【发布时间】:2018-12-09 02:40:32
【问题描述】:
net.blobs['data'].data[...] = transformed_image
output = net.forward()
output_prob = output['prob'][0] # the output probability vector for the
first image in the batch
print 'predicted class is:', output_prob.argmax()
label_index = output_prob.argmax()
caffeLabel = np.zeros((1,1000))
caffeLabel[0,label_index] = 1;
vis_layer = 'pool5' # visualization layer
grads=net.backward(diffs=[vis_layer],**{'prob':caffeLabel})
print(np.sum(grads))
我想用这种方式获取渐变,但是print(np.sum(grads))总是0,我换了图层conv5或者其他图层,都没用!
【问题讨论】: