backend..conditioning: remove code for legacy model

invokeai/backend/prompting/__init__.py

@@ -3,7 +3,6 @@ Initialization file for invokeai.backend.prompting
 """
 from .conditioning import (
     get_prompt_structure,
-    get_tokenizer,
     get_tokens_for_prompt_object,
     get_uc_and_c_and_ec,
     split_weighted_subprompts,

invokeai/backend/prompting/conditioning.py

@@ -7,7 +7,7 @@ get_uc_and_c_and_ec()           get the conditioned and unconditioned latent, an
 
 """
 import re
-from typing import Any, Optional, Union
+from typing import Optional, Union
 
 from compel import Compel
 from compel.prompt_parser import (
@@ -17,7 +17,6 @@ from compel.prompt_parser import (
     Fragment,
     PromptParser,
 )
-from transformers import CLIPTokenizer
 
 from invokeai.backend.globals import Globals
 
@@ -25,36 +24,6 @@ from ..stable_diffusion import InvokeAIDiffuserComponent
 from ..util import torch_dtype
 
 
-def get_tokenizer(model) -> CLIPTokenizer:
-    # TODO remove legacy ckpt fallback handling
-    return (
-        getattr(model, "tokenizer", None)  # diffusers
-        or model.cond_stage_model.tokenizer
-    )  # ldm
-
-
-def get_text_encoder(model) -> Any:
-    # TODO remove legacy ckpt fallback handling
-    return getattr(
-        model, "text_encoder", None
-    ) or UnsqueezingLDMTransformer(  # diffusers
-        model.cond_stage_model.transformer
-    )  # ldm
-
-
-class UnsqueezingLDMTransformer:
-    def __init__(self, ldm_transformer):
-        self.ldm_transformer = ldm_transformer
-
-    @property
-    def device(self):
-        return self.ldm_transformer.device
-
-    def __call__(self, *args, **kwargs):
-        insufficiently_unsqueezed_tensor = self.ldm_transformer(*args, **kwargs)
-        return insufficiently_unsqueezed_tensor.unsqueeze(0)
-
-
 def get_uc_and_c_and_ec(
     prompt_string, model, log_tokens=False, skip_normalize_legacy_blend=False
 ):
@@ -64,11 +33,10 @@ def get_uc_and_c_and_ec(
         prompt_string
     )
 
-    tokenizer = get_tokenizer(model)
+    tokenizer = model.tokenizer
-    text_encoder = get_text_encoder(model)
     compel = Compel(
         tokenizer=tokenizer,
-        text_encoder=text_encoder,
+        text_encoder=model.text_encoder,
         textual_inversion_manager=model.textual_inversion_manager,
         dtype_for_device_getter=torch_dtype,
         truncate_long_prompts=False

invokeai/backend/web/invoke_ai_web_server.py

@@ -29,7 +29,6 @@ from ..image_util import PngWriter, retrieve_metadata
 from ...frontend.merge.merge_diffusers import merge_diffusion_models
 from ..prompting import (
     get_prompt_structure,
-    get_tokenizer,
     get_tokens_for_prompt_object,
 )
 from ..stable_diffusion import PipelineIntermediateState
@@ -1274,7 +1273,7 @@ class InvokeAIWebServer:
                     None
                     if type(parsed_prompt) is Blend
                     else get_tokens_for_prompt_object(
-                        get_tokenizer(self.generate.model), parsed_prompt
+                        self.generate.model.tokenizer, parsed_prompt
                     )
                 )
                 attention_maps_image_base64_url = (