train.py 文件源码

def CNN(input_shape=None, classes=1000):
    inputs = Input(shape=input_shape)

    # Block 1
    x = GaussianNoise(0.3)(inputs)
    x = CBRD(x, 64)
    x = CBRD(x, 64)
    x = MaxPooling2D()(x)

    # Block 2
    x = CBRD(x, 128)
    x = CBRD(x, 128)
    x = MaxPooling2D()(x)

    # Block 3
    x = CBRD(x, 256)
    x = CBRD(x, 256)
    x = CBRD(x, 256)
    x = MaxPooling2D()(x)

    # Classification block
    x = Flatten(name='flatten')(x)
    x = DBRD(x, 4096)
    x = DBRD(x, 4096)
    x = Dense(classes, activation='softmax', name='predictions')(x)

    model = Model(inputs=inputs, outputs=x)

    return model