Added test to check if torch implementation matches reference numpy implementation

Author: kamathhrishi

test/torch/differential_privacy/test_pate.py

@@ -37,3 +37,26 @@ def test_base_dataset_torch():
     )
 
     assert data_dep_eps < data_ind_eps
+
+
+def test_torch_ref_match():
+
+    # Verify if the torch implementation values match the original Numpy implementation.
+
+    num_teachers, num_examples, num_labels = (100, 50, 10)
+    preds = (np.random.rand(num_teachers, num_examples) * num_labels).astype(int)  # fake preds
+
+    indices = (np.random.rand(num_examples) * num_labels).astype(int)  # true answers
+
+    preds[:, 0:10] *= 0
+
+    data_dep_eps, data_ind_eps = pate.perform_analysis_torch(
+        preds, indices, noise_eps=0.1, delta=1e-5
+    )
+
+    data_dep_eps_ref, data_ind_eps_ref = pate.perform_analysis(
+        preds, indices, noise_eps=0.1, delta=1e-5
+    )
+
+    assert torch.isclose(data_dep_eps, torch.tensor(data_dep_eps_ref.item()))
+    assert torch.isclose(data_ind_eps, torch.tensor(data_ind_eps_ref.item()))