From 7027843138ceec001099db13dd5061141525f118 Mon Sep 17 00:00:00 2001 From: nikhilkhatri Date: Fri, 14 Apr 2023 12:59:47 +0100 Subject: [PATCH] Release version 0.3.1 Co-authored-by: Thomas Hoffmann Co-authored-by: Dimitri Kartsaklis Co-authored-by: Charles London --- .github/workflows/build_test.yml | 19 ++- docs/_static/images/Quantinuum_logo.png | Bin 0 -> 18245 bytes docs/clean_notebooks.py | 35 +++++ docs/conf.py | 2 +- docs/discopy.rst | 9 +- docs/examples/classical_pipeline.ipynb | 19 ++- docs/examples/parser.ipynb | 2 +- docs/examples/pennylane.ipynb | 171 +++++++++++++++------- docs/examples/quantum_pipeline.ipynb | 19 ++- docs/examples/quantum_pipeline_jax.ipynb | 19 ++- docs/examples/reader.ipynb | 2 +- docs/examples/rewrite.ipynb | 2 +- docs/examples/tensor.ipynb | 2 +- docs/examples/tree_reader.ipynb | 2 +- docs/index.rst | 6 +- docs/release_notes.rst | 16 +++ docs/tutorials/discocat.ipynb | 86 ++++------- docs/tutorials/extend-lambeq.ipynb | 144 +++++++++---------- docs/tutorials/trainer_classical.ipynb | 21 ++- docs/tutorials/trainer_hybrid.ipynb | 173 +++++++++++++---------- docs/tutorials/trainer_quantum.ipynb | 20 ++- docs/tutorials/training-symbols.ipynb | 58 ++++---- docs/tutorials/training-usecase.ipynb | 18 +++ setup.cfg | 4 +- 24 files changed, 533 insertions(+), 316 deletions(-) create mode 100644 docs/_static/images/Quantinuum_logo.png create mode 100644 docs/clean_notebooks.py diff --git a/.github/workflows/build_test.yml b/.github/workflows/build_test.yml index 0ae1cb92..88a11c36 100644 --- a/.github/workflows/build_test.yml +++ b/.github/workflows/build_test.yml @@ -11,6 +11,7 @@ on: env: SRC_DIR: lambeq TEST_DIR: tests + DOCS_DIR: docs jobs: lint: @@ -76,7 +77,7 @@ jobs: --doctest-modules --durations=50 --ignore=${{ env.TEST_DIR }}/text2diagram/test_depccg_parser.py - --ignore=docs/extract_code_cells.py + --ignore=${{ env.DOCS_DIR }}/extract_code_cells.py - name: Determine if depccg tests should be run # only test depccg if it is explicitly changed, since it is very slow # tests are also disabled on Python 3.11 @@ -108,6 +109,22 @@ jobs: if: steps.depccg-enabled.outcome == 'success' continue-on-error: true run: coverage run --append --source=${{ env.SRC_DIR }} -m pytest -k test_depccg_parser.py + - name: Preparation for notebook testing + run: pip install nbmake + - name: Test example notebooks + env: + TEST_NOTEBOOKS: 1 + run: > + pytest --nbmake ${{ env.DOCS_DIR }}/examples/ + --nbmake-timeout=60 + - name: Test tutorial notebooks + env: + TEST_NOTEBOOKS: 1 + run: > + pytest --nbmake ${{ env.DOCS_DIR }}/tutorials/ + --nbmake-timeout=60 + --ignore ${{ env.DOCS_DIR }}/tutorials/trainer_hybrid.ipynb + --ignore ${{ env.DOCS_DIR }}/tutorials/code - name: Coverage report run: coverage report -m type_check: diff --git a/docs/_static/images/Quantinuum_logo.png b/docs/_static/images/Quantinuum_logo.png new file mode 100644 index 0000000000000000000000000000000000000000..5569581b8e420f14eee561cbf1bf78ca0c96882f GIT binary patch literal 18245 zcmeIa`8$-~{{Vd3_mHw?s}PcX-^r3}VF+1Dma(Pm36u3*C@r?^+t{*Y#+tooQ5gH! 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At its core, DisCoPy is a Python library that allows computation with :term:`monoidal categories `. The main data structure is that of a *monoidal diagram*, or :ref:`string diagram `, which is the format that ``lambeq`` uses internally to encode a sentence (:py:class:`discopy.rigid.Diagram`). DisCoPy makes this easy, by offering many language-related features, such as support for :term:`pregroup grammars ` and :term:`functors ` for implementing :term:`compositional models ` such as :term:`DisCoCat`. Furthermore, from a quantum computing perspective, DisCoPy provides abstractions for creating all standard :term:`quantum gates ` and building :term:`quantum circuits `, which are used by ``lambeq`` in the final stages of the :ref:`pipeline `. +While the :ref:`parser ` provides ``lambeq``'s input, `DisCoPy `_ [FTC2020]_ is ``lambeq``'s underlying engine, the component where all the low-level processing takes place. At its core, DisCoPy is a Python library that allows computation with :term:`monoidal categories `. The main data structure is that of a *monoidal diagram*, or :ref:`string diagram `, which is the format that ``lambeq`` uses internally to encode a sentence (:py:class:`discopy.rigid.Diagram`). DisCoPy makes this easy, by offering many language-related features, such as support for :term:`pregroup grammars ` and :term:`functors ` for implementing :term:`compositional models ` such as :term:`DisCoCat`. Furthermore, from a quantum computing perspective, DisCoPy provides abstractions for creating all standard :term:`quantum gates ` and building :term:`quantum circuits `, which are used by ``lambeq`` in the final stages of the :ref:`pipeline `. Thus, it is not a surprise that the advanced use of ``lambeq``, involving extending the toolkit with new :term:`compositional models ` and :term:`ansätze `, requires some familiarity of DisCoPy. For this, you can use the following resources: - For a gentle introduction to basic DisCoPy concepts, start with ``lambeq``'s tutorial :ref:`sec-advanced`. -- The `basic example notebooks `_ in DisCoPy documentation provide another good starting point. -- The `advanced tutorials `_ in DisCoPy documentation can help you to delve further into DisCoPy. +- The `basic example notebooks `_ in DisCoPy documentation provide another good starting point. +- The `advanced tutorials `_ in DisCoPy documentation can help you to delve further into DisCoPy. -.. rubric:: Footnotes - -.. [#f1] https://github.com/oxford-quantum-group/discopy diff --git a/docs/examples/classical_pipeline.ipynb b/docs/examples/classical_pipeline.ipynb index 46b347a2..91ab0711 100644 --- a/docs/examples/classical_pipeline.ipynb +++ b/docs/examples/classical_pipeline.ipynb @@ -59,6 +59,23 @@ "test_labels, test_data = read_data('datasets/mc_test_data.txt')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "nbsphinx": "hidden" + }, + "outputs": [], + "source": [ + "TESTING = int(os.environ.get('TEST_NOTEBOOKS', '0'))\n", + "\n", + "if TESTING:\n", + " train_labels, train_data = train_labels[:2], train_data[:2]\n", + " dev_labels, dev_data = dev_labels[:2], dev_data[:2]\n", + " test_labels, test_data = test_labels[:2], test_data[:2]\n", + " EPOCHS = 1" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -306,5 +323,5 @@ } }, "nbformat": 4, - "nbformat_minor": 5 + "nbformat_minor": 4 } diff --git a/docs/examples/parser.ipynb b/docs/examples/parser.ipynb index bcc94690..e9787517 100644 --- a/docs/examples/parser.ipynb +++ b/docs/examples/parser.ipynb @@ -64,5 +64,5 @@ } }, "nbformat": 4, - "nbformat_minor": 5 + "nbformat_minor": 4 } diff --git a/docs/examples/pennylane.ipynb b/docs/examples/pennylane.ipynb index a3c1d63a..ee562723 100644 --- a/docs/examples/pennylane.ipynb +++ b/docs/examples/pennylane.ipynb @@ -63,6 +63,25 @@ "test_labels, test_data = read_data('datasets/mc_test_data.txt')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "nbsphinx": "hidden" + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "TESTING = int(os.environ.get('TEST_NOTEBOOKS', '0'))\n", + "\n", + "if TESTING:\n", + " train_labels, train_data = train_labels[:3], train_data[:3]\n", + " dev_labels, dev_data = dev_labels[:3], dev_data[:3]\n", + " test_labels, test_data = test_labels[:3], test_data[:3]\n", + " EPOCHS = 1" + ] + }, { "cell_type": "code", "execution_count": 4, @@ -108,7 +127,7 @@ "outputs": [ { "data": { - 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", 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", 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" ] @@ -141,7 +160,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -181,8 +200,7 @@ "all_circuits = train_circuits + dev_circuits + test_circuits\n", "\n", "model = PennyLaneModel.from_diagrams(all_circuits)\n", - "model.initialise_weights()\n", - "model = model.double()" + "model.initialise_weights()" ] }, { @@ -232,7 +250,7 @@ " torch.argmax(y, dim=1)).sum().item()/len(y)\n", "\n", "def loss(y_hat, y):\n", - " return torch.nn.functional.mse_loss(y_hat, y.double())" + " return torch.nn.functional.mse_loss(y_hat, y)" ] }, { @@ -244,21 +262,21 @@ "name": "stderr", "output_type": "stream", "text": [ - "Epoch 1: train/loss: 0.2386 valid/loss: 0.1175 train/acc: 0.6429 valid/acc: 0.9000\n", - "Epoch 2: train/loss: 0.0845 valid/loss: 0.0676 train/acc: 0.8857 valid/acc: 0.9333\n", - "Epoch 3: train/loss: 0.0357 valid/loss: 0.0626 train/acc: 0.9857 valid/acc: 0.9667\n", - "Epoch 4: train/loss: 0.0328 valid/loss: 0.0299 train/acc: 0.9714 valid/acc: 0.9667\n", - "Epoch 5: train/loss: 0.0144 valid/loss: 0.0213 train/acc: 0.9857 valid/acc: 1.0000\n", - "Epoch 6: train/loss: 0.0092 valid/loss: 0.0181 train/acc: 1.0000 valid/acc: 1.0000\n", - "Epoch 7: train/loss: 0.0062 valid/loss: 0.0173 train/acc: 1.0000 valid/acc: 0.9667\n", - "Epoch 8: train/loss: 0.0083 valid/loss: 