fix c2st-knn bug and add simple example

labproject/metrics/c2st.py

@@ -2,6 +2,7 @@
 
 import numpy as np
 import torch
+import inspect
 from torch import ones, zeros, eye, sum, Tensor, tensor, allclose, manual_seed
 from torch.distributions import MultivariateNormal, Normal
 from sklearn.ensemble import RandomForestClassifier
@@ -332,7 +333,9 @@ def c2st_scores(
     X = X.cpu().numpy()
     Y = Y.cpu().numpy()
 
-    clf = clf_class(random_state=seed, **clf_kwargs)
+    if "random_state" in inspect.signature(clf_class.__init__).parameters.keys():
+        clf_kwargs["random_state"] = seed
+    clf = clf_class(**clf_kwargs)
 
     # prepare data
     data = np.concatenate((X, Y))
@@ -382,3 +385,15 @@ def test_optimal_c2st():
     c2st = c2st_optimal(d1, d2, 100_000)
     target = Normal(0.0, 1.0).cdf(tensor(mean_diff // 2))
     assert allclose(c2st, target, atol=1e-3)
+
+
+if __name__ == "__main__":
+    # Generate random samples
+    samples1 = torch.randn(100, 2)
+    samples2 = torch.randn(100, 2)
+
+    # Compute sliced wasserstein distance
+    c2st_nn_score = c2st_nn(samples1, samples2)
+    c2st_knn_score = c2st_knn(samples1, samples2)
+    c2st_rf_score = c2st_rf(samples1, samples2)
+    print(f"C2ST-NN: {c2st_nn_score}\nC2ST-KNN: {c2st_knn_score}\nC2ST-RF: {c2st_rf_score}")