Pytorch equivalent to tf.signal.frame?

audio
1

Does Pytorch have an equivalent implementation to Tensorflow’s tf.signal.frame  |  TensorFlow Core v2.5.0 ? I’ve been searching everywhere and cannot seem to find anything, even in torchaudio. I know that librosa has an equivalent function, but it requires that the inputs be converted to numpy arrays first

2

Based on the description I guess that tensor.unfold would perform the same operation (with an additional F.pad before if needed).

3

You are correct, thank you! For completeness, this method appears to produce the same results as tf.signal.frame (albeit not tested extensively)

def frame(signal, frame_length, frame_step, pad_end=False, pad_value=0, axis=-1):
    """
    equivalent of tf.signal.frame
    """
    signal_length = signal.shape[axis]
    if pad_end:
        frames_overlap = frame_length - frame_step
        rest_samples = np.abs(signal_length - frames_overlap) % np.abs(frame_length - frames_overlap)
        pad_size = int(frame_length - rest_samples)
        if pad_size != 0:
            pad_axis = [0] * signal.ndim
            pad_axis[axis] = pad_size
            signal = F.pad(signal, pad_axis, "constant", pad_value)
    frames=signal.unfold(axis, frame_length, frame_step)
    return frames

Reference:
https://superkogito.github.io/blog/SignalFraming.html

1 Like
4

This one may be correct.

def frame(signal, frame_length, frame_step, pad_end=False, pad_value=0, axis=-1):
    """
    equivalent of tf.signal.frame
    """
    pad_size = 0
    signal_length = signal.shape[axis]
    if pad_end:
        frames_overlap = frame_length - frame_step
        rest_samples = np.abs(signal_length - frames_overlap) % np.abs(frame_step)
        if rest_samples != 0:
            pad_size = int(frame_length - rest_samples)
            pad_axis = [0] * signal.ndim
            pad_axis[axis] = pad_size
            signal = F.pad(signal, pad_axis, "constant", pad_value)
    frames=signal.unfold(axis, frame_length, frame_step)
    return frames