0.0215 train/acc: 1.0000 valid/acc: 1.0000\n", - "Epoch 9: train/loss: 0.0113 valid/loss: 0.0323 train/acc: 1.0000 valid/acc: 0.9667\n", - "Epoch 10: train/loss: 0.0100 valid/loss: 0.0237 train/acc: 1.0000 valid/acc: 0.9667\n", - "Epoch 11: train/loss: 0.0071 valid/loss: 0.0194 train/acc: 1.0000 valid/acc: 0.9667\n", - "Epoch 12: train/loss: 0.0076 valid/loss: 0.0196 train/acc: 1.0000 valid/acc: 0.9667\n", - "Epoch 13: train/loss: 0.0060 valid/loss: 0.0182 train/acc: 1.0000 valid/acc: 1.0000\n", - "Epoch 14: train/loss: 0.0085 valid/loss: 0.0216 train/acc: 1.0000 valid/acc: 0.9667\n", - "Epoch 15: train/loss: 0.0084 valid/loss: 0.0250 train/acc: 1.0000 valid/acc: 0.9667\n", + "Epoch 1: train/loss: 0.1778 valid/loss: 0.1430 train/acc: 0.7286 valid/acc: 0.8000\n", + "Epoch 2: train/loss: 0.1054 valid/loss: 0.1081 train/acc: 0.8857 valid/acc: 0.9000\n", + "Epoch 3: train/loss: 0.0716 valid/loss: 0.0658 train/acc: 0.9286 valid/acc: 0.9000\n", + "Epoch 4: train/loss: 0.0618 valid/loss: 0.0262 train/acc: 0.9429 valid/acc: 0.9667\n", + "Epoch 5: train/loss: 0.0427 valid/loss: 0.0468 train/acc: 0.9714 valid/acc: 0.9333\n", + "Epoch 6: train/loss: 0.0159 valid/loss: 0.0261 train/acc: 0.9714 valid/acc: 0.9667\n", + "Epoch 7: train/loss: 0.0212 valid/loss: 0.0130 train/acc: 0.9857 valid/acc: 1.0000\n", + "Epoch 8: train/loss: 0.0192 valid/loss: 0.0246 train/acc: 0.9714 valid/acc: 1.0000\n", + "Epoch 9: train/loss: 0.0804 valid/loss: 0.1782 train/acc: 0.9143 valid/acc: 0.6667\n", + "Epoch 10: train/loss: 0.0386 valid/loss: 0.1091 train/acc: 0.9286 valid/acc: 0.8667\n", + "Epoch 11: train/loss: 0.0384 valid/loss: 0.0877 train/acc: 0.9571 valid/acc: 0.8667\n", + "Epoch 12: train/loss: 0.0226 valid/loss: 0.0855 train/acc: 0.9857 valid/acc: 0.8667\n", + "Epoch 13: train/loss: 0.0211 valid/loss: 0.0244 train/acc: 0.9714 valid/acc: 0.9333\n", + "Epoch 14: train/loss: 0.0121 valid/loss: 0.0616 train/acc: 1.0000 valid/acc: 0.9333\n", + "Epoch 15: train/loss: 0.0456 valid/loss: 0.0387 train/acc: 0.9571 valid/acc: 1.0000\n", "\n", "Training completed!\n" ] @@ -298,7 +316,7 @@ { "data": { "text/plain": [ - "1.0" + "0.9" ] }, "execution_count": 11, @@ -346,18 +364,20 @@ "output_type": "stream", "text": [ "Epoch: 0\n", - "Train loss: 1.40214268863387\n", - "Dev acc: 0.6666666666666666\n", + "Train loss: 1.61824881285429\n", + "Dev acc: 0.6333333333333333\n", "Epoch: 5\n", - "Train loss: 0.09461445044355091\n", - "Dev acc: 1.0\n", + "Train loss: 0.4483018293976784\n", + "Dev acc: 0.8666666666666667\n", "Epoch: 10\n", - "Train loss: 0.03627023935725044\n", - "Dev acc: 1.0\n" + "Train loss: 0.07727803220041096\n", + "Dev acc: 0.9333333333333333\n" ] } ], "source": [ + "import pickle\n", + "\n", "model = PennyLaneModel.from_diagrams(all_circuits)\n", "model.initialise_weights()\n", "optimizer = torch.optim.Adam(model.parameters(), lr=0.1)\n", @@ -369,8 +389,10 @@ " for circuits, labels in train_dataset:\n", " optimizer.zero_grad()\n", " probs = model(circuits)\n", + " d_type = model.weights[0].dtype\n", + " probs = probs.to(d_type)\n", " loss = torch.nn.functional.mse_loss(probs, \n", - " torch.tensor(labels).double())\n", + " torch.tensor(labels))\n", " epoch_loss += loss.item()\n", " loss.backward()\n", " optimizer.step()\n", @@ -385,10 +407,14 @@ " if dev_acc > best['acc']:\n", " best['acc'] = dev_acc\n", " best['epoch'] = i\n", - " model.make_checkpoint(\"model.lt\")\n", + " checkpoint = model._make_checkpoint()\n", + " with open(\"model.lt\", \"wb+\") as f:\n", + " pickle.dump(checkpoint, f)\n", " elif i - best['epoch'] >= 10:\n", " print(\"Early stopping\")\n", - " model = PennyLaneModel.from_checkpoint(\"model.lt\")\n", + " with open(\"model.lt\", \"rb\") as f:\n", + " checkpoint = pickle.load(f)\n", + " model = PennyLaneModel._load_checkpoint(checkpoint)\n", " break\n", " " ] @@ -408,7 +434,7 @@ { "data": { "text/plain": [ - "1.0" + "0.9666666666666667" ] }, "execution_count": 14, @@ -461,8 +487,8 @@ "from torch import nn\n", "\n", "class XORSentenceModel(PennyLaneModel):\n", - " def __init__(self):\n", - " PennyLaneModel.__init__(self)\n", + " def __init__(self, **kwargs):\n", + " PennyLaneModel.__init__(self, **kwargs)\n", " \n", " self.xor_net = nn.Sequential(\n", " nn.Linear(4, 10),\n", @@ -522,14 +548,35 @@ "execution_count": 18, "metadata": {}, "outputs": [], + "source": [ + "TRAIN_SAMPLES, DEV_SAMPLES, TEST_SAMPLES = 300, 200, 200" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "nbsphinx": "hidden" + }, + "outputs": [], + "source": [ + "if TESTING:\n", + " TRAIN_SAMPLES, DEV_SAMPLES, TEST_SAMPLES = 2, 2, 2" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], "source": [ "train_pair_circuits, train_pair_labels = (\n", " zip(*random.sample(list(zip(train_pair_circuits, train_pair_labels)),\n", - " 300)))\n", + " TRAIN_SAMPLES)))\n", "dev_pair_circuits, dev_pair_labels = (\n", - " zip(*random.sample(list(zip(dev_pair_circuits, dev_pair_labels)), 200)))\n", + " zip(*random.sample(list(zip(dev_pair_circuits, dev_pair_labels)), DEV_SAMPLES)))\n", "test_pair_circuits, test_pair_labels = (\n", - " zip(*random.sample(list(zip(test_pair_circuits, test_pair_labels)), 200)))" + " zip(*random.sample(list(zip(test_pair_circuits, test_pair_labels)), TEST_SAMPLES)))" ] }, { @@ -541,7 +588,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -555,8 +602,8 @@ "model = model.double()\n", "\n", "train_pair_dataset = Dataset(train_pair_circuits,\n", - " train_pair_labels,\n", - " batch_size=BATCH_SIZE)\n", + " train_pair_labels,\n", + " batch_size=BATCH_SIZE)\n", "\n", "optimizer = torch.optim.Adam(model.parameters(), lr=0.1)" ] @@ -577,7 +624,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -589,7 +636,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -597,16 +644,34 @@ "output_type": "stream", "text": [ "Epoch: 0\n", - "Train loss: 4.216500047571801\n", - "Dev acc: 0.475\n", + "Train loss: 4.202134637529463\n", + "Dev acc: 0.445\n", "Epoch: 5\n", - "Train loss: 0.16129305933880816\n", - "Dev acc: 1.0\n", + "Train loss: 4.152931421145276\n", + "Dev acc: 0.54\n", "Epoch: 10\n", - "Train loss: 0.0008051177015249586\n", - "Dev acc: 1.0\n", + "Train loss: 3.9137668866046615\n", + "Dev acc: 0.62\n", "Epoch: 15\n", - "Train loss: 0.00016974739709550384\n", + "Train loss: 3.4010897127113733\n", + "Dev acc: 0.655\n", + "Epoch: 20\n", + "Train loss: 2.41645528073079\n", + "Dev acc: 0.825\n", + "Epoch: 25\n", + "Train loss: 2.5319179155031915\n", + "Dev acc: 0.885\n", + "Epoch: 30\n", + "Train loss: 0.2144302081166329\n", + "Dev acc: 0.995\n", + "Epoch: 35\n", + "Train loss: 0.07569202568470873\n", + "Dev acc: 1.0\n", + "Epoch: 40\n", + "Train loss: 0.04757411482113485\n", + "Dev acc: 1.0\n", + "Epoch: 45\n", + "Train loss: 0.033591968613830424\n", "Dev acc: 1.0\n", "Early stopping\n" ] @@ -636,17 +701,17 @@ " if dev_acc > best['acc']:\n", " best['acc'] = dev_acc\n", " best['epoch'] = i\n", - " model.make_checkpoint(\"xor_model.lt\")\n", + " model.save(\"xor_model.lt\")\n", " elif i - best['epoch'] >= 10:\n", " print(\"Early stopping\")\n", - " model = XORSentenceModel.from_checkpoint(\"xor_model.lt\")\n", + " model.load(\"xor_model.lt\")\n", " model = model.double()\n", " break" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "metadata": {}, "outputs": [ { @@ -655,7 +720,7 @@ "1.0" ] }, - "execution_count": 22, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -671,5 +736,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/docs/examples/quantum_pipeline.ipynb b/docs/examples/quantum_pipeline.ipynb index eff17781..917b706a 100644 --- a/docs/examples/quantum_pipeline.ipynb +++ b/docs/examples/quantum_pipeline.ipynb @@ -61,6 +61,23 @@ "test_labels, test_data = read_data('datasets/mc_test_data.txt')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "nbsphinx": "hidden" + }, + "outputs": [], + "source": [ + "TESTING = int(os.environ.get('TEST_NOTEBOOKS', '0'))\n", + "\n", + "if TESTING:\n", + " train_labels, train_data = train_labels[:2], train_data[:2]\n", + " dev_labels, dev_data = dev_labels[:2], dev_data[:2]\n", + " test_labels, test_data = test_labels[:2], test_data[:2]\n", + " EPOCHS = 1" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -356,5 +373,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/docs/examples/quantum_pipeline_jax.ipynb b/docs/examples/quantum_pipeline_jax.ipynb index 994b6c40..fdc68c94 100644 --- a/docs/examples/quantum_pipeline_jax.ipynb +++ b/docs/examples/quantum_pipeline_jax.ipynb @@ -64,6 +64,23 @@ "test_labels, test_data = read_data('datasets/mc_test_data.txt')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "nbsphinx": "hidden" + }, + "outputs": [], + "source": [ + "TESTING = int(os.environ.get('TEST_NOTEBOOKS', '0'))\n", + "\n", + "if TESTING:\n", + " train_labels, train_data = train_labels[:2], train_data[:2]\n", + " dev_labels, dev_data = dev_labels[:2], dev_data[:2]\n", + " test_labels, test_data = test_labels[:2], test_data[:2]\n", + " EPOCHS = 1" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -360,5 +377,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/docs/examples/reader.ipynb b/docs/examples/reader.ipynb index 79dbc8c2..9d5bdeb9 100644 --- a/docs/examples/reader.ipynb +++ b/docs/examples/reader.ipynb @@ -137,5 +137,5 @@ } }, "nbformat": 4, - "nbformat_minor": 5 + "nbformat_minor": 4 } diff --git a/docs/examples/rewrite.ipynb b/docs/examples/rewrite.ipynb index 144c2683..707e57e1 100644 --- a/docs/examples/rewrite.ipynb +++ b/docs/examples/rewrite.ipynb @@ -816,5 +816,5 @@ } }, "nbformat": 4, - "nbformat_minor": 5 + "nbformat_minor": 4 } diff --git a/docs/examples/tensor.ipynb b/docs/examples/tensor.ipynb index 13700960..10600b35 100644 --- a/docs/examples/tensor.ipynb +++ b/docs/examples/tensor.ipynb @@ -154,5 +154,5 @@ } }, "nbformat": 4, - "nbformat_minor": 5 + "nbformat_minor": 4 } diff --git a/docs/examples/tree_reader.ipynb b/docs/examples/tree_reader.ipynb index 63a7fb1f..c8dbc574 100644 --- a/docs/examples/tree_reader.ipynb +++ b/docs/examples/tree_reader.ipynb @@ -101,5 +101,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/docs/index.rst b/docs/index.rst index 616f667e..6ba6a88d 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -1,11 +1,11 @@ lambeq ====== -.. image:: _static/images/CQ-logo.png - :width: 120px +.. image:: _static/images/Quantinuum_logo.png + :width: 240px :align: right -``lambeq`` is an open-source, modular, extensible high-level Python library for experimental :term:`Quantum Natural Language Processing ` (QNLP), created by `Cambridge Quantum `_'s QNLP team. At a high level, the library allows the conversion of any sentence to a :term:`quantum circuit`, based on a given :term:`compositional model` and certain parameterisation and choices of :term:`ansätze `, and facilitates :ref:`training ` for both quantum and classical NLP experiments. The notes for the latest release can be found :ref:`here `. +``lambeq`` is an open-source, modular, extensible high-level Python library for experimental :term:`Quantum Natural Language Processing ` (QNLP), created by `Quantinuum `_'s QNLP team. At a high level, the library allows the conversion of any sentence to a :term:`quantum circuit`, based on a given :term:`compositional model` and certain parameterisation and choices of :term:`ansätze `, and facilitates :ref:`training ` for both quantum and classical NLP experiments. The notes for the latest release can be found :ref:`here `. ``lambeq`` is available for Python 3.8 and higher, on Linux, macOS and Windows. To install, type: diff --git a/docs/release_notes.rst b/docs/release_notes.rst index e6560685..e21aaef6 100644 --- a/docs/release_notes.rst +++ b/docs/release_notes.rst @@ -4,6 +4,22 @@ Release notes ============= +.. _rel-0.3.1: + +`0.3.1 `_ +------------------------------------------------------------ + +Changed: + +- Added example and tutorial notebooks to tests. +- Dependencies: pinned the maximum version of Jax and Jaxlib to 0.4.6 to avoid a JIT-compilation error when using the :py:class:`~lambeq.NumpyModel`. + +Fixed: + +- Documentation: fixed broken DisCoPy links. +- Fixed PyTorch datatype errors in example and tutorial notebooks. +- Updated custom :term:`ansätze ` in tutorial notebook to match new structure of :py:class:`~lambeq.CircuitAnsatz` and :py:class:`~lambeq.TensorAnsatz`. + .. _rel-0.3.0: `0.3.0 `_ diff --git a/docs/tutorials/discocat.ipynb b/docs/tutorials/discocat.ipynb index 783c0298..35f53e31 100644 --- a/docs/tutorials/discocat.ipynb +++ b/docs/tutorials/discocat.ipynb @@ -49,14 +49,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "image/png": 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\n", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" }, { @@ -466,14 +452,12 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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\n", 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\n", 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\n", + "image/png": 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BnKE2btyIgwcPIiIi4p5hbWRkJCIiInDw4EG6uWAKLFiwAEVFRXjhhRfg8Xgm9RmPx4Pnn38eRUVFE95cAFAwZ7SNGzeiu7sblZWVyMrKglwux7Jly1BZWYnu7m4K5RSqqqqC1WrFhg0bJuw5HQ4H/vznP2NgYGBSNxcAFMwZTy6Xo6ysDPv27cPKlStRX1+PsrIyGr5OMYlEgrNnzyI6OhppaWnYuXPnPReETCYT3nzzTcybNw8KhQJnzpyZ8NxyCAUzSNATDKafRCLB4cOHUV9fD4/HgyVLlqCtrQ1msxmpqan405/+BK/Xi4sXL+Lw4cOTDiVA/48ZNOgJBoGzYMEC7N+/H7t27cK//vUvrFu3Dg0NDUhKSrqvMA5HwSREIBKJBHPnzoVYLPb7uT80lCWEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRTMICEWixETExPoMmY9l8uFtLQ0v9uhYAaJxMRE/PLLL5N+ahuZGq2trfB6vX63Q8EMEjk5OUhOTsa7774b6FJmLYvFgvLycrz66qt+t0WPFgkSoaGh+Oabb6DRaBAXF4eXXnoJYWH0zztdOjo6sGXLFhQVFaGkpMTv9qjHDCJJSUn48ccfcfr0aeTm5qK6unrSUymQB2O1WlFRUYHFixdj6dKl+OCDDwRpl4IZZB5++GHU1tZi3759qKioQE5ODt566y00NDQIcu5D7oTx66+/xsaNG5Geno4//vgDTU1NeO+99yAWiwXZBo11gpBIJEJxcTEKCwvR0NAAnU6HrVu3oq+vD0VFRXjsscegVquRnZ2NhISESc9OPRu5XC60tbXBYDBAr9ejrq4ODQ0NyM/Ph1arxf79+5GcnCz4dkW8n2OdXbt2weFwYNeuXULVRKbI9evX8cMPP6Cpqcm3o4lEIl9I1Wq1b1mlUs2qwDqdTly7ds33vRgMBhgMBphMJqSkpPi+l7y8PDz11FOTngbxQVGPOYtkZmaivLzc9zPP8/j9999H7IxnzpyBwWBAX18flEolYmJioFAoEBMTc8/yeO9FRERMa7DdbjdsNhv6+/thtVrR399/X8t2ux2ZmZm+g9P69euhVquxcOHCCWdVmwoUzFlMJBIhMTERiYmJvpmQh9jt9gl3ZrPZjJ6eHvT29sJiscBqtWJgYACDg4Nwu92QSqUIDw9HSEgIRCKR78/Qtu+uBbgzW/bQVPbDB3NDy8NfeZ6H2+0Gx3FwuVy+mc+GDhCxsbGIj49HXFwcFAoFVCoVcnJyxjyYsHQVm51KSMB5PB6YTCYYDAa0tbX5wjZWMG0224ggzJ0717eTy+VySKVSiMViXzBDQv7/WuNYwRSLxbh9+zaAsYM5tOz1euHxeMBxHJxOJ6xW64ga29vbYbFYEBISMmYYh5bnzJnj6y1ZmAOGgjkLcRwHo9E4Ygir1+thNBqRmJiI7OxsZGZmIi4uDhkZGaPuyAqFAtHR0Uz1MqPheR63bt3yBXasA82FCxdw6NAhGAwGSCQS3zn38HPv5OTkaRues/2tEkG43W5cvHgROp0O33//Pdra2jBv3jzfTldcXIwdO3YgKytryi9qTDeRSASZTAaZTIakpKQJ1+d5Hp2dnb6DlV6vx7fffguDwQCO45CXlwetVgutVguVSjVldVMwg9jPP/+MQ4cO4ezZs1CpVNBqtThy5Ahyc3MfeBaqYCcSiZCSkoKUlBQ8+eSTI97r6elBXV0ddDod3n77baSmpuKZZ57Byy+/jPj4eEHroBsMgpBer8eaNWuwefNmaDQaXL58GY2NjXjnnXewZMkSCuUDio+Px/r16/HFF1+gq6sLH330ETo7O6FWq7F37144nU7BtkXBDDLvv/8+Vq5ciVWrVsFgMKC8vBypqamBLivohIWFIT8/H1VVVaivr8elS5eQlZWFlpYWYdoXpBXChO+++w4ff/wxmpqaJnU+RYSxcOFCnDp1Cp9++inWrVuHS5cuQS6X+9Um9ZhBor+/H6WlpTh58iSFMkC2bduGpUuXYufOnX63RcEMEs3NzVi2bBkef/zxQJcyq5WXl8NkMvndDgUzSPT19dFvjzAgNjYWzc3NfrdDwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhhEwSSEQRRMQhjk9zN/5HI53G63ELUQP3i9XiQkJAS6DCIQv3tMpVKJq1evClEL8UNLS0tAJr8hU8PvYK5ZswaNjY04deqUEPWQB9DS0oLKykqUlpYGuhQiEL+HskqlEidPnkRhYSHEYjGKi4tn1byKgXblyhWUlJRgz549WLx4caDLIQIR5OKPRqPBV199hYqKCqxatQq//fabEM2ScXR0dGDTpk0oKCjAa6+9hq1btwa6JCIgwR74vHr1aly9ehWHDx+GVqtFeno6tFot1q5di0WLFlEvKoCbN2+iuroaOp0O9fX1eOWVV9Da2oro6OhAl0YE5vdU76PhOM43+YpOp4NMJkNhYSFyc3N9M0wpFAqhNxtUnE4nWltbodfr0dzcjJqaGhiNRhQUFECr1aKgoAAxMTGBLpPcpaOjA0888QQ6Ojr8amdKgjkcz/O4cuUKzp07h+bmZt/c9tHR0aPOQThnzpxZ1bvabLYR81QOLXd2dmL+/Pm+72XFihXIz89HeHh4oEsm45gxwRyN1+vFjRs3RkyaOvTKcRyUSuWYM/9OtCyVSqc12Ldv355wUtTxll0uF7KyskYcoLKzs5GRkUEhnIFmdDDHwvM8BgYGxtyZh14tFgt6enrQ29sLi8UCm80Gm80Gu90OnuchlUoRHh7um1pcJBL5wjrWFONSqRS3bt3y1TG8prtfeZ6Hy+UCx3HweDyIjIyEXC6HQqGAUqmEUqlEQkICYmNjR8zAPNbBZPgU6GRmEyqYTMz2NXzqcbPZPGEw7XY7oqKifDt3enq6bzkyMhJSqRRhYWEICQnxhXK0YN69fHcIhy8PBRK40+O73W5wHAe73Q6r1eqrrbu7G62trejv74dEIpkwmMnJyVCr1cjKykJUVNSUf9dkZpjWYNrtdrS0tNwzhG1vb0daWhrUajUyMjKgVCqRlJQ0Zg8TFRXFfC/D8zwcDse4w1mLxYKmpiZ8+OGHuHbtGuLj4+8Z0qrVasTFxQX6r0Om2ZQOZZ1OJ2pra6HT6XDu3Dl0d3djwYIF9+x8mZmZs36WY4/Hg/b29lHPu2UyGfLz87F27VoUFhYiNjY20OWSMTB7jun1enH69GkcO3YMtbW1eOSRR6DVavH0009j0aJFCA0NFXJzQY/nedy4cQM1NTXQ6XSora3Fo48+iueeew6lpaV0fyxjhAomeAH99NNPvEaj4TUaDX/06FG+p6dHyOYJz/MOh4Ovrq7mn332WV6lUvFHjx7lPR5PoMsi/9Pe3s6rVCq/2xGkx/R6vdi8eTPOnz+P3bt3Y8OGDcyfAwaD+vp67NixAy6XCzU1NXTDAQOE6jEFSc/u3bthMpmg1+tRUlJCoZwmy5cvR319PfLy8rBp0yaauDaI+J2gy5cv48CBAzhx4gSkUqkQNZH7IBKJUFlZid7eXhw8eDDQ5RCB+B3MxsZGlJSUIDk5WYh6yAMQi8UoKysTZIpxwga/g9nV1UVXBhmgVCphMpkCXQYRCJ0MEsIgCiYhDKJgEsIgCiYhDKJgEsIgCiYhDKJgEsIgv38fMykpyfeb/yRwFAoF5s+fH+gyZr3w8HDk5OT43Q5TjxYhhNxBQ1lCGETBJIRBFExCGETBJIRBFExCGETBJIRBFExCGETBJIRBFExCGETBJIRBFExCGETBJIRBFExCGETBJIRBFExCGETBJIRBFExCGETBJIRBFExCGETBJIRBFExCGETBJIRBFExCGETBJIRB/wexVT78afEbkAAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" }, { @@ -757,7 +737,7 @@ "circuit1 >>= SWAP @ Id(1)\n", "\n", "# or you can do\n", - "perm = Circuit.permutation([2, 0, 1])\n", + "perm = Circuit.permutation([2, 0, 1], inverse=True)\n", "circuit2 = perm >> Id(1) @ CX >> perm[::-1]\n", "\n", "assert circuit1 == circuit2\n", @@ -783,26 +763,22 