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Merged
dxqb merged 1 commit into from
Nov 27, 2025
Merged

Code deduplication #1143

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49 changes: 7 additions & 42 deletions modules/modelLoader/ChromaEmbeddingModelLoader.py
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@@ -1,47 +1,12 @@
from modules.model.ChromaModel import ChromaModel
from modules.modelLoader.BaseModelLoader import BaseModelLoader
from modules.modelLoader.chroma.ChromaEmbeddingLoader import ChromaEmbeddingLoader
from modules.modelLoader.chroma.ChromaModelLoader import ChromaModelLoader
from modules.modelLoader.mixin.InternalModelLoaderMixin import InternalModelLoaderMixin
from modules.modelLoader.mixin.ModelSpecModelLoaderMixin import ModelSpecModelLoaderMixin
from modules.modelLoader.GenericEmbeddingModelLoader import make_embedding_model_loader
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes


class ChromaEmbeddingModelLoader(
BaseModelLoader,
ModelSpecModelLoaderMixin,
InternalModelLoaderMixin,
):
def __init__(self):
super().__init__()

def _default_model_spec_name(
self,
model_type: ModelType,
) -> str | None:
match model_type:
case ModelType.CHROMA_1:
return "resources/sd_model_spec/chroma-embedding.json"
case _:
return None

def load(
self,
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
) -> ChromaModel | None:
base_model_loader = ChromaModelLoader()
embedding_loader = ChromaEmbeddingLoader()

model = ChromaModel(model_type=model_type)
self._load_internal_data(model, model_names.embedding.model_name)
model.model_spec = self._load_default_model_spec(model_type)

if model_names.base_model is not None:
base_model_loader.load(model, model_type, model_names, weight_dtypes)
embedding_loader.load(model, model_names.embedding.model_name, model_names)

return model
ChromaEmbeddingModelLoader = make_embedding_model_loader(
model_spec_map={ModelType.CHROMA_1: "resources/sd_model_spec/chroma-embedding.json"},
model_class=ChromaModel,
model_loader_class=ChromaModelLoader,
embedding_loader_class=ChromaEmbeddingLoader,
)
49 changes: 7 additions & 42 deletions modules/modelLoader/ChromaFineTuneModelLoader.py
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@@ -1,47 +1,12 @@
from modules.model.ChromaModel import ChromaModel
from modules.modelLoader.BaseModelLoader import BaseModelLoader
from modules.modelLoader.chroma.ChromaEmbeddingLoader import ChromaEmbeddingLoader
from modules.modelLoader.chroma.ChromaModelLoader import ChromaModelLoader
from modules.modelLoader.mixin.InternalModelLoaderMixin import InternalModelLoaderMixin
from modules.modelLoader.mixin.ModelSpecModelLoaderMixin import ModelSpecModelLoaderMixin
from modules.modelLoader.GenericFineTuneModelLoader import make_fine_tune_model_loader
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes


class ChromaFineTuneModelLoader(
BaseModelLoader,
ModelSpecModelLoaderMixin,
InternalModelLoaderMixin,
):
def __init__(self):
super().__init__()

def _default_model_spec_name(
self,
model_type: ModelType,
) -> str | None:
match model_type:
case ModelType.CHROMA_1:
return "resources/sd_model_spec/chroma.json"
case _:
return None

def load(
self,
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
) -> ChromaModel | None:
base_model_loader = ChromaModelLoader()
embedding_loader = ChromaEmbeddingLoader()

model = ChromaModel(model_type=model_type)

self._load_internal_data(model, model_names.base_model)
model.model_spec = self._load_default_model_spec(model_type)

base_model_loader.load(model, model_type, model_names, weight_dtypes)
embedding_loader.load(model, model_names.base_model, model_names)

return model
ChromaFineTuneModelLoader = make_fine_tune_model_loader(
model_spec_map={ModelType.CHROMA_1: "resources/sd_model_spec/chroma.json"},
model_class=ChromaModel,
model_loader_class=ChromaModelLoader,
embedding_loader_class=ChromaEmbeddingLoader,
)
52 changes: 8 additions & 44 deletions modules/modelLoader/ChromaLoRAModelLoader.py
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@@ -1,50 +1,14 @@
from modules.model.ChromaModel import ChromaModel
from modules.modelLoader.BaseModelLoader import BaseModelLoader
from modules.modelLoader.chroma.ChromaEmbeddingLoader import ChromaEmbeddingLoader
from modules.modelLoader.chroma.ChromaLoRALoader import ChromaLoRALoader
from modules.modelLoader.chroma.ChromaModelLoader import ChromaModelLoader
from modules.modelLoader.mixin.InternalModelLoaderMixin import InternalModelLoaderMixin
from modules.modelLoader.mixin.ModelSpecModelLoaderMixin import ModelSpecModelLoaderMixin
from modules.modelLoader.GenericLoRAModelLoader import make_lora_model_loader
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes


