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Remove ConversationalPipeline and Conversation object (#31165)

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* Remove ConversationalPipeline and Conversation object, as they have been deprecated for some time and are due for removal

* Update not-doctested.txt

* Fix JA and ZH docs

* Fix JA and ZH docs some more

* Fix JA and ZH docs some more
This commit is contained in:
Matt
2024-06-07 17:50:18 +01:00
committed by GitHub
parent 3a10058201
commit 065729a692
46 changed files with 30 additions and 914 deletions
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5
tests/models/bart/test_modeling_bart.py
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@@ -430,7 +430,6 @@ class BartModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin
all_generative_model_classes = (BartForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": BartForConditionalGeneration,
"feature-extraction": BartModel,
"fill-mask": BartForConditionalGeneration,
"question-answering": BartForQuestionAnswering,
@@ -513,10 +512,6 @@ class BartModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin
model.generate(input_ids, attention_mask=attention_mask)
model.generate(num_beams=4, do_sample=True, early_stopping=False, num_return_sequences=3)
@unittest.skip("Does not support conversations.")
def test_pipeline_conversational(self):
pass
def assert_tensors_close(a, b, atol=1e-12, prefix=""):
"""If tensors have different shapes, different values or a and b are not both tensors, raise a nice Assertion error."""

5
tests/models/bart/test_modeling_tf_bart.py
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@@ -198,7 +198,6 @@ class TFBartModelTest(TFModelTesterMixin, TFCoreModelTesterMixin, PipelineTester
all_generative_model_classes = (TFBartForConditionalGeneration,) if is_tf_available() else ()
pipeline_model_mapping = (
{
"conversational": TFBartForConditionalGeneration,
"feature-extraction": TFBartModel,
"summarization": TFBartForConditionalGeneration,
"text-classification": TFBartForSequenceClassification,
@@ -343,10 +342,6 @@ class TFBartModelTest(TFModelTesterMixin, TFCoreModelTesterMixin, PipelineTester
# check that the output for the restored model is the same
self.assert_outputs_same(restored_model_outputs, outputs)
@unittest.skip("Does not support conversations.")
def test_pipeline_conversational(self):
pass
def _long_tensor(tok_lst):
return tf.constant(tok_lst, dtype=tf.int32)

1
tests/models/bigbird_pegasus/test_modeling_bigbird_pegasus.py
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@@ -253,7 +253,6 @@ class BigBirdPegasusModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineT
all_generative_model_classes = (BigBirdPegasusForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": BigBirdPegasusForConditionalGeneration,
"feature-extraction": BigBirdPegasusModel,
"question-answering": BigBirdPegasusForQuestionAnswering,
"summarization": BigBirdPegasusForConditionalGeneration,

1
tests/models/blenderbot/test_modeling_blenderbot.py
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@@ -237,7 +237,6 @@ class BlenderbotModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTeste
all_generative_model_classes = (BlenderbotForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": BlenderbotForConditionalGeneration,
"feature-extraction": BlenderbotModel,
"summarization": BlenderbotForConditionalGeneration,
"text-generation": BlenderbotForCausalLM,

1
tests/models/blenderbot/test_modeling_tf_blenderbot.py
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@@ -183,7 +183,6 @@ class TFBlenderbotModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.Te
all_generative_model_classes = (TFBlenderbotForConditionalGeneration,) if is_tf_available() else ()
pipeline_model_mapping = (
{
"conversational": TFBlenderbotForConditionalGeneration,
"feature-extraction": TFBlenderbotModel,
"summarization": TFBlenderbotForConditionalGeneration,
"text2text-generation": TFBlenderbotForConditionalGeneration,

3
tests/models/blenderbot_small/test_modeling_blenderbot_small.py
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@@ -228,7 +228,6 @@ class BlenderbotSmallModelTest(ModelTesterMixin, GenerationTesterMixin, Pipeline
all_generative_model_classes = (BlenderbotSmallForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": BlenderbotSmallForConditionalGeneration,
"feature-extraction": BlenderbotSmallModel,
"summarization": BlenderbotSmallForConditionalGeneration,
"text-generation": BlenderbotSmallForCausalLM,
@@ -247,7 +246,7 @@ class BlenderbotSmallModelTest(ModelTesterMixin, GenerationTesterMixin, Pipeline
def is_pipeline_test_to_skip(
self, pipeline_test_casse_name, config_class, model_architecture, tokenizer_name, processor_name
):
return pipeline_test_casse_name in ("TextGenerationPipelineTests", "ConversationalPipelineTests")
return pipeline_test_casse_name == "TextGenerationPipelineTests"
def setUp(self):
self.model_tester = BlenderbotSmallModelTester(self)

