Remove redundant dataset utilities (#1086)

Co-authored-by: krishnakalyan3 <skalyan@cloudera.com>

torchaudio/datasets/cmuarctic.py

 import os
+import csv
 from pathlib import Path
 from typing import Tuple, Union
 
@@ -8,7 +9,6 @@ from torch.utils.data import Dataset
 from torchaudio.datasets.utils import (
     download_url,
     extract_archive,
-    unicode_csv_reader,
 )
 
 URL = "aew"
@@ -154,7 +154,7 @@ class CMUARCTIC(Dataset):
         self._text = os.path.join(self._path, self._folder_text, self._file_text)
 
         with open(self._text, "r") as text:
-            walker = unicode_csv_reader(text, delimiter="\n")
+            walker = csv.reader(text, delimiter="\n")
             self._walker = list(walker)
 
     def __getitem__(self, n: int) -> Tuple[Tensor, int, str, str]:

torchaudio/datasets/commonvoice.py

 import os
+import csv
 import warnings
 from pathlib import Path
 from typing import List, Dict, Tuple, Union, Optional
 
 import torchaudio
-from torchaudio.datasets.utils import unicode_csv_reader
 from torch import Tensor
 from torch.utils.data import Dataset
 
@@ -79,7 +79,7 @@ class COMMONVOICE(Dataset):
         self._tsv = os.path.join(self._path, tsv)
 
         with open(self._tsv, "r") as tsv_:
-            walker = unicode_csv_reader(tsv_, delimiter="\t")
+            walker = csv.reader(tsv_, delimiter="\t")
             self._header = next(walker)
             self._walker = list(walker)
 

torchaudio/datasets/ljspeech.py

@@ -4,7 +4,7 @@ from typing import List, Tuple, Union
 from pathlib import Path
 
 import torchaudio
-from torchaudio.datasets.utils import download_url, extract_archive, unicode_csv_reader
+from torchaudio.datasets.utils import download_url, extract_archive
 from torch import Tensor
 from torch.utils.data import Dataset
 
@@ -75,7 +75,7 @@ class LJSPEECH(Dataset):
                 extract_archive(archive)
 
         with open(self._metadata_path, "r", newline='') as metadata:
-            walker = unicode_csv_reader(metadata, delimiter="|", quoting=csv.QUOTE_NONE)
+            walker = csv.reader(metadata, delimiter="|", quoting=csv.QUOTE_NONE)
             self._walker = list(walker)
 
     def __getitem__(self, n: int) -> Tuple[Tensor, int, str, str]:

torchaudio/datasets/utils.py

-import csv
 import errno
 import hashlib
 import logging
@@ -18,49 +17,6 @@ from torch.utils.data import Dataset
 from torch.utils.model_zoo import tqdm
 
 
-def unicode_csv_reader(unicode_csv_data: TextIOWrapper, **kwargs: Any) -> Any:
-    r"""Since the standard csv library does not handle unicode in Python 2, we need a wrapper.
-    Borrowed and slightly modified from the Python docs:
-    https://docs.python.org/2/library/csv.html#csv-examples
-    Args:
-        unicode_csv_data (TextIOWrapper): unicode csv data (see example below)
-
-    Examples:
-        >>> from torchaudio.datasets.utils import unicode_csv_reader
-        >>> import io
-        >>> with io.open(data_path, encoding="utf8") as f:
-        >>>     reader = unicode_csv_reader(f)
-    """
-
-    # Fix field larger than field limit error
-    maxInt = sys.maxsize
-    while True:
-        # decrease the maxInt value by factor 10
-        # as long as the OverflowError occurs.
-        try:
-            csv.field_size_limit(maxInt)
-            break
-        except OverflowError:
-            maxInt = int(maxInt / 10)
-    csv.field_size_limit(maxInt)
-
-    for line in csv.reader(unicode_csv_data, **kwargs):
-        yield line
-
-
-def makedir_exist_ok(dirpath: str) -> None:
-    """
-    Python2 support for os.makedirs(.., exist_ok=True)
-    """
-    try:
-        os.makedirs(dirpath)
-    except OSError as e:
-        if e.errno == errno.EEXIST:
-            pass
-        else:
-            raise
-
-
 def stream_url(url: str,
                start_byte: Optional[int] = None,
                block_size: int = 32 * 1024,
@@ -305,7 +261,7 @@ class _DiskCache(Dataset):
         item = self.dataset[n]
 
         self._cache[n] = f
-        makedir_exist_ok(self.location)
+        os.makedirs(self.location, exist_ok=True)
         torch.save(item, f)
 
         return item

torchaudio/sox_effects/sox_effects.py

@@ -226,7 +226,7 @@ def apply_effects_file(
         ...         self.sample_rate = sample_rate
         ...
         ...     def __getitem__(self, index):
-        ...         speed = 0.5 + 1.5 * torch.rand()
+        ...         speed = 0.5 + 1.5 * random.randn()
         ...         effects = [
         ...             ['gain', '-n', '-10'],  # apply 10 db attenuation
         ...             ['remix', '-'],  # merge all the channels