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

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merged 4 commits into from
Jul 4, 2023
Merged

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

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d8aefc0
Replace deprecated np.bool with bool in FillMisisng operator
oliverholworthy Jun 23, 2023
be6b283
remove unused numpy import
oliverholworthy Jun 23, 2023
a12c1d8
Replace np.long with int
oliverholworthy Jun 23, 2023
8591b24
Merge branch 'main' into ops-fill-numpy-bool
oliverholworthy Jul 4, 2023
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5 changes: 2 additions & 3 deletions nvtabular/ops/fill.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down Expand Up @@ -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__
Expand Down Expand Up @@ -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
8 changes: 4 additions & 4 deletions nvtabular/tools/data_gen.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand All @@ -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")
Expand Down
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