restore NSFW checker

invokeai/backend/__init__.py

@@ -11,5 +11,6 @@ from .generator import (
     Inpaint
 )
 from .model_management import ModelManager
+from .safety_checker import SafetyChecker
 from .args import Args
 from .globals import Globals

invokeai/backend/generate.py

@@ -25,18 +25,19 @@ from accelerate.utils import set_seed
 from diffusers.pipeline_utils import DiffusionPipeline
 from diffusers.utils.import_utils import is_xformers_available
 from omegaconf import OmegaConf
+from pathlib import Path
 
 from .args import metadata_from_png
 from .generator import infill_methods
 from .globals import Globals, global_cache_dir
 from .image_util import InitImageResizer, PngWriter, Txt2Mask, configure_model_padding
 from .model_management import ModelManager
+from .safety_checker import SafetyChecker
 from .prompting import get_uc_and_c_and_ec
 from .prompting.conditioning import log_tokenization
 from .stable_diffusion import HuggingFaceConceptsLibrary
 from .util import choose_precision, choose_torch_device
 
-
 def fix_func(orig):
     if hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
 
@@ -245,31 +246,8 @@ class Generate:
 
         # load safety checker if requested
         if safety_checker:
-            try:
+            print(">> Initializing NSFW checker")
-                print(">> Initializing NSFW checker")
+            self.safety_checker = SafetyChecker(self.device)
-                from diffusers.pipelines.stable_diffusion.safety_checker import (
-                    StableDiffusionSafetyChecker,
-                )
-                from transformers import AutoFeatureExtractor
-
-                safety_model_id = "CompVis/stable-diffusion-safety-checker"
-                safety_model_path = global_cache_dir("hub")
-                self.safety_checker = StableDiffusionSafetyChecker.from_pretrained(
-                    safety_model_id,
-                    local_files_only=True,
-                    cache_dir=safety_model_path,
-                )
-                self.safety_feature_extractor = AutoFeatureExtractor.from_pretrained(
-                    safety_model_id,
-                    local_files_only=True,
-                    cache_dir=safety_model_path,
-                )
-                self.safety_checker.to(self.device)
-            except Exception:
-                print(
-                    "** An error was encountered while installing the safety checker:"
-                )
-                print(traceback.format_exc())
         else:
             print(">> NSFW checker is disabled")
 
@@ -524,15 +502,6 @@ class Generate:
             generator.set_variation(self.seed, variation_amount, with_variations)
             generator.use_mps_noise = use_mps_noise
 
-            checker = (
-                {
-                    "checker": self.safety_checker,
-                    "extractor": self.safety_feature_extractor,
-                }
-                if self.safety_checker
-                else None
-            )
-
             results = generator.generate(
                 prompt,
                 iterations=iterations,
@@ -559,7 +528,7 @@ class Generate:
                 embiggen_strength=embiggen_strength,
                 inpaint_replace=inpaint_replace,
                 mask_blur_radius=mask_blur_radius,
-                safety_checker=checker,
+                safety_checker=self.safety_checker,
                 seam_size=seam_size,
                 seam_blur=seam_blur,
                 seam_strength=seam_strength,

invokeai/backend/safety_checker.py

@@ -15,14 +15,18 @@ from transformers import AutoFeatureExtractor
 
 import invokeai.assets.web as web_assets
 from .globals import global_cache_dir
+from .util import CPU_DEVICE
 
 class SafetyChecker(object):
     CAUTION_IMG = "caution.png"
     
     def __init__(self, device: torch.device):
+        path = Path(web_assets.__path__[0]) / self.CAUTION_IMG
+        caution = Image.open(path)
+        self.caution_img = caution.resize((caution.width // 2, caution.height // 2))
         self.device = device
+        
         try:
-            print(">> Initializing NSFW checker")
             safety_model_id = "CompVis/stable-diffusion-safety-checker"
             safety_model_path = global_cache_dir("hub")
             self.safety_checker = StableDiffusionSafetyChecker.from_pretrained(
@@ -35,15 +39,11 @@ class SafetyChecker(object):
                 local_files_only=True,
                 cache_dir=safety_model_path,
             )
-            self.safety_checker.to(device)
-            self.safety_feature_extractor.to(device)
         except Exception:
             print(
                 "** An error was encountered while installing the safety checker:"
             )
             print(traceback.format_exc())
-        else:
-            print(">> NSFW checker is disabled")
 
     def check(self, image: Image.Image):
         """
@@ -51,7 +51,10 @@ class SafetyChecker(object):
 
         """
 
+        self.safety_checker.to(self.device)
         features = self.safety_feature_extractor([image], return_tensors="pt")
+        features.to(self.device)
+        
         # unfortunately checker requires the numpy version, so we have to convert back
         x_image = np.array(image).astype(np.float32) / 255.0
         x_image = x_image[None].transpose(0, 3, 1, 2)
@@ -60,6 +63,7 @@ class SafetyChecker(object):
         checked_image, has_nsfw_concept = self.safety_checker(
             images=x_image, clip_input=features.pixel_values
         )
+        self.safety_checker.to(CPU_DEVICE) # offload
         if has_nsfw_concept[0]:
             print(
                 "** An image with potential non-safe content has been detected. A blurred image will be returned. **"
@@ -71,19 +75,8 @@ class SafetyChecker(object):
     def blur(self, input):
         blurry = input.filter(filter=ImageFilter.GaussianBlur(radius=32))
         try:
-            caution = self.get_caution_img()
+            if caution := self.caution_img:
-            if caution:
                 blurry.paste(caution, (0, 0), caution)
         except FileNotFoundError:
             pass
         return blurry
-
-    def get_caution_img(self):
-        path = None
-        if self.caution_img:
-            return self.caution_img
-        path = Path(web_assets.__path__[0]) / self.CAUTION_IMG
-        caution = Image.open(path)
-        self.caution_img = caution.resize((caution.width // 2, caution.height // 2))
-        return self.caution_img
-            

tests/nodes/test_graph_execution_state.py

@@ -21,7 +21,7 @@ def simple_graph():
 def mock_services():
     # NOTE: none of these are actually called by the test invocations
     return InvocationServices(
-        generate = None,
+        model_manager = None,
         events = None,
         images = None,
         queue = MemoryInvocationQueue(),

tests/nodes/test_invoker.py

@@ -21,7 +21,7 @@ def simple_graph():
 def mock_services() -> InvocationServices:
     # NOTE: none of these are actually called by the test invocations
     return InvocationServices(
-        generate = None, # type: ignore
+        model_manager = None, # type: ignore
         events = TestEventService(),
         images = None, # type: ignore
         queue = MemoryInvocationQueue(),