MWE fortran python #33
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TomMelt
added this to the Create two MWEs (Python / Fortran) that run inference for a given set of inputs milestone
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TomMelt
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Jan 16, 2025
| @@ -16,7 +13,7 @@ def Inference_and_Save_ANN_CNN(model, testset, testloader, bs_test, device, sten | |||
| nx = len(lon) | |||
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| model.eval() | |||
| model.dropout.train() # this enables dropout during inference. By default dropout is OFF when model.eval()=True | |||
| # model.dropout.train() # this enables dropout during inference. By default dropout is OFF when model.eval()=True | |||
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@amangupta2 , is this ok to disable? or do we need it for inference
TomMelt
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Jan 16, 2025
quick_inference_script/infer.f90
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| call torch_model_load(model, "saved_nlgw_model_gpu.pt", device_type=torch_kCUDA, device_index=0) | ||
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| ! Infer | ||
| ! do i = 1, 100 |
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this loop can be removed
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TomMelt
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Feb 5, 2025
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| # if self.fac == 1: | ||
| # x = torch.squeeze(self.dropout0(self.act_cnn(self.conv1(x)))) | ||
| # elif self.fac == 2: | ||
| # x = torch.squeeze(self.dropout0(self.act_cnn(self.conv1(x)))) | ||
| # x = torch.squeeze(self.dropout0_2(self.act_cnn2(self.conv2(x)))) |
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we should find a proper solution to this for torchscripting
TomMelt
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Feb 5, 2025
| @@ -189,6 +192,22 @@ def Inference_and_Save_ANN_CNN(model, testset, testloader, bs_test, device, sten | |||
| OUT = OUT.reshape(T[0] * T[1], -1) | |||
| PRED = model(INP) | |||
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| print("saving data...") | |||
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make this part optional via command line args
This was referenced Feb 5, 2025
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This PR adds minimum worked examples of inference in python and fortran
README.mdcloses #11
closes #25