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def make_convnet(input_image): | |
net = slim.conv2d(input_image, 32, [11, 11], scope="conv1_11x11") | |
net = slim.conv2d(input_image, 64, [5, 5], scope="conv2_5x5") | |
net = slim.max_pool2d(net, [4, 4], stride=4, scope='pool1') | |
net = slim.conv2d(input_image, 64, [5, 5], scope="conv3_5x5") | |
net = slim.conv2d(input_image, 128, [3, 3], scope="conv4_3x3") | |
net = slim.max_pool2d(net, [2, 2], scope='pool2') | |
net = slim.conv2d(input_image, 128, [3, 3], scope="conv5_3x3") | |
net = slim.max_pool2d(net, [2, 2], scope='pool3') | |
net = slim.conv2d(input_image, 32, [1, 1], scope="conv6_1x1") | |
return net |
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