0.20.0dev0 (#4299)

* 0.20.0dev0

* make style

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("0.19.0.dev0")
+check_min_version("0.20.0.dev0")
 
 logger = logging.getLogger(__name__)
 

examples/text_to_image/train_text_to_image_lora.py

@@ -48,7 +48,7 @@ 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("0.19.0.dev0")
+check_min_version("0.20.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

examples/textual_inversion/textual_inversion.py

@@ -78,7 +78,7 @@ else:
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.19.0.dev0")
+check_min_version("0.20.0.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("0.19.0.dev0")
+check_min_version("0.20.0.dev0")
 
 logger = logging.getLogger(__name__)
 

examples/unconditional_image_generation/train_unconditional.py

@@ -30,7 +30,7 @@ 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("0.19.0.dev0")
+check_min_version("0.20.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

setup.py

@@ -233,7 +233,7 @@ install_requires = [
 
 setup(
     name="diffusers",
-    version="0.19.0.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="0.20.0.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__ = "0.19.0.dev0"
+__version__ = "0.20.0.dev0"
 
 from .configuration_utils import ConfigMixin
 from .utils import (

src/diffusers/loaders.py

@@ -189,7 +189,7 @@ class UNet2DConditionLoadersMixin:
         r"""
         Load pretrained attention processor layers into [`UNet2DConditionModel`]. Attention processor layers have to be
         defined in
-        [`cross_attention.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py)
+        [`attention_processor.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py)
         and be a `torch.nn.Module` class.
 
         Parameters:
@@ -444,7 +444,6 @@ class UNet2DConditionLoadersMixin:
         weight_name: str = None,
         save_function: Callable = None,
         safe_serialization: bool = False,
-        **kwargs,
     ):
         r"""
         Save an attention processor to a directory so that it can be reloaded using the
@@ -468,12 +467,6 @@ class UNet2DConditionLoadersMixin:
             CustomDiffusionXFormersAttnProcessor,
         )
 
-        weight_name = weight_name or deprecate(
-            "weights_name",
-            "0.20.0",
-            "`weights_name` is deprecated, please use `weight_name` instead.",
-            take_from=kwargs,
-        )
         if os.path.isfile(save_directory):
             logger.error(f"Provided path ({save_directory}) should be a directory, not a file")
             return

src/diffusers/models/cross_attention.py

-# Copyright 2023 The HuggingFace Team. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-from ..utils import deprecate
-from .attention_processor import (  # noqa: F401
-    Attention,
-    AttentionProcessor,
-    AttnAddedKVProcessor,
-    AttnProcessor2_0,
-    LoRAAttnProcessor,
-    LoRALinearLayer,
-    LoRAXFormersAttnProcessor,
-    SlicedAttnAddedKVProcessor,
-    SlicedAttnProcessor,
-    XFormersAttnProcessor,
-)
-from .attention_processor import AttnProcessor as AttnProcessorRename  # noqa: F401
-
-
-deprecate(
-    "cross_attention",
-    "0.20.0",
-    "Importing from cross_attention is deprecated. Please import from diffusers.models.attention_processor instead.",
-    standard_warn=False,
-)
-
-
-AttnProcessor = AttentionProcessor
-
-
-class CrossAttention(Attention):
-    def __init__(self, *args, **kwargs):
-        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 `0.20.0`. 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 `0.20.0`. 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 `0.20.0`. 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 `0.20.0`. 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 `0.20.0`. 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 `0.20.0`. 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 `0.20.0`. 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/alt_diffusion/pipeline_alt_diffusion.py

@@ -585,7 +585,7 @@ class AltDiffusionPipeline(DiffusionPipeline, TextualInversionLoaderMixin, LoraL
                 every step.
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the [`AttentionProcessor`] as defined in
-                [`self.processor`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [`self.processor`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
             guidance_rescale (`float`, *optional*, defaults to 0.7):
                 Guidance rescale factor from [Common Diffusion Noise Schedules and Sample Steps are
                 Flawed](https://arxiv.org/pdf/2305.08891.pdf). Guidance rescale factor should fix overexposure when

src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion_img2img.py

@@ -634,7 +634,7 @@ class AltDiffusionImg2ImgPipeline(
                 every step.
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the [`AttentionProcessor`] as defined in
-                [`self.processor`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [`self.processor`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
 
