Merge branch 'master' into tensorboard

1 files changed, 0 insertions, 99 deletions

diff --git a/modules/api/processing.py b/modules/api/processing.py
deleted file mode 100644
index 4c541241..00000000
--- a/modules/api/processing.py
+++ /dev/null
@@ -1,99 +0,0 @@
-from inflection import underscore
-from typing import Any, Dict, Optional
-from pydantic import BaseModel, Field, create_model
-from modules.processing import StableDiffusionProcessingTxt2Img
-import inspect
-
-
-API_NOT_ALLOWED = [
-    "self",
-    "kwargs",
-    "sd_model",
-    "outpath_samples",
-    "outpath_grids",
-    "sampler_index",
-    "do_not_save_samples",
-    "do_not_save_grid",
-    "extra_generation_params",
-    "overlay_images",
-    "do_not_reload_embeddings",
-    "seed_enable_extras",
-    "prompt_for_display",
-    "sampler_noise_scheduler_override",
-    "ddim_discretize"
-]
-
-class ModelDef(BaseModel):
-    """Assistance Class for Pydantic Dynamic Model Generation"""
-
-    field: str
-    field_alias: str
-    field_type: Any
-    field_value: Any
-
-
-class PydanticModelGenerator:
-    """
-    Takes in created classes and stubs them out in a way FastAPI/Pydantic is happy about:
-    source_data is a snapshot of the default values produced by the class
-    params are the names of the actual keys required by __init__
-    """
-
-    def __init__(
-        self,
-        model_name: str = None,
-        class_instance = None,
-        additional_fields = None,
-    ):
-        def field_type_generator(k, v):
-            # field_type = str if not overrides.get(k) else overrides[k]["type"]
-            # print(k, v.annotation, v.default)
-            field_type = v.annotation
-            
-            return Optional[field_type]
-        
-        def merge_class_params(class_):
-            all_classes = list(filter(lambda x: x is not object, inspect.getmro(class_)))
-            parameters = {}
-            for classes in all_classes:
-                parameters = {**parameters, **inspect.signature(classes.__init__).parameters}
-            return parameters
-            
-                
-        self._model_name = model_name
-        self._class_data = merge_class_params(class_instance)
-        self._model_def = [
-            ModelDef(
-                field=underscore(k),
-                field_alias=k,
-                field_type=field_type_generator(k, v),
-                field_value=v.default
-            )
-            for (k,v) in self._class_data.items() if k not in API_NOT_ALLOWED
-        ]
-        
-        for fields in additional_fields:
-            self._model_def.append(ModelDef(
-                field=underscore(fields["key"]), 
-                field_alias=fields["key"], 
-                field_type=fields["type"],
-                field_value=fields["default"]))
-
-    def generate_model(self):
-        """
-        Creates a pydantic BaseModel
-        from the json and overrides provided at initialization
-        """
-        fields = {
-            d.field: (d.field_type, Field(default=d.field_value, alias=d.field_alias)) for d in self._model_def
-        }
-        DynamicModel = create_model(self._model_name, **fields)
-        DynamicModel.__config__.allow_population_by_field_name = True
-        DynamicModel.__config__.allow_mutation = True
-        return DynamicModel
-    
-StableDiffusionProcessingAPI = PydanticModelGenerator(
-    "StableDiffusionProcessingTxt2Img", 
-    StableDiffusionProcessingTxt2Img,
-    [{"key": "sampler_index", "type": str, "default": "Euler"}]
-).generate_model()
\ No newline at end of file