2
tests/models/blenderbot_small/test_modeling_flax_blenderbot_small.py
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@@ -323,7 +323,7 @@ class FlaxBlenderbotSmallModelTest(FlaxModelTesterMixin, unittest.TestCase, Flax
def is_pipeline_test_to_skip(
self, pipeline_test_casse_name, config_class, model_architecture, tokenizer_name, processor_name
):
return pipeline_test_casse_name in ("TextGenerationPipelineTests", "ConversationalPipelineTests")
return pipeline_test_casse_name == "TextGenerationPipelineTests"
def setUp(self):
self.model_tester = FlaxBlenderbotSmallModelTester(self)

3
tests/models/blenderbot_small/test_modeling_tf_blenderbot_small.py
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@@ -185,7 +185,6 @@ class TFBlenderbotSmallModelTest(TFModelTesterMixin, PipelineTesterMixin, unitte
all_generative_model_classes = (TFBlenderbotSmallForConditionalGeneration,) if is_tf_available() else ()
pipeline_model_mapping = (
{
"conversational": TFBlenderbotSmallForConditionalGeneration,
"feature-extraction": TFBlenderbotSmallModel,
"summarization": TFBlenderbotSmallForConditionalGeneration,
"text2text-generation": TFBlenderbotSmallForConditionalGeneration,
@@ -201,7 +200,7 @@ class TFBlenderbotSmallModelTest(TFModelTesterMixin, PipelineTesterMixin, unitte
def is_pipeline_test_to_skip(
self, pipeline_test_casse_name, config_class, model_architecture, tokenizer_name, processor_name
):
return pipeline_test_casse_name in ("TextGenerationPipelineTests", "ConversationalPipelineTests")
return pipeline_test_casse_name == "TextGenerationPipelineTests"
def setUp(self):
self.model_tester = TFBlenderbotSmallModelTester(self)

1
tests/models/fsmt/test_modeling_fsmt.py
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@@ -166,7 +166,6 @@ class FSMTModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin
all_generative_model_classes = (FSMTForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": FSMTForConditionalGeneration,
"feature-extraction": FSMTModel,
"summarization": FSMTForConditionalGeneration,
"text2text-generation": FSMTForConditionalGeneration,

1
tests/models/led/test_modeling_led.py
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@@ -284,7 +284,6 @@ class LEDModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
all_generative_model_classes = (LEDForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": LEDForConditionalGeneration,
"feature-extraction": LEDModel,
"question-answering": LEDForQuestionAnswering,
"summarization": LEDForConditionalGeneration,

1
tests/models/led/test_modeling_tf_led.py
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@@ -197,7 +197,6 @@ class TFLEDModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
all_generative_model_classes = (TFLEDForConditionalGeneration,) if is_tf_available() else ()
pipeline_model_mapping = (
{
"conversational": TFLEDForConditionalGeneration,
"feature-extraction": TFLEDModel,
"summarization": TFLEDForConditionalGeneration,
"text2text-generation": TFLEDForConditionalGeneration,

1
tests/models/longt5/test_modeling_longt5.py
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@@ -504,7 +504,6 @@ class LongT5ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMix
all_generative_model_classes = (LongT5ForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": LongT5ForConditionalGeneration,
"feature-extraction": LongT5Model,
"summarization": LongT5ForConditionalGeneration,
"text2text-generation": LongT5ForConditionalGeneration,

1
tests/models/m2m_100/test_modeling_m2m_100.py
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@@ -243,7 +243,6 @@ class M2M100ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMix
all_generative_model_classes = (M2M100ForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": M2M100ForConditionalGeneration,
"feature-extraction": M2M100Model,
"summarization": M2M100ForConditionalGeneration,
"text2text-generation": M2M100ForConditionalGeneration,

4
tests/models/marian/test_modeling_flax_marian.py
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@@ -311,10 +311,6 @@ class FlaxMarianModelTest(FlaxModelTesterMixin, unittest.TestCase, FlaxGeneratio
outputs = model(input_ids)
self.assertIsNotNone(outputs)
@unittest.skip("Skipping for now, to fix @ArthurZ or @ydshieh")
def test_pipeline_conversational(self):
pass
@require_flax
@require_sentencepiece

