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September 9, 2015 20:36
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import theano | |
from theano import tensor as T | |
import numpy as np | |
from theano.sandbox.cuda.dnn import dnn_conv | |
from theano.sandbox.cuda import host_from_gpu | |
from contexttimer import Timer | |
import theano.compile.mode | |
import theano.printing | |
def speed_test(_func, input_shape): | |
x_val = np.random.randn(*input_shape).astype("float32") | |
X.set_value(x_val) | |
avg = [] | |
for i in range(40): | |
with Timer() as t: | |
_func() | |
avg.append(t.elapsed) | |
print np.mean(avg), np.std(avg) | |
def shared_floatx(*shape): | |
return theano.shared(np.random.randn(*shape).astype("float32")) | |
X = shared_floatx(128, 64, 112, 112) | |
W = shared_floatx(32, 64, 7, 7) | |
y = dnn_conv(X, W, algo="small", border_mode=(0,0))[0,0,0,0] | |
_func = theano.function([], y) | |
speed_test(_func, X.get_value().shape) | |
y = dnn_conv(X, W, algo="large", border_mode=(0,0))[0,0,0,0] | |
_func = theano.function([], y) | |
speed_test(_func, X.get_value().shape) | |
y = dnn_conv(X, W, algo="fft", border_mode=(0,0))[0,0,0,0] | |
_func = theano.function([], y) | |
speed_test(_func, X.get_value().shape) |
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