVV+rfv7/y8/Pl7++vBg0aqGbNmjKZ6IsIAAAAeLJyGYBMmjRJZrNZjzzyiOLj4xUcHFzWTQIAACi/DFPB5uw6ARcolwHI3r17FRoaqnfeeaesmwIAAADAicplAFKtWjWFh4eXdTMAAAA8gmEUbM6uE3CFcrloRs+ePbVv3z5duHChrJsCAAAAwInKZQDywgsvKDAwUI888oiys7PLujkAAADlm+GiDXCBctkFKzIyUt9//72GDRumRo0aaciQIWrYsKEqV67ssMywYcPc2EIAAIByhEHo8CDlMgCRpK1btyotLU0nTpzQa6+9ds3zCUAAAACA8q9cBiCffPKJLaCoV6+eWrRowTogAAAADpiMgs3ZdQKuUC4DkOnTp8tkMmn69OkaO3asvLzK5VAVAAAAACVULgOQX375ReHh4Ro/fnxZNwUAAKD8c8WgcTIgcJFymVqoUaOGateuXdbNAAAAAOBk5TIAufvuu7V7926lp6eXdVMAAADKP+ssWM7eABcolwHItGnTFBERobi4OJ06daqsmwMAAADAScrlGJA333xTd911l9555x01bNhQvXr1uuo6ICaTSc8//7ybWwkAAFBOMAYEHqRcBiBTpkyRyWSSYRjKy8vTsmXL7J5nPYcABAAAVGgEIPAg5TIAmTx5clk3AQAAAIALEIAAAAB4OjIg8CDlchA6AAAAgBsTAYgdEydOlMlkkslk0rRp0xyet3nzZvXr1081a9ZUQECAmjVrpqlTpyo7O9uNrQUAABUe0/DCg5TLLlhW+/fv13//+18dOXJE58+fl2HYzwWaTCbNmzfPKdfct2+fZsyYcc3zFi1apOHDh8tsNis8PFwRERHavXu3Jk2apJUrV2r9+vUOZ+0CAAC4ESUnJ2v16tXaunWrtm7dqj179shsNmvq1KmaOHFiqevdvHmz4uPjtWnTJp0/f14NGjTQkCFDNG7cOPn7+zsst2/fPk2bNk1r167V2bNnFR4ergEDBmjixIkKCQlxWO7YsWN64YUX9PXXX+u3335T7dq11atXL02aNEnh4eGlvg8UKJcBSF5enh5++GF9+OGHkuQw8LByVgBiGIYeeeQR+fj46C9/+YvWrl1r97yUlBSNGjVKZrNZr776qsaOHSuTyaSjR4/qjjvu0LZt2zR+/Hi9+eab190mAACAazEZBZuz6yypWbNmadasWU5tR2lf+q5bt069e/fWpUuXVLNmTTVv3lz79+/Xv//9b61YsUKbNm1S7dq1i5Tbu3evOnfurDNnzig4OFixsbE6fPiw3nvvPS1btkwbNmxQTEyMU++xoimXAcikSZP0wQcfyNfXVwMHDlTr1q1Vs2ZNmUyuTQXOmzdPP/zwg1555RXt3bvX4XkzZsxQTk6OevbsqXHjxtn2169fX/Pnz1enTp303nvv6fnnn7f7xQYAALgRhYaGqk+fPmrfvr3atWunuXPnOlxOoThK+9I3KytL9913ny5duqQnn3xS//rXv+Tj46P09HT169dPGzdu1KhRo/TFF18UKmc2mzV48GCdOXNGgwYN0ocffqjKlSvrwoULGjZsmJYvX6777rtPO3fulJcXIxlKq1wGIAsXLpSXl5dWrVqlLl26uOWap0+f1rPPPqtmzZppzJgxeuihh+yeZxiGVqxYIUkaNWpUkeMdO3ZUTEyM9u/fr4SEBD388MMubTcAAEB5mQXrym5WS5Ysua4mlPal77vvvqvTp0+radOmeu211+Tt7S1JqlGjhj7++GM1bNhQX375pRITE9WmTRtbueXLl2vv3r2qUaOG3n//fVtmJTAwUAsWLNB3332nn376SQkJCRowYMB13VtFVi5Dt/T0dN10001uCz4kacyYMTpz5ozefvtt+fj4ODwvNTVVJ06ckCR16tTJ7jnW/Vu2bHF+QwEAACqA4r70zcvLU0JCQqFjy5cvlySNGDHCFnxYRUZGqkePHpKk//znP3bL3XvvvapatWqhY1WrVtXgwYMlSUuXLi3tbUHlNACJjo52a1przZo1WrRokf7617+qa9euVz334MGDkiQ/Pz+FhYXZPSc6OrrQuQAAACiZ0r70zc/P144dO0pcTpJ+/PHHUpVDyZTLAGTkyJHat2+ffv75Z5dfKzs7W48++qiCg4P1r3/965rnnz17VpIUEhLicExKtWrVCp3rSE5OjjIzMwttAAAAJWXSHwPRnbaV8T2V9qVvSkqK8vLyCh0vTrnc3FylpqYWq9zl10DJlcsAZMyYMerbt6/69OmjlStXuvRa06ZN06FDh/TSSy8Va8C4dY0PX19fh+f4+flJki5dunTVuqZPn67g4GDbFhERUYKWAwAAuN6VL0tzcnLcct3SvvS9/N/W48Upl5GRIYvFUqxyFouFF8fXoVwOQvfy8tLy5cs1aNAg9e/fX9WrV1fDhg0drqthMpm0Zs2aEl/HuuZHmzZt9Le//a1YZaxzTefm5jo8x/qHGRAQcNW6JkyYoGeeecb2c2ZmJkEIAAAoOVcsHPi/+q58Npk8ebKmTJni3GvZUdqXvpcvCO2o7PWWu7IsSqZcBiDnz5/XgAEDtHbtWhmGofT0dKWnpzs8v7TT8z722GPKz8/XO++8U+wxJ9bI99y5czIMw+61rdG0o+jZys/Pr9AXGQAAoLxJS0tTUFCQ7Wd3PbuU9qXv5QsT5ubm2l2osDjlrna9K8uiZMplAPLcc89pzZo1qlGjhh5++GG1atXKJeuA7Ny5UyaTSX379i1yLCMjQ5L0yiuv6M0331RERIS2bdumxo0bSyr4Ah4/ftzuaphHjhyRJNu5AAAALuXCaXiDgoIKBSDuUtqXvpf/++zZs6pbt26xygUHB8vLy0sWi8XhOF7rfi8vrzL5ndwoymUAsmzZMvn4+Oi7775Ts2bNXHots9msU6dOOTx+/vx5nT9/3hYVR0ZGqk6dOjp58qQ2btyoe++9t0iZjRs3SpI6dOjgmkYDAADc4Er70jcqKko+Pj7Ky8vTkSNH7AYg9sr5+voqMjJSKSkpOnLkiP785z87LGe9BkqnXA5CP3v2rGJiYlwefFgjanvb8OHDJUlTp06VYRhKSUmRVNDdy7rwzLx584rUuWnTJu3fv18+Pj52MysAAABOZ7hoK0PWl77SHy93r2TvpW+lSpVsiwuWpNzlP5e0HEqmXAYgTZo0KdcDe8aNGydfX1+tWrVKM2bMkGEU/IUePXpUDz74oCRp9OjRtj8aAAAAV3L6FLz/28r0nq7jpe/AgQMlSQsWLJDZbC50LDU1VatXr5YkDRo0yG65Tz/9VFlZWYWOZWVl2RYgvOeee0p7W1A5DUAee+wxHTp0SOvXry/rptjVoEEDzZkzR15eXho/frwiIiLUpk0bNW7cWAcOHFDbtm01Y8aMsm4mAABAuTdz5kxFRUUpLi6uyLHSvvR99NFHFRoaqn379umZZ56xrdmRnp6uoUOHKj8/X7169VLbtm0LlRs0aJBiYmKUnp6ukSNH6uLFi5KkCxcuaOTIkUpPT1dsbKz69+/v7F9DhVIuA5DRo0frmWee0cCBAzV79mydP3++rJtUxLBhw/TDDz+oT58+unTpkvbu3avo6GhNmTJFGzZsUGBgYFk3EQAAVBTlpAvWxo0bFRoaatuWLFkiqWDts8v3p6Wl2cqcO3dOR48e1cmTJ4vUV9qXvkFBQVqyZIn8/f31xhtvKDw8XDfffLMiIyO1ceNGRUVFaf78+UXKeXt7a+nSpapWrZqWLVumsLAw3XzzzQoPD9eyZctUvXp1ffLJJ8WePRX2lctB6NZVJs+fP6+nn35aTz/9tGrWrHnVdUAOHz7s1DYsWLBACxYsuOo5HTt2dPlCiQAAAJ4iLy/P7tIJFy9etGUTJBXpFnU1w4YNU6NGjTR9+nRt2rTJ9tJ3yJAhevbZZ+1OsytJ3bt31/bt2zVt2jStXbtWP//8s8LDwzVgwABNnDjR4XIJsbGxSkpK0osvvqivv/5aP//8s2rWrKl7771XkyZNUr169YrddthnMqy5rHKkpFGlyWQq0Re5vMrMzFRwcLAi46fJy8EfEwAAKF8s2dlK/cdEZWRkuH1qVuuzQ9TUl5z+7GDJzlbK88+VyX3hxlYuMyDJycll3QQAAAAALlAuA5D69euXdRMAAAA8hitmrSrrWbBw42IEDQAAAAC3KZcZEAAAAJSAYSrYnF0n4AJlngGJjY3VJ598ousdC5+amqpHH31Ur7zyipNaBgAA4CHKyTS8QHGUeQCSlZWloUOH6qabbtLUqVN18ODBYpfNzc3VihUrdM8996hx48aaO3euatWq5cLWAgAAALgeZd4F65dfftEbb7yh+Ph4TZ48WVOmTFHDhg3Vvn17tW3bVnXr1lX16tXl5+enc+fO6cyZM9q3b5+2b9+u7du368KFCzIMQ7fffrteeeUVtWrVqqxvCQAAwK0YhA5PUuYBiJ+fn8aNG6dHH31UCxcu1Jw5c7Rr1y4dOnRIixcvtlvG2l0rMDBQDz74oB5++GG1a9fOnc0GAAAAUAplHoBYVa1aVX/729/0t7/9TQcPHtT333+vTZs26ejRo/r999+VnZ2t6tWrq1atWmrVqpX+8pe/qGPHjg5XRwcAAKgwXDFmgwwIXKTcBCCXa9y4sRo3bqxRo0aVdVMAAAAAOFG5DEAAAABQAi4YA0IGBK5S5rNgAQAAAKg4yIAAAAB4OsaAwIMQgAAAAHg6AhB4ELpgAQAAAHAbMiAAAAAejoUI4UnIgAAAAABwGwIQAAAAAG5TLgOQr7/+WoZB3g8AAAC40ZTLAKR3796KiIjQP/7xD+3bt6+smwMAAFC+GS7aABcolwFI8+bNdfz4cc2YMUOxsbG65ZZb9O677+rcuXNl3TQAAAAA16FcBiA///yztm/frscff1w1atTQ1q1b9fjjj6tu3bqKi4vTN998QxctAACA/7HOguXsDXCFchmASFKbNm30xhtv6Pjx41q+fLn69u0ri8WiTz/9VL1791a9evXoogUAAGBF9yt4iHIbgFhVqlRJ/fv314oVK3T8+HHNmjVLrVq10okTJ2xdtDp06EAXLQAAAMADlPsA5HI1atTQ3//+d23dulXx8fHy9vaWYRjatm2bHn/8cYWFhWnUqFFKTk4u66YCAAC4D4PQ4UE8KgDZs2ePxo8fr8jISE2YMEH5+fkKDQ3Vk08+qXvvvVeS9P7776tFixb64Ycfyri1AAAAAK5UqawbcC3p6en6+OOP9cEHH2jnzp0yDEPe3t6688479eCDD6pv377y8fGRJJ05c0aTJ0/WW2+9pfHjx2vz5s1l3HoAAADXc8WgcQahw1XKZQCSn5+vL774Qh988IG+/vpr5eXlyTAMNW7cWCNGjNCIESNUt27dIuWqV6+u2bNna9WqVUpKSiqDlgMAAAC4mnIZgISFhSk9PV2GYSgwMFBDhgzRgw8+qM6dOxerfN26dXXo0CEXtxIAAKCccMWYDTIgcJFyGYD8/vvv+vOf/6wHH3xQ9913n6pUqVKi8rNmzWJGLAAAAKAcKpcByP79+3XTTTeVunzLli2d2BoAAIDyjTEg8CTlchas6wk+AAAAAJRf5TIDAgAAgBJgDAg8CAEIAACApyMAgQcpl12wAAAAANyYyIAAAAB4OAahw5OQAQEAAADgNmRAAAAAPB1jQOBByIAAAAAAcBsCEEmfffaZHnnkEbVt21Z169aVr6+vQkJC1LFjR82aNUu5ubkOy27evFn9+vVTzZo1FRAQoGbNmmnq1KnKzs524x0AAIAKzXDRBrgAAYikf/3rX3rvvfe0Z88eBQQEqGXLlqpSpYo2b96sp59+Wh07dtS5c+eKlFu0aJE6d+6szz//XH5+fmratKkOHTqkSZMmqUuXLrp48aL7bwYAAKCMffXVV+rRo4eqV6+uwMBAtWnTRrNnz5bFYilxXRkZGZo0aZJiY2NVuXJlhYSEqEuXLlq8eLHDMlFRUTKZTNfcXnjhhULl1q9ff80y7777bonvAYUxBkTS6NGjNW3aNHXq1Ek+Pj62/T/++KMGDx6sHTt26LnnntNbb71lO5aSkqJRo0bJbDbr1Vdf1dixY2UymXT06FHdcccd2rZtm8aPH68333yzLG4JAABUIOVpFqz4+HhNmDBBkhQdHa0qVaooKSlJTz75pFavXq0VK1bIy6t478CPHTum2267TQcPHpS3t7diY2OVl5enDRs26IcfftD333+vd955p0i5du3aqV69enbrvHjxonbu3ClJ+vOf/2z3nKCgILVo0cLusbp16xar7XDMZBgGCbarWLp0qe69916FhYXp2LFjtv2PP/643n77bfXs2VP//e9/C5XZtGmTLZhJS0tT7dq1i3WtzMxMBQcHKzJ+mrz8/Z16HwAAwDUs2dlK/cdEZWRkKCgoyK3Xtj47xPz9ZXn7OffZwZyTrf2z/1mi+9q8ebM6deokk8mkhQsXasiQIZKkpKQk3XHHHTp16pRmzJihsWPHFqu+bt26ad26dWrevLm++OILRUVF2eq76667dPz4cX344Yd64IEHin1fc+fO1UMPPaS6desqLS1N3t7etmPr16/Xbbfdpq5du2r9+vXFrhMlQxesa4iJiZGkQt2pDMPQihUrJEmjRo0qUqZjx46KiYlRXl6eEhIS3NNQAACAMjZt2jQZhqHRo0fbgg9JatmypV577TVJBRmSvLy8a9aVlJSkdevWSSoIGqzBx5X1TZkypURt/OijjyRJQ4cOLRR8wH0IQK5h8+bNkqQ2bdrY9qWmpurEiROSpE6dOtktZ92/ZcsWF7cQAABUdNYuWM7eSiIzM1OrV6+WZP8F7eDBgxUUFKT09HRbYHE1GzdulCTVq1dPt9xyS5HjAwYMkJeXl44cOaIdO3YUq41Hjx7VDz/8IEklyprAuQhA7DCbzfr111/19ttva+zYsQoMDNT06dNtxw8ePChJ8vPzU1hYmN06oqOjC50LAABwI9u5c6dyc3Pl7+9f6MWtlY+Pj9q1ayepeC9oz549K0kKDw+3e9zX11ehoaGSCsbtFseiRYtkGIZatGihli1bOjwvNTVVI0aMUPfu3XX33XdrwoQJ2rVrV7GugWsjALnMzJkzZTKZVKlSJUVEROjxxx9X9+7d9eOPP6p9+/a286x/ECEhITKZTHbrqlatWqFz7cnJyVFmZmahDQAAoMTKwTS81peukZGRqlTJ/jxHJXlBGxwcLEmFxuBeLjc3V7///rsk6cCBA8Vq48KFCyVdO/uRnJysDz74QGvXrtUXX3yh+Ph4tW7dWk888YTMZnOxrgXHCEAuEx4erk6dOql9+/a2gePr1q3T4sWLC33ZrGt8+Pr6OqzLz89PknTp0iWH50yfPl3BwcG2LSIiwhm3AQAA4DRXvizNycmxe571pav1Jaw9xXlBa2XNlvz666/aunVrkeOfffaZbVrf4tS3fft27du3T15eXho6dKjdcwICAjRy5EitWbNGx44dU05Ojvbt26enn35aJpNJb731lp599tlrXgtXRwBymcGDB2vDhg3asmWLTp48qR9//FFRUVF6+eWX9cQTT9jO8//fDFVXW6DQ+scZEBDg8JwJEyYoIyPDtqWlpTnpTgAAQIXiwgxIREREoReml3dLv5yzXtBadejQQW3btpUkjRgxQr/88ovt2JYtWzRmzBjbz8Wpz5r96Natm8NuXR06dND8+fPVrVs3hYWFydfXVzExMXr99df1+uuvSyroMZOcnHzN68ExApCr6NChg7766iv5+fnpvffe09GjRyX9Eb2fO3dOjmYxLs5bAD8/PwUFBRXaAAAAypO0tLRCL0yta3xcyVkvaC+3aNEi1alTR/v27VPTpk3VpEkTNWjQQLfccosuXryou+++W5JUpUqVq9aTn59vW7hw2LBhxbr2lZ544gnVq1dPZrNZn3/+eanqQAECkGsICwtTq1atZLFYlJSUJElq3LixpII/ouPHj9std+TIkULnAgAAuIrJRZukIi9LrVmMKxWne1VxXtBerkmTJtq5c6eeeuopRUVFKSUlRRcuXND999+vxMRE28vbOnXqXLWeVatW6bffflNgYKAGDBhQrGtfydvb2zYm+NChQ6WqAwUIQIohPz+/0P+PjIy0fdGtU8Rdybq/Q4cObmghAACo0MrBIHTrS9fU1FTbM9OVSvOCtk6dOpo5c6YOHz6snJwc/fbbb1q4cKEaNGig7du3S5Ktq5Yj1u5XAwYMuGa25Gp8fHwkyeH9oXgIQK4hJSXFlvmwTtdmMpls0fO8efOKlNm0aZP2798vHx8f9e3b132NBQAAKCOtW7eWj4+PsrOzlZiYWOR4Xl6etm3bJsk5L2j37NmjAwcOyN/fXz169HB4XlZWlm1h6Otd+2PPnj2SCtYmQelV+ABkx44dmjx5si0iv9w333yjXr16KT8/X3fddZcaNmxoOzZu3Dj5+vpq1apVmjFjhm0syNGjR/Xggw9KkkaPHn3NlCAAAMD1Kg8LEQYFBdkCAXsvaJcuXarMzEzVqFFDt95663Xdr2EYtrEo999//1W7dC1btkwXL15U3bp11b1791Jfc9WqVdq9e7ckXTXgwbVV+AAkKytLL774oho2bKi6deuqXbt2atmypapVq6ZevXpp//79ateunT744INC5Ro0aKA5c+bIy8tL48ePV0REhNq0aaPGjRvrwIEDatu2rWbMmFFGdwUAAOB+zz33nEwmk+bOnWsb9C1JSUlJeuaZZyRJ48ePLzRT1syZMxUVFaW4uLgi9W3YsEFr1qwpNOlPenq6Ro4cqZUrV6p27dqKj4+/apus3a+GDh0qb2/vq54bFxentWvX2qb3lQqCnRUrVtja17NnT7rYX6cKH4C0bNlSs2bNUt++fRUYGKj9+/dr//79CggIUK9evfT+++9r06ZNtpU2Lzds2DD98MMP6tOnjy5duqS9e/cqOjpaU6ZM0YYNGxQYGFgGdwQAACqccjAGRJI6deqkqVOnymKxaOjQoWrYsKFatmypNm3a6NSpU+rdu7f+3//7f4XKnDt3TkePHtXJkyeL1Ld9+3b16NFDwcHBatmypf70pz+pTp06+uCDDxQeHq7Vq1fbfUazOnbsmNatWyepeN2vvvnmG3Xv3l1BQUFq1aqVOnTooNq1a2vgwIE6e/as2rVrp0WLFpXwt4Ir2V+msgKpVq2annzyST355JOlKt+xY0etXLnSya0CAADwTM8995xatmyp119/XTt27NDJkyfVokULjRw5Uk888cQ1sxCXu/XWWzVs2DBt3rxZhw8flslkUrNmzTRw4ECNGTPmmksYLFq0SBaLRS1atLCN5b2a+Ph4rV+/XklJSUpNTVVWVpZCQkLUvXt3xcXFafjw4baB6Cg9k+FoIQu4XWZmpoKDgxUZP01e/5tLGwAAlG+W7Gyl/mOiMjIy3L6ml/XZofkjL8vb17nPDubcbO35v3+WyX3hxlbhu2ABAAAAcJ8K3wULAADA05Vm1qri1Am4AgEIAACApyvloPFr1gm4AF2wAAAAALgNGRAAAAAPRxcseBIyIAAAAADchgwIAACAp2MMCDwIGRAAAAAAbkMGBAAAwMMxBgSehAwIAAAAALchAwIAAODpGAMCD0IAAgAA4OkIQOBB6IIFAAAAwG3IgAAAAHg4BqHDk5ABAQAAAOA2ZEAAAAA8HWNA4EHIgAAAAABwGzIgAAAAHs5kGDIZzk1ZOLs+wIoMCAAAAAC3IQMCAADg6RgDAg9CAAIAAODhmIYXnoQuWAAAAADchgwIAACAp6MLFjwIGRAAAAAAbkMGBAAAwMMxBgSehAwIAAAAALchAwIAAODpGAMCD0IGBAAAAIDbkAEBAADwcIwBgSchAAEAAPB0dMGCB6ELFgAAAAC3IQMCAABwA6DLFDwFGRAAAAAAbkMGBAAAwNMZRsHm7DoBFyADAgAAAMBtyIAAAAB4OKbhhSchAwIAAADAbciAAAAAeDrWAYEHIQABAADwcCZLwebsOgFXqPBdsAzD0IYNGzRu3DjdcsstCgkJka+vr8LCwjRo0CCtW7fuquU3b96sfv36qWbNmgoICFCzZs00depUZWdnu+kOAAAAAM9R4QOQtWvXqnPnzvrXv/6lbdu2qXbt2oqNjVVWVpaWL1+ubt266fnnn7dbdtGiRercubM+//xz+fn5qWnTpjp06JAmTZqkLl266OLFi26+GwAAUCEZLtpK6auvvlKPHj1UvXp1BQYGqk2bNpo9e7YslpKnVTIyMjRp0iTFxsaqcuXKCgkJUZcuXbR48WKHZRYsWCCTyXTV7ZtvvnFY/tixY3r44YcVEREhPz8/RUZG6pFHHtGxY8dK3H4UVeEDEMMw1KhRI7399tv6/fffdeDAASUmJio9PV0TJkyQJE2bNk1ffPFFoXIpKSkaNWqUzGazXn31VaWlpSkxMVEHDx5UkyZNtG3bNo0fP74sbgkAAKDMxMfHq3fv3lqzZo2qVaumRo0aKSkpSU8++aQGDBhQoiDk2LFjateunaZOnar9+/frpptuUnh4uDZs2KChQ4fqb3/721XL16pVS506dbK7VatWzW6ZvXv36k9/+pPmzJmjrKwsxcbGKjMzU++9955atmyp/fv3l+j3gaIqfADSvn177du3T3/7298KfRF9fX318ssvq1evXpKkOXPmFCo3Y8YM5eTkqGfPnho3bpxMJpMkqX79+po/f74k6b333tOpU6fcdCcAAKCisk7D6+ytpDZv3qx//vOf8vLy0scff6zDhw8rKSlJiYmJql27tj7//HO99tprxa7vgQce0MGDB9W8eXMdOnRIu3bt0p49e7Rz506FhYXp3Xff1UcffeSwfK9evbRhwwa7W4cOHYqcbzabNXjwYJ05c0aDBg3S8ePHtWPHDh07dkwDBw5Uenq67rvvvlJlcvCHCh+ABAUFqVIlx2Pxb7/9dknSL7/8YttnGIZWrFghSRo1alSRMh07dlRMTIzy8vKUkJDg5BYDAACUT9OmTZNhGBo9erSGDBli29+yZUtb4BEfH6+8vLxr1pWUlGQbizt37lxFRUXZrW/KlClOa//y5cu1d+9e1ahRQ++//74qV64sSQoMDNSCBQtUo0YN/fTTTzzfXacKH4Bci3UweUBAgG1famqqTpw4IUnq1KmT3XLW/Vu2bHFxCwEAQIVnGK7ZSiAzM1OrV6+WZP8F7eDBgxUUFKT09PRrTvIjSRs3bpQk1atXT7fcckuR4wMGDJCXl5eOHDmiHTt2lKitjixfvlySdO+996pq1aqFjlWtWlWDBw+WJC1dutQp16uoCECuwjAM2xfs8kDj4MGDkiQ/Pz+FhYXZLRsdHV3oXAAAgBvZzp07lZubK39/f7Vp06bIcR8fH7Vr105S8V7Qnj17VpIUHh5u97ivr69CQ0MlST/++KPdc5KSkjR06FB169ZN/fv31wsvvKDDhw87vKa1Hl4wuxYByFXMmTNHO3fulK+vr55++mnbfusfREhIiG3sx5Ws40ms59qTk5OjzMzMQhsAAEBJlYcxINaXrpGRkQ67t5fkBW1wcLAkOZx5Kjc3V7///rsk6cCBA3bP2bVrlxYvXqx169YpISFBU6ZMUZMmTfTSSy/ZrS81NbVQOx21PyUlpVjdyGAfAYgDiYmJeuqppyQV9Gds2LCh7Zi1W5avr6/D8n5+fpKkS5cuOTxn+vTpCg4Otm0RERHOaDoAAIDTXPmyNCcnx+551peujmaXuvzY1V7QWlmzJb/++qu2bt1a5Phnn31mGwx+ZX0hISH6+9//ro0bN+rUqVPKzs7Wzp079cADD8hsNmvixIl68803C5XJyMiw1efoHqz7LRYLL46vAwGIHcnJyerTp4+ys7M1dOhQjR07ttBxf39/SQWRsiPWP87Lx45cacKECcrIyLBtaWlpTmg9AACocFy4DkhEREShF6bTp0+32wRnvaC16tChg9q2bStJGjFiRKEJgbZs2aIxY8bYfr6yvv79++uNN95Qx44dVatWLfn5+alVq1b68MMPbb1aJk6cqKysrCLtv9o9WNtf3HuAfQQgVzh58qRuv/12nThxQr1797YtZHM5a/R77tw5GQ4GaBXnLYCfn5+CgoIKbQAAACXlyi5YaWlphV6YWtdJu5KzXtBebtGiRapTp4727dunpk2bqkmTJmrQoIFuueUWXbx4UXfffbckqUqVKsX9VemFF16Qn5+fMjIytHbt2iLtv9o9XJ79Ke49oCgCkMucOXNGt99+uw4fPqyuXbtq6dKl8vHxKXJe48aNJRV8CY8fP263riNHjhQ6FwAAwBNd+bL08izA5YrTvao4L2gv16RJE+3cuVNPPfWUoqKilJKSogsXLuj+++9XYmKi7eVtnTp1SnQ/zZs3lyQdOnTItj84OFheXl5XvQfrfi8vL14cXwcCkP85f/687rrrLu3evVvt2rXTypUrHUa2kZGRti+6dYq4K1n321vkBgAAwKnKwTS81peuqampys/Pt3tOaV7Q1qlTRzNnztThw4eVk5Oj3377TQsXLlSDBg20fft2SbJ11Sou6wvmy9vp6+uryMjIQu101P6oqCi7L6lRPAQgKshk9OvXT1u2bFHz5s31zTffFJn7+XImk0kDBgyQJM2bN6/I8U2bNmn//v3y8fFR3759XdZuAACA8qJ169by8fFRdna2EhMTixzPy8vTtm3bJDnnBe2ePXt04MAB+fv7q0ePHsUuZzabbbNm1atXr9Axa7t4wexaFT4AMZvNiouL09q1a9WwYUN9++23ql69+jXLjRs3Tr6+vlq1apVmzJhhGwty9OhRPfjgg5Kk0aNHlyglCAAAUBrlYRreoKAgWyBg7wXt0qVLlZmZqRo1aujWW2+9rvs1DMM2FuX+++8vdpcua9vOnTsnb2/vIu0YOHCgJOnTTz8tNEBdkrKysmzrw91zzz3X0XpU+ADk008/1WeffSapoD/f4MGD9Ze//KXIZl350qpBgwaaM2eOvLy8NH78eEVERKhNmzZq3LixDhw4oLZt22rGjBllcEcAAABl47nnnpPJZNLcuXO1ePFi2/6kpCQ988wzkqTx48cXmmVq5syZioqKUlxcXJH6NmzYoDVr1hSa9Cc9PV0jR47UypUrVbt2bcXHxxcqk5mZqSFDhhSZutdsNmvOnDm2ZRZGjRpVZJHDQYMGKSYmxnaNixcvSpIuXLigkSNHKj09XbGxserfv38pfjuwsr9KTAVy+WwGBw8edLgwTv369YvsGzZsmBo1aqTp06dr06ZN2rt3r6KjozVkyBA9++yzhWZTAAAAcJnLps11ap0l1KlTJ02dOlUTJ07U0KFDNXHiRFWpUkW7d++WxWJR79699f/+3/8rVObcuXM6evSooqKiitS3fft2jRkzRlWrVlWDBg1kGIb27dun/Px8hYeH65tvvrGthm5lsVi0ZMkSLVmyRCEhIWrQoIEqVaqkgwcP6ty5c5KkXr16adasWUWu5+3traVLl6pLly5atmyZVq9erUaNGunQoUPKyMhQ9erV9cknn9gGq6N0Kvxvb8SIETIM45pbSkqK3fIdO3bUypUrlZ6eruzsbO3fv1+TJ08m+AAAABXSc889p5UrV6pbt25KT0/XoUOH1KJFC82cOVMJCQny9vYudl233nqrhg0bpjp16ujw4cNKTk5Ws2bNNGXKFO3du1exsbFFygQGBurVV19V//79FRoaqsOHD2vXrl3y9/dX79699cknn+jLL790+KwWGxurpKQkjR49WlWqVNHPP/+sKlWq6KGHHlJSUpKaNWtW6t8NCpgMRwtZwO0yMzMVHBysyPhp8iKAAQDAI1iys5X6j4nKyMhw+9Ss1meHjne8qEo+zn12yM/L1qb/TiqT+8KNrcJ3wQIAAPB4FqNgc3adgAtU+C5YAAAAANyHDAgAAICnKyeD0IHiIAMCAAAAwG3IgAAAAHg4k0q+cGBx6gRcgQwIAAAAALchAwIAAODpDKNgc3adgAuQAQEAAADgNmRAAAAAPJzJcMEYEBIgcBECEAAAAE/HNLzwIHTBAgAAAOA2ZEAAAAA8nMkwZHLyoHFn1wdYkQEBAAAA4DZkQAAAADyd5X+bs+sEXIAMCAAAAAC3IQMCAADg4RgDAk9CBgQAAACA25ABAQAA8HSsAwIPQgACAADg6QyjYHN2nYAL0AULAAAAgNuQAQEAAPBwJqNgc3adgCuQAQEAAADgNmRAAAAAPB1jQOBByIAAAAAAcBsyIAAAAB7OZCnYnF0n4ApkQAAAAAC4DRkQAAAAT8cYEHgQAhAAAABPx0ro8CB0wQIAAADgNmRAAAAAPJzJMGRycpcpZ9cHWJEBAQAAAOA2ZEAAAAA8HYPQ4UHIgAAAAABwGzIgAAAAns6Q5OyFA0mAwEXIgAAAAABwGzIgAAAAHo5ZsOBJCEAAAAA8nSEXDEJ3bnWAFV2wAAAAALgNGRAAAABPxzS88CAVPgOSnJysOXPm6KGHHlLLli1VqVIlmUwmTZs27ZplN2/erH79+qlmzZoKCAhQs2bNNHXqVGVnZ7uh5QAAAOXTV199pR49eqh69eoKDAxUmzZtNHv2bFksJZ+qKyMjQ5MmTVJsbKwqV66skJAQdenSRYsXL3ZY5pdfftH06dPVs2dP1alTRz4+Pqpevbpuu+02vf/++w7bsX79eplMpqtu7777bonvAYVV+AzIrFmzNGvWrBKXW7RokYYPHy6z2azw8HBFRERo9+7dmjRpklauXKn169ercuXKLmgxAADAFSySTC6osxTi4+M1YcIESVJ0dLSqVKmipKQkPfnkk1q9erVWrFghL6/ivQM/duyYbrvtNh08eFDe3t6KjY1VXl6eNmzYoB9++EHff/+93nnnnUJlzGazmjRpYvu5Xr16atWqlVJTU7V+/XqtX79eS5YsUUJCgvz9/e1eNygoSC1atLB7rG7dusVqOxyr8BmQ0NBQ9enTRy+++KK+/vprDRo06JplUlJSNGrUKJnNZr366qtKS0tTYmKiDh48qCZNmmjbtm0aP368G1oPAABQfmzevFn//Oc/5eXlpY8//liHDx9WUlKSEhMTVbt2bX3++ed67bXXil3fAw88oIMHD6p58+Y6dOiQdu3apT179mjnzp0KCwvTu+++q48++qhQGcMwFBISookTJ+rw4cNKS0vTtm3bdOrUKX3yyScKCAjQqlWrNHHiRIfXbd26tTZs2GB369evX6l/PyhQ4QOQiRMnauXKlXr++ed15513qkqVKtcsM2PGDOXk5Khnz54aN26cTKaCVw7169fX/PnzJUnvvfeeTp065dK2AwAASH9Mw+vsraSmTZsmwzA0evRoDRkyxLa/ZcuWtsAjPj5eeXl516wrKSlJ69atkyTNnTtXUVFRduubMmVKoXLe3t46cuSIpk6dqujo6ELH7r33Xk2ePFmSNH/+/FJ1CcP1q/ABSEkZhqEVK1ZIkkaNGlXkeMeOHRUTE6O8vDwlJCS4u3kAAABlIjMzU6tXr5Zk/xlp8ODBCgoKUnp6ui2wuJqNGzdKKuhCdcsttxQ5PmDAAHl5eenIkSPasWOHbb/JZFK1atUc1tuzZ09J0tmzZ3X69OlrtgPORwBSQqmpqTpx4oQkqVOnTnbPse7fsmWL29oFAAAqMOssWM7eSmDnzp3Kzc2Vv7+/2rRpU+S4j4+P2rVrJ6l4z0hnz56VJIWHh9s97uvrq9DQUEnSjz/+WOx2Xj5ZUEBAgN1zUlNTNWLECHXv3l133323JkyYoF27dhX7Gri6Cj8IvaQOHjwoSfLz81NYWJjdc6zpPuu5AAAALlUOpuG1PvdERkaqUiX7j5jR0dFas2ZNsZ6RgoODJRUMRLcnNzdXv//+uyTpwIEDxW7np59+KkmKjY1VUFCQ3XOSk5OVnJxs+/mLL75QfHy8Hn/8cc2aNUve3t7Fvh6KIgNSQtZoPCQkxDb240rWtJ/1XEdycnKUmZlZaAMAAChPrnxWycnJsXue9bnnat2fivuMJMmWLfn111+1devWIsc/++wz2xiO4tQnSbt379bbb78tSXYnDAoICNDIkSO1Zs0aHTt2TDk5Odq3b5+efvppmUwmvfXWW3r22WeLdS04RgBSQta0na+vr8Nz/Pz8JEmXLl26al3Tp09XcHCwbYuIiHBeQwEAQMXhwi5YERERhZ5Xpk+fbrcJznxGkqQOHTqobdu2kqQRI0bol19+sR3bsmWLxowZY/u5OPWdO3dOgwYNUm5uru666y498MADdq85f/58devWTWFhYfL19VVMTIxef/11vf7665KkmTNnFsqOoOQIQErIOl90bm6uw3OsbwYc9Su0mjBhgjIyMmxbWlqa8xoKAADgBGlpaYWeV6xrfFzJmc9IVosWLVKdOnW0b98+NW3aVE2aNFGDBg10yy236OLFi7r77rsl6ZqzmObk5Kh///765Zdf1Lx5cy1cuLBY17/cE088oXr16slsNuvzzz8vcXn8gQCkhKypw3Pnzslw0DeyOClIqeAtQFBQUKENAACgxCwu2qQizyrWLMaVitO9qrjPSFZNmjTRzp079dRTTykqKkopKSm6cOGC7r//fiUmJtqenerUqeOwjvz8fN1333367rvvFBUVpVWrVhX7+pfz9vZW+/btJUmHDh0qcXn8gUHoJdS4cWNJBZH08ePH7c7McOTIkULnAgAA3Oiszz2pqanKz8+3OxC9NM9IderU0cyZMzVz5swix7Zv3y5Jtq5aVzIMQyNHjlRCQoLq1q2r1atXO5xEqDh8fHwkFQQ1KD0yICUUGRlpi7Kt81Nfybq/Q4cObmsXAACouMrDQoStW7eWj4+PsrOzlZiYWOR4Xl6etm3bJsk5z0h79uzRgQMH5O/vrx49etg954knntDChQtVo0YNffvtt2rYsOF1X1MqWJsEpUcAUkImk0kDBgyQJM2bN6/I8U2bNmn//v3y8fFR37593d08AACAMhEUFGQLBOw9Iy1dulSZmZmqUaOGbr311uu6lmEYtrEo999/v90uVc8995zefvttVa1aVd98842aN29+XddctWqVdu/eLUkOAx4UDwFIKYwbN06+vr5atWqVZsyYYRsLcvToUT344IOSpNGjR1+1PyIAAIDTlIOFCKWCh36TyaS5c+dq8eLFtv1JSUl65plnJBVMf3v5TFkzZ85UVFSU4uLiitS3YcMGrVmzptC42/T0dI0cOVIrV65U7dq1FR8fX6Tca6+9ppdfflkBAQH64osvdPPNNxer/XFxcVq7dq1tel+pINhZsWKFrX09e/akl8t1MhmORlJXEBs3blS/fv1sP58/f145OTmqXLlyoRkadu7cWWia3A8//FAjR46UxWJReHi4atWqpd27dysvL09t27bVd999p8DAwBK1JTMzU8HBwYqMnyav/80kAQAAyjdLdrZS/zFRGRkZbp9Qxvrs0KPh06rkbX9weGnlm3O0+vDMEt/XSy+9pIkTJ0oqWHiwSpUq2r17tywWi3r37q2EhIRCC/lNmTJFL7zwgrp27ar169cXqmvmzJkaM2aMqlatqgYNGsgwDO3bt0/5+fkKDw/XN998o9jY2EJljh8/rnr16skwDNWqVeuq403+85//FHphHBISooyMDAUGBqpRo0by8/NTcnKyTp8+LalgbZKvvvrKtgI7SqfCD0LPy8tTenp6kf0XL17UxYsXbT+bzeZCx4cNG6ZGjRpp+vTp2rRpk/bu3avo6GgNGTJEzz77rG0qOgAAgIrkueeeU8uWLfX6669rx44dOnnypFq0aKGRI0fqiSeeKNEq4rfeequGDRumzZs36/DhwzKZTGrWrJkGDhyoMWPG2A2McnNzbRmT3377Tb/99pvD+q1rl1jFx8dr/fr1SkpKUmpqqrKyshQSEqLu3bsrLi5Ow4cPtw1ER+lV+AxIeUIGBAAAz1MuMiDRT7kmA3JkVpncF25sjAEBAAAA4DYVvgsWAACA5yvdoPFr1gm4ABkQAAAAAG5DBgQAAMDTlXLa3GvWCbgAGRAAAAAAbkMGBAAAwNNZDDl9zIaFDAhcgwAEAADA0xmWgs3ZdQIuQBcsAAAAAG5DBgQAAMDTMQgdHoQMCAAAAAC3IQMCAADg6RiEDg9CBgQAAACA25ABAQAA8HSMAYEHIQMCAAAAwG3IgAAAAHg6Qy7IgDi3OsCKDAgAAAAAtyEDAgAA4OkYAwIPQgACAADg6SwWSRYX1Ak4H12wAAAAALgNGRAAAABPRxcseBAyIAAAAADchgwIAACApyMDAg9CBgQAAACA25ABAQAA8HQWQ05fOdBCBgSuQQYEAAAAgNuQAQEAAPBwhmGRYTh33Q5n1wdYEYAAAAB4OsNwfpcpBqHDReiCBQAAAMBtyIAAAAB4OsMFg9DJgMBFyIAAAAAAcBsyIAAAAJ7OYpFMTh40ziB0uAgZEAAAAABuQwYEAADA0zEGBB6EDAgAAAAAtyEDAgAA4OEMi0WGk8eAsBAhXIUABAAAwNPRBQsehC5YAAAAANyGDAgAAICnsxiSiQwIPAMZEAAAAABuQwYEAADA0xmGJGcvREgGBK5BBsQJvvrqK/Xo0UPVq1dXYGCg2rRpo9mzZ8tiYfYIAABQ8Tjz2SgjI0OTJk1SbGysKleurJCQEHXp0kWLFy++Ztl9+/bp/vvvV926deXv76+GDRtq7NixOnfu3FXLHTt2TA8//LAiIiLk5+enyMhIPfLIIzp27FiJ24+iTIZBeHs94uPjNWHCBElSdHS0qlSpot27d8tisahv375asWKFvLyKF+dlZmYqODhYkfHT5OXv78pmAwAAJ7FkZyv1HxOVkZGhoKAgt17b+uxwW6V7VMnk49S68408rcv/T4nvy5nPRseOHdNtt92mgwcPytvbW7GxscrLy9O+fftkGIYeffRRvfPOO3bLrlu3Tr1799alS5dUs2ZNRUREaP/+/bp48aKio6O1adMm1a5du0i5vXv3qnPnzjpz5oyCg4PVsGFDHT58WBkZGapRo4Y2bNigmJiYYv8+UBQZkOuwefNm/fOf/5SXl5c+/vhjHT58WElJSUpMTFTt2rX1+eef67XXXivrZgIAALiFs5+NHnjgAR08eFDNmzfXoUOHtGvXLu3Zs0c7d+5UWFiY3n33XX300UdFymVlZem+++7TpUuX9OSTT+rYsWPasWOHUlNT1alTJx05ckSjRo0qUs5sNmvw4ME6c+aMBg0apOPHj2vHjh06duyYBg4cqPT0dN133330crlOBCDXYdq0aTIMQ6NHj9aQIUNs+1u2bGn744qPj1deXl5ZNREAAFQEhsU1Wwk589koKSlJ69atkyTNnTtXUVFRduubMmVKkbLvvvuuTp8+raZNm+q1116Tj09BdqhGjRr6+OOPValSJX355ZdKTEwsVG758uXau3evatSooffff1+VK1eWJAUGBmrBggWqUaOGfvrpJyUkJBT/l4IiCEBKKTMzU6tXr5YkuxH04MGDFRQUpPT0dNsfDwAAgCsYFsMlW0k4+9lo48aNkqR69erplltuKXJ8wIAB8vLy0pEjR7Rjx45Cx5YvXy5JGjFihLy9vQsdi4yMVI8ePSRJ//nPf+yWu/fee1W1atVCx6pWrarBgwdLkpYuXXrN9sMxApBS2rlzp3Jzc+Xv7682bdoUOe7j46N27dpJkrZs2eLu5gEAALiVs5+Nzp49K0kKDw+3e9zX11ehoaGSpB9//NG2Pz8/3xaQdOrUyW5Z6/4r22Gtp6TlUDIEIKV08OBBSQVRdKVK9mczjo6OLnQuAACAS5SDLljOfjYKDg6WJIczT+Xm5ur333+XJB04cMC2PyUlxdbFy3q94rQjNzdXqampxSp3+TVQcqwDUkrWqLxatWoOz7Ees557pZycHOXk5Nh+zsjIkFQwmwYAAPAM1v/dLsuJRfOVJzn58vkqeMDOzMwstN/Pz09+fn5FznfGs9HlrNmSX3/9VVu3blX79u0LHf/ss89sg8Evr+/yfztqi712ZGRk2Oq7VjmLxaLMzEzVqFHjmveBoghASin7f/+x8fX1dXiO9Y/z0qVLdo9Pnz5dL7zwQpH9v06Z5oQWAgAAd8rKyrK9tXcXX19f1alTRxtOfuWS+qtUqaKIiIhC+yZPnmx34Lczno0u16FDB7Vt21Y7duzQiBEj9Nlnn+mmm26SVNAFasyYMbZzL68v+7IXuY7aYq8dJSlX3HuAfQQgpeT/v3U6cnNzHZ5jzW4EBATYPT5hwgQ988wztp/PnTun+vXrKzU11e3/AUPZyMzMVEREhNLS0tw+dzzcj8+74uEzrxgMw1BWVpbCwsLcfm1/f38lJydf9XnkehiGIZPJVGifveyHtS3S9T0bXWnRokW69dZbtW/fPjVt2lSNGjVSbm6uUlJSFBISorvvvlsrV65UlSpVirTD2hZ/O2ur2WvHleWu1v6S3AOKIgAppeKkEK+VinSUwgwODuZ/qCqYoKAgPvMKhM+74uEzv/GV5YtDf39/uw/Z7uaMZ6MrNWnSRDt37lR8fLxWrlyplJQUBQcH6/7779fUqVP1/PPPS5Lq1KlTpB3W69WtW7dY7QgODpaXl5csFovDe7Du9/Ly4m/6OjAIvZQaN24sSUpNTVV+fr7dc44cOVLoXAAAgBuVq56N6tSpo5kzZ+rw4cPKycnRb7/9poULF6pBgwbavn27JKlt27a286OiomzrflivV5x2+Pr6KjIysljlLr8GSo4ApJRat24tHx8fZWdnF1nERpLy8vK0bds2SQV9GAEAAG5k7n422rNnjw4cOCB/f3/buh6SVKlSJds0wNa1RK5k3X9lO6w/l7QcSoYApJSCgoJsX/Z58+YVOb506VLb7Ai33nprser08/PT5MmTHfatxI2Hz7xi4fOuePjMUZG44tnIEcMwNGHCBEnS/fffX6RL18CBAyVJCxYskNlsLnQsNTXVtmDioEGD7Jb79NNPlZWVVehYVlaWbQHCe+6557raX+EZKLUNGzYYJpPJ8PLyMj7++GPb/l27dhm1a9c2JBmvvPJKGbYQAADAfUrzbPT6668b9evXN+67774i9f3www/G6tWrDYvFYtv3+++/G8OHDzckGbVr1zZOnz5dpFxGRoYRGhpqSDKefPJJIzc311a2U6dOhiSjV69eRcrl5+cbMTExhiRj0KBBxoULFwzDMIzz588bgwYNMiQZsbGxhtlsLt0vCIZhGAYByHWaNm2aoYKZt43o6GjjT3/6k+Hl5WVIMnr37m3k5+eXdRMBAADcpqTPRpMnTzYkGV27di1S1+uvv25IMqpWrWr86U9/Mlq0aGFUqlTJkGSEh4cbP//8s8N2rF692vD39zckGTVr1jTatm1rVK5c2ZBkREVFGSdOnLBb7ueffzaqVatmSDKCg4ONtm3bGsHBwYYko3r16saePXuu6/cDw6AL1nV67rnntHLlSnXr1k3p6ek6dOiQWrRooZkzZyohIUHe3t5l3UQAAAC3ceaz0a233qphw4apTp06Onz4sJKTk9WsWTNNmTJFe/fuVWxsrMOy3bt31/bt2xUXFyeTyaSff/5ZtWvX1jPPPKPExMRCM2ddLjY2VklJSRo9erSqVKmin3/+WVWqVNFDDz2kpKQkNWvWrMS/ExRmMowyXLYTAAAAQIVCBgQAAACA2xCAlANfffWVevTooerVqyswMFBt2rTR7NmzZbFYyrppKCHDMLRhwwaNGzdOt9xyi0JCQuTr66uwsDANGjRI69atu2r5zZs3q1+/fqpZs6YCAgLUrFkzTZ06VdnZ2W66AzjDxIkTZTKZZDKZNG3aNIfn8Xl7NrPZrDlz5qhr164KDQ2Vv7+/6tevr/79+yshIcFuGT5zABCzYJW16dOnOxyo1bdvX2ZZ8DCrV6+2fZ5eXl7GTTfdZLRu3dqoUqWKbf/EiRPtll24cKHh7e1tG1jXunVrw8fHx5BktGvXzjYTB8q3vXv3Gr6+vrbPe+rUqXbP4/P2bGfOnDFuueUWQ5JhMpmMJk2aGG3btjXq1q1rmz3nSnzmAFCAAKQMbdq06ZpT1c2YMaMMW4iS+vbbb41GjRoZb7/9tnHmzBnb/pycHGPChAm2h9KVK1cWKpecnGz4+fkZkoxXX33VNt1gSkqK0aRJE0OS8fjjj7v1XlByFovF6Ny5sxEYGGh069bNYQDC5+3ZzGaz8Ze//MWQZAwcONBIS0srdDwtLc347rvvCu3jMweAPxCAlKG77rrLkGQ8/PDDRY4tWrTIkGTUqFHDNnc1yr+MjAwjLy/P4fFevXrZsluXe+yxxwxJRs+ePYuU2bhxoyHJ8PHxMU6ePOn0NsN55syZY5vj3jpHvb0AhM/bs73zzjuGJOO2224rdpaazxwA/sAYkDKSmZlpW4Vz1KhRRY4PHjxYQUFBSk9Pv+a4AZQfQUFBqlSpksPjt99+uyTpl19+se0zDEMrVqyQZP+70LFjR8XExCgvL89hv3KUvdOnT+vZZ59Vs2bNNGbMGIfn8Xl7vlmzZkmSpk6dKi+va//PKJ85ABRGAFJGdu7cqdzcXPn7+6tNmzZFjvv4+Khdu3aSpC1btri7eXAR60DTgIAA277U1FSdOHFCktSpUye75az7+S6UX2PGjNGZM2f09ttvy8fHx+F5fN6e7eDBg9q/f7+qV6+ujh07KiEhQX/961/VvXt3xcXFae7cucrJySlUhs8cAApz/KoWLnXw4EFJUmRkpMM35tHR0VqzZo3tXHg2wzC0dOlSSYUfQqyfr5+fn8LCwuyWjY6OLnQuypc1a9Zo0aJF+utf/6quXbte9Vw+b8+2Y8cOSVJMTIweeOABLVq0qNDxTz75RP/+97/1zTffqH79+pL4zAHgSmRAysjZs2clSdWqVXN4jvWY9Vx4tjlz5mjnzp3y9fXV008/bdtv/XxDQkJkMpnsluW7UH5lZ2fr0UcfVXBwsP71r39d83w+b89mzWRs27ZNixYt0ujRo5WSkqLs7GytXr1a0dHR2r9/vwYNGmSbSp3PHAAKIwApI9auOL6+vg7P8fPzkyRdunTJLW2C6yQmJuqpp56SJE2bNk0NGza0HeO74NmmTZumQ4cO6aWXXlLt2rWveT6ft2e7cOGCJCkvL0+dO3fWnDlzVL9+ffn5+al79+5avny5TCaTduzYoS+//FISnzkAXIkApIz4+/tLknJzcx2eY+1HfPl4AXie5ORk9enTR9nZ2Ro6dKjGjh1b6DjfBc+1b98+zZgxQ23atNHf/va3YpXh8/Zs1s9Pku2lwuVatmyp2267TZL0zTffFCrDZw4ABQhAykhx0u3F6aaF8u3kyZO6/fbbdeLECfXu3VsLFiwo0gXD+vmeO3dOhmHYrYfvQvn02GOPKT8/X++8806xZkOS+Lw93eWfSUxMjN1zmjZtKklKSUkpVIbPHAAKEICUkcaNG0sqmB0lPz/f7jlHjhwpdC48y5kzZ3T77bfr8OHD6tq1q5YuXWp3diTr55uTk6Pjx4/brYvvQvm0c+dOmUwm9e3bV3Xq1Cm0ffLJJ5KkV155RXXq1LHNasfn7dmaNGli+7e129SVrPvNZrMkPnMAuBIBSBlp3bq1fHx8lJ2drcTExCLH8/LytG3bNklShw4d3N08XKfz58/rrrvu0u7du9WuXTutXLnSYdeKyMhI1alTR5K0ceNGu+dY9/NdKH/MZrNOnTpVZLP2+z9//rxOnTql06dPS+Lz9nStW7e2damyBg1Xsu4PDw+XxGcOAFciACkjQUFB6tGjhyRp3rx5RY4vXbpUmZmZqlGjhm699VY3tw7XIycnR/369dOWLVvUvHlzffPNN6patarD800mkwYMGCDJ/ndh06ZN2r9/v3x8fNS3b1+XtRslZ+1SY28bPny4pILF6gzDsHXH4fP2bIGBgbrrrrskSR988EGR4ydPntR///tfSVK3bt0k8ZkDQBFlsfw6CmzYsMEwmUyGl5eX8fHHH9v279q1y6hdu7YhyXjllVfKsIUoqfz8fKN///6GJKNhw4bG8ePHi1XuyJEjhq+vryHJePXVVw2LxWIYhmGkpKQYTZo0MSQZf/vb31zZdDjZ8OHDDUnG1KlTixzj8/Zsu3btMry9vQ0vLy9jwYIFtv1nz5417rjjDkOSER0dbeTk5NiO8ZkDwB9MhuFgRBzc4qWXXtLEiRMlFSxEVaVKFe3evVsWi0W9e/dWQkKCvL29y7iVKK7Fixdr6NChkgr6cteqVcvueXXr1rUtSmj14YcfauTIkbJYLAoPD1etWrW0e/du5eXlqW3btvruu+8UGBjo8nuAc4wYMUIffPCBpk6davsbvxyft2d799139dhjj8kwDEVGRqpWrVrau3evLl68qNDQUH377bdq1apVoTJ85gDwP2UcAMEwjJUrVxrdunUzgoODjcqVKxstW7Y0Zs6caeTn55d101BC77//viHpmlv9+vXtlt+4caPRp08fo3r16oafn5/RpEkTY8qUKcalS5fceyO4blfLgFjxeXu277//3rj77ruN0NBQw9fX14iKijIef/xx49dff3VYhs8cAMiAAAAAAHAjBqEDAAAAcBsCEAAAAABuQwACAAAAwG0IQAAAAAC4DQEIAAAAALchAAEAAADgNgQgAAAAANyGAAQAAACA2xCAAAAAAHAbAhAAAAAAbkMAAgDFlJ2drfr166tZs2ayWCxl3ZxSMZvNuummmxQdHa3c3Nyybg4AoAIiAAGAYpo9e7ZSU1M1ceJEeXl55n8+vb29NWHCBCUnJ+udd94p6+YAACogk2EYRlk3AgDKu8zMTEVFRalatWr65Zdf5O3tXdZNKrX8/HxFR0fr0qVLSklJUWBgYFk3CQBQgXjmKzwAcLNFixbp7NmzeuCBBzw6+JCkSpUqaejQofr999+1ZMmSsm4OAKCCIQABgGKYM2eOJGnIkCFl3BLniIuLkyTNnTu3jFsCAKhoCEAA3FBGjx4tk8mk22+/XfZ6mE6aNEkmk0ktWrRQTk5Oser85ZdftHPnTjVs2FBNmjQpcjwlJUUmk0lRUVGSCh7qW7durcqVKys8PFxPPvmksrKyJBUMAv/3v/+t5s2bKyAgQPXq1dM//vEPuwPCp0yZIpPJpClTpig9PV2PPfaY6tWrp4CAALVs2bJQ9uLo0aMaOXKkwsLCFBAQoLZt2+rLL790eE+tWrVSeHi4fvzxR6Wmphbr9wAAgDMQgAC4ocycOVPR0dFavXq1Zs2aVejYli1b9PLLL8vX11cLFy6Un59fser8/vvvJUnt27e/5rn/7//9Pz300EPKyspSw4YN9dtvv2n27Nnq37+/LBaL7rnnHo0dO1aGYah+/fo6fvy4XnnlFT300EMO6zx79qxuueUWzZs3T7Vr11aNGjX0008/aciQIfrwww914MABtW/fXp9++qnCwsJUpUoVJSYmql+/flq9erXDeq33Y70/AADcgQAEwA2lSpUq+uijj2yzPe3Zs0eSdPHiRT3wwAMym82aOnWqWrZsWew6N23aJElq27btVc87duyY5s2bp9WrV+vQoUP6+eeftXPnTtWoUUNr167VoEGDtH37du3cuVN79+7V/v37tXbtWvn6+urDDz/U3r177db7zjvvKCIiQmlpadqxY4d+/fVXxcfHS5L+8Y9/aNiwYerWrZtOnjyp7du369SpU3rkkUdkNpv13HPPOWxvu3btJEkbNmwo9u8CAIDrRQAC4IbTsWNHjR8/XtnZ2frrX/+q3NxcPfPMMzp48KC6dOmisWPHlqi+o0ePSpLq1q171fPy8/M1ZcoUde/e3bYvNjZWDz/8sCTps88+0+zZs9WqVSvb8VtvvVUDBw6UJP33v/+1W2+lSpW0cOFC1apVy7Zv7Nixqlevnk6cOKG0tDTNmzdPVatWlSR5eXkpPj5e/v7+2rp1q86cOWO3Xuv9WO8PAAB3IAABcEN64YUX1Lp1a+3atUt9+vTR//3f/ykoKEgffvhhidfw+P333yVJ1atXv+a5Dz74YJF91oCjevXq6t+/f5HjrVu3liQdOXLEbp29evVSWFhYoX3e3t5q0aKFpIKB8ZUrVy50PCQkRA0aNJAkJScn263Xej+nT592cDcAADgfAQiAG5KPj48WLlwof39/ffvtt5KkN954Q/Xr1y9xXdnZ2ZJ0zTEjNWvWVFBQkN39ktSwYUOH5STp/Pnzdo9fq1xp6w0ICJAkXbp0ye5xAABcgQAEwA2rUaNGioyMlCQFBwdr0KBBparHmik4d+7cVc+7MgthZTKZinXc0bqwrqrX2jUrNDTU7nEAAFyBAATADeu5557TL7/8Ii8vL2VkZGjMmDGlqsc69sLRWApPZb0fa6YEAAB3IAABcEP6/vvv9dprr6ly5cr69ttvFRISorlz52rlypUlrss6hmPfvn1ObmXZss661aZNmzJuCQCgIiEAAXDDyczM1PDhw2WxWDRjxgx169ZNb731lqSChQpLOuj6L3/5iyRp+/btTm9rWdq6daskqXPnzmXcEgBARUIAAuCG8+STTyolJUU9e/bUY489JkkaOnSo7rvvPv3222+2aXGLq2PHjgoMDNT27dttA9I93fnz55WUlKSQkJBiLbAIAICzEIAAuKGsWLFCH3zwgapVq6b333+/0LF33nlHYWFh+uyzz4ocu5rAwEDFxcXpwoUL+vLLL53d5DKRkJCgnJwcDR06tNgrwgMA4AwEIABuGKdOnbJlN95+++0ia2dYgxKTyaSnnnpKKSkpxa7bWu+iRYuc1t6ytHjxYkkFXdIAAHAnk+FofkYAQCE9e/bUunXrdPDgQUVFRZV1c0rt0KFDiomJ0R133HHDZHQAAJ6DDAgAFNMrr7wis9msl19+uaybcl1eeuklGYah+Pj4sm4KAKACqlTWDQAAT9G6dWvNmTNHv/32mywWi7y8PO8djtlsVqNGjTR37ly1aNGirJsDAKiA6IIFAAAAwG087/UdAAAAAI9FAAIAAADAbQhAAAAAALgNAQgAAAAAtyEAAQAAAOA2/x+QxmKpCAs3MAAAAABJRU5ErkJggg==", "text/html": [ "\n", "
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\n", " " ], @@ -681,46 +695,49 @@ "Operator `acoustic_iso_state` instance configuration:\n", "\t * name=acoustic_iso_state\n", "\t * subs={h_x: 0.0004, h_y: 0.0004, dt: 5e-08}\n", - "\t * opt=advanced-fsg\n", + "\t * opt=advanced\n", "\t * devicecreate=(p(t, x, y),)\n", - "Operator `acoustic_iso_state` generated in 2.75 s\n", - " * lowering.Clusters: 1.26 s (46.0 %)\n", - " * specializing.Clusters: 0.79 s (28.9 %)\n", - " * lowering.Expressions: 0.96 s (35.1 %)\n", - "Flops reduction after symbolic optimization: [503 --> 91]\n", - "recompiling for non-existent cache dir (/tmp/devito-codepy-uid1000/fb896a9/577f1f9575fb092bfd481fcac94f127a).\n", - "gcc -march=native -O3 -g -fPIC -Wall -std=c99 -Wno-unused-result -Wno-unused-variable -Wno-unused-but-set-variable -ffast-math -shared -fopenmp /tmp/devito-jitcache-uid1000/fb896a97036744fe22df05400a59051eeeb3f431.c -lm -o /tmp/devito-jitcache-uid1000/fb896a97036744fe22df05400a59051eeeb3f431.so\n", - "Operator `acoustic_iso_state` jit-compiled `/tmp/devito-jitcache-uid1000/fb896a97036744fe22df05400a59051eeeb3f431.c` in 0.43 s with `GNUCompiler`\n", + "Operator `acoustic_iso_state` generated in 7.82 s\n", + " * lowering.Clusters: 5.57 s (71.3 %)\n", + " * specializing.Clusters: 3.67 s (47.0 %)\n", + " * fuse: 2.09 s (26.8 %)\n", + "Flops reduction after symbolic optimization: [2254 --> 408]\n", + "recompiling for non-existent cache dir (/tmp/devito-codepy-uid1000/13805d3/c604a8a4ecc74d949259aed0d3e6f3f8).\n", + "gcc -march=native -O3 -g -fPIC -Wall -std=c99 -Wno-unused-result -Wno-unused-variable -Wno-unused-but-set-variable -ffast-math -shared -fopenmp /tmp/devito-jitcache-uid1000/13805d3b1c218effeddafed64564742b152d6968.c -lm -o /tmp/devito-jitcache-uid1000/13805d3b1c218effeddafed64564742b152d6968.so\n", + "Operator `acoustic_iso_state` jit-compiled `/tmp/devito-jitcache-uid1000/13805d3b1c218effeddafed64564742b152d6968.c` in 0.91 s with `CustomCompiler`\n", "(ShotID 0) Using inhomogeneous density\n", "(ShotID 0) Using attenuation with power 0\n", "(ShotID 0) Running state equation for shot\n", "AutoTuner: could not perform any runs\n", - "Operator `acoustic_iso_state` ran in 0.19 s\n", - "Global performance: [OI=1.78, 76.60 GFlops/s, 0.95 GPts/s]\n", + "Operator `acoustic_iso_state` ran in 0.22 s\n", + "Global performance: [OI=0.01, 66.57 GFlops/s, 0.82 GPts/s]\n", + "Global performance : [0.22 s, 0.85 GPts/s]\n", "Local performance:\n", - " * section0<120> ran in 0.01 s [OI=0.50, 0.01 GFlops/s, 0.00 GPts/s]\n", - " * section1<<1999,309,309>,<1999,300,300>> ran in 0.18 s [OI=1.78, 81.68 GFlops/s, 1.02 GPts/s]\n", - " * section2<<1999,1,2,2>,<1999,1,2,2>> ran in 0.01 s [OI=5.80, 0.11 GFlops/s, 0.01 GPts/s]\n", - " * section3<<1999,120>,<1999,120,2,2>> ran in 0.01 s [OI=1.32, 2.31 GFlops/s, 0.00 GPts/s]\n", - "Performance[mode=advanced-fsg] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6}\n", + " * multipass0 ran in 0.21 s [OI=0.01, 70.67 GFlops/s, 0.87 GPts/s]\n", + " + section0 ran in 0.08 s [35.75%] \n", + " + section1 ran in 0.14 s [64.18%] \n", + " * section2 ran in 0.01 s\n", + " * section3 ran in 0.01 s\n", + "Performance[mode=advanced] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6, 'pthreads': 0}\n", + "(ShotID 0) Completing state equation run for shot\n", "(ShotID 0) Completed state equation run for shot\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0a12400028bb422eac8949220d4c877b", + "model_id": "e3f84d9e2c7e49fd86e596698c3d8764", "version_major": 2, "version_minor": 0 }, - "image/png": 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", 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", 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", 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\n", - " \n", + " \n", "
\n", " " ], @@ -806,6 +823,7 @@ "output_type": "stream", "text": [ "(ShotID 0) Preparing to run state for shot\n", + "(ShotID 0) Selected boundary type complex_frequency_shift_PML_2\n", "(ShotID 0) Estimated bandwidth for the propagated wavelet 0.260-0.730 MHz\n", "(ShotID 0) Spatial grid spacing (0.400 mm | 5.137 PPW) is below dispersion limit (0.411 mm | 5.000 PPW)\n", "(ShotID 0) Time grid spacing (0.050 μs | 18%) is below OT2 limit (0.120 μs)\n", @@ -814,50 +832,51 @@ "Operator `acoustic_iso_state` instance configuration:\n", "\t * name=acoustic_iso_state\n", "\t * subs={h_x: 0.0004, h_y: 0.0004, dt: 5e-08}\n", - "\t * opt=advanced-fsg\n", + "\t * opt=advanced\n", "\t * devicecreate=(p(t, x, y),)\n", - "Operator `acoustic_iso_state` generated in 7.06 s\n", - " * lowering.Clusters: 4.11 s (58.3 %)\n", - " * specializing.Clusters: 2.93 s (41.6 %)\n", - " * fuse: 2.07 s (29.4 %)\n", - " * lowering.Expressions: 1.71 s (24.3 %)\n", - "Flops reduction after symbolic optimization: [1119 --> 548]\n", - "recompiling for non-existent cache dir (/tmp/devito-codepy-uid1000/854b6b5/504768efa4c9f00e987ce2448a3e4095).\n", - "gcc -march=native -O3 -g -fPIC -Wall -std=c99 -Wno-unused-result -Wno-unused-variable -Wno-unused-but-set-variable -ffast-math -shared -fopenmp /tmp/devito-jitcache-uid1000/854b6b5ab6a9c339e99065419703ba0e1638e61f.c -lm -o /tmp/devito-jitcache-uid1000/854b6b5ab6a9c339e99065419703ba0e1638e61f.so\n", - "Operator `acoustic_iso_state` jit-compiled `/tmp/devito-jitcache-uid1000/854b6b5ab6a9c339e99065419703ba0e1638e61f.c` in 1.23 s with `GNUCompiler`\n", + "Operator `acoustic_iso_state` generated in 12.42 s\n", + " * lowering.Clusters: 8.62 s (69.5 %)\n", + " * specializing.Clusters: 5.96 s (48.1 %)\n", + " * fuse: 4.27 s (34.4 %)\n", + "Flops reduction after symbolic optimization: [2846 --> 844]\n", + "recompiling for non-existent cache dir (/tmp/devito-codepy-uid1000/938da6c/d96370ca8bda2261da76155998c61ade).\n", + "gcc -march=native -O3 -g -fPIC -Wall -std=c99 -Wno-unused-result -Wno-unused-variable -Wno-unused-but-set-variable -ffast-math -shared -fopenmp /tmp/devito-jitcache-uid1000/938da6c0efae4654609aaaa15c12e46a2049ad9d.c -lm -o /tmp/devito-jitcache-uid1000/938da6c0efae4654609aaaa15c12e46a2049ad9d.so\n", + "Operator `acoustic_iso_state` jit-compiled `/tmp/devito-jitcache-uid1000/938da6c0efae4654609aaaa15c12e46a2049ad9d.c` in 1.65 s with `CustomCompiler`\n", "(ShotID 0) Using inhomogeneous density\n", "(ShotID 0) Using attenuation with power 0\n", "(ShotID 0) Running state equation for shot\n", "AutoTuner: could not perform any runs\n", - "Operator `acoustic_iso_state` ran in 0.31 s\n", - "Global performance: [OI=0.01, 78.17 GFlops/s, 0.59 GPts/s]\n", + "Operator `acoustic_iso_state` ran in 0.33 s\n", + "Global performance: [OI=0.01, 75.77 GFlops/s, 0.55 GPts/s]\n", + "Global performance : [0.33 s, 0.55 GPts/s]\n", "Local performance:\n", - " * section0<300> ran in 0.01 s [OI=0.25, 0.02 GFlops/s, 0.00 GPts/s]\n", - " * section1<300> ran in 0.01 s [OI=0.25, 0.40 GFlops/s, 0.00 GPts/s]\n", - " * section2<120> ran in 0.01 s [OI=0.50, 0.24 GFlops/s, 0.00 GPts/s]\n", - " * section3<<1999,40,300>,<1999,40,300>,<1999,40,300>,<1999,40,300>,<1999,40,300>,<1999,40,300>,<1999,300,40>,<1999,300,40>,<1999,300,40>,<1999,300,40>,<1999,300,40>,<1999,300,40>> ran in 0.14 s [OI=0.01, 80.63 GFlops/s, 0.71 GPts/s]\n", - " * section4<<1999,309,309>,<1999,300,300>> ran in 0.17 s [OI=1.50, 81.42 GFlops/s, 1.11 GPts/s]\n", - " * section5<<1999,1,2,2>,<1999,1,2,2>> ran in 0.01 s [OI=5.80, 0.11 GFlops/s, 0.01 GPts/s]\n", - " * section6<<1999,120>,<1999,120,2,2>> ran in 0.01 s [OI=1.32, 2.24 GFlops/s, 0.00 GPts/s]\n", - "Performance[mode=advanced-fsg] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6}\n", + " * section0 ran in 0.01 s\n", + " * section1 ran in 0.01 s\n", + " * section2 ran in 0.11 s [OI=0.01, 105.14 GFlops/s, 0.93 GPts/s]\n", + " * section3 ran in 0.08 s [OI=2.26, 95.20 GFlops/s, 1.29 GPts/s]\n", + " * section4 ran in 0.15 s [OI=0.01, 48.16 GFlops/s, 0.59 GPts/s]\n", + " * section5 ran in 0.01 s\n", + " * section6 ran in 0.01 s\n", + "Performance[mode=advanced] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6, 'pthreads': 0}\n", + "(ShotID 0) Completing state equation run for shot\n", "(ShotID 0) Completed state equation run for shot\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6931078072504526a50a113fbd94f98c", + "model_id": "8a1a63589b9e42788b9251a0b4c5a611", "version_major": 2, "version_minor": 0 }, - "image/png": 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", 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", 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", 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", 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\n", " Figure\n", "
\n", - " \n", + " \n", "
\n", " " ], @@ -976,7 +995,7 @@ " wavelets : Traces\n", " Source wavelets.\n", " vp : ScalarField\n", - " Compressional speed of sound fo the medium, in [m/s].\n", + " Compressional speed of sound for the medium, in [m/s].\n", " rho : ScalarField, optional\n", " Density of the medium, defaults to homogeneous, in [kg/m^3].\n", " alpha : ScalarField, optional\n", @@ -986,7 +1005,7 @@ " save_wavefield : bool, optional\n", " Whether or not to solve the forward wavefield, defaults to True when\n", " a gradient is expected, and to False otherwise.\n", - " save_bounds : tuple of int, optional\n", + " time_bounds : tuple of int, optional\n", " If saving the wavefield, specify the ``(min timestep, max timestep)``\n", " where the wavefield should be saved\n", " save_undersampling : int, optional\n", @@ -994,7 +1013,22 @@ " it is calculated given the bandwidth.\n", " save_compression : str, optional\n", " Compression applied to saved wavefield, only available with DevitoPRO. Defaults to no\n", - " compression in 2D and `bitcomp` in 3D.\n", + " compression in 2D and ``bitcomp`` in 3D.\n", + " save_interpolation : bool, optional\n", + " Whether to interpolate the saved wavefield using natural cubic splines (only\n", + " available in some versions of Stride). Defaults to False.\n", + " dump_forward_wavefield : bool or int, optional\n", + " If True or a positive integer, the forward wavefield will be dumped after running the\n", + " forward kernel. If True, the wavefield will be sampled every ``save_undersampling``\n", + " timesteps. If an integer, the wavefield will be sampled every ``dump_forward_wavefield``\n", + " timesteps. Defaults to False.\n", + " dump_adjoint_wavefield : bool or int, optional\n", + " If True or a positive integer, the adjoint wavefield will be dumped after running the\n", + " adjoint kernel. If True, the wavefield will be sampled every ``save_undersampling``\n", + " timesteps. If an integer, the wavefield will be sampled every ``dump_adjoint_wavefield``\n", + " timesteps. Defaults to False.\n", + " dump_wavefield_id : int, optional\n", + " ID of the shot to dump wavefields. If not provided, all IDs are dumped.\n", " boundary_type : str, optional\n", " Type of boundary for the wave equation (``sponge_boundary_2`` or\n", " ``complex_frequency_shift_PML_2``), defaults to ``sponge_boundary_2``.\n", @@ -1004,7 +1038,7 @@ " Type of source/receiver interpolation (``linear`` for bi-/tri-linear or ``hicks`` for sinc\n", " interpolation), defaults to ``linear``.\n", " attenuation_power : int, optional\n", - " Power of the attenuation law if attenuation is given (``0`` or ``2``),\n", + " Power of the attenuation law if attenuation is given (``0``, ``2``, or None),\n", " defaults to ``0``.\n", " drp : bool, optional\n", " Whether or not to use dispersion-relation preserving coefficients (only\n", @@ -1018,6 +1052,9 @@ " adaptive_boxes : bool, optional\n", " Whether to activate adaptive boxes (requires DevitoPRO and only\n", " available in some versions of Stride). Defaults to False.\n", + " local_prec : bool, optional\n", + " Whether to apply local preconditioning. Only available in some versions of Stride. Defaults to\n", + " True.\n", " platform : str, optional\n", " Platform on which to run the operator, ``None`` to run on the CPU or ``nvidia-acc`` to run on\n", " the GPU with OpenACC. Defaults to ``None``.\n", @@ -1060,7 +1097,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.13" + "version": "3.11.8" } }, "nbformat": 4, diff --git a/stride_examples/tutorials/04_parallelism.ipynb b/stride_examples/tutorials/04_parallelism.ipynb index 1237868..abde77b 100644 --- a/stride_examples/tutorials/04_parallelism.ipynb +++ b/stride_examples/tutorials/04_parallelism.ipynb @@ -91,13 +91,16 @@ "name": "stdout", "output_type": "stream", "text": [ - "Listening at HEAD Listening at \n", - "MONITOR Listening at \n" + "Listening at HEAD Listening at \n", + "MONITOR Listening at \n", + "WORKER:0:1 Solve 1\n", + "WORKER:0:1 Done 1\n", + "WORKER:0:0 Solve 2\n" ] } ], "source": [ - "await mosaic.interactive('on', num_workers=2)\n", + "await mosaic.interactive('on', num_workers=2, log_level='info')\n", "# to start the runtime with two workers" ] }, @@ -142,7 +145,7 @@ { "data": { "text/plain": [ - "<_TesseraProxy object at 140222347082096, uid=tess-solver1-d751011f2b874bde8ff5d5389c6daf95, runtime=None, state=pending>" + "<_TesseraProxy object at 140116268093456, uid=tess-solver1-25e63f16add546edb8b1245552224877, runtime=worker:0:1, state=listening>" ] }, "execution_count": 4, @@ -203,7 +206,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 6, @@ -235,31 +238,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "neither-capacity", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:1 Solve 2\n", - "WORKER:0:0 Solve 1\n", - "WORKER:0:1 Done 2\n", - "WORKER:0:0 Done 1\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# Wait until the remote tasks are finished\n", "await task_1\n", @@ -362,31 +344,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "japanese-strip", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:0 Solve 1\n", - "WORKER:0:0 Done 1\n", - "WORKER:0:1 Solve 2\n", - "WORKER:0:1 Done 2\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# Wait until the remote tasks are finished\n", "# Now we only need to wait for the second task\n", @@ -403,7 +364,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "persistent-green", "metadata": {}, "outputs": [], @@ -423,31 +384,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "employed-ceiling", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:0 Solve More 1\n", - "WORKER:0:0 Done More 1\n", - "WORKER:0:1 Solve More 2\n", - "WORKER:0:1 Done More 2\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# Wait until the remote tasks are finished\n", "# Now we only need to wait for the second task\n", @@ -468,21 +408,10 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "841c80f6", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "obj = dict(a=1, b=2)\n", "\n", @@ -504,21 +433,10 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "0dde4c8f", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'a': 1, 'b': 2}" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "await ref.value()\n", "\n", @@ -541,21 +459,10 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "e5729af1", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "await runtime.put(obj, publish=True)" ] @@ -570,7 +477,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "25ed0bab", "metadata": {}, "outputs": [], @@ -592,7 +499,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "id": "driven-contact", "metadata": {}, "outputs": [], @@ -643,7 +550,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.5" + "version": "3.11.8" } }, "nbformat": 4, diff --git a/stride_examples/tutorials/05_file_io.ipynb b/stride_examples/tutorials/05_file_io.ipynb index 2ba93b0..71cff6d 100644 --- a/stride_examples/tutorials/05_file_io.ipynb +++ b/stride_examples/tutorials/05_file_io.ipynb @@ -93,7 +93,7 @@ " or as a context manager,\n", "\n", " >>> with HDF5(...) as file:\n", - " >>> file.write(...)