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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W+Dzwyapn2R2GT6rOAuC3wOqIeEtERNUDSXsiIvaLiH8AlgH/mJk3VD3T7ti36gGkUmXm74EPR8QZwJeA0Yi4Dvh6Zt5f7XTSxCJiX+AtwF8DZwG3A2/MzIernGtPuMUnVSwzbwKOAN4PHAj8d0TcFRF/HxGzGk80UmUiYmpE/EVEXAk8AnwK+Dnwusz8y06KHrjFJ7WFzEzgDuCOiDgfmAO8F/gucHBE3APc1VhWAT/PzJGq5lX3ioiDgDc0lmMbpzOAe4AbgJMy88HqJtx7hk9qM5k5BtzSWIiIPwJeT/0J6ETgw8BREfEgMAQ8BDwM/O8zp5n5ZKvnVmdo/C75IODVwKvGnb6W+mOsn+deZN1EfevuF5n5dCUDN4Hhk9pcZv4OWNFYgPqbCoCjqQfxUOAkxj2RRcQw9RA+G8PG6QbgcWBTY/ldY2tTHS4ieoBpwEvHLQezY+BeBTzJjo+N24GPAWu7/TFh+KQOlJlPUd/luer51zVe0b+M7Z/sXg0cQ/2V/vgnxv0jYjP1CI4P4vPP/w4YaSzDL3B+BPhDtz9pTpaI2If6cW/jl74JLvdRD9of89z/20Tn96f+f/XM/93jwKPUw3YrzwXu1403VhXL8EldphGe3zaWu3Z22+dtJYx/Mn3m8mHAccBUdv0E3QvsGxHjQ/j8MO7q8ggwBmybxGWU+nPdPnuxxAT/1jPBz+KFfi4TXe6h/gk+u/Nz2cxzL0TWjjs//kXKlszchnbJ8EkFy8xR6h+dNikfnxYRU4D92LMAjL98AHsXqImWJ6jH/cVEM3dy3dPAVurR2dPAD+PWcWUMn6RJ03hjztbGIrUlj+OTJBXF8EmSimL4JElFMXySpKIYPklSUQyfJKkohk+SVBTDJ0kqiuGTJBXF8EmSimL4JElFMXySpKIYPklSUQyfJKkohk+SVBTDJ0kqiuGTJBXF8EmSimL4JElFMXySpKIYPklSUQyfJKkohk+SVBTDJ0kqiuGTJBXF8EmSimL4JElFMXySpKIYPklSUTolfI8BT1U9RAtNAe6qeghJ6kadEj6AI6seoIVmAAdXPYQkdaNOCd9/AX8VET1VD9Ii7wVurnoISepGHRG+zLwbeAh4Z9WzNFtEHAS8G/hy1bNIUjfqiPA1fBL414h4Y9WDNEtE/BH1Lb3PZ+aGqueRpG7UMeHLzFuAhcBNETFY8TiTLiJmAN8DfgpcUPE4ktS1OiZ8AJl5A3AusDQirouIV1c9096KiL6IuABYDfwQ+NvMzIrHkqSu1VHhA8jMm4E/Be4H7oqIqyPi9E5640vU1SLiEuAB4A3A7My8KDO3VTyeJHW16OSNi4gYAN5D/V2QRwH/AfwY+Alwf2aOVTfd9hq7MmcDJwBnAX3AdcDXM3N1haO1hYhYBizJzGVVzyKpu3V0+MaLiEOpB+UE6oF5BbAKuBt4FFhP/UD49Y1l42RtXUVEAFOB6cArxy3Tgdc25tmPepB/Sv3wjDvcpfkcwyepVbomfM8XES8F3ggczXMRGh+lqcAG6jHcBPwBGG2cjl+eBKYBL5lgOWDc90t2jOt64FfUY7fW0L0wwyepVfateoBmycxNwPLGsoOI2A8YoB6taUAPE8dtFAh2DOIfgK00QpeZW5p3byRJk6Vrw7crmfkU8HBjkSQVouPe1SlJ0t4wfJKkohg+SVJRDJ8kqSiGT5JUFMMnSSqK4ZMkFcXwSZKKYvgkSUUxfJKkohg+SVJRDJ8kqSiGT5JUFMMnSSqK4ZMkFcXwSZKKYvgkSUUxfJKkohg+tYv/AX5X9RCSul9kZtUzSJLUMm7xSZKKYvgkSUUxfJKkohg+SVJRDJ8kqSiGT5JUFMMnSSqK4ZMkFcXwSZKKYvgkSUUxfJKkohg+SVJRDJ8kqSiGT5JUFMMnSSqK4ZMkFcXwSZKKYvgkSUUxfJKkohg+SVJRDJ8kqSiGT5JUFMMnSSqK4ZMkFcXwSZKKYvgkSUUxfJKkohg+SVJRDJ8kqSiGT5JUlP8HwsuApXayEOUAAAAASUVORK5CYII=\n", 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\n", 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\n", + "image/png": 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\n", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], diff --git a/docs/tutorials/extend-lambeq.ipynb b/docs/tutorials/extend-lambeq.ipynb index cfc9e173..16b513b5 100644 --- a/docs/tutorials/extend-lambeq.ipynb +++ b/docs/tutorials/extend-lambeq.ipynb @@ -14,8 +14,8 @@ }, "source": [ "In this tutorial you will find examples of how to extend ``lambeq`` to add more :term:`readers `, :term:`rewrite rules ` and :term:`ansätze `, so you can start making your own `contributions `_ to the toolkit.\n", - "\n", - ":download:`Download code <../_code/extend-lambeq.ipynb>`" + "\n", + ":download:`Download code <../_code/extend-lambeq.ipynb>`" ] }, { @@ -61,16 +61,22 @@ "execution_count": 1, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/miniconda3/envs/lambeq/lib/python3.10/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + }, { "data": { - "image/png": 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\n", 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44opRx+zduzcf/vCHs2PHjmzZsiUTJkzIRRddlKGhoVHHXXPNNfnDP/zD1Ov1XHzxxbn00ktHvXaSrFu3Lu9617sybdq0sbsogAYwseoBAA6Vnp6eXHvttXnyySeTJA899FDuvPPO9Pb2jhzzzne+c9Tv3HrrrZk9e3Z2796dRYsWjexfuXJlLr744pHtq6++OosXL85TTz2Vtra29Pf357777ss//MM/jO1FATQAK5TAuDF79uy87W1vy/r167Nu3bq87W1vS2tr66hjHn/88Vx22WWZN29epk+fnrlz5yZJ+vr6Rh3X1dU1avu0007Lb/3Wb2XDhg1Jko0bN+aEE07I2WefPXYXBNAgBCUwrlx55ZVZv359NmzYkCuvvHK/59/+9rfnmWeeyc0335xt27Zl27ZtSZIXXnhh1HFTpkzZ73evvvrqrF+/PsmLb3dfccUVaWpqOvgXAdBgBCUwrpx33nl54YUXsm/fvpx77rmjnnv66afz2GOP5eMf/3jOOeectLe35yc/+cn/+LV7enry5JNP5qabbsru3bvzvve972CPD9CQ/A0lMK684hWvSL1eH/n5182cOTOzZs3Kl770pbS1taWvry/XXHPN//i1Z86cmYsvvjgf/ehH8zu/8zs5/vjjD+rsAI3KCiUw7kyfPj3Tp0/fb/+ECRNy5513ZufOnVm0aFE+9KEP5dOf/vT/6rWvuuqqvPDCCwd8Ox3gSGWFEjji/dffNb6UTZs2jfy8dOnS7N69e9Tzw8PDIz/PnTt31PZ/96Mf/SizZs3KBRdc8H+aFeBwJCgBDoLBwcE89dRTueGGG/K7v/u7aW5urnokgEPGW94AB8GaNWty0kknZc6cObn22murHgfgkBKUAAfBqlWrsm/fvmzZsiVTp06tehyAQ0pQAgBQRFACAFBEUAIAUERQAgBQRFACAFBEUAIAUERQAgBQxDflAIeFer1e9QiVGK/XDRxeBCXQ0FpbW9PS0pKenp6qR6lMS0tLWltbqx4D4CUJSqCh1Wq11Ov1DAwMVHL+lStXJkk+97nPVXL+5MWortVqlZ0f4DcRlEDDq9VqlQXVjBkzkiSdnZ2VnB/gcOCmHAAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgAAighKAACK+GBzgDHS3d2djo6OTJ48OWvXrk1zc3NWrFiRVatWVT0awEFlhRJgDG3YsCFTpkzJtm3bsmbNmqxevTqbN2+ueiyAg0pQAoyhjo6OXH/99VmwYEGWLVuWrq6ubNmypeqxAA4qQQkwhjo6OkZtt7W1pb+/v6JpAMaGoAQYQ5MmTRq13dTUlKGhoYqmARgbghIAgCKCEgCAIoISAIAiPocSYIz09vbut2/Tpk2HfA6AsWaFEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAiE6seAAB+k76+vgwMDFQ9RqVaW1tTq9WqHgMOSFAC0ND6+vrS3t6ewcHBqkepVEtLS+r1uqikIQlKABrawMBABgcHs3HjxrS3t1c9TiXq9Xp6enoyMDAgKGlIghKAw0J7e3s6OzurHgM4ADflAABQRFACAFBEUAIAUERQAgBQRFACAFBEUAIAUERQAgBQRFACAFBEUAIAUERQAgBQRFACAFBEUALAS7j//vtz5plnZsaMGZk1a1bOP//87Nmzp+qxoOEISgB4CXv37s2HP/zh7NixI1u2bMmECRNy0UUXZWhoqOrRoKFMrHoAAGhU73znO0dt33rrrZk9e3Z2796dRYsWVTQVNB4rlADwEh5//PFcdtllmTdvXqZPn565c+cmSfr6+qodDBqMFUoAeAlvf/vbc8IJJ+Tmm2/Oq1/96gwNDWXRokV54YUXqh4NGoqgBIADePrpp/PYY4/l5ptvzllnnZUkefDBByueChqToASAA5g5c2ZmzZqVL33pS2lra0tfX1+uueaaqseChuRvKAHgACZMmJA777wzO3fuzKJFi/KhD30on/70p6seCxqSFUoAeAlLly7N7t27R+0bHh6uaBpoXFYoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAo4qsXATgs1Ov1qkeozHi+dg4PghKAhtba2pqWlpb09PRUPUqlWlpa0traWvUYcECCEoCGVqvVUq/XMzAwUMn5v/rVr+bP/uzPsmPHjkrO/19aW1tTq9UqnQFeiqAEoOHVarXKYmr79u1pampKZ2dnJeeHw4GbcgAAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAo4oPNAWCMdHd3p6OjI5MnT87atWvT3NycFStWZNWqVVWPBgeVFUoAGEMbNmzIlClTsm3btqxZsyarV6/O5s2bqx4LDipBCQBjqKOjI9dff30WLFiQZcuWpaurK1u2bKl6LDioBCUAjKGOjo5R221tbenv769oGhgbghIAxtCkSZNGbTc1NWVoaKiiaWBsCEoAAIoISgAAighKAACK+BxKABgjvb29++3btGnTIZ8DxpoVSgAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgAAighKAACKTKx6AACA36Svry8DAwNVj1Gp1tbW1Gq1qsc4IEEJADS0vr6+tLe3Z3BwsOpRKtXS0pJ6vd6QUSkoAYCGNjAwkMHBwWzcuDHt7e1Vj1OJer2enp6eDAwMCEoAgP+r9vb2dHZ2Vj0GB+CmHAAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgDgiDM8PJwPfOADOfbYY9PU1JQZM2Zk5cqVVY91xBKUAMAR5/7778/69etz77335qmnnsqiRYuqHumI5ru8AYAjzp49e9LW1pbFixcnSSZObKzkeeGFF9Lc3Fz1GAeNFUoA4IiyfPnyfPCDH0xfX1+ampoyd+7c/Y75yU9+kmXLlmXmzJlpaWnJW97yljz++ONJXny7fPbs2bnrrrtGjj/55JPT1tY2sv3ggw/mqKOOyuDgYJLk2WefzdVXX53Zs2dn+vTpefOb35xdu3aNHL9q1aqcfPLJWbt2bV772tdm8uTJY3T11RCUAMAR5S//8i+zevXqHH/88Xnqqaeyffv2/Y5Zvnx5duzYkXvuuSf/9E//lOHh4bz1rW/Nvn370tTUlLPPPju9vb1JXozPer2en/3sZ/nud7+bJNm6dWve+MY3pqWlJUlyySWXpL+/P1//+tezc+fOdHZ25pxzzskzzzwzcs5//dd/zVe/+tXcfffdefTRR8f83+FQaqz1XwCAQsccc0ymTZuWV7ziFZkzZ85+zz/++OO555578tBDD428JX777bfnNa95TTZt2pRLLrkk3d3d+eIXv5gk+cd//MeccsopmTNnTnp7e3PSSSelt7c3S5YsSfLiauW3vvWt9Pf356ijjkqS3Hjjjdm0aVPuuuuufOADH0jy4tvct912W2bPnn0o/hkOKSuUAMC4Uq/XM3HixLzpTW8a2Tdr1qy8/vWvT71eT5IsWbIku3fvzn/8x39k69at6e7uTnd3d3p7e7Nv3748/PDD6e7uTpLs2rUrzz//fGbNmpWpU6eOPH7wgx9kz549I+c44YQTjsiYTKxQAgDs5w1veEOOPfbYbN26NVu3bs2nPvWpzJkzJ3/+53+e7du3Z9++fSOrm88//3za2tpG3iL/dTNmzBj5ecqUKYdo+kNPUAIA40p7e3t++ctfZtu2bSNR+PTTT+exxx7LwoULkyRNTU0566yz8rWvfS3f+c53cuaZZ6alpSW/+MUv8sUvfjFdXV0jgdjZ2Zkf//jHmThx4gFvABoPvOUNAIwrCxYsyAUXXJD3v//9efDBB7Nr16709PTkuOOOywUXXDByXHd3d/7mb/4mJ598cqZOnZoJEybk7LPPzu233z7y95NJsnTp0px++um58MIL841vfCNPPPFEHn744Vx33XXZsWNHFZd4yAlKAGDcWbduXU499dScf/75Of300zM8PJz77rsvkyZNGjlmyZIl+dWvfjXyt5LJi5H53/c1NTXlvvvuy9lnn50rrrgiJ554Yi699NI8+eSTedWrXnUIr6o63vIGAI44K1euHPVVi//97xtnzpyZ22677WVf4+STT87w8PDLvu5/mTZtWm666abcdNNNB3ytVatWZdWqVf+T0Q9LVigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACjiqxcBgMNCvV6veoTKNPq1C0oAoKG1trampaUlPT09VY9SqZaWlrS2tlY9xgEJSgCgodVqtdTr9QwMDFRy/n//93/PW9/61nz+85/P4sWLK5kheTGsa7VaZed/OYISAGh4tVqtspj64Q9/mCSZP39+Ojs7K5mh0bkpBwCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAiPtgcAGAMdXd3p6OjI5MnT87atWvT3NycFStWZNWqVVWPdtBYoQQAGGMbNmzIlClTsm3btqxZsyarV6/O5s2bqx7roBGUAABjrKOjI9dff30WLFiQZcuWpaurK1u2bKl6rINGUAIAjLGOjo5R221tbenv769omoNPUAIAjLFJkyaN2m5qasrQ0FBF0xx8ghIAgCKCEgCAIoISAIAiPocSAGAM9fb27rdv06ZNh3yOsWSFEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAiE6se4OX09fVlYGCgknP/6Ec/yute97rs3r07/f39lcxA9ebNm5dnn302jzzySNWjUJGjjz46SfwfGMeeffbZzJs3z/+BcWxgYCCve93r8qMf/ajS/wetra2p1WqVnf/lNA0PDw9XPcSB9PX1pb29PYODg1WPAgBQuZaWltTr9YaMyoZdoRwYGMjg4GA2btyY9vb2qscBAKhMvV5PT09PBgYGBOX/RXt7ezo7O6seAwCAl+CmHAAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISuCIs3z58lx44YUve8wPf/jDNDc3Z9GiRSP7tm7dmkmTJuXBBx8cdezevXszb968/NEf/VGSpLu7O01NTfs9VqxYMfI7v75/+vTpeeMb35ivfe1rB+8iARqIoATGpfXr1+fd7353/vM//zPbtm1LkixZsiQf/OAHs3z58uzdu3fk2I997GM5+uij88lPfnJk3/vf//489dRTox5r1qwZdY5169blqaeeyo4dO3LGGWfkXe96V/75n//50FwgwCEkKIFxZ3h4OOvWrct73/vevOc978ktt9wy8tz/+3//L83NzfnjP/7jJMkDDzyQtWvX5rbbbsvkyZNHjmtpacmcOXNGPaZPnz7qPDNmzMicOXNy4okn5hOf+ER++ctf5oEHHjg0FwlwCE2segCAQ+2BBx7I4OBgli5dmuOOOy6LFy/OZz/72UyZMiWTJ0/ObbfdlsWLF+e3f/u3s3LlyvzJn/xJTj311P/z+X75y1+ORGtzc/PBugyAhmGFEhh3brnlllx66aV5xStekUWLFmXevHn5yle+MvJ8V1dXrr322lx88cWZNWtWrrvuuv1e46//+q8zderUUY/bb7991DGXXXZZpk6dmqOOOiof+tCHMnfu3Lz73e8e8+sDONQEJTCuPPvss7n77rvT09Mzsq+np2fU295J8qd/+qcZGhrKNddck4kT938z5/LLL8+jjz466vGOd7xj1DGf/exn8+ijj+brX/96Fi5cmLVr1+bYY48dmwsDqJC3vIFx5Y477sjPf/7zvOlNbxrZNzw8nKGhoXzve9/LiSeemCQjEXmgmEySY445JvPnz3/Zc82ZMyfz58/P/Pnzs27durz1rW/N7t2788pXvvIgXQ1AY7BCCYwrt9xySz7ykY+MWlnctWtXzjrrrNx6661jdt7TTjstp556aj71qU+N2TkAqmKFEjgi/fSnP82jjz46at9zzz2XRx55JLfffntOOumkUc9ddtllWb16dT75yU++5KrkrxscHMyPf/zjUfuOOuqozJw58yV/Z+XKlbnooovysY99LMcdd9z//GIAGpwVSuCI1Nvbm1NOOWXU49Zbb83ChQv3i8kkueiii9Lf35/77rvvf/T6N998c9ra2kY9Lrvsspf9nfPOOy+vfe1rrVICRxwrlMARZ/369Vm/fv3/6nfmzJmTX/3qV6P2DQ8PH/DY3t7e3/h6B/rdpqam1Ov1/9VcAIcDK5QAABQRlAAAFBGUAAAUEZQAABQRlAAAFBGUAAAUEZQAABQRlAAAFBGUAAAUEZQAABQRlAAAFGn47/L2vbcAwHjX6D3UsEHZ2tqalpaW9PT0VD0KAEDlWlpa0traWvUYB9Q0PDw8XPUQL6Wvry8DAwNVjwGMYytXrkySfO5zn6t0DoDW1tbUarWqxzighl2hTJJardaw/3DA+DBjxowkSWdnZ7WDADQwN+UAAFBEUAIAUERQAgBQRFACAFBEUAIAUERQAgBQRFACAFBEUAIAUKShP9gc4HDW3d2djo6OTJ48OWvXrk1zc3NWrFiRVatWVT0awEFlhRJgDG3YsCFTpkzJtm3bsmbNmqxevTqbN2+ueiyAg0pQAoyhjo6OXH/99VmwYEGWLVuWrq6ubNmypeqxAA4qQQkwhjo6OkZtt7W1pb+/v6JpAMaGoAQYQ5MmTRq13dTUlKGhoYqmARgbghIAgCLu8gZ4Gffcc0/VIwA0PCuUAAAUaRoeHh6ueggAAA5fVigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKPL/AVExtBw1WGQKAAAAAElFTkSuQmCC\n", 