diff --git a/rg_examples/nn_Conv2d.py b/rg_examples/nn_Conv2d.py
new file mode 100644
index 00000000000000..2175df10ba48bd
--- /dev/null
+++ b/rg_examples/nn_Conv2d.py
@@ -0,0 +1,16 @@
+import torch
+import torch.nn as nn
+
+
+# Create a random input tensor
+in_tensor = torch.randn(1, 3, 448, 448).to('cuda')
+
+# Create a simple convolutional layer
+conv_2d = nn.Conv2d(in_channels=3, out_channels=32, kernel_size=3, padding=1).to('cuda')
+
+# Perform convolution
+output = conv_2d(in_tensor)
+
+print(f"Input shape: {in_tensor.shape}")
+print(f"Output shape: {output.shape}")
+print("Convolution completed successfully")