Pytorch equivalent to tf.signal.frame?

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

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

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