184 lines
24 KiB
Plaintext
184 lines
24 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Using TensorFlow backend.\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
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"/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
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" np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
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]
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}
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],
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"source": [
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"from xception_custom import Xception_wrapper"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from keras.layers import Input"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[[155 225 83]\n",
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" [174 33 86]\n",
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" [ 24 223 10]\n",
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" ...\n",
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" [147 233 79]\n",
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" [232 187 173]\n",
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" [ 69 126 85]]\n",
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"\n",
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" [[166 203 47]\n",
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" [111 65 37]\n",
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" [210 182 244]\n",
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" ...\n",
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" [154 62 70]\n",
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" [ 62 93 101]\n",
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" [132 231 126]]\n",
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"\n",
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" [[ 30 110 125]\n",
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" [242 45 71]\n",
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" [150 10 217]\n",
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" ...\n",
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" [ 38 165 128]\n",
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" [ 64 58 127]\n",
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" [179 174 72]]\n",
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"\n",
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" ...\n",
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"\n",
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" [[159 2 99]\n",
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" [201 220 158]\n",
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" [170 172 13]\n",
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" ...\n",
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" [ 79 72 65]\n",
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" [ 10 228 7]\n",
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" [ 99 60 129]]\n",
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"\n",
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" [[187 249 6]\n",
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" [ 57 166 83]\n",
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" [187 243 66]\n",
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" ...\n",
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" [109 184 147]\n",
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" [142 158 83]\n",
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" [190 61 30]]\n",
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"\n",
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" [[146 238 74]\n",
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" [156 20 43]\n",
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" [ 55 217 43]\n",
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" ...\n",
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" [208 181 141]\n",
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" [196 88 15]\n",
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" [132 225 63]]]\n"
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]
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},
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{
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"ename": "TypeError",
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"evalue": "Error converting shape to a TensorShape: only size-1 arrays can be converted to Python scalars.",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/eager/execute.py\u001b[0m in \u001b[0;36mmake_shape\u001b[0;34m(v, arg_name)\u001b[0m\n\u001b[1;32m 145\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 146\u001b[0;31m \u001b[0mshape\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtensor_shape\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_shape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\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 147\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/tensor_shape.py\u001b[0m in \u001b[0;36mas_shape\u001b[0;34m(shape)\u001b[0m\n\u001b[1;32m 1203\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1204\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mTensorShape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mshape\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 1205\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/tensor_shape.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, dims)\u001b[0m\n\u001b[1;32m 773\u001b[0m \u001b[0;31m# Got a list of dimensions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 774\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dims\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mas_dimension\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0md\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdims_iter\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 775\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/tensor_shape.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 773\u001b[0m \u001b[0;31m# Got a list of dimensions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 774\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dims\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mas_dimension\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0md\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdims_iter\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 775\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/tensor_shape.py\u001b[0m in \u001b[0;36mas_dimension\u001b[0;34m(value)\u001b[0m\n\u001b[1;32m 715\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 716\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mDimension\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\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 717\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/framework/tensor_shape.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, value)\u001b[0m\n\u001b[1;32m 184\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 185\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_value\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\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 186\u001b[0m if (not isinstance(value, compat.bytes_or_text_types) and\n",
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"\u001b[0;31mTypeError\u001b[0m: only size-1 arrays can be converted to Python scalars",
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"\nDuring handling of the above exception, another exception occurred:\n",
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"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-8-8f06c869009e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mxception\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mXception_wrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minclude_top\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweights\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'imagenet'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput_tensor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpooling\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'xception:'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mxception\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mtest_xception_shape\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[0m",
