Restored tests previously disabled for 22.03 base

nemo/collections/tts/modules/waveglow.py

@@ -131,13 +131,19 @@ def forward(self, spec, z=None, audio=None, run_inverse=True, sigma=1.0):
 
     @property
     def input_types(self):
-        return {
-            "spec": NeuralType(('B', 'D', 'T'), MelSpectrogramType()),
-            "z": NeuralType(('B', 'D', 'T'), MelSpectrogramType()),
-            "audio": NeuralType(('B', 'T'), AudioSignal(), optional=True),
-            "run_inverse": NeuralType(elements_type=IntType(), optional=True),
-            "sigma": NeuralType(optional=True),
-        }
+        if self.mode == OperationMode.infer:
+            return {
+                "spec": NeuralType(('B', 'D', 'T'), MelSpectrogramType()),
+                "z": NeuralType(('B', 'D', 'T'), MelSpectrogramType()),
+            }
+        else:
+            return {
+                "spec": NeuralType(('B', 'D', 'T'), MelSpectrogramType()),
+                "z": NeuralType(('B', 'D', 'T'), MelSpectrogramType()),
+                "audio": NeuralType(('B', 'T'), AudioSignal(), optional=True),
+                "run_inverse": NeuralType(elements_type=IntType(), optional=True),
+                "sigma": NeuralType(optional=True),
+            }
 
     @property
     def output_types(self):

tests/collections/nlp/test_huggingface.py

@@ -49,8 +49,7 @@ def test_get_pretrained_bert_model(self):
         self.omega_conf.language_model.pretrained_model_name = 'bert-base-uncased'
         model = nemo_nlp.modules.get_lm_model(cfg=self.omega_conf)
         assert isinstance(model, nemo_nlp.modules.BertEncoder)
-        # TODO: Fix
-        # do_export(model, "bert-base-uncased")
+        do_export(model, "bert-base-uncased")
 
     @pytest.mark.with_downloads()
     @pytest.mark.unit
@@ -74,8 +73,7 @@ def test_get_pretrained_albert_model(self):
         self.omega_conf.language_model.pretrained_model_name = 'albert-base-v1'
         model = nemo_nlp.modules.get_lm_model(cfg=self.omega_conf)
         assert isinstance(model, nemo_nlp.modules.AlbertEncoder)
-        # TODO: fix
-        # do_export(model, "albert-base-v1")
+        do_export(model, "albert-base-v1")
 
     @pytest.mark.with_downloads()
     @pytest.mark.unit

tests/collections/nlp/test_nlp_exportables.py

@@ -99,7 +99,6 @@ def test_IntentSlotClassificationModel_export_to_onnx(self, dummy_data):
             assert onnx_model.graph.output[0].name == 'intent_logits'
             assert onnx_model.graph.output[1].name == 'slot_logits'
 
-    @pytest.mark.pleasefixme
     @pytest.mark.with_downloads()
     @pytest.mark.run_only_on('GPU')
     @pytest.mark.unit
@@ -130,7 +129,6 @@ def test_PunctuationCapitalizationModel_export_to_onnx(self):
             assert onnx_model.graph.output[0].name == 'punct_logits'
             assert onnx_model.graph.output[1].name == 'capit_logits'
 
-    @pytest.mark.pleasefixme
     @pytest.mark.with_downloads()
     @pytest.mark.run_only_on('GPU')
     @pytest.mark.unit

tests/collections/tts/test_tts_exportables.py

@@ -23,23 +23,17 @@
 
 @pytest.fixture()
 def fastpitch_model():
-    test_root = os.path.dirname(os.path.abspath(__file__))
-    conf = OmegaConf.load(os.path.join(test_root, '../../../examples/tts/conf/fastpitch_align_v1.05.yaml'))
-    conf.train_dataset = conf.validation_datasets = '.'
-    conf.model.train_ds = conf.model.test_ds = conf.model.validation_ds = None
-    model = FastPitchModel(cfg=conf.model)
+    model = FastPitchModel.from_pretrained(model_name="tts_en_fastpitch")
     return model
 
 
 @pytest.fixture()
 def hifigan_model():
-    test_root = os.path.dirname(os.path.abspath(__file__))
     model = HifiGanModel.from_pretrained(model_name="tts_hifigan")
     return model
 
 
 class TestExportable:
-    @pytest.mark.pleasefixme
     @pytest.mark.run_only_on('GPU')
     @pytest.mark.unit
     def test_FastPitchModel_export_to_onnx(self, fastpitch_model):

tests/collections/tts/test_waveglow.py

@@ -73,7 +73,6 @@ def forward_wrapper(self, spec, z=None):
 
 
 class TestWaveGlow:
-    @pytest.mark.pleasefixme
     @pytest.mark.run_only_on('GPU')
     @pytest.mark.unit
     def test_export_to_onnx(self):