number of parameters in Caffe LENET or Imagenet mo

Question

How to calculate number of parameters in a model e.g. LENET for mnist, or ConvNet for imagent model etc. Is there any specific function in caffe that returns or saves number of parameters in a model. regards

Answer 1

I can offer an explicit way to do this via the Matlab interface (make sure the matcaffe is installed first). Basically, you extract set of parameters from each network layer and count them. In Matlab:

% load the network
net_model = <path to your *deploy.prototxt file>
net_weights = <path to your *.caffemodel file>
phase = 'test';
test_net = caffe.Net(net_model, net_weights, phase);

% get the list of layers
layers_list = test_net.layer_names;
% for those layers which have parameters, count them
counter = 0;
for j = 1:length(layers_list),
    if ~isempty(test_net.layers(layers_list{j}).params)
    feat = test_net.layers(layers_list{j}).params(1).get_data();
    counter = counter + numel(feat)
    end
end

In the end, 'counter' contains the number of parameters.

Answer 2

Here is a python snippet to compute the number of parameters in a Caffe model:

import caffe
caffe.set_mode_cpu()
import numpy as np
from numpy import prod, sum
from pprint import pprint

def print_net_parameters (deploy_file):
    print "Net: " + deploy_file
    net = caffe.Net(deploy_file, caffe.TEST)
    print "Layer-wise parameters: "
    pprint([(k, v[0].data.shape) for k, v in net.params.items()])
    print "Total number of parameters: " + str(sum([prod(v[0].data.shape) for k, v in net.params.items()]))

deploy_file = "/home/ubuntu/deploy.prototxt"
print_net_parameters(deploy_file)

# Sample output:
# Net: /home/ubuntu/deploy.prototxt
# Layer-wise parameters: 
#[('conv1', (96, 3, 11, 11)),
# ('conv2', (256, 48, 5, 5)),
# ('conv3', (384, 256, 3, 3)),
# ('conv4', (384, 192, 3, 3)),
# ('conv5', (256, 192, 3, 3)),
# ('fc6', (4096, 9216)),
# ('fc7', (4096, 4096)),
# ('fc8', (819, 4096))]
# Total number of parameters: 60213280

https://gist.github.com/kaushikpavani/a6a32bd87fdfe5529f0e908ed743f779