1973269eb8554237642cc5912f61269ae8f1ae1d,dataset/models/tf/linknet.py,LinkNet,decoder_block,#Any#Any#Any#Any#,106

Before Change

        tf.Tensor
        
        num_filters = inputs.get_shape()[-1].value // 4
        return conv_block(inputs, "cna tna cna", [num_filters, num_filters, filters], [1, 3, 1],
                          name=name, strides=[1, 2, 1], **kwargs)

    @classmethod
    def head(cls, inputs, targets, num_classes, name="head", **kwargs):
         3x3 transposed convolution, 3x3 convolution and 2x2 transposed convolution

After Change

        with tf.variable_scope(name):
            x = conv_block(inputs, "cna", num_filters, kernel_size=1, name="conv_pre", **kwargs)
            x = cls.upsample(x, filters=num_filters, name="upsample", **upsample_args)
            x = conv_block(x, "cna", filters, kernel_size=1, name="conv_post", **kwargs)
        return x

    @classmethod
    def head(cls, inputs, targets, num_classes, name="head", **kwargs):
         3x3 transposed convolution, 3x3 convolution and 2x2 transposed convolution

Instances