tf.keras.layers.Permute

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

Inherits From: Layer

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.layers.Permute

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

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.