5
tests/models/marian/test_modeling_marian.py
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@@ -248,7 +248,6 @@ class MarianModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMix
all_generative_model_classes = (MarianMTModel,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": MarianMTModel,
"feature-extraction": MarianModel,
"summarization": MarianMTModel,
"text-generation": MarianForCausalLM,
@@ -350,10 +349,6 @@ class MarianModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMix
def test_tie_word_embeddings_decoder(self):
pass
@unittest.skip("Skipping for now, to fix @ArthurZ or @ydshieh")
def test_pipeline_conversational(self):
pass
@unittest.skip(
reason="This architecure seem to not compute gradients properly when using GC, check: https://github.com/huggingface/transformers/pull/27124"
)

5
tests/models/marian/test_modeling_tf_marian.py
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@@ -184,7 +184,6 @@ class TFMarianModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCa
all_generative_model_classes = (TFMarianMTModel,) if is_tf_available() else ()
pipeline_model_mapping = (
{
"conversational": TFMarianMTModel,
"feature-extraction": TFMarianModel,
"summarization": TFMarianMTModel,
"text2text-generation": TFMarianMTModel,
@@ -208,10 +207,6 @@ class TFMarianModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCa
config_and_inputs = self.model_tester.prepare_config_and_inputs_for_common()
self.model_tester.check_decoder_model_past_large_inputs(*config_and_inputs)
@unittest.skip("Skipping for now, to fix @ArthurZ or @ydshieh")
def test_pipeline_conversational(self):
pass
@require_tf
class AbstractMarianIntegrationTest(unittest.TestCase):

1
tests/models/mbart/test_modeling_mbart.py
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@@ -240,7 +240,6 @@ class MBartModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixi
all_generative_model_classes = (MBartForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": MBartForConditionalGeneration,
"feature-extraction": MBartModel,
"fill-mask": MBartForConditionalGeneration,
"question-answering": MBartForQuestionAnswering,

1
tests/models/mbart/test_modeling_tf_mbart.py
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@@ -161,7 +161,6 @@ class TFMBartModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCas
all_generative_model_classes = (TFMBartForConditionalGeneration,) if is_tf_available() else ()
pipeline_model_mapping = (
{
"conversational": TFMBartForConditionalGeneration,
"feature-extraction": TFMBartModel,
"summarization": TFMBartForConditionalGeneration,
"text2text-generation": TFMBartForConditionalGeneration,

5
tests/models/mt5/test_modeling_mt5.py
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@@ -555,7 +555,6 @@ class MT5ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
all_generative_model_classes = (MT5ForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": MT5ForConditionalGeneration,
"feature-extraction": MT5Model,
"question-answering": MT5ForQuestionAnswering,
"summarization": MT5ForConditionalGeneration,
@@ -886,10 +885,6 @@ class MT5ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
attn_weights = out[attn_name] if attn_name == attention_names[0] else out[attn_name][-1]
self.assertEqual(sum([w.sum().item() for w in attn_weights]), 0.0)
@unittest.skip("Does not support conversations.")
def test_pipeline_conversational(self):
pass
# Copied from tests.models.t5.test_modeling_t5.T5EncoderOnlyModelTester with T5->MT5
class MT5EncoderOnlyModelTester:

1
tests/models/mvp/test_modeling_mvp.py
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@@ -421,7 +421,6 @@ class MvpModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
all_generative_model_classes = (MvpForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": MvpForConditionalGeneration,
"feature-extraction": MvpModel,
"fill-mask": MvpForConditionalGeneration,
"question-answering": MvpForQuestionAnswering,

1
tests/models/nllb_moe/test_modeling_nllb_moe.py
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@@ -250,7 +250,6 @@ class NllbMoeModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
all_generative_model_classes = (NllbMoeForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": NllbMoeForConditionalGeneration,
"feature-extraction": NllbMoeModel,
"summarization": NllbMoeForConditionalGeneration,
"text2text-generation": NllbMoeForConditionalGeneration,

1
tests/models/pegasus/test_modeling_pegasus.py
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@@ -246,7 +246,6 @@ class PegasusModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
all_generative_model_classes = (PegasusForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": PegasusForConditionalGeneration,
"feature-extraction": PegasusModel,
"summarization": PegasusForConditionalGeneration,
"text-generation": PegasusForCausalLM,

1
tests/models/pegasus/test_modeling_tf_pegasus.py
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@@ -182,7 +182,6 @@ class TFPegasusModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestC
all_generative_model_classes = (TFPegasusForConditionalGeneration,) if is_tf_available() else ()
pipeline_model_mapping = (
{
"conversational": TFPegasusForConditionalGeneration,
"feature-extraction": TFPegasusModel,
"summarization": TFPegasusForConditionalGeneration,
"text2text-generation": TFPegasusForConditionalGeneration,

