| | import os |
| | |
| | |
| | |
| | import json |
| | import time |
| | import csv |
| | import pathlib |
| | import difflib |
| | import re |
| | from bleu import _bleu |
| | from fuzzywuzzy import fuzz |
| | import random |
| | import numpy as np |
| | from transformers import RobertaTokenizer |
| | |
| |
|
| | folder = str(pathlib.Path(__file__).parent.resolve()) |
| | isa_type_dir = folder+"/../../../Dataset" |
| | src_dir = folder+"/../../../Dataset/Code_Generation" |
| | dst_dir = folder |
| |
|
| | train_lis = [] |
| | valid_lis = [] |
| | test_lis = [] |
| |
|
| | target_clf = {} |
| | def get_target_clf_list(): |
| | global target_clf |
| | with open(isa_type_dir+"/comback_isa_type.csv","r",encoding="utf-8") as f: |
| | reader = csv.reader(f) |
| | for idx, l in enumerate(reader): |
| | if l[1].lower() == "arc" or l[1].lower() == "riscv" or l[1].lower() == "nvptx": |
| | continue |
| | if l[0] + " " + l[2] not in target_clf.keys(): |
| | target_clf[l[0] + " " + l[2]] = [l[1]] |
| | else: |
| | target_clf[l[0] + " " + l[2]] += [l[1]] |
| |
|
| |
|
| | def Calculate_Statements_Ratio(Src_List, Fork_Lis, src_name, fork_name): |
| | src_code = "" |
| | Fork_code = "" |
| | idx = 0 |
| | cnt_stmt = 0.0 |
| | while idx < len(Src_List): |
| | src_code += Src_List[idx].replace(src_name, "").replace(src_name.upper(), "") |
| | if Src_List[idx] in [";", ":", "{", "}"]: |
| | src_code += "\n" |
| | cnt_stmt += 1 |
| | idx += 1 |
| | while idx < len(Fork_Lis): |
| | Fork_code += Fork_Lis[idx].replace(fork_name, "").replace(fork_name.upper(), "") |
| | if Fork_Lis[idx] in [";", ":", "{", "}"]: |
| | Fork_code += "\n" |
| | idx += 1 |
| | |
| | code_same = 0 |
| | code_modi = 0 |
| | code_add = 0 |
| | diff_code = list(difflib.Differ().compare(src_code.splitlines(), Fork_code.splitlines())) |
| | for idx, dv in enumerate(diff_code): |
| | if dv[0] == '-': |
| | if idx < len(diff_code) - 1 and diff_code[idx+1][0] == '?': |
| | code_modi += 1 |
| | else: |
| | code_add += 1 |
| | elif dv[0] == '+': |
| | continue |
| | elif dv[0] == '?': |
| | continue |
| | |
| | elif dv.strip().replace("\n", "") == '': |
| | continue |
| | else: |
| | code_same += 1 |
| | return round(float(code_same) / cnt_stmt, 2) |
| |
|
| |
|
| |
|
| | def Calculate_ChatGPT(): |
| | get_target_clf_list() |
| | print("############## Exp 2: Calculate ChatGPT Gen ################\n") |
| | |
| | test_lis = ["nvptx","arc","riscv"] |
| |
|
| |
|
| | chatgpt_gcc_code = {} |
| | chatgpt_llvm_code = {} |
| | avg_accuracy = {} |
| |
|
| | with open(dst_dir+"/Input/chatgpt_gen_output_cleaned.csv", encoding="utf-8") as f: |
| | reader = csv.reader(f) |
| | for idx, row in enumerate(reader): |
| | if row[0] == "GCC": |
| | chatgpt_gcc_code[row[1] + " " + str(row[2])] = row[3] |
| | else: |
| | chatgpt_llvm_code[row[1] + " " + str(row[2])] = row[3] |
| |
|
| |
|
| | for comp_type in ["GCC", "LLVM"]: |
| | for isa_type in ["GPU", "MPU", "CPU"]: |
| | target_lis = target_clf[comp_type + " " + isa_type] |
| | test_target_dic = {} |
| | cnt_idx = 0 |
| | if comp_type == "GCC": |
| | if isa_type == "CPU": |
| | cnt_idx = 0 |
| | for line in open(src_dir + "/GCC/riscv.jsonl", 'r'): |
| | dic = json.loads(line) |
| | test_target_dic["riscv" + " " + str(cnt_idx)] = dic["ground_truth"] |
| | cnt_idx += 1 |
| | total_EM = 0.0 |
| | total_ED = 0.0 |
| | total_PoVS = 0.0 |
| | total_BLEU4 = 0.0 |
| | for k in test_target_dic.keys(): |
| | edit_dis = 0.0 |
