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Misleading of the MACS and FLOPS #40

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ProNoobLi opened this issue May 6, 2020 · 1 comment
Open

Misleading of the MACS and FLOPS #40

ProNoobLi opened this issue May 6, 2020 · 1 comment
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@ProNoobLi
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Hey, it's a nice tool
However, I am wondering whether the return of get_model_complexity_info is correct.

Let's assume all calculations are in floating point.
1MACs = 2OPs
MAC = Mult + Add
FLOPS = 2MACS(roughly equivalent, especially those models set up by all convolutional layers)

Thus, in your code:
image
The returns show flops_count, params_count

However, all printing result from the function flops_to_string are in Mac
image
The return type is not consistent with the example as well
image

The units in flops_to_string are supposed to be flops instead of mac. Otherwise, half the flops to macs. Could you please check it out again?

@sovrasov
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sovrasov commented May 7, 2020

Hi! There is no problem here: everywhere variables named flops are handled as macs. The code needs refactoring to get rid of this confusion.

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