Apply suggestions from code review

Co-authored-by: Svetlana Karslioglu <svekars@meta.com>

Author: wz337

recipes_source/distributed_device_mesh.rst

@@ -11,12 +11,12 @@ Prerequisites:
 - `Distributed Communication Package - torch.distributed <https://pytorch.org/docs/stable/distributed.html>`__
 
 .. Setting up the NVIDIA Collective Communication Library (NCCL) communicators for distributed communication during distributed training can pose a significant challenge. For workloads where users need to compose different parallelisms,
-.. users would need to manually set up and manage nccl communicators(for example, :class:`ProcessGroup`) for each parallelism solutions. This is fairly complicated and error-proned.
-.. :class:`DeviceMesh` can help make this process much easier.
+.. users would need to manually set up and manage NCCL communicators (for example, :class:`ProcessGroup`) for each parallelism solutions. This process could be complicated and susceptible to errors.
+.. :class:`DeviceMesh` can simplify this process, making it more manageable and less prone to errors.
 
 What is DeviceMesh
 ------------------
-.. :class:`DeviceMesh` is a higher level abstraction that manages :class:`ProcessGroup`. It allows users to easily
+.. :class:`DeviceMesh` is a higher level abstraction that manages :class:`ProcessGroup`. It allows users to effortlessly 
 .. create inter-node and intra-node process groups without worrying about how to set up ranks correctly for different sub process groups.
 .. Users can also easily manage the underlying process_groups/devices for multi-dimensional parallelism via :class:`DeviceMesh`.
 
@@ -28,7 +28,7 @@ What is DeviceMesh
 Why DeviceMesh is Useful
 ------------------------
 
-.. Below is the code snippet for a 2D setup without :class:`DeviceMesh`. First, we need to manually calculate shard group and replicate group. Then, we need to assign the correct shard and
+.. The following code snippet illustrates a 2D setup without :class:`DeviceMesh`. First, we need to manually calculate the shard group and replicate group. Then, we need to assign the correct shard and
 .. replicate group to each rank.
 
 .. code-block:: python
@@ -57,7 +57,7 @@ current_shard_group = (
     shard_groups[0] if rank in shard_rank_lists[0] else shard_groups[1]
 )
 
-# Create replicate groups (e.g. (0, 4), (1, 5), (2, 6), (3, 7))
+# Create replicate groups (for example, (0, 4), (1, 5), (2, 6), (3, 7))
 # and assign the correct replicate group to each rank
 current_replicate_group = None
 shard_factor = len(shard_rank_lists[0])
@@ -74,7 +74,7 @@ for i in range(num_node_devices // 2):
 torchrun --nnodes=1 --nproc_per_node=8 --rdzv_id=100 --rdzv_endpoint=localhost:29400 2d_setup.py
 
 
-.. With the help of :func:`init_device_mesh`, we can accomplish the above 2D setup in just 2 lines.
+.. With the help of :func:`init_device_mesh`, we can accomplish the above 2D setup in just two lines.
 
 
 .. code-block:: python