mirror of
https://github.com/storytold/storyteller-ml.git
synced 2026-10-19 07:54:56 +00:00
Justin John
316 lines
8.3 KiB
C++
316 lines
8.3 KiB
C++
#include <stdlib.h>
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#include <stdio.h>
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#include <string.h>
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#include <math.h>
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#include <vector>
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#include "tensorflow2.h"
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#define NORMAL "\033[0m"
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#define BLACK "\033[30m" /* Black */
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#define RED "\033[31m" /* Red */
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#define GREEN "\033[32m" /* Green */
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#define YELLOW "\033[33m" /* Yellow */
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float rand_FloatRange(float a, float b)
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{
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return ((b - a) * ((float)rand() / RAND_MAX)) + a;
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}
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int testFloat16()
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{
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unsigned int maxErrors = 10000;
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unsigned int errors=0;
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for (int i=0; i<maxErrors; i++)
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{
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float r1 = rand_FloatRange(-1000,1000);
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float r2 = convertFloat16ToFloat32(convertFloat32ToFloat16(r1));
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float distance = sqrt( (r1-r2) * (r1-r2) );
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if (distance>0.4)
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{
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fprintf(stderr,"%f ",distance);
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++errors;
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}
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}
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fprintf(stderr,"\n\n%u errors / %0.2f %% \n",errors,(float) errors*100/maxErrors);
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return (errors==0);
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}
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int testUpperBody()
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{
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const char* savedModelDirectory = "/home/ammar/Documents/Programming/DNNTracker/tensorflow2GPU/src/tmp.pb/";
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int runOnCPU=1;
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int ndims = 2;
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int64_t dims[] = {1,322};
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//-----------------------------
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float data[1*322];
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for(int i=0; i< (1*322); i++)
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{
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data[i] = 1.00;
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}
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int ndata = sizeof(float)*1*322 ; //number of bytes not number of element
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//-----------------------------
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unsigned int numberOfInputElements = 322;
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unsigned int numberOfOutputElements = 42;
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char inputTensor[]={"input_front"};
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char outputTensor[]={"result_front/concat"};
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//Tensorflow v2 test..
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struct Tensorflow2Instance upperbodyFrontv2={0};
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if ( tf2_loadModel(&upperbodyFrontv2,savedModelDirectory,inputTensor,numberOfInputElements,numberOfOutputElements,runOnCPU) )
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{
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if ( tf2_run(&upperbodyFrontv2,dims,ndims,data,ndata) )
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{
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void* buff = TF_TensorData(upperbodyFrontv2.outputValues[0]);
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float* offsets = (float*)buff;
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printf("Result Tensor v2:\n");
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for(int i=0;i<upperbodyFrontv2.outputElements;i++)
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{
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if(i>0) { printf(","); }
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printf("%f",offsets[i]);
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}
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printf("\n");
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} else
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{
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fprintf(stderr,"Failed tf2_run\n");
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}
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printf("Deallocating v2 \n");
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tf2_unloadModel(&upperbodyFrontv2);
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} else
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{
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fprintf(stderr,"Failed tf2_loadModel\n");
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}
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//Tensorflow v1 test..
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struct Tensorflow2Instance upperbodyFrontv1={0};
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if ( tf2_loadFrozenGraph(&upperbodyFrontv1,"dataset/combinedModel/mocapnet2/mode5/1.0/upperbody_front.pb",inputTensor,outputTensor,numberOfInputElements,numberOfOutputElements,runOnCPU) )
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{
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if ( tf2_run(&upperbodyFrontv1,dims,ndims,data,ndata) )
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{
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fprintf(stderr,"Ready to run..!\n");
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tf2_run(&upperbodyFrontv1,dims,ndims,data,ndata);
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void* buff = TF_TensorData(upperbodyFrontv1.outputValues[0]);
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float* offsets = (float*)buff;
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printf("Result Tensor v1:\n");
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for(int i=0;i<upperbodyFrontv1.outputElements;i++)
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{
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if(i>0) { printf(","); }
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printf("%f",offsets[i]);
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}
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printf("\n");
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}
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printf("Deallocating v1 \n");
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tf2_unloadModel(&upperbodyFrontv1);
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}
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printf("Done\n");
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return 0;
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}
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#include <unistd.h>
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int executeCommandLineAndRetreiveAllResults(const char * command , char * what2GetBack , unsigned int what2GetBackMaxSize, unsigned long * what2GetBackSize)
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{
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/* Open the command for reading. */
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FILE * f = popen(command, "r");
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if (f == 0)
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{
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fprintf(stderr,"Failed to run command (%s) \n",command);
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return 0;
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}
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size_t contentSize = fread(what2GetBack, 1 , what2GetBackMaxSize, f);
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*what2GetBackSize = contentSize;
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/* close */
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pclose(f);
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return 1;
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}
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int getInfoFast(const char * field,char * buffer,unsigned int bufferSize,char terminatorCharacter)
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{
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int fieldOffset = strlen(field);
