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import os
import torch
import megatron.core.parallel_state as ps
class Utils:
world_size = torch.cuda.device_count()
rank = int(os.environ['LOCAL_RANK'])
@staticmethod
def initialize_distributed():
print(f'Initializing torch.distributed with rank: {Utils.rank}, world_size: {Utils.world_size}')
torch.cuda.set_device(Utils.rank % torch.cuda.device_count())
init_method = 'tcp://'
master_ip = os.getenv('MASTER_ADDR', 'localhost')
master_port = os.getenv('MASTER_PORT', '6000')
init_method += master_ip + ':' + master_port
torch.distributed.init_process_group(backend='nccl', world_size=Utils.world_size, rank=Utils.rank, init_method=init_method)
@staticmethod
def destroy_model_parallel():
ps.destroy_model_parallel()
torch.distributed.barrier()
@staticmethod
def initialize_model_parallel(tensor_model_parallel_size = 1, pipeline_model_parallel_size = 1, virtual_pipeline_model_parallel_size = None, pipeline_model_parallel_split_rank = None):
ps.destroy_model_parallel()
if not torch.distributed.is_initialized():
Utils.initialize_distributed()
ps.initialize_model_parallel(tensor_model_parallel_size, pipeline_model_parallel_size, virtual_pipeline_model_parallel_size, pipeline_model_parallel_split_rank) |