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@madaan
Created June 14, 2017 20:14
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{
"cells": [
{
"cell_type": "code",
"execution_count": 81,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from __future__ import print_function\n",
"import keras\n",
"from keras.datasets import mnist\n",
"from keras.models import Sequential\n",
"from keras.layers import *\n",
"from keras.optimizers import RMSprop\n",
"from keras.models import Model\n",
"from keras.layers import Input, Dense\n",
"import scipy.stats\n",
"import math\n",
"from IPython.display import SVG\n",
"from keras.utils.vis_utils import model_to_dot"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Prepare the dataset"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7ff8dbcb9cd0>]"
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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kBT09QGMj25UFElNZXV163BDBC/Lv6uI8d9rVvRF8JH+pPmVVLBJVpe50O4nkrxvQpJGl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\nSUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ff8dbbccb90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ip_range = np.arange(-20, 20, 0.1)\n",
"test_range = np.arange(30, 60, 0.1)\n",
"y = np.sin(ip_range)\n",
"y_test = np.sin(test_range)\n",
"plt.plot(ip_range, y)"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"window = 8"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"train_x = np.array([np.array(y[i:i + window]) for i in range(len(y) - window)])\n",
"train_y = np.array([np.array(y[i + window]) for i in range(len(y) - window)])\n",
"test_x = np.array([np.array(y_test[i:i + window]) for i in range(len(y_test) - window)])\n",
"test_y = np.array([np.array(y_test[i + window]) for i in range(len(y_test) - window)])"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(392, 8)"
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_x.shape"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(392,)"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_y.shape"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([-0.91294525, -0.8676441 , -0.81367374, -0.75157342, -0.68196362,\n",
" -0.60553987, -0.52306577, -0.43536536])"
]
},
"execution_count": 87,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_x[0]"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"-0.3433149288198854"
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_y[0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Prepare the model"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
"input_6 (InputLayer) (None, 8) 0 \n",
"_________________________________________________________________\n",
"dense_26 (Dense) (None, 1800) 16200 \n",
"_________________________________________________________________\n",
"batch_normalization_21 (Batc (None, 1800) 7200 \n",
"_________________________________________________________________\n",
"dense_27 (Dense) (None, 900) 1620900 \n",
"_________________________________________________________________\n",
"batch_normalization_22 (Batc (None, 900) 3600 \n",
"_________________________________________________________________\n",
"dense_28 (Dense) (None, 450) 405450 \n",
"_________________________________________________________________\n",
"batch_normalization_23 (Batc (None, 450) 1800 \n",
"_________________________________________________________________\n",
"dense_29 (Dense) (None, 200) 90200 \n",
"_________________________________________________________________\n",
"batch_normalization_24 (Batc (None, 200) 800 \n",
"_________________________________________________________________\n",
"dense_30 (Dense) (None, 1) 201 \n",
"=================================================================\n",
"Total params: 2,146,351.0\n",
"Trainable params: 2,139,651.0\n",
"Non-trainable params: 6,700.0\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"ip = Input(shape=(window,))\n",
"l1 = Dense(1800, activation='relu')(ip)\n",
"norm1 = BatchNormalization()(l1)\n",
"\n",
"l2 = Dense(900, activation='relu')(norm1)\n",
"norm2 = BatchNormalization()(l2)\n",
"\n",
"l3 = Dense(450, activation='relu')(norm2)\n",
"norm3 = BatchNormalization()(l3)\n",
"\n",
"l4 = Dense(200, activation='relu')(norm3)\n",
"norm4 = BatchNormalization()(l4)\n",
"\n",
"output = Dense(1)(norm4)\n",
"model = Model(ip, output)\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#adam = keras.optimizers.Adam(lr=0.01, beta_1=0.9, beta_2=0.999, epsilon=1e-08, decay=0.0)\n",
