深度学习面试题25：分离卷积(separable卷积)

　　举例

　　单个张量与多个卷积核的分离卷积

　　参考资料

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举例

分离卷积就是先在深度上分别卷积，然后再进行卷积，对应代码为：

import tensorflow as tf

# [batch, in_height, in_width, in_channels]
input =tf.reshape(tf.constant([2,5,3,3,8,2,6,1,1,2,5,4,7,9,2,3,-1,3], tf.float32),[1,3,3,2])

# [filter_height, filter_width, in_channels, out_channels]
depthwise_filter = tf.reshape(tf.constant([3,1,-2,2,-1,-3,4,5], tf.float32),[2,2,2,1])
pointwise_filter = tf.reshape(tf.constant([-1,1], tf.float32),[1,1,2,1])

print(tf.Session().run(tf.nn.separable_conv2d(input,depthwise_filter,pointwise_filter,[1,1,1,1],"VALID")))
[[[[ 20.]
   [  9.]]

  [[-24.]
   [ 29.]]]]

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