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theano_tensorflow_speed_comparison
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import tensorflow as tf\n", | |
"import numpy as np\n", | |
"import theano\n", | |
"import theano.tensor as tt\n", | |
"\n", | |
"tf.enable_eager_execution()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"'1.13.0-dev20190104'" | |
] | |
}, | |
"execution_count": 2, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"tf.__version__" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"'1.0.3'" | |
] | |
}, | |
"execution_count": 3, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"theano.__version__" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 11, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"x = np.random.randn(100, 100)\n", | |
"y = np.random.randn(100, 100)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 12, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"@tf.contrib.eager.defun\n", | |
"def f_tf_defun(x, y):\n", | |
" return tf.reduce_mean(tf.multiply(x ** 2, 3) + y)\n", | |
"\n", | |
"def f_tf(x, y):\n", | |
" return tf.reduce_mean(tf.multiply(x ** 2, 3) + y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 13, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<tf.Tensor: id=24420, shape=(), dtype=float64, numpy=3.06705004392501>" | |
] | |
}, | |
"execution_count": 13, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"f_tf_defun(x, y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 14, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"212 µs ± 31.6 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n" | |
] | |
} | |
], | |
"source": [ | |
"%%timeit\n", | |
"f_tf_defun(x, y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 15, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"84.4 µs ± 3.7 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n" | |
] | |
} | |
], | |
"source": [ | |
"%%timeit\n", | |
"f_tf(x, y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 16, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"x_t = tt.dmatrix()\n", | |
"y_t = tt.dmatrix()\n", | |
"expr = tt.mean(tt.mul(x_t ** 2, 3) + y_t)\n", | |
"\n", | |
"f_theano = theano.function([x_t, y_t], expr)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 17, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"34.7 µs ± 1.58 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n" | |
] | |
} | |
], | |
"source": [ | |
"%%timeit\n", | |
"f_theano(x, y)" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"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": "3.6.7" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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