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Permutes the dimensions of the input according to a given pattern.
Compat aliases for migration
See Migration guide for more details.
tf.keras.layers.Permute( dims, **kwargs )
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
| || Tuple of integers. Permutation pattern, does not include the samples dimension. Indexing starts at 1. For instance, |
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.
Same as the input shape, but with the dimensions re-ordered according to the specified pattern.
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.