I got the error when I tried to fine-tune pre-trained zero123. Have anyone experienced same problem?
Traceback (most recent call last):
File "/home/lambdasix/zero123/zero123/GLI_zero123main.py", line 918, in
trainer.fit(model, data)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 553, in fit
self._run(model)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 918, in _run
self._dispatch()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 986, in _dispatch
self.accelerator.start_training(self)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 92, in start_training
self.training_type_plugin.start_training(trainer)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 161, in start_training
self._results = trainer.run_stage()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 996, in run_stage
return self._run_train()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 1045, in _run_train
self.fit_loop.run()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/base.py", line 111, in run
self.advance(*args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/fit_loop.py", line 200, in advance
epoch_output = self.epoch_loop.run(train_dataloader)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/base.py", line 111, in run
self.advance(*args, *kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 130, in advance
batch_output = self.batch_loop.run(batch, self.iteration_count, self._dataloader_idx)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 101, in run
super().run(batch, batch_idx, dataloader_idx)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/base.py", line 111, in run
self.advance(args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 148, in advance
result = self._run_optimization(batch_idx, split_batch, opt_idx, optimizer)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 202, in _run_optimization
self._optimizer_step(optimizer, opt_idx, batch_idx, closure)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 396, in _optimizer_step
model_ref.optimizer_step(
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/core/lightning.py", line 1618, in optimizer_step
optimizer.step(closure=optimizer_closure)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/core/optimizer.py", line 209, in step
self.optimizer_step(*args, closure=closure, profiler_name=profiler_name, **kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/core/optimizer.py", line 129, in optimizer_step
trainer.accelerator.optimizer_step(optimizer, self._optimizer_idx, lambda_closure=closure, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 296, in optimizer_step
self.run_optimizer_step(optimizer, opt_idx, lambda_closure, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 303, in run_optimizer_step
self.training_type_plugin.optimizer_step(optimizer, lambda_closure=lambda_closure, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 226, in optimizer_step
optimizer.step(closure=lambda_closure, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/optim/lr_scheduler.py", line 65, in wrapper
return wrapped(*args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/optim/optimizer.py", line 113, in wrapper
return func(*args, *kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/optim/adamw.py", line 119, in step
loss = closure()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 236, in _training_step_and_backward_closure
result = self.training_step_and_backward(split_batch, batch_idx, opt_idx, optimizer, hiddens)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 537, in training_step_and_backward
result = self._training_step(split_batch, batch_idx, opt_idx, hiddens)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 307, in _training_step
training_step_output = self.trainer.accelerator.training_step(step_kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 193, in training_step
return self.training_type_plugin.training_step(step_kwargs.values())
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/plugins/training_type/ddp.py", line 383, in training_step
return self.model(args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, *kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 1008, in forward
output = self._run_ddp_forward(inputs, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 969, in _run_ddp_forward
return module_to_run(*inputs[0], kwargs[0])
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, *kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/overrides/base.py", line 82, in forward
output = self.module.training_step(inputs, kwargs)
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 403, in training_step
loss, loss_dict = self.shared_step(batch)
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 866, in shared_step
loss = self(x, c, T)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, kwargs)
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 880, in forward
return self.p_losses(x, c, T, t, args, kwargs)
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 1011, in p_losses
model_output = self.apply_model(x_noisy, t, cond, T, x_start) #x_start added
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 983, in apply_model
x_recon = self.model(x_noisy, t, T, x, cond)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(input, kwargs)
TypeError: forward() got multiple values for argument 'c_crossattn'
I got the error when I tried to fine-tune pre-trained zero123. Have anyone experienced same problem?
Traceback (most recent call last): File "/home/lambdasix/zero123/zero123/GLI_zero123main.py", line 918, in
trainer.fit(model, data)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 553, in fit
self._run(model)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 918, in _run
self._dispatch()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 986, in _dispatch
self.accelerator.start_training(self)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 92, in start_training
self.training_type_plugin.start_training(trainer)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 161, in start_training
self._results = trainer.run_stage()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 996, in run_stage
return self._run_train()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 1045, in _run_train
self.fit_loop.run()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/base.py", line 111, in run
self.advance(*args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/fit_loop.py", line 200, in advance
epoch_output = self.epoch_loop.run(train_dataloader)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/base.py", line 111, in run
self.advance(*args, *kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 130, in advance
batch_output = self.batch_loop.run(batch, self.iteration_count, self._dataloader_idx)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 101, in run
super().run(batch, batch_idx, dataloader_idx)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/base.py", line 111, in run
self.advance(args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 148, in advance
result = self._run_optimization(batch_idx, split_batch, opt_idx, optimizer)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 202, in _run_optimization
self._optimizer_step(optimizer, opt_idx, batch_idx, closure)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 396, in _optimizer_step
model_ref.optimizer_step(
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/core/lightning.py", line 1618, in optimizer_step
optimizer.step(closure=optimizer_closure)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/core/optimizer.py", line 209, in step
self.optimizer_step(*args, closure=closure, profiler_name=profiler_name, **kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/core/optimizer.py", line 129, in optimizer_step
trainer.accelerator.optimizer_step(optimizer, self._optimizer_idx, lambda_closure=closure, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 296, in optimizer_step
self.run_optimizer_step(optimizer, opt_idx, lambda_closure, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 303, in run_optimizer_step
self.training_type_plugin.optimizer_step(optimizer, lambda_closure=lambda_closure, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 226, in optimizer_step
optimizer.step(closure=lambda_closure, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/optim/lr_scheduler.py", line 65, in wrapper
return wrapped(*args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/optim/optimizer.py", line 113, in wrapper
return func(*args, *kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/optim/adamw.py", line 119, in step
loss = closure()
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 236, in _training_step_and_backward_closure
result = self.training_step_and_backward(split_batch, batch_idx, opt_idx, optimizer, hiddens)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 537, in training_step_and_backward
result = self._training_step(split_batch, batch_idx, opt_idx, hiddens)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 307, in _training_step
training_step_output = self.trainer.accelerator.training_step(step_kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/accelerators/accelerator.py", line 193, in training_step
return self.training_type_plugin.training_step(step_kwargs.values())
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/plugins/training_type/ddp.py", line 383, in training_step
return self.model(args, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, *kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 1008, in forward
output = self._run_ddp_forward(inputs, kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 969, in _run_ddp_forward
return module_to_run(*inputs[0], kwargs[0])
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, *kwargs)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/pytorch_lightning/overrides/base.py", line 82, in forward
output = self.module.training_step(inputs, kwargs)
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 403, in training_step
loss, loss_dict = self.shared_step(batch)
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 866, in shared_step
loss = self(x, c, T)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, kwargs)
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 880, in forward
return self.p_losses(x, c, T, t, args, kwargs)
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 1011, in p_losses
model_output = self.apply_model(x_noisy, t, cond, T, x_start) #x_start added
File "/home/lambdasix/zero123/zero123/ldm/models/diffusion/ddpm.py", line 983, in apply_model
x_recon = self.model(x_noisy, t, T, x, cond)
File "/home/lambdasix/anaconda3/envs/zero123/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(input, kwargs)
TypeError: forward() got multiple values for argument 'c_crossattn'