[TTS] Add unit tests

Signed-off-by: Ryan <rlangman@nvidia.com>

tests/collections/tts/parts/utils/test_tts_dataset_utils.py

@@ -15,8 +15,14 @@
 from pathlib import Path
 
 import pytest
+import torch
 
-from nemo.collections.tts.parts.utils.tts_dataset_utils import get_abs_rel_paths, get_audio_filepaths
+from nemo.collections.tts.parts.utils.tts_dataset_utils import (
+    filter_dataset_by_duration,
+    get_abs_rel_paths,
+    get_audio_filepaths,
+    stack_tensors,
+)
 
 
 class TestTTSDatasetUtils:
@@ -53,3 +59,53 @@ def test_get_audio_paths(self):
 
         assert abs_path == Path("/home/audio/examples/example.wav")
         assert rel_path == audio_rel_path
+
+    @pytest.mark.run_only_on('CPU')
+    @pytest.mark.unit
+    def test_stack_tensors(self):
+        tensors = [torch.ones([2]), torch.ones([4]), torch.ones([3])]
+        max_lens = [6]
+        expected_output = torch.tensor(
+            [[1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0], [1, 1, 1, 0, 0, 0]], dtype=torch.float32
+        )
+
+        stacked_tensor = stack_tensors(tensors=tensors, max_lens=max_lens)
+
+        torch.testing.assert_close(stacked_tensor, expected_output)
+
+    @pytest.mark.run_only_on('CPU')
+    @pytest.mark.unit
+    def test_stack_tensors_3d(self):
+        tensors = [torch.ones([2, 2]), torch.ones([1, 3])]
+        max_lens = [4, 2]
+        expected_output = torch.tensor(
+            [[[1, 1, 0, 0], [1, 1, 0, 0]], [[1, 1, 1, 0], [0, 0, 0, 0]]], dtype=torch.float32
+        )
+
+        stacked_tensor = stack_tensors(tensors=tensors, max_lens=max_lens)
+
+        torch.testing.assert_close(stacked_tensor, expected_output)
+
+    @pytest.mark.run_only_on('CPU')
+    @pytest.mark.unit
+    def test_filter_dataset_by_duration(self):
+        min_duration = 1.0
+        max_duration = 10.0
+        entries = [
+            {"duration": 0.5},
+            {"duration": 10.0},
+            {"duration": 20.0},
+            {"duration": 0.1},
+            {"duration": 100.0},
+            {"duration": 5.0},
+        ]
+
+        filtered_entries, total_hours, filtered_hours = filter_dataset_by_duration(
+            entries=entries, min_duration=min_duration, max_duration=max_duration
+        )
+
+        assert len(filtered_entries) == 2
+        assert filtered_entries[0]["duration"] == 10.0
+        assert filtered_entries[1]["duration"] == 5.0
+        assert total_hours == (135.6 / 3600.0)
+        assert filtered_hours == (15.0 / 3600.0)