Missed TensorFlow World? Check out the recap. Learn more

tf.dimension_at_index

tf.dimension_at_index(
    shape,
    index
)

Defined in tensorflow/python/framework/tensor_shape.py.

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.