如何将在 tensorflow 2 中训练的模型转换为 tensorflow 1 冻结图

Question

我想使用 tensorflow 2 训练模型，但之后我需要使用仅与 tensorflow 1 兼容的转换器。是否可能，如果可以，如何将使用 tensorflow 2 训练的模型转换为 tensorflow 1 格式？

Answer 1

If there is no method that reliably converts your TF2 model to TF1, you can always save the trained parameters (weights, biases) and used them later to initiate your TF1 graph. I did it for some other purpose before. You can save as follows:

weights = []
for layer in model.layers:

    w = layer.get_weights()
    if len(w)>0:
      print(layer.name)
      weights.append(w)


with open('mnist_weights.pkl', 'wb') as f:
  pickle.dump(weights, f)  

Where for each layer w[0]=weights and w[1]=biases