Permutes the dimensions of the input according to a given pattern.
Inherits From: Layer
, Module
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
Args |
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.
|
|
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.
|