Keras重置层号 [英] Keras reset layer numbers

问题描述

Keras将递增的ID号分配给相同类型的层，例如max_pooling1d_7，max_pooling1d_8，max_pooling1d_9等我的代码的每次迭代都会构造一个新模型，从model = Sequential()开始，然后通过model.add()添加图层.即使每个循环都创建一个新的顺序对象，图层ID编号仍会从上一个循环开始继续递增.由于我的流程长期运行，因此这些ID号可能会变得非常大.我担心这可能会引起一些问题.为什么model = Sequential()无法重置ID?有没有办法重置它们?在每个周期之后，我不再使用层ID号，可以将其丢弃，但是如何?我正在使用Tensorflow后端.

Keras assigns incrementing ID numbers to layers of the same type, e.g. max_pooling1d_7, max_pooling1d_8, max_pooling1d_9,etc. Each iteration of my code constructs a new model, starting with model = Sequential() and then adding layers via model.add(). Even though each cycle creates a new Sequential object, the layer ID numbers continue incrementing from the previous cycle. Since my process is long-running these ID numbers can grow very large. I am concerned that this could cause some problem. Why are the IDs not reset by model = Sequential()? Is there a way to reset them? After each cycle I have no use for the layer ID numbers and can discard them, but how? I am using the Tensorflow backend.

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