Add dpnp.isdtype implementation (#2274)

The PR proposes to implement `dpnp.isdtype` function.

The function is mandated according to python array API. The
corresponding muted tests are enabled in python array API compliance
scope.

.github/workflows/array-api-skips.txt

@@ -3,11 +3,6 @@
 # no 'uint8' dtype
 array_api_tests/test_array_object.py::test_getitem_masking
 
-# no 'isdtype' function
-array_api_tests/test_data_type_functions.py::test_isdtype
-array_api_tests/test_has_names.py::test_has_names[data_type-isdtype]
-array_api_tests/test_signatures.py::test_func_signature[isdtype]
-
 # missing unique-like functions
 array_api_tests/test_has_names.py::test_has_names[set-unique_all]
 array_api_tests/test_has_names.py::test_has_names[set-unique_counts]

doc/reference/dtype.rst

@@ -14,7 +14,6 @@ Data type routines
    dpnp.min_scalar_type
    dpnp.result_type
    dpnp.common_type
-   dpnp.obj2sctype
 
 Creating data types
 -------------------

dpnp/dpnp_iface_types.py

@@ -64,6 +64,7 @@
     "integer",
     "intc",
     "intp",
+    "isdtype",
     "issubdtype",
     "is_type_supported",
     "nan",
@@ -194,11 +195,66 @@ def iinfo(dtype):
             smallest representable number.
 
     """
+
     if isinstance(dtype, dpnp_array):
         dtype = dtype.dtype
     return dpt.iinfo(dtype)
 
 
+def isdtype(dtype, kind):
+    """
+    Returns a boolean indicating whether a provided `dtype` is
+    of a specified data type `kind`.
+
+    Parameters
+    ----------
+    dtype : dtype
+        The input dtype.
+    kind : {dtype, str, tuple of dtypes or strs}
+        The input dtype or dtype kind. Allowed dtype kinds are:
+
+        * ``'bool'`` : boolean kind
+        * ``'signed integer'`` : signed integer data types
+        * ``'unsigned integer'`` : unsigned integer data types
+        * ``'integral'`` : integer data types
+        * ``'real floating'`` : real-valued floating-point data types
+        * ``'complex floating'`` : complex floating-point data types
+        * ``'numeric'`` : numeric data types
+
+    Returns
+    -------
+    out : bool
+        A boolean indicating whether a provided `dtype` is of a specified data
+        type `kind`.
+
+    See Also
+    --------
+    :obj:`dpnp.issubdtype` : Test if the first argument is a type code
+                             lower/equal in type hierarchy.
+
+    Examples
+    --------
+    >>> import dpnp as np
+    >>> np.isdtype(np.float32, np.float64)
+    False
+    >>> np.isdtype(np.float32, "real floating")
+    True
+    >>> np.isdtype(np.complex128, ("real floating", "complex floating"))
+    True
+
+    """
+
+    if isinstance(dtype, type):
+        dtype = dpt.dtype(dtype)
+
+    if isinstance(kind, type):
+        kind = dpt.dtype(kind)
+    elif isinstance(kind, tuple):
+        kind = tuple(dpt.dtype(k) if isinstance(k, type) else k for k in kind)
+
+    return dpt.isdtype(dtype, kind)
+
+
 def issubdtype(arg1, arg2):
     """
     Returns ``True`` if the first argument is a type code lower/equal

dpnp/tests/test_dtype_routines.py

@@ -0,0 +1,65 @@
+import numpy
+import pytest
+from numpy.testing import assert_raises_regex
+
+import dpnp
+
+from .helper import numpy_version
+
+if numpy_version() >= "2.0.0":
+    from numpy._core.numerictypes import sctypes
+else:
+    from numpy.core.numerictypes import sctypes
+
+
+class TestIsDType:
+    dtype_group = {
+        "signed integer": sctypes["int"],
+        "unsigned integer": sctypes["uint"],
+        "integral": sctypes["int"] + sctypes["uint"],
+        "real floating": sctypes["float"],
+        "complex floating": sctypes["complex"],
+        "numeric": (
+            sctypes["int"]
+            + sctypes["uint"]
+            + sctypes["float"]
+            + sctypes["complex"]
+        ),
+    }
+
+    @pytest.mark.parametrize(
+        "dt, close_dt",
+        [
+            # TODO: replace with (dpnp.uint64, dpnp.uint32) once available
+            (dpnp.int64, dpnp.int32),
+            (numpy.uint64, numpy.uint32),
+            (dpnp.float64, dpnp.float32),
+            (dpnp.complex128, dpnp.complex64),
+        ],
+    )
+    @pytest.mark.parametrize("dt_group", [None] + list(dtype_group.keys()))
+    def test_basic(self, dt, close_dt, dt_group):
+        # First check if same dtypes return "True" and different ones
+        # give "False" (even if they're close in the dtype hierarchy).
+        if dt_group is None:
+            assert dpnp.isdtype(dt, dt)
+            assert not dpnp.isdtype(dt, close_dt)
+            assert dpnp.isdtype(dt, (dt, close_dt))
+
+        # Check that dtype and a dtype group that it belongs to return "True",
+        # and "False" otherwise.
+        elif dt in self.dtype_group[dt_group]:
+            assert dpnp.isdtype(dt, dt_group)
+            assert dpnp.isdtype(dt, (close_dt, dt_group))
+        else:
+            assert not dpnp.isdtype(dt, dt_group)
+
+    def test_invalid_args(self):
+        with assert_raises_regex(TypeError, r"Expected instance of.*"):
+            dpnp.isdtype("int64", dpnp.int64)
+
+        with assert_raises_regex(TypeError, r"Unsupported data type kind:.*"):
+            dpnp.isdtype(dpnp.int64, 1)
+
+        with assert_raises_regex(ValueError, r"Unrecognized data type kind:.*"):
+            dpnp.isdtype(dpnp.int64, "int64")