From 13148a5c6a4404961278df54d8f42a7563ec74fa Mon Sep 17 00:00:00 2001
From: Silviu Marian Udrescu <smu226@nyu.edu>
Date: Wed, 29 Apr 2020 13:41:52 -0400
Subject: [PATCH] Add files via upload

---
 Code/RPN_to_pytorch.py                | 4 ----
 Code/S_NN_eval.py                     | 1 -
 Code/S_NN_train.py                    | 1 -
 Code/S_add_bf_on_numbers_on_pareto.py | 3 ---
 Code/S_add_snap_expr_on_pareto.py     | 4 ----
 Code/S_final_gd.py                    | 4 ----
 Code/S_remove_input_neuron.py         | 8 ++++++--
 Code/S_separability.py                | 1 -
 Code/S_symmetry.py                    | 1 -
 9 files changed, 6 insertions(+), 21 deletions(-)

diff --git a/Code/RPN_to_pytorch.py b/Code/RPN_to_pytorch.py
index 4387bba..e0ab887 100644
--- a/Code/RPN_to_pytorch.py
+++ b/Code/RPN_to_pytorch.py
@@ -9,10 +9,6 @@ import torch.nn.functional as F
 import torch.optim as optim 
 import torch.utils.data as utils
 from torch.autograd import Variable
-from sklearn.metrics import roc_curve, auc
-from sklearn.preprocessing import label_binarize
-from sklearn.manifold import TSNE
-import seaborn as sns
 import warnings
 warnings.filterwarnings("ignore")
 import sympy
diff --git a/Code/S_NN_eval.py b/Code/S_NN_eval.py
index 73489d6..2a429b5 100644
--- a/Code/S_NN_eval.py
+++ b/Code/S_NN_eval.py
@@ -3,7 +3,6 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 import torch.optim as optim
-from torchvision import datasets, transforms
 import pandas as pd
 import numpy as np
 import torch
diff --git a/Code/S_NN_train.py b/Code/S_NN_train.py
index 652b17f..3ad9ea7 100644
--- a/Code/S_NN_train.py
+++ b/Code/S_NN_train.py
@@ -3,7 +3,6 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 import torch.optim as optim
-from torchvision import datasets, transforms
 import pandas as pd
 import numpy as np
 import torch
diff --git a/Code/S_add_bf_on_numbers_on_pareto.py b/Code/S_add_bf_on_numbers_on_pareto.py
index de99770..1ecae27 100644
--- a/Code/S_add_bf_on_numbers_on_pareto.py
+++ b/Code/S_add_bf_on_numbers_on_pareto.py
@@ -9,9 +9,6 @@ import torch.nn.functional as F
 import torch.optim as optim 
 import torch.utils.data as utils
 from torch.autograd import Variable
-from sklearn.metrics import roc_curve, auc
-from sklearn.preprocessing import label_binarize
-from sklearn.manifold import TSNE
 import copy
 import warnings
 warnings.filterwarnings("ignore")
diff --git a/Code/S_add_snap_expr_on_pareto.py b/Code/S_add_snap_expr_on_pareto.py
index e66f308..7c45f21 100644
--- a/Code/S_add_snap_expr_on_pareto.py
+++ b/Code/S_add_snap_expr_on_pareto.py
@@ -9,10 +9,6 @@ import torch.nn.functional as F
 import torch.optim as optim 
 import torch.utils.data as utils
 from torch.autograd import Variable
-from sklearn.metrics import roc_curve, auc
-from sklearn.preprocessing import label_binarize
-from sklearn.manifold import TSNE
-import seaborn as sns
 import copy
 import warnings
 warnings.filterwarnings("ignore")
diff --git a/Code/S_final_gd.py b/Code/S_final_gd.py
index b17febe..6b907be 100644
--- a/Code/S_final_gd.py
+++ b/Code/S_final_gd.py
@@ -9,10 +9,6 @@ import torch.nn.functional as F
 import torch.optim as optim 
 import torch.utils.data as utils
 from torch.autograd import Variable
-from sklearn.metrics import roc_curve, auc
-from sklearn.preprocessing import label_binarize
-from sklearn.manifold import TSNE
-import seaborn as sns
 import warnings
 warnings.filterwarnings("ignore")
 import sympy
diff --git a/Code/S_remove_input_neuron.py b/Code/S_remove_input_neuron.py
index 241482c..7ac383a 100644
--- a/Code/S_remove_input_neuron.py
+++ b/Code/S_remove_input_neuron.py
@@ -5,7 +5,6 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 import torch.optim as optim
-from torchvision import datasets, transforms
 import pandas as pd
 import numpy as np
 import torch
@@ -16,6 +15,8 @@ import torch.utils.data as utils
 import time
 import os
 
+is_cuda = torch.cuda.is_available()
+
 def remove_input_neuron(net,n_inp,idx_neuron,ct_median,save_filename):
     removed_weights = net.linear1.weight[:,idx_neuron]
     # Remove the weights associated with the removed input neuron                                                                                                               
@@ -24,6 +25,9 @@ def remove_input_neuron(net,n_inp,idx_neuron,ct_median,save_filename):
     t = nn.Parameter(t[preserved_ids, :])
     net.linear1.weight = nn.Parameter(torch.transpose(t,0,1))
     # Adjust the biases
-    net.linear1.bias = nn.Parameter(net.linear1.bias+torch.tensor(ct_median*removed_weights).float().cuda())
+    if is_cuda:
+        net.linear1.bias = nn.Parameter(net.linear1.bias+torch.tensor(ct_median*removed_weights).float().cuda())
+    else:
+        net.linear1.bias = nn.Parameter(net.linear1.bias+torch.tensor(ct_median*removed_weights).float())
     torch.save(net.state_dict(), save_filename)
 
diff --git a/Code/S_separability.py b/Code/S_separability.py
index df072b6..bdac418 100644
--- a/Code/S_separability.py
+++ b/Code/S_separability.py
@@ -4,7 +4,6 @@ import os
 import torch.nn as nn
 import torch.nn.functional as F
 import torch.optim as optim
-from torchvision import datasets, transforms
 import pandas as pd
 import numpy as np
 import torch
diff --git a/Code/S_symmetry.py b/Code/S_symmetry.py
index a85598c..1b9e475 100644
--- a/Code/S_symmetry.py
+++ b/Code/S_symmetry.py
@@ -6,7 +6,6 @@ import os
 import torch.nn as nn
 import torch.nn.functional as F
 import torch.optim as optim
-from torchvision import datasets, transforms
 import pandas as pd
 import numpy as np
 import torch