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 a list of Dimensions, or None if the shape is
  unspecified.
docstr_tok: ["Returns","a","list","of","Dimensions",",","or","None","if","the","shape","is","unspecified","."]
code: def dims(self):
      """Returns a list of Dimensions, or None if the shape is
      unspecified."""
      return self._dims
  
imports: from .None import compat, dtypes
  from tensorboard.compat.proto import tensor_shape_pb2
label_desc: Use image node_id 4 for calling the TensorShape obj's underlying member method code with example usage: obj.dims() and returns: self