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Skip tests properly (#31308)

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* Skip tests properly

* [test_all]

* Add 'reason' as kwarg for skipTest

* [test_all] Fix up

* [test_all]
This commit is contained in:
amyeroberts
2024-06-26 21:59:08 +01:00
committed by GitHub
parent 1f9f57ab4c
commit 1de7dc7403
254 changed files with 1721 additions and 1298 deletions
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39
tests/models/whisper/test_modeling_whisper.py
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@@ -504,9 +504,11 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
model(**inputs)[0]
# training is not supported yet
@unittest.skip(reason="Training is not supported yet")
def test_training(self):
pass
@unittest.skip(reason="Training is not supported yet")
def test_training_gradient_checkpointing(self):
pass
@@ -522,6 +524,7 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
def test_training_gradient_checkpointing_use_reentrant_false(self):
pass
@unittest.skip
def test_generate_with_head_masking(self):
pass
@@ -736,7 +739,7 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
inputs_dict,
) = self.model_tester.prepare_config_and_inputs_for_common()
if not self.test_resize_embeddings:
return
self.skipTest(reason="test_resize_embeddings is False")
for model_class in self.all_model_classes:
config = copy.deepcopy(original_config)
@@ -784,13 +787,13 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
inputs_dict,
) = self.model_tester.prepare_config_and_inputs_for_common()
if not self.test_resize_embeddings:
return
self.skipTest(reason="test_resize_embeddings is False")
original_config.tie_word_embeddings = False
# if model cannot untied embeddings -> leave test
if original_config.tie_word_embeddings:
return
self.skipTest(reason="Model cannot untie embeddings")
for model_class in self.all_model_classes:
config = copy.deepcopy(original_config)
@@ -827,6 +830,7 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
# Check that the model can still do a forward pass successfully (every parameter should be resized)
model(**self._prepare_for_class(inputs_dict, model_class))
@unittest.skip
def test_generate_without_input_ids(self):
pass
@@ -901,7 +905,7 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
for model_class in self.all_model_classes:
if not model_class._supports_flash_attn_2:
return
self.skipTest(reason="Model does not support Flash Attention 2")
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
model = model_class(config)
@@ -947,7 +951,7 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
for model_class in self.all_model_classes:
if not model_class._supports_flash_attn_2:
return
self.skipTest(reason="Model does not support flash_attention_2")
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
model = model_class(config)
@@ -996,7 +1000,7 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
def _create_and_check_torchscript(self, config, inputs_dict):
if not self.test_torchscript:
return
self.skipTest(reason="test_torchscript is set to False")
configs_no_init = _config_zero_init(config) # To be sure we have no Nan
configs_no_init.torchscript = True
@@ -1096,8 +1100,7 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
fx_model_class_name = "Flax" + model_class.__name__
if not hasattr(transformers, fx_model_class_name):
# no flax model exists for this class
return
self.skipTest(reason="No Flax model exists for this class")
# Output all for aggressive testing
config.output_hidden_states = True
@@ -1169,8 +1172,7 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
fx_model_class_name = "Flax" + model_class.__name__
if not hasattr(transformers, fx_model_class_name):
# no flax model exists for this class
return
self.skipTest(reason="No Flax model exists for this class")
# Output all for aggressive testing
config.output_hidden_states = True
@@ -3133,8 +3135,9 @@ class WhisperEncoderModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.
def test_model_parallelism(self):
pass
# input embeds is meaningless for an encoder-only acoustic model
@unittest.skip(reason="Not applicable for an encoder-only acoustic model")
def test_inputs_embeds(self):
# input embeds is meaningless for an encoder-only acoustic model
pass
# the equivalent test is passing the encoder outputs directly to the model
@@ -3181,6 +3184,7 @@ class WhisperEncoderModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.
self.assertTrue(x is None or isinstance(x, torch.nn.Conv1d))
# WhisperEncoder cannot resize token embeddings since it has no tokens embeddings
@unittest.skip(reason="Model has no tokens embeds")
def test_resize_tokens_embeddings(self):
pass
@@ -3194,8 +3198,7 @@ class WhisperEncoderModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.
fx_model_class_name = "Flax" + model_class.__name__
if not hasattr(transformers, fx_model_class_name):
# no flax model exists for this class
return
self.skipTest(reason="Flax model does not exist")
# Output all for aggressive testing
config.output_hidden_states = True
@@ -3267,8 +3270,7 @@ class WhisperEncoderModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.
fx_model_class_name = "Flax" + model_class.__name__
if not hasattr(transformers, fx_model_class_name):
# no flax model exists for this class
return
self.skip("Flax model does not exist")
# Output all for aggressive testing
config.output_hidden_states = True
@@ -3562,17 +3564,16 @@ class WhisperStandaloneDecoderModelTest(ModelTesterMixin, GenerationTesterMixin,
config=config, input_ids=inputs_dict["input_ids"]
)
@unittest.skip("Generate needs input ids")
@unittest.skip(reason="Generate needs input ids")
def test_generate_without_input_ids(self):
# generate only works with input ids for whisper
pass
@unittest.skip("Decoder can't keep attention grads")
@unittest.skip(reason="Decoder can't keep attention grads")
def test_retain_grad_hidden_states_attentions(self):
# decoder cannot keep gradients
return
@unittest.skip("The model doesn't support fast init from base")
@unittest.skip(reason="The model doesn't support fast init from base")
def test_save_load_fast_init_from_base(self):
pass

3
tests/models/whisper/test_tokenization_whisper.py
View File

@@ -89,12 +89,15 @@ class WhisperTokenizerTest(TokenizerTesterMixin, unittest.TestCase):
["I", "Ġwas", "Ġborn", "Ġin", "Ġ9", "2000", ",", "Ġand", "Ġthis", "Ġis", "Ġfals", "é", "."], # fmt: skip
)
@unittest.skip
def test_tokenizer_slow_store_full_signature(self):
pass
@unittest.skip
def test_tokenizer_fast_store_full_signature(self):
pass
@unittest.skip
def test_special_tokens_initialization(self):
# Whisper relies on specific additional special tokens, so we skip this
# general test. In particular, this test loads fast tokenizer from slow