class ChromaLoRAModelLoader(
BaseModelLoader,
ModelSpecModelLoaderMixin,
InternalModelLoaderMixin,
):
def __init__(self):
super().__init__()

def _default_model_spec_name(
self,
model_type: ModelType,
) -> str | None:
match model_type:
case ModelType.CHROMA_1:
return "resources/sd_model_spec/chroma-lora.json"
case _:
return None

def load(
self,
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
) -> ChromaModel | None:
base_model_loader = ChromaModelLoader()
lora_model_loader = ChromaLoRALoader()
embedding_loader = ChromaEmbeddingLoader()

model = ChromaModel(model_type=model_type)
self._load_internal_data(model, model_names.lora)
model.model_spec = self._load_default_model_spec(model_type)

if model_names.base_model is not None:
base_model_loader.load(model, model_type, model_names, weight_dtypes)
lora_model_loader.load(model, model_names)
embedding_loader.load(model, model_names.lora, model_names)

return model
ChromaLoRAModelLoader = make_lora_model_loader(
model_spec_map={ModelType.CHROMA_1: "resources/sd_model_spec/chroma-lora.json"},
model_class=ChromaModel,
model_loader_class=ChromaModelLoader,
embedding_loader_class=ChromaEmbeddingLoader,
lora_loader_class=ChromaLoRALoader,
)
54 changes: 10 additions & 44 deletions modules/modelLoader/FluxEmbeddingModelLoader.py
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from modules.model.FluxModel import FluxModel
from modules.modelLoader.BaseModelLoader import BaseModelLoader
from modules.modelLoader.flux.FluxEmbeddingLoader import FluxEmbeddingLoader
from modules.modelLoader.flux.FluxModelLoader import FluxModelLoader
from modules.modelLoader.mixin.InternalModelLoaderMixin import InternalModelLoaderMixin
from modules.modelLoader.mixin.ModelSpecModelLoaderMixin import ModelSpecModelLoaderMixin
from modules.modelLoader.GenericEmbeddingModelLoader import make_embedding_model_loader
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes


class FluxEmbeddingModelLoader(
BaseModelLoader,
ModelSpecModelLoaderMixin,
InternalModelLoaderMixin,
):
def __init__(self):
super().__init__()

def _default_model_spec_name(
self,
model_type: ModelType,
) -> str | None:
match model_type:
case ModelType.FLUX_DEV_1:
return "resources/sd_model_spec/flux_dev_1.0-embedding.json"
case ModelType.FLUX_FILL_DEV_1:
return "resources/sd_model_spec/flux_dev_fill_1.0-embedding.json"
case _:
return None

def load(
self,
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
) -> FluxModel | None:
base_model_loader = FluxModelLoader()
embedding_loader = FluxEmbeddingLoader()

model = FluxModel(model_type=model_type)
self._load_internal_data(model, model_names.embedding.model_name)
model.model_spec = self._load_default_model_spec(model_type)

if model_names.base_model is not None:
base_model_loader.load(model, model_type, model_names, weight_dtypes)
embedding_loader.load(model, model_names.embedding.model_name, model_names)

return model
FluxEmbeddingModelLoader = make_embedding_model_loader(
model_spec_map={
ModelType.FLUX_DEV_1: "resources/sd_model_spec/flux_dev_1.0-embedding.json",
ModelType.FLUX_FILL_DEV_1: "resources/sd_model_spec/flux_dev_fill_1.0-embedding.json",
},
model_class=FluxModel,
model_loader_class=FluxModelLoader,
embedding_loader_class=FluxEmbeddingLoader,
)
54 changes: 10 additions & 44 deletions modules/modelLoader/FluxFineTuneModelLoader.py
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from modules.model.FluxModel import FluxModel
from modules.modelLoader.BaseModelLoader import BaseModelLoader
from modules.modelLoader.flux.FluxEmbeddingLoader import FluxEmbeddingLoader
from modules.modelLoader.flux.FluxModelLoader import FluxModelLoader
from modules.modelLoader.mixin.InternalModelLoaderMixin import InternalModelLoaderMixin
from modules.modelLoader.mixin.ModelSpecModelLoaderMixin import ModelSpecModelLoaderMixin
from modules.modelLoader.GenericFineTuneModelLoader import make_fine_tune_model_loader
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes


