[REVIEW] Fix operator NotImplemented issue with numpy

[galipremsagar]

Description

Root cause:

In [1]: import numpy as np

In [2]: x = np.uint8(1)

In [3]: y = np.float64(1.0)

In [4]: x.__ge__(y)
Out[4]: NotImplemented

In [8]: x >= y
Out[8]: True

This is leading to the following error whenever there is a Scalar binary operation involved:

python/cudf/cudf/tests/test_series.py:449: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
../envs/cudfdev/lib/python3.9/contextlib.py:79: in inner
    return func(*args, **kwds)
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/series.py:2988: in describe
    data = _describe_categorical(self, percentiles)
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/series.py:152: in _describe_categorical
    val_counts = obj.value_counts(ascending=False)
../envs/cudfdev/lib/python3.9/contextlib.py:79: in inner
    return func(*args, **kwds)
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/series.py:2862: in value_counts
    res = res.sort_values(ascending=ascending)
../envs/cudfdev/lib/python3.9/contextlib.py:79: in inner
    return func(*args, **kwds)
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/series.py:1910: in sort_values
    return super().sort_values(
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/indexed_frame.py:1916: in sort_values
    out = self._gather(
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/indexed_frame.py:1523: in _gather
    if not libcudf.copying._gather_map_is_valid(
copying.pyx:67: in cudf._lib.copying._gather_map_is_valid
    ???
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/mixins/mixin_factory.py:11: in wrapper
    return method(self, *args1, *args2, **kwargs1, **kwargs2)
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/scalar.py:350: in _binaryop
    return Scalar(result, dtype=out_dtype)
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/scalar.py:56: in __call__
    obj = super().__call__(value, dtype=dtype)
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/scalar.py:128: in __init__
    self._host_value, self._host_dtype = self._preprocess_host_value(
../envs/cudfdev/lib/python3.9/site-packages/cudf/core/scalar.py:222: in _preprocess_host_value
    value = to_cudf_compatible_scalar(value, dtype=dtype)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

val = NotImplemented, dtype = <class 'numpy.bool_'>

    def to_cudf_compatible_scalar(val, dtype=None):
        """
        Converts the value `val` to a numpy/Pandas scalar,
        optionally casting to `dtype`.
    
        If `val` is None, returns None.
        """
    
        if cudf._lib.scalar._is_null_host_scalar(val) or isinstance(
            val, cudf.Scalar
        ):
            return val
    
        if not cudf.api.types._is_scalar_or_zero_d_array(val):
>           raise ValueError(
                f"Cannot convert value of type {type(val).__name__} "
                "to cudf scalar"
            )
E           ValueError: Cannot convert value of type NotImplementedType to cudf scalar

../envs/cudfdev/lib/python3.9/site-packages/cudf/utils/dtypes.py:248: ValueError

This PR fixes the issue by first trying to call the op with operator standard library and then try to getattr if the op is not found in operator module.

Checklist

• I am familiar with the Contributing Guidelines.

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[wence-]

Can we add a test, for example:

diff --git a/python/cudf/cudf/tests/test_scalar.py b/python/cudf/cudf/tests/test_scalar.py
index 90268ebabe..1d7c09c70d 100644
--- a/python/cudf/cudf/tests/test_scalar.py
+++ b/python/cudf/cudf/tests/test_scalar.py
@@ -412,6 +412,13 @@ def test_datetime_scalar_from_string(data, dtype):
     assert expected == slr.value
 
 
+def test_scalar_numpy_casting():
+    # binop should upcast to wider type
+    s1 = cudf.Scalar(1, dtype=np.int32)
+    s2 = np.int64(2)
+    assert s1 < s2
+
+
 def test_scalar_cache():
     s = cudf.Scalar(1)
     s2 = cudf.Scalar(1)

[galipremsagar]

+def test_scalar_numpy_casting():
+    # binop should upcast to wider type
+    s1 = cudf.Scalar(1, dtype=np.int32)
+    s2 = np.int64(2)
+    assert s1 < s2

Done 👍

[galipremsagar]

@gpucibot merge