Remove usage of deprecated np.bool and np.long (#1851)

* Replace deprecated np.bool with bool in FillMisisng operator * remove unused numpy import * Replace np.long with int
NVIDIA-Merlin · Jul 4, 2023 · 24136ef · 24136ef
1 parent aa5c25c
commit 24136ef
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Showing 2 changed files with 6 additions and 7 deletions.
diff --git a/nvtabular/ops/fill.py b/nvtabular/ops/fill.py
@@ -14,7 +14,6 @@
 # limitations under the License.
 #
 import dask.dataframe as dd
-import numpy as np
 
 from merlin.core.dispatch import DataFrameType, annotate
 from merlin.dag.ops.stat_operator import StatOperator
@@ -75,7 +74,7 @@ def column_mapping(self, col_selector):
     def _compute_dtype(self, col_schema, input_schema):
         col_schema = super()._compute_dtype(col_schema, input_schema)
         if col_schema.name.endswith("_filled"):
-            col_schema = col_schema.with_dtype(np.bool)
+            col_schema = col_schema.with_dtype(bool)
         return col_schema
 
     transform.__doc__ = Operator.transform.__doc__
@@ -143,5 +142,5 @@ def column_mapping(self, col_selector):
     def _compute_dtype(self, col_schema, input_schema):
         col_schema = super()._compute_dtype(col_schema, input_schema)
         if col_schema.name.endswith("_filled"):
-            col_schema = col_schema.with_dtype(np.bool)
+            col_schema = col_schema.with_dtype(bool)
         return col_schema
diff --git a/nvtabular/tools/data_gen.py b/nvtabular/tools/data_gen.py
@@ -114,13 +114,13 @@ def create_cats(self, size, cats_rep, entries=False):
             if col.multi_min and col.multi_max:
                 if HAS_GPU:
                     ser = dist.create_col(
-                        col_size + 1, dtype=np.long, min_val=col.multi_min, max_val=col.multi_max
+                        col_size + 1, dtype=int, min_val=col.multi_min, max_val=col.multi_max
                     )
                     ser = make_series(np.ceil(ser)).astype(ser.dtype)
                     _cumsum = xp.cumsum
                 else:
                     ser = dist.create_col(
-                        col_size + 1, dtype=np.long, min_val=col.multi_min, max_val=col.multi_max
+                        col_size + 1, dtype=int, min_val=col.multi_min, max_val=col.multi_max
                     )
                     ser = make_df(np.ceil(ser))[0]
                     _cumsum = np.cumsum
@@ -130,12 +130,12 @@ def create_cats(self, size, cats_rep, entries=False):
                 offs = offs.astype("int32")
             if HAS_GPU:
                 ser = dist.create_col(
-                    col_size, dtype=np.long, min_val=col.min_val, max_val=col.cardinality
+                    col_size, dtype=int, min_val=col.min_val, max_val=col.cardinality
                 )
                 ser = make_series(np.ceil(ser)).astype(ser.dtype)
             else:
                 ser = dist.create_col(
-                    col_size, dtype=np.long, min_val=col.min_val, max_val=col.cardinality
+                    col_size, dtype=int, min_val=col.min_val, max_val=col.cardinality
                 )
                 ser = make_df(np.ceil(ser))[0]
                 ser = ser.astype("int32")