class FluxFineTuneModelLoader(
BaseModelLoader,
ModelSpecModelLoaderMixin,
InternalModelLoaderMixin,
):
def __init__(self):
super().__init__()

def _default_model_spec_name(
self,
model_type: ModelType,
) -> str | None:
match model_type:
case ModelType.FLUX_DEV_1:
return "resources/sd_model_spec/flux_dev_1.0.json"
case ModelType.FLUX_FILL_DEV_1:
return "resources/sd_model_spec/flux_dev_fill_1.0.json"
case _:
return None

def load(
self,
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
) -> FluxModel | None:
base_model_loader = FluxModelLoader()
embedding_loader = FluxEmbeddingLoader()

model = FluxModel(model_type=model_type)

self._load_internal_data(model, model_names.base_model)
model.model_spec = self._load_default_model_spec(model_type)

base_model_loader.load(model, model_type, model_names, weight_dtypes)
embedding_loader.load(model, model_names.base_model, model_names)

return model
FluxFineTuneModelLoader = make_fine_tune_model_loader(
model_spec_map={
ModelType.FLUX_DEV_1: "resources/sd_model_spec/flux_dev_1.0.json",
ModelType.FLUX_FILL_DEV_1: "resources/sd_model_spec/flux_dev_fill_1.0.json",
},
model_class=FluxModel,
model_loader_class=FluxModelLoader,
embedding_loader_class=FluxEmbeddingLoader,
)
57 changes: 11 additions & 46 deletions modules/modelLoader/FluxLoRAModelLoader.py
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from modules.model.FluxModel import FluxModel
from modules.modelLoader.BaseModelLoader import BaseModelLoader
from modules.modelLoader.flux.FluxEmbeddingLoader import FluxEmbeddingLoader
from modules.modelLoader.flux.FluxLoRALoader import FluxLoRALoader
from modules.modelLoader.flux.FluxModelLoader import FluxModelLoader
from modules.modelLoader.mixin.InternalModelLoaderMixin import InternalModelLoaderMixin
from modules.modelLoader.mixin.ModelSpecModelLoaderMixin import ModelSpecModelLoaderMixin
from modules.modelLoader.GenericLoRAModelLoader import make_lora_model_loader
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes


class FluxLoRAModelLoader(
BaseModelLoader,
ModelSpecModelLoaderMixin,
InternalModelLoaderMixin,
):
def __init__(self):
super().__init__()

def _default_model_spec_name(
self,
model_type: ModelType,
) -> str | None:
match model_type:
case ModelType.FLUX_DEV_1:
return "resources/sd_model_spec/flux_dev_1.0-lora.json"
case ModelType.FLUX_FILL_DEV_1:
return "resources/sd_model_spec/flux_dev_fill_1.0-lora.json"
case _:
return None

def load(
self,
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
) -> FluxModel | None:
base_model_loader = FluxModelLoader()
lora_model_loader = FluxLoRALoader()
embedding_loader = FluxEmbeddingLoader()

model = FluxModel(model_type=model_type)
self._load_internal_data(model, model_names.lora)
model.model_spec = self._load_default_model_spec(model_type)

if model_names.base_model is not None:
base_model_loader.load(model, model_type, model_names, weight_dtypes)
lora_model_loader.load(model, model_names)
embedding_loader.load(model, model_names.lora, model_names)

return model
FluxLoRAModelLoader = make_lora_model_loader(
model_spec_map={
ModelType.FLUX_DEV_1: "resources/sd_model_spec/flux_dev_1.0-lora.json",
ModelType.FLUX_FILL_DEV_1: "resources/sd_model_spec/flux_dev_fill_1.0-lora.json",
},
model_class=FluxModel,
model_loader_class=FluxModelLoader,
embedding_loader_class=FluxEmbeddingLoader,
lora_loader_class=FluxLoRALoader,
)
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