class_docstr: Permutes the dimensions of the input according to a given pattern.
  
  Useful e.g. connecting RNNs and convnets.
  
  Args:
      dims: Tuple of integers. Permutation pattern does not include the
          batch dimension. Indexing starts at 1.
          For instance, `(2, 1)` permutes the first and second dimensions
          of the input.
  
  Input shape:
      Arbitrary.
  
  Output shape:
      Same as the input shape, but with the dimensions re-ordered according
      to the specified pattern.
  
  Example:
  
  >>> x = keras.Input(shape=(10, 64))
  >>> y = keras.layers.Permute((2, 1))(x)
  >>> y.shape
  (None, 64, 10)
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code: def get_config(self):
      config = {"dims": self.dims}
      base_config = super().get_config()
      return {**base_config, **config}
  
file_path: keras/keras/layers/reshaping/permute.py
imports: from keras import ops
  from keras.api_export import keras_export
  from keras.backend.common.keras_tensor import KerasTensor
  from keras.layers.input_spec import InputSpec
  from keras.layers.layer import Layer
label_desc: Use image node_id 5 for calling the Permute obj's underlying member method code with example usage: obj.get_config() and returns: dict