tf.keras.layers.Permute

TensorFlow 1 version View source on GitHub

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

Inherits From: Layer

tf.keras.layers.Permute(
    dims, **kwargs
)

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

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.