class_docstr: Represents the value of one dimension in a TensorShape.
class_docstr_tok: ["Represents","the","value","of","one","dimension","in","a","TensorShape","."]
docstr: Returns the sum of `self` and `other`.
  
  Dimensions are summed as follows:
  
  ```python
  tf.Dimension(m)    + tf.Dimension(n)    == tf.Dimension(m + n)
  tf.Dimension(m)    + tf.Dimension(None) == tf.Dimension(None)
  tf.Dimension(None) + tf.Dimension(n)    == tf.Dimension(None)
  tf.Dimension(None) + tf.Dimension(None) == tf.Dimension(None)
  ```
  
  Args:
    other: Another Dimension, or a value accepted by `as_dimension`.
  
  Returns:
    A Dimension whose value is the sum of `self` and `other`.
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code: def __add__(self, other):
      """Returns the sum of `self` and `other`.
  
      Dimensions are summed as follows:
  
      ```python
      tf.Dimension(m)    + tf.Dimension(n)    == tf.Dimension(m + n)
      tf.Dimension(m)    + tf.Dimension(None) == tf.Dimension(None)
      tf.Dimension(None) + tf.Dimension(n)    == tf.Dimension(None)
      tf.Dimension(None) + tf.Dimension(None) == tf.Dimension(None)
      ```
  
      Args:
        other: Another Dimension, or a value accepted by `as_dimension`.
  
      Returns:
        A Dimension whose value is the sum of `self` and `other`.
      """
      other = as_dimension(other)
      if self._value is None or other.value is None:
          return Dimension(None)
      else:
          return Dimension(self._value + other.value)
  
imports: from .None import compat, dtypes
  from tensorboard.compat.proto import tensor_shape_pb2
label_desc: Use image node_id 13 for calling the Dimension obj's underlying member method code with example usage: obj.__add__(other) and returns: Dimension, Dimension