\n", + " >>> file.dump(...)\n", "\n", " If a particular version is given, the filename will be generated without checks. If no version is given,\n", " the ``path`` will be checked for the latest available version of the file.\n", @@ -164,995 +164,34 @@ "metadata": {}, "outputs": [ { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stderr", + "output_type": "stream", + "text": [ + "Qt: Session management error: None of the authentication protocols specified are supported\n", + "QApplication: invalid style override 'gtk' passed, ignoring it.\n", + "\tAvailable styles: Windows, Fusion\n" + ] }, { "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "52a0dd2598494cc5af477da40d824e6a", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", 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mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:0 (ShotID 0) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 2) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:1 (ShotID 1) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 4) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 2) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 3) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 4) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 5) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 6) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 6) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 7) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 8) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 8) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 10) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 9) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 10) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 3) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 11) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 11) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 13) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:1 (ShotID 12) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 14) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 13) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 16) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 15) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 16) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 17) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 17) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 18) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 19) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 19) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 21) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 20) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 12) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 22) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 21) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 23) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 24) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 24) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 25) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 26) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 26) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 27) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 28) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 28) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 30) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 29) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 22) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 31) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 30) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 32) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 33) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 33) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 34) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 35) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 35) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 36) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 37) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 31) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 37) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 38) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 39) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 41) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 40) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 41) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 42) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 42) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 44) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 43) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 44) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 39) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 45) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 45) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 47) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:1 (ShotID 46) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 47) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 48) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 49) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 49) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 51) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 50) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 51) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 52) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 46) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 52) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 53) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 54) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 56) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 55) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 56) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 57) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 57) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 58) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 59) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 59) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 60) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 61) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 54) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 61) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 62) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 63) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 64) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 65) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 65) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 66) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 67) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 67) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 69) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 68) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 69) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 70) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 70) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 71) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 72) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 72) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 73) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 63) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 74) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 74) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 76) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:1 (ShotID 75) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 76) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 77) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 78) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 78) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 79) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 80) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 80) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 82) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 81) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 75) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 83) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 82) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 84) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 85) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 85) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 86) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 87) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 87) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 89) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 88) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 89) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 90) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 83) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 90) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 91) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 92) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 93) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 94) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 94) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 95) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 96) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 96) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 97) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 98) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 98) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 99) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 100) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 92) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 100) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 101) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 102) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 103) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 104) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 104) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 106) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 105) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 106) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 107) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 107) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 108) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 109) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 109) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 110) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 111) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 102) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 111) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 113) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 112) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 114) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 114) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 115) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 116) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 116) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 117) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 118) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 118) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 (ShotID 119) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 113) Spatial grid spacing (0.500 mm | 3.973 PPW) is higher than dispersion limit (0.397 mm | 5.000 PPW)\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", "MONITOR Pending barrier tasks 1\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "MONITOR Pending barrier tasks 2\n", + "WORKER:0:1 (ShotID 24) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 10) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 44) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "MONITOR Pending barrier tasks 2\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 40) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 45) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 56) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 59) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 64) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 69) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 82) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 87) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 91) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 95) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 108) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 110) Spatial grid spacing (0.500 mm | 4.885 PPW) is higher than dispersion limit (0.489 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "MONITOR Pending barrier tasks 3\n", + "WORKER:0:0 (ShotID 14) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 21) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 26) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 29) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 31) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 35) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 34) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 49) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 65) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 66) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 73) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 77) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 78) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 81) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "MONITOR Pending barrier tasks 2\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 85) Spatial grid spacing (0.500 mm | 4.934 PPW) is higher than dispersion limit (0.493 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "MONITOR Pending barrier tasks 2\n", + "WORKER:0:0 (ShotID 3) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 4) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 17) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 23) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 28) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 51) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 58) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 70) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 71) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 80) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 83) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 104) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 96) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 106) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 109) Spatial grid spacing (0.500 mm | 4.745 PPW) is higher than dispersion limit (0.474 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "MONITOR Pending barrier tasks 2\n", + "WORKER:0:0 (ShotID 1) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 12) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 25) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 39) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 41) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 54) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 57) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 62) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 63) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 76) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 72) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "MONITOR Pending barrier tasks 2\n", - "WORKER:0:1 (ShotID 15) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 90) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 20) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 94) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 22) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 98) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 115) Spatial grid spacing (0.500 mm | 4.343 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 28) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "MONITOR Pending barrier tasks 2\n", + "WORKER:0:0 (ShotID 6) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 8) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 7) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 62) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 9) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 11) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 38) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 77) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 48) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 52) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 79) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 68) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 74) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 81) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 84) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 86) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 89) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 101) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 103) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 107) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 93) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "WORKER:0:1 (ShotID 119) Spatial grid spacing (0.500 mm | 4.299 PPW) is higher than dispersion limit (0.430 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 80) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 99) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", + "MONITOR Pending barrier tasks 1\n", + "WORKER:0:1 (ShotID 5) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 103) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 0) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 15) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 117) Spatial grid spacing (0.500 mm | 5.000 PPW) is higher than dispersion limit (0.500 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 46) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 50) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 55) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "MONITOR Pending barrier tasks 4\n", - "WORKER:0:1 (ShotID 3) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 88) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 89) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 6) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 92) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 93) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 9) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 99) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 112) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 111) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 31) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 113) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 114) Spatial grid spacing (0.500 mm | 4.345 PPW) is higher than dispersion limit (0.434 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 41) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "MONITOR Pending barrier tasks 2\n", + "WORKER:0:1 (ShotID 13) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 2) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 2) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 42) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 16) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 27) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 43) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 30) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 37) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 52) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 42) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 43) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 55) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 (ShotID 67) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 79) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 75) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 60) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 97) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 105) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 82) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", + "WORKER:0:0 (ShotID 116) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:0 AutoTuner: could not perform any runs\n", + "WORKER:0:1 (ShotID 118) Spatial grid spacing (0.500 mm | 4.285 PPW) is higher than dispersion limit (0.429 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 87) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 107) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 78) Spatial grid spacing (0.500 mm | 4.535 PPW) is higher than dispersion limit (0.454 mm | 5.000 PPW)\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "MONITOR Pending barrier tasks 2\n", - "WORKER:0:1 (ShotID 11) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 29) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 33) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 5) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 34) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 44) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 47) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 63) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 65) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 72) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 49) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 96) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 108) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 114) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 118) Spatial grid spacing (0.500 mm | 4.524 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "MONITOR Pending barrier tasks 2\n", - "WORKER:0:1 (ShotID 4) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 8) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 18) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 0) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 19) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 21) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 24) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 38) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 54) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 56) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 64) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 85) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 104) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 119) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 68) Spatial grid spacing (0.500 mm | 4.523 PPW) is higher than dispersion limit (0.452 mm | 5.000 PPW)\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "MONITOR Pending barrier tasks 2\n", - "WORKER:0:1 (ShotID 32) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 36) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 37) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 39) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 12) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 46) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 50) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 66) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 75) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 67) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 76) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 86) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 101) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 (ShotID 111) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 95) Spatial grid spacing (0.500 mm | 4.509 PPW) is higher than dispersion limit (0.451 mm | 5.000 PPW)\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "MONITOR Pending barrier tasks 2\n" + "MONITOR Pending barrier tasks 1\n" ] } ], @@ -644,7 +674,7 @@ "outputs": [], "source": [ "from stride import Space, Time, Grid\n", - "%matplotlib widget\n", + "%matplotlib ipympl\n", "\n", "space = Space(shape=(356, 385), extra=(50, 50), absorbing=(40, 40), spacing=0.5e-3)\n", "time = Time(start=0.0e-6, step=0.08e-6, num=2500)\n", @@ -765,10 +795,19 @@ "id": "handled-economy", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Qt: Session management error: None of the authentication protocols specified are supported\n", + "QApplication: invalid style override 'gtk' passed, ignoring it.\n", + "\tAvailable styles: Windows, Fusion\n" + ] + }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4ed71cc916cf46259748b90c44047f8b", + "model_id": "eaf0389a12104379b0ae62539af4dc5b", "version_major": 2, "version_minor": 0 }, @@ -793,7 +832,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5689f7df49a3497fb8b23a98a38a9d38", + "model_id": "3682114e7fc24a0989285650c9a1016a", "version_major": 2, "version_minor": 0 }, @@ -869,381 +908,381 @@ "text": [ "HEAD Giving shot 0 to worker:0:0\n", "HEAD Giving shot 1 to worker:0:1\n", - "HEAD Shot 1 retrieved\n", - "HEAD Retrieved traces for shot 1\n", - "HEAD Giving shot 2 to worker:0:1\n", "HEAD Shot 0 retrieved\n", "HEAD Retrieved traces for shot 0\n", - "HEAD Giving shot 3 to worker:0:0\n", + "HEAD Shot 1 retrieved\n", + "HEAD Retrieved traces for shot 1\n", + "HEAD Giving shot 2 to worker:0:0\n", + "HEAD Giving shot 3 to worker:0:1\n", "HEAD Shot 2 retrieved\n", "HEAD Retrieved traces for shot 2\n", - "HEAD Giving shot 4 to worker:0:1\n", + "HEAD Giving shot 4 to worker:0:0\n", + "HEAD Shot 3 retrieved\n", + "HEAD Retrieved traces for shot 3\n", + "HEAD Giving shot 5 to worker:0:1\n", "HEAD Shot 4 retrieved\n", "HEAD Retrieved traces for shot 4\n", - "HEAD Giving shot 5 to worker:0:1\n", + "HEAD Giving shot 6 to worker:0:0\n", "HEAD Shot 5 retrieved\n", "HEAD Retrieved traces for shot 5\n", - "HEAD Giving shot 6 to worker:0:1\n", + "HEAD Giving shot 7 to worker:0:1\n", "HEAD Shot 6 retrieved\n", "HEAD Retrieved traces for shot 6\n", - "HEAD Giving shot 7 to worker:0:1\n", + "HEAD Giving shot 8 to worker:0:0\n", "HEAD Shot 7 retrieved\n", "HEAD Retrieved traces for shot 7\n", - "HEAD Giving shot 8 to worker:0:1\n", + "HEAD Giving shot 9 to worker:0:1\n", "HEAD Shot 8 retrieved\n", "HEAD Retrieved traces for shot 8\n", - "HEAD Giving shot 9 to worker:0:1\n", - "HEAD Shot 9 retrieved\n", - "HEAD Retrieved traces for shot 9\n", - "HEAD Giving shot 10 to worker:0:1\n", + "HEAD Giving shot 10 to worker:0:0\n", "HEAD Shot 10 retrieved\n", "HEAD Retrieved traces for shot 10\n", - "HEAD Giving shot 11 to worker:0:1\n", - "HEAD Shot 3 retrieved\n", - "HEAD Retrieved traces for shot 3\n", - "HEAD Giving shot 12 to worker:0:0\n", + "HEAD Giving shot 11 to worker:0:0\n", + "HEAD Shot 9 retrieved\n", + "HEAD Retrieved traces for shot 9\n", + "HEAD Giving shot 12 to worker:0:1\n", "HEAD Shot 11 retrieved\n", "HEAD Retrieved traces for shot 11\n", - "HEAD Giving shot 13 to worker:0:1\n", - "HEAD Shot 13 retrieved\n", - "HEAD Retrieved traces for shot 13\n", + "HEAD Giving shot 13 to worker:0:0\n", + "HEAD Shot 12 retrieved\n", + "HEAD Retrieved traces for shot 12\n", "HEAD Giving shot 14 to worker:0:1\n", "HEAD Shot 14 retrieved\n", "HEAD Retrieved traces for shot 14\n", "HEAD Giving shot 15 to worker:0:1\n", - "HEAD Shot 15 retrieved\n", - "HEAD Retrieved traces for shot 15\n", - "HEAD Giving shot 16 to worker:0:1\n", + "HEAD Shot 13 retrieved\n", + "HEAD Retrieved traces for shot 13\n", + "HEAD Giving shot 16 to worker:0:0\n", "HEAD Shot 16 retrieved\n", "HEAD Retrieved traces for shot 16\n", - "HEAD Giving shot 17 to worker:0:1\n", + "HEAD Giving shot 17 to worker:0:0\n", + "HEAD Shot 15 retrieved\n", + "HEAD Retrieved traces for shot 15\n", + "HEAD Giving shot 18 to worker:0:1\n", "HEAD Shot 17 retrieved\n", "HEAD Retrieved traces for shot 17\n", - "HEAD Giving shot 18 to worker:0:1\n", + "HEAD Giving shot 19 to worker:0:0\n", "HEAD Shot 18 retrieved\n", "HEAD Retrieved traces for shot 18\n", - "HEAD Giving shot 19 to worker:0:1\n", + "HEAD Giving shot 20 to worker:0:1\n", "HEAD Shot 19 retrieved\n", "HEAD Retrieved traces for shot 19\n", - "HEAD Giving shot 20 to worker:0:1\n", - "HEAD Shot 20 retrieved\n", - "HEAD Retrieved traces for shot 20\n", - "HEAD Giving shot 21 to worker:0:1\n", - "HEAD Shot 12 retrieved\n", - "HEAD Retrieved traces for shot 12\n", - "HEAD Giving shot 22 to worker:0:0\n", + "HEAD Giving shot 21 to worker:0:0\n", "HEAD Shot 21 retrieved\n", "HEAD Retrieved traces for shot 21\n", + "HEAD Giving shot 22 to worker:0:0\n", + "HEAD Shot 20 retrieved\n", + "HEAD Retrieved traces for shot 20\n", "HEAD Giving shot 23 to worker:0:1\n", + "HEAD Shot 22 retrieved\n", + "HEAD Retrieved traces for shot 22\n", + "HEAD Giving shot 24 to worker:0:0\n", "HEAD Shot 23 retrieved\n", "HEAD Retrieved traces for shot 23\n", - "HEAD Giving shot 24 to worker:0:1\n", + "HEAD Giving shot 25 to worker:0:1\n", "HEAD Shot 24 retrieved\n", "HEAD Retrieved traces for shot 24\n", - "HEAD Giving shot 25 to worker:0:1\n", + "HEAD Giving shot 26 to worker:0:0\n", "HEAD Shot 25 retrieved\n", "HEAD Retrieved traces for shot 25\n", - "HEAD Giving shot 26 to worker:0:1\n", + "HEAD Giving shot 27 to worker:0:1\n", "HEAD Shot 26 retrieved\n", "HEAD Retrieved traces for shot 26\n", - "HEAD Giving shot 27 to worker:0:1\n", + "HEAD Giving shot 28 to worker:0:0\n", "HEAD Shot 27 retrieved\n", "HEAD Retrieved traces for shot 27\n", - "HEAD Giving shot 28 to worker:0:1\n", + "HEAD Giving shot 29 to worker:0:1\n", "HEAD Shot 28 retrieved\n", "HEAD Retrieved traces for shot 28\n", - "HEAD Giving shot 29 to worker:0:1\n", - "HEAD Shot 29 retrieved\n", - "HEAD Retrieved traces for shot 29\n", - "HEAD Giving shot 30 to worker:0:1\n", - "HEAD Shot 22 retrieved\n", - "HEAD Retrieved traces for shot 22\n", - "HEAD Giving shot 31 to worker:0:0\n", + "HEAD Giving shot 30 to worker:0:0\n", "HEAD Shot 30 retrieved\n", "HEAD Retrieved traces for shot 30\n", + "HEAD Giving shot 31 to worker:0:0\n", + "HEAD Shot 29 retrieved\n", + "HEAD Retrieved traces for shot 29\n", "HEAD Giving shot 32 to worker:0:1\n", + "HEAD Shot 31 retrieved\n", + "HEAD Retrieved traces for shot 31\n", + "HEAD Giving shot 33 to worker:0:0\n", "HEAD Shot 32 retrieved\n", "HEAD Retrieved traces for shot 32\n", - "HEAD Giving shot 33 to worker:0:1\n", + "HEAD Giving shot 34 to worker:0:1\n", "HEAD Shot 33 retrieved\n", "HEAD Retrieved traces for shot 33\n", - "HEAD Giving shot 34 to worker:0:1\n", + "HEAD Giving shot 35 to worker:0:0\n", "HEAD Shot 34 retrieved\n", "HEAD Retrieved traces for shot 34\n", - "HEAD Giving shot 35 to worker:0:1\n", + "HEAD Giving shot 36 to worker:0:1\n", "HEAD Shot 35 retrieved\n", "HEAD Retrieved traces for shot 35\n", - "HEAD Giving shot 36 to worker:0:1\n", + "HEAD Giving shot 37 to worker:0:0\n", "HEAD Shot 36 retrieved\n", "HEAD Retrieved traces for shot 36\n", - "HEAD Giving shot 37 to worker:0:1\n", + "HEAD Giving shot 38 to worker:0:1\n", "HEAD Shot 37 retrieved\n", "HEAD Retrieved traces for shot 37\n", - "HEAD Giving shot 38 to worker:0:1\n", - "HEAD Shot 31 retrieved\n", - "HEAD Retrieved traces for shot 31\n", "HEAD Giving shot 39 to worker:0:0\n", "HEAD Shot 38 retrieved\n", "HEAD Retrieved traces for shot 38\n", "HEAD Giving shot 40 to worker:0:1\n", - "HEAD Shot 40 retrieved\n", - "HEAD Retrieved traces for shot 40\n", - "HEAD Giving shot 41 to worker:0:1\n", + "HEAD Shot 39 retrieved\n", + "HEAD Retrieved traces for shot 39\n", + "HEAD Giving shot 41 to worker:0:0\n", "HEAD Shot 41 retrieved\n", "HEAD Retrieved traces for shot 41\n", - "HEAD Giving shot 42 to worker:0:1\n", + "HEAD Giving shot 42 to worker:0:0\n", + "HEAD Shot 40 retrieved\n", + "HEAD Retrieved traces for shot 40\n", + "HEAD Giving shot 43 to worker:0:1\n", "HEAD Shot 42 retrieved\n", "HEAD Retrieved traces for shot 42\n", - "HEAD Giving shot 43 to worker:0:1\n", - "HEAD Shot 43 retrieved\n", - "HEAD Retrieved traces for shot 43\n", - "HEAD Giving shot 44 to worker:0:1\n", + "HEAD Giving shot 44 to worker:0:0\n", "HEAD Shot 44 retrieved\n", "HEAD Retrieved traces for shot 44\n", - "HEAD Giving shot 45 to worker:0:1\n", - "HEAD Shot 39 retrieved\n", - "HEAD Retrieved traces for shot 39\n", - "HEAD Giving shot 46 to worker:0:0\n", + "HEAD Giving shot 45 to worker:0:0\n", + "HEAD Shot 43 retrieved\n", + "HEAD Retrieved traces for shot 43\n", + "HEAD Giving shot 46 to worker:0:1\n", "HEAD Shot 45 retrieved\n", "HEAD Retrieved traces for shot 45\n", - "HEAD Giving shot 47 to worker:0:1\n", + "HEAD Giving shot 47 to worker:0:0\n", + "HEAD Shot 46 retrieved\n", + "HEAD Retrieved traces for shot 46\n", + "HEAD Giving shot 48 to worker:0:1\n", "HEAD Shot 47 retrieved\n", "HEAD Retrieved traces for shot 47\n", - "HEAD Giving shot 48 to worker:0:1\n", + "HEAD Giving shot 49 to worker:0:0\n", "HEAD Shot 48 retrieved\n", "HEAD Retrieved traces for shot 48\n", - "HEAD Giving shot 49 to worker:0:1\n", + "HEAD Giving shot 50 to worker:0:1\n", "HEAD Shot 49 retrieved\n", "HEAD Retrieved traces for shot 49\n", - "HEAD Giving shot 50 to worker:0:1\n", - "HEAD Shot 50 retrieved\n", - "HEAD Retrieved traces for shot 50\n", - "HEAD Giving shot 51 to worker:0:1\n", + "HEAD Giving shot 51 to worker:0:0\n", "HEAD Shot 51 retrieved\n", "HEAD Retrieved traces for shot 51\n", - "HEAD Giving shot 52 to worker:0:1\n", + "HEAD Giving shot 52 to worker:0:0\n", + "HEAD Shot 50 retrieved\n", + "HEAD Retrieved traces for shot 50\n", + "HEAD Giving shot 53 to worker:0:1\n", "HEAD Shot 52 retrieved\n", "HEAD Retrieved traces for shot 52\n", - "HEAD Giving shot 53 to worker:0:1\n", - "HEAD Shot 46 retrieved\n", - "HEAD Retrieved traces for shot 46\n", "HEAD Giving shot 54 to worker:0:0\n", "HEAD Shot 53 retrieved\n", "HEAD Retrieved traces for shot 53\n", "HEAD Giving shot 55 to worker:0:1\n", - "HEAD Shot 55 retrieved\n", - "HEAD Retrieved traces for shot 55\n", - "HEAD Giving shot 56 to worker:0:1\n", + "HEAD Shot 54 retrieved\n", + "HEAD Retrieved traces for shot 54\n", + "HEAD Giving shot 56 to worker:0:0\n", "HEAD Shot 56 retrieved\n", "HEAD Retrieved traces for shot 56\n", - "HEAD Giving shot 57 to worker:0:1\n", + "HEAD Giving shot 57 to worker:0:0\n", + "HEAD Shot 55 retrieved\n", + "HEAD Retrieved traces for shot 55\n", + "HEAD Giving shot 58 to worker:0:1\n", "HEAD Shot 57 retrieved\n", "HEAD Retrieved traces for shot 57\n", - "HEAD Giving shot 58 to worker:0:1\n", + "HEAD Giving shot 59 to worker:0:0\n", "HEAD Shot 58 retrieved\n", "HEAD Retrieved traces for shot 58\n", - "HEAD Giving shot 59 to worker:0:1\n", + "HEAD Giving shot 60 to worker:0:1\n", "HEAD Shot 59 retrieved\n", "HEAD Retrieved traces for shot 59\n", - "HEAD Giving shot 60 to worker:0:1\n", + "HEAD Giving shot 61 to worker:0:0\n", "HEAD Shot 60 retrieved\n", "HEAD Retrieved traces for shot 60\n", - "HEAD Giving shot 61 to worker:0:1\n", + "HEAD Giving shot 62 to worker:0:1\n", "HEAD Shot 61 retrieved\n", "HEAD Retrieved traces for shot 61\n", - "HEAD Giving shot 62 to worker:0:1\n", - "HEAD Shot 54 retrieved\n", - "HEAD Retrieved traces for shot 54\n", "HEAD Giving shot 63 to worker:0:0\n", "HEAD Shot 62 retrieved\n", "HEAD Retrieved traces for shot 62\n", "HEAD Giving shot 64 to worker:0:1\n", + "HEAD Shot 63 retrieved\n", + "HEAD Retrieved traces for shot 63\n", + "HEAD Giving shot 65 to worker:0:0\n", "HEAD Shot 64 retrieved\n", "HEAD Retrieved traces for shot 64\n", - "HEAD Giving shot 65 to worker:0:1\n", + "HEAD Giving shot 66 to worker:0:1\n", "HEAD Shot 65 retrieved\n", "HEAD Retrieved traces for shot 65\n", - "HEAD Giving shot 66 to worker:0:1\n", + "HEAD Giving shot 67 to worker:0:0\n", "HEAD Shot 66 retrieved\n", "HEAD Retrieved traces for shot 66\n", - "HEAD Giving shot 67 to worker:0:1\n", + "HEAD Giving shot 68 to worker:0:1\n", "HEAD Shot 67 retrieved\n", "HEAD Retrieved traces for shot 67\n", - "HEAD Giving shot 68 to worker:0:1\n", - "HEAD Shot 68 retrieved\n", - "HEAD Retrieved traces for shot 68\n", - "HEAD Giving shot 69 to worker:0:1\n", + "HEAD Giving shot 69 to worker:0:0\n", "HEAD Shot 69 retrieved\n", "HEAD Retrieved traces for shot 69\n", - "HEAD Giving shot 70 to worker:0:1\n", + "HEAD Giving shot 70 to worker:0:0\n", + "HEAD Shot 68 retrieved\n", + "HEAD Retrieved traces for shot 68\n", + "HEAD Giving shot 71 to worker:0:1\n", "HEAD Shot 70 retrieved\n", "HEAD Retrieved traces for shot 70\n", - "HEAD Giving shot 71 to worker:0:1\n", + "HEAD Giving shot 72 to worker:0:0\n", "HEAD Shot 71 retrieved\n", "HEAD Retrieved traces for shot 71\n", - "HEAD Giving shot 72 to worker:0:1\n", + "HEAD Giving shot 73 to worker:0:1\n", "HEAD Shot 72 retrieved\n", "HEAD Retrieved traces for shot 72\n", - "HEAD Giving shot 73 to worker:0:1\n", + "HEAD Giving shot 74 to worker:0:0\n", "HEAD Shot 73 retrieved\n", "HEAD Retrieved traces for shot 73\n", - "HEAD Giving shot 74 to worker:0:1\n", - "HEAD Shot 63 retrieved\n", - "HEAD Retrieved traces for shot 63\n", - "HEAD Giving shot 75 to worker:0:0\n", + "HEAD Giving shot 75 to worker:0:1\n", "HEAD Shot 74 retrieved\n", "HEAD Retrieved traces for shot 74\n", - "HEAD Giving shot 76 to worker:0:1\n", + "HEAD Giving shot 76 to worker:0:0\n", + "HEAD Shot 75 retrieved\n", + "HEAD Retrieved traces for shot 75\n", + "HEAD Giving shot 77 to worker:0:1\n", "HEAD Shot 76 retrieved\n", "HEAD Retrieved traces for shot 76\n", - "HEAD Giving shot 77 to worker:0:1\n", + "HEAD Giving shot 78 to worker:0:0\n", "HEAD Shot 77 retrieved\n", "HEAD Retrieved traces for shot 77\n", - "HEAD Giving shot 78 to worker:0:1\n", + "HEAD Giving shot 79 to worker:0:1\n", "HEAD Shot 78 retrieved\n", "HEAD Retrieved traces for shot 78\n", - "HEAD Giving shot 79 to worker:0:1\n", + "HEAD Giving shot 80 to worker:0:0\n", "HEAD Shot 79 retrieved\n", "HEAD Retrieved traces for shot 79\n", - "HEAD Giving shot 80 to worker:0:1\n", + "HEAD Giving shot 81 to worker:0:1\n", "HEAD Shot 80 retrieved\n", "HEAD Retrieved traces for shot 80\n", - "HEAD Giving shot 81 to worker:0:1\n", - "HEAD Shot 81 retrieved\n", - "HEAD Retrieved traces for shot 81\n", - "HEAD Giving shot 82 to worker:0:1\n", - "HEAD Shot 75 retrieved\n", - "HEAD Retrieved traces for shot 75\n", - "HEAD Giving shot 83 to worker:0:0\n", + "HEAD Giving shot 82 to worker:0:0\n", "HEAD Shot 82 retrieved\n", "HEAD Retrieved traces for shot 82\n", + "HEAD Giving shot 83 to worker:0:0\n", + "HEAD Shot 81 retrieved\n", + "HEAD Retrieved traces for shot 81\n", "HEAD Giving shot 84 to worker:0:1\n", + "HEAD Shot 83 retrieved\n", + "HEAD Retrieved traces for shot 83\n", + "HEAD Giving shot 85 to worker:0:0\n", "HEAD Shot 84 retrieved\n", "HEAD Retrieved traces for shot 84\n", - "HEAD Giving shot 85 to worker:0:1\n", + "HEAD Giving shot 86 to worker:0:1\n", "HEAD Shot 85 retrieved\n", "HEAD Retrieved traces for shot 85\n", - "HEAD Giving shot 86 to worker:0:1\n", + "HEAD Giving shot 87 to worker:0:0\n", "HEAD Shot 86 retrieved\n", "HEAD Retrieved traces for shot 86\n", - "HEAD Giving shot 87 to worker:0:1\n", + "HEAD Giving shot 88 to worker:0:1\n", "HEAD Shot 87 retrieved\n", "HEAD Retrieved traces for shot 87\n", - "HEAD Giving shot 88 to worker:0:1\n", - "HEAD Shot 88 retrieved\n", - "HEAD Retrieved traces for shot 88\n", - "HEAD Giving shot 89 to worker:0:1\n", + "HEAD Giving shot 89 to worker:0:0\n", "HEAD Shot 89 retrieved\n", "HEAD Retrieved traces for shot 89\n", - "HEAD Giving shot 90 to worker:0:1\n", + "HEAD Giving shot 90 to worker:0:0\n", + "HEAD Shot 88 retrieved\n", + "HEAD Retrieved traces for shot 88\n", + "HEAD Giving shot 91 to worker:0:1\n", "HEAD Shot 90 retrieved\n", "HEAD Retrieved traces for shot 90\n", - "HEAD Giving shot 91 to worker:0:1\n", - "HEAD Shot 83 retrieved\n", - "HEAD Retrieved traces for shot 83\n", "HEAD Giving shot 92 to worker:0:0\n", "HEAD Shot 91 retrieved\n", "HEAD Retrieved traces for shot 91\n", "HEAD Giving shot 93 to worker:0:1\n", + "HEAD Shot 92 retrieved\n", + "HEAD Retrieved traces for shot 92\n", + "HEAD Giving shot 94 to worker:0:0\n", "HEAD Shot 93 retrieved\n", "HEAD Retrieved traces for shot 93\n", - "HEAD Giving shot 94 to worker:0:1\n", + "HEAD Giving shot 95 to worker:0:1\n", "HEAD Shot 94 retrieved\n", "HEAD Retrieved traces for shot 94\n", - "HEAD Giving shot 95 to worker:0:1\n", + "HEAD Giving shot 96 to worker:0:0\n", "HEAD Shot 95 retrieved\n", "HEAD Retrieved traces for shot 95\n", - "HEAD Giving shot 96 to worker:0:1\n", + "HEAD Giving shot 97 to worker:0:1\n", "HEAD Shot 96 retrieved\n", "HEAD Retrieved traces for shot 96\n", - "HEAD Giving shot 97 to worker:0:1\n", + "HEAD Giving shot 98 to worker:0:0\n", "HEAD Shot 97 retrieved\n", "HEAD Retrieved traces for shot 97\n", - "HEAD Giving shot 98 to worker:0:1\n", + "HEAD Giving shot 99 to worker:0:1\n", "HEAD Shot 98 retrieved\n", "HEAD Retrieved traces for shot 98\n", - "HEAD Giving shot 99 to worker:0:1\n", + "HEAD Giving shot 100 to worker:0:0\n", "HEAD Shot 99 retrieved\n", "HEAD Retrieved traces for shot 99\n", - "HEAD Giving shot 100 to worker:0:1\n", + "HEAD Giving shot 101 to worker:0:1\n", "HEAD Shot 100 retrieved\n", "HEAD Retrieved traces for shot 100\n", - "HEAD Giving shot 101 to worker:0:1\n", - "HEAD Shot 92 retrieved\n", - "HEAD Retrieved traces for shot 92\n", "HEAD Giving shot 102 to worker:0:0\n", "HEAD Shot 101 retrieved\n", "HEAD Retrieved traces for shot 101\n", "HEAD Giving shot 103 