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Python

# coding=utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch
from .global_vars import get_args
from .global_vars import get_current_global_batch_size
from .global_vars import get_num_microbatches
from .global_vars import update_num_microbatches
from .global_vars import get_tokenizer
from .global_vars import get_tensorboard_writer
from .global_vars import get_adlr_autoresume
from .global_vars import get_timers
from .initialize import initialize_megatron
def print_rank_0(message):
"""If distributed is initialized, print only on rank 0."""
if torch.distributed.is_initialized():
if torch.distributed.get_rank() == 0:
print(message, flush=True)
else:
print(message, flush=True)
def is_last_rank():
return torch.distributed.get_rank() == (torch.distributed.get_world_size() - 1)
def print_rank_last(message):
"""If distributed is initialized, print only on last rank."""
if torch.distributed.is_initialized():
if is_last_rank():
print(message, flush=True)
else:
print(message, flush=True)