Try to fill the filter weights and bias into the Layer.Convolution in pycaffe.
net.params['convres'][0].data= data2
net.params['convres'][0].data points to the filter weights correctly. But it triggers the assertion
when assign data to it.
Is there any solid way to fill the filter weights and bias into Convolution function in python?
I try to design a 3d convolution and needs to debug it step by step with the known filter weights.
Steps to reproduce
If you are having difficulty building Caffe or training a model, please ask the caffe-users mailing list. If you are reporting a build error that seems to be due to a bug in Caffe, please attach your build configuration (either Makefile.config or CMakeCache.txt) and the output of the make (or cmake) command.
Your system configuration
Operating system: ubuntu16 (x64)
Compiler: g++
CUDA version (if applicable): cuda8
CUDNN version (if applicable):cudnn7
BLAS:
Python or MATLAB version (for pycaffe and matcaffe respectively):python27
Issue summary
Try to fill the filter weights and bias into the Layer.Convolution in pycaffe. net.params['convres'][0].data= data2 net.params['convres'][0].data points to the filter weights correctly. But it triggers the assertion when assign data to it. Is there any solid way to fill the filter weights and bias into Convolution function in python? I try to design a 3d convolution and needs to debug it step by step with the known filter weights.
Steps to reproduce
If you are having difficulty building Caffe or training a model, please ask the caffe-users mailing list. If you are reporting a build error that seems to be due to a bug in Caffe, please attach your build configuration (either Makefile.config or CMakeCache.txt) and the output of the make (or cmake) command.
Your system configuration
Operating system: ubuntu16 (x64) Compiler: g++ CUDA version (if applicable): cuda8 CUDNN version (if applicable):cudnn7 BLAS: Python or MATLAB version (for pycaffe and matcaffe respectively):python27