contrib/document_cleanup/light_weight_document_cleanup_ICDAR2021/model.py [137:159]:
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    out = layers.Conv2D(16, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(X_input)
    out = layers.BatchNormalization()(out)
    shortcut3 = out
    out = layers.Conv2D(32, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    shortcut2 = out
    out = layers.Conv2D(64, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    shortcut1 = out
    out = res_net_block(out, 64, 3)
    out = res_net_block(out, 64, 3)
    out = res_net_block(out, 64, 3)
    out = res_net_block(out, 64, 3)
    out = res_net_block(out, 64, 3)
    out = layers.add([shortcut1, out])
    out = layers.Conv2D(64, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    out = layers.Conv2D(32, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    out = layers.add([shortcut2, out])
    out = layers.Conv2D(16, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    out = layers.add([shortcut3, out])
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contrib/document_cleanup/light_weight_document_cleanup_ICDAR2021/model.py [173:195]:
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    out = layers.Conv2D(16, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(X_input)
    out = layers.BatchNormalization()(out)
    shortcut3 = out
    out = layers.Conv2D(32, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    shortcut2 = out
    out = layers.Conv2D(64, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    shortcut1 = out
    out = res_net_block(out, 64, 3)
    out = res_net_block(out, 64, 3)
    out = res_net_block(out, 64, 3)
    out = res_net_block(out, 64, 3)
    out = res_net_block(out, 64, 3)
    out = layers.add([shortcut1, out])
    out = layers.Conv2D(64, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    out = layers.Conv2D(32, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    out = layers.add([shortcut2, out])
    out = layers.Conv2D(16, kernel_size=(3, 3),activation=tf.nn.relu6, strides=_strides, padding='same',kernel_initializer = 'he_normal')(out)
    out = layers.BatchNormalization()(out)
    out = layers.add([shortcut3, out])
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