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fix mixed mm inputs and rlhf-v

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Former-commit-id: 7c248fac20bf85d57a91132ce7a793c7f84e9218
This commit is contained in:
hiyouga
2024-09-01 20:52:47 +08:00
parent 1d8e9c7897
commit 7e4c5d4bb3
20 changed files with 306 additions and 277 deletions
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38
src/llamafactory/data/processors/pairwise.py
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@@ -21,6 +21,7 @@ from .processor_utils import infer_seqlen
if TYPE_CHECKING:
from PIL.Image import Image
from transformers import PreTrainedTokenizer, ProcessorMixin
from ...hparams import DataArguments
@@ -35,13 +36,14 @@ def _encode_pairwise_example(
response: Sequence[Dict[str, str]],
system: Optional[str],
tools: Optional[str],
images: Sequence["Image"],
template: "Template",
tokenizer: "PreTrainedTokenizer",
processor: Optional["ProcessorMixin"],
cutoff_len: int,
) -> Tuple[List[int], List[int], List[int], List[int]]:
chosen_messages = prompt + [response[0]]
rejected_messages = prompt + [response[1]]
) -> Tuple[List[int], List[int], List[int], List[int], Dict[str, Any]]:
chosen_messages = template.mm_plugin.process_messages(prompt + [response[0]], images, processor)
rejected_messages = template.mm_plugin.process_messages(prompt + [response[1]], images, processor)
prompt_ids, chosen_ids = template.encode_oneturn(tokenizer, chosen_messages, system, tools)
_, rejected_ids = template.encode_oneturn(tokenizer, rejected_messages, system, tools)
@@ -49,7 +51,7 @@ def _encode_pairwise_example(
chosen_ids += [tokenizer.eos_token_id]
rejected_ids += [tokenizer.eos_token_id]
prompt_ids, _ = template.mm_plugin.process_token_ids(prompt_ids, None, tokenizer, processor)
prompt_ids, _ = template.mm_plugin.process_token_ids(prompt_ids, None, images, tokenizer, processor)
# consider the response is more important
source_len, target_len = infer_seqlen(len(prompt_ids), max(len(chosen_ids), len(rejected_ids)), cutoff_len)
prompt_ids = prompt_ids[:source_len]
@@ -60,8 +62,15 @@ def _encode_pairwise_example(
chosen_labels = [IGNORE_INDEX] * source_len + chosen_ids
rejected_input_ids = prompt_ids + rejected_ids
rejected_labels = [IGNORE_INDEX] * source_len + rejected_ids
return chosen_input_ids, chosen_labels, rejected_input_ids, rejected_labels
extra_inputs = template.mm_plugin.get_mm_inputs(
images=images,
feature_seqlens={
"chosen_token_type_ids": len(chosen_input_ids),
"rejected_token_type_ids": len(rejected_input_ids),
},
processor=processor,
)
return chosen_input_ids, chosen_labels, rejected_input_ids, rejected_labels, extra_inputs
def preprocess_pairwise_dataset(
@@ -78,12 +87,12 @@ def preprocess_pairwise_dataset(
logger.warning("Dropped invalid example: {}".format(examples["prompt"][i] + examples["response"][i]))
continue
prompt = template.mm_plugin.process_messages(examples["prompt"][i], examples["images"][i], processor)
chosen_input_ids, chosen_labels, rejected_input_ids, rejected_labels = _encode_pairwise_example(
prompt=prompt,
chosen_input_ids, chosen_labels, rejected_input_ids, rejected_labels, extra_inputs = _encode_pairwise_example(
prompt=examples["prompt"][i],
response=examples["response"][i],
system=examples["system"][i],
tools=examples["tools"][i],
images=examples["images"][i],
template=template,
tokenizer=tokenizer,
processor=processor,
@@ -95,15 +104,8 @@ def preprocess_pairwise_dataset(
model_inputs["rejected_input_ids"].append(rejected_input_ids)
model_inputs["rejected_attention_mask"].append([1] * len(rejected_input_ids))
model_inputs["rejected_labels"].append(rejected_labels)
template.mm_plugin.process_model_inputs(
model_inputs=model_inputs,
images=examples["images"][i],
feature_seqlens={
"chosen_token_type_ids": len(chosen_input_ids),
"rejected_token_type_ids": len(rejected_input_ids),
},
processor=processor,
)
for key, value in extra_inputs.items():
model_inputs[key].append(value)
return model_inputs