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https://github.com/hiyouga/LLaMA-Factory.git
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34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
from typing import TYPE_CHECKING, Tuple
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import torch
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from ...extras.logging import get_logger
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if TYPE_CHECKING:
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from transformers import PretrainedConfig, PreTrainedModel
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from ...hparams import ModelArguments
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logger = get_logger(__name__)
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def configure_hidden_size(config: "PretrainedConfig") -> None:
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if getattr(config, "model_type", None) == "llava":
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setattr(config, "hidden_size", getattr(config.text_config, "hidden_size", None))
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def autocast_projector_dtype(
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model: "PreTrainedModel", model_args: "ModelArguments", mm_projector_name: str = "multi_modal_projector"
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) -> None:
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def _mm_projector_forward_post_hook(
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module: "torch.nn.Module", args: Tuple["torch.Tensor"], output: "torch.Tensor"
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) -> "torch.Tensor":
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return output.to(model_args.compute_dtype)
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if hasattr(model, mm_projector_name) and getattr(model.config, "quantization_method", None):
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logger.info("Casting multimodal projector outputs in {}.".format(model_args.compute_dtype))
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mm_projector: "torch.nn.Module" = getattr(model, mm_projector_name)
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mm_projector.register_forward_hook(_mm_projector_forward_post_hook)
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