def setup(self):
    self.feed('data').conv(7, 7, 64, 2, 2, name='conv1_7x7_s2').max_pool(3, 3, 2, 2, name='pool1_3x3_s2').lrn(2, 2e-05, 0.75, name='pool1_norm1').conv(1, 1, 64, 1, 1, name='conv2_3x3_reduce').conv(3, 3, 192, 1, 1, name='conv2_3x3').lrn(2, 2e-05, 0.75, name='conv2_norm2').max_pool(3, 3, 2, 2, name='pool2_3x3_s2').conv(1, 1, 64, 1, 1, name='inception_3a_1x1')
    self.feed('pool2_3x3_s2').conv(1, 1, 96, 1, 1, name='inception_3a_3x3_reduce').conv(3, 3, 128, 1, 1, name='inception_3a_3x3')
    self.feed('pool2_3x3_s2').conv(1, 1, 16, 1, 1, name='inception_3a_5x5_reduce').conv(5, 5, 32, 1, 1, name='inception_3a_5x5')
    self.feed('pool2_3x3_s2').max_pool(3, 3, 1, 1, name='inception_3a_pool').conv(1, 1, 32, 1, 1, name='inception_3a_pool_proj')
    self.feed('inception_3a_1x1', 'inception_3a_3x3', 'inception_3a_5x5', 'inception_3a_pool_proj').concat(3, name='inception_3a_output').conv(1, 1, 128, 1, 1, name='inception_3b_1x1')
    self.feed('inception_3a_output').conv(1, 1, 128, 1, 1, name='inception_3b_3x3_reduce').conv(3, 3, 192, 1, 1, name='inception_3b_3x3')
    self.feed('inception_3a_output').conv(1, 1, 32, 1, 1, name='inception_3b_5x5_reduce').conv(5, 5, 96, 1, 1, name='inception_3b_5x5')
    self.feed('inception_3a_output').max_pool(3, 3, 1, 1, name='inception_3b_pool').conv(1, 1, 64, 1, 1, name='inception_3b_pool_proj')
    self.feed('inception_3b_1x1', 'inception_3b_3x3', 'inception_3b_5x5', 'inception_3b_pool_proj').concat(3, name='inception_3b_output').max_pool(3, 3, 2, 2, name='pool3_3x3_s2').conv(1, 1, 192, 1, 1, name='inception_4a_1x1')
    self.feed('pool3_3x3_s2').conv(1, 1, 96, 1, 1, name='inception_4a_3x3_reduce').conv(3, 3, 208, 1, 1, name='inception_4a_3x3')
    self.feed('pool3_3x3_s2').conv(1, 1, 16, 1, 1, name='inception_4a_5x5_reduce').conv(5, 5, 48, 1, 1, name='inception_4a_5x5')
    self.feed('pool3_3x3_s2').max_pool(3, 3, 1, 1, name='inception_4a_pool').conv(1, 1, 64, 1, 1, name='inception_4a_pool_proj')
    self.feed('inception_4a_1x1', 'inception_4a_3x3', 'inception_4a_5x5', 'inception_4a_pool_proj').concat(3, name='inception_4a_output').conv(1, 1, 160, 1, 1, name='inception_4b_1x1')
    self.feed('inception_4a_output').conv(1, 1, 112, 1, 1, name='inception_4b_3x3_reduce').conv(3, 3, 224, 1, 1, name='inception_4b_3x3')
    self.feed('inception_4a_output').conv(1, 1, 24, 1, 1, name='inception_4b_5x5_reduce').conv(5, 5, 64, 1, 1, name='inception_4b_5x5')
    self.feed('inception_4a_output').max_pool(3, 3, 1, 1, name='inception_4b_pool').conv(1, 1, 64, 1, 1, name='inception_4b_pool_proj')
    self.feed('inception_4b_1x1', 'inception_4b_3x3', 'inception_4b_5x5', 'inception_4b_pool_proj').concat(3, name='inception_4b_output').conv(1, 1, 128, 1, 1, name='inception_4c_1x1')
    self.feed('inception_4b_output').conv(1, 1, 128, 1, 1, name='inception_4c_3x3_reduce').conv(3, 3, 256, 1, 1, name='inception_4c_3x3')
    self.feed('inception_4b_output').conv(1, 1, 24, 1, 1, name='inception_4c_5x5_reduce').conv(5, 5, 64, 1, 1, name='inception_4c_5x5')
    self.feed('inception_4b_output').max_pool(3, 3, 1, 1, name='inception_4c_pool').conv(1, 1, 64, 1, 1, name='inception_4c_pool_proj')
    self.feed('inception_4c_1x1', 'inception_4c_3x3', 'inception_4c_5x5', 'inception_4c_pool_proj').concat(3, name='inception_4c_output').conv(1, 1, 112, 1, 1, name='inception_4d_1x1')
    self.feed('inception_4c_output').conv(1, 1, 144, 1, 1, name='inception_4d_3x3_reduce').conv(3, 3, 288, 1, 1, name='inception_4d_3x3')
    self.feed('inception_4c_output').conv(1, 1, 32, 1, 1, name='inception_4d_5x5_reduce').conv(5, 5, 64, 1, 1, name='inception_4d_5x5')
    self.feed('inception_4c_output').max_pool(3, 3, 1, 1, name='inception_4d_pool').conv(1, 1, 64, 1, 1, name='inception_4d_pool_proj')
    self.feed('inception_4d_1x1', 'inception_4d_3x3', 'inception_4d_5x5', 'inception_4d_pool_proj').concat(3, name='inception_4d_output').conv(1, 1, 256, 1, 1, name='inception_4e_1x1')
    self.feed('inception_4d_output').conv(1, 1, 160, 1, 1, name='inception_4e_3x3_reduce').conv(3, 3, 320, 1, 1, name='inception_4e_3x3')
    self.feed('inception_4d_output').conv(1, 1, 32, 1, 1, name='inception_4e_5x5_reduce').conv(5, 5, 128, 1, 1, name='inception_4e_5x5')
    self.feed('inception_4d_output').max_pool(3, 3, 1, 1, name='inception_4e_pool').conv(1, 1, 128, 1, 1, name='inception_4e_pool_proj')
    self.feed('inception_4e_1x1', 'inception_4e_3x3', 'inception_4e_5x5', 'inception_4e_pool_proj').concat(3, name='inception_4e_output').max_pool(3, 3, 2, 2, name='pool4_3x3_s2').conv(1, 1, 256, 1, 1, name='inception_5a_1x1')
    self.feed('pool4_3x3_s2').conv(1, 1, 160, 1, 1, name='inception_5a_3x3_reduce').conv(3, 3, 320, 1, 1, name='inception_5a_3x3')
    self.feed('pool4_3x3_s2').conv(1, 1, 32, 1, 1, name='inception_5a_5x5_reduce').conv(5, 5, 128, 1, 1, name='inception_5a_5x5')
    self.feed('pool4_3x3_s2').max_pool(3, 3, 1, 1, name='inception_5a_pool').conv(1, 1, 128, 1, 1, name='inception_5a_pool_proj')
    self.feed('inception_5a_1x1', 'inception_5a_3x3', 'inception_5a_5x5', 'inception_5a_pool_proj').concat(3, name='inception_5a_output').conv(1, 1, 384, 1, 1, name='inception_5b_1x1')
    self.feed('inception_5a_output').conv(1, 1, 192, 1, 1, name='inception_5b_3x3_reduce').conv(3, 3, 384, 1, 1, name='inception_5b_3x3')
    self.feed('inception_5a_output').conv(1, 1, 48, 1, 1, name='inception_5b_5x5_reduce').conv(5, 5, 128, 1, 1, name='inception_5b_5x5')
    self.feed('inception_5a_output').max_pool(3, 3, 1, 1, name='inception_5b_pool').conv(1, 1, 128, 1, 1, name='inception_5b_pool_proj')
    self.feed('inception_5b_1x1', 'inception_5b_3x3', 'inception_5b_5x5', 'inception_5b_pool_proj').concat(3, name='inception_5b_output').avg_pool(7, 7, 1, 1, padding='VALID', name='pool5_7x7_s1').fc(1000, relu=False, name='loss3_classifier').softmax(name='prob')
