def create_keras_model():
model = Sequential([
Conv2D(16, 3, padding='same', activation='relu'),
MaxPooling2D(),
Conv2D(32, 3, padding='same', activation='relu'),
MaxPooling2D(),
Conv2D(64, 3, padding='same', activation='relu'),
MaxPooling2D(),
Flatten(),
Dense(512, activation='relu', kernel_regularizer=tf.keras.regularizers.l2(0.001)),
Dropout(0.5),
Dense(1, activation='sigmoid')
])
model.load_weights('/content/drive/My Drive/localmodel/weights')
return model
在 Colab 中尝试过类似的操作,但我得到 errno 21,是一个目录。
然后我尝试了另一种方法,如下所示,
tff_model = create_keras_model() #now this function doesnt load weights, just returns a Sequential model
tff.learning.assign_weights_to_keras_model(tff_model, model_with_weights)
就像 assign_weights_to_keras_model() 将权重从 tff_model 转移到 keras 模型一样,我想将权重从 keras 模型转移到 tff_model。如何才能做到这一点?