    def __init__(self, channels: int, init: float = 0, channel_last=False):
        """
        channel_last = False corresponds to (B, C, T) tensors
        channel_last = True corresponds to (T, B, C) tensors
        """
        super().__init__()
        self.channel_last = channel_last
        self.scale = nn.Parameter(torch.zeros(channels, requires_grad=True))
        self.scale.data[:] = init
channel_last = False corresponds to (B, C, T) tensors
channel_last = True corresponds to (T, B, C) tensors
demucs/transformer.py