def setup(self):
    self.feed('data').conv(7, 7, 64, 2, 2, name='conv1_7x7_s2').max_pool(3, 3, 2, 2, name='pool1_3x3_s2').lrn(2, 2e-05, 0.75, name='pool1_norm1').conv(1, 1, 64, 1, 1, name='conv2_3x3_reduce').conv(3, 3, 192, 1, 1, name='conv2_3x3').lrn(2, 2e-05, 0.75, name='conv2_norm2').max_pool(3, 3, 2, 2, name='pool2_3x3_s2').conv(1, 1, 64, 1, 1, name='inception_3a_1x1')
    self.feed('pool2_3x3_s2').conv(1, 1, 96, 1, 1, name='inception_3a_3x3_reduce').conv(3, 3, 128, 1, 1, name='inception_3a_3x3')
    self.feed('pool2_3x3_s2').conv(1, 1, 16, 1, 1, name='inception_3a_5x5_reduce').conv(5, 5, 32, 1, 1, name='inception_3a_5x5')
    self.feed('pool2_3x3_s2').max_pool(3, 3, 1, 1, name='inception_3a_pool').conv(1, 1, 32, 1, 1, name='inception_3a_pool_proj')
    self.feed('inception_3a_1x1', 'inception_3a_3x3', 'inception_3a_5x5', 'inception_3a_pool_proj').concat(3, name='inception_3a_output').conv(1, 1, 128, 1, 1, name='inception_3b_1x1')
    self.feed('inception_3a_output').conv(1, 1, 128, 1, 1, name='inception_3b_3x3_reduce').conv(3, 3, 192, 1, 1, name='inception_3b_3x3')
    self.feed('inception_3a_output').conv(1, 1, 32, 1, 1, name='inception_3b_5x5_reduce').conv(5, 5, 96, 1, 1, name='inception_3b_5x5')
    self.feed('inception_3a_output').max_pool(3, 3, 1, 1, name='inception_3b_pool').conv(1, 1, 64, 1, 1, name='inception_3b_pool_proj')
    self.feed('inception_3b_1x1', 'inception_3b_3x3', 'inception_3b_5x5', 'inception_3b_pool_proj').concat(3, name='inception_3b_output').max_pool(3, 3, 2, 2, name='pool3_3x3_s2').conv(1, 1, 192, 1, 1, name='inception_4a_1x1')
    self.feed('pool3_3x3_s2').conv(1, 1, 96, 1, 1, name='inception_4a_3x3_reduce').conv(3, 3, 208, 1, 1, name='inception_4a_3x3')
    self.feed('pool3_3x3_s2').conv(1, 1, 16, 1, 1, name='inception_4a_5x5_reduce').conv(5, 5, 48, 1, 1, name='inception_4a_5x5')
    self.feed('pool3_3x3_s2').max_pool(3, 3, 1, 1, name='inception_4a_pool').conv(1, 1, 64, 1, 1, name='inception_4a_pool_proj')
    self.feed('inception_4a_1x1', 'inception_4a_3x3', 'inception_4a_5x5', 'inception_4a_pool_proj').concat(3, name='inception_4a_output').conv(1, 1, 160, 1, 1, name='inception_4b_1x1')
    self.feed('inception_4a_output').conv(1, 1, 112, 1, 1, name='inception_4b_3x3_reduce').conv(3, 3, 224, 1, 1, name='inception_4b_3x3')
    self.feed('inception_4a_output').conv(1, 1, 24, 1, 1, name='inception_4b_5x5_reduce').conv(5, 5, 64, 1, 1, name='inception_4b_5x5')
    self.feed('inception_4a_output').max_pool(3, 3, 1, 1, name='inception_4b_pool').conv(1, 1, 64, 1, 1, name='inception_4b_pool_proj')
    self.feed('inception_4b_1x1', 'inception_4b_3x3', 'inception_4b_5x5', 'inception_4b_pool_proj').concat(3, name='inception_4b_output').conv(1, 1, 128, 1, 1, name='inception_4c_1x1')
    self.feed('inception_4b_output').conv(1, 1, 128, 1, 1, name='inception_4c_3x3_reduce').conv(3, 3, 256, 1, 1, name='inception_4c_3x3')
