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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"os.environ['KERAS_BACKEND'] = 'torch'\n",
"\n",
"import keras\n",
"\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"input = keras.random.normal( [32, 20, 8] )\n",
"\n",
"lstm = keras.layers.LSTM(16)\n",
"output = lstm(input)\n",
"\n",
"print('input shape is : ',input.shape)\n",
"print('output shape is : ',output.shape)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"input = keras.random.normal( [32, 20, 8] )\n",
"\n",
"lstm = keras.layers.LSTM(18, return_sequences=True, return_state=True)\n",
"output, memory_state, carry_state = lstm(input)\n",
"\n",
"print('input shape : ',input.shape)\n",
"print('output shape : ',output.shape)\n",
"print('memory_state : ', memory_state.shape)\n",
"print('carry_state : ', memory_state.shape)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "fidle-env",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}