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After successfully run the tutorial, I built a small system to test (C10H22). All the pre-steps run without problem (the delta-force preparation and embedding preparation).
When I start to train the network I got the following error. Can anyone take a look at this and give me some suggestions where I made a mistake?
0 | model | TorchMD_Net | 276 K
--------------------------------------
276 K Trainable params
0 Non-trainable params
276 K Total params
1.107 Total estimated model params size (MB)
/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead
warnings.warn(out)
/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/utils/data/dataloader.py:487: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 1, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
warnings.warn(_create_warning_msg(
Traceback (most recent call last):
File "/scratch/user/sli259/torchmd/torchmd-net/scripts/train.py", line 173, in <module>
main()
File "/scratch/user/sli259/torchmd/torchmd-net/scripts/train.py", line 166, in main
trainer.fit(model, data)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 458, in fit
self._run(model)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 756, in _run
self.dispatch()
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 797, in dispatch
self.accelerator.start_training(self)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 96, in start_training
self.training_type_plugin.start_training(trainer)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 144, in start_training
self._results = trainer.run_stage()
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 807, in run_stage
return self.run_train()
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 842, in run_train
self.run_sanity_check(self.lightning_module)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 1107, in run_sanity_check
self.run_evaluation()
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 962, in run_evaluation
output = self.evaluation_loop.evaluation_step(batch, batch_idx, dataloader_idx)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/trainer/evaluation_loop.py", line 174, in evaluation_step
output = self.trainer.accelerator.validation_step(args)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 226, in validation_step
return self.training_type_plugin.validation_step(*args)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/plugins/training_type/ddp.py", line 322, in validation_step
return self.model(*args, **kwargs)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 965, in forward
output = self.module(*inputs, **kwargs)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/pytorch_lightning/overrides/base.py", line 57, in forward
output = self.module.validation_step(*inputs, **kwargs)
File "/scratch/user/sli259/torchmd/torchmd-net/torchmdnet/module.py", line 64, in validation_step
return self.step(batch, mse_loss, "val")
File "/scratch/user/sli259/torchmd/torchmd-net/torchmdnet/module.py", line 75, in step
pred, deriv = self(batch.z, batch.pos, batch=batch.batch,
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/scratch/user/sli259/torchmd/torchmd-net/torchmdnet/module.py", line 56, in forward
return self.model(z, pos, batch=batch, q=q, s=s)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/scratch/user/sli259/torchmd/torchmd-net/torchmdnet/models/model.py", line 170, in forward
x, v, z, pos, batch = self.representation_model(z, pos, batch, q=q, s=s)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/scratch/user/sli259/torchmd/torchmd-net/torchmdnet/models/torchmd_gn.py", line 162, in forward
x = x + interaction(x, edge_index, edge_weight, edge_attr)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/scratch/user/sli259/torchmd/torchmd-net/torchmdnet/models/torchmd_gn.py", line 224, in forward
x = self.conv(x, edge_index, edge_weight, edge_attr)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/tmp/job.3878131/sli259_pyg/tmpf0jhxsc9.py", line 182, in forward
W = self.net(edge_attr) * C.view(-1, 1)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/container.py", line 141, in forward
input = module(input)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/scratch/user/sli259/Anaconda3/2020.07/envs/torchmd/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 103, in forward
return F.linear(input, self.weight, self.bias)
RuntimeError: expected scalar type Float but found Double
The text was updated successfully, but these errors were encountered:
After successfully run the tutorial, I built a small system to test (C10H22). All the pre-steps run without problem (the delta-force preparation and embedding preparation).
When I start to train the network I got the following error. Can anyone take a look at this and give me some suggestions where I made a mistake?
The text was updated successfully, but these errors were encountered: