Can someone share with me how to use the pycaffe interface to time each layer including some customized python layer?
I have observed there are timing operations in caffe source file: tools/caffe.cpp:
forward_timer.Start();
for (int i = 0; i < layers.size(); ++i) {
timer.Start();
layers[i]->Forward(bottom_vecs[i], top_vecs[i]);
forward_time_per_layer[i] += timer.MicroSeconds();
}
but I don't know how to use it in the pycaffe interface.
There is official doc says:
Benchmarking: caffe time benchmarks model execution layer-by-layer through timing and synchronization. This is useful to check system performance and measure relative execution times for models.
caffe time -model examples/mnist/lenet_train_test.prototxt -weights examples/mnist/lenet_iter_10000.caffemodel -gpu 0 -iterations 10
but this is used at caffe command line, I'm actually running faster-rcnn, which contains python implementations, and called by python scripts, I dont know how to use it.
with command caffe time -model xxx.prototxt -weight caffemodel, it cannot find my python layers, how to set the path so caffe can find it?
EDIT: after adding python layer file path to PYTHONPATH, it can find the module, but some error happens, which does not happen when I did with python interface:
F0119 22:24:39.621578 9314 net.cpp:141] Check failed: param_size <= num_param_blobs (0 vs. -2) Too many params specified for layer proposal
*** Check failure stack trace: ***
@ 0x7efd9bde9daa (unknown)
@ 0x7efd9bde9ce4 (unknown)
@ 0x7efd9bde96e6 (unknown)
@ 0x7efd9bdec687 (unknown)
@ 0x7efd9c4555b6 caffe::Net<>::Init()
@ 0x7efd9c45667b caffe::Net<>::Net()
@ 0x408c0c time()
@ 0x405bec main
@ 0x7efd9a799f45 (unknown)
@ 0x4064f3 (unknown)
@ (nil) (unknown)
Aborted