include_math_kernels.h

namespace ONNX_LIGHT_NAMESPACE

namespace onnx_backend_test

namespace kernel

class Abs

#include <include_math_kernels.h>

Element-wise absolute value.

Public Functions

inline explicit Abs(const KernelContext &ctx)

Tensor operator()(const Tensor &x) const

void operator()(const Tensor &x, Tensor &output) const

Public Static Functions

static inline constexpr bool CanRunInPlace() noexcept

Element-wise unary kernel: the output buffer may alias the input buffer.

Private Members

KernelContext ctx_

class Add

#include <include_math_kernels.h>

Element-wise addition with NumPy-style broadcasting.

Public Functions

inline explicit Add(const KernelContext &ctx)

Tensor operator()(const Tensor &x, const Tensor &y) const

void operator()(const Tensor &x, const Tensor &y, Tensor &output) const

Public Static Functions

static inline constexpr bool CanRunInPlace() noexcept

Element-wise binary kernel: the output buffer may alias an input buffer when that input is not broadcast-expanded (i.e. its shape equals the output shape).

Private Members

KernelContext ctx_

class BlackmanWindow

#include <include_math_kernels.h>

BlackmanWindow function evaluated at size integer samples. When periodic is true the window is computed as if of length size+1 and the last sample is discarded (matches NumPy/ONNX conventions).

Public Functions

inline explicit BlackmanWindow(const KernelContext &ctx)

Tensor operator()(const Tensor &size, bool periodic = true) const

void operator()(const Tensor &size, bool periodic, Tensor &output) const

Public Static Functions

static inline constexpr bool CanRunInPlace() noexcept

Output is a float vector while the input is an int scalar: storage can never be shared with an input.

Private Members

KernelContext ctx_