"model.compile(loss='mse', optimizer='adam', metrics=['mean_squared_error'])"
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/data/segmentation/segplat-deployments/infra/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:1: UserWarning: The `nb_epoch` argument in `fit` has been renamed `epochs`.\n",
" if __name__ == '__main__':\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/2\n",
"392/392 [==============================] - 20s - loss: 2.0124 - mean_squared_error: 2.0124 \n",
"Epoch 2/2\n",
"392/392 [==============================] - 1s - loss: 0.1694 - mean_squared_error: 0.1694 \n"
]
},
{
"data": {
"text/plain": [
"<keras.callbacks.History at 0x7ff8d2a7e4d0>"
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.fit(train_x, train_y, nb_epoch=2)"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def predict_and_plot(model, x, y_true):\n",
" width = 12\n",
" height = 6\n",
" plt.figure(figsize=(width, height))\n",
" y_preds = model.predict(x)\n",
" plt.plot(y_true, color='green')\n",
" plt.plot(y_preds, color='red')\n",
" plt.legend(['Actual y', 'Predicted y'], loc='upper left')"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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rZJes7RLi+aXwF6SHpSMqKErWdmekzcD3Od/L2iYhngZHA34u+Fn2Neny/pfjm5xvZG1T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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ff8e3a83e10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"predict_and_plot(model, test_x, test_y)"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/2\n",
"\r",
" 32/392 [=>............................] - ETA: 1s - loss: 0.0460 - mean_squared_error: 0.0460"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/data/segmentation/segplat-deployments/infra/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:1: UserWarning: The `nb_epoch` argument in `fit` has been renamed `epochs`.\n",
" if __name__ == '__main__':\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"392/392 [==============================] - 1s - loss: 0.0801 - mean_squared_error: 0.0801 \n",
"Epoch 2/2\n",
"392/392 [==============================] - 1s - loss: 0.0977 - mean_squared_error: 0.0977 \n"
]
},
{
"data": {
"text/plain": [
"<keras.callbacks.History at 0x7ff8db272590>"
]
},
"execution_count": 95,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.fit(train_x, train_y, nb_epoch=2)"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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MZHZJNKC/xYWURBMySmoYiZ6eNB1H6o/Qcc4c+L72e6ZTrYC040J+fD6ONNBx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ctxbcq1/MBqxSgZ0rH56GaEtA9BYkiiIuMxxuPqpKuxMnOlIgnM1XXVWH1oNce3tmJ6h/eGp/DE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\nTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ff8db2725d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"predict_and_plot(model, test_x, test_y)"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/50\n",
"\r",
" 32/392 [=>............................] - ETA: 1s - loss: 0.0264 - mean_squared_error: 0.0264"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/data/segmentation/segplat-deployments/infra/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:1: UserWarning: The `nb_epoch` argument in `fit` has been renamed `epochs`.\n",
" if __name__ == '__main__':\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"392/392 [==============================] - 1s - loss: 0.0318 - mean_squared_error: 0.0318 \n",
"Epoch 2/50\n",
"392/392 [==============================] - 2s - loss: 0.0237 - mean_squared_error: 0.0237 \n",
"Epoch 3/50\n",
"392/392 [==============================] - 1s - loss: 0.0271 - mean_squared_error: 0.0271 \n",
"Epoch 4/50\n",
"392/392 [==============================] - 1s - loss: 0.0334 - mean_squared_error: 0.0334 \n",
"Epoch 5/50\n",
"392/392 [==============================] - 1s - loss: 0.0297 - mean_squared_error: 0.0297 \n",
"Epoch 6/50\n",
"392/392 [==============================] - 1s - loss: 0.0252 - mean_squared_error: 0.0252 \n",
"Epoch 7/50\n",
"392/392 [==============================] - 1s - loss: 0.0400 - mean_squared_error: 0.0400 \n",
"Epoch 8/50\n",
"392/392 [==============================] - 1s - loss: 0.0370 - mean_squared_error: 0.0370 \n",
"Epoch 9/50\n",
"392/392 [==============================] - 2s - loss: 0.0441 - mean_squared_error: 0.0441 \n",
