I'm trying to rewrite a model from caffe to tensorflow. To make sure I did not make mistake, I count the macc and Flops and then I find this interesting thing:
For example, when input a image 112x112x3, and conv2d it with 32 3x3 kernel, stride=1, the macc in Caffe is 2.71M, while the FLOPs computed in tensorflow is 5. 42M.
I wonder why this 2x difference happen?