From c9e62c4f446255eb00bd2d50e5589c5cac1dcecc Mon Sep 17 00:00:00 2001 From: kklein Date: Tue, 30 Jul 2024 09:57:14 +0200 Subject: [PATCH] Add netron visualization. --- docs/examples/example_onnx.ipynb | 142 ++++++++++++++++++++++++++--- docs/examples/imgs/onnx_netron.png | Bin 0 -> 73943 bytes 2 files changed, 127 insertions(+), 15 deletions(-) create mode 100644 docs/examples/imgs/onnx_netron.png diff --git a/docs/examples/example_onnx.ipynb b/docs/examples/example_onnx.ipynb index 0a66ecc..b0b10e0 100644 --- a/docs/examples/example_onnx.ipynb +++ b/docs/examples/example_onnx.ipynb @@ -67,7 +67,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -113,9 +113,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from metalearners import XLearner\n", "from lightgbm import LGBMRegressor, LGBMClassifier\n", @@ -161,9 +172,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'propensity_model': [LGBMClassifier(n_estimators=5, verbose=-1)],\n", + " 'control_effect_model': [LGBMRegressor(n_estimators=5, verbose=-1)],\n", + " 'treatment_effect_model': [LGBMRegressor(n_estimators=5, verbose=-1)]}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "necessary_models = xlearner._necessary_onnx_models()\n", "necessary_models" @@ -187,9 +211,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "The maximum opset needed by this model is only 9.\n", + "The maximum opset needed by this model is only 8.\n", + "The maximum opset needed by this model is only 8.\n" + ] + } + ], "source": [ "import onnx\n", "from onnxmltools import convert_lightgbm\n", @@ -221,9 +255,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/kevinklein/Code/metalearners/metalearners/xlearner.py:463: UserWarning: _build_onnx is an experimental feature. Use it at your own risk!\n", + " warning_experimental_feature(\"_build_onnx\")\n" + ] + } + ], "source": [ "onnx_model = xlearner._build_onnx(onnx_models)" ] @@ -239,14 +282,60 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ONNX model input: [name: \"X\"\n", + "type {\n", + " tensor_type {\n", + " elem_type: 1\n", + " shape {\n", + " dim {\n", + " }\n", + " dim {\n", + " dim_value: 11\n", + " }\n", + " }\n", + " }\n", + "}\n", + "]\n", + "ONNX model output: [name: \"tau\"\n", + "type {\n", + " tensor_type {\n", + " elem_type: 1\n", + " shape {\n", + " dim {\n", + " }\n", + " dim {\n", + " dim_value: 1\n", + " }\n", + " dim {\n", + " dim_value: 1\n", + " }\n", + " }\n", + " }\n", + "}\n", + "]\n" + ] + } + ], "source": [ "print(\"ONNX model input: \", onnx_model.graph.input)\n", "print(\"ONNX model output: \", onnx_model.graph.output)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also visualize the ONNX model with, e.g. [netron](https://netron.app/):\n", + "\"Drawing\"" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -261,7 +350,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -282,7 +371,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -298,6 +387,15 @@ ")" ] }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "onnx.save_model(onnx_model, \"model.onnx\")" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -340,10 +438,24 @@ } ], "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/docs/examples/imgs/onnx_netron.png b/docs/examples/imgs/onnx_netron.png new file mode 100644 index 0000000000000000000000000000000000000000..56efd3c772106d2092ab58170592619d47ac3add GIT binary patch literal 73943 zcmeFZWmHt}8#X#KFvK8=NGJv)NDV0x0s@1Av@}SogfvJuGbk2HhXTSVNQZ!Qt4K*m zill@{ch~!DK!5-Bo^?K-FUPeMnc4B|`?>SFuX{gJy(LSDVnD%QFiLqjX>}Nk2myl; zlarBvPh9$|R>2Rrle+A6Sa!>~N$|@(v)l6K%E~Yd_&*s8{=^bS3>^agGJwC})Ud}e zQt*=+{8c5uVMO339QvMs_(q+-)78Q()KJMZte<&7AL|-ED2`oJ8HlnGTK+1^hsA zbK`Nl!ej4vpZBtehzKtqKQBK&H#maZ$-~b1t~*Ay#{?Ms%q(OW}_=@ zX$!;y?jdoR@5+^H2PgbLzWVQ$|8wf?|4tPa=KJ3>|L2?k`%En-GsheDw&0%568~+@ z(aHb&<4EiO@N?AgkYkh>HJ}VVPZl3fN|VQ zWM_Jgw%uFz^4-7ky7%?Kn}IhH3Co^YSDdCx=AGnQoK#9=-lETt!-=V|u%mxa3Iqiy zLvH#&7=jFqJNoAq4vRYr|L-t7f(A{+UVVKc?Bu@_snArz7ykPVOMoHCh*2NfN=*Of 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