"Epoch 10/50\n",
"392/392 [==============================] - 1s - loss: 0.0405 - mean_squared_error: 0.0405 \n",
"Epoch 11/50\n",
"392/392 [==============================] - 1s - loss: 0.0346 - mean_squared_error: 0.0346 \n",
"Epoch 12/50\n",
"392/392 [==============================] - 2s - loss: 0.0257 - mean_squared_error: 0.0257 \n",
"Epoch 13/50\n",
"392/392 [==============================] - 1s - loss: 0.0264 - mean_squared_error: 0.0264 \n",
"Epoch 14/50\n",
"392/392 [==============================] - 1s - loss: 0.0243 - mean_squared_error: 0.0243 \n",
"Epoch 15/50\n",
"392/392 [==============================] - 2s - loss: 0.0236 - mean_squared_error: 0.0236 \n",
"Epoch 16/50\n",
"392/392 [==============================] - 1s - loss: 0.0294 - mean_squared_error: 0.0294 \n",
"Epoch 17/50\n",
"392/392 [==============================] - 2s - loss: 0.0166 - mean_squared_error: 0.0166 \n",
"Epoch 18/50\n",
"392/392 [==============================] - 1s - loss: 0.0288 - mean_squared_error: 0.0288 \n",
"Epoch 19/50\n",
"392/392 [==============================] - 1s - loss: 0.0280 - mean_squared_error: 0.0280 \n",
"Epoch 20/50\n",
"392/392 [==============================] - 1s - loss: 0.0292 - mean_squared_error: 0.0292 \n",
"Epoch 21/50\n",
"392/392 [==============================] - 1s - loss: 0.0178 - mean_squared_error: 0.0178 \n",
"Epoch 22/50\n",
"392/392 [==============================] - 1s - loss: 0.0167 - mean_squared_error: 0.0167 \n",
"Epoch 23/50\n",
"392/392 [==============================] - 1s - loss: 0.0224 - mean_squared_error: 0.0224 \n",
"Epoch 24/50\n",
"392/392 [==============================] - 1s - loss: 0.0311 - mean_squared_error: 0.0311 \n",
"Epoch 25/50\n",
"392/392 [==============================] - 1s - loss: 0.0257 - mean_squared_error: 0.0257 \n",
"Epoch 26/50\n",
"392/392 [==============================] - 1s - loss: 0.0204 - mean_squared_error: 0.0204 \n",
"Epoch 27/50\n",
"392/392 [==============================] - 1s - loss: 0.0270 - mean_squared_error: 0.0270 \n",
"Epoch 28/50\n",
"392/392 [==============================] - 1s - loss: 0.0133 - mean_squared_error: 0.0133 \n",
"Epoch 29/50\n",
"392/392 [==============================] - 1s - loss: 0.0322 - mean_squared_error: 0.0322 \n",
"Epoch 30/50\n",
"392/392 [==============================] - 1s - loss: 0.0218 - mean_squared_error: 0.0218 \n",
"Epoch 31/50\n",
"392/392 [==============================] - 1s - loss: 0.0164 - mean_squared_error: 0.0164 \n",
"Epoch 32/50\n",
"392/392 [==============================] - 1s - loss: 0.0162 - mean_squared_error: 0.0162 \n",
"Epoch 33/50\n",
"392/392 [==============================] - 1s - loss: 0.0214 - mean_squared_error: 0.0214 \n",
"Epoch 34/50\n",
"392/392 [==============================] - 1s - loss: 0.0182 - mean_squared_error: 0.0182 \n",
"Epoch 35/50\n",
"392/392 [==============================] - 1s - loss: 0.0245 - mean_squared_error: 0.0245 \n",
"Epoch 36/50\n",
"392/392 [==============================] - 1s - loss: 0.0233 - mean_squared_error: 0.0233 \n",
"Epoch 37/50\n",
"392/392 [==============================] - 1s - loss: 0.0300 - mean_squared_error: 0.0300 \n",
"Epoch 38/50\n",
"392/392 [==============================] - 1s - loss: 0.0311 - mean_squared_error: 0.0311 \n",
"Epoch 39/50\n",
"392/392 [==============================] - 2s - loss: 0.0131 - mean_squared_error: 0.0131 \n",
"Epoch 40/50\n",
"392/392 [==============================] - 1s - loss: 0.0316 - mean_squared_error: 0.0316 \n",
"Epoch 41/50\n",
"392/392 [==============================] - 1s - loss: 0.0283 - mean_squared_error: 0.0283 \n",
"Epoch 42/50\n",
"392/392 [==============================] - 2s - loss: 0.0280 - mean_squared_error: 0.0280 \n",
"Epoch 43/50\n",
"392/392 [==============================] - 1s - loss: 0.0201 - mean_squared_error: 0.0201 \n",
"Epoch 44/50\n",
"392/392 [==============================] - 1s - loss: 0.0185 - mean_squared_error: 0.0185 \n",
"Epoch 45/50\n",
"392/392 [==============================] - 1s - loss: 0.0195 - mean_squared_error: 0.0195 \n",
"Epoch 46/50\n",
"392/392 [==============================] - 1s - loss: 0.0189 - mean_squared_error: 0.0189 \n",
"Epoch 47/50\n",
"392/392 [==============================] - 1s - loss: 0.0356 - mean_squared_error: 0.0356 \n",
"Epoch 48/50\n",
"392/392 [==============================] - 1s - loss: 0.0333 - mean_squared_error: 0.0333 \n",