| | EM = 0.0 |
| | bleu4 = 0.0 |
| | stmt_mod = 0.0 |
| | src_code = " ".join(test_target_dic[k]).replace("riscv", "") |
| | if k in chatgpt_gcc_code.keys(): |
| | chat_code = " ".join(chatgpt_gcc_code[k]).replace("riscv", "").replace("RISCV", "") |
| | stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], chatgpt_gcc_code[k], "riscv", "riscv") |
| | with open(dst_dir+"/test.output",'w') as f, open(dst_dir+"/test.gold",'w') as f1: |
| | f.write(chat_code+'\n') |
| | f1.write(src_code+'\n') |
| | if chat_code==src_code: |
| | EM = 1 |
| | edit_dis = fuzz.ratio(chat_code, src_code) |
| | if chat_code.strip() == "": |
| | bleu4 = 0 |
| | else: |
| | bleu4 = _bleu(dst_dir+"/test.gold", dst_dir+"/test.output") |
| | total_BLEU4 += bleu4 |
| | total_ED += edit_dis |
| | total_PoVS += stmt_mod |
| | total_EM += EM |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "riscv", k.split(" ")[1], str(round(float(bleu4),2)), str(round(EM*100,2)), str(round(float(edit_dis),2)), str(round(float(stmt_mod)*100,2))]) |
| | else: |
| | print(k) |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "riscv", "average", str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))]) |
| | avg_accuracy[comp_type + " " + "riscv"] = [str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))] |
| |
|
| | if isa_type == "GPU": |
| | cnt_idx = 0 |
| | for line in open(src_dir + "/GCC/nvptx.jsonl", 'r'): |
| | dic = json.loads(line) |
| | test_target_dic["nvptx" + " " + str(cnt_idx)] = dic["ground_truth"] |
| | cnt_idx += 1 |
| | total_EM = 0.0 |
| | total_ED = 0.0 |
| | total_PoVS = 0.0 |
| | total_BLEU4 = 0.0 |
| | for k in test_target_dic.keys(): |
| | edit_dis = 0.0 |
| | EM = 0.0 |
| | bleu4 = 0.0 |
| | stmt_mod = 0.0 |
| | src_code = " ".join(test_target_dic[k]).replace("nvptx", "") |
| | if k in chatgpt_gcc_code.keys(): |
| | chat_code = " ".join(chatgpt_gcc_code[k]).replace("nvptx", "").replace("NVPTX", "") |
| | stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], chatgpt_gcc_code[k], "nvptx", "nvptx") |
| | with open(dst_dir+"/test.output",'w') as f, open(dst_dir+"/test.gold",'w') as f1: |
| | f.write(chat_code+'\n') |
| | f1.write(src_code+'\n') |
| | if chat_code==src_code: |
| | EM = 1 |
| | edit_dis = fuzz.ratio(chat_code, src_code) |
| | if chat_code.strip() == "": |
| | bleu4 = 0 |
| | else: |
| | bleu4 = _bleu(dst_dir+"/test.gold", dst_dir+"/test.output") |
| | total_BLEU4 += bleu4 |
| | total_ED += edit_dis |
| | total_PoVS += stmt_mod |
| | total_EM += EM |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "nvptx", k.split(" ")[1], str(round(float(bleu4),2)), str(round(EM*100,2)), str(round(float(edit_dis),2)), str(round(float(stmt_mod)*100,2))]) |
| | else: |
| | print(k) |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "nvptx", "average", str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))]) |
| | avg_accuracy[comp_type + " " + "nvptx"] = [str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))] |
| | |
| | if isa_type == "MPU": |
| | cnt_idx = 0 |
| | for line in open(src_dir + "/GCC/arc.jsonl", 'r'): |
| | dic = json.loads(line) |
| | test_target_dic["arc" + " " + str(cnt_idx)] = dic["ground_truth"] |
| | cnt_idx += 1 |
| | total_EM = 0.0 |
| | total_ED = 0.0 |
| | total_PoVS = 0.0 |
| | total_BLEU4 = 0.0 |
| | for k in test_target_dic.keys(): |
| | edit_dis = 0.0 |
| | EM = 0.0 |
| | bleu4 = 0.0 |
| | stmt_mod = 0.0 |
| | src_code = " ".join(test_target_dic[k]).replace("arc", "") |
