dpnp.linalg.vector_norm raises exception for zero sized input array

[antonwolfy]

The example below with dpnp.linalg.vector_norm triggers ValueError exception:

import dpnp

dpnp.__version__
# Out: '0.17.0dev6+25.g1ee8e197e0c'

x = dpnp.zeros(0)
dpnp.linalg.norm(x, ord=dpnp.inf)  # the same with ord=-dpnp.inf
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[3], line 1
----> 1 np.linalg.norm(x, ord=np.inf)

File ~/code/dpnp/dpnp/linalg/dpnp_iface_linalg.py:1419, in norm(x, ord, axis, keepdims)
   1266 r"""
   1267 Matrix or vector norm.
   1268
   (...)
   1415
   1416 """
   1418 dpnp.check_supported_arrays_type(x)
-> 1419 return dpnp_norm(x, ord, axis, keepdims)

File ~/code/dpnp/dpnp/linalg/dpnp_utils_linalg.py:2403, in dpnp_norm(x, ord, axis, keepdims)
   2401 if len(axis) == 1:
   2402     axis = normalize_axis_index(axis[0], ndim)
-> 2403     return _norm_int_axis(x, ord, axis, keepdims)
   2405 if len(axis) == 2:
   2406     row_axis, col_axis = axis

File ~/code/dpnp/dpnp/linalg/dpnp_utils_linalg.py:1186, in _norm_int_axis(x, ord, axis, keepdims)
   1178 """
   1179 _norm_int_axis(x, ord, axis, keepdims)
   1180
   1181 Compute matrix or vector norm of `x` along integer `axis`.
   1182
   1183 """
   1185 if ord == dpnp.inf:
-> 1186     return dpnp.abs(x).max(axis=axis, keepdims=keepdims)
   1187 if ord == -dpnp.inf:
   1188     return dpnp.abs(x).min(axis=axis, keepdims=keepdims)

File ~/code/dpnp/dpnp/dpnp_array.py:1272, in dpnp_array.max(self, axis, out, keepdims, initial, where)
   1257 def max(
   1258     self,
   1259     axis=None,
   (...)
   1263     where=True,
   1264 ):
   1265     """
   1266     Return the maximum along an axis.
   1267
   1268     Refer to :obj:`dpnp.max` for full documentation.
   1269
   1270     """
-> 1272     return dpnp.max(
   1273         self,
   1274         axis=axis,
   1275         out=out,
   1276         keepdims=keepdims,
   1277         initial=initial,
   1278         where=where,
   1279     )

File ~/code/dpnp/dpnp/dpnp_iface_statistics.py:999, in max(a, axis, out, keepdims, initial, where)
    996 dpnp.check_limitations(initial=initial, where=where)
    997 usm_a = dpnp.get_usm_ndarray(a)
--> 999 return dpnp_wrap_reduction_call(
   1000     usm_a,
   1001     out,
   1002     dpt.max,
   1003     a.dtype,
   1004     axis=axis,
   1005     keepdims=keepdims,
   1006 )

File ~/code/dpnp/dpnp/dpnp_utils/dpnp_utils_reduction.py:48, in dpnp_wrap_reduction_call(usm_a, out, _reduction_fn, res_dt, **kwargs)
     45     usm_out = dpnp.get_usm_ndarray(out)
     47 kwargs["out"] = usm_out
---> 48 res_usm = _reduction_fn(usm_a, **kwargs)
     49 return dpnp.get_result_array(res_usm, input_out, casting="unsafe")

File ~/miniforge3/envs/dpnp_dev/lib/python3.12/site-packages/dpctl/tensor/_reduction.py:569, in max(x, axis, keepdims, out)
    539 def max(x, /, *, axis=None, keepdims=False, out=None):
    540     """
    541     Calculates the maximum value of the input array ``x``.
    542
   (...)
    567             array has the same data type as ``x``.
    568     """
--> 569     return _comparison_over_axis(x, axis, keepdims, out, tri._max_over_axis)

File ~/miniforge3/envs/dpnp_dev/lib/python3.12/site-packages/dpctl/tensor/_reduction.py:458, in _comparison_over_axis(x, axis, keepdims, out, _reduction_fn)
    456 red_nd = len(axis)
    457 if any([x_tmp.shape[i] == 0 for i in range(-red_nd, 0)]):
--> 458     raise ValueError("reduction cannot be performed over zero-size axes")
    459 res_shape = x_tmp.shape[: nd - red_nd]
    460 exec_q = x.sycl_queue

ValueError: reduction cannot be performed over zero-size axes

[vtavana]

NumPy raises a similar Error, what is the use case that you encountered it?

>>> import numpy
>>> numpy.linalg.norm(numpy.zeros(0), ord=numpy.inf)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[2], line 1
----> 1 numpy.linalg.norm(numpy.zeros(0), ord=numpy.inf)

File /localdisk/work/vtavana/miniforge/envs/dpnp_2025/lib/python3.12/site-packages/numpy/linalg/_linalg.py:2765, in norm(x, ord, axis, keepdims)
   2763 if len(axis) == 1:
   2764     if ord == inf:
-> 2765         return abs(x).max(axis=axis, keepdims=keepdims)
   2766     elif ord == -inf:
   2767         return abs(x).min(axis=axis, keepdims=keepdims)

File /localdisk/work/vtavana/miniforge/envs/dpnp_2025/lib/python3.12/site-packages/numpy/_core/_methods.py:44, in _amax(a, axis, out, keepdims, initial, where)
     42 def _amax(a, axis=None, out=None, keepdims=False,
     43           initial=_NoValue, where=True):
---> 44     return umr_maximum(a, axis, None, out, keepdims, initial, where)

ValueError: zero-size array to reduction operation maximum which has no identity

[antonwolfy]

NumPy is going to resolve that in numpy#28343