from tensorflow.python.framework import ops


  Returns:
    A `Tensor` with type `tf.float32`.  The max pooled output tensor.
  """
  with ops.op_scope([value], name, "MaxPool") as name:
    value = ops.convert_to_tensor(value, name="input")
    return gen_nn_ops._max_pool(value, ksize=ksize, strides=strides,
                                padding=padding,
                                data_format=data_format,
                                name=name)


ops.RegisterShape("Relu")(common_shapes.unchanged_shape)
ops.RegisterShape("Relu6")(common_shapes.unchanged_shape)
ops.RegisterShape("Elu")(common_shapes.unchanged_shape)
ops.RegisterShape("Softplus")(common_shapes.unchanged_shape)
ops.RegisterShape("Softsign")(common_shapes.unchanged_shape)


@ops.RegisterShape("ReluGrad")
@ops.RegisterShape("Relu6Grad")
@ops.RegisterShape("EluGrad")
@ops.RegisterShape("SoftplusGrad")
@ops.RegisterShape("SoftsignGrad")
def _BinaryElementwiseShape(op):
  """Returns same shape as both inputs to op.

  Args:
