1 files changed, 15 insertions, 2 deletions
diff --git a/numpy/_array_api/_creation_functions.py b/numpy/_array_api/_creation_functions.py
index 4be482199..197960211 100644
--- a/numpy/_array_api/_creation_functions.py
+++ b/numpy/_array_api/_creation_functions.py
@@ -2,6 +2,7 @@ from __future__ import annotations
 
 from ._types import (Optional, SupportsDLPack, SupportsBufferProtocol, Tuple,
                      Union, array, device, dtype)
+from ._dtypes import _all_dtypes
 
 import numpy as np
 
@@ -88,7 +89,14 @@ def full(shape: Union[int, Tuple[int, ...]], fill_value: Union[int, float], /, *
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return ndarray._new(np.full(shape, fill_value, dtype=dtype))
+    if isinstance(fill_value, ndarray) and fill_value.ndim == 0:
+            fill_value = fill_value._array[...]
+    res = np.full(shape, fill_value, dtype=dtype)
+    if res.dtype not in _all_dtypes:
+        # This will happen if the fill value is not something that NumPy
+        # coerces to one of the acceptable dtypes.
+        raise TypeError("Invalid input to full")
+    return ndarray._new(res)
 
 def full_like(x: array, fill_value: Union[int, float], /, *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array:
     """
@@ -100,7 +108,12 @@ def full_like(x: array, fill_value: Union[int, float], /, *, dtype: Optional[dty
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return ndarray._new(np.full_like._implementation(x._array, fill_value, dtype=dtype))
+    res = np.full_like._implementation(x._array, fill_value, dtype=dtype)
+    if res.dtype not in _all_dtypes:
+        # This will happen if the fill value is not something that NumPy
+        # coerces to one of the acceptable dtypes.
+        raise TypeError("Invalid input to full_like")
+    return ndarray._new(res)
 
 def linspace(start: Union[int, float], stop: Union[int, float], num: int, /, *, dtype: Optional[dtype] = None, device: Optional[device] = None, endpoint: bool = True) -> array:
     """