dep(diffusers): upgrade diffusers to 0.20

invokeai/backend/model_management/convert_ckpt_to_diffusers.py

@@ -20,29 +20,22 @@
 import re
 from contextlib import nullcontext
 from io import BytesIO
-from typing import Optional, Union
 from pathlib import Path
+from typing import Optional, Union
 
 import requests
 import torch
-from transformers import (
-    AutoFeatureExtractor,
-    BertTokenizerFast,
-    CLIPImageProcessor,
-    CLIPTextConfig,
-    CLIPTextModel,
-    CLIPTextModelWithProjection,
-    CLIPTokenizer,
-    CLIPVisionConfig,
-    CLIPVisionModelWithProjection,
-)
-
 from diffusers.models import (
     AutoencoderKL,
     ControlNetModel,
     PriorTransformer,
     UNet2DConditionModel,
 )
+from diffusers.pipelines.latent_diffusion.pipeline_latent_diffusion import LDMBertConfig, LDMBertModel
+from diffusers.pipelines.paint_by_example import PaintByExampleImageEncoder
+from diffusers.pipelines.pipeline_utils import DiffusionPipeline
+from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
+from diffusers.pipelines.stable_diffusion.stable_unclip_image_normalizer import StableUnCLIPImageNormalizer
 from diffusers.schedulers import (
     DDIMScheduler,
     DDPMScheduler,
@@ -54,18 +47,23 @@
     PNDMScheduler,
     UnCLIPScheduler,
 )
-from diffusers.utils import is_accelerate_available, is_omegaconf_available, is_safetensors_available
+from diffusers.utils import is_accelerate_available, is_omegaconf_available
 from diffusers.utils.import_utils import BACKENDS_MAPPING
-from diffusers.pipelines.latent_diffusion.pipeline_latent_diffusion import LDMBertConfig, LDMBertModel
-from diffusers.pipelines.paint_by_example import PaintByExampleImageEncoder
-from diffusers.pipelines.pipeline_utils import DiffusionPipeline
-from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
-from diffusers.pipelines.stable_diffusion.stable_unclip_image_normalizer import StableUnCLIPImageNormalizer
+from picklescan.scanner import scan_file_path
+from transformers import (
+    AutoFeatureExtractor,
+    BertTokenizerFast,
+    CLIPImageProcessor,
+    CLIPTextConfig,
+    CLIPTextModel,
+    CLIPTextModelWithProjection,
+    CLIPTokenizer,
+    CLIPVisionConfig,
+    CLIPVisionModelWithProjection,
+)
 
-from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.app.services.config import InvokeAIAppConfig
-
-from picklescan.scanner import scan_file_path
+from invokeai.backend.util.logging import InvokeAILogger
 from .models import BaseModelType, ModelVariantType
 
 try:
@@ -1221,9 +1219,6 @@ def download_from_original_stable_diffusion_ckpt(
         raise ValueError(BACKENDS_MAPPING["omegaconf"][1])
 
     if from_safetensors:
-        if not is_safetensors_available():
-            raise ValueError(BACKENDS_MAPPING["safetensors"][1])
-
         from safetensors.torch import load_file as safe_load
 
         checkpoint = safe_load(checkpoint_path, device="cpu")
@@ -1662,9 +1657,6 @@ def download_controlnet_from_original_ckpt(
     from omegaconf import OmegaConf
 
     if from_safetensors:
-        if not is_safetensors_available():
-            raise ValueError(BACKENDS_MAPPING["safetensors"][1])
-
         from safetensors import safe_open
 
         checkpoint = {}
@@ -1741,7 +1733,7 @@ def convert_ckpt_to_diffusers(
 
     pipe.save_pretrained(
         dump_path,
-        safe_serialization=use_safetensors and is_safetensors_available(),
+        safe_serialization=use_safetensors,
     )
 
 
@@ -1757,7 +1749,4 @@ def convert_controlnet_to_diffusers(
     """
     pipe = download_controlnet_from_original_ckpt(checkpoint_path, **kwargs)
 
-    pipe.save_pretrained(
-        dump_path,
-        safe_serialization=is_safetensors_available(),
-    )
+    pipe.save_pretrained(dump_path, safe_serialization=True)

invokeai/backend/model_management/models/vae.py

@@ -5,7 +5,6 @@
 
 import safetensors
 import torch
-from diffusers.utils import is_safetensors_available
 from omegaconf import OmegaConf
 
 from invokeai.app.services.config import InvokeAIAppConfig
@@ -175,5 +174,5 @@ def _convert_vae_ckpt_and_cache(
         vae_config=config,
         image_size=image_size,
     )
-    vae_model.save_pretrained(output_path, safe_serialization=is_safetensors_available())
+    vae_model.save_pretrained(output_path, safe_serialization=True)
     return output_path

pyproject.toml

@@ -40,7 +40,7 @@ dependencies = [
   "controlnet-aux>=0.0.6",
   "timm==0.6.13",   # needed to override timm latest in controlnet_aux, see  https://github.com/isl-org/ZoeDepth/issues/26
   "datasets",
-  "diffusers[torch]~=0.19.3",
+  "diffusers[torch]~=0.20.0",
   "dnspython~=2.4.0",
   "dynamicprompts",
   "easing-functions",
@@ -49,7 +49,7 @@ dependencies = [
   "fastapi==0.88.0",
   "fastapi-events==0.8.0",
   "fastapi-socketio==0.0.10",
-  "huggingface-hub>=0.11.1",
+  "huggingface-hub~=0.16.4",
   "invisible-watermark~=0.2.0", # needed to install SDXL base and refiner using their repo_ids
   "matplotlib",                 # needed for plotting of Penner easing functions
   "mediapipe",                  # needed for "mediapipeface" controlnet model