🔥Rework pipeline testing by removing PipelineTestCaseMeta 🚀 (#21516)
* Add PipelineTesterMixin * remove class PipelineTestCaseMeta * move validate_test_components * Add for ViT * Add to SPECIAL_MODULE_TO_TEST_MAP * style and quality * Add feature-extraction * update * raise instead of skip * add tiny_model_summary.json * more explicit * skip tasks not in mapping * add availability check * Add Copyright * A way to diable irrelevant tests * update with main * remove disable_irrelevant_tests * skip tests * better skip message * better skip message * Add all pipeline task tests * revert * Import PipelineTesterMixin * subclass test classes with PipelineTesterMixin * Add pipieline_model_mapping * Fix import after adding pipieline_model_mapping * Fix style and quality after adding pipieline_model_mapping * Fix one more import after adding pipieline_model_mapping * Fix style and quality after adding pipieline_model_mapping * Fix test issues * Fix import requirements * Fix mapping for MobileViTModelTest * Update * Better skip message * pipieline_model_mapping could not be None * Remove some PipelineTesterMixin * Fix typo * revert tests_fetcher.py * update * rename * revert * Remove PipelineTestCaseMeta from ZeroShotAudioClassificationPipelineTests * style and quality * test fetcher for all pipeline/model tests --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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@@ -23,6 +23,7 @@ from transformers.testing_utils import require_torch, slow, torch_device
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from ...generation.test_utils import GenerationTesterMixin
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from ...test_configuration_common import ConfigTester
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from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
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from ...test_pipeline_mixin import PipelineTesterMixin
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if is_torch_available():
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@@ -885,9 +886,20 @@ class ProphetNetStandaloneEncoderModelTester:
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@require_torch
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class ProphetNetModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
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class ProphetNetModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
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all_model_classes = (ProphetNetModel, ProphetNetForConditionalGeneration) if is_torch_available() else ()
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all_generative_model_classes = (ProphetNetForConditionalGeneration,) if is_torch_available() else ()
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pipeline_model_mapping = (
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{
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"conversational": ProphetNetForConditionalGeneration,
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"feature-extraction": ProphetNetModel,
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"summarization": ProphetNetForConditionalGeneration,
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"text2text-generation": ProphetNetForConditionalGeneration,
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"text-generation": ProphetNetForCausalLM,
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}
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if is_torch_available()
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else {}
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)
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test_pruning = False
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test_resize_embeddings = False
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is_encoder_decoder = True
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