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https://github.com/invoke-ai/InvokeAI
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Fix IP-Adapter calculation of memory footprint.
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@ -9,6 +9,8 @@ from diffusers.models import UNet2DConditionModel
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from PIL import Image
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from PIL import Image
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from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
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from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
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from invokeai.backend.model_management.models.base import calc_model_size_by_data
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from .attention_processor import AttnProcessor2_0, IPAttnProcessor2_0
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from .attention_processor import AttnProcessor2_0, IPAttnProcessor2_0
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from .resampler import Resampler
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from .resampler import Resampler
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@ -87,6 +89,20 @@ class IPAdapter:
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if self._attn_processors is not None:
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if self._attn_processors is not None:
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torch.nn.ModuleList(self._attn_processors.values()).to(device=self.device, dtype=self.dtype)
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torch.nn.ModuleList(self._attn_processors.values()).to(device=self.device, dtype=self.dtype)
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def calc_size(self):
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if self._state_dict is not None:
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image_proj_size = sum(
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[tensor.nelement() * tensor.element_size() for tensor in self._state_dict["image_proj"].values()]
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)
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ip_adapter_size = sum(
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[tensor.nelement() * tensor.element_size() for tensor in self._state_dict["ip_adapter"].values()]
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)
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return image_proj_size + ip_adapter_size
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else:
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return calc_model_size_by_data(self._image_proj_model) + calc_model_size_by_data(
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torch.nn.ModuleList(self._attn_processors.values())
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)
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def _init_image_proj_model(self, state_dict):
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def _init_image_proj_model(self, state_dict):
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return ImageProjModel.from_state_dict(state_dict, self._num_tokens).to(self.device, dtype=self.dtype)
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return ImageProjModel.from_state_dict(state_dict, self._num_tokens).to(self.device, dtype=self.dtype)
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@ -13,6 +13,7 @@ from invokeai.backend.model_management.models.base import (
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ModelConfigBase,
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ModelConfigBase,
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ModelType,
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ModelType,
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SubModelType,
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SubModelType,
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calc_model_size_by_fs,
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classproperty,
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classproperty,
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)
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)
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@ -30,7 +31,7 @@ class IPAdapterModel(ModelBase):
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assert model_type == ModelType.IPAdapter
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assert model_type == ModelType.IPAdapter
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super().__init__(model_path, base_model, model_type)
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super().__init__(model_path, base_model, model_type)
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self.model_size = os.path.getsize(self.model_path)
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self.model_size = calc_model_size_by_fs(self.model_path)
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@classmethod
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@classmethod
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def detect_format(cls, path: str) -> str:
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def detect_format(cls, path: str) -> str:
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@ -63,10 +64,13 @@ class IPAdapterModel(ModelBase):
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if child_type is not None:
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if child_type is not None:
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raise ValueError("There are no child models in an IP-Adapter model.")
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raise ValueError("There are no child models in an IP-Adapter model.")
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return build_ip_adapter(
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model = build_ip_adapter(
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ip_adapter_ckpt_path=os.path.join(self.model_path, "ip_adapter.bin"), device="cpu", dtype=torch_dtype
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ip_adapter_ckpt_path=os.path.join(self.model_path, "ip_adapter.bin"), device="cpu", dtype=torch_dtype
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)
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)
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self.model_size = model.calc_size()
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return model
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@classmethod
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@classmethod
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def convert_if_required(
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def convert_if_required(
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cls,
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cls,
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