Add unit test for LJSpeech dataset (#826)

Co-authored-by: lawrencechen <lawrencechen@devvm3189.vll0.facebook.com>

test/assets/LJSpeech-1.1/metadata.csv

-LJ001-0001|Printing, in the only sense with which we are at present concerned, differs from most if not from all the arts and crafts represented in the Exhibition|Printing, in the only sense with which we are at present concerned, differs from most if not from all the arts and crafts represented in the Exhibition

test/datasets/datasets_test.py

@@ -2,7 +2,6 @@ from torchaudio.datasets.commonvoice import COMMONVOICE
 from torchaudio.datasets.speechcommands import SPEECHCOMMANDS
 from torchaudio.datasets.utils import diskcache_iterator, bg_iterator
 from torchaudio.datasets.vctk import VCTK
-from torchaudio.datasets.ljspeech import LJSPEECH
 from torchaudio.datasets.cmuarctic import CMUARCTIC
 
 from ..common_utils import (
@@ -19,10 +18,6 @@ class TestDatasets(TorchaudioTestCase):
         data = VCTK(self.path)
         data[0]
 
-    def test_ljspeech(self):
-        data = LJSPEECH(self.path)
-        data[0]
-
     def test_speechcommands(self):
         data = SPEECHCOMMANDS(self.path)
         data[0]

test/datasets/ljspeech_test.py

+import csv
+import os
+
+from torchaudio.datasets import ljspeech
+
+from ..common_utils import (
+    TempDirMixin,
+    TorchaudioTestCase,
+    get_whitenoise,
+    normalize_wav,
+    save_wav,
+)
+
+
+class TestLJSpeech(TempDirMixin, TorchaudioTestCase):
+    backend = "default"
+
+    root_dir = None
+    data = []
+    transcripts = [
+        "Test transcript 1",
+        "Test transcript 2",
+        "Test transcript 3",
+        "In 1465 Sweynheim and Pannartz began printing in the monastery of Subiaco near Rome,"
+    ]
+
+    normalized_transcripts = [
+        "Test transcript one",
+        "Test transcript two",
+        "Test transcript three",
+        "In fourteen sixty-five Sweynheim and Pannartz began printing in the monastery of Subiaco near Rome,"
+    ]
+
+    @classmethod
+    def setUpClass(cls):
+        cls.root_dir = cls.get_base_temp_dir()
+        base_dir = os.path.join(cls.root_dir, "LJSpeech-1.1")
+        archive_dir = os.path.join(base_dir, "wavs")
+        os.makedirs(archive_dir, exist_ok=True)
+        metadata_path = os.path.join(base_dir, "metadata.csv")
+        sample_rate = 22050
+
+        with open(metadata_path, mode="w", newline='') as metadata_file:
+            metadata_writer = csv.writer(
+                metadata_file, delimiter="|", quoting=csv.QUOTE_NONE
+            )
+            for i, (transcript, normalized_transcript) in enumerate(
+                zip(cls.transcripts, cls.normalized_transcripts)
+            ):
+                fileid = f'LJ001-{i:04d}'
+                metadata_writer.writerow([fileid, transcript, normalized_transcript])
+                filename = fileid + ".wav"
+                path = os.path.join(archive_dir, filename)
+                data = get_whitenoise(
+                    sample_rate=sample_rate, duration=1, n_channels=1, dtype="int16", seed=i
+                )
+                save_wav(path, data, sample_rate)
+                cls.data.append(normalize_wav(data))
+
+    def test_ljspeech(self):
+        dataset = ljspeech.LJSPEECH(self.root_dir)
+        n_ite = 0
+        for i, (waveform, sample_rate, transcript, normalized_transcript) in enumerate(
+            dataset
+        ):
+            expected_transcript = self.transcripts[i]
+            expected_normalized_transcript = self.normalized_transcripts[i]
+            expected_data = self.data[i]
+            self.assertEqual(expected_data, waveform, atol=5e-5, rtol=1e-8)
+            assert sample_rate == sample_rate
+            assert transcript == expected_transcript
+            assert normalized_transcript == expected_normalized_transcript
+            n_ite += 1
+        assert n_ite == len(self.data)

torchaudio/datasets/ljspeech.py

@@ -63,7 +63,7 @@ class LJSPEECH(Dataset):
                     download_url(url, root, hash_value=checksum)
                 extract_archive(archive)
 
-        with open(self._metadata_path, "r") as metadata:
+        with open(self._metadata_path, "r", newline='') as metadata:
             walker = unicode_csv_reader(metadata, delimiter="|", quoting=csv.QUOTE_NONE)
             self._walker = list(walker)