Small style updates.

Author: TEChopra1000

doc/api/training/smd_model_parallel_release_notes/smd_model_parallel_change_log.md

@@ -8,14 +8,14 @@
 
 ### PyTorch
 
-#### Add support for PyTorch 1.7
+#### Add support for PyTorch (PT) 1.7
 
-- Adds support for `gradient_as_bucket_view` (PT 1.7 only), `find_unused_parameters` (PT 1.7 only) and `broadcast_buffers` options to `smp.DistributedModel`. These options behave the same as the corresponding options (with the same names) in
-`torch.DistributedDataParallel` API. Please refer to the [SMP API documentation](https://sagemaker.readthedocs.io/en/stable/api/training/smd_model_parallel_pytorch.html#smp.DistributedModel) for more information.
+- Adds support for `gradient_as_bucket_view` (PyTorch 1.7 only), `find_unused_parameters` (PyTorch 1.7 only) and `broadcast_buffers` options to `smp.DistributedModel`. These options behave the same as the corresponding options (with the same names) in
+`torch.DistributedDataParallel` API. Please refer to the [SageMaker distributed model parallel API documentation](https://sagemaker.readthedocs.io/en/stable/api/training/smd_model_parallel_pytorch.html#smp.DistributedModel) for more information.
 
-- Adds support for `join` (PT 1.7 only) context manager, which is to be used in conjunction with an instance of `torch.nn.parallel.DistributedDataParallel` to be able to train with uneven inputs across participating processes.
+- Adds support for `join` (PyTorch 1.7 only) context manager, which is to be used in conjunction with an instance of `torch.nn.parallel.DistributedDataParallel` to be able to train with uneven inputs across participating processes.
 
-- Adds support for `_register_comm_hook` (PT 1.7 only) which will register the callable as a communication hook for DDP. NOTE: Like in DDP, this is an experimental API and subject to change.
+- Adds support for `_register_comm_hook` (PyTorch 1.7 only) which will register the callable as a communication hook for DDP. NOTE: Like in DDP, this is an experimental API and subject to change.
 
 ### Tensorflow