Sin
Applicability
Product |
Supported |
|---|---|
Atlas 350 Accelerator Card |
√ |
√ |
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√ |
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x |
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√ |
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x |
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x |
Function Usage
Performs element-wise sine computation using the following formula:

The Taylor's Formula of Sin(x) is as follows:

Prototype
- Pass the temporary space through the sharedTmpBuffer input parameter.
- All or part of the source operand tensors are involved in computation.
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template<typename T, bool isReuseSource = false, const SinConfig& config = defaultSinConfig> __aicore__ inline void Sin(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, const LocalTensor<uint8_t>& sharedTmpBuffer, const uint32_t calCount)
- All source operand tensors are involved in computation.
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template<typename T, bool isReuseSource = false, const SinConfig& config = defaultSinConfig> __aicore__ inline void Sin(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, const LocalTensor<uint8_t>& sharedTmpBuffer)
- All or part of the source operand tensors are involved in computation.
- Allocate the temporary space through the API framework.
- All or part of the source operand tensors are involved in computation.
1 2
template<typename T, bool isReuseSource = false, const SinConfig& config = defaultSinConfig> __aicore__ inline void Sin(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, const uint32_t calCount)
- All source operand tensors are involved in computation.
1 2
template<typename T, bool isReuseSource = false, const SinConfig& config = defaultSinConfig> __aicore__ inline void Sin(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor)
- All or part of the source operand tensors are involved in computation.
Due to the complex mathematical computation involved in the internal implementation of this API, additional temporary space is required to store intermediate variables generated during computation. The temporary space can be passed by developers through the sharedTmpBuffer input parameter or allocated through the API framework.
- When the API framework is used for temporary space allocation, developers do not need to allocate the space, but must reserve the required size for the space.
- When the sharedTmpBuffer input parameter is used for passing the temporary space, the tensor serves as the temporary space. In this case, the API framework is not required for temporary space allocation. This enables developers to manage the sharedTmpBuffer space and reuse the buffer after calling the API, so that the buffer is not repeatedly allocated and deallocated, improving the flexibility and buffer utilization.
If the API framework is used, developers must reserve the temporary space. If sharedTmpBuffer is used, developers must allocate space for the tensor. To obtain the size of the temporary space (BufferSize) to be reserved, use the GetSinMaxMinTmpSize API.
Parameters
Parameter |
Description |
|---|---|
T |
Data type of the operand. For the Atlas 350 Accelerator Card, the supported data types are half and float. For the For the For the |
isReuseSource |
Whether the source operand can be modified. The default value is false. This parameter is valid only when the input data type is float.
|
config |
Only the Atlas 350 Accelerator Card supports this option. Sin algorithm configuration. This is an optional parameter of the SinConfig type. The code below describes the definition. algo: an algorithm used for internal implementation of Sin. It is of the SinAlgo type. The supported values are as follows:
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1 2 3 4 5 6 7 | struct SinConfig { SinAlgo algo = SinAlgo::POLYNOMIAL_APPROXIMATION; } enum class SinAlgo { POLYNOMIAL_APPROXIMATION = 0; RADIAN_REDUCTION; } |
Parameter |
Input/Output |
Description |
|---|---|---|
dstTensor |
Output |
Destination operand. The type is LocalTensor, and TPosition can be VECIN, VECCALC, or VECOUT. |
srcTensor |
Input |
Source operand. The type is LocalTensor, and TPosition can be VECIN, VECCALC, or VECOUT. The source operand must have the same data type as the destination operand. |
sharedTmpBuffer |
Input |
Temporary buffer. The type is LocalTensor, and TPosition can be VECIN, VECCALC, or VECOUT. This parameter is used to store intermediate variables during complex computation in Sin and is provided by developers. For details about how to obtain the temporary space size (BufferSize), see GetSinMaxMinTmpSize. |
calCount |
Input |
Number of elements involved in the computation. |
Returns
None
Restrictions
- For the Atlas 350 Accelerator Card, when the polynomial fitting algorithm POLYNOMIAL_APPROXIMATION is used in the template parameter config, ensure that the input source data must be within the value range of [–65504.0, 65504.0].
- For the following products, the input source data must be within the value range of [–65504.0, 65504.0].
Atlas A3 training product /Atlas A3 inference product Atlas A2 training product /Atlas A2 inference product Atlas inference product AI Core
- The source operand address must not overlap the destination operand address.
- The address of sharedTmpBuffer must not overlap the addresses of the source operand and destination operand.
- For details about the operand address alignment requirements, see General Address Alignment Restrictions.
Example
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | // dstLocal: tensor for storing the Sin computation result // srcLocal: tensor for storing the Sin computation input // sharedTmpBuffer: tensor for storing the temporary buffer during Sin computation // Allocate the temporary space through the API framework, all of which is used for computation. AscendC::Sin(dstLocal, srcLocal); // Allocate the temporary space through the API framework, part of which is used for computation, with the number of elements involved in the computation being 512. AscendC::Sin(dstLocal, srcLocal, 512); // Pass the temporary space through the sharedTmpBuffer input parameter, all of which is used for computation. AscendC::Sin(dstLocal, srcLocal, sharedTmpBuffer); // Pass the temporary space through the sharedTmpBuffer input parameter, part of which is used for computation, with the number of elements involved in computation being 512. AscendC::Sin(dstLocal, srcLocal, sharedTmpBuffer, 512); constexpr AscendC::SinAlgo algo = AscendC::SinAlgo::RADIAN_REDUCTION; constexpr AscendC::SinConfig config = { algo }; AscendC::Sin<half, false, config>(dstLocal, srcLocal, sharedTmpBuffer, 512); |
1 2 3 4 | Input (srcLocal): [-2.56 -2.55 -2.54 ... 0. ... 2.53 2.54 2.55] Output (dstLocal): [-0.54889839 -0.55703507 -0.56672889 ... 0. 0.57474768 0.56672889 0.55703507] |