tf.keras.layers.Permute | TensorFlow v2.0.0 (original) (raw)
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
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tf.compat.v1.keras.layers.Permute
tf.keras.layers.Permute(
dims, **kwargs
)
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.