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Add numerically sound implementations for log1p and expm1 (#234)
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Lines changed: 66 additions & 21 deletions

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‎CHANGELOG.rst‎

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@@ -7,6 +7,14 @@
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Changelog
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=========
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0.22.0 (unreleased)
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-------------------
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**New feature**
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- Added support for :func:`ndonnx.log1p` and :func:`ndonnx.expm1`.
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0.21.0 (2026-08-07)
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-------------------
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‎ndonnx/_funcs.py‎

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@@ -449,15 +449,11 @@ def expand_dims(x: Array, /, *, axis: int = 0) -> Array:
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def expm1(x: Array, /) -> Array:
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# Requires special operator to meet standards precision requirements
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# TODO: Add upstream tracking issue
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raise NotImplementedError
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return Array._from_tyarray(x._tyarray.expm1())
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def log1p(x: Array, /) -> Array:
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# Requires special operator to meet standards precision requirements
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# TODO: Add upstream tracking issue
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raise NotImplementedError
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return Array._from_tyarray(x._tyarray.log1p())
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def conj(x: Array, /) -> Array:

‎ndonnx/_typed_array/masked_onnx.py‎

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@@ -755,7 +755,9 @@ def dtype(self) -> FloatDTypes:
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cos = _make_unary_member_same_type("cos") # type: ignore
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cosh = _make_unary_member_same_type("cosh") # type: ignore
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exp = _make_unary_member_same_type("exp") # type: ignore
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expm1 = _make_unary_member_same_type("expm1") # type: ignore
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log = _make_unary_member_same_type("log") # type: ignore
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log1p = _make_unary_member_same_type("log1p") # type: ignore
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log2 = _make_unary_member_same_type("log2") # type: ignore
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log10 = _make_unary_member_same_type("log10") # type: ignore
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sin = _make_unary_member_same_type("sin") # type: ignore

‎ndonnx/_typed_array/onnx.py‎

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Original file line numberDiff line numberDiff line change
@@ -1928,6 +1928,38 @@ def __ndx_rlogaddexp__(self, x1: TyArrayBase | int | float, /) -> TyArrayFloatin
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return safe_cast(TyArrayFloating, (x1.exp() + x2.exp()).log())
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return NotImplemented
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@overload
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def __add__(self: Self, other: Self | int | float) -> Self: ...
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@overload
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def __add__(self, other: TyArrayNumber | int | float) -> TyArrayNumber: ...
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@overload
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def __add__(self, other: TyArrayBase | PyScalar) -> TyArrayBase: ...
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def __add__(self, other: TyArrayBase | PyScalar) -> TyArrayBase:
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return super().__add__(other)
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@overload
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def __sub__(self: Self, other: Self | int | float) -> Self: ...
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@overload
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def __sub__(self, other: TyArrayNumber | int | float) -> TyArrayNumber: ...
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@overload
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def __sub__(self, other: TyArrayBase | PyScalar) -> TyArrayBase: ...
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def __sub__(self, other: TyArrayBase | PyScalar) -> TyArrayBase:
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return super().__sub__(other)
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@overload
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def __mul__(self: Self, other: Self | int | float) -> Self: ...
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@overload
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def __mul__(self, other: TyArrayBase | PyScalar) -> TyArrayBase: ...
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def __mul__(self, other: TyArrayBase | PyScalar) -> TyArrayBase:
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return super().__mul__(other)
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@overload
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def __truediv__(self: Self, other: Self | int | float) -> Self: ...
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@overload
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def __truediv__(self, other: TyArrayBase | PyScalar) -> TyArrayBase: ...
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def __truediv__(self, other: TyArrayBase | PyScalar) -> TyArrayBase:
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return super().__truediv__(other)
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def ceil(self) -> Self:
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return type(self)(op.ceil(self._var))
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@@ -2073,6 +2105,14 @@ def cosh(self) -> Self:
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def exp(self) -> Self:
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return type(self)(op.exp(self._var))
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def expm1(self) -> Self:
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# expm1(x) = (u - 1) * x / log(u) with u = exp(x); == x where u == 1.
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# Analog of Goldberg's log1p (see below).
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u = self.exp()
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d = u - 1.0
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tail = (d == -1.0) | u.isinf()
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return where(u == 1.0, self, where(tail, d, d * self / u.log()))
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def log(self) -> Self:
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return type(self)(op.log(self._var))
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@@ -2084,6 +2124,16 @@ def log10(self) -> Self:
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res = self.log() / float(np.log(10))
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return safe_cast(type(self), res)
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def log1p(self) -> Self:
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# log1p(x) = log(u) * x / (u - 1) with u = 1 + x; == x where u == 1.
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# Goldberg, "What Every Computer Scientist Should Know About
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# Floating-Point Arithmetic", Theorem 4:
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# https://docs.oracle.com/cd/E19957-01/806-3568/ncg_goldberg.html
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u = self + 1.0
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d = u - 1.0
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short_circuit = (u == 1.0) | (self.isinf() & (self > 0.0))
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return where(short_circuit, self, u.log() * (self / d))
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def sin(self) -> Self:
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return type(self)(op.sin(self._var))
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‎skips.txt‎

