Standardize docstring section header to 'Warnings'

Change 'Warning' to 'Warnings' (plural) in docstring section headers
across multiple modules to follow NumPy/SciPy documentation style guide.

Files modified:
- dpnp/scipy/linalg/_decomp_lu.py (3 functions)
- dpnp/dpnp_iface_histograms.py (5 functions)
- dpnp/dpnp_iface_manipulation.py (2 functions)
- dpnp/dpnp_iface_nanfunctions.py (4 functions)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

Author: antonwolfy

dpnp/dpnp_iface_histograms.py

@@ -306,8 +306,8 @@ def bincount(x, weights=None, minlength=0):
 
     For full documentation refer to :obj:`numpy.bincount`.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function synchronizes in order to calculate binning edges.
     This may harm performance in some applications.
 
@@ -504,8 +504,8 @@ def histogram(a, bins=10, range=None, density=None, weights=None):
 
     For full documentation refer to :obj:`numpy.histogram`.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function may synchronize in order to check a monotonically increasing
     array of bin edges. This may harm performance in some applications.
 
@@ -675,8 +675,8 @@ def histogram_bin_edges(a, bins=10, range=None, weights=None):
 
     For full documentation refer to :obj:`numpy.histogram_bin_edges`.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function may synchronize in order to check a monotonically increasing
     array of bin edges. This may harm performance in some applications.
 
@@ -767,8 +767,8 @@ def histogram2d(x, y, bins=10, range=None, density=None, weights=None):
 
     For full documentation refer to :obj:`numpy.histogram2d`.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function may synchronize in order to check a monotonically increasing
     array of bin edges. This may harm performance in some applications.
 
@@ -1100,8 +1100,8 @@ def histogramdd(sample, bins=10, range=None, density=None, weights=None):
 
     For full documentation refer to :obj:`numpy.histogramdd`.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function may synchronize in order to check a monotonically increasing
     array of bin edges. This may harm performance in some applications.
 

dpnp/dpnp_iface_manipulation.py

@@ -829,8 +829,8 @@ def asfarray(a, dtype=None, *, device=None, usm_type=None, sycl_queue=None):
     out : dpnp.ndarray
         The input `a` as a float ndarray.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function is deprecated in favor of :obj:`dpnp.asarray` and
     will be removed in a future release.
 
@@ -3099,8 +3099,8 @@ def resize(a, new_shape):
     be used. In most other cases either indexing (to reduce the size) or
     padding (to increase the size) may be a more appropriate solution.
 
-    Warning
-    -------
+    Warnings
+    --------
     This functionality does **not** consider axes separately, i.e. it does not
     apply interpolation/extrapolation.
     It fills the return array with the required number of elements, iterating

dpnp/dpnp_iface_nanfunctions.py

@@ -122,15 +122,15 @@ def nanargmax(a, axis=None, out=None, *, keepdims=False):
 
     For full documentation refer to :obj:`numpy.nanargmax`.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function synchronizes in order to test for all-NaN slices in the array.
     This may harm performance in some applications. To avoid synchronization,
     the user is recommended to filter NaNs themselves and use `dpnp.argmax`
     on the filtered array.
 
-    Warning
-    -------
+    Warnings
+    --------
     The results cannot be trusted if a slice contains only NaNs
     and -Infs.
 
@@ -206,15 +206,15 @@ def nanargmin(a, axis=None, out=None, *, keepdims=False):
 
     For full documentation refer to :obj:`numpy.nanargmin`.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function synchronizes in order to test for all-NaN slices in the array.
     This may harm performance in some applications. To avoid synchronization,
     the user is recommended to filter NaNs themselves and use `dpnp.argmax`
     on the filtered array.
 
-    Warning
-    -------
+    Warnings
+    --------
     The results cannot be trusted if a slice contains only NaNs
     and -Infs.
 

dpnp/scipy/linalg/_decomp_lu.py

@@ -130,8 +130,8 @@ def lu(
     permutation matrix is still needed then it can be constructed by
     ``dpnp.eye(M)[P, :]``.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function synchronizes in order to validate array elements
     when ``check_finite=True``, and also synchronizes to compute the
     permutation from LAPACK pivot indices.
@@ -233,8 +233,8 @@ def lu_factor(a, overwrite_a=False, check_finite=True):
         row i of matrix was interchanged with row piv[i].
         Where ``K = min(M, N)``.
 
-    Warning
-    -------
+    Warnings
+    --------
     This function synchronizes in order to validate array elements
     when ``check_finite=True``.
 
@@ -302,8 +302,8 @@ def lu_solve(lu_and_piv, b, trans=0, overwrite_b=False, check_finite=True):
     x : {(M,), (..., M, K)} dpnp.ndarray
         Solution to the system
 
-    Warning
-    -------
+    Warnings
+    --------
     This function synchronizes in order to validate array elements
     when ``check_finite=True``.