| |
|
|
| import os |
|
|
| import torch.distributed as dist |
|
|
|
|
| class COMM_INFO: |
|
|
| def __init__(self): |
| self.group = None |
| self.sp_size = 1 |
| self.global_rank = 0 |
| self.rank_within_group = 0 |
| self.group_id = 0 |
|
|
|
|
| nccl_info = COMM_INFO() |
| _SEQUENCE_PARALLEL_STATE = False |
|
|
|
|
| def initialize_sequence_parallel_state(sequence_parallel_size): |
| global _SEQUENCE_PARALLEL_STATE |
| if sequence_parallel_size > 1: |
| _SEQUENCE_PARALLEL_STATE = True |
| initialize_sequence_parallel_group(sequence_parallel_size) |
| else: |
| nccl_info.sp_size = 1 |
| nccl_info.global_rank = int(os.getenv("RANK", "0")) |
| nccl_info.rank_within_group = 0 |
| nccl_info.group_id = int(os.getenv("RANK", "0")) |
|
|
|
|
| def set_sequence_parallel_state(state): |
| global _SEQUENCE_PARALLEL_STATE |
| _SEQUENCE_PARALLEL_STATE = state |
|
|
|
|
| def get_sequence_parallel_state(): |
| return _SEQUENCE_PARALLEL_STATE |
|
|
|
|
| def initialize_sequence_parallel_group(sequence_parallel_size): |
| """Initialize the sequence parallel group.""" |
| rank = int(os.getenv("RANK", "0")) |
| world_size = int(os.getenv("WORLD_SIZE", "1")) |
| assert ( |
| world_size % sequence_parallel_size == 0 |
| ), "world_size must be divisible by sequence_parallel_size, but got world_size: {}, sequence_parallel_size: {}".format( |
| world_size, sequence_parallel_size) |
| nccl_info.sp_size = sequence_parallel_size |
| nccl_info.global_rank = rank |
| num_sequence_parallel_groups: int = world_size // sequence_parallel_size |
| for i in range(num_sequence_parallel_groups): |
| ranks = range(i * sequence_parallel_size, |
| (i + 1) * sequence_parallel_size) |
| group = dist.new_group(ranks) |
| if rank in ranks: |
| nccl_info.group = group |
| nccl_info.rank_within_group = rank - i * sequence_parallel_size |
| nccl_info.group_id = i |
|
|
|
|
| def destroy_sequence_parallel_group(): |
| """Destroy the sequence parallel group.""" |
| dist.destroy_process_group() |
|
|
