Adding batch_size support for (almost) all pipelines (#13724)
* Tentative enabling of `batch_size` for pipelines. * Add systematic test for pipeline batching. * Enabling batch_size on almost all pipelines - Not `zero-shot` (it's already passing stuff as batched so trickier) - Not `QA` (preprocess uses squad features, we need to switch to real tensors at this boundary. * Adding `min_length_for_response` for conversational. * Making CTC, speech mappings avaiable regardless of framework. * Attempt at fixing automatic tests (ffmpeg not enabled for fast tests) * Removing ffmpeg dependency in tests. * Small fixes. * Slight cleanup. * Adding docs and adressing comments. * Quality. * Update docs/source/main_classes/pipelines.rst Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/pipelines/question_answering.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/pipelines/zero_shot_classification.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Improving docs. * Update docs/source/main_classes/pipelines.rst Co-authored-by: Philipp Schmid <32632186+philschmid@users.noreply.github.com> * N -> oberved_batch_size softmax trick. * Follow `padding_side`. * Supporting image pipeline batching (and padding). * Rename `unbatch` -> `loader_batch`. * unbatch_size forgot. * Custom padding for offset mappings. * Attempt to remove librosa. * Adding require_audio. * torchaudio. * Back to using datasets librosa. * Adding help to set a pad_token on the tokenizer. * Update src/transformers/pipelines/base.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/pipelines/base.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/pipelines/base.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Quality. Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Philipp Schmid <32632186+philschmid@users.noreply.github.com>
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@@ -31,9 +31,13 @@ class ZeroShotClassificationPipelineTests(unittest.TestCase, metaclass=PipelineT
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model_mapping = MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING
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tf_model_mapping = TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING
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def run_pipeline_test(self, model, tokenizer, feature_extractor):
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classifier = ZeroShotClassificationPipeline(model=model, tokenizer=tokenizer)
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def get_test_pipeline(self, model, tokenizer, feature_extractor):
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classifier = ZeroShotClassificationPipeline(
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model=model, tokenizer=tokenizer, candidate_labels=["polics", "health"]
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)
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return classifier, ["Who are you voting for in 2020?", "My stomach hurts."]
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def run_pipeline_test(self, classifier, _):
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outputs = classifier("Who are you voting for in 2020?", candidate_labels="politics")
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self.assertEqual(outputs, {"sequence": ANY(str), "labels": [ANY(str)], "scores": [ANY(float)]})
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