(optimizer, num_training_steps, num_labels, batch_size)
| 248 | return LambdaLR(optimizer, _lr_lambda, last_epoch) |
| 249 | |
| 250 | def get_imagenet_schedule(optimizer, num_training_steps, num_labels, batch_size): |
| 251 | def iter2epoch(iter): |
| 252 | iter_per_ep = num_labels // batch_size |
| 253 | ep = iter // iter_per_ep |
| 254 | return ep |
| 255 | def epoch2iter(epoch): |
| 256 | iter_per_ep = num_labels // batch_size |
| 257 | iter = epoch * iter_per_ep |
| 258 | return iter |
| 259 | def _lr_lambda(iter): |
| 260 | return None |
| 261 | |
| 262 | |
| 263 | def accuracy(output, target, topk=(1,)): |
nothing calls this directly
no outgoing calls
no test coverage detected