| 2047 | return torch.min(a, axis, keepdim=keepdims)[0] |
| 2048 | |
| 2049 | def maximum(self, a, b): |
| 2050 | if isinstance(a, int) or isinstance(a, float): |
| 2051 | a = torch.tensor([float(a)], dtype=b.dtype, device=b.device) |
| 2052 | if isinstance(b, int) or isinstance(b, float): |
| 2053 | b = torch.tensor([float(b)], dtype=a.dtype, device=a.device) |
| 2054 | if hasattr(torch, "maximum"): |
| 2055 | return torch.maximum(a, b) |
| 2056 | else: |
| 2057 | return torch.max(torch.stack(torch.broadcast_tensors(a, b)), axis=0)[0] |
| 2058 | |
| 2059 | def minimum(self, a, b): |
| 2060 | if isinstance(a, int) or isinstance(a, float): |