Log

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 logarithm computations with bases e, 2, and 10 using the following formulas:

Prototype

  • e as the base:
    • All or part of the source operand tensors are involved in computation.
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    template<typename T, bool isReuseSource = false>
    __aicore__ inline void Log(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, uint32_t calCount)
    
    • All source operand tensors are involved in computation.
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    template<typename T, bool isReuseSource = false>
    __aicore__ inline void Log(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor)
    
  • 2 as the base:
    • 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>
        __aicore__ inline void Log2(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, const LocalTensor<uint8_t>& sharedTmpBuffer, uint32_t calCount)
        
      • All source operand tensors are involved in computation.
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        template <typename T, bool isReuseSource = false>
        __aicore__ inline void Log2(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.
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        template<typename T, bool isReuseSource = false>
        __aicore__ inline void Log2(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, uint32_t calCount)
        
      • All source operand tensors are involved in computation.
        1
        2
        template <typename T, bool isReuseSource = false>
        __aicore__ inline void Log2(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor)
        
  • 10 as the base:
    • All or part of the source operand tensors are involved in computation.
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      template<typename T, bool isReuseSource = false>
      __aicore__ inline void Log10(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, uint32_t calCount)
      
    • All source operand tensors are involved in computation.
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      template<typename T, bool isReuseSource = false>
      __aicore__ inline void Log10(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 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.
  • 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.

If sharedTmpBuffer is used, developers must allocate space for the tensor. If the API framework is used, developers must reserve the temporary space. To obtain the size of the temporary space (BufferSize) to be reserved, use the API provided in GetLogMaxMinTmpSize.

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 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 GetLogMaxMinTmpSize.

calCount

Input

Number of elements involved in the computation.

Returns

None

Restrictions

Example

For a complete call example, see Log operator sample.

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// dstLocal: tensor for storing the computation result
// srcLocal: input tensor involved in computation

// e as the base. All elements are involved in the computation.
AscendC::Log(dstLocal, srcLocal);
// 10 as the base
// AscendC::Log10(dstLocal, srcLocal);
// 2 as the base
// AscendC::Log2(dstLocal, srcLocal);
Result example of the Log API:
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Input (srcLocal): [144.22607 9634.764 ... 1835.1245 3145.5125]
Output (dstLocal): [4.971382 9.173133 ... 7.514868 8.053732]
Result example of the Log2 API:
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Input (srcLocal): [6299.54 338.45963 ... 2.853525 5752.1323]
Output (dstLocal): [12.621031 8.40284 ... 1.5127451 12.4898815]
Result example of the Log10 API:
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Input (srcLocal): [712.7535 78.36265 ... 3099.0571 9313.082]
Output (dstLocal): [2.8529394 1.8941091 ... 3.4912295 3.9690933]