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cliffburdick merged 3 commits into from
Oct 1, 2026
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Return a finite value for single-element windows, linspace and logspace #1252

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5e3a8da
Return a finite value for single-element windows, linspace and logspace
Arthur031221 Oct 1, 2026
2d02688
Fix singleton logspace and half-precision bartlett, test one-point JI…
Arthur031221 Oct 1, 2026
2d1e605
Test singleton windows with explicit float and double generators
Arthur031221 Oct 1, 2026
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4 changes: 2 additions & 2 deletions include/matx/generators/bartlett.h
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Original file line number Diff line number Diff line change
Expand Up @@ -72,7 +72,7 @@ namespace matx
" template <typename CapType>\n" +
" __MATX_INLINE__ __MATX_DEVICE__ auto operator()(index_t i) const\n" +
" {\n" +
" return detail::ApplyGeneratorVecFunc<CapType, T>([](index_t idx) { return 1 - cuda::std::abs(((2*T(idx))/(T(size_ - 1))) - 1); }, i);\n" +
" return detail::ApplyGeneratorVecFunc<CapType, T>([](index_t idx) { if (size_ == 1) { return T(1); } return T(1 - cuda::std::abs(((2*T(idx))/(T(size_ - 1))) - 1)); }, i);\n" +
" }\n" +
" static __MATX_INLINE__ constexpr __MATX_DEVICE__ int32_t Rank() { return 1; }\n" +
" constexpr __MATX_INLINE__ __MATX_DEVICE__ index_t Size([[maybe_unused]] int dim) const { return size_; }\n" +
Expand All @@ -92,7 +92,7 @@ namespace matx
template <typename CapType>
inline __MATX_HOST__ __MATX_DEVICE__ auto operator()(index_t i) const
{
return detail::ApplyGeneratorVecFunc<CapType, T>([this](index_t idx) { return 1 - cuda::std::abs(((2*T(idx))/(T(size_ - 1))) - 1); }, i);
return detail::ApplyGeneratorVecFunc<CapType, T>([this](index_t idx) { if (size_ == 1) { return T(1); } return T(1 - cuda::std::abs(((2*T(idx))/(T(size_ - 1))) - 1)); }, i);
}

inline __MATX_HOST__ __MATX_DEVICE__ auto operator()(index_t i) const
Expand Down
4 changes: 2 additions & 2 deletions include/matx/generators/blackman.h
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Expand Up @@ -72,7 +72,7 @@ namespace matx
" template <typename CapType>\n" +
" __MATX_INLINE__ __MATX_DEVICE__ auto operator()(index_t i) const\n" +
" {\n" +
" return detail::ApplyGeneratorVecFunc<CapType, T>([](index_t idx) { return T(.42) - T(.5) * cuda::std::cos(T(2 * cuda::std::numbers::pi) * T(idx) / T(size_ - 1)) + T(.08) * cuda::std::cos(T(4 * cuda::std::numbers::pi) * T(idx) / T(size_ - 1)); }, i);\n" +
" return detail::ApplyGeneratorVecFunc<CapType, T>([](index_t idx) { if (size_ == 1) { return T(1); } return T(.42) - T(.5) * cuda::std::cos(T(2 * cuda::std::numbers::pi) * T(idx) / T(size_ - 1)) + T(.08) * cuda::std::cos(T(4 * cuda::std::numbers::pi) * T(idx) / T(size_ - 1)); }, i);\n" +
" }\n" +
" static __MATX_INLINE__ constexpr __MATX_DEVICE__ int32_t Rank() { return 1; }\n" +
" constexpr __MATX_INLINE__ __MATX_DEVICE__ index_t Size([[maybe_unused]] int dim) const { return size_; }\n" +
Expand All @@ -92,7 +92,7 @@ namespace matx
template <typename CapType>
__MATX_INLINE__ __MATX_HOST__ __MATX_DEVICE__ auto operator()(index_t i) const
{
return detail::ApplyGeneratorVecFunc<CapType, T>([this](index_t idx) { return T(.42) - T(.5) * cuda::std::cos(T(2 * M_PI) * T(idx) / T(size_ - 1))
return detail::ApplyGeneratorVecFunc<CapType, T>([this](index_t idx) { if (size_ == 1) { return T(1); } return T(.42) - T(.5) * cuda::std::cos(T(2 * M_PI) * T(idx) / T(size_ - 1))
+ T(.08) * cuda::std::cos(T(4 * M_PI) * T(idx) / T(size_ - 1)); }, i);
}

