class_docstr: Concatenates a list of inputs.
  
  It takes as input a list of tensors, all of the same shape except
  for the concatenation axis, and returns a single tensor that is the
  concatenation of all inputs.
  
  Examples:
  
  >>> x = np.arange(20).reshape(2, 2, 5)
  >>> y = np.arange(20, 30).reshape(2, 1, 5)
  >>> keras.layers.Concatenate(axis=1)([x, y])
  
  Usage in a Keras model:
  
  >>> x1 = keras.layers.Dense(8)(np.arange(10).reshape(5, 2))
  >>> x2 = keras.layers.Dense(8)(np.arange(10, 20).reshape(5, 2))
  >>> y = keras.layers.Concatenate()([x1, x2])
  
  Args:
      axis: Axis along which to concatenate.
      **kwargs: Standard layer keyword arguments.
  
  Returns:
      A tensor, the concatenation of the inputs alongside axis `axis`.
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code: def get_config(self):
      config = {"axis": self.axis}
      base_config = super().get_config()
      return dict(list(base_config.items()) + list(config.items()))
  
file_path: keras/keras/layers/merging/concatenate.py
imports: from keras import ops
  from keras.api_export import keras_export
  from keras.layers.merging.base_merge import Merge
label_desc: Use image node_id 6 for calling the Concatenate obj's underlying member method code with example usage: obj.get_config() and returns: dict