Tensorflow: What exactly does depthwise convolution do? -


i want use depthwise_conv2d tensorflow. fas understand now, performs regular 2d convolutions every single channel, each depth_multiplier number of features.

then should expect, if depth_multiplier = 1, have number of input channels same number of output channels. why can have 256 input channels , 512 output channels ? channels come from?

the filters of size[filter_height, filter_width, in_channels, channel_multiplier]. if channel_multiplier = 1, same number of input channels output. if n, n*input_channels output channels, each input channel convolved n filters.

for example,

inputs = tf.variable(tf.random_normal((20, 64,64,100))) filters = tf.variable(tf.random_normal((5,5,100,10))) out = tf.nn.depthwise_conv2d(       inputs,       filters,       strides=[1,1,1,1],       padding='same')

you out of shape: shape=(20, 64, 64, 1000)


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