Support file-like object in save func (#1141)

* Support file-like object in save func

* Disable CircleCI cache for TP artifacts for cleaner build

Author: mthrok

.circleci/config.yml

@@ -411,7 +411,6 @@ jobs:
           paths:
             - conda
             - env
-            - third_party/install
       - run:
           name: Install torchaudio
           command: .circleci/unittest/linux/scripts/install.sh
@@ -456,7 +455,6 @@ jobs:
           paths:
             - conda
             - env
-            - third_party/install
       - run:
           name: Install torchaudio
           command: docker run -t --gpus all -e UPLOAD_CHANNEL -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/install.sh
@@ -569,7 +567,6 @@ jobs:
           paths:
             - conda
             - env
-            - third_party/install
       - run:
           name: Install torchaudio
           command: .circleci/unittest/linux/scripts/install.sh
@@ -606,7 +603,6 @@ jobs:
           paths:
             - conda
             - env
-            - third_party/install
       - run:
           name: Run style check
           command: .circleci/unittest/linux/scripts/run_style_checks.sh

.circleci/config.yml.in

@@ -411,7 +411,6 @@ jobs:
           paths:
             - conda
             - env
-            - third_party/install
       - run:
           name: Install torchaudio
           command: .circleci/unittest/linux/scripts/install.sh
@@ -456,7 +455,6 @@ jobs:
           paths:
             - conda
             - env
-            - third_party/install
       - run:
           name: Install torchaudio
           command: docker run -t --gpus all -e UPLOAD_CHANNEL -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/install.sh
@@ -569,7 +567,6 @@ jobs:
           paths:
             - conda
             - env
-            - third_party/install
       - run:
           name: Install torchaudio
           command: .circleci/unittest/linux/scripts/install.sh
@@ -606,7 +603,6 @@ jobs:
           paths:
             - conda
             - env
-            - third_party/install
       - run:
           name: Run style check
           command: .circleci/unittest/linux/scripts/run_style_checks.sh

test/torchaudio_unittest/soundfile_backend/save_test.py

@@ -1,9 +1,9 @@
+import io
 import itertools
 from unittest.mock import patch
 
 from torchaudio._internal import module_utils as _mod_utils
 from torchaudio.backend import _soundfile_backend as soundfile_backend
-from parameterized import parameterized
 
 from torchaudio_unittest.common_utils import (
     TempDirMixin,
@@ -209,3 +209,43 @@ def test_channels_first(self, channels_first):
         found = load_wav(path)[0]
         expected = data if channels_first else data.transpose(1, 0)
         self.assertEqual(found, expected, atol=1e-4, rtol=1e-8)
+
+
+@skipIfNoModule("soundfile")
+class TestFileObject(TempDirMixin, PytorchTestCase):
+    def _test_fileobj(self, ext):
+        """Saving audio to file-like object works"""
+        sample_rate = 16000
+        path = self.get_temp_path(f'test.{ext}')
+
+        subtype = 'FLOAT' if ext == 'wav' else None
+        data = get_wav_data('float32', num_channels=2)
+        soundfile.write(path, data.numpy().T, sample_rate, subtype=subtype)
+        expected = soundfile.read(path, dtype='float32')[0]
+
+        fileobj = io.BytesIO()
+        soundfile_backend.save(fileobj, data, sample_rate, format=ext)
+        fileobj.seek(0)
+        found, sr = soundfile.read(fileobj, dtype='float32')
+
+        assert sr == sample_rate
+        self.assertEqual(expected, found)
+
+    def test_fileobj_wav(self):
+        """Saving audio via file-like object works"""
+        self._test_fileobj('wav')
+
+    @skipIfFormatNotSupported("FLAC")
+    def test_fileobj_flac(self):
+        """Saving audio via file-like object works"""
+        self._test_fileobj('flac')
+
+    @skipIfFormatNotSupported("NIST")
+    def test_fileobj_nist(self):
+        """Saving audio via file-like object works"""
+        self._test_fileobj('NIST')
+
+    @skipIfFormatNotSupported("OGG")
+    def test_fileobj_ogg(self):
+        """Saving audio via file-like object works"""
+        self._test_fileobj('OGG')

test/torchaudio_unittest/sox_io_backend/save_test.py

@@ -1,3 +1,4 @@
+import io
 import itertools
 
 from torchaudio.backend import sox_io_backend
@@ -417,3 +418,88 @@ def test_tensor_preserve(self, dtype):
         sox_io_backend.save(path, data, 8000)
 
