Additionally, when loading ControlNet in train_controlnet_inpaint.py, the following warning appears:
{‘mid_block_type’} was not found in config. Values will be initialized to default values.
I am using the mask as the conditioning_image, as proposed in your paper.
down_block_res_samples, mid_block_res_sample = controlnet(
^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/parallel/distributed.py", line 1523, in forward
else self._run_ddp_forward(*inputs, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/parallel/distributed.py", line 1359, in _run_ddp_forward
return self.module(*inputs, **kwargs) # type: ignore[index]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/accelerate/utils/operations.py", line 822, in forward
return model_forward(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/accelerate/utils/operations.py", line 810, in __call__
return convert_to_fp32(self.model_forward(*args, **kwargs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/amp/autocast_mode.py", line 16, in decorate_autocast
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/diffusers/models/controlnet.py", line 795, in forward
sample = self.conv_in(sample)
^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/conv.py", line 460, in forward
return self._conv_forward(input, self.weight, self.bias)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/conv.py", line 456, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Given groups=1, weight of size [320, 9, 3, 3], expected input[4, 4, 64, 64] to have 9 channels, but got 4 channels instead
Traceback (most recent call last):
File "/home/helloworld/workspace/photo-background-generation/train_controlnet_inpaint.py", line 1249, in <module>
main(args)
File "/home/helloworld/workspace/photo-background-generation/train_controlnet_inpaint.py", line 1137, in main
down_block_res_samples, mid_block_res_sample = controlnet(
^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/parallel/distributed.py", line 1523, in forward
else self._run_ddp_forward(*inputs, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/parallel/distributed.py", line 1359, in _run_ddp_forward
return self.module(*inputs, **kwargs) # type: ignore[index]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/accelerate/utils/operations.py", line 822, in forward
return model_forward(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/accelerate/utils/operations.py", line 810, in __call__
return convert_to_fp32(self.model_forward(*args, **kwargs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/amp/autocast_mode.py", line 16, in decorate_autocast
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/diffusers/models/controlnet.py", line 795, in forward
sample = self.conv_in(sample)
^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/conv.py", line 460, in forward
return self._conv_forward(input, self.weight, self.bias)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/helloworld/miniconda3/envs/diffusers/lib/python3.11/site-packages/torch/nn/modules/conv.py", line 456, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Given groups=1, weight of size [320, 9, 3, 3], expected input[4, 4, 64, 64] to have 9 channels, but got 4 channels instead
Thank you for your great research 😆
When I try to run
train_controlnet_inpaint.py, I encounter the following code block error.Is
train_controlnet.pythe code used for training the inpaint model?Additionally, when loading ControlNet in train_controlnet_inpaint.py, the following warning appears:
{‘mid_block_type’} was not found in config. Values will be initialized to default values.I am using the mask as the conditioning_image, as proposed in your paper.