(self, *size, type_as=None)
| 2245 | return torch.rand(size=size, generator=self.rng_) |
| 2246 | |
| 2247 | def randn(self, *size, type_as=None): |
| 2248 | if type_as is not None: |
| 2249 | generator = ( |
| 2250 | self.rng_cuda_ if self.device_type(type_as) == "GPU" else self.rng_ |
| 2251 | ) |
| 2252 | return torch.randn( |
| 2253 | size=size, |
| 2254 | dtype=type_as.dtype, |
| 2255 | generator=generator, |
| 2256 | device=type_as.device, |
| 2257 | ) |
| 2258 | else: |
| 2259 | return torch.randn(size=size, generator=self.rng_) |
| 2260 | |
| 2261 | def randperm(self, size, type_as=None): |
| 2262 | if not isinstance(size, int): |
nothing calls this directly
no test coverage detected