Keras 如何将mobilenet最后一层的输出馈送到Unet模型

我正在尝试使用在imagenet数据集上预先训练的Keras mobilenet模型构建一个图像分割模型。如何进一步训练模型，我想将U-net层添加到现有模型中，并且只训练U-net体系结构的层，以mobilenet模型作为主干

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问题：mobilenet模型的最后一层尺寸为7x7x1024，这是一个RelU层，我希望将其重新塑造为256x256x3，U-net输入层可以理解它。

不是最后一层，但可以使用以下代码在mobilenet上创建unet：

ALPHA = 1 # Width hyper parameter for MobileNet (0.25, 0.5, 0.75, 1.0). Higher width means more accurate but slower

IMAGE_HEIGHT = 224
IMAGE_WIDTH = 224

HEIGHT_CELLS = 28
WIDTH_CELLS = 28

def create_model(trainable=True):
    model = MobileNet(input_shape=(IMAGE_HEIGHT, IMAGE_WIDTH, 3), include_top=False, alpha=ALPHA, weights="imagenet")

    block0 = model.get_layer("conv_pw_1_relu").output 
    block = model.get_layer("conv_pw_1_relu").output
    block1 = model.get_layer("conv_pw_3_relu").output
    block2 = model.get_layer("conv_pw_5_relu").output
    block3 = model.get_layer("conv_pw_11_relu").output
    block4 = model.get_layer("conv_pw_13_relu").output

    x = Concatenate()([UpSampling2D()(block4), block3])
    x = Concatenate()([UpSampling2D()(x), block2])
    x = Concatenate()([UpSampling2D()(x), block1])
    x = Concatenate()([UpSampling2D()(x), block])
 #   x = Concatenate()([UpSampling2D()(x), block0])
    x = UpSampling2D()(x)
    x = Conv2D(1, kernel_size=1, activation="sigmoid")(x)

    x = Reshape((IMAGE_HEIGHT, IMAGE_HEIGHT))(x)

    return Model(inputs=model.input, outputs=x)

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不是最后一层，但可以使用以下代码在mobilenet上创建unet：

ALPHA = 1 # Width hyper parameter for MobileNet (0.25, 0.5, 0.75, 1.0). Higher width means more accurate but slower

IMAGE_HEIGHT = 224
IMAGE_WIDTH = 224

HEIGHT_CELLS = 28
WIDTH_CELLS = 28

def create_model(trainable=True):
    model = MobileNet(input_shape=(IMAGE_HEIGHT, IMAGE_WIDTH, 3), include_top=False, alpha=ALPHA, weights="imagenet")

    block0 = model.get_layer("conv_pw_1_relu").output 
    block = model.get_layer("conv_pw_1_relu").output
    block1 = model.get_layer("conv_pw_3_relu").output
    block2 = model.get_layer("conv_pw_5_relu").output
    block3 = model.get_layer("conv_pw_11_relu").output
    block4 = model.get_layer("conv_pw_13_relu").output

    x = Concatenate()([UpSampling2D()(block4), block3])
    x = Concatenate()([UpSampling2D()(x), block2])
    x = Concatenate()([UpSampling2D()(x), block1])
    x = Concatenate()([UpSampling2D()(x), block])
 #   x = Concatenate()([UpSampling2D()(x), block0])
    x = UpSampling2D()(x)
    x = Conv2D(1, kernel_size=1, activation="sigmoid")(x)

    x = Reshape((IMAGE_HEIGHT, IMAGE_HEIGHT))(x)

    return Model(inputs=model.input, outputs=x)

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什么是mobilenet任务？如何调整？mobilenet的任务是什么？它是如何调整的？我在执行此操作时遇到OOM错误，对我有任何引用吗？抱歉，我必须重新启动并运行内核，错误再次消失谢谢。我在执行此操作时遇到OOM错误，对我有任何引用吗？抱歉，我必须重新启动并运行内核，错误再次消失谢谢。