Sin

Applicability

Function

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.

    1 2	template<typename T, bool isReuseSource = false> __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.

    1 2	template<typename T, bool isReuseSource = false> __aicore__ inline void Sin(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, const LocalTensor<uint8_t>& sharedTmpBuffer)

• 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> __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> __aicore__ inline void Sin(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor)

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

Returns

None

Restrictions

• For the following products, the input source data must be within the value range of [–65504.0, 65504.0].
  • Atlas A3 training products/Atlas A3 inference products
  • Atlas A2 training products/Atlas A2 inference products
  • Atlas inference product's 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

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AscendC::TPipe pipe;
AscendC::TQue<AscendC::TPosition::VECCALC, 1> tmpQue;
pipe.InitBuffer(tmpQue, 1, bufferSize); // bufferSize is obtained through the tiling parameter on the host.
AscendC::LocalTensor<uint8_t> sharedTmpBuffer = tmpQue.AllocTensor<uint8_t>();
// The input tensor length is 1024, the input data type of the operator is half, and the number of actually computed data elements is 512.
AscendC::Sin(dstLocal, srcLocal, sharedTmpBuffer, 512);

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Input data (srcLocal):
[-0.44476402 -0.43156096 -0.38648438  0.30285975 -0.73223037 -0.57837343 ... -0.25575528  0.5976324 ]
Output data (dstLocal):
[-0.43024486 -0.41828915 -0.37693444  0.29825103 -0.66853    -0.5466626 ... -0.25297618  0.56268686]