Unverified Commit f73c2097 authored by Yih-Dar's avatar Yih-Dar Committed by GitHub
Browse files

Fix imports (#25869)



fix
Co-authored-by: default avatarydshieh <ydshieh@users.noreply.github.com>
parent ed290b08
...@@ -255,7 +255,7 @@ def run_hp_search_ray(trainer, n_trials: int, direction: str, **kwargs) -> BestR ...@@ -255,7 +255,7 @@ def run_hp_search_ray(trainer, n_trials: int, direction: str, **kwargs) -> BestR
ray.tune.report(objective=local_trainer.objective, **metrics, done=True) ray.tune.report(objective=local_trainer.objective, **metrics, done=True)
if not trainer._memory_tracker.skip_memory_metrics: if not trainer._memory_tracker.skip_memory_metrics:
from .trainer_utils import TrainerMemoryTracker from ..trainer_utils import TrainerMemoryTracker
logger.warning( logger.warning(
"Memory tracking for your Trainer is currently " "Memory tracking for your Trainer is currently "
...@@ -463,7 +463,7 @@ def run_hp_search_sigopt(trainer, n_trials: int, direction: str, **kwargs) -> Be ...@@ -463,7 +463,7 @@ def run_hp_search_sigopt(trainer, n_trials: int, direction: str, **kwargs) -> Be
def run_hp_search_wandb(trainer, n_trials: int, direction: str, **kwargs) -> BestRun: def run_hp_search_wandb(trainer, n_trials: int, direction: str, **kwargs) -> BestRun:
from .integrations import is_wandb_available from ..integrations import is_wandb_available
if not is_wandb_available(): if not is_wandb_available():
raise ImportError("This function needs wandb installed: `pip install wandb`") raise ImportError("This function needs wandb installed: `pip install wandb`")
...@@ -763,7 +763,7 @@ class WandbCallback(TrainerCallback): ...@@ -763,7 +763,7 @@ class WandbCallback(TrainerCallback):
if self._wandb is None: if self._wandb is None:
return return
if self._log_model in ("end", "checkpoint") and self._initialized and state.is_world_process_zero: if self._log_model in ("end", "checkpoint") and self._initialized and state.is_world_process_zero:
from .trainer import Trainer from ..trainer import Trainer
fake_trainer = Trainer(args=args, model=model, tokenizer=tokenizer) fake_trainer = Trainer(args=args, model=model, tokenizer=tokenizer)
with tempfile.TemporaryDirectory() as temp_dir: with tempfile.TemporaryDirectory() as temp_dir:
......
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