Post 0.17.0 release (#3721)

* Post release

* Post release

examples/controlnet/train_controlnet.py

@@ -55,7 +55,7 @@ if is_wandb_available():
     import wandb
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = get_logger(__name__)
 

examples/controlnet/train_controlnet_flax.py

@@ -59,7 +59,7 @@ if is_wandb_available():
     import wandb
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = logging.getLogger(__name__)
 

examples/custom_diffusion/train_custom_diffusion.py

@@ -56,7 +56,7 @@ from diffusers.utils.import_utils import is_xformers_available
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = get_logger(__name__)
 

examples/dreambooth/train_dreambooth.py

@@ -58,7 +58,7 @@ if is_wandb_available():
     import wandb
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = get_logger(__name__)
 

examples/dreambooth/train_dreambooth_flax.py

@@ -36,7 +36,7 @@ from diffusers.utils import check_min_version
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 # Cache compiled models across invocations of this script.
 cc.initialize_cache(os.path.expanduser("~/.cache/jax/compilation_cache"))

examples/dreambooth/train_dreambooth_lora.py

@@ -64,7 +64,7 @@ from diffusers.utils.import_utils import is_xformers_available
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = get_logger(__name__)
 

examples/instruct_pix2pix/train_instruct_pix2pix.py

@@ -51,7 +51,7 @@ from diffusers.utils.import_utils import is_xformers_available
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

examples/text_to_image/train_text_to_image.py

@@ -52,7 +52,7 @@ if is_wandb_available():
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

examples/text_to_image/train_text_to_image_flax.py

@@ -33,7 +33,7 @@ from diffusers.utils import check_min_version
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = logging.getLogger(__name__)
 

examples/text_to_image/train_text_to_image_lora.py

@@ -47,7 +47,7 @@ from diffusers.utils.import_utils import is_xformers_available
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

examples/textual_inversion/textual_inversion.py

@@ -77,7 +77,7 @@ else:
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = get_logger(__name__)
 

examples/textual_inversion/textual_inversion_flax.py

@@ -56,7 +56,7 @@ else:
 # ------------------------------------------------------------------------------
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = logging.getLogger(__name__)
 

examples/unconditional_image_generation/train_unconditional.py

@@ -28,7 +28,7 @@ from diffusers.utils.import_utils import is_xformers_available
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.17.0.dev0")
+check_min_version("0.18.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

setup.py

@@ -227,7 +227,7 @@ install_requires = [
 
 setup(
     name="diffusers",
-    version="0.17.0.dev0",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
+    version="0.18.0.dev0",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
     description="Diffusers",
     long_description=open("README.md", "r", encoding="utf-8").read(),
     long_description_content_type="text/markdown",

src/diffusers/__init__.py

-__version__ = "0.17.0.dev0"
+__version__ = "0.18.0.dev0"
 
 from .configuration_utils import ConfigMixin
 from .utils import (

src/diffusers/loaders.py

@@ -366,7 +366,7 @@ class UNet2DConditionLoadersMixin:
         """
         weight_name = weight_name or deprecate(
             "weights_name",
-            "0.18.0",
+            "0.20.0",
             "`weights_name` is deprecated, please use `weight_name` instead.",
             take_from=kwargs,
         )

src/diffusers/models/cross_attention.py

@@ -29,7 +29,7 @@ from .attention_processor import AttnProcessor as AttnProcessorRename  # noqa: F
 
 deprecate(
     "cross_attention",
-    "0.18.0",
+    "0.20.0",
     "Importing from cross_attention is deprecated. Please import from diffusers.models.attention_processor instead.",
     standard_warn=False,
 )
@@ -40,55 +40,55 @@ AttnProcessor = AttentionProcessor
 
 class CrossAttention(Attention):
     def __init__(self, *args, **kwargs):
-        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.18.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
-        deprecate("cross_attention", "0.18.0", deprecation_message, standard_warn=False)
+        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
+        deprecate("cross_attention", "0.20.0", deprecation_message, standard_warn=False)
         super().__init__(*args, **kwargs)
 
 
 class CrossAttnProcessor(AttnProcessorRename):
     def __init__(self, *args, **kwargs):
-        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.18.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
-        deprecate("cross_attention", "0.18.0", deprecation_message, standard_warn=False)
+        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
+        deprecate("cross_attention", "0.20.0", deprecation_message, standard_warn=False)
         super().__init__(*args, **kwargs)
 
 
 class LoRACrossAttnProcessor(LoRAAttnProcessor):
     def __init__(self, *args, **kwargs):
-        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.18.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
-        deprecate("cross_attention", "0.18.0", deprecation_message, standard_warn=False)
+        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
+        deprecate("cross_attention", "0.20.0", deprecation_message, standard_warn=False)
         super().__init__(*args, **kwargs)
 
