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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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86
tests/models/speecht5/test_modeling_speecht5.py
View File

@@ -212,31 +212,31 @@ class SpeechT5ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
)
self.assertListEqual(arg_names[: len(expected_arg_names)], expected_arg_names)
# this model has no inputs_embeds
@unittest.skip(reason="Model has no input_embeds")
def test_inputs_embeds(self):
pass
# this model has no input embeddings
@unittest.skip(reason="Model has no input_embeds")
def test_model_get_set_embeddings(self):
pass
@unittest.skip(reason="Decoder cannot keep gradients")
def test_retain_grad_hidden_states_attentions(self):
# decoder cannot keep gradients
pass
@slow
@unittest.skip(reason="Model does not have decoder_input_ids")
def test_torchscript_output_attentions(self):
# disabled because this model doesn't have decoder_input_ids
pass
@slow
@unittest.skip(reason="Model does not have decoder_input_ids")
def test_torchscript_output_hidden_state(self):
# disabled because this model doesn't have decoder_input_ids
pass
@slow
@unittest.skip(reason="Model does not have decoder_input_ids")
def test_torchscript_simple(self):
# disabled because this model doesn't have decoder_input_ids
pass
@@ -598,19 +598,20 @@ class SpeechT5ForSpeechToTextTest(ModelTesterMixin, unittest.TestCase):
)
# this model has no inputs_embeds
@unittest.skip(reason="Model has no input_embeds")
def test_inputs_embeds(self):
pass
def test_resize_embeddings_untied(self):
original_config, 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 set to 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)
@@ -650,7 +651,7 @@ class SpeechT5ForSpeechToTextTest(ModelTesterMixin, unittest.TestCase):
def test_resize_tokens_embeddings(self):
original_config, 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 set to False")
for model_class in self.all_model_classes:
config = copy.deepcopy(original_config)
@@ -692,14 +693,16 @@ class SpeechT5ForSpeechToTextTest(ModelTesterMixin, unittest.TestCase):
self.assertTrue(models_equal)
@unittest.skip(reason="Decoder cannot keep gradients")
def test_retain_grad_hidden_states_attentions(self):
# decoder cannot keep gradients
pass
# 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
@@ -928,15 +931,15 @@ class SpeechT5ForTextToSpeechTest(ModelTesterMixin, unittest.TestCase):
(self.model_tester.batch_size, self.model_tester.decoder_seq_length, self.model_tester.num_mel_bins),
)
# skipped because there is always dropout in SpeechT5SpeechDecoderPrenet
@unittest.skip(reason="Dropout is always present in SpeechT5SpeechDecoderPrenet")
def test_decoder_model_past_with_large_inputs(self):
pass
# skipped because there is always dropout in SpeechT5SpeechDecoderPrenet
@unittest.skip(reason="Dropout is always present in SpeechT5SpeechDecoderPrenet")
def test_determinism(self):
pass
@unittest.skip("skipped because there is always dropout in SpeechT5SpeechDecoderPrenet")
@unittest.skip(reason="skipped because there is always dropout in SpeechT5SpeechDecoderPrenet")
def test_batching_equivalence(self):
pass
@@ -985,41 +988,43 @@ class SpeechT5ForTextToSpeechTest(ModelTesterMixin, unittest.TestCase):
msg=f"Parameter {name} of model {model_class} seems not properly initialized",
)
# this model has no inputs_embeds
@unittest.skip(reason="Model has no inputs_embeds")
def test_inputs_embeds(self):
pass
# skipped because there is always dropout in SpeechT5SpeechDecoderPrenet
@unittest.skip(reason="Dropout is always present in SpeechT5SpeechDecoderPrenet")
def test_model_outputs_equivalence(self):
pass
# skipped because there is always dropout in SpeechT5SpeechDecoderPrenet
@unittest.skip(reason="Dropout is always present in SpeechT5SpeechDecoderPrenet")
def test_save_load(self):
pass
@unittest.skip(reason="Decoder cannot keep gradients")
def test_retain_grad_hidden_states_attentions(self):
# decoder cannot keep gradients
pass
@slow
@unittest.skip(reason="Model doesn't have decoder_input_ids")
def test_torchscript_output_attentions(self):
# disabled because this model doesn't have decoder_input_ids
pass
@slow
@unittest.skip(reason="Model doesn't have decoder_input_ids")
def test_torchscript_output_hidden_state(self):
# disabled because this model doesn't have decoder_input_ids
pass