         Examples:
 

src/diffusers/pipelines/audioldm/pipeline_audioldm.py

@@ -428,7 +428,7 @@ class AudioLDMPipeline(DiffusionPipeline):
                 every step.
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the [`AttentionProcessor`] as defined in
-                [`self.processor`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [`self.processor`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
             output_type (`str`, *optional*, defaults to `"np"`):
                 The output format of the generated image. Choose between `"np"` to return a NumPy `np.ndarray` or
                 `"pt"` to return a PyTorch `torch.Tensor` object.

src/diffusers/pipelines/controlnet/pipeline_controlnet.py

@@ -760,7 +760,7 @@ class StableDiffusionControlNetPipeline(
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
                 `self.processor` in
-                [diffusers.cross_attention](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [diffusers.models.attention_processor](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
             controlnet_conditioning_scale (`float` or `List[float]`, *optional*, defaults to 1.0):
                 The outputs of the controlnet are multiplied by `controlnet_conditioning_scale` before they are added
                 to the residual in the original unet. If multiple ControlNets are specified in init, you can set the

src/diffusers/pipelines/controlnet/pipeline_controlnet_img2img.py

@@ -851,7 +851,7 @@ class StableDiffusionControlNetImg2ImgPipeline(
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
                 `self.processor` in
-                [diffusers.cross_attention](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [diffusers.models.attention_processor](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
             controlnet_conditioning_scale (`float` or `List[float]`, *optional*, defaults to 1.0):
                 The outputs of the controlnet are multiplied by `controlnet_conditioning_scale` before they are added
                 to the residual in the original unet. If multiple ControlNets are specified in init, you can set the

src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py

@@ -1048,7 +1048,7 @@ class StableDiffusionControlNetInpaintPipeline(
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
                 `self.processor` in
-                [diffusers.cross_attention](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [diffusers.models.attention_processor](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
             controlnet_conditioning_scale (`float` or `List[float]`, *optional*, defaults to 0.5):
                 The outputs of the controlnet are multiplied by `controlnet_conditioning_scale` before they are added
                 to the residual in the original unet. If multiple ControlNets are specified in init, you can set the

src/diffusers/pipelines/controlnet/pipeline_controlnet_sd_xl.py

@@ -741,7 +741,7 @@ class StableDiffusionXLControlNetPipeline(DiffusionPipeline, TextualInversionLoa
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
                 `self.processor` in
-                [diffusers.cross_attention](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [diffusers.models.attention_processor](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
             controlnet_conditioning_scale (`float` or `List[float]`, *optional*, defaults to 1.0):
                 The outputs of the controlnet are multiplied by `controlnet_conditioning_scale` before they are added
                 to the residual in the original unet. If multiple ControlNets are specified in init, you can set the

src/diffusers/pipelines/deepfloyd_if/pipeline_if.py

@@ -662,7 +662,7 @@ class IFPipeline(DiffusionPipeline, LoraLoaderMixin):
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
                 `self.processor` in
-                [diffusers.cross_attention](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [diffusers.models.attention_processor](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
 
         Examples:
 

src/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img.py

@@ -783,7 +783,7 @@ class IFImg2ImgPipeline(DiffusionPipeline, LoraLoaderMixin):
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
                 `self.processor` in
-                [diffusers.cross_attention](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [diffusers.models.attention_processor](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
 
         Examples:
 

src/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img_superresolution.py

@@ -865,7 +865,7 @@ class IFImg2ImgSuperResolutionPipeline(DiffusionPipeline, LoraLoaderMixin):
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
                 `self.processor` in
-                [diffusers.cross_attention](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [diffusers.models.attention_processor](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
             noise_level (`int`, *optional*, defaults to 250):
                 The amount of noise to add to the upscaled image. Must be in the range `[0, 1000)`
             clean_caption (`bool`, *optional*, defaults to `True`):

src/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting.py

@@ -883,7 +883,7 @@ class IFInpaintingPipeline(DiffusionPipeline, LoraLoaderMixin):
             cross_attention_kwargs (`dict`, *optional*):
                 A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
                 `self.processor` in
-                [diffusers.cross_attention](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
+                [diffusers.models.attention_processor](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
 
         Examples: