Remove deprecated codes (#24837)
* remove `xpu_backend` training argument * always call `contextlib.nullcontext()` since transformers updated to python3.8 * these codes will not be executed
This commit is contained in:
@@ -629,20 +629,7 @@ class Trainer:
|
|||||||
# bf16 does not need grad scaling
|
# bf16 does not need grad scaling
|
||||||
self.do_grad_scaling = self.amp_dtype == torch.float16
|
self.do_grad_scaling = self.amp_dtype == torch.float16
|
||||||
if self.do_grad_scaling:
|
if self.do_grad_scaling:
|
||||||
if self.sharded_ddp is not None:
|
self.scaler = ShardedGradScaler()
|
||||||
self.scaler = ShardedGradScaler()
|
|
||||||
elif self.fsdp is not None:
|
|
||||||
from torch.distributed.fsdp.sharded_grad_scaler import (
|
|
||||||
ShardedGradScaler as FSDPShardedGradScaler,
|
|
||||||
)
|
|
||||||
|
|
||||||
self.scaler = FSDPShardedGradScaler()
|
|
||||||
elif is_torch_tpu_available():
|
|
||||||
from torch_xla.amp import GradScaler
|
|
||||||
|
|
||||||
self.scaler = GradScaler()
|
|
||||||
else:
|
|
||||||
self.scaler = torch.cuda.amp.GradScaler()
|
|
||||||
elif args.half_precision_backend == "cpu_amp":
|
elif args.half_precision_backend == "cpu_amp":
|
||||||
self.use_cpu_amp = True
|
self.use_cpu_amp = True
|
||||||
self.amp_dtype = torch.bfloat16
|
self.amp_dtype = torch.bfloat16
|
||||||
@@ -2621,7 +2608,7 @@ class Trainer:
|
|||||||
else torch.cuda.amp.autocast(cache_enabled=cache_enabled, dtype=self.amp_dtype)
|
else torch.cuda.amp.autocast(cache_enabled=cache_enabled, dtype=self.amp_dtype)
|
||||||
)
|
)
|
||||||
else:
|
else:
|
||||||
ctx_manager = contextlib.nullcontext() if sys.version_info >= (3, 7) else contextlib.suppress()
|
ctx_manager = contextlib.nullcontext()
|
||||||
|
|
||||||
return ctx_manager
|
return ctx_manager
|
||||||
|
|
||||||
|
|||||||
@@ -1189,14 +1189,6 @@ class TrainingArguments:
|
|||||||
},
|
},
|
||||||
)
|
)
|
||||||
|
|
||||||
xpu_backend: Optional[str] = field(
|
|
||||||
default=None,
|
|
||||||
metadata={
|
|
||||||
"help": "The backend to be used for distributed training on Intel XPU.",
|
|
||||||
"choices": ["mpi", "ccl", "gloo"],
|
|
||||||
},
|
|
||||||
)
|
|
||||||
|
|
||||||
def __post_init__(self):
|
def __post_init__(self):
|
||||||
# expand paths, if not os.makedirs("~/bar") will make directory
|
# expand paths, if not os.makedirs("~/bar") will make directory
|
||||||
# in the current directory instead of the actual home
|
# in the current directory instead of the actual home
|
||||||
@@ -1220,14 +1212,6 @@ class TrainingArguments:
|
|||||||
# Go back to the underlying string or we won't be able to instantiate `IntervalStrategy` on it.
|
# Go back to the underlying string or we won't be able to instantiate `IntervalStrategy` on it.
|
||||||
self.evaluation_strategy = self.evaluation_strategy.value
|
self.evaluation_strategy = self.evaluation_strategy.value
|
||||||
|
|
||||||
if self.xpu_backend is not None:
|
|
||||||
warnings.warn(
|
|
||||||
"using `xpu_backend` is deprecated and will be removed in version 4.31"
|
|
||||||
" of 🤗 Transformers. Use `ddp_backend` instead",
|
|
||||||
FutureWarning,
|
|
||||||
)
|
|
||||||
self.ddp_backend = self.xpu_backend
|
|
||||||
|
|
||||||
self.evaluation_strategy = IntervalStrategy(self.evaluation_strategy)
|
self.evaluation_strategy = IntervalStrategy(self.evaluation_strategy)
|
||||||
self.logging_strategy = IntervalStrategy(self.logging_strategy)
|
self.logging_strategy = IntervalStrategy(self.logging_strategy)
|
||||||
self.save_strategy = IntervalStrategy(self.save_strategy)
|
self.save_strategy = IntervalStrategy(self.save_strategy)
|
||||||
|
|||||||
Reference in New Issue
Block a user