|
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])) |
|
|
|
|
