chore: import upstream snapshot with attribution

python/paddle/audio/backends/wave_backend.py

@@ -0,0 +1,236 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import wave
+from typing import TYPE_CHECKING, BinaryIO
+
+import numpy as np
+
+import paddle
+
+from .backend import AudioInfo
+
+if TYPE_CHECKING:
+    from pathlib import Path
+
+    from paddle import Tensor
+
+
+def _error_message():
+    package = "paddleaudio"
+    warn_msg = (
+        "only PCM16 WAV supported. \n"
+        "if want support more other audio types, please "
+        f"manually installed (usually with `pip install {package}`). \n "
+        "and use paddle.audio.backends.set_backend('soundfile') to set audio backend"
+    )
+    return warn_msg
+
+
+def info(filepath: str | BinaryIO) -> AudioInfo:
+    """Get signal information of input audio file.
+
+    Args:
+        filepath: audio path or file object.
+
+    Returns:
+        AudioInfo: info of the given audio.
+
+    Example:
+        .. code-block:: pycon
+
+            >>> import os
+            >>> import paddle
+
+            >>> sample_rate = 16000
+            >>> wav_duration = 0.5
+            >>> num_channels = 1
+            >>> num_frames = sample_rate * wav_duration
+            >>> wav_data = paddle.linspace(-1.0, 1.0, int(num_frames)) * 0.1
+            >>> waveform = wav_data.tile([num_channels, 1])
+            >>> base_dir = os.getcwd()
+            >>> filepath = os.path.join(base_dir, "test.wav")
+
+            >>> paddle.audio.save(filepath, waveform, sample_rate)
+            >>> wav_info = paddle.audio.info(filepath)
+    """
+
+    if hasattr(filepath, 'read'):
+        file_obj = filepath
+    else:
+        file_obj = open(filepath, 'rb')
+
+    try:
+        file_ = wave.open(file_obj)
+    except wave.Error:
+        file_obj.seek(0)
+        file_obj.close()
+        err_msg = _error_message()
+        raise NotImplementedError(err_msg)
+
+    channels = file_.getnchannels()
+    sample_rate = file_.getframerate()
+    sample_frames = file_.getnframes()  # audio frame
+    bits_per_sample = file_.getsampwidth() * 8
+    encoding = "PCM_S"  # default WAV encoding, only support
+    file_obj.close()
+    return AudioInfo(
+        sample_rate, sample_frames, channels, bits_per_sample, encoding
+    )
+
+
+def load(
+    filepath: str | Path,
+    frame_offset: int = 0,
+    num_frames: int = -1,
+    normalize: bool = True,
+    channels_first: bool = True,
+) -> tuple[Tensor, int]:
+    """Load audio data from file. load the audio content start form frame_offset, and get num_frames.
+
+    Args:
+        frame_offset: from 0 to total frames,
+        num_frames: from -1 (means total frames) or number frames which want to read,
+        normalize:
+            if True: return audio which norm to (-1, 1), dtype=float32
+            if False: return audio with raw data, dtype=int16
+
+        channels_first:
+            if True: return audio with shape (channels, time)
+
+    Return:
+        Tuple[paddle.Tensor, int]: (audio_content, sample rate)
+
+    Examples:
+        .. code-block:: pycon
+
+            >>> import os
+            >>> import paddle
+
+            >>> sample_rate = 16000
+            >>> wav_duration = 0.5
+            >>> num_channels = 1
+            >>> num_frames = sample_rate * wav_duration
+            >>> wav_data = paddle.linspace(-1.0, 1.0, int(num_frames)) * 0.1
+            >>> waveform = wav_data.tile([num_channels, 1])
+            >>> base_dir = os.getcwd()
+            >>> filepath = os.path.join(base_dir, "test.wav")
+
+            >>> paddle.audio.save(filepath, waveform, sample_rate)
+            >>> wav_data_read, sr = paddle.audio.load(filepath)
+    """
+    if hasattr(filepath, 'read'):
+        file_obj = filepath
+    else:
+        file_obj = open(filepath, 'rb')
+
+    try:
+        file_ = wave.open(file_obj)
+    except wave.Error:
+        file_obj.seek(0)
+        file_obj.close()
+        err_msg = _error_message()
+        raise NotImplementedError(err_msg)
+
+    channels = file_.getnchannels()
+    sample_rate = file_.getframerate()
+    frames = file_.getnframes()  # audio frame
+
+    audio_content = file_.readframes(frames)
+    file_obj.close()
+
+    # default_subtype = "PCM_16", only support PCM16 WAV
+    audio_as_np16 = np.frombuffer(audio_content, dtype=np.int16)
+    audio_as_np32 = audio_as_np16.astype(np.float32)
+    if normalize:
+        # dtype = "float32"
+        audio_norm = audio_as_np32 / (2**15)
+    else:
+        # dtype = "int16"
+        audio_norm = audio_as_np32
+
+    waveform = np.reshape(audio_norm, (frames, channels))
+    if num_frames != -1:
+        waveform = waveform[frame_offset : frame_offset + num_frames, :]
+    waveform = paddle.to_tensor(waveform)
+    if channels_first:
+        waveform = paddle.transpose(waveform, perm=[1, 0])
+    return waveform, sample_rate
+
+
+def save(
+    filepath: str,
+    src: Tensor,
+    sample_rate: int,
+    channels_first: bool = True,
+    encoding: str | None = None,
+    bits_per_sample: int | None = 16,
+) -> None:
+    """
+    Save audio tensor to file.
+
+    Args:
+        filepath: saved path
+        src: the audio tensor
+        sample_rate: the number of samples of audio per second.
+        channels_first: src channel information
+            if True, means input tensor is (channels, time)
+            if False, means input tensor is (time, channels)
+        encoding: audio encoding format, wave_backend only support PCM16 now.
+        bits_per_sample: bits per sample, wave_backend only support 16 bits now.
+
+    Returns:
+        None
+
+    Examples:
+        .. code-block:: pycon
+
+            >>> import paddle
+
+            >>> sample_rate = 16000
+            >>> wav_duration = 0.5
+            >>> num_channels = 1
+            >>> num_frames = sample_rate * wav_duration
+            >>> wav_data = paddle.linspace(-1.0, 1.0, int(num_frames)) * 0.1
+            >>> waveform = wav_data.tile([num_channels, 1])
+            >>> filepath = "./test.wav"
+
+            >>> paddle.audio.save(filepath, waveform, sample_rate)
+    """
+    assert src.ndim == 2, "Expected 2D tensor"
+
+    audio_numpy = src.numpy()
+
+    # change src shape to (time, channels)
+    if channels_first:
+        audio_numpy = np.transpose(audio_numpy)
+
+    channels = audio_numpy.shape[1]
+
+    # only support PCM16
+    if bits_per_sample not in (None, 16):
+        raise ValueError("Invalid bits_per_sample, only support 16 bit")
+
+    sample_width = int(bits_per_sample / 8)  # 2
+
+    if src.dtype == paddle.float32:
+        audio_numpy = (audio_numpy * (2**15)).astype("<h")
+
+    with wave.open(filepath, 'w') as f:
+        f.setnchannels(channels)
+        f.setsampwidth(sample_width)
+        f.setframerate(sample_rate)
+        f.writeframes(audio_numpy.tobytes())