python - 使用 TensorFlow.js 加载 Keras 模型时，"The first layer in a Sequential model must get an ` inputShape ` or ` batchInputShape ` argument."

Question

我使用 Keras 训练了以下模型(版本2.2.4):

# imports ...
model = Sequential()
model.add(Conv2D(filters=64, kernel_size=5, data_format="channels_last", activation="relu"))
model.add(BatchNormalization())
model.add(MaxPooling2D(data_format="channels_last"))
model.add(Conv2D(filters=32, kernel_size=3, data_format="channels_last", activation="relu"))
model.add(BatchNormalization())
model.add(MaxPooling2D(data_format="channels_last"))
model.add(Flatten(data_format="channels_last"))
model.add(Dense(units=256, activation="relu"))
model.add(Dense(units=128, activation="relu"))
model.add(Dense(units=32, activation="relu"))
model.add(Dense(units=8, activation="softmax"))
# training ...
model.save("model.h5")

输入是形状为(28, 28, 1)的 28 x 28 灰度图像。

我用 tensorflowjs_converter 转换了模型现在我想使用 TensorFlow.js 将其加载到我的网站中(版本1.1.0):

tf.loadLayersModel('./model/model.json')

这会产生以下错误:

The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.
    at new e (errors.ts:48)
    at e.add (models.ts:440)
    at e.fromConfig (models.ts:1020)
    at vp (generic_utils.ts:277)
    at nd (serialization.ts:31)
    at models.ts:299
    at common.ts:14
    at Object.next (common.ts:14)
    at o (common.ts:14)

如何在无需重新训练模型的情况下修复此错误？

Answer 1

尝试将你的神经网络调整为这种格式:

input_img = Input(batch_shape=(None, 28,28,1))
layer1=Conv2D(filters=64, kernel_size=5, data_format="channels_last", activation="relu")(input_img)
layer2=BatchNormalization()(layer1)
.
.
.
final_layer=Dense(units=8, activation="softmax")(previous_layer)

...等等。最后:

model = Model(inputs = input_img, outputs = final_layer)