@@ -144,6 +144,11 @@ def nanargmax(a, axis=None, out=None, *, keepdims=False):
144144 the user is recommended to filter NaNs themselves and use `dpnp.argmax`
145145 on the filtered array.
146146
147+ Warning
148+ -------
149+ The results cannot be trusted if a slice contains only NaNs
150+ and -Infs.
151+
147152 Parameters
148153 ----------
149154 a : {dpnp.ndarray, usm_ndarray}
@@ -173,8 +178,6 @@ def nanargmax(a, axis=None, out=None, *, keepdims=False):
173178 values ignoring NaNs. The returned array must have the default array
174179 index data type.
175180 For all-NaN slices ``ValueError`` is raised.
176- Warning: the results cannot be trusted if a slice contains only NaNs
177- and -Infs.
178181
179182 Limitations
180183 -----------
@@ -225,6 +228,11 @@ def nanargmin(a, axis=None, out=None, *, keepdims=False):
225228 the user is recommended to filter NaNs themselves and use `dpnp.argmax`
226229 on the filtered array.
227230
231+ Warning
232+ -------
233+ The results cannot be trusted if a slice contains only NaNs
234+ and -Infs.
235+
228236 Parameters
229237 ----------
230238 a : {dpnp.ndarray, usm_ndarray}
@@ -254,8 +262,6 @@ def nanargmin(a, axis=None, out=None, *, keepdims=False):
254262 values ignoring NaNs. The returned array must have the default array
255263 index data type.
256264 For all-NaN slices ``ValueError`` is raised.
257- Warning: the results cannot be trusted if a slice contains only NaNs
258- and Infs.
259265
260266 Limitations
261267 -----------
0 commit comments