Reconsider Loss generic parameter

I brought this up with @JimClarke5 but wanted to get some wider comments on it.

The generic parameter for Losses doesn't seem right:

<T extends TNumber> Operand<T> call(Ops tf, Operand<? extends TNumber> labels, Operand<T> predictions, Operand<T> sampleWeights);

It binds the loss value, the predictions, and the weights to the same data type. There is no relation there: it's easy enough to imagine float-weighted cosine similarity of one hot vector predictions, which would return a float. The only necessary data type parameter I can think of is the return type, and that should be on the class.

从 issue 中显示的 Loss 泛型方法签名开始，检查周围的 Loss API 及其调用方。查看现有的评论讨论，确认对类型关系的共识。泛型设计确定，并且受影响的 API 和调用方一致反映该决定，即视为完成。