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Fix flaky test_batching_equivalence (#35564)

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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Yih-Dar 2025-01-09 14:00:08 +01:00 committed by GitHub
parent 4adc415b6d
commit 1b2f942af7
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3 changed files with 34 additions and 6 deletions
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35
src/transformers/testing_utils.py
View File

@ -1409,17 +1409,42 @@ def assert_screenout(out, what):
def set_model_tester_for_less_flaky_test(test_case):
if hasattr(test_case.model_tester, "num_hidden_layers"):
test_case.model_tester.num_hidden_layers = 1
target_num_hidden_layers = 1
# TODO (if possible): Avoid exceptional cases
exceptional_classes = [
"ZambaModelTester",
"RwkvModelTester",
"AriaVisionText2TextModelTester",
"GPTNeoModelTester",
"DPTModelTester",
]
if test_case.model_tester.__class__.__name__ in exceptional_classes:
target_num_hidden_layers = None
if hasattr(test_case.model_tester, "out_features") or hasattr(test_case.model_tester, "out_indices"):
target_num_hidden_layers = None
if hasattr(test_case.model_tester, "num_hidden_layers") and target_num_hidden_layers is not None:
test_case.model_tester.num_hidden_layers = target_num_hidden_layers
if (
hasattr(test_case.model_tester, "vision_config")
and "num_hidden_layers" in test_case.model_tester.vision_config
and target_num_hidden_layers is not None
):
test_case.model_tester.vision_config = copy.deepcopy(test_case.model_tester.vision_config)
test_case.model_tester.vision_config["num_hidden_layers"] = 1
if hasattr(test_case.model_tester, "text_config") and "num_hidden_layers" in test_case.model_tester.text_config:
test_case.model_tester.vision_config["num_hidden_layers"] = target_num_hidden_layers
if (
hasattr(test_case.model_tester, "text_config")
and "num_hidden_layers" in test_case.model_tester.text_config
and target_num_hidden_layers is not None
):
test_case.model_tester.text_config = copy.deepcopy(test_case.model_tester.text_config)
test_case.model_tester.text_config["num_hidden_layers"] = 1
test_case.model_tester.text_config["num_hidden_layers"] = target_num_hidden_layers
# A few model class specific handling
# For Albert
if hasattr(test_case.model_tester, "num_hidden_groups"):
test_case.model_tester.num_hidden_groups = test_case.model_tester.num_hidden_layers
def set_config_for_less_flaky_test(config):

1
tests/models/upernet/test_modeling_upernet.py
View File

@ -82,7 +82,6 @@ class UperNetModelTester:
self.out_features = out_features
self.num_labels = num_labels
self.scope = scope
self.num_hidden_layers = num_stages
def prepare_config_and_inputs(self):
pixel_values = floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size])

4
tests/test_modeling_common.py
View File

@ -816,7 +816,10 @@ class ModelTesterMixin:
),
)
set_model_tester_for_less_flaky_test(self)
config, batched_input = self.model_tester.prepare_config_and_inputs_for_common()
set_config_for_less_flaky_test(config)
equivalence = get_tensor_equivalence_function(batched_input)
for model_class in self.all_model_classes:
@ -827,6 +830,7 @@ class ModelTesterMixin:
config, batched_input = self.model_tester.prepare_config_and_inputs_for_model_class(model_class)
batched_input_prepared = self._prepare_for_class(batched_input, model_class)
model = model_class(config).to(torch_device).eval()
set_model_for_less_flaky_test(model)
batch_size = self.model_tester.batch_size
single_row_input = {}