def __init__(self, event_shape_out, event_shape_in=(-<NUM_LIT:1>,),<EOL>validate_args=False, name=None):
with tf.name_scope(name or '<STR_LIT>'):<EOL><INDENT>event_shape_out = tf.convert_to_tensor(<EOL>value=event_shape_out, name='<STR_LIT>', dtype_hint=tf.int32)<EOL>event_shape_in = tf.convert_to_tensor(<EOL>value=event_shape_in, name='<STR_LIT>', dtype_hint=tf.int32)<EOL>forward_min_event_ndims_ = tensorshape_util.num_elements(<EOL>event_shape_in.shape)<EOL>if forward_min_event_ndims_ is None:<EOL><INDENT>raise NotImplementedError(<EOL>'<STR_LIT>'<EOL>'<STR_LIT>')<EOL><DEDENT>inverse_min_event_ndims_ = tensorshape_util.num_elements(<EOL>event_shape_out.shape)<EOL>if inverse_min_event_ndims_ is None:<EOL><INDENT>raise NotImplementedError(<EOL>'<STR_LIT>'<EOL>'<STR_LIT>')<EOL><DEDENT>assertions = []<EOL>assertions.extend(_maybe_check_valid_shape(<EOL>event_shape_out, validate_args))<EOL>assertions.extend(_maybe_check_valid_shape(<EOL>event_shape_in, validate_args))<EOL>if assertions:<EOL><INDENT>with tf.control_dependencies(assertions):<EOL><INDENT>event_shape_in = tf.identity(<EOL>event_shape_in, name='<STR_LIT>')<EOL>event_shape_out = tf.identity(<EOL>event_shape_out, name='<STR_LIT>')<EOL><DEDENT><DEDENT>self._event_shape_in = event_shape_in<EOL>self._event_shape_out = event_shape_out<EOL>super(Reshape, self).__init__(<EOL>forward_min_event_ndims=forward_min_event_ndims_,<EOL>inverse_min_event_ndims=inverse_min_event_ndims_,<EOL>is_constant_jacobian=True,<EOL>validate_args=validate_args,<EOL>name=name or '<STR_LIT>')<EOL><DEDENT>
Creates a `Reshape` bijector.

        Args:
          event_shape_out: An `int`-like vector-shaped `Tensor`
            representing the event shape of the transformed output.
          event_shape_in: An optional `int`-like vector-shape `Tensor`
            representing the event shape of the input. This is required in
            order to define inverse operations; the default of (-1,)
            assumes a vector-shaped input.
          validate_args: Python `bool` indicating whether arguments should
            be checked for correctness.
          name: Python `str`, name given to ops managed by this object.

        Raises:
          TypeError: if either `event_shape_in` or `event_shape_out` has
            non-integer `dtype`.
          ValueError: if either of `event_shape_in` or `event_shape_out`
           has non-vector shape (`rank > 1`), or if their sizes do not
           match.