[numpy] Fix users of NumPy APIs that are removed in NumPy 2.0.

This change migrates users of APIs removed in NumPy 2.0 to their recommended replacements (https://numpy.org/doc/stable/numpy_2_0_migration_guide.html).

This change replaces uses of `np.math`, which is a deprecated alias for the builtin `math` module, with the builtin `math` module. `np.math` is removed in NumPy 2.0.

PiperOrigin-RevId: 660122558

tensorflow_probability/python/distributions/gumbel_test.py

@@ -14,15 +14,16 @@
 # ============================================================================
 """Tests for Gumbel."""
 
+import math
+
 # Dependency imports
+
 import numpy as np
 from scipy import stats
-
 import tensorflow.compat.v1 as tf1
 import tensorflow.compat.v2 as tf
 from tensorflow_probability.python.distributions import gumbel
 from tensorflow_probability.python.distributions import kullback_leibler
-
 from tensorflow_probability.python.internal import test_util
 
 
@@ -258,12 +259,16 @@ def testGumbelGumbelKL(self):
     a = gumbel.Gumbel(loc=a_loc, scale=a_scale, validate_args=True)
     b = gumbel.Gumbel(loc=b_loc, scale=b_scale, validate_args=True)
 
-    true_kl = (np.log(b_scale) - np.log(a_scale)
-               + np.euler_gamma * (a_scale / b_scale - 1.)
-               + np.expm1((b_loc - a_loc) / b_scale
-                          + np.vectorize(np.math.lgamma)(a_scale / b_scale
-                                                         + 1.))
-               + (a_loc - b_loc) / b_scale)
+    true_kl = (
+        np.log(b_scale)
+        - np.log(a_scale)
+        + np.euler_gamma * (a_scale / b_scale - 1.0)
+        + np.expm1(
+            (b_loc - a_loc) / b_scale
+            + np.vectorize(math.lgamma)(a_scale / b_scale + 1.0)
+        )
+        + (a_loc - b_loc) / b_scale
+    )
 
     kl = kullback_leibler.kl_divergence(a, b)
 

tensorflow_probability/python/distributions/weibull_test.py

@@ -13,10 +13,12 @@
 # limitations under the License.
 # ============================================================================
 """Tests for Weibull distribution."""
+import math
+
 # Dependency imports
+
 import numpy as np
 from scipy import stats
-
 import tensorflow.compat.v2 as tf
 from tensorflow_probability.python.distributions import gamma
 from tensorflow_probability.python.distributions import kullback_leibler
@@ -274,12 +276,18 @@ def testWeibullWeibullKL(self):
 
     kl = kullback_leibler.kl_divergence(a, b)
     expected_kl = (
-        np.log(a_concentration / a_scale**a_concentration) -
-        np.log(b_concentration / b_scale**b_concentration) +
-        ((a_concentration - b_concentration) *
-         (np.log(a_scale) - np.euler_gamma / a_concentration)) +
-        ((a_scale / b_scale)**b_concentration *
-         np.exp(np.math.lgamma(b_concentration / a_concentration + 1.))) - 1.)
+        np.log(a_concentration / a_scale**a_concentration)
+        - np.log(b_concentration / b_scale**b_concentration)
+        + (
+            (a_concentration - b_concentration)
+            * (np.log(a_scale) - np.euler_gamma / a_concentration)
+        )
+        + (
+            (a_scale / b_scale) ** b_concentration
+            * np.exp(math.lgamma(b_concentration / a_concentration + 1.0))
+        )
+        - 1.0
+    )
 
     x = a.sample(int(1e5), seed=test_util.test_seed())
     kl_samples = a.log_prob(x) - b.log_prob(x)