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2WH7wgx+M3vfDH/4wjz76aOr1etFzHzhwoHQewBFNUAJTQmdnZ04++eQ88cQTo/c98cQTqdfrOfPMM0fve+aZZ3L++edn3rx5WbBgQS677LLs27dv9PFXXnkltVotf/mXf5lly5Zl1qxZeeCBBzJ37txs2bJlzGv29vZm9uzZefvttyf+BAEqJCiBKWP16tV5+OGHR28/9NBDueGGG8Yc8+677+bWW2/Nrl27sm3btkybNi1XXnllhoeHxxx3++2353d/93fTaDRy1VVX5dprrx3z3Eny8MMP59d//dczZ86ciTspgCYwveoBAJOlp6cnd9xxR1599dUkyXPPPZfHHnssfX19o8dcffXVY/7PQw89lIULF2bv3r1ZsmTJ6P233HJLrrrqqtHbN910U84999y89tpraWtry8DAQJ5++un83d/93cSeFEATcIUSmDIWLlyYT3ziE9m4cWMefvjhfOITn0hra+uYY15++eVcd911OfXUUzN37twsWrQoSdLf3z/muK6urjG3zz777PzyL/9yNm3alCTZvHlzTjnllFx44YUTd0IATUJQAlPK6tWrs3HjxmzatCmrV68+6PHLL788b7zxRh588MHs2LEjO3bsSJLs379/zHGzZ88+6P/edNNN2bhxY5L33u6+4YYbUqvVxv8kAJqMoASmlEsuuST79+/PgQMHcvHFF4957PXXX89LL72Uz33uc7nooovS3t6eN9988+d+7p6enrz66qu5//77s3fv3nz6058e7/kATcnPUAJTyvve9740Go3Rr3/a/Pnzs2DBgjzwwANpa2tLf39/br/99p/7uefPn5+rrroqt912W371V381J5100rhuB2hWrlACU87cuXMzd+7cg+6fNm1aHnvssezevTtLlizJZz/72dxzzz3/X8994403Zv/+/Yd8Ox3gaOUKJXDU+8nPNR5Ob2/v6NfLly/P3r17xzw+MjIy+vWiRYvG3P6f/uM//iMLFizIihUr/k9bAY5EghJgHAwNDeW1117L3Xffnd/8zd/MzJkzq54EMGm85Q0wDtavX5/TTz89J554Yu64446q5wBMKkEJMA7Wrl2bAwcOZNu2bTn22GOrngMwqQQlAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARaZXPQDg59FoNKqeUImpet7AkUVQAk2ttbU1LS0t6enpqXpKZVpaWtLa2lr1DIDDEpRAU6vX62k0GhkcHKzk9W+55ZYkyZ/8yZ9U8vrJe1Fdr9cre32An0VQAk2vXq9XFlTz5s1LknR2dlby+gBHAh/KAQCgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIi/lAMwQbq7u9PR0ZFZs2Zlw4YNmTlzZtasWZO1a9dWPQ1gXLlCCTCBNm3alNmzZ2fHjh1Zv3591q1bl61bt1Y9C2BcCUqACdTR0ZG77rorixcvzsqVK9PV1ZVt27ZVPQtgXAlKgAnU0dEx5nZbW1sGBgYqWgMwMQQlwASaMWPGmNu1Wi3Dw8MVrQGYGIISAIAighIAgCKCEgCAIn4PJcAE6evrO+i+3t7eSd8BMNFcoQQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgyPSqBwDAz9Lf35/BwcGqZ1SqtbU19Xq96hlwSIISgKbW39+f9vb2DA0NVT2lUi0tLWk0GqKSpiQoAWhqg4ODGRoayubNm9Pe3l71nEo0Go309PRkcHBQUNKUBCUAR4T29vZ0dnZWPQM4BB/KAQCgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBIDDeOaZZ3L++edn3rx5WbBgQS677LLs27ev6lnQdAQlABzGu+++m1tvvTW7du3Ktm3bMm3atFx55ZUZHh6ueho0lelVDwCAZnX11VePuf3QQw9l4cKF2bt3b5YsWVLRKmg+rlACwGG8/PLLue6663Lqqadm7ty5WbRoUZKkv7+/2mHQZFyhBIDDuPzyy3PKKafkwQcfzAc+8IEMDw9nyZIl2b9/f9XToKkISgA4hNdffz0vvfRSHnzwwVxwwQVJkmeffbbiVdCcBCUAHML8+fOzYMGCPPDAA2lra0t/f39uv/32qmdBU/IzlABwCNOmTctjjz2W3bt3Z8mSJfnsZz+be+65p+pZ0JRcoQSAw1i+fHn27t075r6RkZGK1kDzcoUSAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCLTqx4AAD+PRqNR9YTKTOVz58ggKAFoaq2trWlpaUlPT0/VUyrV0tKS1tbWqmfAIQlKAJpavV5Po9HI4OBgJa//+OOP5w/+4A+ya9euSl7/J1pbW1Ov1yvdAIcjKAFoevV6vbKY2rlzZ2q1Wjo7Oyt5fTgS+FAOAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARfylHACYIN3d3eno6MisWbOyYcOGzJw5M2vWrMnatWurngbjyhVKAJhAmzZtyuzZs7Njx46sX78+69aty9atW6ueBeNKUALABOro6Mhdd92VxYsXZ+XKlenq6sq2bduqngXjSlACwATq6OgYc7utrS0DAwMVrYGJISgBYALNmDFjzO1arZbh4eGK1sDEEJQAABQRlAAAFBGUAAAU8XsoAWCC9PX1HXRfb2/vpO+AieYKJQAARQQlAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARQQlAABFBCUAAEUEJQAARQQlAABFplc9AADgZ+nv78/g4GDVMyrV2tqaer1e9YxDEpQAQFPr7+9Pe3t7hoaGqp5SqZaWljQajaaMSkEJADS1wcHBDA0NZfPmzWlvb696TiUajUZ6enoyODgoKAEA/q/a29vT2dlZ9QwOwYdyAAAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAYCjzsjISG6++eYcf/zxqdVqmTdvXm655ZaqZx21BCUAcNR55plnsnHjxjz11FN57bXXsmTJkqonHdWmVz0AAGC87du3L21tbTn33HOTJNOnN1fy7N+/PzNnzqx6xrhxhRIAOKqsWrUqn/nMZ9Lf359arZZFixYddMybb76ZlStXZv78+Wlpacmll16al19+Ocl7b5cvXLgwW7ZsGT1+6dKlaWtrG7397LPP5phjjsnQ0FCS5K233spNN92UhQsXZu7cufnYxz6WPXv2jB6/du3aLF26NBs2bMgv/uIvZtasWRN09tUQlADAUeVP//RPs27dupx00kl57bXXsnPnzoOOWbVqVXbt2pUnn3wy//iP/5iRkZF8/OMfz4EDB1Kr1XLhhRemr68vyXvx2Wg08oMf/CAvvvhikmT79u356Ec/mpaWliTJNddck4GBgXzta1/L7t2709nZmYsuuihvvPHG6Gv+67/+ax5//PE88cQT+ad/+qcJ/z5Mpua6/gsAUOi4447LnDlz8r73vS8nnnjiQY+//PLLefLJJ/Pcc8+NviX+yCOP5OSTT05vb2+uueaadHd358tf/nKS5B/+4R9y5pln5sQTT0xfX19OP/309PX1ZdmyZUneu1r5zW9+MwMDAznmmGOSJPfee296e3uzZcuW3HzzzUnee5v7K1/5ShYuXDgZ34ZJ5QolADClNBqNTJ8+Pb/yK78yet+CBQvy4Q9/OI1GI0mybNmy7N27N//1X/+V7du3p7u7O93d3enr68uBAwfy/PPPp7u7O0myZ8+evPPOO1mwYEGOPfbY0X/f/e53s2/fvtHXOOWUU47KmExcoQQAOMhHPvKRHH/88dm+fXu2b9+eL3zhCznxxBPzh3/4h9m5c2cOHDgwenXznXfeSVtb2+hb5D9t3rx5o1/Pnj17ktZPPkEJAEwp7e3t+e///u/s2LFjNApff/31vPTSSznjjDOSJLVaLRdccEH+5m/+Jt/+9rdz/vnnp6WlJT/60Y/y5S9/OV1dXaOB2NnZme9973uZPn36IT8ANBV4yxsAmFIWL16cFStW5Dd+4zfy7LPPZs+ePenp6ckHP/jBrFixYvS47u7u/MVf/EWWLl2aY489NtOmTcuFF16YRx55ZPTnJ5Nk+fLlOeecc3LFFVfk61//el555ZU8//zzufPOO7Nr164qTnHSCUoAYMp5+OGHc9ZZZ+Wyyy7LOeeck5GRkTz99NOZMWPG6DHLli3Lj3/849GflUzei8z/eV+tVsvTTz+dCy+8MDfccEM+9KEP5dprr82rr76aE044YRLPqjre8gYAjjq33HLLmD+1+D9/vnH+/Pn5yle+8r8+x9KlSzMyMvK/Pu9PzJkzJ/fff3/uv//+Qz7X2rVrs3bt2p9n+hHJFUoAAIoISgAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgAAighKAACKCEoAAIoISgAAikyvegAAwM+j0WhUPaEyzX7ughIAaGqtra1paWlJT09P1VMq1dLSktbW1qpnHJKgBACaWr1eT6PRyODgYCWv/5//+Z/5+Mc/ni9+8Ys599xzK9mQvBfW9Xq9stf/3whKAKDp1ev1ymLq3//935Mkp512Wjo7OyvZ0Ox8KAcAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAighIAgCKCEgCAIoISAIAi/lIOAMAE6u7uTkdHR2bNmpUNGzZk5syZWbNmTdauXVv1tHHjCiUAwATbtGlTZs+enR07dmT9+vVZt25dtm7dWvWscSMoAQAmWEdHR+66664sXrw4K1euTFdXV7Zt21b1rHEjKAEAJlhHR8eY221tbRkYGKhozfgTlAAAE2zGjBljbtdqtQwPD1e0ZvwJSgAAighKAACKCEoAAIr4PZQAABOor6/voPt6e3snfcdEqo2MjIxUPQIAgCOXt7wBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACgiKAEAKCIoAQAoIigBACjy/wCv2jM66txyVAAAAABJRU5ErkJggg==\n", "text/plain": [ - "
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\n", 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\n", 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\n", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -322,10 +322,10 @@ "\n", "An :term:`ansatz ` should be initialised with an ``ob_map`` argument, a dictionary which maps a rigid type to the number of :term:`qubits ` in the quantum case, or to a dimension size (e.g. ``Dim(2, 2)``) for the classical case. Some :term:`ansätze ` may require additional arguments (see the `API documentation <../root-api.rst>`_ for more details).\n", "\n", - "In :term:`DisCoPy`, a :term:`functor` is defined by specifying the mappings for objects ``ob`` and arrows ``ar``. The :py:class:`.CircuitAnsatz` and :py:class:`.TensorAnsatz` classes already implement the ``_ob`` method, which extends ``ob_map`` to map not just base (atomic) types, but also compound types, into :term:`qubits ` and dimensions respectively. Therefore, to complete a new :term:`ansatz ` class, you only need to implement the ``_ar`` method, i.e. the mapping from rigid boxes to diagrams. This typically involves the following steps:\n", + "In :term:`DisCoPy`, a :term:`functor` is defined by specifying the mappings for objects ``ob`` and arrows ``ar``. The :py:class:`.CircuitAnsatz` and :py:class:`.TensorAnsatz` classes already implement methods which extend ``ob_map`` to map not just base (atomic) types, but also compound types, into :term:`qubits ` and dimensions respectively. Therefore, to complete a new :term:`ansatz ` class, you only need to provide the mapping from rigid boxes to diagrams. This typically involves the following steps:\n", "\n", "1. Obtain the label of the box using the ``_summarise_box`` method. This provides a unique token which can be used to parameterise the box.\n", - "2. Apply the :term:`functor` to the domain and the codomain of the box using the ``_ob`` method.\n", + "2. Apply the :term:`functor` to the domain and the codomain of the box.\n", "3. Construct and return an :term:`ansatz ` with new domain and codomain -- see how to construct diagrams using :term:`DisCoPy` `here `_." ] }, @@ -342,7 +342,8 @@ "raw_mimetype": "text/restructuredtext" }, "source": [ - "This :term:`ansatz ` always returns a tensor with real-valued entries, since the ansatz is constructed using only the CNOT and Y rotation gates, which both implement real-valued unitaries." + "This :term:`ansatz ` always returns a tensor with real-valued entries, since the ansatz is constructed using only the CNOT and Y rotation gates, which both implement real-valued unitaries.\n", + "The :py:class:`.CircuitAnsatz` provides functionality to add postselections or discards to ensure that domains and codomains for the boxes match. To extend the :py:class:`.CircuitAnsatz` to create a new ansatz thus only involves providing a function to generate the circuit within a box." ] }, { @@ -351,51 +352,41 @@ "metadata": {}, "outputs": [], "source": [ - "from discopy.quantum.circuit import Functor, Id\n", - "from discopy.quantum.gates import Bra, CX, Ket, Ry\n", + "from discopy.quantum.circuit import Id\n", + "from discopy.quantum.gates import CX, Ry\n", "from lambeq import CircuitAnsatz\n", - "from lambeq.ansatz import Symbol\n", + " \n", + "def real_ansatz_circuit(n_qubits, params):\n", "\n", - "class RealAnsatz(CircuitAnsatz):\n", - " def __init__(self, ob_map, n_layers):\n", - " super().