Inline typing _backend

torchaudio/_backend.py

@@ -1,7 +1,9 @@
 from functools import wraps
+from typing import Any, List, Union
 
 import platform
 import torch
+from torch import Tensor
 
 from . import _soundfile_backend, _sox_backend
 
@@ -10,11 +12,11 @@
 _audio_backends = {"sox": _sox_backend, "soundfile": _soundfile_backend}
 
 
-def set_audio_backend(backend):
+def set_audio_backend(backend: str) -> None:
     """
     Specifies the package used to load.
     Args:
-        backend (string): Name of the backend. One of {}.
+        backend (str): Name of the backend. One of {}.
     """.format(_audio_backends.keys())
     global _audio_backend
     if backend not in _audio_backends:
@@ -24,22 +26,22 @@ def set_audio_backend(backend):
     _audio_backend = backend
 
 
-def get_audio_backend():
+def get_audio_backend() -> str:
     """
     Gets the name of the package used to load.
     """
     return _audio_backend
 
 
-def _get_audio_backend_module():
+def _get_audio_backend_module() -> Any:
     """
     Gets the module backend to load.
     """
     backend = get_audio_backend()
     return _audio_backends[backend]
 
 
-def _audio_backend_guard(backends):
+def _audio_backend_guard(backends: Union[str, List[str]]) -> Any:
 
     if isinstance(backends, str):
         backends = [backends]
@@ -55,7 +57,7 @@ def wrapper(*args, **kwargs):
     return decorator
 
 
-def check_input(src):
+def check_input(src: Tensor) -> None:
     if not torch.is_tensor(src):
         raise TypeError('Expected a tensor, got %s' % type(src))
     if src.is_cuda:

torchaudio/_soundfile_backend.py

@@ -1,6 +1,8 @@
 import os
+from typing import Any, Optional, Tuple, Union
 
 import torch
+from torch import Tensor
 
 _subtype_to_precision = {
     'PCM_S8': 8,
@@ -12,24 +14,26 @@
 
 
 class SignalInfo:
-    def __init__(self, channels=None, rate=None, precision=None, length=None):
+    def __init__(self,
+                 channels: Optional[int] = None,
+                 rate: Optional[float] = None,
+                 precision: Optional[int] = None,
+                 length: Optional[int] = None) -> None:
         self.channels = channels
         self.rate = rate
         self.precision = precision
         self.length = length
 
 
 class EncodingInfo:
-    def __init__(
-            self,
-            encoding=None,
-            bits_per_sample=None,
-            compression=None,
-            reverse_bytes=None,
-            reverse_nibbles=None,
-            reverse_bits=None,
-            opposite_endian=None
-    ):
+    def __init__(self,
+                 encoding: Any = None,
+                 bits_per_sample: Optional[int] = None,
+                 compression: Optional[float] = None,
+                 reverse_bytes: Any = None,
+                 reverse_nibbles: Any = None,
+                 reverse_bits: Any = None,
+                 opposite_endian: Optional[bool] = None) -> None:
         self.encoding = encoding
         self.bits_per_sample = bits_per_sample
         self.compression = compression
@@ -39,24 +43,22 @@ def __init__(
         self.opposite_endian = opposite_endian
 
 
-def check_input(src):
+def check_input(src: Tensor) -> None:
     if not torch.is_tensor(src):
         raise TypeError("Expected a tensor, got %s" % type(src))
     if src.is_cuda:
         raise TypeError("Expected a CPU based tensor, got %s" % type(src))
 
 
-def load(
-    filepath,
-    out=None,
-    normalization=True,
-    channels_first=True,
-    num_frames=0,
-    offset=0,
-    signalinfo=None,
-    encodinginfo=None,
-    filetype=None,
-):
+def load(filepath: str,
+         out: Optional[Tensor] = None,
+         normalization: Optional[bool] = True,
+         channels_first: Optional[bool] = True,
+         num_frames: int = 0,
+         offset: int = 0,
+         signalinfo: SignalInfo = None,
+         encodinginfo: EncodingInfo = None,
+         filetype: Optional[str] = None) -> Tuple[Tensor, int]:
     r"""See torchaudio.load"""
 
     assert out is None
@@ -96,7 +98,7 @@ def load(
     return out, sample_rate
 
 
-def save(filepath, src, sample_rate, precision=16, channels_first=True):
+def save(filepath: str, src: Tensor, sample_rate: int, precision: int = 16, channels_first: bool = True) -> None:
     r"""See torchaudio.save"""
 
     ch_idx, len_idx = (0, 1) if channels_first else (1, 0)
@@ -129,7 +131,7 @@ def save(filepath, src, sample_rate, precision=16, channels_first=True):
     return soundfile.write(filepath, src, sample_rate, precision)
 
 
-def info(filepath):
+def info(filepath: str) -> Tuple[SignalInfo, EncodingInfo]:
     r"""See torchaudio.info"""
 
     import soundfile

torchaudio/_sox_backend.py

@@ -1,21 +1,21 @@
 import os.path
+from typing import Any, Optional, Tuple, Union
 
 import torch
-
+from torch import Tensor
 import torchaudio
-
-
-def load(
-    filepath,
-    out=None,
-    normalization=True,
-    channels_first=True,
-    num_frames=0,
-    offset=0,
-    signalinfo=None,
-    encodinginfo=None,
-    filetype=None,
-):
+from torchaudio._soundfile_backend import SignalInfo, EncodingInfo
+
+
+def load(filepath: str,
+         out: Optional[Tensor] = None,
+         normalization: Optional[bool] = True,
+         channels_first: Optional[bool] = True,
+         num_frames: int = 0,
+         offset: int = 0,
+         signalinfo: SignalInfo = None,
+         encodinginfo: EncodingInfo = None,
+         filetype: Optional[str] = None) -> Tuple[Tensor, int]:
     r"""See torchaudio.load"""
 
     # stringify if `pathlib.Path` (noop if already `str`)
@@ -53,7 +53,7 @@ def load(
     return out, sample_rate
 
 
-def save(filepath, src, sample_rate, precision=16, channels_first=True):
+def save(filepath: str, src: Tensor, sample_rate: int, precision: int = 16, channels_first: bool = True) -> None:
     r"""See torchaudio.save"""
 
     si = torchaudio.sox_signalinfo_t()
@@ -65,7 +65,7 @@ def save(filepath, src, sample_rate, precision=16, channels_first=True):
     return torchaudio.save_encinfo(filepath, src, channels_first, si)
 
 
-def info(filepath):
+def info(filepath: str) -> Tuple[SignalInfo, EncodingInfo]:
     r"""See torchaudio.info"""
 
     import _torch_sox