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ryujaehun/data_visualization.ipynb

Created April 8, 2020 06:14
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data_visualization_test
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data_visualization.ipynb
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"Using matplotlib backend: GTK3Agg\n",
"Populating the interactive namespace from numpy and matplotlib\n"
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"# import library\n",
"%pylab\n",
"%matplotlib inline\n",
"import pandas as pd\n",
"import os,glob,re\n",
"import cufflinks as cf\n",
"import plotly.offline\n",
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"import time"
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"# define path\n",
"result_folder_path='/home/jaehun/results'\n",
"llvm_result_folder_path=os.path.join(result_folder_path,'llvm')\n",
"cuda_result_folder_path=os.path.join(result_folder_path,'cuda')\n",
"llvm_result_folder_list=glob.glob(llvm_result_folder_path+'/*/*.out')\n",
"cuda_result_folder_list=glob.glob(cuda_result_folder_path+'/*/*.out')\n",
"# sort list\n",
"llvm_result_folder_list.sort()\n",
"cuda_result_folder_list.sort()\n",
"columns=['network','batchs','threads','algorithm','trials','mean_inference_time(ms)','std_inference_time(ms)']"
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"results_llvm=[]\n",
"\n",
"for i in llvm_result_folder_list:\n",
" with open(i, 'r') as f:\n",
" for line in f.readlines():\n",
" if 'Mean' in line:\n",
" times=re.findall('\\d+.\\d+',line)\n",
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" results_llvm.append([temp[1][:-1],temp[-5][0],temp[-5][1],temp[-3],temp[-1],float(times[0]),float(times[1])])\n",
" \n",
"# print('network: ',temp[1][:-1],'batch: ',temp[-5][0],'threads: ',temp[-5][1],\\\n",
"# 'algorithm: ',temp[-3],'trial',temp[-1],'\\nmean_inference_time: ',times[0],'std_inference_time: ',times[1],'\\n')\n",
" "
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"llvm=pd.DataFrame(data=results_llvm,columns=columns)\n",
"llvm.to_csv('~/llvm.csv',index=False)"
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