PYTHON

max pooling in cnn

1.  def pooling(feature_map, size=2, stride=2):  
2.      #Preparing the output of the pooling operation.  
3.      pool_out = numpy.zeros((numpy.uint16((feature_map.shape[0]-size+1)/stride),  
4.                              numpy.uint16((feature_map.shape[1]-size+1)/stride),  
5.                              feature_map.shape[-1]))  
6.      for map_num in range(feature_map.shape[-1]):  
7.          r2 = 0  
8.          for r in numpy.arange(0,feature_map.shape[0]-size-1, stride):  
9.              c2 = 0  
10.             for c in numpy.arange(0, feature_map.shape[1]-size-1, stride):  
11.                 pool_out[r2, c2, map_num] = numpy.max(feature_map[r:r+size,  c:c+size])  
12.                 c2 = c2 + 1  
13.             r2 = r2 +1