Cosh

Applicability

Product	Supported
Atlas 350 Accelerator Card	√
Atlas A3 training product/Atlas A3 inference product	√
Atlas A2 training product/Atlas A2 inference product	√
Atlas 200I/500 A2 inference product	x
Atlas inference product AI Core	√
Atlas inference product Vector Core	x
Atlas training product	x

Function Usage

Performs element-wise hyperbolic cosine computation using the following formula:

$\text{[math]}$

Prototype

Pass the temporary space through the sharedTmpBuffer input parameter.

All or part of the source operand tensors are involved in computation.

template <typename T, bool isReuseSource = false>
__aicore__ inline void Cosh(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.

template <typename T, bool isReuseSource = false>
__aicore__ inline void Cosh(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.

template <typename T, bool isReuseSource = false>
__aicore__ inline void Cosh(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, const uint32_t calCount)

All source operand tensors are involved in computation.

template <typename T, bool isReuseSource = false>
__aicore__ inline void Cosh(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 allocated through the API framework or passed by developers through the sharedTmpBuffer input parameter.

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 API provided in GetCoshMaxMinTmpSize.

Parameters

**Table 1** Template 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 Atlas A3 training product/Atlas A3 inference product, the supported data types are half and float. For the Atlas A2 training product/Atlas A2 inference product, the supported data types are half and float. For the Atlas inference product AI Core, the supported data types are half and float.
isReuseSource	Whether the source operand can be modified. This parameter is reserved. Pass the default value false.

**Table 2** API parameters
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. For details about how to obtain the temporary space size (BufferSize), see GetCoshMaxMinTmpSize.
calCount	Input	Number of elements involved in the computation.

Returns

None

Restrictions

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

For more examples, see Cosh operator sample.

// dstLocal: tensor for storing the computation result
// srcLocal: input tensor involved in computation
// sharedTmpBuffer: temporary buffer for storing intermediate variables during complex internal computation
// The input tensor length is 512, the input data type of the operator is half, and the number of actually computed data elements is 256.
AscendC::Cosh(dstLocal, srcLocal, sharedTmpBuffer, 256);

Result example:

// Use the last three special values for verification.
Input (srcLocal): [0.000000   0.010000  0.020000  ...  2.520000  -11.089000    0.000000  11.089000]
Output (dstLocal): [1.000000   1.000050  1.000200  ...  6.254528  32723.625000  1.000000  32723.625000]

Parent topic: Cosh APIs