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Change a logic in pipeline test regarding TF (#20710)

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* Fix the pipeline test regarding TF

* Fix the pipeline test regarding TF

* update comment

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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Yih-Dar 2022-12-13 13:42:36 +01:00 committed by GitHub
parent 1af4bee896
commit a12c5cbcd8
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1 changed files with 13 additions and 5 deletions
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18
tests/pipelines/test_pipelines_summarization.py
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@ -18,9 +18,10 @@ from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
SummarizationPipeline,
TFPreTrainedModel,
pipeline,
)
from transformers.testing_utils import require_tf, require_torch, slow, torch_device
from transformers.testing_utils import get_gpu_count, require_tf, require_torch, slow, torch_device
from transformers.tokenization_utils import TruncationStrategy
from .test_pipelines_common import ANY, PipelineTestCaseMeta
@ -51,6 +52,7 @@ class SummarizationPipelineTests(unittest.TestCase, metaclass=PipelineTestCaseMe
)
self.assertEqual(outputs, [{"summary_text": ANY(str)}])
# Some models (Switch Transformers, LED, T5, LongT5, etc) can handle long sequences.
model_can_handle_longer_seq = [
"SwitchTransformersConfig",
"T5Config",
@ -62,10 +64,16 @@ class SummarizationPipelineTests(unittest.TestCase, metaclass=PipelineTestCaseMe
"ProphetNetConfig", # positional embeddings up to a fixed maximum size (otherwise clamping the values)
]
if model.config.__class__.__name__ not in model_can_handle_longer_seq:
# Switch Transformers, LED, T5, LongT5 can handle it.
# Too long.
with self.assertRaises(Exception):
outputs = summarizer("This " * 1000)
# Too long and exception is expected.
# For TF models, if the weights are initialized in GPU context, we won't get expected index error from
# the embedding layer.
if not (
isinstance(model, TFPreTrainedModel)
and get_gpu_count() > 0
and len(summarizer.model.trainable_weights) > 0
):
with self.assertRaises(Exception):
outputs = summarizer("This " * 1000)
outputs = summarizer("This " * 1000, truncation=TruncationStrategy.ONLY_FIRST)
@require_torch