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dreiss/ProtoScript.ipynb

Created October 22, 2019 20:00
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ProtoScript.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Untitled0.ipynb",
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "code",
"metadata": {
"id": "DkaZSyXmBBzS",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 121
},
"outputId": "fa551830-a2ee-4412-ec7a-860d94d9509e"
},
"source": [
"!pip install onnx"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"text": [
"Requirement already satisfied: onnx in /usr/local/lib/python3.6/dist-packages (1.6.0)\n",
"Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from onnx) (1.16.5)\n",
"Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from onnx) (1.12.0)\n",
"Requirement already satisfied: protobuf in /usr/local/lib/python3.6/dist-packages (from onnx) (3.10.0)\n",
"Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.6/dist-packages (from onnx) (3.7.4)\n",
"Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf->onnx) (41.4.0)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "1g5s0-tcAlZy",
"colab_type": "code",
"colab": {}
},
"source": [
"import torch\n",
"import onnx"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "ZGGc7QTmBLbu",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "29c77844-64bc-4fca-efd0-529e165596d6"
},
"source": [
"torch.version.__version__"
],
"execution_count": 3,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"'1.3.0+cu100'"
]
},
"metadata": {
"tags": []
},
"execution_count": 3
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "IqPC_p3GBxBM",
"colab_type": "code",
"colab": {}
},
"source": [
"attr = onnx.helper.make_attribute(\"strides\", (1, 1))"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "TIh8_CiRB3CT",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "4565d1c0-5f95-45f9-d284-0701248a8fac"
},
"source": [
"attr.ints"
],
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[1, 1]"
]
},
"metadata": {
"tags": []
},
"execution_count": 5
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "iu7uhwTDB5Rj",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "5d8d4c55-6122-4b98-bb7b-a6a59fd19928"
},
"source": [
"type(attr.ints)"
],
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"google.protobuf.pyext._message.RepeatedScalarContainer"
]
},
"metadata": {
"tags": []
},
"execution_count": 6
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "lXs9M5rmCbkD",
"colab_type": "code",
"colab": {}
},
"source": [
"class ScriptableModule(torch.nn.Module):\n",
" def __init__(self):\n",
" super(ScriptableModule, self).__init__() \n",
" conv = torch.nn.quantized.Conv2d(1, 1, (1, 1), stride=attr.ints)\n",
" self.add_module(\"conv\", conv)\n",
" \n",
" def forward(self, image):\n",
" return self.conv(image)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "4DnXQvWvDKta",
"colab_type": "code",
"colab": {}
},
"source": [
"sm = ScriptableModule()"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "bWuHzYYgDNP_",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "c16570d8-d1d9-4caa-dc0d-4b86f559bfc6"
},
"source": [
"sm.conv.stride"
],
"execution_count": 9,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[1, 1]"
]
},
"metadata": {
"tags": []
},
"execution_count": 9
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "U2DIFJPTDStx",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "7409e893-f10d-4a53-f882-f8e19dd9a4b1"
},
"source": [
"type(sm.conv.stride)"
],
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"google.protobuf.pyext._message.RepeatedScalarContainer"
]
},
"metadata": {
"tags": []
},
"execution_count": 10
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "NMb4ux-uCg8F",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 625
},
"outputId": "1a365d27-99f1-4fa9-ebfe-68d5996f73c9"
},
"source": [
"torch.jit.script(sm)"
],
"execution_count": 11,
"outputs": [
{
"output_type": "error",
"ename": "RuntimeError",
"evalue": "ignored",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-11-cd32a39eb30b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscript\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msm\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/jit/__init__.py\u001b[0m in \u001b[0;36mscript\u001b[0;34m(obj, optimize, _frames_up, _rcb)\u001b[0m\n\u001b[1;32m 1201\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1202\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mModule\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1203\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_recursive\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecursive_script\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1204\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1205\u001b[0m \u001b[0mqualified_name\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_qualified_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mrecursive_script\u001b[0;34m(mod, exclude_methods)\u001b[0m\n\u001b[1;32m 171\u001b[0m \u001b[0mfiltered_methods\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfilter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mignore_overloaded\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethods\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 172\u001b[0m \u001b[0mstubs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmake_stub\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfiltered_methods\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 173\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mcopy_to_script_module\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moverload_stubs\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstubs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 174\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mcopy_to_script_module\u001b[0;34m(original, stubs)\u001b[0m\n\u001b[1;32m 93\u001b[0m \u001b[0msetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscript_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 94\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 