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modify style

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BUAADreamer
2024-04-25 21:15:16 +08:00
parent 43d7ad5ecc
commit 1dcabafe72
16 changed files with 374 additions and 502 deletions
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49
src/llmtuner/data/aligner.py
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@@ -13,9 +13,7 @@ if TYPE_CHECKING:
from .parser import DatasetAttr
def convert_alpaca(
examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr"
) -> Dict[str, List[Any]]:
def convert_alpaca(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr") -> Dict[str, List[Any]]:
outputs = {"prompt": [], "response": [], "system": [], "tools": []}
for i in range(len(examples[dataset_attr.prompt])):
prompt = []
@@ -33,16 +31,11 @@ def convert_alpaca(
prompt.append({"role": Role.USER.value, "content": "\n".join(content)})
if dataset_attr.response and isinstance(
examples[dataset_attr.response][i], list
):
if dataset_attr.response and isinstance(examples[dataset_attr.response][i], list):
response = [
{"role": Role.ASSISTANT.value, "content": content}
for content in examples[dataset_attr.response][i]
{"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
):
elif dataset_attr.response and isinstance(examples[dataset_attr.response][i], str):
response = [
{
"role": Role.ASSISTANT.value,
@@ -54,17 +47,13 @@ def convert_alpaca(
outputs["prompt"].append(prompt)
outputs["response"].append(response)
outputs["system"].append(
examples[dataset_attr.system][i] if dataset_attr.system else ""
)
outputs["system"].append(examples[dataset_attr.system][i] if dataset_attr.system else "")
outputs["tools"].append("")
outputs["images"].append([])
return outputs
def convert_sharegpt(
examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr"
) -> Dict[str, List[Any]]:
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,
@@ -77,10 +66,7 @@ def convert_sharegpt(
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
):
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:
@@ -105,17 +91,13 @@ def convert_sharegpt(
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["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]]:
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,
@@ -128,10 +110,7 @@ def convert_llava(
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
):
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:
@@ -156,13 +135,9 @@ def convert_llava(
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["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 []
)
outputs["images"].append(examples[dataset_attr.images][i] if dataset_attr.images else [])
return outputs