to worker:0:1\n", + "HEAD Shot 102 retrieved\n", + "HEAD Retrieved traces for shot 102\n", + "HEAD Giving shot 104 to worker:0:0\n", "HEAD Shot 103 retrieved\n", "HEAD Retrieved traces for shot 103\n", - "HEAD Giving shot 104 to worker:0:1\n", + "HEAD Giving shot 105 to worker:0:1\n", "HEAD Shot 104 retrieved\n", "HEAD Retrieved traces for shot 104\n", - "HEAD Giving shot 105 to worker:0:1\n", - "HEAD Shot 105 retrieved\n", - "HEAD Retrieved traces for shot 105\n", - "HEAD Giving shot 106 to worker:0:1\n", + "HEAD Giving shot 106 to worker:0:0\n", "HEAD Shot 106 retrieved\n", "HEAD Retrieved traces for shot 106\n", - "HEAD Giving shot 107 to worker:0:1\n", + "HEAD Giving shot 107 to worker:0:0\n", + "HEAD Shot 105 retrieved\n", + "HEAD Retrieved traces for shot 105\n", + "HEAD Giving shot 108 to worker:0:1\n", "HEAD Shot 107 retrieved\n", "HEAD Retrieved traces for shot 107\n", - "HEAD Giving shot 108 to worker:0:1\n", + "HEAD Giving shot 109 to worker:0:0\n", "HEAD Shot 108 retrieved\n", "HEAD Retrieved traces for shot 108\n", - "HEAD Giving shot 109 to worker:0:1\n", + "HEAD Giving shot 110 to worker:0:1\n", "HEAD Shot 109 retrieved\n", "HEAD Retrieved traces for shot 109\n", - "HEAD Giving shot 110 to worker:0:1\n", + "HEAD Giving shot 111 to worker:0:0\n", "HEAD Shot 110 retrieved\n", "HEAD Retrieved traces for shot 110\n", - "HEAD Giving shot 111 to worker:0:1\n", + "HEAD Giving shot 112 to worker:0:1\n", "HEAD Shot 111 retrieved\n", "HEAD Retrieved traces for shot 111\n", - "HEAD Giving shot 112 to worker:0:1\n", - "HEAD Shot 102 retrieved\n", - "HEAD Retrieved traces for shot 102\n", "HEAD Giving shot 113 to worker:0:0\n", + "HEAD Shot 113 retrieved\n", + "HEAD Retrieved traces for shot 113\n", + "HEAD Giving shot 114 to worker:0:0\n", "HEAD Shot 112 retrieved\n", "HEAD Retrieved traces for shot 112\n", - "HEAD Giving shot 114 to worker:0:1\n", + "HEAD Giving shot 115 to worker:0:1\n", "HEAD Shot 114 retrieved\n", "HEAD Retrieved traces for shot 114\n", - "HEAD Giving shot 115 to worker:0:1\n", + "HEAD Giving shot 116 to worker:0:0\n", "HEAD Shot 115 retrieved\n", "HEAD Retrieved traces for shot 115\n", - "HEAD Giving shot 116 to worker:0:1\n", + "HEAD Giving shot 117 to worker:0:1\n", "HEAD Shot 116 retrieved\n", "HEAD Retrieved traces for shot 116\n", - "HEAD Giving shot 117 to worker:0:1\n", + "HEAD Giving shot 118 to worker:0:0\n", "HEAD Shot 117 retrieved\n", "HEAD Retrieved traces for shot 117\n", - "HEAD Giving shot 118 to worker:0:1\n", + "HEAD Giving shot 119 to worker:0:1\n", "HEAD Shot 118 retrieved\n", "HEAD Retrieved traces for shot 118\n", - "HEAD Giving shot 119 to worker:0:1\n", "HEAD Shot 119 retrieved\n", - "HEAD Retrieved traces for shot 119\n", - "HEAD Shot 113 retrieved\n", - "HEAD Retrieved traces for shot 113\n" + "HEAD Retrieved traces for shot 119\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "05067a3d39d740728d1f61196aa716e5", + "model_id": "5dfc94021fa041da82674509faa245ca", "version_major": 2, "version_minor": 0 }, - "image/png": 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", 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18\n", + "HEAD Retrieved gradient for shot 7\n", + "HEAD Giving shot 19 to worker:0:0\n", + "HEAD Retrieved gradient for shot 18\n", + "HEAD Giving shot 20 to worker:0:1\n", + "HEAD Functional value for shot 19: loss 1.845396e+00 for shot 19\n", + "HEAD Functional value for shot 20: loss 2.047032e+00 for shot 20\n", + "HEAD Retrieved gradient for shot 19\n", + "HEAD Giving shot 22 to worker:0:0\n", + "HEAD Retrieved gradient for shot 20\n", + "HEAD Giving shot 32 to worker:0:1\n", + "HEAD Functional value for shot 22: loss 2.476382e+00 for shot 22\n", + "HEAD Functional value for shot 32: loss 2.640929e+00 for shot 32\n", + "HEAD Retrieved gradient for shot 22\n", + "HEAD Giving shot 33 to worker:0:0\n", + "HEAD Retrieved gradient for shot 32\n", + "HEAD Giving shot 36 to worker:0:1\n", + "HEAD Functional value for shot 33: loss 2.379189e+00 for shot 33\n", + "HEAD Retrieved gradient for shot 33\n", + "HEAD Giving shot 47 to worker:0:0\n", + "HEAD Functional value for shot 36: loss 2.357563e+00 for shot 36\n", + "HEAD Functional value for shot 47: loss 1.396611e+00 for shot 47\n", + "HEAD Retrieved gradient for shot 36\n", + "HEAD Giving shot 53 to worker:0:1\n", + "HEAD Retrieved gradient for shot 47\n", + "HEAD Giving shot 60 to worker:0:0\n", + "HEAD Functional value for shot 60: loss 9.697318e-01 for shot 60\n", + "HEAD Functional value for shot 53: loss 1.332564e+00 for shot 53\n", + "HEAD Retrieved gradient for shot 60\n", + "HEAD Giving shot 61 to worker:0:0\n", + "HEAD Retrieved gradient for shot 53\n", + "HEAD Giving shot 100 to worker:0:1\n", + "HEAD Functional value for shot 61: loss 1.375144e+00 for shot 61\n", + "HEAD Functional value for shot 100: loss 1.520611e+00 for shot 100\n", + "HEAD Retrieved gradient for shot 61\n", + "HEAD Giving shot 102 to worker:0:0\n", + "HEAD Retrieved gradient for shot 100\n", + "HEAD Giving shot 117 to worker:0:1\n", + "HEAD Functional value for shot 102: loss 1.345103e+00 for shot 102\n", + "HEAD Retrieved gradient for shot 102\n", + "HEAD Functional value for shot 117: loss 1.174481e+00 for shot 117\n", + "HEAD Retrieved gradient for shot 117\n", + "HEAD Done iteration 1 (out of 4), block 1 (out of 2) - Total loss_freq 2.626820e+01\n", + "HEAD ====================================================================\n", + "HEAD Starting iteration 2 (out of 4), block 1 (out of 2)\n", + "HEAD Giving shot 10 to worker:0:0\n", + "HEAD Giving shot 24 to worker:0:1\n", + "HEAD Functional value for shot 24: loss 6.506002e+00 for shot 24\n", + "HEAD Functional value for shot 10: loss 6.268174e+00 for shot 10\n", + "HEAD Retrieved gradient for shot 24\n", "HEAD Giving shot 40 to worker:0:1\n", - "HEAD Functional value for shot 40: loss 1.678519e+00 for shot 40\n", + "HEAD Retrieved gradient for shot 10\n", + "HEAD Giving shot 44 to worker:0:0\n", + "HEAD Functional value for shot 44: loss 5.412094e+00 for shot 44\n", + "HEAD Functional value for shot 40: loss 4.766835e+00 for shot 40\n", + "HEAD Retrieved gradient for shot 44\n", + "HEAD Giving shot 45 to worker:0:0\n", "HEAD Retrieved gradient for shot 40\n", - "HEAD Giving shot 45 to worker:0:1\n", - "HEAD Functional value for shot 45: loss 1.577361e+00 for shot 45\n", + "HEAD Giving shot 56 to worker:0:1\n", + "HEAD Functional value for shot 45: loss 6.761315e+00 for shot 45\n", + "HEAD Functional value for shot 56: loss 6.466547e+00 for shot 56\n", "HEAD Retrieved gradient for shot 45\n", - "HEAD Giving shot 61 to worker:0:1\n", - "HEAD Functional value for shot 61: loss 1.375144e+00 for shot 61\n", - "HEAD Retrieved gradient for shot 61\n", - "HEAD Giving shot 69 to worker:0:1\n", - "HEAD Retrieved gradient for shot 16\n", - "HEAD Giving shot 70 to worker:0:0\n", - "HEAD Functional value for shot 69: loss 1.638430e+00 for shot 69\n", + "HEAD Giving shot 59 to worker:0:0\n", + "HEAD Retrieved gradient for shot 56\n", + "HEAD Giving shot 64 to worker:0:1\n", + "HEAD Functional value for shot 59: loss 6.411827e+00 for shot 59\n", + "HEAD Retrieved gradient for shot 59\n", + "HEAD Giving shot 69 to worker:0:0\n", + "HEAD Functional value for shot 64: loss 6.418069e+00 for shot 64\n", + "HEAD Functional value for shot 69: loss 7.742792e+00 for shot 69\n", + "HEAD Retrieved gradient for shot 64\n", + "HEAD Giving shot 82 to worker:0:1\n", "HEAD Retrieved gradient for shot 69\n", - "HEAD Giving shot 71 to worker:0:1\n", - "HEAD Functional value for shot 71: loss 1.660910e+00 for shot 71\n", - "HEAD Retrieved gradient for shot 71\n", - "HEAD Giving shot 73 to worker:0:1\n", - "HEAD Functional value for shot 73: loss 1.770017e+00 for shot 73\n", - "HEAD Retrieved gradient for shot 73\n", - "HEAD Giving shot 83 to worker:0:1\n", - "HEAD Functional value for shot 70: loss 1.657740e+00 for shot 70\n", - "HEAD Functional value for shot 83: loss 2.230196e+00 for shot 83\n", - "HEAD Retrieved gradient for shot 83\n", - "HEAD Giving shot 90 to worker:0:1\n", - "HEAD Functional value for shot 90: loss 1.995775e+00 for shot 90\n", - "HEAD Retrieved gradient for shot 90\n", + "HEAD Giving shot 87 to worker:0:0\n", + "HEAD Functional value for shot 82: loss 9.763827e+00 for shot 82\n", + "HEAD Functional value for shot 87: loss 9.227037e+00 for shot 87\n", + "HEAD Retrieved gradient for shot 82\n", "HEAD Giving shot 91 to worker:0:1\n", - "HEAD Functional value for shot 91: loss 1.725538e+00 for shot 91\n", + "HEAD Retrieved gradient for shot 87\n", + "HEAD Giving shot 95 to worker:0:0\n", + "HEAD Functional value for shot 91: loss 8.896646e+00 for shot 91\n", + "HEAD Functional value for shot 95: loss 1.052438e+01 for shot 95\n", "HEAD Retrieved gradient for shot 91\n", - "HEAD Giving shot 102 to worker:0:1\n", - "HEAD Functional value for shot 102: loss 1.345104e+00 for shot 102\n", - "HEAD Retrieved gradient for shot 70\n", - "HEAD Giving shot 113 to worker:0:0\n", - "HEAD Retrieved gradient for shot 102\n", - "HEAD Functional value for shot 113: loss 1.522479e+00 for shot 113\n", - "HEAD Retrieved gradient for shot 113\n", - "HEAD Done iteration 1 (out of 4), block 1 (out of 2) - Total loss_freq 2.631405e+01\n", + "HEAD Giving shot 108 to worker:0:1\n", + "HEAD Retrieved gradient for shot 95\n", + "HEAD Giving shot 110 to worker:0:0\n", + "HEAD Functional value for shot 108: loss 7.482195e+00 for shot 108\n", + "HEAD Functional value for shot 110: loss 8.642723e+00 for shot 110\n", + "HEAD Retrieved gradient for shot 110\n", + "HEAD Retrieved gradient for shot 108\n", + "HEAD Done iteration 2 (out of 4), block 1 (out of 2) - Total loss_freq 1.112905e+02\n", "HEAD ====================================================================\n", - "HEAD Starting iteration 2 (out of 4), block 1 (out of 2)\n", - "HEAD Giving shot 13 to worker:0:0\n", - "HEAD Giving shot 14 to worker:0:1\n", - "HEAD Functional value for shot 14: loss 1.302665e+00 for shot 14\n", + "HEAD Starting iteration 3 (out of 4), block 1 (out of 2)\n", + "HEAD Giving shot 14 to worker:0:0\n", + "HEAD Giving shot 21 to worker:0:1\n", + "HEAD Functional value for shot 14: loss 1.677761e+01 for shot 14\n", "HEAD Retrieved gradient for shot 14\n", - "HEAD Giving shot 23 to worker:0:1\n", - "HEAD Functional value for shot 23: loss 1.799923e+00 for shot 23\n", - "HEAD Retrieved gradient for shot 23\n", - "HEAD Giving shot 26 to worker:0:1\n", - "HEAD Functional value for shot 26: loss 1.852457e+00 for shot 26\n", + "HEAD Giving shot 26 to worker:0:0\n", + "HEAD Functional value for shot 21: loss 1.414504e+01 for shot 21\n", + "HEAD Functional value for shot 26: loss 1.378035e+01 for shot 26\n", + "HEAD Retrieved gradient for shot 21\n", + "HEAD Giving shot 29 to worker:0:1\n", "HEAD Retrieved gradient for shot 26\n", - "HEAD Giving shot 35 to worker:0:1\n", - "HEAD Functional value for shot 35: loss 1.955671e+00 for shot 35\n", - "HEAD Functional value for shot 13: loss 1.373600e+00 for shot 13\n", + "HEAD Giving shot 31 to worker:0:0\n", + "HEAD Functional value for shot 29: loss 1.200254e+01 for shot 29\n", + "HEAD Functional value for shot 31: loss 1.168658e+01 for shot 31\n", + "HEAD Retrieved gradient for shot 29\n", + "HEAD Giving shot 34 to worker:0:1\n", + "HEAD Retrieved gradient for shot 31\n", + "HEAD Giving shot 35 to worker:0:0\n", + "HEAD Functional value for shot 35: loss 1.379514e+01 for shot 35\n", + "HEAD Functional value for shot 34: loss 1.262961e+01 for shot 34\n", "HEAD Retrieved gradient for shot 35\n", - "HEAD Giving shot 48 to worker:0:1\n", - "HEAD Functional value for shot 48: loss 9.249851e-01 for shot 48\n", - "HEAD Retrieved gradient for shot 48\n", - "HEAD Giving shot 58 to worker:0:1\n", - "HEAD Functional value for shot 58: loss 1.092716e+00 for shot 58\n", + "HEAD Giving shot 49 to worker:0:0\n", + "HEAD Retrieved gradient for shot 34\n", + "HEAD Giving shot 65 to worker:0:1\n", + "HEAD Functional value for shot 49: loss 1.781697e+01 for shot 49\n", + "HEAD Functional value for shot 65: loss 2.088942e+01 for shot 65\n", + "HEAD Retrieved gradient for shot 49\n", + "HEAD Giving shot 66 to worker:0:0\n", + "HEAD Retrieved gradient for shot 65\n", + "HEAD Giving shot 73 to worker:0:1\n", + "HEAD Functional value for shot 66: loss 1.860376e+01 for shot 66\n", + "HEAD Retrieved gradient for shot 66\n", + "HEAD Giving shot 77 to worker:0:0\n", + "HEAD Functional value for shot 73: loss 2.113954e+01 for shot 73\n", + "HEAD Functional value for shot 77: loss 2.001622e+01 for shot 77\n", + "HEAD Retrieved gradient for shot 73\n", + "HEAD Giving shot 78 to worker:0:1\n", + "HEAD Retrieved gradient for shot 77\n", + "HEAD Giving shot 81 to worker:0:0\n", + "HEAD Functional value for shot 78: loss 1.830110e+01 for shot 78\n", + "HEAD Functional value for shot 81: loss 2.244708e+01 for shot 81\n", + "HEAD Retrieved gradient for shot 78\n", + "HEAD Giving shot 85 to worker:0:1\n", + "HEAD Functional value for shot 85: loss 2.141579e+01 for shot 85\n", + "HEAD Retrieved gradient for shot 81\n", + "HEAD Retrieved gradient for shot 85\n", + "HEAD Done iteration 3 (out of 4), block 1 (out of 2) - Total loss_freq 2.554467e+02\n", + "HEAD ====================================================================\n", + "HEAD Starting iteration 4 (out of 4), block 1 (out of 2)\n", + "HEAD Giving shot 3 to worker:0:0\n", + "HEAD Giving shot 4 to worker:0:1\n", + "HEAD Functional value for shot 3: loss 2.193146e+00 for shot 3\n", + "HEAD Functional value for shot 4: loss 3.188060e+00 for shot 4\n", + "HEAD Retrieved gradient for shot 3\n", + "HEAD Giving shot 17 to worker:0:0\n", + "HEAD Retrieved gradient for shot 4\n", + "HEAD Giving shot 23 to worker:0:1\n", + "HEAD Functional value for shot 17: loss 4.177312e+00 for shot 17\n", + "HEAD Retrieved gradient for shot 17\n", + "HEAD Giving shot 28 to worker:0:0\n", + "HEAD Functional value for shot 23: loss 4.745093e+00 for shot 23\n", + "HEAD Functional value for shot 28: loss 4.135056e+00 for shot 28\n", + "HEAD Retrieved gradient for shot 23\n", + "HEAD Giving shot 51 to worker:0:1\n", + "HEAD Functional value for shot 51: loss 6.362376e+00 for shot 51\n", + "HEAD Retrieved gradient for shot 28\n", + "HEAD Giving shot 58 to worker:0:0\n", + "HEAD Retrieved gradient for shot 51\n", + "HEAD Giving shot 70 to worker:0:1\n", + "HEAD Functional value for shot 58: loss 6.997436e+00 for shot 58\n", "HEAD Retrieved gradient for shot 58\n", - "HEAD Giving shot 74 to worker:0:1\n", - "HEAD Functional value for shot 74: loss 1.233636e+00 for shot 74\n", - "HEAD Retrieved gradient for shot 13\n", - "HEAD Giving shot 84 to worker:0:0\n", - "HEAD Retrieved gradient for shot 74\n", - "HEAD Giving shot 97 to worker:0:1\n", - "HEAD Functional value for shot 97: loss 1.200127e+00 for shot 97\n", - "HEAD Retrieved gradient for shot 97\n", - "HEAD Giving shot 100 to worker:0:1\n", - "HEAD Functional value for shot 100: loss 1.053366e+00 for shot 100\n", - "HEAD Retrieved gradient for shot 100\n", - "HEAD Giving shot 105 to worker:0:1\n", - "HEAD Functional value for shot 105: loss 1.199744e+00 for shot 105\n", - "HEAD Retrieved gradient for shot 105\n", - "HEAD Giving shot 106 to worker:0:1\n", - "HEAD Functional value for shot 106: loss 1.124721e+00 for shot 106\n", - "HEAD Functional value for shot 84: loss 1.726474e+00 for shot 84\n", + "HEAD Giving shot 71 to worker:0:0\n", + "HEAD Functional value for shot 70: loss 6.798005e+00 for shot 70\n", + "HEAD Functional value for shot 71: loss 6.563156e+00 for shot 71\n", + "HEAD Retrieved gradient for shot 70\n", + "HEAD Giving shot 80 to worker:0:1\n", + "HEAD Retrieved gradient for shot 71\n", + "HEAD Giving shot 83 to worker:0:0\n", + "HEAD Functional value for shot 80: loss 5.114809e+00 for shot 80\n", + "HEAD Functional value for shot 83: loss 5.641373e+00 for shot 83\n", + "HEAD Retrieved gradient for shot 80\n", + "HEAD Giving shot 96 to worker:0:1\n", + "HEAD Retrieved gradient for shot 83\n", + "HEAD Giving shot 104 to worker:0:0\n", + "HEAD Functional value for shot 104: loss 2.898531e+00 for shot 104\n", + "HEAD Functional value for shot 96: loss 3.810362e+00 for shot 96\n", + "HEAD Retrieved gradient for shot 104\n", + "HEAD Giving shot 106 to worker:0:0\n", + "HEAD Retrieved gradient for shot 96\n", + "HEAD Giving shot 109 to worker:0:1\n", + "HEAD Functional value for shot 106: loss 2.960517e+00 for shot 106\n", + "HEAD Functional value for shot 109: loss 2.953939e+00 for shot 109\n", "HEAD Retrieved gradient for shot 106\n", - "HEAD Giving shot 115 to worker:0:1\n", - "HEAD Functional value for shot 115: loss 1.297943e+00 for shot 115\n", - "HEAD Retrieved gradient for shot 115\n", - "HEAD Giving shot 116 to worker:0:1\n", - "HEAD Functional value for shot 116: loss 1.253540e+00 for shot 116\n", - "HEAD Retrieved gradient for shot 116\n", - "HEAD Retrieved gradient for shot 84\n", - "HEAD Done iteration 2 (out of 4), block 1 (out of 2) - Total loss_freq 2.039157e+01\n", + "HEAD Retrieved gradient for shot 109\n", + "HEAD Done iteration 4 (out of 4), block 1 (out of 2) - Total loss_freq 6.853917e+01\n", "HEAD ====================================================================\n", - "HEAD Starting iteration 3 (out of 4), block 1 (out of 2)\n", + "HEAD Starting iteration 1 (out of 4), block 2 (out of 2)\n", "HEAD Giving shot 1 to worker:0:0\n", - "HEAD Giving shot 10 to worker:0:1\n", - "HEAD Functional value for shot 10: loss 1.192814e+00 for shot 10\n", - "HEAD Retrieved gradient for shot 10\n", - "HEAD Giving shot 25 to worker:0:1\n", - "HEAD Functional value for shot 25: loss 1.497280e+00 for shot 25\n", + "HEAD Giving shot 12 to worker:0:1\n", + "HEAD Functional value for shot 1: loss 1.591766e+00 for shot 1\n", + "HEAD Functional value for shot 12: loss 2.045354e+00 for shot 12\n", + "HEAD Retrieved gradient for shot 1\n", + "HEAD Giving shot 25 to worker:0:0\n", + "HEAD Retrieved gradient for shot 12\n", + "HEAD Giving shot 39 to worker:0:1\n", + "HEAD Functional value for shot 25: loss 2.635685e+00 for shot 25\n", "HEAD Retrieved gradient for shot 25\n", - "HEAD Giving shot 30 to worker:0:1\n", - "HEAD Functional value for shot 30: loss 1.742769e+00 for shot 30\n", - "HEAD Retrieved gradient for shot 30\n", - "HEAD Giving shot 51 to worker:0:1\n", - "HEAD Functional value for shot 51: loss 9.617972e-01 for shot 51\n", - "HEAD Retrieved gradient for shot 51\n", - "HEAD Giving shot 53 to worker:0:1\n", - "HEAD Functional value for shot 1: loss 1.089886e+00 for shot 1\n", - "HEAD Functional value for shot 53: loss 9.857967e-01 for shot 53\n", - "HEAD Retrieved gradient for shot 53\n", - "HEAD Giving shot 57 to worker:0:1\n", - "HEAD Functional value for shot 57: loss 7.078637e-01 for shot 57\n", + "HEAD Giving shot 41 to worker:0:0\n", + "HEAD Functional value for shot 39: loss 2.975608e+00 for shot 39\n", + "HEAD Functional value for shot 41: loss 1.787923e+00 for shot 41\n", + "HEAD Retrieved gradient for shot 39\n", + "HEAD Giving shot 54 to worker:0:1\n", + "HEAD Retrieved gradient for shot 41\n", + "HEAD Giving shot 57 to worker:0:0\n", + "HEAD Functional value for shot 54: loss 3.719377e+00 for shot 54\n", + "HEAD Functional value for shot 57: loss 3.145941e+00 for shot 57\n", + "HEAD Retrieved gradient for shot 54\n", + "HEAD Giving shot 62 to worker:0:1\n", "HEAD Retrieved gradient for shot 57\n", - "HEAD Giving shot 59 to worker:0:1\n", - "HEAD Functional value for shot 59: loss 9.039650e-01 for shot 59\n", - "HEAD Retrieved gradient for shot 1\n", - "HEAD Giving shot 88 to worker:0:0\n", - "HEAD Retrieved gradient for shot 59\n", - "HEAD Giving shot 92 to worker:0:1\n", - "HEAD Functional value for shot 92: loss 1.194708e+00 for shot 92\n", - "HEAD Retrieved gradient for shot 92\n", - "HEAD Giving shot 94 to worker:0:1\n", - "HEAD Functional value for shot 94: loss 1.151145e+00 for shot 94\n", + "HEAD Giving shot 63 to worker:0:0\n", + "HEAD Functional value for shot 62: loss 5.204585e+00 for shot 62\n", + "HEAD Functional value for shot 63: loss 3.808007e+00 for shot 63\n", + "HEAD Retrieved gradient for shot 63\n", + "HEAD Giving shot 72 to worker:0:0\n", + "HEAD Retrieved gradient for shot 62\n", + "HEAD Giving shot 76 to worker:0:1\n", + "HEAD Functional value for shot 76: loss 4.339418e+00 for shot 76\n", + "HEAD Functional value for shot 72: loss 4.620985e+00 for shot 72\n", + "HEAD Retrieved gradient for shot 76\n", + "HEAD Giving shot 90 to worker:0:1\n", + "HEAD Retrieved gradient for shot 72\n", + "HEAD Giving shot 94 to worker:0:0\n", + "HEAD Functional value for shot 90: loss 2.184664e+00 for shot 90\n", + "HEAD Functional value for shot 94: loss 2.150727e+00 for shot 94\n", "HEAD Retrieved gradient for shot 94\n", - "HEAD Giving shot 98 to worker:0:1\n", - "HEAD Functional value for shot 98: loss 1.050555e+00 for shot 98\n", + "HEAD Giving shot 98 to worker:0:0\n", + "HEAD Retrieved gradient for shot 90\n", + "HEAD Giving shot 115 to worker:0:1\n", + "HEAD Functional value for shot 98: loss 2.153457e+00 for shot 98\n", + "HEAD Functional value for shot 115: loss 1.574050e+00 for shot 