"Epoch 49/50\n",
"392/392 [==============================] - 1s - loss: 0.0275 - mean_squared_error: 0.0275 \n",
"Epoch 50/50\n",
"392/392 [==============================] - 1s - loss: 0.0378 - mean_squared_error: 0.0378 \n"
]
},
{
"data": {
"text/plain": [
"<keras.callbacks.History at 0x7ff9596c5e50>"
]
},
"execution_count": 98,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.fit(train_x, train_y, nb_epoch=50)"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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V/fpxsxRFUYui7tGLpdFLSSlPoaShRJ+pJa288oo60hUYCMD69PXk/fJJdTQjNrZ/x1y+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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ff9596c5e10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"predict_and_plot(model, test_x, test_y)"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/20\n",
"\r",
" 32/392 [=>............................] - ETA: 1s - loss: 0.0084 - mean_squared_error: 0.0084"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/data/segmentation/segplat-deployments/infra/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:1: UserWarning: The `nb_epoch` argument in `fit` has been renamed `epochs`.\n",
" if __name__ == '__main__':\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"392/392 [==============================] - 1s - loss: 0.0444 - mean_squared_error: 0.0444 \n",
"Epoch 2/20\n",
"392/392 [==============================] - 1s - loss: 0.0186 - mean_squared_error: 0.0186 \n",
"Epoch 3/20\n",
"392/392 [==============================] - 1s - loss: 0.0402 - mean_squared_error: 0.0402 \n",
"Epoch 4/20\n",
"392/392 [==============================] - 1s - loss: 0.0160 - mean_squared_error: 0.0160 \n",
"Epoch 5/20\n",
"392/392 [==============================] - 1s - loss: 0.0133 - mean_squared_error: 0.0133 \n",
"Epoch 6/20\n",
"392/392 [==============================] - 1s - loss: 0.0147 - mean_squared_error: 0.0147 \n",
"Epoch 7/20\n",
"392/392 [==============================] - 2s - loss: 0.0190 - mean_squared_error: 0.0190 \n",
"Epoch 8/20\n",
"392/392 [==============================] - 1s - loss: 0.0272 - mean_squared_error: 0.0272 \n",
"Epoch 9/20\n",
"392/392 [==============================] - 1s - loss: 0.0471 - mean_squared_error: 0.0471 \n",
"Epoch 10/20\n",
"392/392 [==============================] - 1s - loss: 0.0189 - mean_squared_error: 0.0189 \n",
"Epoch 11/20\n",
"392/392 [==============================] - 1s - loss: 0.0322 - mean_squared_error: 0.0322 \n",
"Epoch 12/20\n",
"392/392 [==============================] - 1s - loss: 0.0207 - mean_squared_error: 0.0207 \n",
"Epoch 13/20\n",
"392/392 [==============================] - 1s - loss: 0.0215 - mean_squared_error: 0.0215 \n",
"Epoch 14/20\n",
"392/392 [==============================] - 1s - loss: 0.0256 - mean_squared_error: 0.0256 \n",
"Epoch 15/20\n",
"392/392 [==============================] - 1s - loss: 0.0130 - mean_squared_error: 0.0130 \n",
"Epoch 16/20\n",
"392/392 [==============================] - 1s - loss: 0.0134 - mean_squared_error: 0.0134 \n",
"Epoch 17/20\n",
"392/392 [==============================] - 1s - loss: 0.0325 - mean_squared_error: 0.0325 \n",
"Epoch 18/20\n",
"392/392 [==============================] - 1s - loss: 0.0250 - mean_squared_error: 0.0250 \n",
"Epoch 19/20\n",
"392/392 [==============================] - 1s - loss: 0.0254 - mean_squared_error: 0.0254 \n",
"Epoch 20/20\n",
"392/392 [==============================] - 1s - loss: 0.0211 - mean_squared_error: 0.0211 \n"
]
},
{
"data": {
"text/plain": [
"<keras.callbacks.History at 0x7ff8d18cbd10>"
]
},
"execution_count": 100,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.fit(train_x, train_y, nb_epoch=20)"
]
},
{
"cell_type": "code",
"execution_count": 101,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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Vr35FU1MTL7/8MmvXrqWhoQGA+++/n2nTplFfX88vf/lL3n///Zse98EHH7ym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\nQATRAAAAQEAE0QAAAEBABNEAAABAQP8PYi+aoMsmUbEAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ff8d18cbdd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"predict_and_plot(model, test_x, test_y)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.13"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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