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TensorFlow 1 version
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View source on GitHub
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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 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. |