Disabling attention optimization
============= Diagnostic Run torch.onnx.export version 2.0.1+cu118 =============
verbose: False, log level: Level.ERROR
======================= 0 NONE 0 NOTE 0 WARNING 0 ERROR ========================
*** Error completing request
*** Arguments: ('', 17) {}
Traceback (most recent call last):
File "/home/user/stable-diffusion-webui/modules/call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "/home/user/stable-diffusion-webui/modules/call_queue.py", line 36, in f
res = func(*args, **kwargs)
File "/home/user/stable-diffusion-webui/extensions/stable-diffusion-webui-tensorrt/ui_trt.py", line 21, in export_unet_to_onnx
export_onnx.export_current_unet_to_onnx(filename, opset)
File "/home/user/stable-diffusion-webui/extensions/stable-diffusion-webui-tensorrt/export_onnx.py", line 27, in export_current_unet_to_onnx
torch.onnx.export(
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 506, in export
_export(
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 1548, in _export
graph, params_dict, torch_out = _model_to_graph(
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 1113, in _model_to_graph
graph, params, torch_out, module = _create_jit_graph(model, args)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 989, in _create_jit_graph
graph, torch_out = _trace_and_get_graph_from_model(model, args)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/onnx/utils.py", line 893, in _trace_and_get_graph_from_model
trace_graph, torch_out, inputs_states = torch.jit._get_trace_graph(
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/jit/_trace.py", line 1268, in _get_trace_graph
outs = ONNXTracedModule(f, strict, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/jit/_trace.py", line 127, in forward
graph, out = torch._C._create_graph_by_tracing(
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/jit/_trace.py", line 118, in wrapper
outs.append(self.inner(*trace_inputs))
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1488, in _slow_forward
result = self.forward(*input, **kwargs)
File "/home/user/stable-diffusion-webui/modules/sd_unet.py", line 91, in UNetModel_forward
return original_forward(self, x, timesteps, context, *args, **kwargs)
File "/home/user/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/modules/diffusionmodules/openaimodel.py", line 797, in forward
h = module(h, emb, context)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1488, in _slow_forward
result = self.forward(*input, **kwargs)
File "/home/user/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/modules/diffusionmodules/openaimodel.py", line 86, in forward
x = layer(x)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1488, in _slow_forward
result = self.forward(*input, **kwargs)
File "/home/user/stable-diffusion-webui/extensions-builtin/Lora/networks.py", line 444, in network_Conv2d_forward
return originals.Conv2d_forward(self, input)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 463, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/home/user/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 459, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Given groups=1, weight of size [320, 9, 3, 3], expected input[1, 4, 16, 16] to have 9 channels, but got 4 channels instead
yuvraj108c
commented
10 months ago