Implement kl divergence methods and tests

tests/test_metrics.py

@@ -0,0 +1,18 @@
+import torch
+import numpy as np
+
+from src import metrics
+from src.metrics import divergence
+
+def test_kl_divergence():
+    p = torch.randn(1000000)
+    q = 1.0 + 2.0 * torch.randn(1000000)
+
+    d1 = divergence(p, q, type='kl', n_components=0)
+    assert isinstance(d1, float)
+    d2 = divergence(p, q, type='kl', n_components=1)
+    assert isinstance(d2, float)
+    assert np.isclose(d1, d2, atol=1e-5)
+    d3 = divergence(p, q, type='kl', n_components=3)
+    assert isinstance(d3, float)
+