In [1]:
import tensorflow as tf
import numpy as np
import time
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
In [2]:
image_tensor = tf.placeholder(tf.float32, shape=[100, 227, 227, 3], name='input_tensor')
kernel_tensor = tf.placeholder(tf.float32, shape=[11, 11, 3, 96], name='kernel_tensor')
conv2d_out = tf.nn.conv2d(image_tensor, kernel_tensor, strides=[1, 4, 4, 1], padding='VALID', name='output')
In [3]:
def run_conv2d(sess, image, kernel):
out = sess.run([conv2d_out], feed_dict={image_tensor:image, kernel_tensor:kernel})
return out
In [10]:
sess = tf.Session()
sess.run(tf.global_variables_initializer())
image = np.random.randn(100, 227, 227, 3)
kernel = np.random.randn(11, 11, 3, 96)
start = time.clock()
run_conv2d(sess, image, kernel)
end = time.clock()
print((end - start)*1000, 'ms')
In [6]:
%timeit run_conv2d(sess, image, kernel)
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