Improve dpctl.tensor.full error for invalid fill_value

CHANGELOG.md

@@ -17,6 +17,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
+* Improved error in constructors `tensor.full` and `tensor.full_like` when provided a non-numeric fill value [gh-1878](https://github.com/IntelPython/dpctl/pull/1878)
+
 ### Maintenance
 
 * Update black version used in Python code style workflow [gh-1828](https://github.com/IntelPython/dpctl/pull/1828)

dpctl/tensor/_ctors.py

@@ -15,6 +15,7 @@
 #  limitations under the License.
 
 import operator
+from numbers import Number
 
 import numpy as np
 
@@ -1037,6 +1038,19 @@ def _cast_fill_val(fill_val, dt):
         return fill_val
 
 
+def _validate_fill_value(fill_val):
+    """
+    Validates that `fill_val` is a numeric or boolean scalar.
+    """
+    # TODO: verify if `np.True_` and `np.False_` should be instances of
+    # Number in NumPy, like other NumPy scalars and like Python bools
+    # check for `np.bool_` separately as NumPy<2 has no `np.bool`
+    if not isinstance(fill_val, Number) and not isinstance(fill_val, np.bool_):
+        raise TypeError(
+            f"array cannot be filled with scalar of type {type(fill_val)}"
+        )
+
+
 def full(
     shape,
     fill_value,
@@ -1110,6 +1124,8 @@ def full(
             sycl_queue=sycl_queue,
         )
         return dpt.copy(dpt.broadcast_to(X, shape), order=order)
+    else:
+        _validate_fill_value(fill_value)
 
     sycl_queue = normalize_queue_device(sycl_queue=sycl_queue, device=device)
     usm_type = usm_type if usm_type is not None else "device"
@@ -1480,6 +1496,8 @@ def full_like(
             )
             _manager.add_event_pair(hev, copy_ev)
             return res
+        else:
+            _validate_fill_value(fill_value)
 
         dtype = _get_dtype(dtype, sycl_queue, ref_type=type(fill_value))
         res = _empty_like_orderK(x, dtype, usm_type, sycl_queue)

dpctl/tests/test_usm_ndarray_ctor.py

@@ -2621,3 +2621,14 @@ def test_setitem_from_numpy_contig():
 
     expected = dpt.reshape(dpt.arange(-10, 10, dtype=fp_dt), (4, 5))
     assert dpt.all(dpt.flip(Xdpt, axis=-1) == expected)
+
+
+def test_full_functions_raise_type_error():
+    get_queue_or_skip()
+
+    with pytest.raises(TypeError):
+        dpt.full(1, "0")
+
+    x = dpt.ones(1, dtype="i4")
+    with pytest.raises(TypeError):
+        dpt.full_like(x, "0")