TensorFlow 2 version View source on GitHub

Class Permute

Permutes the dimensions of the input according to a given pattern.

Inherits From: Layer


Useful for e.g. connecting RNNs and convnets together.


model = Sequential()
model.add(Permute((2, 1), input_shape=(10, 64)))
# now: model.output_shape == (None, 64, 10)
# note: `None` is the batch dimension


  • 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.


View source