Fix inline typing for mypy (#544)

* fix inline typing for mypy

* fix flake8

* change check position

* fix for py3.5

* fix for py3.5

* change to inline typing

* add inline typing

torchaudio/__init__.py

@@ -168,13 +168,13 @@ def save_encinfo(filepath: str,
     # sox stores the sample rate as a float, though practically sample rates are almost always integers
     # convert integers to floats
     if signalinfo:
-        if not isinstance(signalinfo.rate, float):
+        if signalinfo.rate and not isinstance(signalinfo.rate, float):
             if float(signalinfo.rate) == signalinfo.rate:
                 signalinfo.rate = float(signalinfo.rate)
             else:
                 raise TypeError('Sample rate should be a float or int')
         # check if the bit precision (i.e. bits per sample) is an integer
-        if not isinstance(signalinfo.precision, int):
+        if signalinfo.precision and not isinstance(signalinfo.precision, int):
             if int(signalinfo.precision) == signalinfo.precision:
                 signalinfo.precision = int(signalinfo.precision)
             else:

torchaudio/_sox_backend.py

 import os.path
-from typing import Any, Optional, Tuple, Union
+from typing import Optional, Tuple
 
 import torch
 from torch import Tensor
@@ -9,8 +9,8 @@ from torchaudio._soundfile_backend import SignalInfo, EncodingInfo
 
 def load(filepath: str,
          out: Optional[Tensor] = None,
-         normalization: Optional[bool] = True,
-         channels_first: Optional[bool] = True,
+         normalization: bool = True,
+         channels_first: bool = True,
          num_frames: int = 0,
          offset: int = 0,
          signalinfo: SignalInfo = None,

torchaudio/datasets/utils.py

@@ -7,17 +7,18 @@ import sys
 import tarfile
 import threading
 import zipfile
-from io import TextIOWrapper
+from _io import TextIOWrapper
 from queue import Queue
 from typing import Any, Iterable, List, Optional, Tuple, Union
 
 import torch
 import urllib
+import urllib.request
 from torch.utils.data import Dataset
 from torch.utils.model_zoo import tqdm
 
 
-def unicode_csv_reader(unicode_csv_data: TextIOWrapper, **kwargs: Any) -> str:
+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
@@ -63,7 +64,7 @@ def makedir_exist_ok(dirpath: str) -> None:
 def stream_url(url: str,
                start_byte: Optional[int] = None,
                block_size: int = 32 * 1024,
-               progress_bar: bool = True) -> None:
+               progress_bar: bool = True) -> Iterable:
     """Stream url by chunk
 
     Args:
@@ -126,10 +127,10 @@ def download_url(url: str,
     # Detect filename
     filename = filename or req_info.get_filename() or os.path.basename(url)
     filepath = os.path.join(download_folder, filename)
-
     if resume and os.path.exists(filepath):
         mode = "ab"
-        local_size = os.path.getsize(filepath)
+        local_size: Optional[int] = os.path.getsize(filepath)
+
     elif not resume and os.path.exists(filepath):
         raise RuntimeError(
             "{} already exists. Delete the file manually and retry.".format(filepath)
@@ -215,7 +216,7 @@ def extract_archive(from_path: str, to_path: Optional[str] = None, overwrite: bo
         with tarfile.open(from_path, "r") as tar:
             logging.info("Opened tar file {}.".format(from_path))
             files = []
-            for file_ in tar:
+            for file_ in tar:  # type: Any
                 file_path = os.path.join(to_path, file_.name)
                 if file_.isfile():
                     files.append(file_path)
@@ -249,7 +250,7 @@ def extract_archive(from_path: str, to_path: Optional[str] = None, overwrite: bo
 def walk_files(root: str,
                suffix: Union[str, Tuple[str]],
                prefix: bool = False,
-               remove_suffix: bool = False) -> str:
+               remove_suffix: bool = False) -> Iterable[str]:
     """List recursively all files ending with a suffix at a given root
     Args:
         root (str): Path to directory whose folders need to be listed
@@ -286,7 +287,7 @@ class _DiskCache(Dataset):
         self.location = location
 
         self._id = id(self)
-        self._cache = [None] * len(dataset)
+        self._cache: List = [None] * len(dataset)
 
     def __getitem__(self, n: int) -> Any:
         if self._cache[n]:
@@ -325,7 +326,7 @@ class _ThreadedIterator(threading.Thread):
 
     def __init__(self, generator: Iterable, maxsize: int) -> None:
         threading.Thread.__init__(self)
-        self.queue = Queue(maxsize)
+        self.queue: Queue = Queue(maxsize)
         self.generator = generator
         self.daemon = True
         self.start()

torchaudio/datasets/vctk.py

@@ -76,7 +76,7 @@ class VCTK(Dataset):
         if downsample:
             warnings.warn(
                 "In the next version, transforms will not be part of the dataset. "
-                "Please use `downsample=False` to enable this behavior now, ",
+                "Please use `downsample=False` to enable this behavior now, "
                 "and suppress this warning."
             )
 

torchaudio/sox_effects.py

@@ -86,8 +86,8 @@ class SoxEffectsChain(object):
                  out_siginfo: Any = None,
                  out_encinfo: Any = None,
                  filetype: str = "raw") -> None:
-        self.input_file = None
-        self.chain = []
+        self.input_file: Optional[str] = None
+        self.chain: List[str] = []
         self.MAX_EFFECT_OPTS = 20
         self.out_siginfo = out_siginfo
         self.out_encinfo = out_encinfo
@@ -100,12 +100,12 @@ class SoxEffectsChain(object):
 
     def append_effect_to_chain(self,
                                ename: str,
-                               eargs: Optional[List[str]] = None) -> None:
+                               eargs: Optional[Union[List[str], str]] = None) -> None:
         r"""Append effect to a sox effects chain.
 
         Args:
             ename (str): which is the name of effect
-            eargs (List[str], optional): which is a list of effect options. (Default: ``None``)
+            eargs (List[str] or str, optional): which is a list of effect options. (Default: ``None``)
         """
         e = SoxEffect()
         # check if we have a valid effect

torchaudio/transforms.py

@@ -454,7 +454,7 @@ class MFCC(torch.nn.Module):
         super(MFCC, self).__init__()
         supported_dct_types = [2]
         if dct_type not in supported_dct_types:
-            raise ValueError('DCT type not supported'.format(dct_type))
+            raise ValueError('DCT type not supported: {}'.format(dct_type))
         self.sample_rate = sample_rate
         self.n_mfcc = n_mfcc
         self.dct_type = dct_type