(self, tensor: torch.Tensor, is_reference: bool)
| 110 | self.random_fetch = random_fetch |
| 111 | |
| 112 | def push(self, tensor: torch.Tensor, is_reference: bool) -> None: |
| 113 | if self.random_fetch: |
| 114 | tensor = batch_random_fetch(tensor, seed=self.seed, fetches_per_batch=self.fetchs) |
| 115 | if is_reference: self.references.append(tensor) |
| 116 | else: self.outputs.append(tensor) |
| 117 | |
| 118 | def pop(self) -> Tuple[torch.Tensor]: |
| 119 | assert len(self.outputs) == len(self.references), ('Inconsistent samples detected.' |
nothing calls this directly
no test coverage detected