你好，我尝试在云gpu上运行该代码，出现了如下错误，请问该如何解决呢，劳烦大神回复，谢谢
Traceback (most recent call last):
File "train.py", line 603, in
main() # pylint: disable=no-value-for-parameter
File "/root/miniconda3/lib/python3.8/site-packages/click/core.py", line 1157, in call
return self.main(*args, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/click/core.py", line 1078, in main
rv = self.invoke(ctx)
File "/root/miniconda3/lib/python3.8/site-packages/click/core.py", line 1434, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/root/miniconda3/lib/python3.8/site-packages/click/core.py", line 783, in invoke
return __callback(*args, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/click/decorators.py", line 33, in new_func
return f(get_current_context(), *args, **kwargs)
File "train.py", line 596, in main
subprocess_fn(rank=0, args=args, temp_dir=temp_dir)
File "train.py", line 422, in subprocess_fn
training_loop.training_loop(rank=rank, **args)
File "/root/GAN/Diffusion-GAN-main/diffusion-insgen/training/training_loop.py", line 351, in training_loop
loss.accumulate_gradients(phase=phase.name, real_img=real_img, real_c=real_c, gen_z=gen_z, gen_c=gen_c, sync=sync, gain=gain, cl_phases=cl_phases, D_ema=D_ema, g_fake_cl=not no_cl_on_g, **cl_loss_weight)
File "/root/GAN/Diffusion-GAN-main/diffusion-insgen/training/contrastive_loss.py", line 107, in accumulate_gradients
loss_Gmain.mean().mul(gain).backward()
File "/root/miniconda3/lib/python3.8/site-packages/torch/_tensor.py", line 363, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
File "/root/miniconda3/lib/python3.8/site-packages/torch/autograd/init.py", line 173, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
File "/root/miniconda3/lib/python3.8/site-packages/torch/autograd/function.py", line 253, in apply
return user_fn(self, *args)
File "/root/GAN/Diffusion-GAN-main/diffusion-insgen/torch_utils/ops/grid_sample_gradfix.py", line 50, in backward
grad_input, grad_grid = _GridSample2dBackward.apply(grad_output, input, grid)
File "/root/GAN/Diffusion-GAN-main/diffusion-insgen/torch_utils/ops/grid_sample_gradfix.py", line 59, in forward
grad_input, grad_grid = op(grad_output, input, grid, 0, 0, False)
RuntimeError: aten::grid_sampler_2d_backward() is missing value for argument 'output_mask'. Declaration: aten::grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor)
你好，我尝试在云gpu上运行该代码，出现了如下错误，请问该如何解决呢，劳烦大神回复，谢谢
Traceback (most recent call last):
File "train.py", line 603, in
main() # pylint: disable=no-value-for-parameter
File "/root/miniconda3/lib/python3.8/site-packages/click/core.py", line 1157, in call
return self.main(*args, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/click/core.py", line 1078, in main
rv = self.invoke(ctx)
File "/root/miniconda3/lib/python3.8/site-packages/click/core.py", line 1434, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/root/miniconda3/lib/python3.8/site-packages/click/core.py", line 783, in invoke
return __callback(*args, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/click/decorators.py", line 33, in new_func
return f(get_current_context(), *args, **kwargs)
File "train.py", line 596, in main
subprocess_fn(rank=0, args=args, temp_dir=temp_dir)
File "train.py", line 422, in subprocess_fn
training_loop.training_loop(rank=rank, **args)
File "/root/GAN/Diffusion-GAN-main/diffusion-insgen/training/training_loop.py", line 351, in training_loop
loss.accumulate_gradients(phase=phase.name, real_img=real_img, real_c=real_c, gen_z=gen_z, gen_c=gen_c, sync=sync, gain=gain, cl_phases=cl_phases, D_ema=D_ema, g_fake_cl=not no_cl_on_g, **cl_loss_weight)
File "/root/GAN/Diffusion-GAN-main/diffusion-insgen/training/contrastive_loss.py", line 107, in accumulate_gradients
loss_Gmain.mean().mul(gain).backward()
File "/root/miniconda3/lib/python3.8/site-packages/torch/_tensor.py", line 363, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
File "/root/miniconda3/lib/python3.8/site-packages/torch/autograd/init.py", line 173, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
File "/root/miniconda3/lib/python3.8/site-packages/torch/autograd/function.py", line 253, in apply
return user_fn(self, *args)
File "/root/GAN/Diffusion-GAN-main/diffusion-insgen/torch_utils/ops/grid_sample_gradfix.py", line 50, in backward
grad_input, grad_grid = _GridSample2dBackward.apply(grad_output, input, grid)
File "/root/GAN/Diffusion-GAN-main/diffusion-insgen/torch_utils/ops/grid_sample_gradfix.py", line 59, in forward
grad_input, grad_grid = op(grad_output, input, grid, 0, 0, False)
RuntimeError: aten::grid_sampler_2d_backward() is missing value for argument 'output_mask'. Declaration: aten::grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor)