(model, model_engine, eval_dataloaders, tb_writer, step, eval_gradient_accumulation_steps, disable_block_swap)
| 228 | |
| 229 | |
| 230 | def evaluate(model, model_engine, eval_dataloaders, tb_writer, step, eval_gradient_accumulation_steps, disable_block_swap): |
| 231 | if len(eval_dataloaders) == 0: |
| 232 | return |
| 233 | empty_cuda_cache() |
| 234 | model.prepare_block_swap_inference(disable_block_swap=disable_block_swap) |
| 235 | with torch.no_grad(), isolate_rng(): |
| 236 | seed = get_rank() |
| 237 | random.seed(seed) |
| 238 | torch.manual_seed(seed) |
| 239 | np.random.seed(seed) |
| 240 | _evaluate(model_engine, eval_dataloaders, tb_writer, step, eval_gradient_accumulation_steps) |
| 241 | empty_cuda_cache() |
| 242 | model.prepare_block_swap_training() |
| 243 | |
| 244 | |
| 245 | def distributed_init(args): |
no test coverage detected