| 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_Gen(): |
| get_target_clf_list() |
| print("############## Exp 2: Calculate Code-LLaMA Gen ################\n") |
| |
| test_lis = ["nvptx","arc","riscv"] |
|
|
| avg_accuracy = {} |
| codellama_gcc_code = {} |
| codellama_llvm_code = {} |
| dst_file = dst_dir+"/Input/codellama_gen_output_cleaned.csv" |
| with open(dst_file,encoding="utf-8") as f: |
| reader = csv.reader(f) |
| for idx, row in enumerate(reader): |
| if row[0] == "GCC": |
| codellama_gcc_code[row[1] + " " + str(row[2])] = row[3] |
| else: |
| codellama_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 codellama_gcc_code.keys(): |
| chat_code = " ".join(codellama_gcc_code[k]).replace("riscv", "").replace("RISCV", "") |
| stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], codellama_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 codellama_gcc_code.keys(): |
| chat_code = " ".join(codellama_gcc_code[k]).replace("nvptx", "").replace("NVPTX", "") |
| stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], codellama_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 codellama_gcc_code.keys(): |
| chat_code = " ".join(codellama_gcc_code[k]).replace("arc", "").replace("ARC", "") |
| stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], codellama_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 codellama_llvm_code.keys(): |
| chat_code = " ".join(codellama_llvm_code[k]).replace("riscv", "").replace("RISCV", "") |
| stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], codellama_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 codellama_llvm_code.keys(): |
| chat_code = " ".join(codellama_llvm_code[k]).replace("nvptx", "").replace("NVPTX", "") |
| stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], codellama_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 codellama_llvm_code.keys(): |
| chat_code = " ".join(codellama_llvm_code[k]).replace("arc", "").replace("ARC", "") |
| stmt_mod = Calculate_Statements_Ratio(test_target_dic[k], codellama_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_Gen() |
|
|
| for k in avg_dic: |
| print("########################") |
| |
| print(k) |
| print(" ".join(["BLEU4", "Exact Match", "Edit Didtance", "Stmt_Ratio"])) |
| print(" ".join(avg_dic[k])) |
|
|
|
|
