Add config option for FP32 embedding grads
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# What does this PR do ?

Add a config option to control whether the distributed Adam optimizer stores embedding grads in FP32.

**Collection**: NLP

# Changelog 
- Add config option for FP32 embedding grads

# Usage

Run GPT, e.g. with the config at https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/language_modeling/conf/megatron_gpt_config.yaml.

Enable the distributed optimizer with `model.optim.name=distributed_fused_adam`. FP32 embedding grads are enabled by default and can be disabled with `model.with_fp32_embedding_grads=False`.

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**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation

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# Additional Information
* Currently only supported with GPT and T5.
* Support for FP32 embedding grads was recently refactored in https://github.com/NVIDIA/NeMo/pull/8792 and https://github.com/NVIDIA/NeMo/pull/8867.