Permute the dimensions of an input according to a given pattern
layer_permute( object, dims, input_shape = NULL, batch_input_shape = NULL, batch_size = NULL, dtype = NULL, name = NULL, trainable = NULL, weights = NULL )
What to call the new
List of integers. Permutation pattern, does not include the
samples dimension. Indexing starts at 1. For instance,
Input shape (list of integers, does not include the samples axis) which is required when using this layer as the first layer in a model.
Shapes, including the batch size. For instance,
Fixed batch size for layer
The data type expected by the input, as a string (
An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn't provided.
Whether the layer weights will be updated during training.
Initial weights for layer.
Useful for e.g. connecting RNNs and convnets together.
Input shape: Arbitrary
Output shape: Same as the input shape, but with the dimensions re-ordered according to the specified pattern.