| | if k in chatgpt_gcc_code.keys(): |
| | chat_code = " ".join(chatgpt_gcc_code[k]).replace("arc", "").replace("ARC", "") |
| | stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], chatgpt_gcc_code[k], "arc", "arc") |
| | with open(dst_dir+"/test.output",'w') as f, open(dst_dir+"/test.gold",'w') as f1: |
| | f.write(chat_code+'\n') |
| | f1.write(src_code+'\n') |
| | if chat_code==src_code: |
| | EM = 1 |
| | edit_dis = fuzz.ratio(chat_code, src_code) |
| | if chat_code.strip() == "": |
| | bleu4 = 0 |
| | else: |
| | bleu4 = _bleu(dst_dir+"/test.gold", dst_dir+"/test.output") |
| | total_BLEU4 += bleu4 |
| | total_ED += edit_dis |
| | total_PoVS += stmt_mod |
| | total_EM += EM |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "arc", k.split(" ")[1], str(round(float(bleu4),2)), str(round(EM*100,2)), str(round(float(edit_dis),2)), str(round(float(stmt_mod)*100,2))]) |
| | else: |
| | print(k) |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "arc", "average", str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))]) |
| | avg_accuracy[comp_type + " " + "arc"] = [str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))] |
| |
|
| | if comp_type == "LLVM": |
| | if isa_type == "CPU": |
| | cnt_idx = 0 |
| | for line in open(src_dir + "/LLVM/RISCV.jsonl", 'r'): |
| | dic = json.loads(line) |
| | test_target_dic["RISCV" + " " + str(cnt_idx)] = dic["ground_truth"] |
| | cnt_idx += 1 |
| | total_EM = 0.0 |
| | total_ED = 0.0 |
| | total_PoVS = 0.0 |
| | total_BLEU4 = 0.0 |
| | for k in test_target_dic.keys(): |
| | edit_dis = 0.0 |
| | EM = 0.0 |
| | bleu4 = 0.0 |
| | stmt_mod = 0.0 |
| | src_code = " ".join(test_target_dic[k]).replace("RISCV", "") |
| | if k in chatgpt_llvm_code.keys(): |
| | chat_code = " ".join(chatgpt_llvm_code[k]).replace("riscv", "").replace("RISCV", "") |
| | stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], chatgpt_llvm_code[k], "riscv", "riscv") |
| | with open(dst_dir+"/test.output",'w') as f, open(dst_dir+"/test.gold",'w') as f1: |
| | f.write(chat_code+'\n') |
| | f1.write(src_code+'\n') |
| | if chat_code==src_code: |
| | EM = 1 |
| | edit_dis = fuzz.ratio(chat_code, src_code) |
| | if chat_code.strip() == "": |
| | bleu4 = 0 |
| | else: |
| | bleu4 = _bleu(dst_dir+"/test.gold", dst_dir+"/test.output") |
| | total_BLEU4 += bleu4 |
| | total_ED += edit_dis |
| | total_PoVS += stmt_mod |
| | total_EM += EM |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "RISCV", k.split(" ")[1], str(round(float(bleu4),2)), str(round(EM*100,2)), str(round(float(edit_dis),2)), str(round(float(stmt_mod)*100,2))]) |
| | else: |
| | print(k) |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "RISCV", "average", str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))]) |
| | avg_accuracy[comp_type + " " + "RISCV"] = [str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))] |
| | if isa_type == "GPU": |
| | cnt_idx = 0 |
| | for line in open(src_dir + "/LLVM/NVPTX.jsonl", 'r'): |
| | dic = json.loads(line) |
| | test_target_dic["NVPTX" + " " + str(cnt_idx)] = dic["ground_truth"] |
| | cnt_idx += 1 |
| | |
| | total_EM = 0.0 |
| | total_ED = 0.0 |
| | total_PoVS = 0.0 |
| | total_BLEU4 = 0.0 |
| | for k in test_target_dic.keys(): |
| | edit_dis = 0.0 |
| | EM = 0.0 |
| | bleu4 = 0.0 |
| | stmt_mod = 0.0 |
| | src_code = " ".join(test_target_dic[k]).replace("NVPTX", "") |
| | if k in chatgpt_llvm_code.keys(): |
| | chat_code = " ".join(chatgpt_llvm_code[k]).replace("nvptx", "").replace("NVPTX", "") |
| | stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], chatgpt_llvm_code[k], "nvptx", "nvptx") |
| | with open(dst_dir+"/test.output",'w') as f, open(dst_dir+"/test.gold",'w') as f1: |
| | f.write(chat_code+'\n') |
| | f1.write(src_code+'\n') |
| | if chat_code==src_code: |
| | EM = 1 |
| | edit_dis = fuzz.ratio(chat_code, src_code) |
| | if chat_code.strip() == "": |
| | bleu4 = 0 |
| | else: |
| | bleu4 = _bleu(dst_dir+"/test.gold", dst_dir+"/test.output") |
| | total_BLEU4 += bleu4 |
| | total_ED += edit_dis |
| | total_PoVS += stmt_mod |
| | total_EM += EM |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "NVPTX", k.split(" ")[1], str(round(float(bleu4),2)), str(round(EM*100,2)), str(round(float(edit_dis),2)), str(round(float(stmt_mod)*100,2))]) |
| | else: |
| | print(k) |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "NVPTX", "average", str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))]) |
| | avg_accuracy[comp_type + " " + "NVPTX"] = [str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))] |
| | |
| | if isa_type == "MPU": |
| | cnt_idx = 0 |
| | for line in open(src_dir + "/LLVM/ARC.jsonl", 'r'): |
| | dic = json.loads(line) |
| | test_target_dic["ARC" + " " + str(cnt_idx)] = dic["ground_truth"] |
| | cnt_idx += 1 |
| | total_EM = 0.0 |
| | total_ED = 0.0 |
| | total_PoVS = 0.0 |
| | total_BLEU4 = 0.0 |
| | for k in test_target_dic.keys(): |
| | edit_dis = 0.0 |
| | EM = 0.0 |
| | bleu4 = 0.0 |
| | stmt_mod = 0.0 |
| | src_code = " ".join(test_target_dic[k]).replace("ARC", "") |
| | if k in chatgpt_llvm_code.keys(): |
| | chat_code = " ".join(chatgpt_llvm_code[k]).replace("arc", "").replace("ARC", "") |
| | stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], chatgpt_llvm_code[k], "arc", "arc") |
| | with open(dst_dir+"/test.output",'w') as f, open(dst_dir+"/test.gold",'w') as f1: |
| | f.write(chat_code+'\n') |
| | f1.write(src_code+'\n') |
| | if chat_code==src_code: |
| | EM = 1 |
| | edit_dis = fuzz.ratio(chat_code, src_code) |
| | if chat_code.strip() == "": |
| | bleu4 = 0 |
| | else: |
| | bleu4 = _bleu(dst_dir+"/test.gold", dst_dir+"/test.output") |
| | total_BLEU4 += bleu4 |
| | total_ED += edit_dis |
| | total_PoVS += stmt_mod |
| | total_EM += EM |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "ARC", k.split(" ")[1], str(round(float(bleu4),2)), str(round(EM*100,2)), str(round(float(edit_dis),2)), str(round(float(stmt_mod)*100,2))]) |
| | else: |
| | print(k) |
| | with open(dst_dir + '/result.csv', 'a', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow([comp_type, "ARC", "average", str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))]) |
| | avg_accuracy[comp_type + " " + "ARC"] = [str(round(float(total_BLEU4 / cnt_idx),2)), str(round((total_EM / cnt_idx)*100,2)), str(round(float(total_ED / cnt_idx),2)), str(round(float(total_PoVS / cnt_idx)*100,2))] |
| |
|
| | return avg_accuracy |
| |
|
| |
|
| |
|
| |
|
| | if __name__ == "__main__": |
| | with open(dst_dir + '/result.csv', 'w', newline='') as file: |
| | writer = csv.writer(file) |
| | writer.writerow(["Compiler Type", "Target", "Idx", "BLEU4", "Exact Match", "Edit Didtance", "Stmt_Ratio"]) |
| |
|
| | avg_dic = Calculate_ChatGPT() |
| |
|
| | for k in avg_dic: |
| | print("########################") |
| | |
| | print(k) |
| | print(" ".join(["BLEU4", "Exact Match", "Edit Didtance", "Stmt_Ratio"])) |
| | print(" ".join(avg_dic[k])) |
| |
|
| |
|
