class_docstr: A layer that reshapes high-dimension input into a vector.
  
  Then we often apply Dense, RNN, Concat and etc on the top of a flatten layer.
  [batch_size, mask_row, mask_col, n_mask] ---> [batch_size, mask_row * mask_col * n_mask]
  
  Parameters
  ----------
  name : None or str
      A unique layer name.
  
  Examples
  --------
  >>> x = tl.layers.Input([8, 4, 3], name='input')
  >>> y = tl.layers.Flatten(name='flatten')(x)
  [8, 12]
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code: def __repr__(self):
      s = "{classname}("
      s += "name='{name}'"
      s += ")"
      return s.format(
          classname=self.__class__.__name__, **self.__dict__
      )
  
imports: import tensorflow
  from tensorlayer import logging
  from tensorlayer.decorators import deprecated_alias
  from tensorlayer.layers.core import Layer
  from tensorlayer.layers.utils import flatten_reshape
label_desc: Use image node_id 2 for calling the Flatten obj's underlying member method code with example usage: obj.__repr__() and returns: s