         self.assertEqual(data, expected)
+
+
+@skipIfNoExtension
+@skipIfNoExec('sox')
+class TestFileObject(SaveTestBase):
+    """
+    We campare the result of file-like object input against file path input because
+    `save` function is rigrously tested for file path inputs to match libsox's result,
+    """
+    @parameterized.expand([
+        ('wav', None),
+        ('mp3', 128),
+        ('mp3', 320),
+        ('flac', 0),
+        ('flac', 5),
+        ('flac', 8),
+        ('vorbis', -1),
+        ('vorbis', 10),
+        ('amb', None),
+    ])
+    def test_fileobj(self, ext, compression):
+        """Saving audio to file object returns the same result as via file path."""
+        sample_rate = 16000
+        dtype = 'float32'
+        num_channels = 2
+        num_frames = 16000
+        channels_first = True
+
+        data = get_wav_data(dtype, num_channels, num_frames=num_frames)
+
+        ref_path = self.get_temp_path(f'reference.{ext}')
+        res_path = self.get_temp_path(f'test.{ext}')
+        sox_io_backend.save(
+            ref_path, data, channels_first=channels_first,
+            sample_rate=sample_rate, compression=compression)
+        with open(res_path, 'wb') as fileobj:
+            sox_io_backend.save(
+                fileobj, data, channels_first=channels_first,
+                sample_rate=sample_rate, compression=compression, format=ext)
+
+        expected_data, _ = sox_io_backend.load(ref_path)
+        data, sr = sox_io_backend.load(res_path)
+
+        assert sample_rate == sr
+        self.assertEqual(expected_data, data)
+
+    @parameterized.expand([
+        ('wav', None),
+        ('mp3', 128),
+        ('mp3', 320),
+        ('flac', 0),
+        ('flac', 5),
+        ('flac', 8),
+        ('vorbis', -1),
+        ('vorbis', 10),
+        ('amb', None),
+    ])
+    def test_bytesio(self, ext, compression):
+        """Saving audio to BytesIO object returns the same result as via file path."""
+        sample_rate = 16000
+        dtype = 'float32'
+        num_channels = 2
+        num_frames = 16000
+        channels_first = True
+
+        data = get_wav_data(dtype, num_channels, num_frames=num_frames)
+
+        ref_path = self.get_temp_path(f'reference.{ext}')
+        res_path = self.get_temp_path(f'test.{ext}')
+        sox_io_backend.save(
+            ref_path, data, channels_first=channels_first,
+            sample_rate=sample_rate, compression=compression)
+        fileobj = io.BytesIO()
+        sox_io_backend.save(
+            fileobj, data, channels_first=channels_first,
+            sample_rate=sample_rate, compression=compression, format=ext)
+        fileobj.seek(0)
+        with open(res_path, 'wb') as file_:
+            file_.write(fileobj.read())
+
+        expected_data, _ = sox_io_backend.load(ref_path)
+        data, sr = sox_io_backend.load(res_path)
+
+        assert sample_rate == sr
+        self.assertEqual(expected_data, data)

torchaudio/backend/_soundfile_backend.py

@@ -138,6 +138,7 @@ def save(
     sample_rate: int,
     channels_first: bool = True,
     compression: Optional[float] = None,
+    format: Optional[str] = None,
 ):
     """Save audio data to file.
 
@@ -168,6 +169,9 @@ def save(
             otherwise ``[time, channel]``.
         compression (Optional[float]):
             Not used. It is here only for interface compatibility reson with "sox_io" backend.
+        format (str, optional):
+            Output audio format. This is required when the output audio format cannot be infered from
+            ``filepath``, (such as file extension or ``name`` attribute of the given file object).
     """
     if src.ndim != 2:
         raise ValueError(f"Expected 2D Tensor, got {src.ndim}D.")
@@ -176,8 +180,13 @@ def save(
             '`save` function of "soundfile" backend does not support "compression" parameter. '
             "The argument is silently ignored."
         )
+    if hasattr(filepath, 'write'):
+        if format is None:
+            raise RuntimeError('`format` is required when saving to file object.')
+        ext = format
+    else:
+        ext = str(filepath).split(".")[-1].lower()
 
-    ext = str(filepath).split(".")[-1].lower()
     if ext != "wav":
         subtype = None
     elif src.dtype == torch.uint8:
@@ -193,17 +202,16 @@ def save(
     else:
         raise ValueError(f"Unsupported dtype for WAV: {src.dtype}")
 
-    format_ = None
     # sph is a extension used in TED-LIUM but soundfile does not recognize it as NIST format,
     # so we extend the extensions manually here
-    if ext in ["nis", "nist", "sph"]:
-        format_ = "NIST"
+    if ext in ["nis", "nist", "sph"] and format is None:
+        format = "NIST"
 
     if channels_first:
         src = src.t()
 
     soundfile.write(
-        file=filepath, data=src, samplerate=sample_rate, subtype=subtype, format=format_
+        file=filepath, data=src, samplerate=sample_rate, subtype=subtype, format=format
     )
 
 

torchaudio/backend/sox_io_backend.py

@@ -134,13 +134,33 @@ def load(
     return signal.get_tensor(), signal.get_sample_rate()
 
 
+@torch.jit.unused
+def _save(
+        filepath: str,
+        src: torch.Tensor,
+        sample_rate: int,
+        channels_first: bool = True,
+        compression: Optional[float] = None,
+        format: Optional[str] = None,
+):
+    if hasattr(filepath, 'write'):
+        if format is None:
+            raise RuntimeError('`format` is required when saving to file object.')
+        torchaudio._torchaudio.save_audio_fileobj(
+            filepath, src, sample_rate, channels_first, compression, format)
+    else:
+        torch.ops.torchaudio.sox_io_save_audio_file(
+            os.fspath(filepath), src, sample_rate, channels_first, compression, format)
+
+
 @_mod_utils.requires_module('torchaudio._torchaudio')
 def save(
         filepath: str,
         src: torch.Tensor,
         sample_rate: int,
         channels_first: bool = True,
         compression: Optional[float] = None,
+        format: Optional[str] = None,
 ):
     """Save audio data to file.
 
@@ -184,23 +204,15 @@ def save(
                   | and lowest quality. Default: ``3``.
 
             See the detail at http://sox.sourceforge.net/soxformat.html.
+        format (str, optional):
+            Output audio format. This is required when the output audio format cannot be infered from
+            ``filepath``, (such as file extension or ``name`` attribute of the given file object).
     """
-    # Cast to str in case type is `pathlib.Path`
-    filepath = str(filepath)
-    if compression is None:
-        ext = str(filepath).split('.')[-1].lower()
-        if ext in ['wav', 'sph', 'amb', 'amr-nb']:
-            compression = 0.
-        elif ext == 'mp3':
-            compression = -4.5
-        elif ext == 'flac':
-            compression = 8.
-        elif ext in ['ogg', 'vorbis']:
-            compression = 3.
-        else:
-            raise RuntimeError(f'Unsupported file type: "{ext}"')
-    signal = torch.classes.torchaudio.TensorSignal(src, sample_rate, channels_first)
-    torch.ops.torchaudio.sox_io_save_audio_file(filepath, signal, compression)
+    if not torch.jit.is_scripting():
+        _save(filepath, src, sample_rate, channels_first, compression, format)
+        return
+    torch.ops.torchaudio.sox_io_save_audio_file(
+        filepath, src, sample_rate, channels_first, compression, format)
 
 
 @_mod_utils.requires_module('torchaudio._torchaudio')

torchaudio/csrc/pybind.cpp

@@ -100,4 +100,8 @@ PYBIND11_MODULE(_torchaudio, m) {
       "load_audio_fileobj",
       &torchaudio::sox_io::load_audio_fileobj,
       "Load audio from file object.");
+  m.def(
+      "save_audio_fileobj",
+      &torchaudio::sox_io::save_audio_fileobj,
+      "Save audio to file obj.");
 }

torchaudio/csrc/sox/effects.cpp

@@ -59,8 +59,8 @@ c10::intrusive_ptr<TensorSignal> apply_effects_tensor(
   // Create SoxEffectsChain
   const auto dtype = in_tensor.dtype();
   torchaudio::sox_effects_chain::SoxEffectsChain chain(
-      /*input_encoding=*/get_encodinginfo("wav", dtype, 0.),
-      /*output_encoding=*/get_encodinginfo("wav", dtype, 0.));
+      /*input_encoding=*/get_encodinginfo("wav", dtype),
+      /*output_encoding=*/get_encodinginfo("wav", dtype));
 
   // Prepare output buffer
   std::vector<sox_sample_t> out_buffer;
@@ -112,7 +112,7 @@ c10::intrusive_ptr<TensorSignal> apply_effects_file(
   // Create and run SoxEffectsChain
   torchaudio::sox_effects_chain::SoxEffectsChain chain(
       /*input_encoding=*/sf->encoding,
-      /*output_encoding=*/get_encodinginfo("wav", dtype, 0.));
+      /*output_encoding=*/get_encodinginfo("wav", dtype));
 
   chain.addInputFile(sf);
   for (const auto& effect : effects) {
@@ -193,7 +193,7 @@ std::tuple<torch::Tensor, int64_t> apply_effects_fileobj(
   const auto dtype = get_dtype(sf->encoding.encoding, sf->signal.precision);
   torchaudio::sox_effects_chain::SoxEffectsChain chain(
       /*input_encoding=*/sf->encoding,
-      /*output_encoding=*/get_encodinginfo("wav", dtype, 0.));
+      /*output_encoding=*/get_encodinginfo("wav", dtype));
   chain.addInputFileObj(sf, in_buf, in_buffer_size, &fileobj);
   for (const auto& effect : effects) {
     chain.addEffect(effect);