5.3. TensorFlow 2
3.2.0
New features
None
Bug Fixes
None
Other improvements
Make TensorFlow for the IPU compatible with NumPy version 1.24.
Known issues
TensorFlow 2 IPUStrategy is initialised with the wrong number of replicas.
When training a model with multiple replicas, this issue causes an optimizer to apply the sum of the gradients, instead of the mean, over all the replicas. A workaround is for the user to provide a
gradient_transformer
function to the optimizer that divides the gradients (after the sum-reduction across replicas) by the number of replicas being used.See, for example, the optimizer_factory module in our TensorFlow 2 CNN example.
The program can terminate unexpectedly if you provide a 0-dimensional Tensor to a
tf.Dataset
.
Compatibility changes
None
3.1.0
New features
Simplified public API for collectives.
Bug Fixes
None
Other improvements
Improved documentation on recomputation.
Known issues
TensorFlow 2 IPUStrategy is initialised with the wrong number of replicas.
When training a model with multiple replicas, this issue causes an optimizer to apply the sum of the gradients, instead of the mean, over all the replicas. A workaround is for the user to provide a
gradient_transformer
function to the optimizer that divides the gradients (after the sum-reduction across replicas) by the number of replicas being used.See, for example, the optimizer_factory module in our TensorFlow 2 CNN example.
The program can terminate unexpectedly if you provide a 0-dimensional Tensor to a
tf.Dataset
.
Compatibility changes
Compatibility changes are listed in the user guide Targeting the IPU from TensorFlow 2: