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support function calling

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Former-commit-id: 66533b3f65babf2429c92c0f8fafe4eff5e0ff63
This commit is contained in:
hiyouga
2024-01-18 09:54:23 +08:00
parent f7329b1a0e
commit a423274fd9
67 changed files with 1239 additions and 1079 deletions
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96
src/llmtuner/hparams/data_args.py
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@@ -1,40 +1,7 @@
import os
import json
from typing import List, Literal, Optional
from typing import Literal, Optional
from dataclasses import dataclass, field
DATA_CONFIG = "dataset_info.json"
def use_modelscope() -> bool:
return bool(int(os.environ.get("USE_MODELSCOPE_HUB", "0")))
@dataclass
class DatasetAttr:
load_from: Literal["hf_hub", "ms_hub", "script", "file"]
dataset_name: Optional[str] = None
dataset_sha1: Optional[str] = None
subset: Optional[str] = None
folder: Optional[str] = None
ranking: Optional[bool] = False
formatting: Optional[Literal["alpaca", "sharegpt"]] = "alpaca"
prompt: Optional[str] = "instruction"
query: Optional[str] = "input"
response: Optional[str] = "output"
history: Optional[str] = None
messages: Optional[str] = "conversations"
role: Optional[str] = "from"
content: Optional[str] = "value"
system: Optional[str] = None
def __repr__(self) -> str:
return self.dataset_name
@dataclass
class DataArguments:
r"""
@@ -126,64 +93,3 @@ class DataArguments:
if self.streaming and self.max_samples is not None:
raise ValueError("`max_samples` is incompatible with `streaming`.")
def init_for_training(self, seed: int): # support mixing multiple datasets
self.seed = seed
dataset_names = [ds.strip() for ds in self.dataset.split(",")] if self.dataset is not None else []
try:
with open(os.path.join(self.dataset_dir, DATA_CONFIG), "r") as f:
dataset_info = json.load(f)
except Exception as err:
if self.dataset is not None:
raise ValueError("Cannot open {} due to {}.".format(os.path.join(self.dataset_dir, DATA_CONFIG), str(err)))
dataset_info = None
if self.interleave_probs is not None:
self.interleave_probs = [float(prob.strip()) for prob in self.interleave_probs.split(",")]
self.dataset_list: List[DatasetAttr] = []
for name in dataset_names:
if name not in dataset_info:
raise ValueError("Undefined dataset {} in {}.".format(name, DATA_CONFIG))
has_hf_url = "hf_hub_url" in dataset_info[name]
has_ms_url = "ms_hub_url" in dataset_info[name]
if has_hf_url or has_ms_url:
if (use_modelscope() and has_ms_url) or (not has_hf_url):
dataset_attr = DatasetAttr(
"ms_hub",
dataset_name=dataset_info[name]["ms_hub_url"]
)
else:
dataset_attr = DatasetAttr(
"hf_hub",
dataset_name=dataset_info[name]["hf_hub_url"]
)
elif "script_url" in dataset_info[name]:
dataset_attr = DatasetAttr(
"script",
dataset_name=dataset_info[name]["script_url"]
)
else:
dataset_attr = DatasetAttr(
"file",
dataset_name=dataset_info[name]["file_name"],
dataset_sha1=dataset_info[name].get("file_sha1", None)
)
if "columns" in dataset_info[name]:
dataset_attr.prompt = dataset_info[name]["columns"].get("prompt", None)
dataset_attr.query = dataset_info[name]["columns"].get("query", None)
dataset_attr.response = dataset_info[name]["columns"].get("response", None)
dataset_attr.history = dataset_info[name]["columns"].get("history", None)
dataset_attr.messages = dataset_info[name]["columns"].get("messages", None)
dataset_attr.role = dataset_info[name]["columns"].get("role", None)
dataset_attr.content = dataset_info[name]["columns"].get("content", None)
dataset_attr.system = dataset_info[name]["columns"].get("system", None)
dataset_attr.subset = dataset_info[name].get("subset", None)
dataset_attr.folder = dataset_info[name].get("folder", None)
dataset_attr.ranking = dataset_info[name].get("ranking", False)
dataset_attr.formatting = dataset_info[name].get("formatting", "alpaca")
self.dataset_list.append(dataset_attr)