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103 lines
3.4 KiB
103 lines
3.4 KiB
2 years ago
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from typing import Optional
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import paddle
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import scipy.io.wavfile
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def normalize_wav(tensor: paddle.Tensor) -> paddle.Tensor:
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if tensor.dtype == paddle.float32:
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pass
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elif tensor.dtype == paddle.int32:
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tensor = paddle.cast(tensor, paddle.float32)
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tensor[tensor > 0] /= 2147483647.0
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tensor[tensor < 0] /= 2147483648.0
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elif tensor.dtype == paddle.int16:
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tensor = paddle.cast(tensor, paddle.float32)
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tensor[tensor > 0] /= 32767.0
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tensor[tensor < 0] /= 32768.0
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elif tensor.dtype == paddle.uint8:
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tensor = paddle.cast(tensor, paddle.float32) - 128
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tensor[tensor > 0] /= 127.0
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tensor[tensor < 0] /= 128.0
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return tensor
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def get_wav_data(
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dtype: str,
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num_channels: int,
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*,
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num_frames: Optional[int]=None,
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normalize: bool=True,
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channels_first: bool=True, ):
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"""Generate linear signal of the given dtype and num_channels
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Data range is
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[-1.0, 1.0] for float32,
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[-2147483648, 2147483647] for int32
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[-32768, 32767] for int16
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[0, 255] for uint8
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num_frames allow to change the linear interpolation parameter.
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Default values are 256 for uint8, else 1 << 16.
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1 << 16 as default is so that int16 value range is completely covered.
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"""
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dtype_ = getattr(paddle, dtype)
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if num_frames is None:
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if dtype == "uint8":
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num_frames = 256
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else:
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num_frames = 1 << 16
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# paddle linspace not support uint8, int8, int16
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#if dtype == "uint8":
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# base = paddle.linspace(0, 255, num_frames, dtype=dtype_)
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#dtype_np = getattr(np, dtype)
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#base_np = np.linspace(0, 255, num_frames, dtype_np)
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#base = paddle.to_tensor(base_np, dtype=dtype_)
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#elif dtype == "int8":
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# base = paddle.linspace(-128, 127, num_frames, dtype=dtype_)
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#dtype_np = getattr(np, dtype)
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#base_np = np.linspace(-128, 127, num_frames, dtype_np)
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#base = paddle.to_tensor(base_np, dtype=dtype_)
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if dtype == "float32":
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base = paddle.linspace(-1.0, 1.0, num_frames, dtype=dtype_)
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elif dtype == "float64":
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base = paddle.linspace(-1.0, 1.0, num_frames, dtype=dtype_)
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elif dtype == "int32":
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base = paddle.linspace(
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-2147483648, 2147483647, num_frames, dtype=dtype_)
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#elif dtype == "int16":
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# base = paddle.linspace(-32768, 32767, num_frames, dtype=dtype_)
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#dtype_np = getattr(np, dtype)
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#base_np = np.linspace(-32768, 32767, num_frames, dtype_np)
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#base = paddle.to_tensor(base_np, dtype=dtype_)
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else:
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raise NotImplementedError(f"Unsupported dtype {dtype}")
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data = base.tile([num_channels, 1])
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if not channels_first:
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data = data.transpose([1, 0])
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if normalize:
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data = normalize_wav(data)
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return data
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def load_wav(path: str, normalize=True, channels_first=True) -> paddle.Tensor:
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"""Load wav file without paddleaudio"""
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sample_rate, data = scipy.io.wavfile.read(path)
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data = paddle.to_tensor(data.copy())
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if data.ndim == 1:
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data = data.unsqueeze(1)
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if normalize:
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data = normalize_wav(data)
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if channels_first:
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data = data.transpose([1, 0])
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return data, sample_rate
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def save_wav(path, data, sample_rate, channels_first=True):
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"""Save wav file without paddleaudio"""
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if channels_first:
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data = data.transpose([1, 0])
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scipy.io.wavfile.write(path, sample_rate, data.numpy())
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