b039cceb43f0575c863f9a36d5143bb43fe44678,luminoth/models/base/ssd_feature_extractor.py,SSDFeatureExtractor,_build,#SSDFeatureExtractor#Any#Any#,26

Before Change

            // We"ll add the feature maps to a collection. In the paper they use
            // one of vgg16"s layers as a feature map, so we start by adding it.
            tf.add_to_collection("FEATURE_MAPS", base_net_endpoints[
                scope + "/vgg_16/conv4/conv4_3"]
            )

            // TODO: check that the usage of `padding="VALID"` is correct
            // TODO: check that the 1x1 convs actually use relu
            // Modifications to vgg16

After Change

                inputs_rank = inputs_shape.ndims
                dtype = vgg_conv4_3.dtype.base_dtype

                norm_dim = tf.range(inputs_rank - 1, inputs_rank)
                params_shape = inputs_shape[-1:]

                vgg_conv4_3_norm = tf.nn.l2_normalize(
                    vgg_conv4_3, norm_dim, epsilon=1e-12

Instances