remove unneccessary parts with updates in dpctl #1465

Author: vtavana

dpnp/dpnp_iface_searching.py

@@ -110,22 +110,9 @@ def argmax(a, axis=None, out=None, *, keepdims=False):
     """
 
     dpt_array = dpnp.get_usm_ndarray(a)
-    if dpt_array.size == 0:
-        # TODO: get rid of this if condition when dpctl supports it
-        for i in range(a.ndim):
-            if a.shape[i] == 0:
-                if i == axis or axis is None:
-                    raise ValueError(
-                        "reduction does not support zero-size arrays"
-                    )
-                else:
-                    indices = [i for i in range(a.ndim) if i != axis]
-                    res_shape = tuple([a.shape[i] for i in indices])
-                    result = dpnp.empty(res_shape, dtype=int)
-    else:
-        result = dpnp_array._create_from_usm_ndarray(
-            dpt.argmax(dpt_array, axis=axis, keepdims=keepdims)
-        )
+    result = dpnp_array._create_from_usm_ndarray(
+        dpt.argmax(dpt_array, axis=axis, keepdims=keepdims)
+    )
 
     if out is None:
         return result
@@ -210,22 +197,9 @@ def argmin(a, axis=None, out=None, *, keepdims=False):
     """
 
     dpt_array = dpnp.get_usm_ndarray(a)
-    if dpt_array.size == 0:
-        # TODO: get rid of this if condition when dpctl supports it
-        for i in range(a.ndim):
-            if a.shape[i] == 0:
-                if i == axis or axis is None:
-                    raise ValueError(
-                        "reduction does not support zero-size arrays"
-                    )
-                else:
-                    indices = [i for i in range(a.ndim) if i != axis]
-                    res_shape = tuple([a.shape[i] for i in indices])
-                    result = dpnp.empty(res_shape, dtype=int)
-    else:
-        result = dpnp_array._create_from_usm_ndarray(
-            dpt.argmin(dpt_array, axis=axis, keepdims=keepdims)
-        )
+    result = dpnp_array._create_from_usm_ndarray(
+        dpt.argmin(dpt_array, axis=axis, keepdims=keepdims)
+    )
 
     if out is None:
         return result

dpnp/dpnp_iface_statistics.py

@@ -410,23 +410,10 @@ def max(a, axis=None, out=None, keepdims=False, initial=None, where=True):
         )
     else:
         dpt_array = dpnp.get_usm_ndarray(a)
-        if dpt_array.size == 0:
-            # TODO: get rid of this if condition when dpctl supports it
-            axis = (axis,) if isinstance(axis, int) else axis
-            for i in range(a.ndim):
-                if a.shape[i] == 0:
-                    if axis is None or i in axis:
-                        raise ValueError(
-                            "reduction does not support zero-size arrays"
-                        )
-                    else:
-                        indices = [i for i in range(a.ndim) if i not in axis]
-                        res_shape = tuple([a.shape[i] for i in indices])
-                        result = dpnp.empty(res_shape, dtype=a.dtype)
-        else:
-            result = dpnp_array._create_from_usm_ndarray(
-                dpt.max(dpt_array, axis=axis, keepdims=keepdims)
-            )
+        result = dpnp_array._create_from_usm_ndarray(
+            dpt.max(dpt_array, axis=axis, keepdims=keepdims)
+        )
+
         if out is None:
             return result
         else:
@@ -655,22 +642,10 @@ def min(a, axis=None, out=None, keepdims=False, initial=None, where=True):
         )
     else:
         dpt_array = dpnp.get_usm_ndarray(a)
-        if dpt_array.size == 0:
-            # TODO: get rid of this if condition when dpctl supports it
-            for i in range(a.ndim):
-                if a.shape[i] == 0:
-                    if axis is None or i in axis:
-                        raise ValueError(
-                            "reduction does not support zero-size arrays"
-                        )
-                    else:
-                        indices = [i for i in range(a.ndim) if i not in axis]
-                        res_shape = tuple([a.shape[i] for i in indices])
-                        result = dpnp.empty(res_shape, dtype=a.dtype)
-        else:
-            result = dpnp_array._create_from_usm_ndarray(
-                dpt.min(dpt_array, axis=axis, keepdims=keepdims)
-            )
+        result = dpnp_array._create_from_usm_ndarray(
+            dpt.min(dpt_array, axis=axis, keepdims=keepdims)
+        )
+
         if out is None:
             return result
         else: