import torch
import fvcore.nn
import fvcore.common
from fvcore.nn import FlopCountAnalysis
from classification_ScanObjectNN.models import pointMLPElite

model = pointMLPElite()
# model = deit_tiny_patch16_224()

inputs = (torch.randn((1,3,1024)),)
k = 1024.0
flops = FlopCountAnalysis(model, inputs).total()
print(f"Flops : {flops}")
flops = flops/(k**3)
print(f"Flops : {flops:.1f}G")
params = fvcore.nn.parameter_count(model)[""]
print(f"Params : {params}")
params = params/(k**2)
print(f"Params : {params:.1f}M")