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Fix dpnp.interp returning nan at exact knot when fp contains inf #2986

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Fix dpnp.interp returning nan at exact knot when fp contains inf #2986

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fc3574c
Fix dpnp.interp returning nan at exact knot when fp contains inf
antonwolfy Jul 2, 2026
eaa717d
Update changelog
antonwolfy Jul 2, 2026
8573ee7
Consider use case when device has no fp64
antonwolfy Jul 2, 2026
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,7 @@ This release is compatible with NumPy 2.5.
* Fixed `icx`/`icpx` warning during `conda build` by stripping the GCC-only `-fno-merge-constants` flag injected by conda-forge into `CFLAGS`/`CXXFLAGS` [#2978](https://github.com/IntelPython/dpnp/pull/2978)
* Fixed `dpnp.asnumpy` and `dpnp.ndarray.asnumpy` ignoring the `order` keyword, which caused a non-contiguous source array to be returned with a non-contiguous layout even when `order="C"` was requested [#2980](https://github.com/IntelPython/dpnp/pull/2980)
* Fixed `dpnp.tensor.acosh` and `dpnp.tensor.acos` returning infinity for complex numbers with large negative real parts [#2928](https://github.com/IntelPython/dpnp/pull/2928)
* Fixed `dpnp.interp` returning `nan` when querying at an exact knot point whose adjacent `fp` value is `inf` [#2985](https://github.com/IntelPython/dpnp/pull/2985)

### Security

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3 changes: 3 additions & 0 deletions dpnp/backend/kernels/elementwise_functions/interpolate.hpp
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Expand Up @@ -88,6 +88,9 @@ class InterpolateFunctor
else if (x_idx >= static_cast<TIdx>(xp_size - 1)) {
out[id] = right_val;
}
else if (x_val == xp[x_idx]) {
out[id] = fp[x_idx];
}
else {
TValue slope =
(fp[x_idx + 1] - fp[x_idx]) / (xp[x_idx + 1] - xp[x_idx]);
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12 changes: 12 additions & 0 deletions dpnp/tests/third_party/cupy/math_tests/test_misc.py
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Expand Up @@ -626,6 +626,18 @@ def test_interp_inf_to_nan(self, xp, dtype_y, dtype_x):
fy = xp.asarray([0, 10], dtype=dtype_y)
return xp.interp(x, fx, fy)

@testing.for_float_dtypes(name="dtype_x")
@testing.for_dtypes("efdFD", name="dtype_y")
@testing.numpy_cupy_allclose(atol=1e-5, type_check=has_support_aspect64())
def test_interp_inf_fy_at_knot(self, xp, dtype_y, dtype_x):
# Regression test: querying at an exact knot point should return the
# knot value, not nan, even when the adjacent fy value is inf.
# See https://github.com/cupy/cupy/issues/9823
x = xp.asarray([2.0], dtype=dtype_x)
fx = xp.asarray([1.0, 2.0, 3.0, 4.0], dtype=dtype_x)
fy = xp.asarray([1.0, 2.0, xp.inf, 4.0], dtype=dtype_y)
return xp.interp(x, fx, fy)

@testing.for_all_dtypes(name="dtype_2", no_bool=True, no_complex=True)
@testing.for_all_dtypes(name="dtype_1", no_bool=True, no_complex=True)
@testing.numpy_cupy_array_equal(type_check=has_support_aspect64())
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