__init__(ob_map=ob_map, n_layers=n_layers)\n", + " circuit = Id(n_qubits)\n", + " n_layers = params.shape[0]\n", "\n", - " self.n_layers = n_layers\n", - " self.functor = Functor(ob=self.ob_map, ar=self._ar)\n", + " for i in range(n_layers):\n", + " offset = i * n_qubits\n", + " syms = params[i]\n", "\n", + " # adds a ladder of CNOTs\n", + " for j in range(n_qubits - 1):\n", + " circuit >>= Id(j) @ CX @ Id(n_qubits - j - 2)\n", "\n", - " def _ar(self, box):\n", - " # step 1: obtain label\n", - " label = self._summarise_box(box)\n", - "\n", - " # step 2: map domain and codomain\n", - " dom, cod = self._ob(box.dom), self._ob(box.cod)\n", + " # adds a layer of Y rotations\n", + " circuit >>= Id().tensor(*[Ry(sym) for sym in syms])\n", + " \n", + " return circuit \n", "\n", - " n_qubits = max(dom, cod)\n", - " n_layers = self.n_layers\n", - " \n", - " # step 3: construct and return ansatz\n", - " if n_qubits == 1:\n", - " circuit = Ry(Symbol(f'{label}_0'))\n", - " else:\n", - " # this also deals with the n_qubits == 0 case correctly\n", - " circuit = Id(n_qubits)\n", - " for i in range(n_layers):\n", - " offset = i * n_qubits\n", - " syms = [Symbol(f'{label}_{offset + j}') for j in range(n_qubits)]\n", "\n", - " # adds a ladder of CNOTs\n", - " for j in range(n_qubits - 1):\n", - " circuit >>= Id(j) @ CX @ Id(n_qubits - j - 2)\n", + "class RealAnsatz(CircuitAnsatz):\n", + " def __init__(self, ob_map, n_layers, n_single_qubit_params = 1, discard = False):\n", "\n", - " # adds a layer of Y rotations\n", - " circuit >>= Id().tensor(*[Ry(sym) for sym in syms])\n", + " super().__init__(ob_map,\n", + " n_layers,\n", + " n_single_qubit_params,\n", + " real_ansatz_circuit,\n", + " discard,\n", + " [Ry, ])\n", "\n", - " if cod <= dom:\n", - " circuit >>= Id(cod) @ Bra(*[0]*(dom - cod))\n", - " else:\n", - " circuit <<= Id(dom) @ Ket(*[0]*(cod - dom))\n", - " return circuit" + " def params_shape(self, n_qubits):\n", + " return (self.n_layers, n_qubits)" ] }, { @@ -405,14 +396,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -443,22 +432,25 @@ "metadata": {}, "outputs": [], "source": [ - "from lambeq import TensorAnsatz\n", + "from lambeq import TensorAnsatz, Symbol\n", "from discopy import rigid, tensor\n", "from functools import reduce\n", + "import math\n", "\n", "class PositiveAnsatz(TensorAnsatz):\n", + "\n", " def _ar(self, box):\n", " # step 1: obtain label\n", " label = self._summarise_box(box)\n", "\n", " # step 2: map domain and codomain\n", - " dom, cod = self._ob(box.dom), self._ob(box.cod)\n", + " dom, cod = self.functor(box.dom), self.functor(box.cod)\n", "\n", " # step 3: construct and return ansatz\n", " name = self._summarise_box(box)\n", - " n_params = reduce(lambda x, y: x * y, dom @ cod, 1)\n", - " syms = Symbol(name, size=n_params)\n", + "\n", + " syms = Symbol(name, math.prod(dom), math.prod(cod))\n", + "\n", " return tensor.Box(box.name, dom, cod, syms ** 2)" ] }, @@ -469,14 +461,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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0aefbN27cGKtXr466urpu38uH8zWUAEBmysrK4oILLogrr7wyBg8eHJWVlXHttddGjx49oqioKA477LA488wz46/+6q/illtuibKysrjqqqtixIgRceaZZ2Y9n//nCiUAkKm5c+fGCSecEKeffnr80R/9UUyZMiVqa2ujT58+EfHbJ+mMHz8+Tj/99DjhhBMil8vFf/3Xf0XPnj0zXs5urlACAJkqKyuLO++8s/P21q1b42//9m/j4osvjoiIQYMGxW233ZbVPD4GQQkAZGrlypXx8ssvx8SJE6O1tTW+/e1vR0T4lPZ+RFACAJn77ne/G6tXr45evXrF+PHj48knn4yKioqsZ/ExCUoAIFPHHXdcrFixIusZJPCkHAAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkngdSgDIQ01NTVlPII/k++8HQQkAeaSioiJKS0tj5syZWU8hz5SWlubtdw8SlACQR6qrq6OpqSlaWlq69HGvvPLK2L59e/zzP/9zlz4uv9Pc3BznnHNO3HrrrTF27Nguf/yKioqorq7u8sftCoISAPJMdXV1l4fDoEGDolevXjFu3LgufVx+p0+fPhERccQRRxxw59mTcgAASCIoAQBIIigBAEgiKAEASCIoAQBIIigBAEgiKAGAPcyZMycmTJgQZWVlUVlZGTNmzIjVq1dnPaugFNo5FpQAwB4WLVoUDQ0N8cwzz8Sjjz4a7e3tceqpp8bWrVuznlYwCu0ce2FzAGAPCxcu3OP2/Pnzo7KyMlasWBHTpk3LaFVhKbRz7AolALBXra2tERExePDgjJcUrv39HAtKAOAjdXR0xOzZs2PKlClx9NFHZz2nIBXCOfYpbwDgIzU0NMSqVati8eLFWU8pWIVwjgUlAPChZs2aFQsWLIgnnngiRo4cmfWcglQo51hQAgB7yOVycdlll8X9998fjY2NUVNTk/WkglNo51hQAgB7aGhoiLvuuisefPDBKCsriw0bNkRERHl5efTt2zfjdYWh0M6xJ+UAAHu4+eabo7W1Nerr66OqqqrzuOeee7KeVjAK7Ry7QgkA7CGXy2U9oeAV2jl2hRIAgCSCEgCAJIISAIAkghIAgCSCEgCAJIISAIAkghIAgCSCEgCAJIISAIAkghIAgCSCEgCAJIISAIAkghIAgCSCEgCAJCVZDwDgwFZcXBwTJkyIXbt2ZT2loFVUVMTgwYOznkGBcoUSgEyVlZXFsmXLorW1NespBW316tWxZcuWrGdQoAQlAJkaOnRoRES88cYbGS8pbL/61a86zzV0NUEJQKZKS0tj3Lhx8ZOf/CTrKQXr5ZdfjjVr1sS0adOynkKBEpQAZO7888+PBQsWxMaNG7OeUpBuv/32GDhwYJx++ulZT6FACUoAMveFL3whcrlc3HPPPVlPKTgdHR1x++23x7nnnht9+vTJeg4FSlACkLnKyso47bTTYu7cubFp06as5xSUW2+9NX7xi1/E+eefn/UUCpigBCAvfO9734tNmzbF2WefHTt27Mh6TkH4n//5n7jkkkviq1/9apxwwglZz6GACUoA8sJhhx0WDzzwQCxZsiS++tWvRi6Xy3rSfq2pqSnOOuusOPnkk+Of/umfoqioKOtJFDBBCUDeOPHEE+PWW2+N+fPnx6WXXhptbW1ZT9ovLVmyJP74j/84Ro0aFffee2/07Nkz60kUOEEJQF754he/GDfffHP8+Mc/js985jPx6KOPZj1pv9HW1haXX355nHjiiVFVVRUPP/xwlJeXZz2LA4CgBCDv/PVf/3W8+OKLUVNTE6eeemp8+ctfjrfffjvrWXlt4cKFcdRRR8W//uu/xty5c2PJkiVRXV2d9SwOEIISgLx0yCGHxGOPPRY/+MEP4r777ovq6ur4yle+Ek8//bSvr/x/ra2tMW/evJgwYUKcdtppcfjhh8eqVati9uzZUVxcnPU8DiCCEoC8VVRUFBdddFG8/PLLceWVV8Zjjz0WkydPjqOOOirmzp0bb731VtYTu10ul4snn3wyLrjggqiqqoqGhoYYNmxYPPDAA/HII49ETU1N1hM5AAlKAPJeVVVVXHvttdHc3ByPPPJIfOYzn4mrr746RowYEVOnTo2rrroqFixYUJCfFu/o6IgXX3wx5s2bFzNnzozRo0fHtGnTYsmSJfGtb30r1q9fHz/5yU/izDPP9ExuMlOS9QAA+Lh69OgRp5xySpxyyinR0tIS9957bzQ2NsZtt90WN9xwQ0RE1NXVxZQpU2LKlClRV1cXNTU1MWTIkP0itnbs2BHr16+P5ubmWL58eSxZsiSeeuqp2Lx5c5SUlMS4cePiL/7iL+L000+P6dOnR48erguRHwQlAPulioqKuPTSS+PSSy+NXC4X69ati8WLF3ceP/jBDzrft3///jFmzJioqanZ4xg+fHiUl5fHgAEDYsCAAdG7d+99Ep4dHR3R1tYWra2t8c4778SmTZti3bp1sXbt2mhubo61a9fG2rVr45e//GV0dHRERERZWVlMnjw5vv71r8fUqVNj4sSJ0a9fvy7fBl1BUAKw3ysqKuqMxPPOOy8iIjZv3hyvvfZaZ6ztPn7605/G2rVrP/S78fTs2XOPwHx/aBYXF3ceJSUlMXjw4GhpaYldu3Z1Hjt37oytW7d2huPuY8uWLR+6e+jQoZ27TzjhhD2id/To0Z5Yw35DUAJQkAYOHBjjx4+P8ePHf+BtHR0d8etf/zrefPPNzuj7/Qjcfbu1tTW2bNnygXAcNWpUvPHGGx8IzQEDBsTIkSM7Y/T3A7W8vDzKy8ujuro6+vfvn8GZga4nKAE44PTo0SNGjBgRI0aMyHoKFARfzQsAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJsBeHHHJI9O3bN+sZwH6gra0txo4dG/379896SrcTlAB7UVZWFgsXLoxNmzZlPQXIc4899lj8/Oc/j1GjRmU9pdsJSoC9uPTSS6O9vT2+973vZT0FyGOtra1x4403xsUXXxyDBg3Kek63E5QAezFs2LCYPXt2XH/99fGjH/0o6zlAHnr77bfjT//0T2PHjh3xzW9+M+s5mSjJegBAvvvOd74TGzdujAsvvDDeeOONuOqqq6KkxB+fQMRrr70WZ555ZmzYsCEee+yxGD58eNaTMuEKJcAfUFxcHPPmzYtrr702rrnmmhg7dmwsXLgw61lAhjZv3hzf+MY3ora2NrZu3RqLFy+OSZMmZT0rM4IS4GMoKiqK6667LpYtWxYVFRVx2mmnxSmnnBL33XdfvPfee1nPA7pJc3NzfPvb345DDz005s2bF9dcc0289NJLceSRR2Y9LVOCEuATOP7446OxsTHuv//+ePvtt+Pss8+OYcOGxcUXXxyLFi2Kjo6OrCcCXaylpSX+5V/+JSZPnhyHHHJI/P3f/32cffbZ8corr8Q111wTpaWlWU/MnKAE+ISKiopixowZsWLFinjppZfi0ksvjUceeSTq6+tj9OjRcfXVV8eyZcuivb0966nAp/Sb3/wm7r777jjjjDOiqqoqLr/88hg0aFDcdddd8eabb8Ytt9wSVVVVWc/MG76qHCBBXV1d/N3f/V185zvfiaeeeiruvPPOuOWWW+L666+PPn36xPjx42PSpEkxadKk+OxnPxujRo2KoqKirGcD7/Puu+/GypUrY+nSpZ3H2rVrIyJi0qRJcdNNN8XnP//5qKyszHhp/hKUAF2gR48eMXXq1Jg6dWp8//vfj+XLl8fSpUvjmWeeif/8z/+MuXPnRsRvX4bo/YF5/PHHR1lZWcbr4cCRy+Xitdde6/z/c+nSpfH8889He3t79O7dO8aNGxczZsyISZMmxQknnBDV1dVZT94vCEqALtarV6+YPHlyTJ48ufO+DRs2xLPPPtv5F9icOXNiy5Yt0aNHj6irq4tJkyZFbW1t1NTUdB4DBw7M7oOA/dyuXbvil7/8ZTQ3N8fatWujubm58yrkxo0bIyLisMMOi0mTJsX5558fn/3sZ+OYY46JXr16Zbx8/yQoAbrBsGHD4owzzogzzjgjIn77l93LL7/cGZjPPvts3H333bF169bOnzNw4MAYM2bMHpG5+xg9enT06dMnqw8HMpfL5eKtt96KtWvXdgbj7h+vXbs21q9fHzt37ux8/+HDh8cxxxwTs2bNikmTJsXEiRNjyJAhGX4EhUVQAmSguLg4jjrqqDjqqKPiK1/5SkR88C/I9x/33Xffh/4F+fuRWVlZGRUVFZ1HeXm5r9lkv7Njx47YuHFjtLS0dB5vvPHGHuG4bt26Pf4BNmjQoM7/F84666w9/jF28MEH+wfYPiYoAfJEUVFRVFZWRmVl5Ye+QPLOnTs7/1J9/9Hc3ByPPfZY/PrXv/7AzykpKYkhQ4bsEZm/f/v3j/79+4tQuszOnTs74/D3I/Gjji1btnzgcfr06dMZiPX19Z0/3h2O5eXlGXx07CYoAfYTJSUlcfDBB8fBBx8c9fX1H3j7h13V+f1j48aNsW7dus7b77/Cs1uvXr06w3PIkCHRv3//6Nev316Pvb1PaWlpFBcXd8MZIlUul4sdO3bE1q1bO4+2trY9bn+co7W1tfP32ObNmz/w6/To0SMGDx68xz9kxo4du9d/+Ljant8EJUCB6NWrV1RVVX2i18bbvn37ByL0/bc3btwYbW1t8dZbb3V+ivH9x7Zt2yKXy/3BX6dPnz57DdJevXpFz549o2fPnlFSUtL549+/vbe3fdKfW1xcHEVFRZ/62C2Xy+1xdHR0fOC+jzra29tj586d0d7e/oEff9LbH/d9t2/fvtcY3LVr1x/879mzZ8+9/vesqqqKoUOHfugV8CFDhsTAgQP9I6PACEqAA1jfvn1j5MiRMXLkyE/183O53B8MlD90pWvTpk2fOpI+TszuK8cee2w8//zzmf36JSUlnyqo+/TpE+Xl5TFixIg/eOX5o46ePXtm9nGTnwQlAJ9aUVFRlJaWRmlpaQwdOrTbf/2Ojo5PfXVv165dH+sq4kddcezZs2e0t7dHjx49PtYVzQ97v097lbWkpMSnf8krghKA/VaPHj2id+/e0bt376ynwAHN9/IGACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACCJoAQAIImgBAAgiaAEACBJSdYDultxcXEceuih0dHRkfWUgjZw4MAoKyvLegYA0A0OuCuUpaWl8eqrr0ZbW1vWUwraunXror29PesZAEA3OOCCsrKyMiIiNmzYkPGSwvbmm292nmsAoLAdcEE5dOjQGDVqVPz3f/931lMK1po1a2Lt2rUxfvz4rKcAAN3ggAvKHj16xHnnnRd33313vPvuu1nPKUi33XZblJeXxxlnnJH1FACgGxxwQRkRcd5558XmzZtjwYIFWU8pOB0dHXH77bfHueeeG3369Ml6DgDQDQ7IoDzyyCNj4sSJMXfu3NixY0fWcwrKvffeG+vXr4/zzz8/6ykAQDc5IIMyIuLGG2+M5cuXxyWXXBK5XC7rOQVh2bJlceGFF8bnP//5mDx5ctZzAIBucsAG5bRp0+KHP/xh3HrrrXHDDTdkPWe/9/rrr8ef/dmfxdixY2P+/PlRVFSU9SQAoJsccC9s/n7nn39+vPbaa3H11VdHv379oqGhIXr0OGAb+1Nbs2ZN/Pmf/3mUlpbGgw8+GH379s16EgDQjQ74erruuuvisssui8svvzxOPvnkeOWVV7KetN9ob2+P66+/Po455ph477334uGHH/bakwBwADrgg7KoqCj+8R//MX72s5/FL37xizjmmGPixhtvjJ07d2Y9La+tXLkyJk2aFH/zN38Tl112Wfzv//5v1NbWZj0LAMjAAR+Uu33uc5+LF198MRoaGuKqq66Kurq6uOGGG3xHnffZuXNnPPzww3HWWWfFhAkTYteuXbF06dK48cYbo7S0NOt5AEBGBOX7lJaWxne/+9149tlnY+LEiXHdddfFyJEjY8aMGbFgwYID9qplc3NzfOtb34rRo0fH6aefHs3NzfH9738/li1bFscff3zW8wCAjBXlvGbOR9q0aVPcdddd8cMf/jCef/75qKqqilNPPTWmTp0aU6dOjSOOOKIgn828efPmePrpp2Px4sWxaNGiWLJkSQwYMCD+8i//Mi666KIYN25cQX7c+5vly5fHhAkT4vnnn4+xY8dmPQeAA5ig/Jiee+65uP3222PRokXxwgsvREdHRwwZMiSmTJkSU6dOjSlTpsSRRx4ZgwYN2q9ia8eOHfH666/HsmXLYvHixbF48eJYtWpV5HK5OOigg2LKlClxxhlnxDnnnOPT2nlGUAKQLwTlp/DOO+/E0qVLOwPsmWeeiW3btkVExIABA6KmpiZqampizJgxnT+uqamJqqqqGDBgQBQXF3fLzlwuF9u3b4+333471q1bF2vXro3m5uZYu3Zt5/HGG29ER0dHRPz2OwjtjuOpU6fGIYccsl/F8YFGUAKQLwRlF2hvb49Vq1bFq6++2hlqu8Pt9ddf/8C3d+zXr18MGDAgBgwYEOXl5Z0/3n27V69eUVxcHMXFxVFSUhLFxcVRWloabW1tsWvXrs5j586d0dbWFu+88060trbGO++803nsvr1r1649fu2DDjpoj8jdfYwdOzYqKiq687SRSFACkC8O6Bc27yo9e/aM4447Lo477rgPvK2joyN+9atfxdq1a+M3v/nNR4bfO++8Exs2bIjW1tbYsWPHHtG4a9euOPTQQ6O5ubkzNHfHZv/+/TtDdMyYMR8aqgMHDoyDDz44Ro8eHf369cvgDAEAhUxQ7mM9evSIkSNHxsiRI7OeAgCwT3jZIAAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIISgAAkghKAACSCEoAAJIU5XK5XNYjAADYf7lCCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAEkEJAEASQQkAQBJBCQBAkv8D7A07FzXnr+4AAAAASUVORK5CYII=\n", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -508,6 +498,7 @@ "import numpy as np\n", "from sympy import default_sort_key\n", "\n", + "\n", "syms = sorted(positive_d.free_symbols, key=default_sort_key)\n", "sym_dict = {k: -np.ones(k.size) for k in syms}\n", "subbed_diagram = positive_d.lambdify(*syms)(*sym_dict.values())\n", @@ -536,8 +527,7 @@ "* rewrites to language circuits (DisCoCirc): [CW2021]_\n", "\n", "* ansätze benchmarked by their expressibility: [SJA2019]_\n", - "* high-level examples of ansätze: `[link] `_", - "\n", + "* high-level examples of ansätze: `[link] `_\n", ".. rubric:: See also:\n", "\n", "- :ref:`General information about sub-packages `\n", diff --git a/docs/tutorials/trainer_classical.ipynb b/docs/tutorials/trainer_classical.ipynb index 96131519..afd0f971 100644 --- a/docs/tutorials/trainer_classical.ipynb +++ b/docs/tutorials/trainer_classical.ipynb @@ -73,6 +73,25 @@ "test_labels, test_data = read_data('../examples/datasets/mc_test_data.txt')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "nbsphinx": "hidden" + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "TESTING = int(os.environ.get('TEST_NOTEBOOKS', '0'))\n", + "\n", + "if TESTING:\n", + " train_labels, train_data = train_labels[:2], train_data[:2]\n", + " val_labels, val_data = val_labels[:2], val_data[:2]\n", + " test_labels, test_data = test_labels[:2], test_data[:2]\n", + " EPOCHS = 1" + ] + }, { "cell_type": "code", "execution_count": 3, @@ -605,5 +624,5 @@ } }, "nbformat": 4, - "nbformat_minor": 5 + "nbformat_minor": 4 } diff --git a/docs/tutorials/trainer_hybrid.ipynb b/docs/tutorials/trainer_hybrid.ipynb index 7c586a43..61921daf 100644 --- a/docs/tutorials/trainer_hybrid.ipynb +++ b/docs/tutorials/trainer_hybrid.ipynb @@ -85,6 +85,25 @@ "test_labels, test_data = read_data('../examples/datasets/mc_test_data.txt')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "nbsphinx": "hidden" + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "TESTING = int(os.environ.get('TEST_NOTEBOOKS', '0'))\n", + "\n", + "if TESTING:\n", + " train_labels, train_data = train_labels[:2], train_data[:2]\n", + " dev_labels, dev_data = dev_labels[:2], dev_data[:2]\n", + " test_labels, test_data = test_labels[:2], test_data[:2]\n", + " EPOCHS = 1" + ] + }, { "cell_type": "code", "execution_count": 4, @@ -318,13 +337,12 @@ "all_circuits = train_circuits + dev_circuits + test_circuits\n", "\n", "# if no backend_config is provided, the default is used, which is the same as below\n", - "backend_config = {'backend': 'default.qubit', # this is the default PennyLane simulator\n", - " 'probabilities': True,\n", - " 'normalize': True}\n", + "backend_config = {'backend': 'default.qubit'} # this is the default PennyLane simulator\n", "model = PennyLaneModel.from_diagrams(all_circuits,\n", + " probabilities=True,\n", + " normalize=True,\n", " backend_config=backend_config)\n", - "model.initialise_weights()\n", - "model = model.double()" + "model.initialise_weights()" ] }, { @@ -347,7 +365,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -359,17 +377,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "backend_config = {'backend': 'qiskit.ibmq',\n", " 'device': 'ibmq_manila',\n", - " 'probabilities': True,\n", - " 'normalize': True,\n", " 'shots': 1000}\n", "\n", "q_model = PennyLaneModel.from_diagrams(all_circuits,\n", + " probabilities=True,\n", + " normalize=True,\n", " backend_config=backend_config)\n", "q_model.initialise_weights()" ] @@ -389,7 +407,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -400,17 +418,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "backend_config = {'backend': 'honeywell.hqs',\n", " 'device': 'H1-1E',\n", - " 'probabilities': True,\n", - " 'normalize': True,\n", " 'shots': 1000}\n", "\n", "h_model = PennyLaneModel.from_diagrams(all_circuits,\n", + " probabilities=True,\n", + " normalize=True,\n", " backend_config=backend_config)\n", "h_model.initialise_weights()" ] @@ -442,7 +460,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -482,7 +500,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -491,7 +509,7 @@ " torch.argmax(y, dim=1)).sum().item()/len(y)\n", "\n", "def loss(y_hat, y):\n", - " return torch.nn.functional.mse_loss(y_hat, y.double())" + " return torch.nn.functional.mse_loss(y_hat, y)" ] }, { @@ -512,7 +530,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -549,7 +567,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -563,14 +581,14 @@ "Epoch 5: train/loss: 0.0244 valid/loss: 0.0216 train/acc: 0.9857 valid/acc: 1.0000\n", "Epoch 6: train/loss: 0.0362 valid/loss: 0.0183 train/acc: 0.9571 valid/acc: 0.9667\n", "Epoch 7: train/loss: 0.0153 valid/loss: 0.0363 train/acc: 0.9857 valid/acc: 0.9667\n", - "Epoch 8: train/loss: 0.0204 valid/loss: 0.0495 train/acc: 0.9857 valid/acc: 0.9333\n", + "Epoch 8: train/loss: 0.0204 valid/loss: 0.0496 train/acc: 0.9857 valid/acc: 0.9333\n", "Epoch 9: train/loss: 0.0314 valid/loss: 0.0312 train/acc: 0.9714 valid/acc: 0.9667\n", - "Epoch 10: train/loss: 0.0382 valid/loss: 0.0707 train/acc: 0.9429 valid/acc: 0.9333\n", - "Epoch 11: train/loss: 0.0364 valid/loss: 0.1207 train/acc: 0.9571 valid/acc: 0.8333\n", - "Epoch 12: train/loss: 0.0451 valid/loss: 0.1437 train/acc: 0.9429 valid/acc: 0.7667\n", - "Epoch 13: train/loss: 0.0646 valid/loss: 0.0522 train/acc: 0.9143 valid/acc: 0.9333\n", - "Epoch 14: train/loss: 0.0398 valid/loss: 0.0710 train/acc: 0.9571 valid/acc: 0.9333\n", - "Epoch 15: train/loss: 0.0376 valid/loss: 0.0496 train/acc: 0.9714 valid/acc: 0.9333\n", + "Epoch 10: train/loss: 0.0383 valid/loss: 0.0707 train/acc: 0.9429 valid/acc: 0.9333\n", + "Epoch 11: train/loss: 0.0364 valid/loss: 0.1187 train/acc: 0.9571 valid/acc: 0.8333\n", + "Epoch 12: train/loss: 0.0423 valid/loss: 0.1750 train/acc: 0.9429 valid/acc: 0.7333\n", + "Epoch 13: train/loss: 0.0753 valid/loss: 0.0993 train/acc: 0.8857 valid/acc: 0.8667\n", + "Epoch 14: train/loss: 0.0419 valid/loss: 0.0970 train/acc: 0.9571 valid/acc: 0.8333\n", + "Epoch 15: train/loss: 0.0512 valid/loss: 0.0555 train/acc: 0.9286 valid/acc: 0.9667\n", "\n", "Training completed!\n" ] @@ -591,19 +609,19 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Final test accuracy: 0.9333333333333333\n" + "Final test accuracy: 0.9\n" ] }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -652,7 +670,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -671,7 +689,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -679,13 +697,13 @@ "output_type": "stream", "text": [ "Epoch: 0\n", - "Train loss: 1.3878655338080799\n", + "Train loss: 1.3878655098378658\n", "Dev acc: 0.6333333333333333\n", "Epoch: 5\n", - "Train loss: 0.08868915156910184\n", + "Train loss: 0.08868948055896908\n", "Dev acc: 0.9333333333333333\n", "Epoch: 10\n", - "Train loss: 0.024855887882005913\n", + "Train loss: 0.02485578407504363\n", "Dev acc: 1.0\n" ] } @@ -703,7 +721,7 @@ " optimizer.zero_grad()\n", " probs = model(circuits)\n", " loss = torch.nn.functional.mse_loss(probs,\n", - " torch.tensor(labels).double())\n", + " torch.tensor(labels))\n", " epoch_loss += loss.item()\n", " loss.backward()\n", " optimizer.step()\n", @@ -718,13 +736,13 @@ " if dev_acc > best['acc']:\n", " best['acc'] = dev_acc\n", " best['epoch'] = i\n", - " model.make_checkpoint('model.lt')\n", + " model.save('model.lt')\n", " elif i - best['epoch'] >= 10:\n", " print('Early stopping')\n", " break\n", "\n", "if best['acc'] > accuracy(dev_circuits, dev_labels): \n", - " model = PennyLaneModel.from_checkpoint('model.lt')" + " model.load('model.lt')" ] }, { @@ -736,7 +754,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -768,7 +786,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -790,15 +808,15 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "from torch import nn\n", "\n", "class XORSentenceModel(PennyLaneModel):\n", - " def __init__(self, probabilities=True, normalize=True):\n", - " PennyLaneModel.