8fd34961576804563b80c0c8b6bd5ccbc1ce79ae,tensorflow2/tf2cv/models/deeplabv3.py,DeepLabv3FinalBlock,call,#DeepLabv3FinalBlock#Any#Any#Any#,59

Before Change

        x = self.conv1(x, training=training)
        x = self.dropout(x, training=training)
        x = self.conv2(x)
        x_shape = x.get_shape().as_list()
        if is_channels_first(self.data_format):
            height = x_shape[2]
            width = x_shape[3]
        else:
            height = x_shape[1]
            width = x_shape[2]
        x = nn.UpSampling2D(
            size=(out_size[0] // height, out_size[1] // width),
            data_format=self.data_format,
            interpolation="bilinear",
            name="upsample")(x)
        return x


class ASPPAvgBranch(nn.Layer):

After Change

    def call(self, x, out_size, training=None):
        x = self.conv1(x, training=training)
        x = self.dropout(x, training=training)
        x = self.conv2(x)
        x = interpolate_im(x, out_size=out_size, data_format=self.data_format)
        return x


class ASPPAvgBranch(nn.Layer):

Instances