Merge branch 'main' of https://github.com/huggingface/diffusers into main

Author: patrickvonplaten

docs/source/api/pipelines/stable_diffusion.mdx

@@ -95,3 +95,10 @@ If you want to use all possible use cases in a single `DiffusionPipeline` you ca
 	- __call__
 	- enable_attention_slicing
 	- disable_attention_slicing
+
+
+## StableDiffusionUpscalePipeline
+[[autodoc]] StableDiffusionUpscalePipeline
+	- __call__
+	- enable_attention_slicing
+	- disable_attention_slicing

src/diffusers/__init__.py

@@ -75,6 +75,7 @@
         StableDiffusionInpaintPipelineLegacy,
         StableDiffusionPipeline,
         StableDiffusionPipelineSafe,
+        StableDiffusionUpscalePipeline,
         VersatileDiffusionDualGuidedPipeline,
         VersatileDiffusionImageVariationPipeline,
         VersatileDiffusionPipeline,

src/diffusers/pipeline_utils.py

@@ -554,7 +554,9 @@ def load_module(name, value):
         init_dict = {k: v for k, v in init_dict.items() if load_module(k, v)}
 
         if len(unused_kwargs) > 0:
-            logger.warning(f"Keyword arguments {unused_kwargs} not recognized.")
+            logger.warning(
+                f"Keyword arguments {unused_kwargs} are not expected by {pipeline_class.__name__} and will be ignored."
+            )
 
         # import it here to avoid circular import
         from diffusers import pipelines
@@ -680,8 +682,8 @@ def load_module(name, value):
     @staticmethod
     def _get_signature_keys(obj):
         parameters = inspect.signature(obj.__init__).parameters
-        required_parameters = {k: v for k, v in parameters.items() if v.default is not True}
-        optional_parameters = set({k for k, v in parameters.items() if v.default is True})
+        required_parameters = {k: v for k, v in parameters.items() if v.default == inspect._empty}
+        optional_parameters = set({k for k, v in parameters.items() if v.default != inspect._empty})
         expected_modules = set(required_parameters.keys()) - set(["self"])
         return expected_modules, optional_parameters
 

src/diffusers/pipelines/__init__.py

@@ -24,6 +24,7 @@
         StableDiffusionInpaintPipeline,
         StableDiffusionInpaintPipelineLegacy,
         StableDiffusionPipeline,
+        StableDiffusionUpscalePipeline,
     )
     from .stable_diffusion_safe import StableDiffusionPipelineSafe
     from .versatile_diffusion import (

src/diffusers/pipelines/stable_diffusion/__init__.py

@@ -40,6 +40,7 @@ class StableDiffusionPipelineOutput(BaseOutput):
     from .pipeline_stable_diffusion_img2img import StableDiffusionImg2ImgPipeline
     from .pipeline_stable_diffusion_inpaint import StableDiffusionInpaintPipeline
     from .pipeline_stable_diffusion_inpaint_legacy import StableDiffusionInpaintPipelineLegacy
+    from .pipeline_stable_diffusion_upscale import StableDiffusionUpscalePipeline
     from .safety_checker import StableDiffusionSafetyChecker
 
 if is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0.dev0"):

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py

@@ -154,6 +154,21 @@ def from_pretrained(cls, *args, **kwargs):
         requires_backends(cls, ["torch", "transformers"])
 
 
+class StableDiffusionUpscalePipeline(metaclass=DummyObject):
+    _backends = ["torch", "transformers"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch", "transformers"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+
 class VersatileDiffusionDualGuidedPipeline(metaclass=DummyObject):
     _backends = ["torch", "transformers"]
 

src/diffusers/utils/dummy_torch_and_transformers_objects.py

@@ -34,7 +34,7 @@
 )
 from diffusers.utils import load_numpy, slow, torch_device
 from diffusers.utils.testing_utils import CaptureLogger, require_torch_gpu
-from transformers import CLIPFeatureExtractor, CLIPTextConfig, CLIPTextModel, CLIPTokenizer
+from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
 
 from ...test_pipelines_common import PipelineTesterMixin
 
@@ -100,21 +100,6 @@ def dummy_text_encoder(self):
         )
         return CLIPTextModel(config)
 
-    @property
-    def dummy_extractor(self):
-        def extract(*args, **kwargs):
-            class Out:
-                def __init__(self):
-                    self.pixel_values = torch.ones([0])
-
-                def to(self, device):
-                    self.pixel_values.to(device)
-                    return self
-
-            return Out()
-
-        return extract
-
     def test_save_pretrained_from_pretrained(self):
         device = "cpu"  # ensure determinism for the device-dependent torch.Generator
         unet = self.dummy_cond_unet
@@ -129,7 +114,6 @@ def test_save_pretrained_from_pretrained(self):
         vae = self.dummy_vae
         bert = self.dummy_text_encoder
         tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip")
-        feature_extractor = CLIPFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-clip")
 