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2 changes: 2 additions & 0 deletions include/matx/generators/flattop.h
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Expand Up @@ -85,6 +85,7 @@ namespace matx
" __MATX_INLINE__ __MATX_DEVICE__ auto operator()(index_t i) const\n" +
" {\n" +
" return detail::ApplyGeneratorVecFunc<CapType, T>([](index_t idx) {\n" +
" if (size_ == 1) { return T(1); }\n" +
" static constexpr T tmp_pi = cuda::std::numbers::pi;\n" +
" return a0 - a1 * cuda::std::cos(static_cast<T>(2) * tmp_pi * idx / (size_ - 1)) + a2 * cuda::std::cos(static_cast<T>(4) * tmp_pi * idx / (size_ - 1)) - a3 * cuda::std::cos(static_cast<T>(6) * tmp_pi * idx / (size_ - 1)) + a4 * cuda::std::cos(static_cast<T>(8) * tmp_pi * idx / (size_ - 1));\n" +
" }, i);\n" +
Expand All @@ -108,6 +109,7 @@ namespace matx
inline __MATX_HOST__ __MATX_DEVICE__ auto operator()(index_t i) const
{
return detail::ApplyGeneratorVecFunc<CapType, T>([this](index_t idx) {
if (size_ == 1) { return T(1); }
static constexpr T tmp_pi = cuda::std::numbers::pi;
return a0
- a1 * cuda::std::cos(static_cast<T>(2)*tmp_pi*idx / (size_ - 1))
Expand Down
4 changes: 2 additions & 2 deletions include/matx/generators/hamming.h
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Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,7 @@ namespace matx
" template <typename CapType>\n" +
" __MATX_INLINE__ __MATX_DEVICE__ auto operator()(index_t i) const\n" +
" {\n" +
" return detail::ApplyGeneratorVecFunc<CapType, T>([](index_t idx) { return T(.54) - T(.46) * cuda::std::cos(T(2 * cuda::std::numbers::pi) * T(idx) / T(size_ - 1)); }, i);\n" +
" return detail::ApplyGeneratorVecFunc<CapType, T>([](index_t idx) { if (size_ == 1) { return T(1); } return T(.54) - T(.46) * cuda::std::cos(T(2 * cuda::std::numbers::pi) * T(idx) / T(size_ - 1)); }, i);\n" +
" }\n" +
" static __MATX_INLINE__ constexpr __MATX_DEVICE__ int32_t Rank() { return 1; }\n" +
" constexpr __MATX_INLINE__ __MATX_DEVICE__ index_t Size([[maybe_unused]] int dim) const { return size_; }\n" +
Expand All @@ -93,7 +93,7 @@ namespace matx
template <typename CapType>
inline __MATX_HOST__ __MATX_DEVICE__ auto operator()(index_t i) const
{
return detail::ApplyGeneratorVecFunc<CapType, T>([this](index_t idx) { return T(.54) - T(.46) * cuda::std::cos(T(2 * M_PI) * T(idx) / T(size_ - 1)); }, i);
return detail::ApplyGeneratorVecFunc<CapType, T>([this](index_t idx) { if (size_ == 1) { return T(1); } return T(.54) - T(.46) * cuda::std::cos(T(2 * M_PI) * T(idx) / T(size_ - 1)); }, i);
}

