From 1a35d08f669a734b7d96fa7e7a47a3d3a984eb2a Mon Sep 17 00:00:00 2001
From: Eduardo Cueto-Mendoza <cueto303@gmail.com>
Date: Tue, 30 Jul 2024 14:14:18 +0100
Subject: [PATCH] Finally entropy and efficiency are on the same scale

---
 .gitignore       |  1 +
 functions.py     | 16 ++++++++++------
 general_plots.py | 14 +++++++-------
 get_entropy.py   | 20 +++++++++++++++-----
 4 files changed, 33 insertions(+), 18 deletions(-)

diff --git a/.gitignore b/.gitignore
index 5642422..1a4925e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,3 @@
 __pycache__/
 *.pkl
+*.png
diff --git a/functions.py b/functions.py
index 1c1e442..685c000 100644
--- a/functions.py
+++ b/functions.py
@@ -46,9 +46,11 @@ def neumann_entropy(tensor):
     if len(tensor_size) == 1:
         return 0
     elif len(tensor_size) == 2:
-        e = alg.eigvals(tensor)
-        # temp_abs = torch.abs(e)
-        temp_abs = e.real
+        e = alg.eigvals(tensor)#.real
+        #se = sum(e)
+        #e = e / se
+        temp_abs = torch.abs(e)
+        #temp_abs = e
         temp = torch.log(temp_abs).real
         temp = torch.nan_to_num(temp,
                                 nan=0.0, posinf=0.0, neginf=0.0)
@@ -56,9 +58,11 @@ def neumann_entropy(tensor):
     elif len(tensor_size) > 2:
         for i, x in enumerate(tensor):
             for j, t in enumerate(x):
-                e = alg.eigvals(t)
-                # temp_abs = torch.abs(e)
-                temp_abs = e.real
+                e = alg.eigvals(t)#.real
+                #se = sum(e)
+                #e = e / se
+                temp_abs = torch.abs(e)
+                # temp_abs = e
                 temp = torch.log(temp_abs).real
                 temp = torch.nan_to_num(temp,
                                         nan=0.0, posinf=0.0, neginf=0.0)
diff --git a/general_plots.py b/general_plots.py
index ae59af8..32c1b87 100644
--- a/general_plots.py
+++ b/general_plots.py
@@ -18,12 +18,12 @@ lenet_keys = ['conv1.weight', 'conv1.bias', 'conv2.weight', 'conv2.bias',
               'fc3.bias']
 
 for size in range(1, 8):
-    if size != 8:
-        plt.plot(eff_df['CIFAR']['BCNN'][size],
-                 label='Efficiency size {}'.format(size))
-        plt.plot(entropy_data['CIFAR']['BCNN'][size],
-                 label='Entropy size {}'.format(size))
+    # if size != 8:
+    plt.plot(eff_df['MNIST']['BCNN'][size],
+             label='Efficiency size {}'.format(size))
+    plt.plot(entropy_data['MNIST']['BCNN'][size],
+             label='Entropy size {}'.format(size))
 
-# plt.legend(loc='upper right')
-plt.legend(loc='lower right')
+plt.legend(loc='upper right')
+# plt.legend(loc='lower right')
 plt.show()
diff --git a/get_entropy.py b/get_entropy.py
index 2824295..4b00a2e 100644
--- a/get_entropy.py
+++ b/get_entropy.py
@@ -1,6 +1,8 @@
 import functions as aux
 import statistics as st
 
+alpha = 100000
+
 models_bayes_cifar = aux.load_pickle("bayes_data_cifar.pkl")
 models_bayes_mnist = aux.load_pickle("bayes_data_mnist.pkl")
 models_lenet_cifar = aux.load_pickle("lenet_data_cifar.pkl")
@@ -34,7 +36,6 @@ bayes_keys = ['conv1.W_mu', 'conv1.W_rho', 'conv1.bias_mu', 'conv1.bias_rho',
 lenet_keys = ['conv1.weight', 'conv1.bias', 'conv2.weight', 'conv2.bias',
               'fc1.weight', 'fc1.bias', 'fc2.weight', 'fc2.bias', 'fc3.weight',
               'fc3.bias']
-"""
 
 bayes_keys = ['conv1.W_mu', 'conv1.W_rho',
               'conv2.W_mu', 'conv2.W_rho',
@@ -42,6 +43,15 @@ bayes_keys = ['conv1.W_mu', 'conv1.W_rho',
               'fc2.W_mu', 'fc2.W_rho',
               'fc3.W_mu', 'fc3.W_rho']
 
+"""
+
+bayes_keys = ['conv1.W_mu',
+              'conv2.W_mu',
+              'fc1.W_mu',
+              'fc2.W_mu',
+              'fc3.W_mu',]
+
+
 lenet_keys = ['conv1.weight', 'conv2.weight',
               'fc1.weight', 'fc2.weight', 'fc3.weight']
 
@@ -67,7 +77,7 @@ for size in range(1, 8):
         temp_epoch.append(
             temp_mean
         )
-    entropy_data['CIFAR']['BCNN'][size] = temp_epoch
+    entropy_data['CIFAR']['BCNN'][size] = [x / alpha for x in temp_epoch]# temp_epoch
 
 # aux.save_pickle("bayes_data_cifar_ne.pkl", models_bayes_cifar)
 del models_bayes_cifar
@@ -94,7 +104,7 @@ for size in range(1, 8):
         temp_epoch.append(
             temp_mean
         )
-    entropy_data['MNIST']['BCNN'][size] = temp_epoch
+    entropy_data['MNIST']['BCNN'][size] = [x / alpha for x in temp_epoch]# temp_epoch
 
 # aux.save_pickle("bayes_data_mnist_ne.pkl", models_bayes_mnist)
 del models_bayes_mnist
@@ -121,7 +131,7 @@ for size in range(1, 8):
         temp_epoch.append(
             temp_mean
         )
-    entropy_data['CIFAR']['LeNet'][size] = temp_epoch
+    entropy_data['CIFAR']['LeNet'][size] = [x / alpha for x in temp_epoch]# temp_epoch
 
 # aux.save_pickle("lenet_data_cifar_ne.pkl", models_lenet_cifar)
 del models_lenet_cifar
@@ -148,7 +158,7 @@ for size in range(1, 8):
         temp_epoch.append(
             temp_mean
         )
-    entropy_data['MNIST']['LeNet'][size] = temp_epoch
+    entropy_data['MNIST']['LeNet'][size] = [x / alpha for x in temp_epoch]# temp_epoch
 
 
 # aux.save_pickle("lenet_data_mnist_ne.pkl", models_lenet_mnist)