         # make sure here that pndm scheduler skips prk
         sd_pipe = StableDiffusionPipeline(
@@ -139,7 +123,8 @@ def test_save_pretrained_from_pretrained(self):
             text_encoder=bert,
             tokenizer=tokenizer,
             safety_checker=None,
-            feature_extractor=feature_extractor,
+            feature_extractor=None,
+            requires_safety_checker=False,
         )
         sd_pipe = sd_pipe.to(device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -185,7 +170,8 @@ def test_stable_diffusion_ddim(self):
             text_encoder=bert,
             tokenizer=tokenizer,
             safety_checker=None,
-            feature_extractor=self.dummy_extractor,
+            feature_extractor=None,
+            requires_safety_checker=False,
         )
         sd_pipe = sd_pipe.to(device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -231,7 +217,8 @@ def test_stable_diffusion_pndm(self):
             text_encoder=bert,
             tokenizer=tokenizer,
             safety_checker=None,
-            feature_extractor=self.dummy_extractor,
+            feature_extractor=None,
+            requires_safety_checker=False,
         )
         sd_pipe = sd_pipe.to(device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -276,7 +263,8 @@ def test_stable_diffusion_k_lms(self):
             text_encoder=bert,
             tokenizer=tokenizer,
             safety_checker=None,
-            feature_extractor=self.dummy_extractor,
+            feature_extractor=None,
+            requires_safety_checker=False,
         )
         sd_pipe = sd_pipe.to(device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -321,7 +309,8 @@ def test_stable_diffusion_k_euler_ancestral(self):
             text_encoder=bert,
             tokenizer=tokenizer,
             safety_checker=None,
-            feature_extractor=self.dummy_extractor,
+            feature_extractor=None,
+            requires_safety_checker=False,
         )
         sd_pipe = sd_pipe.to(device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -366,7 +355,8 @@ def test_stable_diffusion_k_euler(self):
             text_encoder=bert,
             tokenizer=tokenizer,
             safety_checker=None,
-            feature_extractor=self.dummy_extractor,
+            feature_extractor=None,
+            requires_safety_checker=False,
         )
         sd_pipe = sd_pipe.to(device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -411,7 +401,8 @@ def test_stable_diffusion_attention_chunk(self):
             text_encoder=bert,
             tokenizer=tokenizer,
             safety_checker=None,
-            feature_extractor=self.dummy_extractor,
+            feature_extractor=None,
+            requires_safety_checker=False,
         )
         sd_pipe = sd_pipe.to(device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -449,7 +440,8 @@ def test_stable_diffusion_fp16(self):
             text_encoder=bert,
             tokenizer=tokenizer,
             safety_checker=None,
-            feature_extractor=self.dummy_extractor,
+            feature_extractor=None,
+            requires_safety_checker=False,
         )
         sd_pipe = sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -475,7 +467,8 @@ def test_stable_diffusion_long_prompt(self):
             text_encoder=bert,
             tokenizer=tokenizer,
             safety_checker=None,
-            feature_extractor=self.dummy_extractor,
+            feature_extractor=None,
+            requires_safety_checker=False,
         )
         sd_pipe = sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -572,7 +565,7 @@ def test_stable_diffusion_k_lms(self):
         expected_slice = np.array([0.0548, 0.0626, 0.0612, 0.0611, 0.0706, 0.0586, 0.0843, 0.0333, 0.1197])
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
 
-    def test_stable_diffusion_memory_chunking(self):
+    def test_stable_diffusion_attention_slicing(self):
         torch.cuda.reset_peak_memory_stats()
         model_id = "stabilityai/stable-diffusion-2-base"
         pipe = StableDiffusionPipeline.from_pretrained(model_id, revision="fp16", torch_dtype=torch.float16)
@@ -651,7 +644,7 @@ def test_stable_diffusion_text2img_pipeline_default(self):
         prompt = "astronaut riding a horse"
 
         generator = torch.Generator(device=torch_device).manual_seed(0)
-        output = pipe(prompt=prompt, strength=0.75, guidance_scale=7.5, generator=generator, output_type="np")
+        output = pipe(prompt=prompt, guidance_scale=7.5, generator=generator, output_type="np")
         image = output.images[0]
 
         assert image.shape == (512, 512, 3)