Repository: volcengine/verl
File: verl/trainer/sft_trainer_ray.py (Python)

Code before:
# Copyright 2024 Bytedance Ltd. and/or its affiliates
#
# 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 os
from functools import partial

from tensordict.tensorclass import NonTensorData

from verl.utils.import_utils import is_torch_npu_pkg_available

os.environ["NCCL_DEBUG"] = "WARN"
os.environ["TOKENIZERS_PARALLELISM"] = "true"

import logging

import hydra
import ray
import torch
import torch.distributed
from omegaconf import OmegaConf
from torch.utils.data import DistributedSampler
from torchdata.stateful_dataloader import StatefulDataLoader
from tqdm import tqdm

from verl.utils import tensordict_utils as tu
from verl.utils.checkpoint import CheckpointHandler, OrchestrationMode
from verl.utils.dataset.dataset_utils import SFTTensorCollator
from verl.utils.dataset.multiturn_sft_dataset import MultiTurnSFTDataset
from verl.utils.device import get_device_name
from verl.utils.logger import log_with_rank
from verl.utils.tracking import Tracking
from verl.workers.engine_workers import TrainingWorker

logger = logging.getLogger(__file__)

Review comment (suggestion):
```suggestion
from verl.utils.import_utils import is_torch_npu_available
```

Code after:
# Copyright 2024 Bytedance Ltd. and/or its affiliates
#
# 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 os
from functools import partial

from tensordict.tensorclass import NonTensorData

os.environ["NCCL_DEBUG"] = "WARN"
os.environ["TOKENIZERS_PARALLELISM"] = "true"

import logging

import hydra
import ray
import torch
import torch.distributed
from omegaconf import OmegaConf
from torch.utils.data import DistributedSampler
from torchdata.stateful_dataloader import StatefulDataLoader
from tqdm import tqdm

from verl.utils import tensordict_utils as tu
from verl.utils.checkpoint import CheckpointHandler, OrchestrationMode
from verl.utils.dataset.dataset_utils import SFTTensorCollator
from verl.utils.dataset.multiturn_sft_dataset import MultiTurnSFTDataset
from verl.utils.device import get_device_name
from verl.utils.logger import log_with_rank
from verl.utils.tracking import Tracking
from verl.workers.engine_workers import TrainingWorker

logger = logging.getLogger(__file__)
logger.setLevel(os.getenv("VERL_SFT_LOGGING_LEVEL", "WARN"))