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Add pad token #35

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Merged
merged 1 commit into from
Aug 29, 2024
Merged

Add pad token #35

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27 changes: 23 additions & 4 deletions hf_mini/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1091,11 +1091,16 @@

import re
import time
import torch
from typing import Union, Dict
from transformers import AutoTokenizer

from hf_mini.filter import SensitiveInforRM
is_security = SensitiveInforRM()

def input_wrapper(code_string, later_code: str = "", path: str = "") -> str:

is_security = SensitiveInforRM()

def input_wrapper(tokenizer: AutoTokenizer, code_string: str, later_code: str = "", path: str = "", pad_token: str = "☺" ) -> Union[Dict,None]:
start = time.time()
_sequerity = True
for i in [code_string, later_code, path]:
Expand All @@ -1104,7 +1109,7 @@ def input_wrapper(code_string, later_code: str = "", path: str = "") -> str:
break
print(f"Done inputs checking with {(time.time()-start) * 1000:.2f}ms", flush=True)
if not _sequerity:
return ""
return None

extension_pattern = re.compile(r"(\.\w+)$")
p = ""
Expand All @@ -1119,4 +1124,18 @@ def input_wrapper(code_string, later_code: str = "", path: str = "") -> str:
des = LANGUAGE_WRAPPER.get(lang, "")
if len(des) > 0 and "<AIX-SPE>" in des:
p = des.replace("<AIX-SPE>", f"the file path is: {path}") + "\n"
return f"<s>▁<AIX-SPAN-PRE>▁<AIX-SPAN-POST>{later_code}▁<AIX-SPAN-MIDDLE>{p}{code_string}"

# SPM
pad_ids = tokenizer(pad_token, return_tensors="pt", return_token_type_ids=False)
pad_len = len(pad_ids["input_ids"][0])
pre_code_ids = tokenizer("<s>▁<AIX-SPAN-PRE>▁<AIX-SPAN-POST>", return_tensors="pt", return_token_type_ids=False)

later_code_ids = tokenizer(pad_token + later_code, return_tensors="pt", return_token_type_ids=False)
later_code_ids["input_ids"] = later_code_ids["input_ids"][:,pad_len:]
later_code_ids["attention_mask"] = later_code_ids["attention_mask"][:,pad_len:]

code_string_ids = tokenizer(f"▁<AIX-SPAN-MIDDLE>{p}{code_string}", return_tensors="pt", return_token_type_ids=False)
code_string_ids["input_ids"] = torch.cat([pre_code_ids["input_ids"], later_code_ids["input_ids"], code_string_ids["input_ids"]], dim = 1)
code_string_ids["attention_mask"] = torch.cat([pre_code_ids["attention_mask"], later_code_ids["attention_mask"], code_string_ids["attention_mask"]], dim = 1)

return code_string_ids
11 changes: 5 additions & 6 deletions sess_huggingface.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,19 +9,18 @@
model = AutoModelForCausalLM.from_pretrained("aiXcoder/aixcoder-7b-base", torch_dtype=torch.bfloat16)


text = input_wrapper(
inputs = input_wrapper(
tokenizer=tokenizer,
code_string="# 快速排序算法",
later_code="\n",
path="test.py"
path="test.py",
)

if len(text) == 0:
if inputs is None:
sys.exit()

inputs = tokenizer(text, return_tensors="pt", return_token_type_ids=False)

inputs = inputs.to(device)
model.to(device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=False))
print(tokenizer.decode(outputs[0], skip_special_tokens=False))