| 20 | |
| 21 | |
| 22 | class CL_Base_Model: |
| 23 | def __init__(self, |
| 24 | model, |
| 25 | tokenizer, |
| 26 | optimizer, |
| 27 | train_task_list, |
| 28 | eval_task_list, |
| 29 | test_task_list, |
| 30 | args): |
| 31 | self.model = model |
| 32 | self.tokenizer = tokenizer |
| 33 | self.optimizer = optimizer |
| 34 | self.train_task_list = train_task_list |
| 35 | self.eval_task_list = eval_task_list |
| 36 | self.test_task_list = test_task_list |
| 37 | self.args = args |
| 38 | |
| 39 | |
| 40 | def perplexity_evaluation(self, eval_dataloader, device): |
| 41 | self.model.eval() |
| 42 | losses = 0 |
| 43 | for step, batch in enumerate(eval_dataloader): |
| 44 | # implementation, batch = {k: v.to(device) for k, v in batch.items()} |
| 45 | del batch['sources'] |
| 46 | batch = to_device(batch, device) |
| 47 | with torch.no_grad(): |
| 48 | outputs = self.model(**batch, use_cache=False) |
| 49 | loss = outputs.loss |
| 50 | losses += loss.float() |
| 51 | losses = losses / (step + 1) |
| 52 | try: |
| 53 | perplexity = torch.exp(losses) |
| 54 | except OverflowError: |
| 55 | perplexity = float("inf") |
| 56 | try: |
| 57 | perplexity = get_all_reduce_mean(perplexity).item() |
| 58 | except: |
| 59 | pass |
| 60 | return perplexity |
| 61 | |
| 62 | |
| 63 | def train_one_task(self, task, i_task, epochs): |
| 64 | if self.args.local_rank == -1: |
| 65 | device = torch.device("cuda") |
| 66 | else: |
| 67 | torch.cuda.set_device(self.args.local_rank) |
| 68 | device = torch.device("cuda", self.args.local_rank) |
| 69 | |
| 70 | #### TRAIN #### |
| 71 | train_dataloader = self.train_task_list[task] |
| 72 | eval_dataloader = self.eval_task_list[task] |
| 73 | total_steps = epochs * len(train_dataloader) |
| 74 | progress_bar = tqdm(total=total_steps, leave=True, disable=(self.args.global_rank != 0)) |
| 75 | for epoch in range(epochs): |
| 76 | print_rank_0( |
| 77 | f"Beginning of Epoch {epoch+1}/{epochs}, Total Micro Batches {len(train_dataloader)}", |
| 78 | self.args.global_rank) |
| 79 | self.model.train() |
nothing calls this directly
no outgoing calls
no test coverage detected