You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I ran into the following problem when converting densenet121_baseline_att_256x256_B_epoch_160.pth and also resnet18_baseline_att_224x224_A_epoch_249.pth into a trt model, which appears to be due to a mismatch between the model weight and the model definition. Does anyone know how to fix it?
>>> model_trt = torch2trt.torch2trt(model, [data], fp16_mode=True, max_workspace_size=1<<25) [08/01/2024-17:37:36] [TRT] [E] Error Code: 3: 1.cmap_up.0:0:DECONVOLUTION:GPU:kernel weights has count 2097152 but 4194304 was expected [08/01/2024-17:37:36] [TRT] [E] ITensor::getDimensions: Error Code 4: API Usage Error (1.cmap_up.0:0:DECONVOLUTION:GPU: count of 2097152 weights in kernel, but kernel dimensions (4,4) with 512 input channels, 512 output channels and 1 groups were specified. Expected Weights count is 512 * 4*4 * 512 / 1 = 4194304) [08/01/2024-17:37:36] [TRT] [E] Error Code: 3: 1.paf_up.0:0:DECONVOLUTION:GPU:kernel weights has count 2097152 but 4194304 was expected [08/01/2024-17:37:36] [TRT] [E] ITensor::getDimensions: Error Code 4: API Usage Error (1.paf_up.0:0:DECONVOLUTION:GPU: count of 2097152 weights in kernel, but kernel dimensions (4,4) with 512 input channels, 512 output channels and 1 groups were specified. Expected Weights count is 512 * 4*4 * 512 / 1 = 4194304) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch2trt-0.5.0-py3.8-linux-x86_64.egg/torch2trt/torch2trt.py", line 643, in torch2trt outputs = module(*inputs) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1538, in _call_impl result = forward_call(*args, **kwargs) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch/nn/modules/container.py", line 217, in forward input = module(input) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1538, in _call_impl result = forward_call(*args, **kwargs) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/trt_pose-0.0.1-py3.8-linux-x86_64.egg/trt_pose/models/common.py", line 76, in forward return self.cmap_conv(xc * ac), self.paf_conv(xp * ap) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch2trt-0.5.0-py3.8-linux-x86_64.egg/torch2trt/torch2trt.py", line 262, in wrapper converter["converter"](ctx) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch2trt-0.5.0-py3.8-linux-x86_64.egg/torch2trt/converters/native_converters.py", line 1496, in convert_mul input_a_trt, input_b_trt = broadcast_trt_tensors(ctx.network, [input_a_trt, input_b_trt], len(output.shape)) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch2trt-0.5.0-py3.8-linux-x86_64.egg/torch2trt/torch2trt.py", line 146, in broadcast_trt_tensors if len(t.shape) < broadcast_ndim: ValueError: __len__() should return >= 0
The text was updated successfully, but these errors were encountered:
Hi. I meet the same problem when converting resnet18_baseline_att_224x224_A_epoch_249.pth to a trt model. The error is "[TRT] [E] Error Code: 3: 1.cmap_up.0:0:DECONVOLUTION:GPU: kernel weights has count 2097152 but 4194304 was expected". Have you fixed it?
I ran into the following problem when converting
densenet121_baseline_att_256x256_B_epoch_160.pth
and alsoresnet18_baseline_att_224x224_A_epoch_249.pth
into a trt model, which appears to be due to a mismatch between the model weight and the model definition. Does anyone know how to fix it?>>> model_trt = torch2trt.torch2trt(model, [data], fp16_mode=True, max_workspace_size=1<<25) [08/01/2024-17:37:36] [TRT] [E] Error Code: 3: 1.cmap_up.0:0:DECONVOLUTION:GPU:kernel weights has count 2097152 but 4194304 was expected [08/01/2024-17:37:36] [TRT] [E] ITensor::getDimensions: Error Code 4: API Usage Error (1.cmap_up.0:0:DECONVOLUTION:GPU: count of 2097152 weights in kernel, but kernel dimensions (4,4) with 512 input channels, 512 output channels and 1 groups were specified. Expected Weights count is 512 * 4*4 * 512 / 1 = 4194304) [08/01/2024-17:37:36] [TRT] [E] Error Code: 3: 1.paf_up.0:0:DECONVOLUTION:GPU:kernel weights has count 2097152 but 4194304 was expected [08/01/2024-17:37:36] [TRT] [E] ITensor::getDimensions: Error Code 4: API Usage Error (1.paf_up.0:0:DECONVOLUTION:GPU: count of 2097152 weights in kernel, but kernel dimensions (4,4) with 512 input channels, 512 output channels and 1 groups were specified. Expected Weights count is 512 * 4*4 * 512 / 1 = 4194304) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch2trt-0.5.0-py3.8-linux-x86_64.egg/torch2trt/torch2trt.py", line 643, in torch2trt outputs = module(*inputs) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1538, in _call_impl result = forward_call(*args, **kwargs) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch/nn/modules/container.py", line 217, in forward input = module(input) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1538, in _call_impl result = forward_call(*args, **kwargs) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/trt_pose-0.0.1-py3.8-linux-x86_64.egg/trt_pose/models/common.py", line 76, in forward return self.cmap_conv(xc * ac), self.paf_conv(xp * ap) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch2trt-0.5.0-py3.8-linux-x86_64.egg/torch2trt/torch2trt.py", line 262, in wrapper converter["converter"](ctx) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch2trt-0.5.0-py3.8-linux-x86_64.egg/torch2trt/converters/native_converters.py", line 1496, in convert_mul input_a_trt, input_b_trt = broadcast_trt_tensors(ctx.network, [input_a_trt, input_b_trt], len(output.shape)) File "/root/miniconda3/envs/trtpose/lib/python3.8/site-packages/torch2trt-0.5.0-py3.8-linux-x86_64.egg/torch2trt/torch2trt.py", line 146, in broadcast_trt_tensors if len(t.shape) < broadcast_ndim: ValueError: __len__() should return >= 0
The text was updated successfully, but these errors were encountered: