Create analysis.py

analysis.py

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+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")