Update test_core.py to use tolerance rather than stdev

UnitTests/test_core.py

@@ -1,9 +1,9 @@
 import unittest
-from unittest.mock import patch, mock_open
+from unittest.mock import patch
 from tempfile import TemporaryDirectory
 
 import os
-import glob
+import math
 import random
 import numpy as np
 import pandas as pd
@@ -115,11 +115,13 @@ def __init__(self):
             self.conv1 = nn.Conv2d(1, 20, 5)
             self.bn1 = nn.BatchNorm2d(20)
 
-    def is_normal_distribution(self, tensor, mean, std, num_std=3):
-        # Calculate Z-score
-        z_scores = (tensor - mean) / std
-        # Check if values are within num_std standard deviations
-        return torch.all(torch.abs(z_scores) < num_std).item()
+
+    def is_normal_distribution(self, tensor, mean, std, tolerance=0.01):
+        # Check if the mean of the tensor is close to the expected mean
+        mean_close = math.isclose(tensor.mean().item(), mean, abs_tol=tolerance)
+        # Check if the standard deviation of the tensor is close to the expected std
+        std_close = math.isclose(tensor.std().item(), std, abs_tol=tolerance)
+        return mean_close and std_close
 
     def setUp(self):
         self.net = test_NetworkWeights.MockNetwork()