import torch

def get_tensor(x):
    if isinstance(x, torch.Tensor):
        return x
    if hasattr(x, 'parameters') and len(list(x.parameters())) > 0:
        return list(x.parameters())[0]
    if callable(x):
        try:
            out = x()
            if isinstance(out, torch.Tensor):
                return out
        except Exception:
            pass
    raise RuntimeError('Could not extract tensor')

a = torch.load('test/output/resnet/sample_0_image_preprocessed_python.pt')
b = torch.load('test/output/resnet/sample_0_image_preprocessed_cpp.pt')
a = get_tensor(a)
b = get_tensor(b)
print('py:', a.shape, a.dtype, a.min().item(), a.max().item(), a.mean().item())
print('cpp:', b.shape, b.dtype, b.min().item(), b.max().item(), b.mean().item())
print('diff:', (a-b).abs().max().item(), (a-b).abs().mean().item())