output

scripts/training_reg.py

@@ -183,6 +183,7 @@ sampler = torch.utils.data.sampler.WeightedRandomSampler(weights, num_samples= l
 
 dataset_tr = Dataset(data_in_scaled[ixs_tr], data_out_scaled[ixs_tr])
 data_loader_tr = utils_data.DataLoader(dataset_tr, batch_size=BATCH_SIZE, num_workers = 4, shuffle=False, sampler = sampler)
+#data_loader_tr = utils_data.DataLoader(dataset_tr, batch_size=BATCH_SIZE, num_workers = 4, shuffle=True)
 
 class DSTnet(nn.Module):
     def __init__(self, nvars, nhidden_i, nhidden_o, n_out_i, before, after):
@@ -232,9 +233,9 @@ loss_f = nn.L1Loss()
 loss_mse = nn.MSELoss()
 
 
-nhidden_i = 1
-nhidden_o = 64
-n_out_i = 16
+nhidden_i = 2
+nhidden_o = 96
+n_out_i = 8
 before = BEFORE
 nvars = data_in_scaled.shape[-1]
 
@@ -341,8 +342,8 @@ for epoch in range(num_epochs):
 #        dataset_tr = Dataset(data_in_scaled[ixs_tr], data_out_scaled[ixs_tr])
 #        data_loader_tr = utils_data.DataLoader(dataset_tr, batch_size=BATCH_SIZE, num_workers = 4, shuffle=False, sampler = sampler)        
 
-torch.save(dst_net.state_dict(), '/home/mcristofo/DST/models/dst_reg_64_16_all.pth')    
+torch.save(dst_net.state_dict(), '/home/mcristofo/DST/models/dst_reg_96_8_ns.pth')    
 
-np.savetxt('/home/mcristofo/DST/hist/history_tr_rmse_mae_reg_64_16_all.txt', history_tr)
-np.savetxt('/home/mcristofo/DST/hist/history_valid_rmse_mae_reg_64_16_all.txt', history_valid)
-np.savetxt('/home/mcristofo/DST/hist/history_ts_rmse_mae_reg_64_16_all.txt', history_ts)
+np.savetxt('/home/mcristofo/DST/hist/history_tr_rmse_mae_reg_96_8_ns.txt', history_tr)
+np.savetxt('/home/mcristofo/DST/hist/history_valid_rmse_mae_reg_96_8_ns.txt', history_valid)
+np.savetxt('/home/mcristofo/DST/hist/history_ts_rmse_mae_reg_96_8_ns.txt', history_ts)