[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: 495546406
Change-Id: Iaf1bfd2000fee1bffada5138ae16ec192916c076

alphafold/data/templates.py

@@ -89,8 +89,8 @@ TEMPLATE_FEATURES = {
     'template_aatype': np.float32,
     'template_all_atom_masks': np.float32,
     'template_all_atom_positions': np.float32,
-    'template_domain_names': np.object,
-    'template_sequence': np.object,
+    'template_domain_names': object,
+    'template_sequence': object,
     'template_sum_probs': np.float32,
 }
 
@@ -1002,8 +1002,8 @@ class HmmsearchHitFeaturizer(TemplateHitFeaturizer):
               (1, num_res, residue_constants.atom_type_num), np.float32),
           'template_all_atom_positions': np.zeros(
               (1, num_res, residue_constants.atom_type_num, 3), np.float32),
-          'template_domain_names': np.array([''.encode()], dtype=np.object),
-          'template_sequence': np.array([''.encode()], dtype=np.object),
+          'template_domain_names': np.array([''.encode()], dtype=object),
+          'template_sequence': np.array([''.encode()], dtype=object),
           'template_sum_probs': np.array([0], dtype=np.float32)
       }
     return TemplateSearchResult(

alphafold/notebooks/notebook_utils.py

@@ -137,8 +137,8 @@ def empty_placeholder_template_features(
       'template_all_atom_positions': np.zeros(
           (num_templates, num_res, residue_constants.atom_type_num, 3),
           dtype=np.float32),
-      'template_domain_names': np.zeros([num_templates], dtype=np.object),
-      'template_sequence': np.zeros([num_templates], dtype=np.object),
+      'template_domain_names': np.zeros([num_templates], dtype=object),
+      'template_sequence': np.zeros([num_templates], dtype=object),
       'template_sum_probs': np.zeros([num_templates], dtype=np.float32),
   }