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deprecate no_cuda (#24863)
* deprecate no_cuda * style * remove doc * remove doc 2 * fix style
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@ -297,8 +297,8 @@ class TrainingArguments:
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This should not be activated when the different nodes use the same storage as the files will be saved with
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This should not be activated when the different nodes use the same storage as the files will be saved with
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the same names for each node.
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the same names for each node.
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no_cuda (`bool`, *optional*, defaults to `False`):
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use_cpu (`bool`, *optional*, defaults to `False`):
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Whether to not use CUDA even when it is available or not.
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Whether or not to use cpu. If set to False, we will use cuda or mps device if available.
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seed (`int`, *optional*, defaults to 42):
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seed (`int`, *optional*, defaults to 42):
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Random seed that will be set at the beginning of training. To ensure reproducibility across runs, use the
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Random seed that will be set at the beginning of training. To ensure reproducibility across runs, use the
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[`~Trainer.model_init`] function to instantiate the model if it has some randomly initialized parameters.
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[`~Trainer.model_init`] function to instantiate the model if it has some randomly initialized parameters.
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@ -313,7 +313,7 @@ class TrainingArguments:
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installation](https://github.com/intel/intel-extension-for-pytorch).
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installation](https://github.com/intel/intel-extension-for-pytorch).
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bf16 (`bool`, *optional*, defaults to `False`):
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bf16 (`bool`, *optional*, defaults to `False`):
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Whether to use bf16 16-bit (mixed) precision training instead of 32-bit training. Requires Ampere or higher
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Whether to use bf16 16-bit (mixed) precision training instead of 32-bit training. Requires Ampere or higher
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NVIDIA architecture or using CPU (no_cuda). This is an experimental API and it may change.
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NVIDIA architecture or using CPU (use_cpu). This is an experimental API and it may change.
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fp16 (`bool`, *optional*, defaults to `False`):
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fp16 (`bool`, *optional*, defaults to `False`):
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Whether to use fp16 16-bit (mixed) precision training instead of 32-bit training.
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Whether to use fp16 16-bit (mixed) precision training instead of 32-bit training.
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fp16_opt_level (`str`, *optional*, defaults to 'O1'):
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fp16_opt_level (`str`, *optional*, defaults to 'O1'):
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@ -793,7 +793,14 @@ class TrainingArguments:
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)
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)
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},
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},
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)
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)
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no_cuda: bool = field(default=False, metadata={"help": "Do not use CUDA even when it is available"})
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no_cuda: bool = field(
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default=False,
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metadata={"help": "This argument is deprecated. It will be removed in version 5.0 of 🤗 Transformers."},
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)
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use_cpu: bool = field(
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default=False,
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metadata={"help": " Whether or not to use cpu. If set to False, we will use cuda or mps device if available."},
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)
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use_mps_device: bool = field(
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use_mps_device: bool = field(
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default=False,
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default=False,
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metadata={
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metadata={
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@ -820,7 +827,7 @@ class TrainingArguments:
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metadata={
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metadata={
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"help": (
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"help": (
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"Whether to use bf16 (mixed) precision instead of 32-bit. Requires Ampere or higher NVIDIA"
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"Whether to use bf16 (mixed) precision instead of 32-bit. Requires Ampere or higher NVIDIA"
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" architecture or using CPU (no_cuda). This is an experimental API and it may change."
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" architecture or using CPU (use_cpu). This is an experimental API and it may change."
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)
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)
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},
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},
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)
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)
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@ -1211,6 +1218,13 @@ class TrainingArguments:
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)
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)
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# Go back to the underlying string or we won't be able to instantiate `IntervalStrategy` on it.
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# Go back to the underlying string or we won't be able to instantiate `IntervalStrategy` on it.
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self.evaluation_strategy = self.evaluation_strategy.value
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self.evaluation_strategy = self.evaluation_strategy.value
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if self.no_cuda:
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warnings.warn(
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"using `no_cuda` is deprecated and will be removed in version 5.0 of 🤗 Transformers. "
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"Use `use_cpu` instead",
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FutureWarning,
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)
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self.use_cpu = self.no_cuda
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self.evaluation_strategy = IntervalStrategy(self.evaluation_strategy)
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self.evaluation_strategy = IntervalStrategy(self.evaluation_strategy)
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self.logging_strategy = IntervalStrategy(self.logging_strategy)
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self.logging_strategy = IntervalStrategy(self.logging_strategy)
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@ -1305,10 +1319,10 @@ class TrainingArguments:
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self.half_precision_backend = self.fp16_backend
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self.half_precision_backend = self.fp16_backend
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if self.bf16 or self.bf16_full_eval:
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if self.bf16 or self.bf16_full_eval:
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if self.no_cuda and not is_torch_bf16_cpu_available() and not is_torch_tpu_available():
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if self.use_cpu and not is_torch_bf16_cpu_available() and not is_torch_tpu_available():
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# cpu
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# cpu
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raise ValueError("Your setup doesn't support bf16/(cpu, tpu, neuroncore). You need torch>=1.10")
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raise ValueError("Your setup doesn't support bf16/(cpu, tpu, neuroncore). You need torch>=1.10")
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elif not self.no_cuda and torch.cuda.is_available() and not is_torch_bf16_gpu_available():
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elif not self.use_cpu and torch.cuda.is_available() and not is_torch_bf16_gpu_available():
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# gpu
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# gpu
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raise ValueError(
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raise ValueError(
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"Your setup doesn't support bf16/gpu. You need torch>=1.10, using Ampere GPU with cuda>=11.0"
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"Your setup doesn't support bf16/gpu. You need torch>=1.10, using Ampere GPU with cuda>=11.0"
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@ -1702,7 +1716,7 @@ class TrainingArguments:
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)
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)
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AcceleratorState._reset_state(reset_partial_state=True)
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AcceleratorState._reset_state(reset_partial_state=True)
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self.distributed_state = None
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self.distributed_state = None
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if self.no_cuda:
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if self.use_cpu:
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self.distributed_state = PartialState(cpu=True, backend=self.ddp_backend)
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self.distributed_state = PartialState(cpu=True, backend=self.ddp_backend)
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self._n_gpu = 0
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self._n_gpu = 0
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elif is_sagemaker_mp_enabled():
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elif is_sagemaker_mp_enabled():
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@ -1752,7 +1766,7 @@ class TrainingArguments:
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)
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)
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if device.type == "mps":
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if device.type == "mps":
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self._n_gpu = 1
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self._n_gpu = 1
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elif self.no_cuda:
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elif self.use_cpu:
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device = torch.device("cpu")
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device = torch.device("cpu")
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self._n_gpu = 0
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self._n_gpu = 0
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else:
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else:
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