inline __MATX_HOST__ __MATX_DEVICE__ auto operator()(index_t i) const
Expand Down
4 changes: 2 additions & 2 deletions include/matx/generators/hanning.h
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Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,7 @@ namespace matx
" template <typename CapType>\n" +
" __MATX_INLINE__ __MATX_DEVICE__ auto operator()(index_t i) const\n" +
" {\n" +
" return detail::ApplyGeneratorVecFunc<CapType, T>([](index_t idx) { return T(0.5) * (1 - cuda::std::cos(T(2 * cuda::std::numbers::pi) * T(idx) / T(size_ - 1))); }, i);\n" +
" return detail::ApplyGeneratorVecFunc<CapType, T>([](index_t idx) { if (size_ == 1) { return T(1); } return T(0.5) * (1 - cuda::std::cos(T(2 * cuda::std::numbers::pi) * T(idx) / T(size_ - 1))); }, i);\n" +
" }\n" +
" static __MATX_INLINE__ constexpr __MATX_DEVICE__ int32_t Rank() { return 1; }\n" +
" constexpr __MATX_INLINE__ __MATX_DEVICE__ index_t Size([[maybe_unused]] int dim) const { return size_; }\n" +
Expand All @@ -93,7 +93,7 @@ namespace matx
template <typename CapType>
inline __MATX_HOST__ __MATX_DEVICE__ auto operator()(index_t i) const
{
return detail::ApplyGeneratorVecFunc<CapType, T>([this](index_t idx) { return T(0.5) * (1 - cuda::std::cos(T(2 * M_PI) * T(idx) / T(size_ - 1))); }, i);
return detail::ApplyGeneratorVecFunc<CapType, T>([this](index_t idx) { if (size_ == 1) { return T(1); } return T(0.5) * (1 - cuda::std::cos(T(2 * M_PI) * T(idx) / T(size_ - 1))); }, i);
}

inline __MATX_HOST__ __MATX_DEVICE__ T operator()(index_t i) const
Expand Down
2 changes: 1 addition & 1 deletion include/matx/generators/linspace.h
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Original file line number Diff line number Diff line change
Expand Up @@ -131,7 +131,7 @@ namespace matx
count_ = count;
for (int i = 0; i < NUM_RC; ++i) {
firsts_[i] = firsts[i];
steps_[i] = (lasts[i] - firsts[i]) / static_cast<T>(count - 1);
steps_[i] = (count > 1) ? (lasts[i] - firsts[i]) / static_cast<T>(count - 1) : static_cast<T>(0);
}
}

Expand Down
10 changes: 5 additions & 5 deletions include/matx/generators/logspace.h
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Expand Up @@ -96,20 +96,20 @@ namespace matx
{
#ifdef __CUDA_ARCH__
if constexpr (is_matx_half_v<T>) {
range_ = Range<T>{first, (last - first) / static_cast<T>(count - 1.0f)};
range_ = Range<T>{first, count > 1 ? (last - first) / static_cast<T>(count - 1.0f) : static_cast<T>(0.0f)};
}
else {
range_ = Range<T>{first, (last - first) / static_cast<T>(count - 1)};
range_ = Range<T>{first, count > 1 ? (last - first) / static_cast<T>(count - 1) : static_cast<T>(0)};
}
#else
// Host has no support for most half precision operators/intrinsics
if constexpr (is_matx_half_v<T>) {
range_ = Range<T>{static_cast<float>(first),
(static_cast<float>(last) - static_cast<float>(first)) /
static_cast<float>(count - 1)};
count > 1 ? (static_cast<float>(last) - static_cast<float>(first)) /
static_cast<float>(count - 1) : 0.0f};
}
else {
range_ = Range<T>{first, (last - first) / static_cast<T>(count - 1)};
range_ = Range<T>{first, count > 1 ? (last - first) / static_cast<T>(count - 1) : static_cast<T>(0)};
}
MATX_LOG_TRACE("Logspace constructor: first={}, last={}, count={}", first, last, count);
#endif
Expand Down
102 changes: 102 additions & 0 deletions test/00_operators/GeneratorTests.cu
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Expand Up @@ -137,6 +137,76 @@ TYPED_TEST(BasicGeneratorTestsFloatNonComplex, Windows)
MATX_EXIT_HANDLER();
}