1
tests/models/pegasus_x/test_modeling_pegasus_x.py
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@@ -206,7 +206,6 @@ class PegasusXModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterM
all_generative_model_classes = (PegasusXForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": PegasusXForConditionalGeneration,
"feature-extraction": PegasusXModel,
"summarization": PegasusXForConditionalGeneration,
"text2text-generation": PegasusXForConditionalGeneration,

1
tests/models/plbart/test_modeling_plbart.py
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@@ -227,7 +227,6 @@ class PLBartModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMix
all_generative_model_classes = (PLBartForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": PLBartForConditionalGeneration,
"feature-extraction": PLBartModel,
"summarization": PLBartForConditionalGeneration,
"text-classification": PLBartForSequenceClassification,

1
tests/models/prophetnet/test_modeling_prophetnet.py
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@@ -891,7 +891,6 @@ class ProphetNetModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTeste
all_generative_model_classes = (ProphetNetForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": ProphetNetForConditionalGeneration,
"feature-extraction": ProphetNetModel,
"summarization": ProphetNetForConditionalGeneration,
"text-generation": ProphetNetForCausalLM,

1
tests/models/seamless_m4t/test_modeling_seamless_m4t.py
View File

@@ -645,7 +645,6 @@ class SeamlessM4TModelWithTextInputTest(
pipeline_model_mapping = (
{
"automatic-speech-recognition": SeamlessM4TForSpeechToText,
"conversational": SeamlessM4TForTextToText,
"feature-extraction": SeamlessM4TModel,
"summarization": SeamlessM4TForTextToText,
"text-to-audio": SeamlessM4TForTextToSpeech,

1
tests/models/switch_transformers/test_modeling_switch_transformers.py
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@@ -559,7 +559,6 @@ class SwitchTransformersModelTest(ModelTesterMixin, GenerationTesterMixin, Pipel
all_generative_model_classes = (SwitchTransformersForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": SwitchTransformersForConditionalGeneration,
"feature-extraction": SwitchTransformersModel,
"summarization": SwitchTransformersForConditionalGeneration,
"text2text-generation": SwitchTransformersForConditionalGeneration,

5
tests/models/t5/test_modeling_t5.py
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@@ -558,7 +558,6 @@ class T5ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
all_generative_model_classes = (T5ForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": T5ForConditionalGeneration,
"feature-extraction": T5Model,
"question-answering": T5ForQuestionAnswering,
"summarization": T5ForConditionalGeneration,
@@ -889,10 +888,6 @@ class T5ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
attn_weights = out[attn_name] if attn_name == attention_names[0] else out[attn_name][-1]
self.assertEqual(sum([w.sum().item() for w in attn_weights]), 0.0)
@unittest.skip("Does not support conversations.")
def test_pipeline_conversational(self):
pass
class T5EncoderOnlyModelTester:
def __init__(

9
tests/models/t5/test_modeling_tf_t5.py
View File

@@ -248,7 +248,6 @@ class TFT5ModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
all_generative_model_classes = (TFT5ForConditionalGeneration,) if is_tf_available() else ()
pipeline_model_mapping = (
{
"conversational": TFT5ForConditionalGeneration,
"feature-extraction": TFT5Model,
"summarization": TFT5ForConditionalGeneration,
"text2text-generation": TFT5ForConditionalGeneration,
@@ -314,10 +313,6 @@ class TFT5ModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_keras_save_load(self):
pass
@unittest.skip("Does not support conversations.")
def test_pipeline_conversational(self):
pass
class TFT5EncoderOnlyModelTester:
def __init__(
@@ -611,10 +606,6 @@ class TFT5GenerationIntegrationTests(unittest.TestCase):
expected_output_string = ["Ich liebe es so sehr!", "die Transformatoren sind wirklich erstaunlich"]
self.assertListEqual(expected_output_string, output_strings)
@unittest.skip("Does not support conversations.")
def test_pipeline_conversational(self):
pass
@require_tf
@require_sentencepiece

1
tests/models/umt5/test_modeling_umt5.py
View File

@@ -297,7 +297,6 @@ class UMT5ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin
all_generative_model_classes = (UMT5ForConditionalGeneration,) if is_torch_available() else ()
pipeline_model_mapping = (
{
"conversational": UMT5ForConditionalGeneration,
"feature-extraction": UMT5Model,
"question-answering": UMT5ForQuestionAnswering,
"summarization": UMT5ForConditionalGeneration,