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enhance require_deterministic_for_xpu (#37437)

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* enhance require_deterministic_for_xpu

Signed-off-by: YAO Matrix <matrix.yao@intel.com>

* fix style

Signed-off-by: YAO Matrix <matrix.yao@intel.com>

* fix style

Signed-off-by: YAO Matrix <matrix.yao@intel.com>

---------

Signed-off-by: YAO Matrix <matrix.yao@intel.com>
This commit is contained in:
Yao Matrix
2025-04-11 14:06:08 +08:00
committed by GitHub
parent 371c44d0ef
commit c7064cdba1
3 changed files with 16 additions and 7 deletions
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20
src/transformers/testing_utils.py
View File

@@ -139,7 +139,6 @@ from .utils import (
is_torch_available, is_torch_available,
is_torch_bf16_available_on_device, is_torch_bf16_available_on_device,
is_torch_bf16_gpu_available, is_torch_bf16_gpu_available,
is_torch_deterministic,
is_torch_fp16_available_on_device, is_torch_fp16_available_on_device,
is_torch_greater_or_equal, is_torch_greater_or_equal,
is_torch_hpu_available, is_torch_hpu_available,
@@ -1073,12 +1072,19 @@ def require_torch_bf16_gpu(test_case):
def require_deterministic_for_xpu(test_case): def require_deterministic_for_xpu(test_case):
if is_torch_xpu_available(): @wraps(test_case)
return unittest.skipUnless(is_torch_deterministic(), "test requires torch to use deterministic algorithms")( def wrapper(*args, **kwargs):
test_case if is_torch_xpu_available():
) original_state = torch.are_deterministic_algorithms_enabled()
else: try:
return test_case torch.use_deterministic_algorithms(True)
return test_case(*args, **kwargs)
finally:
torch.use_deterministic_algorithms(original_state)
else:
return test_case(*args, **kwargs)
return wrapper
def require_torch_tf32(test_case): def require_torch_tf32(test_case):

2
tests/models/encoder_decoder/test_modeling_encoder_decoder.py
View File

@@ -936,6 +936,7 @@ class BertGenerationEncoderDecoderModelTest(EncoderDecoderMixin, unittest.TestCa
} }
@slow @slow
@require_deterministic_for_xpu
def test_roberta2roberta_summarization(self): def test_roberta2roberta_summarization(self):
model = EncoderDecoderModel.from_pretrained("google/roberta2roberta_L-24_bbc") model = EncoderDecoderModel.from_pretrained("google/roberta2roberta_L-24_bbc")
model.to(torch_device) model.to(torch_device)
@@ -1080,6 +1081,7 @@ class GPT2EncoderDecoderModelTest(EncoderDecoderMixin, unittest.TestCase):
pass pass
@slow @slow
@require_deterministic_for_xpu
def test_bert2gpt2_summarization(self): def test_bert2gpt2_summarization(self):
model = EncoderDecoderModel.from_pretrained("patrickvonplaten/bert2gpt2-cnn_dailymail-fp16") model = EncoderDecoderModel.from_pretrained("patrickvonplaten/bert2gpt2-cnn_dailymail-fp16")

1
tests/models/speech_encoder_decoder/test_modeling_speech_encoder_decoder.py
View File

@@ -634,6 +634,7 @@ class Speech2TextBertModelTest(EncoderDecoderMixin, unittest.TestCase):
def test_encoder_decoder_model_from_pretrained_configs(self): def test_encoder_decoder_model_from_pretrained_configs(self):
pass pass
@require_deterministic_for_xpu
@unittest.skip(reason="Cannot save full model as Speech2TextModel != Speech2TextEncoder") @unittest.skip(reason="Cannot save full model as Speech2TextModel != Speech2TextEncoder")
def test_save_and_load_from_pretrained(self): def test_save_and_load_from_pretrained(self):
pass pass