[1/200][1134/1216] Loss: 0.857
[1/200][1184/1216] Loss: 0.856
Evaluate on refinement
0%| | 0/257 [00:04<?, ?it/s]
Traceback (most recent call last):
File "main.py", line 163, in
train(args)
File "main.py", line 81, in train
trainer(train_fn, evaluate_fn, tasks=train_dataset.tasks,
File "/home/tjzn/LayoutGeneration/LayoutFormer++/src/trainer/multitask_trainer.py", line 160, in call
eval_step_loss, eval_step_pred = eval_step(self.model, data,
File "/home/tjzn/LayoutGeneration/LayoutFormer++/src/tasks/task_utils.py", line 277, in call
prediction = self._measure_prediction(model, in_tokenization, tokenizer,
File "/home/tjzn/LayoutGeneration/LayoutFormer++/src/tasks/task_utils.py", line 199, in _measure_prediction
output_sequences = model(in_ids, in_padding_mask,
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, *kwargs)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 169, in forward
return self.gather(outputs, self.output_device)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 181, in gather
return gather(outputs, output_device, dim=self.dim)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 78, in gather
res = gather_map(outputs)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 69, in gather_map
return type(out)((k, gather_map([d[k] for d in outputs]))
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 69, in
return type(out)((k, gather_map([d[k] for d in outputs]))
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 63, in gather_map
return Gather.apply(target_device, dim, outputs)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/_functions.py", line 75, in forward
return comm.gather(inputs, ctx.dim, ctx.target_device)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/comm.py", line 235, in gather
return torch._C._gather(tensors, dim, destination)
RuntimeError: Input tensor at index 2 has invalid shape [16, 120], but expected [16, 114]
wandb: - 0.008 MB of 0.008 MB uploaded
For training rico dataset, no error occurs. I download pre-processed dataset from Huggingface.
Hello, I met an error of training publaynet datasets when I use the following instruction:
./scripts/publaynet_refinement.sh train ../datasets output_dir basic 1 none
[1/200][1134/1216] Loss: 0.857 [1/200][1184/1216] Loss: 0.856 Evaluate on refinement 0%| | 0/257 [00:04<?, ?it/s] Traceback (most recent call last): File "main.py", line 163, in
train(args)
File "main.py", line 81, in train
trainer(train_fn, evaluate_fn, tasks=train_dataset.tasks,
File "/home/tjzn/LayoutGeneration/LayoutFormer++/src/trainer/multitask_trainer.py", line 160, in call
eval_step_loss, eval_step_pred = eval_step(self.model, data,
File "/home/tjzn/LayoutGeneration/LayoutFormer++/src/tasks/task_utils.py", line 277, in call
prediction = self._measure_prediction(model, in_tokenization, tokenizer,
File "/home/tjzn/LayoutGeneration/LayoutFormer++/src/tasks/task_utils.py", line 199, in _measure_prediction
output_sequences = model(in_ids, in_padding_mask,
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, *kwargs)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 169, in forward
return self.gather(outputs, self.output_device)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 181, in gather
return gather(outputs, output_device, dim=self.dim)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 78, in gather
res = gather_map(outputs)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 69, in gather_map
return type(out)((k, gather_map([d[k] for d in outputs]))
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 69, in
return type(out)((k, gather_map([d[k] for d in outputs]))
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 63, in gather_map
return Gather.apply(target_device, dim, outputs)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/_functions.py", line 75, in forward
return comm.gather(inputs, ctx.dim, ctx.target_device)
File "/home/tjzn/miniconda3/envs/layoutformer/lib/python3.8/site-packages/torch/nn/parallel/comm.py", line 235, in gather
return torch._C._gather(tensors, dim, destination)
RuntimeError: Input tensor at index 2 has invalid shape [16, 120], but expected [16, 114]
wandb: - 0.008 MB of 0.008 MB uploaded
For training rico dataset, no error occurs. I download pre-processed dataset from Huggingface.