A BUG

[ODDHOOD]

for _ in train_iterator:
    local_steps = 0  # update step
    tr_loss = 0.0
    epoch_iterator = tqdm(train_dataloader, desc="Iteration", disable=False)
    step = 0  # backward step
    total_log_loss = 0
    model.train()
    for step, batch in enumerate(epoch_iterator):

        batch=batch.to(args.device)
    ------->    loss = model(batch)
        step += 1
        # loss=model(batch)
        total_log_loss += loss.mean().item()
        if args.gradient_accumulation_steps > 1:
            loss = loss / args.gradient_accumulation_steps
        loss.mean().backward()
        tr_loss += loss.mean().item()

 bug-detail:

File "prompt.py", line 9, in main.main() File "/home/jnu/zf/dstc11-track5/prompt/main.py", line 573, in main loss = model(batch) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, kwargs) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 171, in forward outputs = self.parallel_apply(replicas, inputs, kwargs) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 181, in parallel_apply return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)]) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/parallel/parallel_apply.py", line 89, in parallel_apply output.reraise() File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/_utils.py", line 644, in reraise raise exception TypeError: Caught TypeError in replica 0 on device 0. Original Traceback (most recent call last): File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/parallel/parallel_apply.py", line 64, in _worker output = module(*input, *kwargs) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(args, kwargs) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/openprompt/pipeline_base.py", line 449, in forward return self._forward(*args, kwargs) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/openprompt/pipeline_base.py", line 465, in _forward outputs = self.prompt_model(batch) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/openprompt/pipeline_base.py", line 210, in forward batch = self.template.process_batch(batch) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/openprompt/prompts/soft_template.py", line 94, in process_batch inputs_embeds = self.raw_embedding(batch['input_ids']) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(args, kwargs) File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/modules/sparse.py", line 162, in forward return F.embedding( File "/home/jnu/anaconda3/envs/zf/lib/python3.8/site-packages/torch/nn/functional.py", line 2210, in embedding return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse) TypeError: embedding(): argument 'indices' (position 2) must be Tensor, not tuple

how to solve it thanks