class_docstr: Represents the shape of a `Tensor`.
  
  A `TensorShape` represents a possibly-partial shape specification for a
  `Tensor`. It may be one of the following:
  
  * *Fully-known shape:* has a known number of dimensions and a known size
    for each dimension. e.g. `TensorShape([16, 256])`
  * *Partially-known shape:* has a known number of dimensions, and an unknown
    size for one or more dimension. e.g. `TensorShape([None, 256])`
  * *Unknown shape:* has an unknown number of dimensions, and an unknown
    size in all dimensions. e.g. `TensorShape(None)`
  
  If a tensor is produced by an operation of type `"Foo"`, its shape
  may be inferred if there is a registered shape function for
  `"Foo"`. See @{$adding_an_op#shape-functions-in-c$`Shape functions in C++`}
  for details of shape functions and how to register them. Alternatively,
  the shape may be set explicitly using @{tf.Tensor.set_shape}.
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docstr: Returns the concatenation of the dimension in `self` and `other`.
  
  *N.B.* If either `self` or `other` is completely unknown,
  concatenation will discard information about the other shape. In
  future, we might support concatenation that preserves this
  information for use with slicing.
  
  Args:
    other: Another `TensorShape`.
  
  Returns:
    A `TensorShape` whose dimensions are the concatenation of the
    dimensions in `self` and `other`.
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code: def concatenate(self, other):
      """Returns the concatenation of the dimension in `self` and `other`.
  
      *N.B.* If either `self` or `other` is completely unknown,
      concatenation will discard information about the other shape. In
      future, we might support concatenation that preserves this
      information for use with slicing.
  
      Args:
        other: Another `TensorShape`.
  
      Returns:
        A `TensorShape` whose dimensions are the concatenation of the
        dimensions in `self` and `other`.
      """
      # TODO(mrry): Handle the case where we concatenate a known shape with a
      # completely unknown shape, so that we can use the partial information.
      other = as_shape(other)
      if self._dims is None or other.dims is None:
          return unknown_shape()
      else:
          return TensorShape(self._dims + other.dims)
  
imports: from .None import compat, dtypes
  from tensorboard.compat.proto import tensor_shape_pb2
label_desc: Use image node_id 13 for calling the TensorShape obj's underlying member method code with example usage: obj.concatenate(other) and returns: unknown_shape, TensorShape