Comments (7)
Hi @nitish11 ,
Thanks for your interest in our work and thanks for this cool repository:
https://github.com/nitish11/GenderRecognition
It's embarrassing to admit it, but I never worked with Torch and I really can't say which one is faster (or in this case - why you get faster run-times in Torch).
Best,
Gil.
from agegenderdeeplearning.
LuaJIT is faster than Python and Torch is generally faster than Caffe from what I've seen in benchmarks, which are a bit outdated: https://github.com/soumith/convnet-benchmarks. I hear Nvidia gives the best support to Torch, which they use for much of their own work (e.g., autonomous car demonstrations), as others like Google and Nervana/Intel compete on hardware. cuDNN 5 speeds up Torch quite a bit: https://devblogs.nvidia.com/parallelforall/optimizing-recurrent-neural-networks-cudnn-5/.
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@adam-erickson :
But, the huge difference in only one frame is the concern. The benchmark has not compared LuaJIT with Caffe.
from agegenderdeeplearning.
I checked torch and Caffe computation engine called BLAS.
In Ubuntu 14.04,
ldd /home/nitish/caffe/build/lib/libcaffe.so
ldd /home/nitish/torch/install/lib/libTH.so
From the output, I observed that torch is linked against openblas, and caffe is linked against libcblas, which might be the reason for slower Caffe.
Solution : Build Caffe with OpenBlas
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Are you sure it's not simply the difference in looping speed between LuaJIT and Python? It can be quite large. Similar to Julia, LuaJIT is closer to C.
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I am not sure about looping speed between LuaJIT and Python.
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There is a better way to call torch from python code using wrapper.
Please check
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Related Issues (20)
- Age estimation confusion matrix ,the sum of a row is not 1? HOT 2
- order of mean HOT 2
- gender recognition based on the whole body HOT 1
- Help me fix errror when i run model . HOT 2
- FiducialFaceDetector source code HOT 4
- Mean shape incompatible with input shape HOT 1
- Age group labels HOT 1
- Human Vs Animal problem HOT 5
- Unbalanced folds HOT 2
- Age Classification accuracy HOT 4
- Assertion `cur_target >= 0 && cur_target < n_classesβ failed HOT 1
- faces.tar.gz labels HOT 2
- how can someone run it on their machine HOT 1
- Problem with Running Code HOT 1
- Mean subtraction for each channel
- AttributeError: 'module' object has no attribute 'io'; a = caffe.io.caffe_pb2.BlobProto.FromString(proto_data)
- Please May I know the gender labels used
- issues
- Gender Classification Confusion Matrix
- Issue during predictions
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