02b898fffc3a078438f0aa9f8596001af6d28c47,test/common_utils/data_utils.py,,get_whitenoise,#,16

Before Change

    if dtype == torch.int32:
        tensor *= (tensor > 0) * 2147483647 + (tensor < 0) * 2147483648
    if dtype == torch.int16:
        tensor *= (tensor > 0) * 32767 + (tensor < 0) * 32768
    if dtype == torch.uint8:
        tensor *= (tensor > 0) * 127 + (tensor < 0) * 128
        tensor += 128
    tensor = tensor.to(dtype)
    tensor = tensor.repeat([n_channels, 1])
    if not channels_first:
        tensor = tensor.t()
    return tensor.to(device=device)


def get_sinusoid(
    *,

After Change

    // so we only fork on CPU, generate values and move the data to the given device
    with torch.random.fork_rng([]):
        torch.random.manual_seed(seed)
        tensor = torch.randn([int(sample_rate * duration)], dtype=torch.float32, device="cpu")
    tensor /= 2.0
    tensor *= scale_factor
    tensor.clamp_(-1.0, 1.0)

Instances