Tests: move generate tests to the right mixin and delete redundant tests (#34464)
* tmp commit * tmp commit * cull overwrites of deleted tests * typo * more specific docstring * make fixup * parameterize at the top? * correction * more deletions :D * tmp commit * for VLMs too * fix _check_outputs * test nit * make fixup * fix another flaky * test_generate_from_inputs_embeds -- handle missing attention mask
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@@ -1574,59 +1574,6 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
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)
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assert isinstance(pred_ids, expected_output_type)
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@require_flash_attn
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@require_torch_gpu
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@pytest.mark.flash_attn_test
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@slow
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def test_flash_attn_2_generate_reuse_cache(self):
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max_new_tokens = 2
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for model_class in self.all_generative_model_classes:
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if not model_class._supports_flash_attn_2:
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self.skipTest(f"{model_class.__name__} does not support Flash Attention 2")
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config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
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dummy_input = inputs_dict[model_class.main_input_name][..., :10]
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if dummy_input.dtype in [torch.float32, torch.bfloat16]:
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dummy_input = dummy_input.to(torch.float16)
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# make sure that all models have enough positions for generation
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if hasattr(config, "max_position_embeddings"):
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config.max_position_embeddings = dummy_input.shape[1] * 2 + max_new_tokens * 2 + 1
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model = model_class(config)
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with tempfile.TemporaryDirectory() as tmpdirname:
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model.save_pretrained(tmpdirname)
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model = model_class.from_pretrained(
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tmpdirname,
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torch_dtype=torch.float16,
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attn_implementation="flash_attention_2",
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low_cpu_mem_usage=True,
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).to(torch_device)
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# run generate once to get filled cache
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output = model.generate(
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dummy_input,
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max_new_tokens=max_new_tokens,
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do_sample=False,
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use_cache=True,
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return_dict_in_generate=True,
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)
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past_key_values = output.past_key_values
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# Try to continue generation from where we left, given that we have more than 1 new token to process
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# e.g. this can happen in speculative decoding when feeding candidate tokens back to target model
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_ = model.generate(
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dummy_input,
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decoder_input_ids=output.sequences,
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max_new_tokens=max_new_tokens,
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do_sample=False,
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use_cache=True,
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past_key_values=past_key_values,
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)
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def test_labels_sequence_max_length_correct(self):
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config, input_dict = self.model_tester.prepare_config_and_inputs_for_common()
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@@ -3961,11 +3908,6 @@ class WhisperStandaloneDecoderModelTest(ModelTesterMixin, GenerationTesterMixin,
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# generate only works with input ids for whisper
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pass
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@unittest.skip(reason="Generate needs input ids")
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def test_inputs_embeds_matches_input_ids_with_generate(self):
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# generate only works with input ids for whisper
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pass
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@unittest.skip(reason="Decoder can't keep attention grads")
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def test_retain_grad_hidden_states_attentions(self):
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return
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@@ -3974,18 +3916,6 @@ class WhisperStandaloneDecoderModelTest(ModelTesterMixin, GenerationTesterMixin,
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def test_save_load_fast_init_from_base(self):
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pass
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@unittest.skip(
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reason="FA2 testing suite needs to be refactored to be compatible with WhisperDecoder for that test"
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)
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def test_flash_attn_2_generate_reuse_cache(self):
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pass
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@unittest.skip(
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"Duplicated test with WhisperModelTest + the FA2 testing suite needs to be refactored to be compatible with WhisperDecoder for that test"
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)
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def test_flash_attn_2_generate_padding_right(self):
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pass
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@unittest.skip(
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"Duplicated test with WhisperModelTest + the FA2 testing suite needs to be refactored to be compatible with WhisperDecoder for that test"
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)
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