95\u001b[0;31m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_create_methods_from_stubs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscript_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstubs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 96\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 97\u001b[0m \u001b[0;31m# Now that methods have been compiled, take methods that have been compiled\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/jit/__init__.py\u001b[0m in \u001b[0;36m_create_methods_from_stubs\u001b[0;34m(self, stubs)\u001b[0m\n\u001b[1;32m 1421\u001b[0m \u001b[0mrcbs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresolution_callback\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mm\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mstubs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1422\u001b[0m \u001b[0mdefaults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mget_default_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moriginal_method\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mm\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mstubs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1423\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_c\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_create_methods\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdefs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrcbs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdefaults\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1424\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1425\u001b[0m \u001b[0;31m# For each user-defined class that subclasses ScriptModule this meta-class,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mmake_strong_submodule\u001b[0;34m(field, module, parent)\u001b[0m\n\u001b[1;32m 193\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 194\u001b[0m \u001b[0;31m# Convert the module to a ScriptModule\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 195\u001b[0;31m \u001b[0mnew_strong_submodule\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrecursive_script\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodule\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 196\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 197\u001b[0m \u001b[0;31m# Install the ScriptModule on the python side\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mrecursive_script\u001b[0;34m(mod, exclude_methods)\u001b[0m\n\u001b[1;32m 171\u001b[0m \u001b[0mfiltered_methods\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfilter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mignore_overloaded\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethods\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 172\u001b[0m \u001b[0mstubs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmake_stub\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfiltered_methods\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 173\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mcopy_to_script_module\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moverload_stubs\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstubs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 174\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mcopy_to_script_module\u001b[0;34m(original, stubs)\u001b[0m\n\u001b[1;32m 93\u001b[0m \u001b[0msetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscript_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 94\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 95\u001b[0;31m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_create_methods_from_stubs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscript_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstubs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 96\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 97\u001b[0m \u001b[0;31m# Now that methods have been compiled, take methods that have been compiled\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/jit/__init__.py\u001b[0m in \u001b[0;36m_create_methods_from_stubs\u001b[0;34m(self, stubs)\u001b[0m\n\u001b[1;32m 1421\u001b[0m \u001b[0mrcbs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresolution_callback\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mm\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mstubs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1422\u001b[0m \u001b[0mdefaults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mget_default_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moriginal_method\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mm\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mstubs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1423\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_c\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_create_methods\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdefs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrcbs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdefaults\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1424\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1425\u001b[0m \u001b[0;31m# For each user-defined class that subclasses ScriptModule this meta-class,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mRuntimeError\u001b[0m: \nmodule has no attribute 'stride':\nat /usr/local/lib/python3.6/dist-packages/torch/nn/quantized/modules/conv.py:131:36\n def forward(self, input):\n # Temporarily using len(shape) instead of ndim due to JIT issue\n # https://github.com/pytorch/pytorch/issues/23890\n if len(input.shape) != 4:\n raise ValueError(\"Input shape must be `(N, C, H, W)`!\")\n return ops.quantized.conv2d(input,\n self._packed_params,\n self.stride, self.padding,\n ~~~~~~~~~~~ <--- HERE\n self.dilation, self.groups,\n self.scale, self.zero_point)\n'__torch__.torch.nn.quantized.modules.conv.Conv2d.forward' is being compiled since it was called from '__torch__.ScriptableModule.forward'\nat <ipython-input-7-be83f8971396>:8:15\n def forward(self, image):\n return self.conv(image)\n ~~~~~~~~~~~~~~~ <--- HERE\n"
]
}
]
}
]
}
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