Implement dpctl.tensor.isdtype

dpctl/tensor/__init__.py

@@ -51,6 +51,7 @@
     int16,
     int32,
     int64,
+    isdtype,
     uint8,
     uint16,
     uint32,
@@ -125,6 +126,7 @@
     "tril",
     "triu",
     "dtype",
+    "isdtype",
     "bool",
     "int8",
     "uint8",

dpctl/tensor/_data_types.py

@@ -31,8 +31,52 @@
 complex64 = dtype("complex64")
 complex128 = dtype("complex128")
 
+
+def isdtype(dtype_, kind):
+    """isdtype(dtype, kind)
+
+    Returns a boolean indicating whether a provided `dtype` is
+    of a specified data type `kind`.
+
+    See [array API](array_api) for more information.
+
+    [array_api]: https://data-apis.org/array-api/latest/
+    """
+
+    if not isinstance(dtype_, dtype):
+        raise TypeError("Expected instance of `dpt.dtype`, got {dtype_}")
+
+    if isinstance(kind, dtype):
+        return dtype_ == kind
+
+    elif isinstance(kind, str):
+        if kind == "bool":
+            return dtype_ == dtype("bool")
+        elif kind == "signed integer":
+            return dtype_.kind == "i"
+        elif kind == "unsigned integer":
+            return dtype_.kind == "u"
+        elif kind == "integral":
+            return dtype_.kind in "iu"
+        elif kind == "real floating":
+            return dtype_.kind == "f"
+        elif kind == "complex floating":
+            return dtype_.kind == "c"
+        elif kind == "numeric":
+            return dtype_.kind in "iufc"
+        else:
+            raise ValueError(f"Unrecognized data type kind: {kind}")
+
+    elif isinstance(kind, tuple):
+        return any(isdtype(dtype_, k) for k in kind)
+
+    else:
+        raise TypeError(f"Unsupported data type kind: {kind}")
+
+
 __all__ = [
     "dtype",
+    "isdtype",
     "bool",
     "int8",
     "uint8",

dpctl/tests/test_tensor_dtype_routines.py

@@ -0,0 +1,129 @@
+#                      Data Parallel Control (dpctl)
+#
+# Copyright 2020-2023 Intel Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import pytest
+
+import dpctl.tensor as dpt
+
+list_dtypes = [
+    "bool",
+    "int8",
+    "int16",
+    "int32",
+    "int64",
+    "uint8",
+    "uint16",
+    "uint32",
+    "uint64",
+    "float16",
+    "float32",
+    "float64",
+    "complex64",
+    "complex128",
+]
+
+
+dtype_categories = {
+    "bool": ["bool"],
+    "signed integer": ["int8", "int16", "int32", "int64"],
+    "unsigned integer": ["uint8", "uint16", "uint32", "uint64"],
+    "integral": [
+        "int8",
+        "int16",
+        "int32",
+        "int64",
+        "uint8",
+        "uint16",
+        "uint32",
+        "uint64",
+    ],
+    "real floating": ["float16", "float32", "float64"],
+    "complex floating": ["complex64", "complex128"],
+    "numeric": [d for d in list_dtypes if d != "bool"],
+}
+
+
+@pytest.mark.parametrize("kind_str", dtype_categories.keys())
+@pytest.mark.parametrize("dtype_str", list_dtypes)
+def test_isdtype_kind_str(dtype_str, kind_str):
+    dt = dpt.dtype(dtype_str)
+    is_in_kind = dpt.isdtype(dt, kind_str)
+    expected = dtype_str in dtype_categories[kind_str]
+    assert is_in_kind == expected
+
+
+@pytest.mark.parametrize("dtype_str", list_dtypes)
+def test_isdtype_kind_tuple(dtype_str):
+    dt = dpt.dtype(dtype_str)
+    if dtype_str.startswith("bool"):
+        assert dpt.isdtype(dt, ("real floating", "bool"))
+        assert not dpt.isdtype(
+            dt, ("integral", "real floating", "complex floating")
+        )
+    elif dtype_str.startswith("int"):
+        assert dpt.isdtype(dt, ("real floating", "signed integer"))
+        assert not dpt.isdtype(
+            dt, ("bool", "unsigned integer", "real floating")
+        )
+    elif dtype_str.startswith("uint"):
+        assert dpt.isdtype(dt, ("bool", "unsigned integer"))
+        assert not dpt.isdtype(dt, ("real floating", "complex floating"))
+    elif dtype_str.startswith("float"):
+        assert dpt.isdtype(dt, ("complex floating", "real floating"))
+        assert not dpt.isdtype(dt, ("integral", "complex floating", "bool"))
+    else:
+        assert dpt.isdtype(dt, ("integral", "complex floating"))
+        assert not dpt.isdtype(dt, ("bool", "integral", "real floating"))
+
+
+@pytest.mark.parametrize("dtype_str", list_dtypes)
+def test_isdtype_kind_tuple_dtypes(dtype_str):
+    dt = dpt.dtype(dtype_str)
+    if dtype_str.startswith("bool"):
+        assert dpt.isdtype(dt, (dpt.int32, dpt.bool))
+        assert not dpt.isdtype(dt, (dpt.int16, dpt.uint32, dpt.float64))
+
+    elif dtype_str.startswith("int"):
+        assert dpt.isdtype(dt, (dpt.int8, dpt.int16, dpt.int32, dpt.int64))
+        assert not dpt.isdtype(dt, (dpt.bool, dpt.float32, dpt.complex64))
+
+    elif dtype_str.startswith("uint"):
+        assert dpt.isdtype(dt, (dpt.uint8, dpt.uint16, dpt.uint32, dpt.uint64))
+        assert not dpt.isdtype(dt, (dpt.bool, dpt.int32, dpt.float32))
+
+    elif dtype_str.startswith("float"):
+        assert dpt.isdtype(dt, (dpt.float16, dpt.float32, dpt.float64))
+        assert not dpt.isdtype(dt, (dpt.bool, dpt.complex64, dpt.int8))
+
+    else:
+        assert dpt.isdtype(dt, (dpt.complex64, dpt.complex128))
+        assert not dpt.isdtype(dt, (dpt.bool, dpt.uint64, dpt.int8))
+
+
+@pytest.mark.parametrize(
+    "kind",
+    [
+        [dpt.int32, dpt.bool],
+        "f4",
+        float,
+        123,
+        "complex",
+    ],
+)
+def test_isdtype_invalid_kind(kind):
+    with pytest.raises((TypeError, ValueError)):
+        dpt.isdtype(dpt.int32, kind)