115\n", "HEAD Retrieved gradient for shot 98\n", - "HEAD Giving shot 109 to worker:0:1\n", - "HEAD Functional value for shot 109: loss 1.015291e+00 for shot 109\n", - "HEAD Functional value for shot 88: loss 1.292400e+00 for shot 88\n", - "HEAD Retrieved gradient for shot 109\n", - "HEAD Giving shot 110 to worker:0:1\n", - "HEAD Functional value for shot 110: loss 1.055282e+00 for shot 110\n", - "HEAD Retrieved gradient for shot 110\n", - "HEAD Giving shot 112 to worker:0:1\n", - "HEAD Functional value for shot 112: loss 9.233050e-01 for shot 112\n", - "HEAD Retrieved gradient for shot 112\n", - "HEAD Retrieved gradient for shot 88\n", - "HEAD Done iteration 3 (out of 4), block 1 (out of 2) - Total loss_freq 1.676486e+01\n", + "HEAD Retrieved gradient for shot 115\n", + "HEAD Done iteration 1 (out of 4), block 2 (out of 2) - Total loss_freq 4.393755e+01\n", "HEAD ====================================================================\n", - "HEAD Starting iteration 4 (out of 4), block 1 (out of 2)\n", - "HEAD Giving shot 7 to worker:0:0\n", + "HEAD Starting iteration 2 (out of 4), block 2 (out of 2)\n", + "HEAD Giving shot 6 to worker:0:0\n", + "HEAD Giving shot 8 to worker:0:1\n", + "HEAD Functional value for shot 6: loss 1.034736e+00 for shot 6\n", + "HEAD Functional value for shot 8: loss 9.897235e-01 for shot 8\n", + "HEAD Retrieved gradient for shot 6\n", + "HEAD Giving shot 9 to worker:0:0\n", + "HEAD Retrieved gradient for shot 8\n", + "HEAD Giving shot 11 to worker:0:1\n", + "HEAD Functional value for shot 9: loss 1.132927e+00 for shot 9\n", + "HEAD Retrieved gradient for shot 9\n", + "HEAD Giving shot 38 to worker:0:0\n", + "HEAD Functional value for shot 11: loss 1.560557e+00 for shot 11\n", + "HEAD Functional value for shot 38: loss 3.323248e+00 for shot 38\n", + "HEAD Retrieved gradient for shot 11\n", + "HEAD Giving shot 48 to worker:0:1\n", + "HEAD Retrieved gradient for shot 38\n", + "HEAD Giving shot 52 to worker:0:0\n", + "HEAD Functional value for shot 48: loss 4.380332e+00 for shot 48\n", + "HEAD Functional value for shot 52: loss 4.833606e+00 for shot 52\n", + "HEAD Retrieved gradient for shot 48\n", + "HEAD Giving shot 68 to worker:0:1\n", + "HEAD Retrieved gradient for shot 52\n", + "HEAD Giving shot 74 to worker:0:0\n", + "HEAD Functional value for shot 68: loss 6.192408e+00 for shot 68\n", + "HEAD Functional value for shot 74: loss 5.918913e+00 for shot 74\n", + "HEAD Retrieved gradient for shot 74\n", + "HEAD Giving shot 84 to worker:0:0\n", + "HEAD Retrieved gradient for shot 68\n", + "HEAD Giving shot 86 to worker:0:1\n", + "HEAD Functional value for shot 84: loss 5.017056e+00 for shot 84\n", + "HEAD Functional value for shot 86: loss 4.219666e+00 for shot 86\n", + "HEAD Retrieved gradient for shot 84\n", + "HEAD Giving shot 101 to worker:0:0\n", + "HEAD Retrieved gradient for shot 86\n", + "HEAD Giving shot 103 to worker:0:1\n", + "HEAD Functional value for shot 101: loss 1.599049e+00 for shot 101\n", + "HEAD Functional value for shot 103: loss 1.983486e+00 for shot 103\n", + "HEAD Retrieved gradient for shot 101\n", + "HEAD Giving shot 107 to worker:0:0\n", + "HEAD Functional value for shot 107: loss 1.551904e+00 for shot 107\n", + "HEAD Retrieved gradient for shot 103\n", + "HEAD Giving shot 119 to worker:0:1\n", + "HEAD Functional value for shot 119: loss 1.257727e+00 for shot 119\n", + "HEAD Retrieved gradient for shot 107\n", + "HEAD Retrieved gradient for shot 119\n", + "HEAD Done iteration 2 (out of 4), block 2 (out of 2) - Total loss_freq 4.499534e+01\n", + "HEAD ====================================================================\n", + "HEAD Starting iteration 3 (out of 4), block 2 (out of 2)\n", + "HEAD Giving shot 0 to worker:0:0\n", + "HEAD Giving shot 5 to worker:0:1\n", + "HEAD Functional value for shot 5: loss 2.243644e+00 for shot 5\n", + "HEAD Functional value for shot 0: loss 1.504635e+00 for shot 0\n", + "HEAD Retrieved gradient for shot 5\n", "HEAD Giving shot 15 to worker:0:1\n", - "HEAD Functional value for shot 15: loss 9.959779e-01 for shot 15\n", + "HEAD Retrieved gradient for shot 0\n", + "HEAD Giving shot 46 to worker:0:0\n", + "HEAD Functional value for shot 15: loss 2.787277e+00 for shot 15\n", + "HEAD Functional value for shot 46: loss 5.178318e+00 for shot 46\n", + "HEAD Retrieved gradient for shot 46\n", + "HEAD Giving shot 50 to worker:0:0\n", "HEAD Retrieved gradient for shot 15\n", - "HEAD Giving shot 20 to worker:0:1\n", - "HEAD Functional value for shot 20: loss 1.072309e+00 for shot 20\n", - "HEAD Retrieved gradient for shot 20\n", - "HEAD Giving shot 22 to worker:0:1\n", - "HEAD Functional value for shot 22: loss 1.319239e+00 for shot 22\n", - "HEAD Retrieved gradient for shot 22\n", - "HEAD Giving shot 28 to worker:0:1\n", - "HEAD Functional value for shot 28: loss 1.363289e+00 for shot 28\n", - "HEAD Functional value for shot 7: loss 9.282386e-01 for shot 7\n", - "HEAD Retrieved gradient for shot 28\n", - "HEAD Giving shot 62 to worker:0:1\n", - "HEAD Functional value for shot 62: loss 7.194777e-01 for shot 62\n", - "HEAD Retrieved gradient for shot 62\n", - "HEAD Giving shot 77 to worker:0:1\n", - "HEAD Functional value for shot 77: loss 9.600102e-01 for shot 77\n", - "HEAD Retrieved gradient for shot 77\n", - "HEAD Giving shot 79 to worker:0:1\n", - "HEAD Functional value for shot 79: loss 8.640406e-01 for shot 79\n", - "HEAD Retrieved gradient for shot 7\n", - "HEAD Giving shot 80 to worker:0:0\n", - "HEAD Retrieved gradient for shot 79\n", - "HEAD Giving shot 81 to worker:0:1\n", - "HEAD Functional value for shot 81: loss 1.240638e+00 for shot 81\n", - "HEAD Retrieved gradient for shot 81\n", + "HEAD Giving shot 55 to worker:0:1\n", + "HEAD Functional value for shot 50: loss 5.693784e+00 for shot 50\n", + "HEAD Functional value for shot 55: loss 6.312356e+00 for shot 55\n", + "HEAD Retrieved gradient for shot 50\n", + "HEAD Giving shot 88 to worker:0:0\n", + "HEAD Retrieved gradient for shot 55\n", "HEAD Giving shot 89 to worker:0:1\n", - "HEAD Functional value for shot 89: loss 9.015474e-01 for shot 89\n", + "HEAD Functional value for shot 88: loss 3.610848e+00 for shot 88\n", + "HEAD Retrieved gradient for shot 88\n", + "HEAD Giving shot 92 to worker:0:0\n", + "HEAD Functional value for shot 89: loss 3.122985e+00 for shot 89\n", + "HEAD Functional value for shot 92: loss 3.250080e+00 for shot 92\n", "HEAD Retrieved gradient for shot 89\n", "HEAD Giving shot 93 to worker:0:1\n", - "HEAD Functional value for shot 93: loss 9.438744e-01 for shot 93\n", - "HEAD Functional value for shot 80: loss 1.003544e+00 for shot 80\n", + "HEAD Retrieved gradient for shot 92\n", + "HEAD Giving shot 99 to worker:0:0\n", + "HEAD Functional value for shot 93: loss 2.856540e+00 for shot 93\n", + "HEAD Functional value for shot 99: loss 2.391837e+00 for shot 99\n", "HEAD Retrieved gradient for shot 93\n", - "HEAD Giving shot 99 to worker:0:1\n", - "HEAD Functional value for shot 99: loss 8.847746e-01 for shot 99\n", + "HEAD Giving shot 111 to worker:0:1\n", "HEAD Retrieved gradient for shot 99\n", - "HEAD Giving shot 103 to worker:0:1\n", - "HEAD Functional value for shot 103: loss 7.527244e-01 for shot 103\n", - "HEAD Retrieved gradient for shot 103\n", - "HEAD Giving shot 117 to worker:0:1\n", - "HEAD Functional value for shot 117: loss 6.467879e-01 for shot 117\n", - "HEAD Retrieved gradient for shot 117\n", - "HEAD Retrieved gradient for shot 80\n", - "HEAD Done iteration 4 (out of 4), block 1 (out of 2) - Total loss_freq 1.459647e+01\n", - "HEAD ====================================================================\n", - "HEAD Starting iteration 1 (out of 4), block 2 (out of 2)\n", - "HEAD Giving shot 2 to worker:0:0\n", - "HEAD Giving shot 3 to worker:0:1\n", - "HEAD Functional value for shot 3: loss 7.558197e-01 for shot 3\n", - "HEAD Retrieved gradient for shot 3\n", - "HEAD Giving shot 6 to worker:0:1\n", - "HEAD Functional value for shot 6: loss 1.025622e+00 for shot 6\n", - "HEAD Retrieved gradient for shot 6\n", - "HEAD Giving shot 9 to worker:0:1\n", - "HEAD Functional value for shot 9: loss 1.076054e+00 for shot 9\n", - "HEAD Retrieved gradient for shot 9\n", - "HEAD Giving shot 31 to worker:0:1\n", - "HEAD Functional value for shot 31: loss 1.515861e+00 for shot 31\n", - "HEAD Retrieved gradient for shot 31\n", - "HEAD Giving shot 41 to worker:0:1\n", - "HEAD Functional value for shot 41: loss 9.670873e-01 for shot 41\n", - "HEAD Retrieved gradient for shot 41\n", - "HEAD Giving shot 42 to worker:0:1\n", - "HEAD Functional value for shot 2: loss 9.920448e-01 for shot 2\n", - "HEAD Functional value for shot 42: loss 9.719697e-01 for shot 42\n", - "HEAD Retrieved gradient for shot 42\n", - "HEAD Giving shot 43 to worker:0:1\n", - "HEAD Functional value for shot 43: loss 1.018190e+00 for shot 43\n", - "HEAD Retrieved gradient for shot 43\n", - "HEAD Giving shot 52 to worker:0:1\n", - "HEAD Functional value for shot 52: loss 8.038019e-01 for shot 52\n", - "HEAD Retrieved gradient for shot 52\n", - "HEAD Giving shot 55 to worker:0:1\n", - "HEAD Functional value for shot 55: loss 1.013667e+00 for shot 55\n", - "HEAD Retrieved gradient for shot 55\n", - "HEAD Giving shot 60 to worker:0:1\n", - "HEAD Functional value for shot 60: loss 5.470030e-01 for shot 60\n", - "HEAD Retrieved gradient for shot 2\n", - "HEAD Giving shot 78 to worker:0:0\n", - "HEAD Retrieved gradient for shot 60\n", - "HEAD Giving shot 82 to worker:0:1\n", - "HEAD Functional value for shot 82: loss 1.623824e+00 for shot 82\n", - "HEAD Retrieved gradient for shot 82\n", - "HEAD Giving shot 87 to worker:0:1\n", - "HEAD Functional value for shot 87: loss 1.269356e+00 for shot 87\n", - "HEAD Retrieved gradient for shot 87\n", - "HEAD Giving shot 107 to worker:0:1\n", - "HEAD Functional value for shot 107: loss 8.909570e-01 for shot 107\n", - "HEAD Retrieved gradient for shot 107\n", - "HEAD Functional value for shot 78: loss 9.574547e-01 for shot 78\n", - "HEAD Retrieved gradient for shot 78\n", - "HEAD Done iteration 1 (out of 4), block 2 (out of 2) - Total loss_freq 1.542871e+01\n", - "HEAD ====================================================================\n", - "HEAD Starting iteration 2 (out of 4), block 2 (out of 2)\n", - "HEAD Giving shot 5 to worker:0:0\n", - "HEAD Giving shot 11 to worker:0:1\n", - "HEAD Functional value for shot 11: loss 1.030801e+00 for shot 11\n", - "HEAD Retrieved gradient for shot 11\n", - "HEAD Giving shot 29 to worker:0:1\n", - "HEAD Functional value for shot 29: loss 1.228628e+00 for shot 29\n", - "HEAD Retrieved gradient for shot 29\n", - "HEAD Giving shot 33 to worker:0:1\n", - "HEAD Functional value for shot 33: loss 1.450502e+00 for shot 33\n", - "HEAD Retrieved gradient for shot 33\n", - "HEAD Giving shot 34 to worker:0:1\n", - "HEAD Functional value for shot 5: loss 9.146921e-01 for shot 5\n", - "HEAD Functional value for shot 34: loss 1.506798e+00 for shot 34\n", - "HEAD Retrieved gradient for shot 34\n", - "HEAD Giving shot 44 to worker:0:1\n", - "HEAD Functional value for shot 44: loss 7.956617e-01 for shot 44\n", - "HEAD Retrieved gradient for shot 44\n", - "HEAD Giving shot 47 to worker:0:1\n", - "HEAD Retrieved gradient for shot 5\n", - "HEAD Giving shot 49 to worker:0:0\n", - "HEAD Functional value for shot 47: loss 9.335254e-01 for shot 47\n", - "HEAD Retrieved gradient for shot 47\n", - "HEAD Giving shot 63 to worker:0:1\n", - "HEAD Functional value for shot 63: loss 5.334662e-01 for shot 63\n", - "HEAD Retrieved gradient for shot 63\n", - "HEAD Giving shot 65 to worker:0:1\n", - "HEAD Functional value for shot 65: loss 9.077389e-01 for shot 65\n", - "HEAD Retrieved gradient for shot 65\n", - "HEAD Giving shot 72 to worker:0:1\n", - "HEAD Functional value for shot 72: loss 8.337521e-01 for shot 72\n", - "HEAD Functional value for shot 49: loss 8.743588e-01 for shot 49\n", - "HEAD Retrieved gradient for shot 72\n", - "HEAD Giving shot 96 to worker:0:1\n", - "HEAD Functional value for shot 96: loss 9.939452e-01 for shot 96\n", - "HEAD Retrieved gradient for shot 96\n", - "HEAD Giving shot 108 to worker:0:1\n", - "HEAD Functional value for shot 108: loss 6.731066e-01 for shot 108\n", - "HEAD Retrieved gradient for shot 108\n", + "HEAD Giving shot 112 to worker:0:0\n", + "HEAD Functional value for shot 112: loss 1.695836e+00 for shot 112\n", + "HEAD Functional value for shot 111: loss 1.950174e+00 for shot 111\n", + "HEAD Retrieved gradient for shot 112\n", + "HEAD Giving shot 113 to worker:0:0\n", + "HEAD Retrieved gradient for shot 111\n", "HEAD Giving shot 114 to worker:0:1\n", - "HEAD Functional value for shot 114: loss 8.088626e-01 for shot 114\n", + "HEAD Functional value for shot 113: loss 1.552647e+00 for shot 113\n", + "HEAD Functional value for shot 114: loss 1.541781e+00 for shot 114\n", + "HEAD Retrieved gradient for shot 113\n", "HEAD Retrieved gradient for shot 114\n", - "HEAD Giving shot 118 to worker:0:1\n", - "HEAD Functional value for shot 118: loss 8.542686e-01 for shot 118\n", - "HEAD Retrieved gradient for shot 118\n", - "HEAD Retrieved gradient for shot 49\n", - "HEAD Done iteration 2 (out of 4), block 2 (out of 2) - Total loss_freq 1.434011e+01\n", - "HEAD ====================================================================\n", - "HEAD Starting iteration 3 (out of 4), block 2 (out of 2)\n", - "HEAD Giving shot 0 to worker:0:0\n", - "HEAD Giving shot 4 to worker:0:1\n", - "HEAD Functional value for shot 4: loss 8.293226e-01 for shot 4\n", - "HEAD Retrieved gradient for shot 4\n", - "HEAD Giving shot 8 to worker:0:1\n", - "HEAD Functional value for shot 8: loss 7.360731e-01 for shot 8\n", - "HEAD Retrieved gradient for shot 8\n", - "HEAD Giving shot 18 to worker:0:1\n", - "HEAD Functional value for shot 18: loss 8.943943e-01 for shot 18\n", - "HEAD Retrieved gradient for shot 18\n", - "HEAD Giving shot 19 to worker:0:1\n", - "HEAD Functional value for shot 0: loss 5.655379e-01 for shot 0\n", - "HEAD Functional value for shot 19: loss 8.734545e-01 for shot 19\n", - "HEAD Retrieved gradient for shot 19\n", - "HEAD Giving shot 21 to worker:0:1\n", - "HEAD Functional value for shot 21: loss 1.147754e+00 for shot 21\n", - "HEAD Retrieved gradient for shot 21\n", - "HEAD Giving shot 24 to worker:0:1\n", - "HEAD Functional value for shot 24: loss 1.338102e+00 for shot 24\n", - "HEAD Retrieved gradient for shot 24\n", - "HEAD Giving shot 38 to worker:0:1\n", - "HEAD Functional value for shot 38: loss 1.352444e+00 for shot 38\n", - "HEAD Retrieved gradient for shot 38\n", - "HEAD Giving shot 54 to worker:0:1\n", - "HEAD Functional value for shot 54: loss 7.585951e-01 for shot 54\n", - "HEAD Retrieved gradient for shot 54\n", - "HEAD Giving shot 56 to worker:0:1\n", - "HEAD Functional value for shot 56: loss 7.968095e-01 for shot 56\n", - "HEAD Retrieved gradient for shot 56\n", - "HEAD Giving shot 64 to worker:0:1\n", - "HEAD Retrieved gradient for shot 0\n", - "HEAD Giving shot 68 to worker:0:0\n", - "HEAD Functional value for shot 64: loss 7.274514e-01 for shot 64\n", - "HEAD Retrieved gradient for shot 64\n", - "HEAD Giving shot 85 to worker:0:1\n", - "HEAD Functional value for shot 85: loss 1.272877e+00 for shot 85\n", - "HEAD Retrieved gradient for shot 85\n", - "HEAD Giving shot 104 to worker:0:1\n", - "HEAD Functional value for shot 104: loss 6.462344e-01 for shot 104\n", - "HEAD Retrieved gradient for shot 104\n", - "HEAD Giving shot 119 to worker:0:1\n", - "HEAD Functional value for shot 119: loss 8.429440e-01 for shot 119\n", - "HEAD Retrieved gradient for shot 119\n", - "HEAD Functional value for shot 68: loss 7.852683e-01 for shot 68\n", - "HEAD Retrieved gradient for shot 68\n", - "HEAD Done iteration 3 (out of 4), block 2 (out of 2) - Total loss_freq 1.356726e+01\n", + "HEAD Done iteration 3 (out of 4), block 2 (out of 2) - Total loss_freq 4.569274e+01\n", "HEAD ====================================================================\n", "HEAD Starting iteration 4 (out of 4), block 2 (out of 2)\n", - "HEAD Giving shot 12 to worker:0:0\n", - "HEAD Giving shot 32 to worker:0:1\n", - "HEAD Functional value for shot 32: loss 1.344790e+00 for shot 32\n", - "HEAD Retrieved gradient for shot 32\n", - "HEAD Giving shot 36 to worker:0:1\n", - "HEAD Functional value for shot 36: loss 1.255521e+00 for shot 36\n", - "HEAD Retrieved gradient for shot 36\n", + "HEAD Giving shot 2 to worker:0:0\n", + "HEAD Giving shot 13 to worker:0:1\n", + "HEAD Functional value for shot 13: loss 1.099498e+01 for shot 13\n", + "HEAD Functional value for shot 2: loss 9.776863e+00 for shot 2\n", + "HEAD Retrieved gradient for shot 2\n", + "HEAD Giving shot 16 to worker:0:0\n", + "HEAD Retrieved gradient for shot 13\n", + "HEAD Giving shot 27 to worker:0:1\n", + "HEAD Functional value for shot 16: loss 9.795203e+00 for shot 16\n", + "HEAD Functional value for shot 27: loss 9.669251e+00 for shot 27\n", + "HEAD Retrieved gradient for shot 16\n", + "HEAD Giving shot 30 to worker:0:0\n", + "HEAD Functional value for shot 30: loss 1.063250e+01 for shot 30\n", + "HEAD Retrieved gradient for shot 27\n", "HEAD Giving shot 37 to worker:0:1\n", - "HEAD Functional value for shot 37: loss 1.129683e+00 for shot 37\n", + "HEAD Retrieved gradient for shot 30\n", + "HEAD Giving shot 42 to worker:0:0\n", + "HEAD Functional value for shot 37: loss 1.390970e+01 for shot 37\n", + "HEAD Functional value for shot 42: loss 1.414288e+01 for shot 42\n", "HEAD Retrieved gradient for shot 37\n", - "HEAD Giving shot 39 to worker:0:1\n", - "HEAD Functional value for shot 39: loss 1.010604e+00 for shot 39\n", - "HEAD Functional value for shot 12: loss 8.125896e-01 for shot 12\n", - "HEAD Retrieved gradient for shot 39\n", - "HEAD Giving shot 46 to worker:0:1\n", - "HEAD Functional value for shot 46: loss 8.060646e-01 for shot 46\n", - "HEAD Retrieved gradient for shot 46\n", - "HEAD Giving shot 50 to worker:0:1\n", - "HEAD Functional value for shot 50: loss 7.412825e-01 for shot 50\n", - "HEAD Retrieved gradient for shot 50\n", - "HEAD Giving shot 66 to worker:0:1\n", - "HEAD Retrieved gradient for shot 12\n", + "HEAD Giving shot 43 to worker:0:1\n", + "HEAD Retrieved gradient for shot 42\n", "HEAD Giving shot 67 to worker:0:0\n", - "HEAD Functional value for shot 66: loss 7.007262e-01 for shot 66\n", - "HEAD Retrieved gradient for shot 66\n", + "HEAD Functional value for shot 43: loss 1.620085e+01 for shot 43\n", + "HEAD Functional value for shot 67: loss 1.303449e+01 for shot 67\n", + "HEAD Retrieved gradient for shot 43\n", "HEAD Giving shot 75 to worker:0:1\n", - "HEAD Functional value for shot 75: loss 9.774604e-01 for shot 75\n", - "HEAD Functional value for shot 67: loss 7.374524e-01 for shot 67\n", - "HEAD Retrieved gradient for shot 75\n", - "HEAD Giving shot 76 to worker:0:1\n", - "HEAD Functional value for shot 76: loss 8.130559e-01 for shot 76\n", - "HEAD Retrieved gradient for shot 76\n", - "HEAD Giving shot 86 to worker:0:1\n", "HEAD Retrieved gradient for shot 67\n", - "HEAD Giving shot 95 to worker:0:0\n", - "HEAD Functional value for shot 86: loss 1.088886e+00 for shot 86\n", - "HEAD Retrieved gradient for shot 86\n", - "HEAD Giving shot 101 to worker:0:1\n", - "HEAD Functional value for shot 101: loss 5.647735e-01 for shot 101\n", - "HEAD Retrieved gradient for shot 101\n", - "HEAD Giving shot 111 to worker:0:1\n", - "HEAD Functional value for shot 111: loss 8.084124e-01 for shot 111\n", - "HEAD Retrieved gradient for shot 111\n", - "HEAD Functional value for shot 95: loss 8.929266e-01 for shot 95\n", - "HEAD Retrieved gradient for shot 95\n", - "HEAD Done iteration 4 (out of 4), block 2 (out of 2) - Total loss_freq 1.368423e+01\n", + "HEAD Giving shot 79 to worker:0:0\n", + "HEAD Functional value for shot 79: loss 1.073063e+01 for shot 79\n", + "HEAD Functional value for shot 75: loss 1.404534e+01 for shot 75\n", + "HEAD Retrieved gradient for shot 79\n", + "HEAD Giving shot 97 to worker:0:0\n", + "HEAD Retrieved gradient for shot 75\n", + "HEAD Giving shot 105 to worker:0:1\n", + "HEAD Functional value for shot 97: loss 1.200648e+01 for shot 97\n", + "HEAD Functional value for shot 105: loss 1.108809e+01 for shot 105\n", + "HEAD Retrieved gradient for shot 97\n", + "HEAD Giving shot 116 to worker:0:0\n", + "HEAD Retrieved gradient for shot 105\n", + "HEAD Giving shot 118 to worker:0:1\n", + "HEAD Functional value for shot 116: loss 9.791444e+00 for shot 116\n", + "HEAD Retrieved gradient for shot 116\n", + "HEAD Functional value for shot 118: loss 8.953126e+00 for shot 118\n", + "HEAD Retrieved gradient for shot 118\n", + "HEAD Done iteration 4 (out of 4), block 2 (out of 2) - Total loss_freq 1.747718e+02\n", "HEAD ====================================================================\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9c12595a171049388184a2aa738d1234", + "model_id": "1cded3a28ba54a00ace6e374703cc37d", "version_major": 2, "version_minor": 0 }, - "image/png": 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", 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\n", - " \n", + " \n", "