__init__(self, probabilities, normalize)\n", + " def __init__(self, **kwargs):\n", + " PennyLaneModel.__init__(self, **kwargs)\n", " \n", " self.xor_net = nn.Sequential(nn.Linear(4, 10),\n", " nn.ReLU(),\n", @@ -826,7 +844,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ @@ -856,7 +874,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -887,7 +905,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -918,7 +936,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ @@ -930,7 +948,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 29, "metadata": {}, "outputs": [ { @@ -938,23 +956,26 @@ "output_type": "stream", "text": [ "Epoch: 0\n", - "Train loss: 4.272213361858267\n", + "Train loss: 4.272213414468282\n", "Dev acc: 0.45\n", "Epoch: 5\n", - "Train loss: 4.10759657209212\n", + "Train loss: 4.107582013803147\n", "Dev acc: 0.52\n", "Epoch: 10\n", - "Train loss: 3.952059008977611\n", - "Dev acc: 0.655\n", + "Train loss: 4.009163821491491\n", + "Dev acc: 0.485\n", "Epoch: 15\n", - "Train loss: 0.5362579409411792\n", - "Dev acc: 0.975\n", + "Train loss: 3.869323840623094\n", + "Dev acc: 0.53\n", "Epoch: 20\n", - "Train loss: 1.2632150297657396\n", - "Dev acc: 0.945\n", + "Train loss: 0.3866653899992134\n", + "Dev acc: 0.965\n", "Epoch: 25\n", - "Train loss: 0.9304246438466377\n", - "Dev acc: 0.95\n", + "Train loss: 0.6390147764771847\n", + "Dev acc: 0.845\n", + "Epoch: 30\n", + "Train loss: 0.7195060019336509\n", + "Dev acc: 0.885\n", "Early stopping\n" ] } @@ -983,26 +1004,26 @@ " if dev_acc > best['acc']:\n", " best['acc'] = dev_acc\n", " best['epoch'] = i\n", - " model.make_checkpoint('xor_model.lt')\n", + " model.save('xor_model.lt')\n", " elif i - best['epoch'] >= 10:\n", " print('Early stopping')\n", " break\n", "\n", "if best['acc'] > accuracy(dev_pair_circuits, dev_pair_labels): \n", - " model = XORSentenceModel.from_checkpoint('xor_model.lt')\n", + " model.load('xor_model.lt')\n", " model = model.double()" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Final test accuracy: 0.915\n" + "Final test accuracy: 0.94\n" ] } ], @@ -1024,19 +1045,19 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([[0.91843098],\n", - " [0.91843098],\n", - " [0.20070643],\n", - " [0.10345918]])" + "array([[0.94320787],\n", + " [0.94320787],\n", + " [0.27014615],\n", + " [0.2668538 ]])" ] }, - "execution_count": 27, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -1060,7 +1081,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -1073,10 +1094,10 @@ { "data": { "text/plain": [ - "array([0.00709793, 0.99290207])" + "array([0.01249293, 0.98750707])" ] }, - "execution_count": 28, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -1085,14 +1106,15 @@ "print(test_data[0])\n", "\n", "p_circ = test_circuits[0].to_pennylane(probabilities=True)\n", - "unnorm = p_circ.eval(model.symbols, model.weights).detach().numpy()\n", + "p_circ.initialise_concrete_params(model.symbols, model.weights)\n", + "unnorm = p_circ.eval().detach().numpy()\n", "\n", "unnorm / np.sum(unnorm)" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -1105,10 +1127,10 @@ { "data": { "text/plain": [ - "array([0.93675346, 0.06324654])" + "array([0.83502102, 0.16497898])" ] }, - "execution_count": 29, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -1117,7 +1139,8 @@ "print(test_data[6])\n", "\n", "p_circ = test_circuits[6].to_pennylane(probabilities=True)\n", - "unnorm = p_circ.eval(model.symbols, model.weights).detach().numpy()\n", + "p_circ.initialise_concrete_params(model.symbols, model.weights)\n", + "unnorm = p_circ.eval().detach().numpy()\n", "\n", "unnorm / np.sum(unnorm)" ] @@ -1149,5 +1172,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/docs/tutorials/trainer_quantum.ipynb b/docs/tutorials/trainer_quantum.ipynb index 70764703..cc32961b 100644 --- a/docs/tutorials/trainer_quantum.ipynb +++ b/docs/tutorials/trainer_quantum.ipynb @@ -97,6 +97,24 @@ "val_labels, val_data = read_data('../examples/datasets/rp_test_data.txt')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "nbsphinx": "hidden" + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "TESTING = int(os.environ.get('TEST_NOTEBOOKS', '0'))\n", + "\n", + "if TESTING:\n", + " train_labels, train_data = train_labels[:2], train_data[:2]\n", + " val_labels, val_data = val_labels[:2], val_data[:2]\n", + " EPOCHS = 1" + ] + }, { "cell_type": "code", "execution_count": 4, @@ -646,5 +664,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/docs/tutorials/training-symbols.ipynb b/docs/tutorials/training-symbols.ipynb index 5f03ad43..08370477 100644 --- a/docs/tutorials/training-symbols.ipynb +++ b/docs/tutorials/training-symbols.ipynb @@ -25,14 +25,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -105,11 +103,11 @@ { "data": { "text/plain": [ - "[(walks__n.r@s, 8),\n", + "[(in__s.r@n.r.r@n.r@s@n.l, 256),\n", + " (walks__n.r@s, 8),\n", + " (park__n, 4),\n", " (the__n@n.l, 16),\n", - " (John__n, 4),\n", - " (in__s.r@n.r.r@n.r@s@n.l, 256),\n", - " (park__n, 4)]" + " (John__n, 4)]" ] }, "execution_count": 3, @@ -146,14 +144,12 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -171,7 +167,7 @@ "raw_mimetype": "text/restructuredtext" }, "source": [ - "Let's see the :term:`symbols ` of the :term:`circuit ` and their sizes:" + "Let's see the :term:`symbols ` of the :term:`circuit `:" ] }, { @@ -182,18 +178,18 @@ { "data": { "text/plain": [ - "[(in__s.r@n.r.r@n.r@s@n.l_3, 1),\n", - " (walks__n.r@s_0, 1),\n", - " (park__n_0, 1),\n", - " (John__n_0, 1),\n", - " (in__s.r@n.r.r@n.r@s@n.l_0, 1),\n", - " (in__s.r@n.r.r@n.r@s@n.l_2, 1),\n", - " (park__n_2, 1),\n", - " (park__n_1, 1),\n", - " (John__n_2, 1),\n", - " (the__n@n.l_0, 1),\n", - " (in__s.r@n.r.r@n.r@s@n.l_1, 1),\n", - " (John__n_1, 1)]" + "{John__n_0,\n", + " John__n_1,\n", + " John__n_2,\n", + " in__s.r@n.r.r@n.r@s@n.l_0,\n", + " in__s.r@n.r.r@n.r@s@n.l_1,\n", + " in__s.r@n.r.r@n.r@s@n.l_2,\n", + " in__s.r@n.r.r@n.r@s@n.l_3,\n", + " park__n_0,\n", + " park__n_1,\n", + " park__n_2,\n", + " the__n@n.l_0,\n", + " walks__n.r@s_0}" ] }, "execution_count": 5, @@ -202,7 +198,7 @@ } ], "source": [ - "[(s, s.size) for s in circuit.free_symbols]" + "circuit.free_symbols" ] }, { @@ -211,7 +207,7 @@ "raw_mimetype": "text/restructuredtext" }, "source": [ - "Note that all sizes are equal to 1; this is because the parameters of the :term:`circuit ` are numbers, defining rotation angles on :term:`qubits `. " + "In contrast to the tensor case, the above symbols are not associated with a specific size; this is because the parameters of the :term:`circuit ` are not tensors but numbers (i.e. \"tensors\" of size 1), defining rotation angles on :term:`qubits `. " ] }, { @@ -257,7 +253,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "[0.69545749 0.70027778 0.79763124 0.40774577]\n" + "[0.2863774 0.61130277 0.12182877 0.11392914]\n" ] } ], @@ -287,7 +283,7 @@ "output_type": "stream", "text": [ "Before lambdify: John__n\n", - "After lambdify: [0.69545749 0.70027778 0.79763124 0.40774577]\n" + "After lambdify: [0.2863774 0.61130277 0.12182877 0.11392914]\n" ] } ], @@ -315,7 +311,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Tensor(dom=Dim(1), cod=Dim(2), array=[13.4525461 , 12.83309003])\n" + "Tensor(dom=Dim(1), cod=Dim(2), array=[8.5302217 , 8.97638124])\n" ] } ], @@ -345,7 +341,7 @@ { "data": { "text/plain": [ - "array([13.4525461 , 12.83309003])" + "array([8.5302217 , 8.97638124])" ] }, "execution_count": 10, diff --git a/docs/tutorials/training-usecase.ipynb b/docs/tutorials/training-usecase.ipynb index 162124e8..874af615 100644 --- a/docs/tutorials/training-usecase.ipynb +++ b/docs/tutorials/training-usecase.ipynb @@ -97,6 +97,24 @@ "test_data, test_targets = read_data('../examples/datasets/mc_test_data.txt')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "nbsphinx": "hidden" + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "TESTING = int(os.environ.get('TEST_NOTEBOOKS', '0'))\n", + "\n", + "if TESTING:\n", + " train_targets, train_data = train_targets[:2], train_data[:2]\n", + " test_targets, test_data = test_targets[:2], test_data[:2]\n", + " EPOCHS = 1" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/setup.cfg b/setup.cfg index d7b33df4..018464c7 100644 --- a/setup.cfg +++ b/setup.cfg @@ -64,8 +64,8 @@ python_requires = >=3.8 [options.extras_require] extras = - jax - jaxlib + jax <= 0.4.6 + jaxlib <= 0.4.6 pennylane >= 0.29.1 pennylane-honeywell pennylane-qiskit