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char * foundAt = strstr(buffer,field);
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if (foundAt!=0)
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{
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foundAt += fieldOffset;
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char * termination = strchr(foundAt,terminatorCharacter);
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if (termination!=0)
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{
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char retainOldTerminator = *termination;
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*termination = 0;
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fprintf(stderr,"Field `%s` => `%s` \n",field,foundAt);
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*termination =retainOldTerminator;
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}
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}
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return 0;
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}
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int testHands()
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{
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// const char* savedModelDirectory = "/home/ammar/Documents/Programming/DNNTracker/DNNTracker/dataset/combinedModel/mocapnet2/mode1/1.0/rhand_half_all.pb";
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const char* savedModelDirectory = "/home/ammar/Documents/Programming/DNNTracker/DNNTracker/dataset/combinedModel/mocapnet2/mode1/1.0/lhand_all.pb";
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#define NUMBER_OF_OUTPUTS 52
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#define NUMBER_OF_INPUTS 319
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int runOnCPU=1;
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int ndims = 2;
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int64_t dims[] = {1,NUMBER_OF_INPUTS};
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//-----------------------------
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float data[1*NUMBER_OF_INPUTS];
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for(int i=0; i< (1*NUMBER_OF_INPUTS); i++)
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{
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data[i] = 1.00;
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}
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int ndata = sizeof(float)*1*NUMBER_OF_INPUTS ; //number of bytes not number of element
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//-----------------------------
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//Check using external tool and a parser
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//-------------------------------------
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tf2_checkModelUsingExternalTool(savedModelDirectory);
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/*
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static int maxOutputLength=4096;
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unsigned long outputSize=0;
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char output[maxOutputLength]={0};
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executeCommandLineAndRetreiveAllResults(commandToCheck,output,maxOutputLength,&outputSize);
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fprintf(stderr,"Retrieved.. %s\n",output);
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getInfoFast("inputs['",output,outputSize,'\'');
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getInfoFast("shape: ",output,outputSize,10);
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getInfoFast("name: ",output,outputSize,10);
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char * outputTensorsStart = strstr(output,"output(s):");
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if (outputTensorsStart!=0)
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{
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getInfoFast("outputs['",outputTensorsStart,outputSize,'\'');
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getInfoFast("shape: ",outputTensorsStart,outputSize,10);
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getInfoFast("name: ",output,outputSize,10);
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}
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//-------------------------------------
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*/
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unsigned int numberOfInputElements = NUMBER_OF_INPUTS;
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unsigned int numberOfOutputElements = NUMBER_OF_OUTPUTS;
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//https://medium.com/analytics-vidhya/deploying-tensorflow-2-1-as-c-c-executable-1d090845055c
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char inputTensor[]={"input_all"}; //{"input_front"};
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char outputTensor[]={"result_all/concat"}; //{"result_front/concat"};
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//Tensorflow v2 test..
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struct Tensorflow2Instance upperbodyFrontv2={0};
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if ( tf2_loadModel(&upperbodyFrontv2,savedModelDirectory,inputTensor,numberOfInputElements,numberOfOutputElements,runOnCPU) )
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{
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upperbodyFrontv2.inputIsHalfFloats=1;
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if ( tf2_run(&upperbodyFrontv2,dims,ndims,data,ndata) )
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{
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void* buff = TF_TensorData(upperbodyFrontv2.outputValues[0]);
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float* offsets = (float*)buff;
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printf("Result Tensor v2:\n");
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for(int i=0; i<upperbodyFrontv2.outputElements; i++)
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{
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if(i>0) { printf(","); }
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printf("%f",offsets[i]);
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}
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printf("\n");
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} else
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{
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fprintf(stderr,"Failed tf2_run\n");
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}
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printf("Deallocating v2 \n");
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tf2_unloadModel(&upperbodyFrontv2);
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} else
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{
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fprintf(stderr,RED "Failed tf2_loadModel\n" NORMAL);
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}
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//Tensorflow v1 test..
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struct Tensorflow2Instance upperbodyFrontv1={0};
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if ( tf2_loadFrozenGraph(&upperbodyFrontv1,"dataset/combinedModel/mocapnet2/mode1/1.0/_rhand_all.pb",inputTensor,outputTensor,numberOfInputElements,numberOfOutputElements,runOnCPU) )
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{
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if ( tf2_run(&upperbodyFrontv1,dims,ndims,data,ndata) )
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{
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fprintf(stderr,"Ready to run..!\n");
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tf2_run(&upperbodyFrontv1,dims,ndims,data,ndata);
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void* buff = TF_TensorData(upperbodyFrontv1.outputValues[0]);
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float* offsets = (float*)buff;
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printf("Result Tensor v1:\n");
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for(int i=0; i<upperbodyFrontv1.outputElements; i++)
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{
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if(i>0) { printf(","); }
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printf("%f",offsets[i]);
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}
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printf("\n");
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}
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printf("Deallocating v1 \n");
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tf2_unloadModel(&upperbodyFrontv1);
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}
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printf("Done\n");
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return 0;
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}
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int main()
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{
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testFloat16();
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return testHands();
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//return testUpperBody();
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}
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