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merge with main and resolve conflicts

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Lincoln Stein
2024-05-27 22:20:34 -04:00
parent 987ee704a1 ddff9b4584
commit 34e1eb19f9
256 changed files with 9360 additions and 6061 deletions
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9
invokeai/app/services/model_load/model_load_base.py
View File

@ -7,7 +7,6 @@ from typing import Callable, Dict, Optional
from torch import Tensor
from invokeai.app.services.shared.invocation_context import InvocationContextData
from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType
from invokeai.backend.model_manager.load import LoadedModel
from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
@ -18,18 +17,12 @@ class ModelLoadServiceBase(ABC):
"""Wrapper around AnyModelLoader."""
@abstractmethod
def load_model(
self,
model_config: AnyModelConfig,
submodel_type: Optional[SubModelType] = None,
context_data: Optional[InvocationContextData] = None,
) -> LoadedModel:
def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
"""
Given a model's configuration, load it and return the LoadedModel object.
:param model_config: Model configuration record (as returned by ModelRecordBase.get_model())
:param submodel: For main (pipeline models), the submodel to fetch.
:param context_data: Invocation context data used for event reporting
"""
@property

59
invokeai/app/services/model_load/model_load_default.py
View File

@ -11,7 +11,6 @@ from torch import load as torch_load
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.app.services.invoker import Invoker
from invokeai.app.services.shared.invocation_context import InvocationContextData
from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType
from invokeai.backend.model_manager.load import (
LoadedModel,
@ -59,25 +58,18 @@ class ModelLoadService(ModelLoadServiceBase):
"""Return the checkpoint convert cache used by this loader."""
return self._convert_cache
def load_model(
self,
model_config: AnyModelConfig,
submodel_type: Optional[SubModelType] = None,
context_data: Optional[InvocationContextData] = None,
) -> LoadedModel:
def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
"""
Given a model's configuration, load it and return the LoadedModel object.
:param model_config: Model configuration record (as returned by ModelRecordBase.get_model())
:param submodel: For main (pipeline models), the submodel to fetch.
:param context: Invocation context used for event reporting
"""
if context_data:
self._emit_load_event(
context_data=context_data,
model_config=model_config,
submodel_type=submodel_type,
)
# We don't have an invoker during testing
# TODO(psyche): Mock this method on the invoker in the tests
if hasattr(self, "_invoker"):
self._invoker.services.events.emit_model_load_started(model_config, submodel_type)
implementation, model_config, submodel_type = self._registry.get_implementation(model_config, submodel_type) # type: ignore
loaded_model: LoadedModel = implementation(
@ -87,13 +79,9 @@ class ModelLoadService(ModelLoadServiceBase):
convert_cache=self._convert_cache,
).load_model(model_config, submodel_type)
if context_data:
self._emit_load_event(
context_data=context_data,
model_config=model_config,
submodel_type=submodel_type,
loaded=True,
)
if hasattr(self, "_invoker"):
self._invoker.services.events.emit_model_load_complete(model_config, submodel_type)
return loaded_model
def load_model_from_path(
@ -150,32 +138,3 @@ class ModelLoadService(ModelLoadServiceBase):
raw_model = loader(model_path)
ram_cache.put(key=cache_key, model=raw_model)
return LoadedModel(_locker=ram_cache.get(key=cache_key))
def _emit_load_event(
self,
context_data: InvocationContextData,
model_config: AnyModelConfig,
loaded: Optional[bool] = False,
submodel_type: Optional[SubModelType] = None,
) -> None:
if not self._invoker:
return
if not loaded:
self._invoker.services.events.emit_model_load_started(
queue_id=context_data.queue_item.queue_id,
queue_item_id=context_data.queue_item.item_id,
queue_batch_id=context_data.queue_item.batch_id,
graph_execution_state_id=context_data.queue_item.session_id,
model_config=model_config,
submodel_type=submodel_type,
)
else:
self._invoker.services.events.emit_model_load_completed(
queue_id=context_data.queue_item.queue_id,
queue_item_id=context_data.queue_item.item_id,
queue_batch_id=context_data.queue_item.batch_id,
graph_execution_state_id=context_data.queue_item.session_id,
model_config=model_config,
submodel_type=submodel_type,
)