Implement batch norm test

tools/batch_norm_test.py

@@ -0,0 +1,31 @@
+import torch
+
+from utils import print_cpp_vector
+
+batch_norm = torch.nn.BatchNorm2d(2, track_running_stats=False)
+
+weights = torch.Tensor([0.63508, 0.64903])
+biases= torch.Tensor([0.25079, 0.66841])
+
+batch_norm.weight = torch.nn.Parameter(weights)
+batch_norm.bias = torch.nn.Parameter(biases)
+
+input = torch.Tensor([
+    # Channel 0
+    0.38899, 0.80478, 0.48836, 0.97381,
+    0.57508, 0.60835, 0.65467, 0.00168,
+    0.65869, 0.74235, 0.17928, 0.70349,
+    0.15524, 0.38664, 0.23411, 0.7137,
+    # Channel 1
+    0.32473, 0.15698, 0.314, 0.60888,
+    0.80268, 0.99766, 0.93694, 0.89237,
+    0.13449, 0.27367, 0.53036, 0.18962,
+    0.57672, 0.48364, 0.10863, 0.0571
+]).reshape(1, 2, 4, 4)
+
+output = batch_norm(input)
+print_cpp_vector(output.flatten())
+
+print(batch_norm.running_mean)
+print(batch_norm.running_var)
+