class_docstr: Reshapes an output to a certain shape.
  Supports shape inference by allowing one -1 in the target shape.
  For example, if input_shape = (2, 3, 4), target_shape = (3, -1),
  then output_shape will be (3, 8).
  
  When you use this layer as the first layer of a model, you need to provide the argument
  input_shape (a shape tuple, does not include the batch dimension).
  
  # Arguments
  target_shape: A shape tuple. The target shape that you desire to have.
                Batch dimension should be excluded.
  input_shape: A shape tuple, not including batch.
  name: String to set the name of the layer.
        If not specified, its name will by default to be a generated string.
  
  >>> reshape = Reshape((2, 10), input_shape=(5, 4))
  creating: createZooKerasReshape
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code: def __init__(self, target_shape, input_shape=None, **kwargs):
      super(Reshape, self).__init__(
          None,
          target_shape,
          list(input_shape) if input_shape else None,
          **kwargs,
      )
  
imports: import sys
  from bigdl.util.common import INTMIN
  from ..engine.topology import ZooKerasLayer
label_desc: Use image node_id 1 to create a new Reshape object from inherited base classes: ZooKerasLayer with example: obj = Reshape(target_shape, input_shape)