    self.feed('inception_4b_output').conv(1, 1, 24, 1, 1, name='inception_4c_5x5_reduce').conv(5, 5, 64, 1, 1, name='inception_4c_5x5')
    self.feed('inception_4b_output').max_pool(3, 3, 1, 1, name='inception_4c_pool').conv(1, 1, 64, 1, 1, name='inception_4c_pool_proj')
    self.feed('inception_4c_1x1', 'inception_4c_3x3', 'inception_4c_5x5', 'inception_4c_pool_proj').concat(3, name='inception_4c_output').conv(1, 1, 112, 1, 1, name='inception_4d_1x1')
    self.feed('inception_4c_output').conv(1, 1, 144, 1, 1, name='inception_4d_3x3_reduce').conv(3, 3, 288, 1, 1, name='inception_4d_3x3')
    self.feed('inception_4c_output').conv(1, 1, 32, 1, 1, name='inception_4d_5x5_reduce').conv(5, 5, 64, 1, 1, name='inception_4d_5x5')
    self.feed('inception_4c_output').max_pool(3, 3, 1, 1, name='inception_4d_pool').conv(1, 1, 64, 1, 1, name='inception_4d_pool_proj')
    self.feed('inception_4d_1x1', 'inception_4d_3x3', 'inception_4d_5x5', 'inception_4d_pool_proj').concat(3, name='inception_4d_output').conv(1, 1, 256, 1, 1, name='inception_4e_1x1')
    self.feed('inception_4d_output').conv(1, 1, 160, 1, 1, name='inception_4e_3x3_reduce').conv(3, 3, 320, 1, 1, name='inception_4e_3x3')
    self.feed('inception_4d_output').conv(1, 1, 32, 1, 1, name='inception_4e_5x5_reduce').conv(5, 5, 128, 1, 1, name='inception_4e_5x5')
    self.feed('inception_4d_output').max_pool(3, 3, 1, 1, name='inception_4e_pool').conv(1, 1, 128, 1, 1, name='inception_4e_pool_proj')
    self.feed('inception_4e_1x1', 'inception_4e_3x3', 'inception_4e_5x5', 'inception_4e_pool_proj').concat(3, name='inception_4e_output').max_pool(3, 3, 2, 2, name='pool4_3x3_s2').conv(1, 1, 256, 1, 1, name='inception_5a_1x1')
    self.feed('pool4_3x3_s2').conv(1, 1, 160, 1, 1, name='inception_5a_3x3_reduce').conv(3, 3, 320, 1, 1, name='inception_5a_3x3')
    self.feed('pool4_3x3_s2').conv(1, 1, 32, 1, 1, name='inception_5a_5x5_reduce').conv(5, 5, 128, 1, 1, name='inception_5a_5x5')
    self.feed('pool4_3x3_s2').max_pool(3, 3, 1, 1, name='inception_5a_pool').conv(1, 1, 128, 1, 1, name='inception_5a_pool_proj')
    self.feed('inception_5a_1x1', 'inception_5a_3x3', 'inception_5a_5x5', 'inception_5a_pool_proj').concat(3, name='inception_5a_output').conv(1, 1, 384, 1, 1, name='inception_5b_1x1')
    self.feed('inception_5a_output').conv(1, 1, 192, 1, 1, name='inception_5b_3x3_reduce').conv(3, 3, 384, 1, 1, name='inception_5b_3x3')
    self.feed('inception_5a_output').conv(1, 1, 48, 1, 1, name='inception_5b_5x5_reduce').conv(5, 5, 128, 1, 1, name='inception_5b_5x5')
    self.feed('inception_5a_output').max_pool(3, 3, 1, 1, name='inception_5b_pool').conv(1, 1, 128, 1, 1, name='inception_5b_pool_proj')
    self.feed('inception_5b_1x1', 'inception_5b_3x3', 'inception_5b_5x5', 'inception_5b_pool_proj').concat(3, name='inception_5b_output').avg_pool(7, 7, 1, 1, padding='VALID', name='pool5_7x7_s1').fc(1000, relu=False, name='loss3_classifier').softmax(name='prob')