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from typing import List |
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import torch |
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from methods.base.model import BaseModel |
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import tqdm |
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from torch import nn |
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import torch.nn.functional as F |
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from abc import abstractmethod |
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from methods.elasticdnn.model.base import ElasticDNNUtil |
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from methods.elasticdnn.pipeline.offline.fm_to_md.base import FM_to_MD_Util |
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from methods.elasticdnn.pipeline.offline.fm_lora.base import FMLoRA_Util |
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from utils.dl.common.model import LayerActivation |
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class HuggingFaceModelAPI: |
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@abstractmethod |
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def get_feature_hook(self, fm: nn.Module) -> LayerActivation: |
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pass |
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@abstractmethod |
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def get_task_head_params(self, fm: nn.Module): |
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pass |
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@abstractmethod |
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def get_qkv_proj_ff1_ff2_layer_names(self): |
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pass |
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@abstractmethod |
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def get_accuracy(self, fm: nn.Module, test_loader, device, *args, **kwargs): |
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pass |
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@abstractmethod |
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def infer(self, fm: nn.Module, x, *args, **kwargs): |
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pass |
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@abstractmethod |
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def forward_to_get_task_loss(self, fm: nn.Module, x, y, *args, **kwargs): |
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pass |
