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Fix is_torch_tpu_available in ORT Trainer #2028

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merged 1 commit into from
Sep 18, 2024
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Fix is_torch_tpu_available in ORT Trainer #2028

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10 changes: 5 additions & 5 deletions optimum/onnxruntime/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -103,14 +103,14 @@
from transformers.deepspeed import deepspeed_init, deepspeed_load_checkpoint, is_deepspeed_zero3_enabled

if check_if_transformers_greater("4.39"):
from transformers.utils import is_torch_xla_available
from transformers.utils import is_torch_xla_available as is_torch_tpu_xla_available

if is_torch_xla_available():
if is_torch_tpu_xla_available():
import torch_xla.core.xla_model as xm
else:
from transformers.utils import is_torch_tpu_available
from transformers.utils import is_torch_tpu_available as is_torch_tpu_xla_available

if is_torch_tpu_available(check_device=False):
if is_torch_tpu_xla_available(check_device=False):
import torch_xla.core.xla_model as xm

if TYPE_CHECKING:
Expand Down Expand Up @@ -735,7 +735,7 @@ def get_dataloader_sampler(dataloader):

if (
args.logging_nan_inf_filter
and not is_torch_tpu_available()
and not is_torch_tpu_xla_available()
and (torch.isnan(tr_loss_step) or torch.isinf(tr_loss_step))
):
# if loss is nan or inf simply add the average of previous logged losses
Expand Down
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