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applications/ColossalChat/coati/distributed/grpo_consumer.py
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@ -8,7 +8,6 @@ from coati.distributed.consumer import BaseConsumer
from coati.distributed.loss import PolicyLoss from coati.distributed.loss import PolicyLoss
from coati.distributed.reward.reward_fn import boxed_math_reward_fn, math_reward_fn from coati.distributed.reward.reward_fn import boxed_math_reward_fn, math_reward_fn
from coati.distributed.reward.verifiable_reward import VerifiableReward from coati.distributed.reward.verifiable_reward import VerifiableReward
from coati.distributed.utils import calc_action_log_probs
from coati.trainer.utils import all_reduce_mean, all_reduce_sum from coati.trainer.utils import all_reduce_mean, all_reduce_sum
from transformers import AutoModelForCausalLM, AutoTokenizer from transformers import AutoModelForCausalLM, AutoTokenizer

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applications/ColossalChat/coati/distributed/producer.py
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@ -10,7 +10,6 @@ import tqdm
import wandb import wandb
from coati.dataset.loader import RawConversationDataset, collate_fn_grpo from coati.dataset.loader import RawConversationDataset, collate_fn_grpo
from coati.distributed.reward.reward_fn import boxed_math_reward_fn, code_reward_fn, math_reward_fn from coati.distributed.reward.reward_fn import boxed_math_reward_fn, code_reward_fn, math_reward_fn
from coati.distributed.reward.verifiable_reward import VerifiableReward
from ray.util.collective import allreduce from ray.util.collective import allreduce
from ray.util.collective.types import ReduceOp from ray.util.collective.types import ReduceOp
from torch.utils.data import DataLoader, DistributedSampler from torch.utils.data import DataLoader, DistributedSampler