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33 lines
775 B
Python
33 lines
775 B
Python
import torch
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from transformers import T5EncoderModel, T5Config
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from .sd_text_encoder import SDTextEncoder
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class FluxTextEncoder2(T5EncoderModel):
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def __init__(self, config):
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super().__init__(config)
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self.eval()
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def forward(self, input_ids):
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outputs = super().forward(input_ids=input_ids)
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prompt_emb = outputs.last_hidden_state
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return prompt_emb
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@staticmethod
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def state_dict_converter():
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return FluxTextEncoder2StateDictConverter()
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class FluxTextEncoder2StateDictConverter():
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def __init__(self):
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pass
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def from_diffusers(self, state_dict):
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state_dict_ = state_dict
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return state_dict_
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def from_civitai(self, state_dict):
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return self.from_diffusers(state_dict)
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