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merge some func

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BUAADreamer
2024-04-25 22:35:17 +08:00
parent c27f7fbf62
commit 31420f7b31
3 changed files with 10 additions and 205 deletions
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51
src/llmtuner/data/aligner.py
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@@ -36,12 +36,7 @@ def convert_alpaca(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr")
{"role": Role.ASSISTANT.value, "content": content} for content in examples[dataset_attr.response][i]
]
elif dataset_attr.response and isinstance(examples[dataset_attr.response][i], str):
response = [
{
"role": Role.ASSISTANT.value,
"content": examples[dataset_attr.response][i],
}
]
response = [{"role": Role.ASSISTANT.value, "content": examples[dataset_attr.response][i]}]
else:
response = []
@@ -54,47 +49,6 @@ def convert_alpaca(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr")
def convert_sharegpt(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr") -> Dict[str, List[Any]]:
outputs = {"prompt": [], "response": [], "system": [], "tools": []}
tag_mapping = {
dataset_attr.user_tag: Role.USER.value,
dataset_attr.assistant_tag: Role.ASSISTANT.value,
dataset_attr.observation_tag: Role.OBSERVATION.value,
dataset_attr.function_tag: Role.FUNCTION.value,
dataset_attr.system_tag: Role.SYSTEM.value,
}
odd_tags = (dataset_attr.user_tag, dataset_attr.observation_tag)
even_tags = (dataset_attr.assistant_tag, dataset_attr.function_tag)
accept_tags = (odd_tags, even_tags)
for i, messages in enumerate(examples[dataset_attr.messages]):
if dataset_attr.system_tag and messages[0][dataset_attr.role_tag] == dataset_attr.system_tag:
system = messages[0][dataset_attr.content_tag]
messages = messages[1:]
else:
system = examples[dataset_attr.system][i] if dataset_attr.system else ""
messages = messages[: len(messages) // 2 * 2] # should be multiples of 2
if len(messages) == 0:
continue
aligned_messages = []
for turn_idx, message in enumerate(messages):
if message[dataset_attr.role_tag] not in accept_tags[turn_idx % 2]:
raise ValueError("Invalid role tag in {}.".format(messages))
aligned_messages.append(
{"role": tag_mapping[message[dataset_attr.role_tag]], "content": message[dataset_attr.content_tag]}
)
outputs["prompt"].append(aligned_messages[:-1])
outputs["response"].append(aligned_messages[-1:])
outputs["system"].append(system)
outputs["tools"].append(examples[dataset_attr.tools][i] if dataset_attr.tools else "")
outputs["images"].append([])
return outputs
def convert_llava(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr") -> Dict[str, List[Any]]:
outputs = {"prompt": [], "response": [], "system": [], "tools": [], "images": []}
tag_mapping = {
dataset_attr.user_tag: Role.USER.value,
@@ -130,7 +84,6 @@ def convert_llava(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr") -
outputs["response"].append(aligned_messages[-1:])
outputs["system"].append(system)
outputs["tools"].append(examples[dataset_attr.tools][i] if dataset_attr.tools else "")
print(examples[dataset_attr.images][i])
outputs["images"].append(examples[dataset_attr.images][i] if dataset_attr.images else [])
return outputs
@@ -148,8 +101,6 @@ def align_dataset(
"""
if dataset_attr.formatting == "alpaca":
convert_func = partial(convert_alpaca, dataset_attr=dataset_attr)
elif dataset_attr.formatting == "llava":
convert_func = partial(convert_llava, dataset_attr=dataset_attr)
else:
convert_func = partial(convert_sharegpt, dataset_attr=dataset_attr)