 
 class CrossAttnAddedKVProcessor(AttnAddedKVProcessor):
     def __init__(self, *args, **kwargs):
-        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.18.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
-        deprecate("cross_attention", "0.18.0", deprecation_message, standard_warn=False)
+        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
+        deprecate("cross_attention", "0.20.0", deprecation_message, standard_warn=False)
         super().__init__(*args, **kwargs)
 
 
 class XFormersCrossAttnProcessor(XFormersAttnProcessor):
     def __init__(self, *args, **kwargs):
-        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.18.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
-        deprecate("cross_attention", "0.18.0", deprecation_message, standard_warn=False)
+        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
+        deprecate("cross_attention", "0.20.0", deprecation_message, standard_warn=False)
         super().__init__(*args, **kwargs)
 
 
 class LoRAXFormersCrossAttnProcessor(LoRAXFormersAttnProcessor):
     def __init__(self, *args, **kwargs):
-        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.18.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
-        deprecate("cross_attention", "0.18.0", deprecation_message, standard_warn=False)
+        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
+        deprecate("cross_attention", "0.20.0", deprecation_message, standard_warn=False)
         super().__init__(*args, **kwargs)
 
 
 class SlicedCrossAttnProcessor(SlicedAttnProcessor):
     def __init__(self, *args, **kwargs):
-        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.18.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
-        deprecate("cross_attention", "0.18.0", deprecation_message, standard_warn=False)
+        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
+        deprecate("cross_attention", "0.20.0", deprecation_message, standard_warn=False)
         super().__init__(*args, **kwargs)
 
 
 class SlicedCrossAttnAddedKVProcessor(SlicedAttnAddedKVProcessor):
     def __init__(self, *args, **kwargs):
-        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.18.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
-        deprecate("cross_attention", "0.18.0", deprecation_message, standard_warn=False)
+        deprecation_message = f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'))} instead."
+        deprecate("cross_attention", "0.20.0", deprecation_message, standard_warn=False)
         super().__init__(*args, **kwargs)

src/diffusers/pipelines/pipeline_utils.py

@@ -1099,13 +1099,6 @@ class DiffusionPipeline(ConfigMixin):
 
         # 8. Instantiate the pipeline
         model = pipeline_class(**init_kwargs)
-
-        return_cached_folder = kwargs.pop("return_cached_folder", False)
-        if return_cached_folder:
-            message = f"Passing `return_cached_folder=True` is deprecated and will be removed in `diffusers=0.18.0`. Please do the following instead: \n 1. Load the cached_folder via `cached_folder={cls}.download({pretrained_model_name_or_path})`. \n 2. Load the pipeline by loading from the cached folder: `pipeline={cls}.from_pretrained(cached_folder)`."
-            deprecate("return_cached_folder", "0.18.0", message)
-            return model, cached_folder
-
         return model
 
     @classmethod
@@ -1254,7 +1247,7 @@ class DiffusionPipeline(ConfigMixin):
             # if the whole pipeline is cached we don't have to ping the Hub
             if revision in DEPRECATED_REVISION_ARGS and version.parse(
                 version.parse(__version__).base_version
-            ) >= version.parse("0.18.0"):
+            ) >= version.parse("0.20.0"):
                 warn_deprecated_model_variant(
                     pretrained_model_name, use_auth_token, variant, revision, model_filenames
                 )

src/diffusers/utils/hub_utils.py

@@ -280,7 +280,7 @@ def _get_model_file(
         if (
             revision in DEPRECATED_REVISION_ARGS
             and (weights_name == WEIGHTS_NAME or weights_name == SAFETENSORS_WEIGHTS_NAME)
-            and version.parse(version.parse(__version__).base_version) >= version.parse("0.18.0")
+            and version.parse(version.parse(__version__).base_version) >= version.parse("0.20.0")
         ):
             try:
                 model_file = hf_hub_download(

tests/pipelines/test_pipelines.py

@@ -244,27 +244,6 @@ class DownloadTests(unittest.TestCase):
                     use_safetensors=True,
                 )
 
-    def test_returned_cached_folder(self):
-        prompt = "hello"
-        pipe = StableDiffusionPipeline.from_pretrained(
-            "hf-internal-testing/tiny-stable-diffusion-torch", safety_checker=None
-        )
-        _, local_path = StableDiffusionPipeline.from_pretrained(
-            "hf-internal-testing/tiny-stable-diffusion-torch", safety_checker=None, return_cached_folder=True
-        )
-        pipe_2 = StableDiffusionPipeline.from_pretrained(local_path)
-
-        pipe = pipe.to(torch_device)
-        pipe_2 = pipe_2.to(torch_device)
-
-        generator = torch.manual_seed(0)
-        out = pipe(prompt, num_inference_steps=2, generator=generator, output_type="numpy").images
-
-        generator = torch.manual_seed(0)
-        out_2 = pipe_2(prompt, num_inference_steps=2, generator=generator, output_type="numpy").images
-
-        assert np.max(np.abs(out - out_2)) < 1e-3
-
     def test_download_safetensors(self):
         with tempfile.TemporaryDirectory() as tmpdirname:
             # pipeline has Flax weights