Created
November 21, 2017 11:45
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Transform performance test
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Transformation performance test" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"import numpy as np" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"def transform_apply(tensor, transform):\n", | |
" feat_tensor = []\n", | |
" org_shape = tensor.shape\n", | |
" for plane in tensor[0]:\n", | |
" feat_tensor.append(transform(plane))\n", | |
" ret = np.concatenate(feat_tensor)\n", | |
" ret = ret.reshape(org_shape)\n", | |
" return ret" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"BD_transforms = [\n", | |
" lambda f:f, \n", | |
" lambda f:np.rot90(f,1), \n", | |
" lambda f:np.rot90(f,2), \n", | |
" lambda f:np.rot90(f,3), \n", | |
" lambda f:np.fliplr(f), \n", | |
" lambda f:np.flipud(f), \n", | |
" lambda f:np.transpose(f), \n", | |
" lambda f:np.fliplr(np.rot90(f, 1))\n", | |
"]" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"BD_fasttrans = [\n", | |
" lambda f: f,\n", | |
" lambda f: np.rot90(f, 1, axes=(2,3)),\n", | |
" lambda f: np.rot90(f, 2, axes=(2,3)),\n", | |
" lambda f: np.rot90(f, 3, axes=(2,3)),\n", | |
" lambda f: f[:, :, :, ::-1],\n", | |
" lambda f: f[:, :, ::-1, :],\n", | |
" lambda f: np.transpose(f, axes=(0, 1, 3, 2)),\n", | |
" lambda f: np.rot90(f, 1, axes=(2,3))[:, :, :, ::-1]\n", | |
"]" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"True\n", | |
"org 2.79942035675e-05\n", | |
"fast 5.63967943192e-08\n", | |
"times 496.379340448\n", | |
"\n", | |
"True\n", | |
"org 0.00023686504364\n", | |
"fast 4.14942979813e-06\n", | |
"times 57.0837573266\n", | |
"\n", | |
"True\n", | |
"org 0.000192616319656\n", | |
"fast 3.43266010284e-06\n", | |
"times 56.1128436505\n", | |
"\n", | |
"True\n", | |
"org 0.000235383987427\n", | |
"fast 4.21041965485e-06\n", | |
"times 55.9051132007\n", | |
"\n", | |
"True\n", | |
"org 6.21682882309e-05\n", | |
"fast 3.42023849487e-07\n", | |
"times 181.765945048\n", | |
"\n", | |
"True\n", | |
"org 6.14371061325e-05\n", | |
"fast 3.40197086334e-07\n", | |
"times 180.592687593\n", | |
"\n", | |
"True\n", | |
"org 5.45855045319e-05\n", | |
"fast 5.8767914772e-07\n", | |
"times 92.8831739966\n", | |
"\n", | |
"True\n", | |
"org 0.000263137102127\n", | |
"fast 4.56223011017e-06\n", | |
"times 57.6772972368\n", | |
"\n" | |
] | |
} | |
], | |
"source": [ | |
"for i in range(0, 8):\n", | |
" t = np.random.randint(low=0, high=2, size=[1,49,19,19])\n", | |
" transform = BD_transforms[i]\n", | |
" fasttrans = BD_fasttrans[i]\n", | |
" \n", | |
" # sanity check\n", | |
" r1 = transform_apply(t, transform)\n", | |
" r2 = fasttrans(t)\n", | |
" sanity = (r1 == r2).all()\n", | |
" print sanity\n", | |
" assert sanity, \"The transformation is not same\"\n", | |
" \n", | |
" # time check\n", | |
" t1 = %timeit -oq transform_apply(t, transform)\n", | |
" t2 = %timeit -oq fasttrans(t)\n", | |
" \n", | |
" print \"org \", t1.best\n", | |
" print \"fast \", t2.best\n", | |
" print \"times\", t1.best / t2.best \n", | |
" print" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"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": "2.7.6" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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