DeepCompression-caffe | Caffe for Deep Compression | Compression library
kandi X-RAY | DeepCompression-caffe Summary
kandi X-RAY | DeepCompression-caffe Summary
This is a simple caffe implementation of Deep Compression(including weight prunning and quantization. According to the paper, the compression are implemented only on convolution and fully-connected layers. Thus we add a CmpConvolution and a CmpInnerProduct layer. The params that controlls the sparsity including:. For a better understanding, please see the examples/mnist and run the demo script, which automatically compresses a pretrained MNIST LeNet caffemodel.
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QUESTION
i hope you are doing well, i tried to run a python code that i downloaded from here : "https://github.com/may0324/DeepCompression-caffe/tree/master/examples/mnist"
i am using Ubuntu 16.04,python (2.7,3.5),
...ANSWER
Answered 2019-Feb-13 at 09:31Your version of caffe does not have sparse_ratio
as part of its inner_product_param
or its convolution_param
(see these definitions in caffe.proto
).
It seems like the specific code you are trying to run requires its own version of caffe that has a slightly different caffe.proto
definitions.
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