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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:
The returns show flops_count, params_count
However, all printing result from the function flops_to_string are in Mac
The return type is not consistent with the example as well
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?
The text was updated successfully, but these errors were encountered:
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:
The returns show flops_count, params_count
However, all printing result from the function flops_to_string are in Mac
The return type is not consistent with the example as well
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?
The text was updated successfully, but these errors were encountered: