Function dimension_at_index

tensorflow/python/framework/tensor_shape.py:134–177

Compatibility utility required to allow for both V1 and V2 behavior in TF. Until the release of TF 2.0, we need the legacy behavior of `TensorShape` to coexist with the new behavior. This utility is a bridge between the two. If you want to retrieve the Dimension instance corresponding to a c

(shape, index)

    "compat.dimension_at_index",
    v1=["dimension_at_index", "compat.dimension_at_index"])
def dimension_at_index(shape, index):
  """Compatibility utility required to allow for both V1 and V2 behavior in TF.

  Until the release of TF 2.0, we need the legacy behavior of `TensorShape` to
  coexist with the new behavior. This utility is a bridge between the two.

  If you want to retrieve the Dimension instance corresponding to a certain
  index in a TensorShape instance, use this utility, like this:

  ```
  # If you had this in your V1 code:
  dim = tensor_shape[i]

  # Use `dimension_at_index` as direct replacement compatible with both V1 & V2:
  dim = dimension_at_index(tensor_shape, i)

  # Another possibility would be this, but WARNING: it only works if the
  # tensor_shape instance has a defined rank.
  dim = tensor_shape.dims[i]  # `dims` may be None if the rank is undefined!

  # In native V2 code, we recommend instead being more explicit:
  if tensor_shape.rank is None:
    dim = Dimension(None)
  else:
    dim = tensor_shape.dims[i]

  # Being more explicit will save you from the following trap (present in V1):
  # you might do in-place modifications to `dim` and expect them to be reflected
  # in `tensor_shape[i]`, but they would not be (as the Dimension object was
  # instantiated on the fly.
  ```

  Arguments:
    shape: A TensorShape instance.
    index: An integer index.

  Returns:
    A dimension object.
  """
  assert isinstance(shape, TensorShape)
  if shape.rank is None:
    return Dimension(None)
  else:
    return shape.dims[index]


@tf_export(v1=["Dimension"])