@slow
@unittest.skip(reason="Model doesn't have decoder_input_ids")
def test_torchscript_simple(self):
# disabled because this model doesn't have decoder_input_ids
pass
# 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
@@ -1472,15 +1477,15 @@ class SpeechT5ForSpeechToSpeechTest(ModelTesterMixin, unittest.TestCase):
(self.model_tester.batch_size, self.model_tester.decoder_seq_length, self.model_tester.num_mel_bins),
)
# skipped because there is always dropout in SpeechT5SpeechDecoderPrenet
@unittest.skip(reason="There is always dropout in SpeechT5SpeechDecoderPrenet")
def test_decoder_model_past_with_large_inputs(self):
pass
# skipped because there is always dropout in SpeechT5SpeechDecoderPrenet
@unittest.skip(reason="There is always dropout in SpeechT5SpeechDecoderPrenet")
def test_determinism(self):
pass
@unittest.skip("skipped because there is always dropout in SpeechT5SpeechDecoderPrenet")
@unittest.skip(reason="skipped because there is always dropout in SpeechT5SpeechDecoderPrenet")
def test_batching_equivalence(self):
pass
@@ -1685,45 +1690,46 @@ class SpeechT5ForSpeechToSpeechTest(ModelTesterMixin, unittest.TestCase):
msg=f"Parameter {name} of model {model_class} seems not properly initialized",
)
# this model has no inputs_embeds
@unittest.skip(reason="Model has no input_embeds")
def test_inputs_embeds(self):
pass
# this model has no input embeddings
@unittest.skip(reason="Model has no input_embeds")
def test_model_get_set_embeddings(self):
pass
# skipped because there is always dropout in SpeechT5SpeechDecoderPrenet
@unittest.skip(reason="Dropout is always present in SpeechT5SpeechDecoderPrenet")
def test_model_outputs_equivalence(self):
pass
@unittest.skip(reason="Decoder cannot keep gradients")
def test_retain_grad_hidden_states_attentions(self):
# decoder cannot keep gradients
pass
# skipped because there is always dropout in SpeechT5SpeechDecoderPrenet
@unittest.skip(reason="Dropout is always present in SpeechT5SpeechDecoderPrenet")
def test_save_load(self):
pass
@slow
@unittest.skip(reason="Model doesn't have decoder_input_ids")
def test_torchscript_output_attentions(self):
# disabled because this model doesn't have decoder_input_ids
pass
@slow
@unittest.skip(reason="Model doesn't have decoder_input_ids")
def test_torchscript_output_hidden_state(self):
# disabled because this model doesn't have decoder_input_ids
pass
@slow
@unittest.skip(reason="Model doesn't have decoder_input_ids")
def test_torchscript_simple(self):
# disabled because this model doesn't have decoder_input_ids
pass
# 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
@@ -1873,35 +1879,35 @@ class SpeechT5HifiGanTest(ModelTesterMixin, unittest.TestCase):
]
self.assertListEqual(arg_names[: len(expected_arg_names)], expected_arg_names)
# this model does not output hidden states
@unittest.skip(reason="Model does not output hidden states")
def test_hidden_states_output(self):
pass
# skip
@unittest.skip
def test_initialization(self):
pass
# this model has no inputs_embeds
@unittest.skip(reason="Model has no input_embeds")
def test_inputs_embeds(self):
pass
# this model has no input embeddings
@unittest.skip(reason="Model has no input_embeds")
def test_model_get_set_embeddings(self):
pass
# skip as this model doesn't support all arguments tested
@unittest.skip(reason="Model does not support all arguments tested")
def test_model_outputs_equivalence(self):
pass
# this model does not output hidden states
@unittest.skip(reason="Model does not output hidden states")
def test_retain_grad_hidden_states_attentions(self):
pass
# skip because it fails on automapping of SpeechT5HifiGanConfig
@unittest.skip(reason="Fails on automapping of SpeechT5HifiGanConfig")
def test_save_load_fast_init_from_base(self):
pass
# skip because it fails on automapping of SpeechT5HifiGanConfig
@unittest.skip(reason="Fails on automapping of SpeechT5HifiGanConfig")
def test_save_load_fast_init_to_base(self):
pass

2
tests/models/speecht5/test_tokenization_speecht5.py
View File

@@ -143,9 +143,11 @@ class SpeechT5TokenizerTest(TokenizerTesterMixin, unittest.TestCase):
self.assertEqual(tokens[0], tokenizer.eos_token_id)
self.assertEqual(tokens[-3], tokenizer.pad_token_id)
@unittest.skip
def test_pickle_subword_regularization_tokenizer(self):
pass
@unittest.skip
def test_subword_regularization_tokenizer(self):
pass