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"\u001b[0;32m<ipython-input-8-8f06c869009e>\u001b[0m in \u001b[0;36mtest_xception_shape\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0minput_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m256\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m240\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m320\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\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[1;32m 3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0minp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mInput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_\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 5\u001b[0m \u001b[0mxception\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mXception_wrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minclude_top\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweights\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'imagenet'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput_tensor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpooling\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'xception:'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mxception\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/keras/engine/input_layer.py\u001b[0m in \u001b[0;36mInput\u001b[0;34m(shape, batch_shape, name, dtype, sparse, tensor)\u001b[0m\n\u001b[1;32m 176\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 177\u001b[0m \u001b[0msparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msparse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 178\u001b[0;31m input_tensor=tensor)\n\u001b[0m\u001b[1;32m 179\u001b[0m \u001b[0;31m# Return tensor including _keras_shape and _keras_history.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 180\u001b[0m \u001b[0;31m# Note that in this case train_output and test_output are the same pointer.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/keras/legacy/interfaces.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 89\u001b[0m warnings.warn('Update your `' + object_name + '` call to the ' +\n\u001b[1;32m 90\u001b[0m 'Keras 2 API: ' + signature, stacklevel=2)\n\u001b[0;32m---> 91\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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 92\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_original_function\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 93\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/keras/engine/input_layer.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, input_shape, batch_size, batch_input_shape, dtype, input_tensor, sparse, name)\u001b[0m\n\u001b[1;32m 85\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 86\u001b[0m \u001b[0msparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msparse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 87\u001b[0;31m name=self.name)\n\u001b[0m\u001b[1;32m 88\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 89\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_placeholder\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py\u001b[0m in \u001b[0;36mplaceholder\u001b[0;34m(shape, ndim, dtype, sparse, name)\u001b[0m\n\u001b[1;32m 734\u001b[0m \u001b[0mdtype\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfloatx\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[1;32m 735\u001b[0m x = tf_keras_backend.placeholder(\n\u001b[0;32m--> 736\u001b[0;31m shape=shape, ndim=ndim, dtype=dtype, sparse=sparse, name=name)\n\u001b[0m\u001b[1;32m 737\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mshape\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 738\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mndim\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/keras/backend.py\u001b[0m in \u001b[0;36mplaceholder\u001b[0;34m(shape, ndim, dtype, sparse, name)\u001b[0m\n\u001b[1;32m 996\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marray_ops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msparse_placeholder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 997\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 998\u001b[0;31m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marray_ops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplaceholder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\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 999\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1000\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/ops/array_ops.py\u001b[0m in \u001b[0;36mplaceholder\u001b[0;34m(dtype, shape, name)\u001b[0m\n\u001b[1;32m 2141\u001b[0m \"eager execution.\")\n\u001b[1;32m 2142\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2143\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mgen_array_ops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplaceholder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\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 2144\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2145\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/ops/gen_array_ops.py\u001b[0m in \u001b[0;36mplaceholder\u001b[0;34m(dtype, shape, name)\u001b[0m\n\u001b[1;32m 6258\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mshape\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6259\u001b[0m \u001b[0mshape\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6260\u001b[0;31m \u001b[0mshape\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_execute\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmake_shape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"shape\"\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 6261\u001b[0m _, _, _op = _op_def_lib._apply_op_helper(\n\u001b[1;32m 6262\u001b[0m \"Placeholder\", dtype=dtype, shape=shape, name=name)\n",
|
|
"\u001b[0;32m/netpool/homes/wangyo/.conda/envs/tf-cuda9/lib/python3.7/site-packages/tensorflow/python/eager/execute.py\u001b[0m in \u001b[0;36mmake_shape\u001b[0;34m(v, arg_name)\u001b[0m\n\u001b[1;32m 146\u001b[0m \u001b[0mshape\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtensor_shape\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_shape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 147\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 148\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Error converting %s to a TensorShape: %s.\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0marg_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0me\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[0m\u001b[1;32m 149\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 150\u001b[0m raise ValueError(\"Error converting %s to a TensorShape: %s.\" % (arg_name,\n",
|
|
"\u001b[0;31mTypeError\u001b[0m: Error converting shape to a TensorShape: only size-1 arrays can be converted to Python scalars."
|
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]
|
|
}
|
|
],
|
|
"source": [
|
|
"def test_xception_shape():\n",
|
|
" input_ = np.random.randint(0,256, (240,320,3))\n",
|
|
" print(input_)\n",
|
|
" inp = Input(input_)\n",
|
|
" xception = Xception_wrapper(include_top=False, weights='imagenet', input_tensor=inp, pooling=None)\n",
|
|
" print('xception:',xception.output.shape)\n",
|
|
"test_xception_shape()"
|
|
]
|
|
},
|
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{
|
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"cell_type": "code",
|
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"execution_count": null,
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"metadata": {},
|
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"outputs": [],
|
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"source": []
|
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}
|
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],
|
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"metadata": {
|
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"kernelspec": {
|
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"display_name": "Python 3",
|
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"language": "python",
|
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"name": "python3"
|
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},
|
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"language_info": {
|
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"codemirror_mode": {
|
|
"name": "ipython",
|
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"version": 3
|
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},
|
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"file_extension": ".py",
|
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"mimetype": "text/x-python",
|
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"name": "python",
|
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"nbconvert_exporter": "python",
|
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"pygments_lexer": "ipython3",
|
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"version": "3.7.9"
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}
|
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},
|
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"nbformat": 4,
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"nbformat_minor": 4
|
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}
|