nn-sdk 1.2.9

nn_sdk推理tf1 tf2 pb nlp模型 , input tensor[input_ids , input_mask], output tensor[pred_ids]

nn-sdk是一个基于tf1 tf2神经网络推理开发包

# -*- coding: utf-8 -*-
from nn_sdk.py_tf_csdk import csdk_object
'''
    python 推理demo
    支持 python (demo.py) , c (nn_sdk.h) , java (nn_sdk.java)
    python 使用如下
    支持多子图,支持图多输入多输出.
    支持tensorflow 1 pb , tensorflow 2 pb , tensorflow ckpt
    net_stage 推理子图序号0-n
'''
config = {
    "model_dir": r'./model.ckpt',
    "log_level": 4, # 0 fatal , 2 error , 4 info , 8 debug
    "model_type": 1,  # 0 pb format   if 1 ckpt format
    "ConfigProto": {
        "log_device_placement": False,
        "allow_soft_placement": True,
        "gpu_options": {
            "allow_growth": True
        },
    },
    "graph_inf_version": 1,  # the format of tensorflow pb model [1,2]
    "graph": [
        {
            #tf 1 node sample "input_ids:0" ,  tf2 sample "input_ids"  data_type  int int64 long longlong float double
            #python 接口可以忽视 data_type,shape字段,在 c接口会使用，例子 python {"node":"input_ids:0"}
            "input": [
                {"node":"input_ids:0", "data_type":"float", "shape":[1, 256]},
                {"node":"input_mask:0", "data_type":"float", "shape":[1, 256]}
            ],
            "output": [
                {"node":"input_ids:0", "data_type":"float", "shape":[1, 256]},
            ],
        }
    ]}

seq_length = 256
input_ids = [[10.] * seq_length]
input_mask = [[1] * seq_length]
sdk_inf = csdk_object(config)
if sdk_inf.valid():
    net_stage = 0
    ret, out = sdk_inf.process(net_stage, input_ids,input_mask)
    print(ret)
    print(out)
    sdk_inf.close()

nn-sdk java

package nn_sdk;
//包名必须是nn_sdk
public class nn_sdk {
    //输入输出内存节点，名字跟图配置一样，根据图对象修改此属性。 
	public float [] input_ids = null;//推理图的输入,
	//public float [] input_mask = null;//推理图的输入,
	public float[] pred_ids =   null;//推理的结果保存

	public nn_sdk() {
		//初始化配置图的输入输出内存
		input_ids = new float[1 * 20];
		pred_ids =  new float[1 * 20];
		for(int i =0;i<20;i++) {
			input_ids[i] = 1;
			pred_ids[i] = 0;
		}
	}

	//推理函数
	public native static int  sdk_init_cc();
	public native static int  sdk_uninit_cc();
	public native static long sdk_new_cc(String json);
	public native static int  sdk_delete_cc(long handle);
	public native static int sdk_process_cc(long handle, int net_state, nn_sdk data);

	static {
		//动态库的绝对路径windows是tf_csdk.pyd , linux是 tf_csdk.so
		System.load("E:\\algo_text\\nn_csdk\\build_py36\\Release\\tf_csdk.pyd");  
	}

	public static void main(String[] args){  
		System.out.println("java main...........");

	   nn_sdk instance = new nn_sdk();
	   sdk_init_cc();

	   String json =  "{" + "\"model_dir\": \"E:/algo_text/nn_csdk/nn_csdk/py_test_ckpt/model.ckpt\"," + "\n" +
	   "\"log_level\":4," + "\n" +
	   "\"model_type\":1, " + "\n" +
	   "\"ConfigProto\": {" + "\n" +
				 "\"log_device_placement\":false," + "\n" +
	   "\"allow_soft_placement\":true," + "\n" +
				 "\"gpu_options\":{\"allow_growth\": true}" + "\n" +
	   "}," + "\n" +
				 "\"graph_inf_version\": 1," + "\n" +
	   "\"graph\": [" + "\n" +
				 "{" + "\n" +
	   "\"input\": [{\"node\":\"input_ids:0\", \"data_type\":\"float\", \"shape\":[1, 20]}]," + "\n" +
				 "\"output\" : [{\"node\":\"pred_ids:0\", \"data_type\":\"float\", \"shape\":[1, 20]}]" + "\n" +
	"}" + "\n" +
				 "]" + "\n" +
	"}";


	  System.out.println(json);

	  long handle = sdk_new_cc(json);
	  System.out.println(handle);

	  int code = sdk_process_cc(handle,0,instance);
	  System.out.printf("sdk_process_cc %d \n" ,code);
	  if(code == 0) {
		  for(int i = 0;i<20 ; i++) {
			  System.out.printf("%f ",instance.pred_ids[i]);
		  }
		  System.out.println();
	  }
	  sdk_delete_cc(handle);
	   sdk_uninit_cc();
	   System.out.println("end");
	}
}

nn-sdk c

#ifndef __CC_SDK_H__
#define __CC_SDK_H__

#include <stdio.h>


#ifdef _WIN32
#ifdef _CC_SDK_EXPORT
#define CC_SDK_EXPORT _declspec( dllexport )
#else
#define CC_SDK_EXPORT _declspec(dllimport)
#endif
#else
#define CC_SDK_EXPORT
#endif // _WIN32



#ifdef __cplusplus
extern "C" {
#endif

	typedef long long SDK_HANDLE_CC;

	CC_SDK_EXPORT int sdk_init_cc();

	CC_SDK_EXPORT int sdk_uninit_cc();

	CC_SDK_EXPORT SDK_HANDLE_CC sdk_new_cc(const char* json);

	CC_SDK_EXPORT int sdk_delete_cc(SDK_HANDLE_CC handle);

	CC_SDK_EXPORT int sdk_process_ex_cc(SDK_HANDLE_CC handle, void** final_result, int net_stage, void**input_buffer_list);

#ifdef __cplusplus
}
#endif


#endif