Tweak test name by appending factory function name (#1780)

Apply tweak around the test names so that it's easier to see which tests are failing.

Before: `test_import_finetuned_model_2`
After:  `test_import_finetuned_model_2_wav2vec2_large_lv60k`

test/torchaudio_unittest/models/wav2vec2/fairseq_integration_test.py

@@ -23,6 +23,10 @@ def _load_config(*paths):
         return json.load(file_)
 
 
+def _name_func(testcase_func, i, param):
+    return f'{testcase_func.__name__}_{i}_{param[0][1].__name__}'
+
+
 # Pretrined (not fine-tuned) models
 BASE = _load_config('wav2vec_small')
 LARGE = _load_config('libri960_big')
@@ -35,18 +39,18 @@ LARGE_LV60K_960H = _load_config('wav2vec_large_lv60k_960h')
 LARGE_LV60K_SELF_960H = _load_config('wav2vec_large_lv60k_self_960h')
 
 # Config and corresponding factory functions
-PRETRAINED_CONFIGS = [
+PRETRAINED_CONFIGS = parameterized.expand([
     (BASE, wav2vec2_base),
     (LARGE, wav2vec2_large),
     (LARGE_LV60K, wav2vec2_large_lv60k),
     (XLSR_53_56K, wav2vec2_large_lv60k),
-]
-FINETUNED_CONFIGS = [
+], name_func=_name_func)
+FINETUNED_CONFIGS = parameterized.expand([
     (BASE_960H, wav2vec2_base),
     (LARGE_960H, wav2vec2_large),
     (LARGE_LV60K_960H, wav2vec2_large_lv60k),
     (LARGE_LV60K_SELF_960H, wav2vec2_large_lv60k),
-]
+], name_func=_name_func)
 
 
 @skipIfNoModule('fairseq')
@@ -75,9 +79,10 @@ class TestFairseqIntegration(TorchaudioTestCase):
             return Wav2VecEncoder(Wav2Vec2CtcConfig(**config), num_out)
         if config['_name'] == 'wav2vec2':
             return Wav2Vec2Model(Wav2Vec2Config(**config))
+        raise ValueError(f'Unexpected configuration: {config["_name"]}')
 
-    @parameterized.expand([conf[:1] for conf in PRETRAINED_CONFIGS])
-    def test_import_pretrained_model(self, config):
+    @PRETRAINED_CONFIGS
+    def test_import_pretrained_model(self, config, _):
         """Pretrained wav2vec2 models from fairseq can be imported and yields the same results"""
         num_out = 28
         batch_size, num_frames = 3, 1024
@@ -91,7 +96,7 @@ class TestFairseqIntegration(TorchaudioTestCase):
         for i, (ref, _) in enumerate(refs['layer_results']):
             self.assertEqual(hyp[i], ref.transpose(0, 1))
 
-    @parameterized.expand(PRETRAINED_CONFIGS)
+    @PRETRAINED_CONFIGS
     def test_recreate_pretrained_model(self, config, factory_func):
         """Imported pretrained models can be recreated via a factory function without fairseq."""
         num_out = 28
@@ -117,8 +122,8 @@ class TestFairseqIntegration(TorchaudioTestCase):
         self.assertEqual(ref, hyp)
         self.assertEqual(ref_lengths, hyp_lengths)
 
-    @parameterized.expand([conf[:1] for conf in FINETUNED_CONFIGS])
-    def test_import_finetuned_model(self, config):
+    @FINETUNED_CONFIGS
+    def test_import_finetuned_model(self, config, _):
         """Fintuned wav2vec2 models from fairseq can be imported and yields the same results"""
         num_out = 28
         batch_size, num_frames = 3, 1024
@@ -140,7 +145,7 @@ class TestFairseqIntegration(TorchaudioTestCase):
         for i, l in enumerate(output_lengths):
             self.assertEqual(ref[i, :l, ...], hyp[i, :l, ...])
 
-    @parameterized.expand(FINETUNED_CONFIGS)
+    @FINETUNED_CONFIGS
     def test_recreate_finetuned_model(self, config, factory_func):
         """Imported finetuned models can be recreated via a factory function without fairseq."""
         num_out = 28

test/torchaudio_unittest/models/wav2vec2/huggingface_intergration_test.py

@@ -21,6 +21,10 @@ def _load_config(*paths):
         return json.load(file_)
 
 
+def _name_func(testcase_func, i, param):
+    return f"{testcase_func.__name__}_{i}_{param[0][1].__name__}"
+
+
 # Pretrained
 HF_BASE = _load_config('facebook', 'wav2vec2-base')
 HF_LARGE = _load_config('facebook', 'wav2vec2-large')
@@ -35,7 +39,7 @@ HF_LARGE_LV60_SELF_960H = _load_config('facebook', 'wav2vec2-large-960h-lv60-sel
 HF_LARGE_XLSR_DE = _load_config('facebook', 'wav2vec2-large-xlsr-53-german')
 
 # Config and corresponding factory functions
-HF_CONFIGS = [
+HF_CONFIGS = parameterized.expand([
     # pretrained
     (HF_BASE, wav2vec2_base),
     (HF_LARGE, wav2vec2_large),
@@ -48,7 +52,7 @@ HF_CONFIGS = [
     (HF_LARGE_LV60_960H, wav2vec2_large_lv60k),
     (HF_LARGE_LV60_SELF_960H, wav2vec2_large_lv60k),
     (HF_LARGE_XLSR_DE, wav2vec2_large_lv60k),
-]
+], name_func=_name_func)
 
 
 @skipIfNoModule('transformers')
@@ -72,8 +76,8 @@ class TestHFIntegration(TorchaudioTestCase):
         )
         return Wav2Vec2ForCTC(Wav2Vec2Config(**config))
 
-    @parameterized.expand([cfg[:1] for cfg in HF_CONFIGS])
-    def test_import(self, config):
+    @HF_CONFIGS
+    def test_import(self, config, _):
         """wav2vec2 models from HF transformers can be imported and yields the same results"""
         original = self._get_model(config).eval()
         imported = import_huggingface_model(original).eval()
@@ -138,7 +142,7 @@ class TestHFIntegration(TorchaudioTestCase):
         for i, l in enumerate(output_lengths):
             self.assertEqual(ref[i, :l, ...], hyp[i, :l, ...])
 
-    @parameterized.expand(HF_CONFIGS)
+    @HF_CONFIGS
     def test_recreate(self, config, factory_func):
         """Imported models can be recreated via a factory function without Hugging Face transformers."""
         imported = import_huggingface_model(self._get_model(config)).eval()

test/torchaudio_unittest/models/wav2vec2/model_test.py

@@ -15,8 +15,8 @@ from torchaudio_unittest.common_utils import (
 from parameterized import parameterized
 
 
-def _name_func(testcase_func, _, param):
-    return f"{testcase_func.__name__}_{param[0][0].__name__}"
+def _name_func(testcase_func, i, param):
+    return f"{testcase_func.__name__}_{i}_{param[0][0].__name__}"
 
 
 factory_funcs = parameterized.expand([