\n", " " ], @@ -1885,836 +1924,6 @@ "metadata": {}, "output_type": "execute_result" }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:1 (ShotID 35) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 35) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.64 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 42.22 GFlops/s, 0.87 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.56 s [OI=2.82, 45.97 GFlops/s, 1.00 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.92 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 21.42 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 29) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 29\n", - "HEAD Giving shot 36 to worker:0:0\n", - "WORKER:0:0 (ShotID 36) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 36) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 36) Spatial grid spacing (0.500 mm | 4.139 PPW) is higher than dispersion limit (0.414 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 36) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 36) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 36) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 36) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.64 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 42.22 GFlops/s, 0.87 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.56 s [OI=2.82, 46.17 GFlops/s, 1.01 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.88 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.07 s [OI=0.25, 22.53 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 35) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 35\n", - "HEAD Giving shot 51 to worker:0:1\n", - "WORKER:0:1 (ShotID 51) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 51) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 51) Spatial grid spacing (0.500 mm | 4.139 PPW) is higher than dispersion limit (0.414 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 51) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 51) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 51) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 51) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.58 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 47.67 GFlops/s, 0.96 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.52 s [OI=2.82, 49.14 GFlops/s, 1.07 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.15 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 53.22 GFlops/s, 13.31 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 36) Completed state equation run for shot\n", - "HEAD Functional value for shot 36: loss 1.413133e+00 for shot 36\n", - "WORKER:0:0 (ShotID 36) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 36) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.69 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 40.07 GFlops/s, 0.81 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.63 s [OI=2.82, 40.43 GFlops/s, 0.88 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.07 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 50.44 GFlops/s, 12.61 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 51) Completed state equation run for shot\n", - "HEAD Functional value for shot 51: loss 7.501166e-01 for shot 51\n", - "WORKER:0:1 (ShotID 51) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 51) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.62 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 43.58 GFlops/s, 0.90 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.54 s [OI=2.82, 47.79 GFlops/s, 1.04 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 5.00 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 21.12 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 36) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 36\n", - "HEAD Giving shot 52 to worker:0:0\n", - "WORKER:0:0 (ShotID 52) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 52) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 52) Spatial grid spacing (0.500 mm | 4.139 PPW) is higher than dispersion limit (0.414 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 52) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 52) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 52) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 52) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.71 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 38.06 GFlops/s, 0.78 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.62 s [OI=2.82, 41.02 GFlops/s, 0.90 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.90 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 20.57 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 51) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 51\n", - "HEAD Giving shot 70 to worker:0:1\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.54 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 51.20 GFlops/s, 1.03 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.49 s [OI=2.82, 52.60 GFlops/s, 1.15 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.13 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.39 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.04 s [OI=0.50, 56.08 GFlops/s, 14.02 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 52) Completed state equation run for shot\n", - "WORKER:0:1 (ShotID 70) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 70) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 70) Spatial grid spacing (0.500 mm | 4.139 PPW) is higher than dispersion limit (0.414 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 70) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 70) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 70) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 70) Running state equation for shot\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "HEAD Functional value for shot 52: loss 6.635887e-01 for shot 52\n", - "WORKER:0:0 (ShotID 52) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 52) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.48 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 57.60 GFlops/s, 1.16 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.43 s [OI=2.82, 59.64 GFlops/s, 1.30 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.14 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.54 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.04 s [OI=0.50, 58.17 GFlops/s, 14.55 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 70) Completed state equation run for shot\n", - "HEAD Functional value for shot 70: loss 8.399595e-01 for shot 70\n", - "WORKER:0:1 (ShotID 70) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 70) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.81 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 33.36 GFlops/s, 0.69 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.71 s [OI=2.82, 35.96 GFlops/s, 0.79 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.44 GFlops/s, 0.08 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 19.72 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 52) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 52\n", - "HEAD Giving shot 73 to worker:0:0\n", - "WORKER:0:0 (ShotID 73) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 73) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 73) Spatial grid spacing (0.500 mm | 4.139 PPW) is higher than dispersion limit (0.414 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 73) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 73) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 73) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 73) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.68 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 39.74 GFlops/s, 0.82 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.59 s [OI=2.82, 43.73 GFlops/s, 0.96 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 5.15 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 19.38 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 70) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 70\n", - "HEAD Giving shot 78 to worker:0:1\n", - "WORKER:0:1 (ShotID 78) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 78) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 78) Spatial grid spacing (0.500 mm | 4.139 PPW) is higher than dispersion limit (0.414 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 78) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 78) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 78) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 78) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.68 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 40.66 GFlops/s, 0.82 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.62 s [OI=2.82, 41.22 GFlops/s, 0.90 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.13 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.18 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 46.00 GFlops/s, 11.50 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 73) Completed state equation run for shot\n", - "HEAD Functional value for shot 73: loss 9.289600e-01 for shot 73\n", - "WORKER:0:0 (ShotID 73) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 73) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.56 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 49.38 GFlops/s, 0.99 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.51 s [OI=2.82, 50.81 GFlops/s, 1.11 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.14 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.43 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 55.09 GFlops/s, 13.78 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 78) Completed state equation run for shot\n", - "HEAD Functional value for shot 78: loss 8.744242e-01 for shot 78\n", - "WORKER:0:1 (ShotID 78) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 78) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.65 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 41.57 GFlops/s, 0.86 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.56 s [OI=2.82, 45.99 GFlops/s, 1.00 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.86 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 20.23 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 73) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 73\n", - "HEAD Giving shot 94 to worker:0:0\n", - "WORKER:0:0 (ShotID 94) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 94) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 94) Spatial grid spacing (0.500 mm | 4.139 PPW) is higher than dispersion limit (0.414 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 94) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 94) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 94) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 94) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.66 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 40.94 GFlops/s, 0.84 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.58 s [OI=2.82, 44.56 GFlops/s, 0.97 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.83 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 21.22 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 78) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 78\n", - "HEAD Giving shot 105 to worker:0:1\n", - "WORKER:0:1 (ShotID 105) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 105) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:1 (ShotID 105) Spatial grid spacing (0.500 mm | 4.139 PPW) is higher than dispersion limit (0.414 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 105) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 105) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 105) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 105) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.63 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 43.89 GFlops/s, 0.88 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.58 s [OI=2.82, 44.53 GFlops/s, 0.97 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.18 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 47.68 GFlops/s, 11.92 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 94) Completed state equation run for shot\n", - "HEAD Functional value for shot 94: loss 9.263841e-01 for shot 94\n", - "WORKER:0:0 (ShotID 94) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 94) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.60 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 46.08 GFlops/s, 0.93 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.55 s [OI=2.82, 46.68 GFlops/s, 1.02 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.12 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 53.09 GFlops/s, 13.28 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 105) Completed state equation run for shot\n", - "HEAD Functional value for shot 105: loss 7.975154e-01 for shot 105\n", - "WORKER:0:1 (ShotID 105) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 105) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.63 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 42.89 GFlops/s, 0.88 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.54 s [OI=2.82, 47.92 GFlops/s, 1.05 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.82 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 19.90 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 94) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 94\n", - "HEAD Giving shot 107 to worker:0:0\n", - "WORKER:0:0 (ShotID 107) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 107) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 107) Spatial grid spacing (0.500 mm | 4.139 PPW) is higher than dispersion limit (0.414 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 107) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 107) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 107) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 107) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.63 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 42.89 GFlops/s, 0.88 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.55 s [OI=2.82, 46.89 GFlops/s, 1.02 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 5.12 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 21.26 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 105) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 105\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.49 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 56.43 GFlops/s, 1.13 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.45 s [OI=2.82, 57.76 GFlops/s, 1.26 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.13 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.34 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.04 s [OI=0.50, 63.99 GFlops/s, 16.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 107) Completed state equation run for shot\n", - "HEAD Functional value for shot 107: loss 7.735520e-01 for shot 107\n", - "WORKER:0:0 (ShotID 107) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 107) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.45 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 60.04 GFlops/s, 1.23 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.40 s [OI=2.82, 64.83 GFlops/s, 1.41 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 6.27 GFlops/s, 0.11 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.04 s [OI=0.25, 41.15 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 107) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 107\n", - "MONITOR Pending barrier tasks 1\n", - "HEAD Updating variable vp,\n", - "HEAD \t grad before processing in range [-2.889714e-04, 2.582439e-04]\n", - "HEAD \t grad after processing in range [-1.000000e+00, 8.933002e-01]\n", - "HEAD \t variable range before update [1.479618e+03, 1.538667e+03]\n", - "HEAD \t variable range after update [1.474682e+03, 1.542711e+03]\n", - "HEAD Done iteration 3 (out of 4), block 2 (out of 2) - Total loss_freq 1.400848e+01\n", - "HEAD ====================================================================\n", - "HEAD Starting iteration 4 (out of 4), block 2 (out of 2)\n", - "HEAD Giving shot 4 to worker:0:0\n", - "HEAD Giving shot 12 to worker:0:1\n", - "WORKER:0:1 (ShotID 12) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 12) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 12) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 12) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 12) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 12) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 12) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 (ShotID 4) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 4) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 4) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 4) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 4) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 4) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 4) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.54 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 51.20 GFlops/s, 1.03 GPts/s]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.49 s [OI=2.82, 52.48 GFlops/s, 1.15 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.14 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.48 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 54.57 GFlops/s, 13.65 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 4) Completed state equation run for shot\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.63 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 43.89 GFlops/s, 0.88 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.58 s [OI=2.82, 44.52 GFlops/s, 0.97 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.14 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.43 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 47.38 GFlops/s, 11.85 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 12) Completed state equation run for shot\n", - "HEAD Functional value for shot 4: loss 1.158213e+00 for shot 4\n", - "WORKER:0:0 (ShotID 4) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 4) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "HEAD Functional value for shot 12: loss 1.083143e+00 for shot 12\n", - "WORKER:0:1 (ShotID 12) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 12) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.56 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 48.25 GFlops/s, 0.99 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.48 s [OI=2.82, 53.62 GFlops/s, 1.17 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 5.35 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.07 s [OI=0.25, 23.37 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 4) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 4\n", - "HEAD Giving shot 26 to worker:0:0\n", - "WORKER:0:0 (ShotID 26) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 26) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 26) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 26) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 26) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 26) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 26) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.74 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 36.51 GFlops/s, 0.75 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.65 s [OI=2.82, 39.21 GFlops/s, 0.86 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.78 GFlops/s, 0.08 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 20.46 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 12) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 12\n", - "HEAD Giving shot 34 to worker:0:1\n", - "WORKER:0:1 (ShotID 34) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 34) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 34) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 34) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 34) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 34) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 34) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.61 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 45.33 GFlops/s, 0.91 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.55 s [OI=2.82, 46.54 GFlops/s, 1.02 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.08 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 51.07 GFlops/s, 12.77 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 26) Completed state equation run for shot\n", - "HEAD Functional value for shot 26: loss 1.402728e+00 for shot 26\n", - "WORKER:0:0 (ShotID 26) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 26) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.60 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 46.08 GFlops/s, 0.93 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.55 s [OI=2.82, 46.97 GFlops/s, 1.03 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.13 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.17 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 52.35 GFlops/s, 13.09 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 34) Completed state equation run for shot\n", - "HEAD Functional value for shot 34: loss 1.525372e+00 for shot 34\n", - "WORKER:0:1 (ShotID 34) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 34) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.65 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 41.57 GFlops/s, 0.86 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.56 s [OI=2.82, 46.17 GFlops/s, 1.01 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.71 GFlops/s, 0.08 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 19.50 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 26) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 26\n", - "HEAD Giving shot 38 to worker:0:0\n", - "WORKER:0:0 (ShotID 38) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 38) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 38) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 38) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 38) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 38) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 38) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.66 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 40.94 GFlops/s, 0.84 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.57 s [OI=2.82, 44.86 GFlops/s, 0.98 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.66 GFlops/s, 0.08 GPts/s]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:1 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 20.39 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 34) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 34\n", - "HEAD Giving shot 40 to worker:0:1\n", - "WORKER:0:1 (ShotID 40) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 40) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 40) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 40) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 40) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 40) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 40) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.57 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 48.51 GFlops/s, 0.97 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.53 s [OI=2.82, 48.87 GFlops/s, 1.07 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.13 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.30 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.04 s [OI=0.50, 58.87 GFlops/s, 14.72 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 38) Completed state equation run for shot\n", - "HEAD Functional value for shot 38: loss 1.433229e+00 for shot 38\n", - "WORKER:0:0 (ShotID 38) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 38) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.56 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 49.38 GFlops/s, 0.99 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.51 s [OI=2.82, 50.38 GFlops/s, 1.10 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.14 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.41 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.04 s [OI=0.50, 56.24 GFlops/s, 14.06 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 40) Completed state equation run for shot\n", - "HEAD Functional value for shot 40: loss 1.138412e+00 for shot 40\n", - "WORKER:0:1 (ShotID 40) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 40) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.63 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 42.89 GFlops/s, 0.88 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.54 s [OI=2.82, 47.22 GFlops/s, 1.03 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 5.00 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 21.39 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 38) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 38\n", - "HEAD Giving shot 42 to worker:0:0\n", - "WORKER:0:0 (ShotID 42) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 42) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 42) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 42) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 42) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 42) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 42) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.67 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 40.33 GFlops/s, 0.83 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.58 s [OI=2.82, 44.04 GFlops/s, 0.96 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.72 GFlops/s, 0.08 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.07 s [OI=0.25, 21.95 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 40) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 40\n", - "HEAD Giving shot 45 to worker:0:1\n", - "WORKER:0:1 (ShotID 45) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 45) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 45) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 45) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 45) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 45) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 45) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.68 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 40.66 GFlops/s, 0.82 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.62 s [OI=2.82, 41.33 GFlops/s, 0.90 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.16 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.06 s [OI=0.50, 43.77 GFlops/s, 10.95 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 42) Completed state equation run for shot\n", - "HEAD Functional value for shot 42: loss 1.068982e+00 for shot 42\n", - "WORKER:0:0 (ShotID 42) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 42) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.55 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 50.27 GFlops/s, 1.01 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.50 s [OI=2.82, 51.30 GFlops/s, 1.12 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.13 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.27 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.04 s [OI=0.50, 55.43 GFlops/s, 13.86 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 45) Completed state equation run for shot\n", - "HEAD Functional value for shot 45: loss 1.383274e+00 for shot 45\n", - "WORKER:0:1 (ShotID 45) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 45) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.65 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 41.57 GFlops/s, 0.86 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.56 s [OI=2.82, 45.87 GFlops/s, 1.00 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.81 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 20.41 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:0 (ShotID 42) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 42\n", - "HEAD Giving shot 46 to worker:0:0\n", - "WORKER:0:0 (ShotID 46) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 46) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 46) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 46) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 46) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 46) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 46) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.70 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 38.60 GFlops/s, 0.79 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.61 s [OI=2.82, 42.22 GFlops/s, 0.92 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.74 GFlops/s, 0.08 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 20.67 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 45) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 45\n", - "HEAD Giving shot 59 to worker:0:1\n", - "WORKER:0:1 (ShotID 59) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 59) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 59) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 59) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 59) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 59) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 59) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.62 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 44.60 GFlops/s, 0.90 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.57 s [OI=2.82, 45.25 GFlops/s, 0.99 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.17 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 50.75 GFlops/s, 12.69 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 46) Completed state equation run for shot\n", - "HEAD Functional value for shot 46: loss 1.293593e+00 for shot 46\n", - "WORKER:0:0 (ShotID 46) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 46) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.65 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 42.54 GFlops/s, 0.86 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.60 s [OI=2.82, 42.91 GFlops/s, 0.94 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.15 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 51.60 GFlops/s, 12.90 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 59) Completed state equation run for shot\n", - "HEAD Functional value for shot 59: loss 1.215001e+00 for shot 59\n", - "WORKER:0:1 (ShotID 59) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 59) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.67 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 40.33 GFlops/s, 0.83 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.58 s [OI=2.82, 43.98 GFlops/s, 0.96 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.66 GFlops/s, 0.08 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 21.68 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 46) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 46\n", - "HEAD Giving shot 74 to worker:0:0\n", - "WORKER:0:0 (ShotID 74) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 74) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 74) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 74) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 74) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 74) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 74) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.64 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 42.22 GFlops/s, 0.87 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.56 s [OI=2.82, 46.15 GFlops/s, 1.01 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.90 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 21.66 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 59) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 59\n", - "HEAD Giving shot 77 to worker:0:1\n", - "WORKER:0:1 (ShotID 77) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 77) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 77) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 77) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 77) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 77) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 77) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.65 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 42.54 GFlops/s, 0.86 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.59 s [OI=2.82, 43.38 GFlops/s, 0.95 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.11 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 51.58 GFlops/s, 12.90 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 74) Completed state equation run for shot\n", - "HEAD Functional value for shot 74: loss 1.264620e+00 for shot 74\n", - "WORKER:0:0 (ShotID 74) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 74) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.56 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 49.38 GFlops/s, 0.99 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.51 s [OI=2.82, 50.17 GFlops/s, 1.10 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.09 GFlops/s, 0.00 GPts/s]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:1 * section3<2499,456,485> ran in 0.04 s [OI=0.50, 58.49 GFlops/s, 14.63 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 77) Completed state equation run for shot\n", - "HEAD Functional value for shot 77: loss 1.185848e+00 for shot 77\n", - "WORKER:0:1 (ShotID 77) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 77) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.64 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 42.22 GFlops/s, 0.87 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.55 s [OI=2.82, 46.59 GFlops/s, 1.02 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.91 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 21.13 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 74) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 74\n", - "HEAD Giving shot 100 to worker:0:0\n", - "WORKER:0:0 (ShotID 100) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 100) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 100) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 100) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 100) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 100) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 100) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.67 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 40.33 GFlops/s, 0.83 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.59 s [OI=2.82, 43.69 GFlops/s, 0.95 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.63 GFlops/s, 0.08 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 21.25 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 77) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 77\n", - "HEAD Giving shot 111 to worker:0:1\n", - "WORKER:0:1 (ShotID 111) Preparing to run state for shot\n", - "WORKER:0:1 (ShotID 111) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:1 (ShotID 111) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:1 (ShotID 111) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:1 (ShotID 111) Selected undersampling level 4\n", - "WORKER:0:1 (ShotID 111) Selected time stepping scheme OT2\n", - "WORKER:0:1 (ShotID 111) Running state equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.59 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 46.87 GFlops/s, 0.94 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.53 s [OI=2.82, 48.04 GFlops/s, 1.05 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.13 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.23 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 53.52 GFlops/s, 13.38 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 100) Completed state equation run for shot\n", - "HEAD Functional value for shot 100: loss 1.048634e+00 for shot 100\n", - "WORKER:0:0 (ShotID 100) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 100) Running adjoint equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_state` ran in 0.59 s\n", - "WORKER:0:1 Global performance: [OI=2.06, 46.87 GFlops/s, 0.94 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.53 s [OI=2.82, 48.23 GFlops/s, 1.05 GPts/s]\n", - "WORKER:0:1 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.12 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:1 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.10 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 * section3<2499,456,485> ran in 0.05 s [OI=0.50, 52.70 GFlops/s, 13.18 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 111) Completed state equation run for shot\n", - "HEAD Functional value for shot 111: loss 1.281054e+00 for shot 111\n", - "WORKER:0:1 (ShotID 111) Preparing to run adjoint for shot\n", - "WORKER:0:1 (ShotID 111) Running adjoint equation for shot\n", - "WORKER:0:1 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.72 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 37.53 GFlops/s, 0.77 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.63 s [OI=2.82, 40.77 GFlops/s, 0.89 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 4.43 GFlops/s, 0.08 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.08 s [OI=0.25, 20.32 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 100) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 100\n", - "HEAD Giving shot 115 to worker:0:0\n", - "WORKER:0:0 (ShotID 115) Preparing to run state for shot\n", - "WORKER:0:0 (ShotID 115) Estimated bandwidth for the propagated wavelet 0.245-0.715 MHz\n", - "WORKER:0:0 (ShotID 115) Spatial grid spacing (0.500 mm | 4.125 PPW) is higher than dispersion limit (0.412 mm | 5.000 PPW)\n", - "WORKER:0:0 (ShotID 115) Time grid spacing (0.080 μs | 24%) is below OT2 limit (0.146 μs)\n", - "WORKER:0:0 (ShotID 115) Selected undersampling level 4\n", - "WORKER:0:0 (ShotID 115) Selected time stepping scheme OT2\n", - "WORKER:0:0 (ShotID 115) Running state equation for shot\n", - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:1 Operator `acoustic_iso_adjoint` ran in 0.61 s\n", - "WORKER:0:1 Global performance: [OI=1.79, 44.30 GFlops/s, 0.91 GPts/s]\n", - "WORKER:0:1 Local performance:\n", - "WORKER:0:1 * section0<2499,456,485> ran in 0.53 s [OI=2.82, 48.20 GFlops/s, 1.05 GPts/s]\n", - "WORKER:0:1 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 5.16 GFlops/s, 0.09 GPts/s]\n", - "WORKER:0:1 * section2<2499,376,405> ran in 0.07 s [OI=0.25, 22.55 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:1 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:1 (ShotID 111) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 111\n", - "WORKER:0:0 Operator `acoustic_iso_state` ran in 0.46 s\n", - "WORKER:0:0 Global performance: [OI=2.06, 60.11 GFlops/s, 1.21 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.42 s [OI=2.82, 60.91 GFlops/s, 1.33 GPts/s]\n", - "WORKER:0:0 * section1<<2499,1,2,2>,<2499,1,2,2>> ran in 0.01 s [OI=5.80, 0.16 GFlops/s, 0.01 GPts/s]\n", - "WORKER:0:0 * section2<<2499,120>,<2499,120,2,2>> ran in 0.01 s [OI=1.84, 2.65 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 * section3<2499,456,485> ran in 0.04 s [OI=0.50, 66.20 GFlops/s, 16.55 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 115) Completed state equation run for shot\n", - "HEAD Functional value for shot 115: loss 1.354216e+00 for shot 115\n", - "WORKER:0:0 (ShotID 115) Preparing to run adjoint for shot\n", - "WORKER:0:0 (ShotID 115) Running adjoint equation for shot\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WORKER:0:0 AutoTuner: could not perform any runs\n", - "WORKER:0:0 Operator `acoustic_iso_adjoint` ran in 0.46 s\n", - "WORKER:0:0 Global performance: [OI=1.79, 58.74 GFlops/s, 1.21 GPts/s]\n", - "WORKER:0:0 Local performance:\n", - "WORKER:0:0 * section0<2499,456,485> ran in 0.41 s [OI=2.82, 63.00 GFlops/s, 1.37 GPts/s]\n", - "WORKER:0:0 * section1<<2499,120,2,2>,<2499,120,2,2>> ran in 0.02 s [OI=6.00, 6.41 GFlops/s, 0.11 GPts/s]\n", - "WORKER:0:0 * section2<2499,376,405> ran in 0.04 s [OI=0.25, 39.54 GFlops/s, 0.00 GPts/s]\n", - "WORKER:0:0 Performance[mode=advanced-fsg] arguments: {'nthreads': 3, 'nthreads_nonaffine': 3}\n", - "WORKER:0:0 (ShotID 115) Completed adjoint equation run for shot\n", - "HEAD Retrieved gradient for shot 115\n", - "MONITOR Pending barrier tasks 1\n", - "HEAD Updating variable vp,\n", - "HEAD \t grad before processing in range [-5.321078e-04, 1.947885e-04]\n", - "HEAD \t grad after processing in range [-1.000000e+00, 3.660839e-01]\n", - "HEAD \t variable range before update [1.474682e+03, 1.542711e+03]\n", - "HEAD \t variable range after update [1.477018e+03, 1.548610e+03]\n", - "HEAD Done iteration 4 (out of 4), block 2 (out of 2) - Total loss_freq 1.883632e+01\n", - "HEAD ====================================================================\n" - ] - }, { "data": { "application/javascript": [ @@ -3758,15 +2967,14 @@ " traces = process_traces(modelled, observed, f_max=f_max, filter_relaxation=0.75, runtime=worker)\n", " # and use these pre-processed versions to calculate the\n", " # value of the loss_freq function\n", - " fun = await loss(traces.outputs[0], traces.outputs[1],\n", - " problem=sub_problem, runtime=worker).result()\n", + " fun = loss(traces.outputs[0], traces.outputs[1],\n", + " problem=sub_problem, runtime=worker)\n", "\n", - " iteration.add_loss(fun)\n", - " runtime.logger.info('Functional value for shot %d: %s' % (shot_id, fun))\n", + " # run adjoint\n", + " fun_value = await fun.remote.adjoint().result()\n", "\n", - " # Now, we can calculate the gradient by executing the adjoint of the\n", - " # forward process\n", - " await fun.adjoint()\n", + " iteration.add_loss(fun_value)\n", + " runtime.logger.info('Functional value for shot %d: %s' % (shot_id, fun_value))\n", "\n", " runtime.logger.info('Retrieved gradient for shot %d' % sub_problem.shot_id)\n", "\n", @@ -3854,7 +3062,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.8" } }, "nbformat": 4,