The calflops is designed to calculate FLOPs、MACs and Parameters in all various neural networks, such as Linear、 CNN、 RNN、 GCN、Transformer(Bert、LlaMA etc Large Language Model)
I think the result FLOPs and MACs are influenced not only by input length but also output length, I'm I right?
If yes, is the tool considering out put length? How to control the output length?
Of course, it is relevant. The calculation of FLOPs here strictly defaults to the calculation amount of the prefill phase of the model, which can be regarded as the default output of a token.
I think the result FLOPs and MACs are influenced not only by input length but also output length, I'm I right? If yes, is the tool considering out put length? How to control the output length?