---
title: conv1d_gemm_?
description: "GEMM算法实现的通用1D卷积接口。"
url: https://www.hikunpeng.com/document/detail/zh/hpchistory/hpckit/develop2400/kunpengaccel_kml_17_0013.html
sourcePath: /source/zh/hpchistory/hpckit/develop2400/kunpengaccel_kml_17_0013.html
indexId: 9d36fbd75f29f0786ff3cf4957e5e7ed5ed1444d76c14dd969c93c37c7c045fe70
---
# conv1d_gemm_?

GEMM算法实现的通用1D卷积接口。

#### 接口定义

C interface：

void conv1d_gemm_fp32(const float *input, const int batch, const int inputChannels, const int inputLength, const float* kernel, const int kernelLength, const int stride, const int padLength, const int dilation, const float *bias, float *output, const int outputChannels);

void conv1d_gemm_fp16(const __fp16 *input, const int batch, const int inputChannels, const int inputLength, const __fp16 *kernel, const int kernelLength, const int stride, const int padLength, const int dilation, const __fp16 *bias, __fp16 *output, const int outputChannels);


#### 参数

| 参数名 | 类型 | 描述 | 输入/输出 |
| --- | --- | --- | --- |
| input | conv1d\_gemm\_fp32中是float类型 conv1d\_gemm\_fp16中是\_\_fp16类型 | 输入数据 | 输入 |
| batch | int类型 | 输入数据的批数 | 输入 |
| inputChannels | int类型 | 输入通道数 | 输入 |
| inputLength | int类型 | 输入数据的长度 | 输入 |
| kernel | conv1d\_gemm\_fp32中是float类型 conv1d\_gemm\_fp16中是\_\_fp16类型 | 卷积核 | 输入 |
| kernelLength | int类型 | 卷积核长度 | 输入 |
| stride | int类型 | 步长 | 输入 |
| padLength | int类型 | 在原始input数据两端分别置零的长度 | 输入 |
| dilation | int类型 | 膨胀系数 | 输入 |
| bias | conv1d\_gemm\_fp32中是float类型 conv1d\_gemm\_fp16中是\_\_fp16类型 | 偏置值, 值为NULL时表示无偏置 | 输入 |
| output | conv1d\_gemm\_fp32中是float类型 conv1d\_gemm\_fp16中是\_\_fp16类型 | 输出结果数据 | 输出 |
| outputChannels | int类型 | 输出通道数 | 输入 |


#### 依赖

#include "conv.h"


#### 示例

C interface：

```
int batch = 1;
int inputChannels = 1;
int inputLength = 10;
int kernelLength = 3;
int stride = 1;
int padLength = 0;
int dilation = 1;
int outputChannels = 1;
float input[10] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0};
float kernel[3] = {1.0, 2.0, 3.0};
float *bias = NULL;
int outputLength = (inputLength + 2 * padLength - dilation * (kernelLength - 1) - 1) / stride + 1;
/*
*
outputLength = 8
*/
float output[8] = {0.0};
conv1d_gemm_fp32(input, batch, inputChannels, inputLength, kernel, kernelLength, stride, padLength, dilation, bias, output, outputChannels);
/*
* output = [14.0 20.0 26.0 32.0 38.0 44.0 50.0 56.0]
*/
```