|TensorFlow 2.0 version||View source on GitHub|
Compatibility utility required to allow for both V1 and V2 behavior in TF.
tf.compat.dimension_at_index( shape, index )
Until the release of TF 2.0, we need the legacy behavior of
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.
shape: A TensorShape instance.
index: An integer index.
A dimension object.