Refactor: Move some code to the comfy/text_encoders folder.

comfy/sd.py

@@ -19,8 +19,8 @@ from . import model_detection
 from . import sd1_clip
 from . import sd2_clip
 from . import sdxl_clip
-from . import sd3_clip
-from . import sa_t5
+import comfy.text_encoders.sd3_clip
+import comfy.text_encoders.sa_t5
 import comfy.text_encoders.aura_t5
 
 import comfy.model_patcher
@@ -414,27 +414,27 @@ def load_clip(ckpt_paths, embedding_directory=None, clip_type=CLIPType.STABLE_DI
             weight = clip_data[0]["encoder.block.23.layer.1.DenseReluDense.wi_1.weight"]
             dtype_t5 = weight.dtype
             if weight.shape[-1] == 4096:
-                clip_target.clip = sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, dtype_t5=dtype_t5)
-                clip_target.tokenizer = sd3_clip.SD3Tokenizer
+                clip_target.clip = comfy.text_encoders.sd3_clip.sd3_clip(clip_l=False, clip_g=False, t5=True, dtype_t5=dtype_t5)
+                clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer
             elif weight.shape[-1] == 2048:
                 clip_target.clip = comfy.text_encoders.aura_t5.AuraT5Model
                 clip_target.tokenizer = comfy.text_encoders.aura_t5.AuraT5Tokenizer
         elif "encoder.block.0.layer.0.SelfAttention.k.weight" in clip_data[0]:
-            clip_target.clip = sa_t5.SAT5Model
-            clip_target.tokenizer = sa_t5.SAT5Tokenizer
+            clip_target.clip = comfy.text_encoders.sa_t5.SAT5Model
+            clip_target.tokenizer = comfy.text_encoders.sa_t5.SAT5Tokenizer
         else:
             clip_target.clip = sd1_clip.SD1ClipModel
             clip_target.tokenizer = sd1_clip.SD1Tokenizer
     elif len(clip_data) == 2:
         if clip_type == CLIPType.SD3:
-            clip_target.clip = sd3_clip.sd3_clip(clip_l=True, clip_g=True, t5=False)
-            clip_target.tokenizer = sd3_clip.SD3Tokenizer
+            clip_target.clip = comfy.text_encoders.sd3_clip.sd3_clip(clip_l=True, clip_g=True, t5=False)
+            clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer
         else:
             clip_target.clip = sdxl_clip.SDXLClipModel
             clip_target.tokenizer = sdxl_clip.SDXLTokenizer
     elif len(clip_data) == 3:
-        clip_target.clip = sd3_clip.SD3ClipModel
-        clip_target.tokenizer = sd3_clip.SD3Tokenizer
+        clip_target.clip = comfy.text_encoders.sd3_clip.SD3ClipModel
+        clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer
 
     clip = CLIP(clip_target, embedding_directory=embedding_directory)
     for c in clip_data:

comfy/supported_models.py

@@ -5,8 +5,8 @@ from . import utils
 from . import sd1_clip
 from . import sd2_clip
 from . import sdxl_clip
-from . import sd3_clip
-from . import sa_t5
+import comfy.text_encoders.sd3_clip
+import comfy.text_encoders.sa_t5
 import comfy.text_encoders.aura_t5
 
 from . import supported_models_base
@@ -524,7 +524,7 @@ class SD3(supported_models_base.BASE):
             t5 = True
             dtype_t5 = state_dict[t5_key].dtype
 
-        return supported_models_base.ClipTarget(sd3_clip.SD3Tokenizer, sd3_clip.sd3_clip(clip_l=clip_l, clip_g=clip_g, t5=t5, dtype_t5=dtype_t5))
+        return supported_models_base.ClipTarget(comfy.text_encoders.sd3_clip.SD3Tokenizer, comfy.text_encoders.sd3_clip.sd3_clip(clip_l=clip_l, clip_g=clip_g, t5=t5, dtype_t5=dtype_t5))
 
 class StableAudio(supported_models_base.BASE):
     unet_config = {
@@ -555,7 +555,7 @@ class StableAudio(supported_models_base.BASE):
         return utils.state_dict_prefix_replace(state_dict, replace_prefix)
 
     def clip_target(self, state_dict={}):
-        return supported_models_base.ClipTarget(sa_t5.SAT5Tokenizer, sa_t5.SAT5Model)
+        return supported_models_base.ClipTarget(comfy.text_encoders.sa_t5.SAT5Tokenizer, comfy.text_encoders.sa_t5.SAT5Model)
 
 class AuraFlow(supported_models_base.BASE):
     unet_config = {

comfy/text_encoders/aura_t5.py

 from comfy import sd1_clip
 from .llama_tokenizer import LLAMATokenizer
-import comfy.t5
+import comfy.text_encoders.t5
 import os
 
 class PT5XlModel(sd1_clip.SDClipModel):
     def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None):
         textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_pile_config_xl.json")
-        super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 2, "pad": 1}, model_class=comfy.t5.T5, enable_attention_masks=True, zero_out_masked=True)
+        super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 2, "pad": 1}, model_class=comfy.text_encoders.t5.T5, enable_attention_masks=True, zero_out_masked=True)
 
 class PT5XlTokenizer(sd1_clip.SDTokenizer):
     def __init__(self, embedding_directory=None):

comfy/sa_t5.py → comfy/text_encoders/sa_t5.py

 from comfy import sd1_clip
 from transformers import T5TokenizerFast
-import comfy.t5
+import comfy.text_encoders.t5
 import os
 
 class T5BaseModel(sd1_clip.SDClipModel):
     def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None):
         textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_config_base.json")
-        super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.t5.T5, enable_attention_masks=True, zero_out_masked=True)
+        super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.text_encoders.t5.T5, enable_attention_masks=True, zero_out_masked=True)
 
 class T5BaseTokenizer(sd1_clip.SDTokenizer):
     def __init__(self, embedding_directory=None):

comfy/sd3_clip.py → comfy/text_encoders/sd3_clip.py

 from comfy import sd1_clip
 from comfy import sdxl_clip
 from transformers import T5TokenizerFast
-import comfy.t5
+import comfy.text_encoders.t5
 import torch
 import os
 import comfy.model_management
@@ -10,7 +10,7 @@ import logging
 class T5XXLModel(sd1_clip.SDClipModel):
     def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None):
         textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_config_xxl.json")
-        super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.t5.T5)
+        super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.text_encoders.t5.T5)
 
 class T5XXLTokenizer(sd1_clip.SDTokenizer):
     def __init__(self, embedding_directory=None):