Lines changed: 4 additions & 15 deletions
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@@ -37,15 +37,11 @@ array_api_tests/test_has_names.py::test_has_names[elementwise-imag]
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array_api_tests/test_has_names.py::test_has_names[elementwise-real]
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array_api_tests/test_has_names.py::test_has_names[elementwise-signbit]
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array_api_tests/test_has_names.py::test_has_names[elementwise-atan2]
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array_api_tests/test_has_names.py::test_has_names[elementwise-expm1]
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array_api_tests/test_has_names.py::test_has_names[elementwise-log1p]
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array_api_tests/test_has_names.py::test_has_names[elementwise-nextafter]
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array_api_tests/test_operators_and_elementwise_functions.py::test_atan2
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array_api_tests/test_operators_and_elementwise_functions.py::test_copysign
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array_api_tests/test_operators_and_elementwise_functions.py::test_expm1
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array_api_tests/test_operators_and_elementwise_functions.py::test_hypot
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array_api_tests/test_operators_and_elementwise_functions.py::test_log1p
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array_api_tests/test_operators_and_elementwise_functions.py::test_signbit
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array_api_tests/test_operators_and_elementwise_functions.py::test_nextafter
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@@ -85,24 +81,17 @@ array_api_tests/test_special_cases.py::test_binary[nextafter(x1_i is NaN or x2_i
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array_api_tests/test_special_cases.py::test_binary[nextafter(x1_i is -0 and x2_i is +0) -> +0]
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array_api_tests/test_special_cases.py::test_binary[nextafter(x1_i is +0 and x2_i is -0) -> -0]
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# log1p and expm1 fail to propagate -0 because onnxruntime's where fails to do so
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array_api_tests/test_special_cases.py::test_unary[log1p(x_i is -0) -> -0]
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array_api_tests/test_special_cases.py::test_unary[expm1(x_i is -0) -> -0]
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array_api_tests/test_special_cases.py::test_unary[acos(x_i < -1) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[acos(x_i > 1) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[acosh(x_i < 1) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[asin(x_i < -1) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[asin(x_i > 1) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[atanh(x_i < -1) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[atanh(x_i > 1) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[expm1(x_i is +0) -> +0]
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array_api_tests/test_special_cases.py::test_unary[expm1(x_i is +infinity) -> +infinity]
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array_api_tests/test_special_cases.py::test_unary[expm1(x_i is -0) -> -0]
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array_api_tests/test_special_cases.py::test_unary[expm1(x_i is -infinity) -> -1]
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array_api_tests/test_special_cases.py::test_unary[expm1(x_i is NaN) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[log1p(x_i < -1) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[log1p(x_i is +0) -> +0]
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array_api_tests/test_special_cases.py::test_unary[log1p(x_i is +infinity) -> +infinity]
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array_api_tests/test_special_cases.py::test_unary[log1p(x_i is -0) -> -0]
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array_api_tests/test_special_cases.py::test_unary[log1p(x_i is -1) -> -infinity]
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array_api_tests/test_special_cases.py::test_unary[log1p(x_i is NaN) -> NaN]
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array_api_tests/test_special_cases.py::test_unary[signbit(isfinite(x_i) and x_i < 0) -> True]
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array_api_tests/test_special_cases.py::test_unary[signbit(isfinite(x_i) and x_i > 0) -> False]
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array_api_tests/test_special_cases.py::test_unary[signbit(x_i is +0) -> False]

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