TYPED_TEST(BasicGeneratorTestsFloatNonComplex, SingleElementWindows)
{
MATX_ENTER_HANDLER();

using TestType = cuda::std::tuple_element_t<0, TypeParam>;
using ExecType = cuda::std::tuple_element_t<1, TypeParam>;
ExecType exec{};
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auto ov = make_tensor<TestType>({1});
using Shape = cuda::std::array<index_t, 1>;
// These windows cannot currently be instantiated with half or bfloat16 output types.
using WindowType = cuda::std::conditional_t<is_matx_half_v<TestType>, float, TestType>;

// A one-point window is 1, matching numpy and scipy.
(ov = hanning<0, Shape, WindowType>({1})).run(exec);
exec.sync();
EXPECT_EQ(static_cast<float>(ov(0)), 1.0f);

(ov = hamming<0, Shape, WindowType>({1})).run(exec);
exec.sync();
EXPECT_EQ(static_cast<float>(ov(0)), 1.0f);

(ov = bartlett<0, Shape, TestType>({1})).run(exec);
exec.sync();
EXPECT_EQ(static_cast<float>(ov(0)), 1.0f);

(ov = blackman<0, Shape, WindowType>({1})).run(exec);
exec.sync();
EXPECT_EQ(static_cast<float>(ov(0)), 1.0f);

(ov = flattop<0, Shape, WindowType>({1})).run(exec);
exec.sync();
EXPECT_EQ(static_cast<float>(ov(0)), 1.0f);

MATX_EXIT_HANDLER();
}

TEST(OperatorTests, SingleElementLinspaceLogspace)
{
MATX_ENTER_HANDLER();
cudaExecutor exec{};

auto ov = make_tensor<float>({1});

// A single point is the start value, matching numpy.
(ov = linspace(2.0f, 5.0f, 1)).run(exec);
exec.sync();
EXPECT_EQ(ov(0), 2.0f);

(ov = logspace<0>({1}, 1.0f, 3.0f)).run(exec);
exec.sync();
EXPECT_NEAR(ov(0), 10.0f, 1e-4f);

// The endpoint must not matter for a single point, even when last - first overflows.
(ov = logspace<0>({1}, -1e38f, 3e38f)).run(exec);
exec.sync();
EXPECT_FALSE(std::isnan(ov(0)));
EXPECT_EQ(ov(0), 0.0f);

const float firsts[] = {2.0f, 3.0f};
const float lasts[] = {5.0f, 9.0f};
auto ov2 = make_tensor<float>({1, 2});
(ov2 = linspace(firsts, lasts, 1, 0)).run(exec);
exec.sync();
EXPECT_EQ(ov2(0, 0), 2.0f);
EXPECT_EQ(ov2(0, 1), 3.0f);

MATX_EXIT_HANDLER();
}

TYPED_TEST(BasicGeneratorTestsAll, Diag)
{
using TestType = cuda::std::tuple_element_t<0, TypeParam>;
Expand Down Expand Up @@ -824,6 +894,38 @@ TEST(OperatorTests, RandomJITCapabilityLimits)
MATX_EXIT_HANDLER();
}

#ifdef MATX_EN_JIT
TEST(OperatorTests, SingleElementWindowsJIT)
{
MATX_ENTER_HANDLER();
CUDAJITExecutor exec{};

auto ov = make_tensor<float>({1});

(ov = hanning<0>({1})).run(exec);
exec.sync();
EXPECT_EQ(ov(0), 1.0f);

(ov = hamming<0>({1})).run(exec);
exec.sync();
EXPECT_EQ(ov(0), 1.0f);

(ov = bartlett<0>({1})).run(exec);
exec.sync();
EXPECT_EQ(ov(0), 1.0f);

(ov = blackman<0>({1})).run(exec);
exec.sync();
EXPECT_EQ(ov(0), 1.0f);

(ov = flattop<0>({1})).run(exec);
exec.sync();
EXPECT_EQ(ov(0), 1.0f);

MATX_EXIT_HANDLER();
}
#endif

#if defined(MATX_EN_MATHDX) && defined(MATX_EN_JIT)
TEST(OperatorTests, RandomJITFusedUniform)
{
Expand Down