Does the convolutional layer in TensorFlow support dropout?

Question

I am wondering whether I can simply apply dropout to convolutions in TensorFlow. How will it be applied? Are weights of the convolution mask randomly set to zero while it 'slides' over the input?

Answer 1

You can apply dropout on arbitrary input tensors. How this input was computed doesn't matter; each element of the input will simply either be kept (and scaled, see below) or set to zero.

From https://www.tensorflow.org/api_docs/python/tf/nn/dropout:

With probability keep_prob, outputs the input element scaled up by 1 / keep_prob, otherwise outputs 0. The scaling is so that the expected sum is unchanged.

By default, each element is kept or dropped independently.

For example:

conv = tf.nn.conv2d(...)
drop = tf.nn.dropout(conv, keep_prob=0.5)