| 224 | return obj.tensors[index] |
| 225 | |
| 226 | def to_numpy(self, obj, edgeitems=None): |
| 227 | cpu_obj = self.to_cpu(obj) |
| 228 | length = cpu_obj.batch_size |
| 229 | |
| 230 | if length == 0: |
| 231 | return [] |
| 232 | |
| 233 | # Determine which samples to convert |
| 234 | if edgeitems is not None and length > 2 * edgeitems + 1: |
| 235 | indices = list(range(edgeitems)) + list(range(length - edgeitems, length)) |
| 236 | else: |
| 237 | indices = range(length) |
| 238 | |
| 239 | return [np.array(cpu_obj.tensors[i]) for i in indices] |
| 240 | |
| 241 | |
| 242 | def format_tensor(obj, show_data: bool = True, adapter: Optional[TensorAdapter] = None) -> str: |