[NumPy] Remove references to deprecated NumPy type aliases.

This change replaces references to a number of deprecated NumPy type aliases (np.bool, np.int, np.float, np.complex, np.object, np.str) with their recommended replacement (bool, int, float, complex, object, str).

NumPy 1.24 drops the deprecated aliases, so we must remove uses before updating NumPy.

PiperOrigin-RevId: 501824360

rigl/experimental/jax/datasets/cifar10_test.py

@@ -49,7 +49,7 @@ def test_train_image_dims_content(self):
       self.assertTupleEqual(image.shape, (self._batch_size, 32, 32, 3))
 
     with self.subTest(name='DataType'):
-      self.assertTrue(np.issubdtype(image.dtype, np.float))
+      self.assertTrue(np.issubdtype(image.dtype, float))
 
     with self.subTest(name='DataValues'):
       # Normalized by stddev., expect nothing to fall outside 3 stddev.
@@ -59,7 +59,7 @@ def test_train_image_dims_content(self):
       self.assertLen(label, self._batch_size)
 
     with self.subTest(name='LabelType'):
-      self.assertTrue(np.issubdtype(label.dtype, np.int))
+      self.assertTrue(np.issubdtype(label.dtype, int))
 
     with self.subTest(name='LabelValues'):
       self.assertTrue((label >= 0).all() and
@@ -75,7 +75,7 @@ def test_test_image_dims_content(self):
       self.assertTupleEqual(image.shape, (self._batch_size_test, 32, 32, 3))
 
     with self.subTest(name='DataType'):
-      self.assertTrue(np.issubdtype(image.dtype, np.float))
+      self.assertTrue(np.issubdtype(image.dtype, float))
 
     with self.subTest(name='DataValues'):
       # Normalized by stddev., expect nothing to fall outside 3 stddev.
@@ -85,7 +85,7 @@ def test_test_image_dims_content(self):
       self.assertLen(label, self._batch_size_test)
 
     with self.subTest(name='LabelType'):
-      self.assertTrue(np.issubdtype(label.dtype, np.int))
+      self.assertTrue(np.issubdtype(label.dtype, int))
 
     with self.subTest(name='LabelValues'):
       self.assertTrue((label >= 0).all() and

rigl/experimental/jax/datasets/mnist_test.py

@@ -52,13 +52,13 @@ def test_train_image_dims_content(self):
       self.assertTrue((image >= -1.).all() and (image <= 1.).all())
 
     with self.subTest(name='data_type'):
-      self.assertTrue(np.issubdtype(image.dtype, np.float))
+      self.assertTrue(np.issubdtype(image.dtype, float))
 
     with self.subTest(name='label_shape'):
       self.assertLen(label, self._batch_size)
 
     with self.subTest(name='label_type'):
-      self.assertTrue(np.issubdtype(label.dtype, np.int))
+      self.assertTrue(np.issubdtype(label.dtype, int))
 
     with self.subTest(name='label_values'):
       self.assertTrue((label >= 0).all() and
@@ -74,7 +74,7 @@ def test_test_image_dims_content(self):
       self.assertTupleEqual(image.shape, (self._batch_size_test, 28, 28, 1))
 
     with self.subTest(name='data_type'):
-      self.assertTrue(np.issubdtype(image.dtype, np.float))
+      self.assertTrue(np.issubdtype(image.dtype, float))
 
     # TODO: Find a better approach to testing with JAX arrays.
     with self.subTest(name='data_values'):
@@ -84,7 +84,7 @@ def test_test_image_dims_content(self):
       self.assertLen(label, self._batch_size_test)
 
     with self.subTest(name='label_type'):
-      self.assertTrue(np.issubdtype(label.dtype, np.int))
+      self.assertTrue(np.issubdtype(label.dtype, int))
 
     with self.subTest(name='label_values'):
       self.assertTrue((label >= 0).all() and