Caffe CNN模型FLOPs 计算脚本
作者:互联网
简单估算caffe模型参数量和计算量的脚本,包含Convolution, MaxPooling, Eltwise和InnerProduct层
import os, sys
os.environ['GLOG_minloglevel'] = '2'
CAFFE_ROOT = "/home/hp/Documents/caffe-master"
if os.path.join(CAFFE_ROOT, 'python') not in sys.path:
sys.path.insert(0, os.path.join(CAFFE_ROOT, 'python'))
import caffe
import google.protobuf.text_format
import google.protobuf as pb
from caffe.proto.caffe_pb2 import NetParameter
model="models/bvlc_alexnet/deploy.prototxt"
def main():
net=caffe.Net(model,caffe.TEST)
params_num=0
flops=0
net_info = NetParameter()
with open(model, 'r') as fp:
pb.text_format.Merge(fp.read(), net_info)
layer_dict = {layer.name : layer for layer in net_info.layer}
blobs=net.blobs
params=net.params
print("name".ljust(25)+"type".ljust(25)+"param".ljust(25)+"FLOPs".ljust(25))
for item in layer_dict.items():
name,layer=item
type=layer.type
if type == 'Convolution':
b=blobs[name]
weights=params[name][0]
c1=weights.count/layer.convolution_param.group
c2=0
if len(params[name]) > 1:
bias=params[name][1]
c2=bias.count
param=c1+c2
flop=2*param*b.width*b.height*b.num+b.count #Convolution+ReLU
print(name.ljust(25)+str(type).ljust(25)+str(param).ljust(25)+str(flop).ljust(25))
params_num+=param
flops+=flop
elif type == 'Pooling': #MaxPooling
b=blobs[name]
k=layer.pooling_param.kernel_size
param=0
flop=k*k*b.count
print(name.ljust(25)+str(type).ljust(25)+str(param).ljust(25)+str(flop).ljust(25))
params_num+=param
flops+=flop
elif type == 'Eltwise':
b=blobs[name]
param=0
flop=b.count
print(name.ljust(25)+str(type).ljust(25)+str(param).ljust(25)+str(flop).ljust(25))
params_num+=param
flops+=flop
elif type == 'InnerProduct':
b=blobs[name]
weights=params[name][0]
c1=weights.count
c2=0
if len(params[name]) > 1:
bias=params[name][1]
c2=bias.count
param=c1+c2
flop=2*b.count*weights.channels
print(name.ljust(25)+str(type).ljust(25)+str(param).ljust(25)+str(flop).ljust(25))
params_num+=param
flops+=flop
print("total params(M)",params_num/1000/1000)
print("GFLOPs:",flops/1000/1000/1000)
if __name__ == '__main__':
main()
hp@hp-HP-Pavilion-Laptop-15-ck0xx:~/Documents/caffe-master$ conda activate caffe_env
(caffe_env) hp@hp-HP-Pavilion-Laptop-15-ck0xx:~/Documents/caffe-master$ python FLOPs.py
name type param FLOPs
fc6 InnerProduct 37752832 754974720
fc7 InnerProduct 16781312 335544320
pool5 Pooling 0 829440
fc8 InnerProduct 4097000 81920000
conv3 Convolution 885120.0 2992354560.0
conv5 Convolution 221440.0 748899840.0
conv2 Convolution 153856.0 2245086720.0
pool2 Pooling 0 3893760
pool1 Pooling 0 6298560
conv1 Convolution 34944.0 2117016000.0
conv4 Convolution 332160.0 1123349760.0
total params(M) 60.258663999999996
GFLOPs: 10.41016768
(caffe_env) hp@hp-HP-Pavilion-Laptop-15-ck0xx:~/Documents/caffe-master$
如有错误欢迎指正
标签:25,ljust,name,caffe,param,Caffe,CNN,params,FLOPs 来源: https://blog.csdn.net/Z1007513207/article/details/118638578