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Class Permute
Permutes the dimensions of the input according to a given pattern.
Inherits From: Layer
Aliases:
Useful for e.g. connecting RNNs and convnets together.
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.
__init__
__init__(
dims,
**kwargs
)