Refactor: Move sd2_clip.py to text_encoders folder.
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@ -17,8 +17,8 @@ from . import diffusers_convert
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from . import model_detection
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from . import model_detection
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from . import sd1_clip
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from . import sd1_clip
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from . import sd2_clip
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from . import sdxl_clip
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from . import sdxl_clip
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import comfy.text_encoders.sd2_clip
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import comfy.text_encoders.sd3_clip
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import comfy.text_encoders.sd3_clip
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import comfy.text_encoders.sa_t5
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import comfy.text_encoders.sa_t5
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import comfy.text_encoders.aura_t5
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import comfy.text_encoders.aura_t5
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@ -414,8 +414,8 @@ def load_clip(ckpt_paths, embedding_directory=None, clip_type=CLIPType.STABLE_DI
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clip_target.clip = sdxl_clip.SDXLRefinerClipModel
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clip_target.clip = sdxl_clip.SDXLRefinerClipModel
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clip_target.tokenizer = sdxl_clip.SDXLTokenizer
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clip_target.tokenizer = sdxl_clip.SDXLTokenizer
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elif "text_model.encoder.layers.22.mlp.fc1.weight" in clip_data[0]:
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elif "text_model.encoder.layers.22.mlp.fc1.weight" in clip_data[0]:
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clip_target.clip = sd2_clip.SD2ClipModel
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clip_target.clip = comfy.text_encoders.sd2_clip.SD2ClipModel
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clip_target.tokenizer = sd2_clip.SD2Tokenizer
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clip_target.tokenizer = comfy.text_encoders.sd2_clip.SD2Tokenizer
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elif "encoder.block.23.layer.1.DenseReluDense.wi_1.weight" in clip_data[0]:
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elif "encoder.block.23.layer.1.DenseReluDense.wi_1.weight" in clip_data[0]:
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weight = clip_data[0]["encoder.block.23.layer.1.DenseReluDense.wi_1.weight"]
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weight = clip_data[0]["encoder.block.23.layer.1.DenseReluDense.wi_1.weight"]
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dtype_t5 = weight.dtype
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dtype_t5 = weight.dtype
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@ -3,8 +3,8 @@ from . import model_base
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from . import utils
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from . import utils
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from . import sd1_clip
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from . import sd1_clip
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from . import sd2_clip
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from . import sdxl_clip
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from . import sdxl_clip
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import comfy.text_encoders.sd2_clip
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import comfy.text_encoders.sd3_clip
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import comfy.text_encoders.sd3_clip
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import comfy.text_encoders.sa_t5
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import comfy.text_encoders.sa_t5
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import comfy.text_encoders.aura_t5
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import comfy.text_encoders.aura_t5
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@ -101,7 +101,7 @@ class SD20(supported_models_base.BASE):
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return state_dict
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return state_dict
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def clip_target(self, state_dict={}):
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def clip_target(self, state_dict={}):
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return supported_models_base.ClipTarget(sd2_clip.SD2Tokenizer, sd2_clip.SD2ClipModel)
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return supported_models_base.ClipTarget(comfy.text_encoders.sd2_clip.SD2Tokenizer, comfy.text_encoders.sd2_clip.SD2ClipModel)
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class SD21UnclipL(SD20):
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class SD21UnclipL(SD20):
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unet_config = {
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unet_config = {
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