Permute layer
Permute class
tf_keras.layers.Permute(dims, **kwargs)
Permutes the dimensions of the input according to a given pattern.
Useful e.g. connecting RNNs and convnets.
Example
model = Sequential()
model.add(Permute((2, 1), input_shape=(10, 64)))
# now: model.output_shape == (None, 64, 10)
# note: `None` is the batch dimension
Arguments
- dims: Tuple of integers. Permutation pattern does not include the
samples dimension. Indexing starts at 1.
For instance,
(2, 1)permutes the first and second dimensions of the input.
Input shape
Arbitrary. Use the keyword argument input_shape
(tuple of integers, does not include the samples axis)
when using this layer as the first layer in a model.
Output shape
Same as the input shape, but with the dimensions re-ordered according to the specified pattern.