|TensorFlow 1 version||View source on GitHub|
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.
Arbitrary. Use the keyword argument
(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.