[Bump version] 0.13.0dev0 & Deprecate predict_epsilon (huggingface#…

…2109)

* [Bump version] 0.13

* Bump model up

* up

examples/community/imagic_stable_diffusion.py

@@ -185,7 +185,7 @@ def train(
             (nsfw) content, according to the `safety_checker`.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         accelerator = Accelerator(

examples/community/lpw_stable_diffusion.py

@@ -759,7 +759,7 @@ def __call__(
             (nsfw) content, according to the `safety_checker`.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         # 0. Default height and width to unet

examples/community/lpw_stable_diffusion_onnx.py

@@ -745,7 +745,7 @@ def __call__(
             (nsfw) content, according to the `safety_checker`.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         # 0. Default height and width to unet

examples/dreambooth/train_dreambooth.py

@@ -46,7 +46,7 @@
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.dev0")
 
 logger = get_logger(__name__)
 

examples/dreambooth/train_dreambooth_flax.py

@@ -36,7 +36,7 @@
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.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

@@ -54,7 +54,7 @@
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.dev0")
 
 logger = get_logger(__name__)
 

examples/text_to_image/train_text_to_image.py

@@ -45,7 +45,7 @@
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

examples/text_to_image/train_text_to_image_flax.py

@@ -34,7 +34,7 @@
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.dev0")
 
 logger = logging.getLogger(__name__)
 

examples/text_to_image/train_text_to_image_lora.py

@@ -47,7 +47,7 @@
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

examples/textual_inversion/textual_inversion.py

@@ -68,7 +68,7 @@
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.dev0")
 
 logger = get_logger(__name__)
 

examples/textual_inversion/textual_inversion_flax.py

@@ -57,7 +57,7 @@
 # ------------------------------------------------------------------------------
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.dev0")
 
 logger = logging.getLogger(__name__)
 

examples/unconditional_image_generation/train_unconditional.py

@@ -33,7 +33,7 @@
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

examples/unconditional_image_generation/train_unconditional_ort.py

@@ -30,7 +30,7 @@
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.12.0")
+check_min_version("0.13.0.dev0")
 
 logger = get_logger(__name__)
 

setup.py

@@ -219,7 +219,7 @@ def run(self):
 
 setup(
     name="diffusers",
-    version="0.12.0",  # 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="0.13.0.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

@@ -1,4 +1,4 @@
-__version__ = "0.12.0"
+__version__ = "0.13.0.dev0"
 
 from .configuration_utils import ConfigMixin
 from .utils import (

src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion_img2img.py

@@ -606,7 +606,7 @@ def __call__(
             (nsfw) content, according to the `safety_checker`.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         # 1. Check inputs. Raise error if not correct

src/diffusers/pipelines/ddpm/pipeline_ddpm.py

@@ -17,8 +17,7 @@
 
 import torch
 
-from ...configuration_utils import FrozenDict
-from ...utils import deprecate, randn_tensor
+from ...utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 
 
@@ -46,7 +45,6 @@ def __call__(
         num_inference_steps: int = 1000,
         output_type: Optional[str] = "pil",
         return_dict: bool = True,
-        **kwargs,
     ) -> Union[ImagePipelineOutput, Tuple]:
         r"""
         Args:
@@ -68,30 +66,6 @@ def __call__(
             [`~pipelines.ImagePipelineOutput`] or `tuple`: [`~pipelines.utils.ImagePipelineOutput`] if `return_dict` is
             True, otherwise a `tuple. When returning a tuple, the first element is a list with the generated images.
         """
-        message = (
-            "Please make sure to instantiate your scheduler with `prediction_type` instead. E.g. `scheduler ="
-            " DDPMScheduler.from_pretrained(<model_id>, prediction_type='epsilon')`."
-        )
-        predict_epsilon = deprecate("predict_epsilon", "0.13.0", message, take_from=kwargs)
-
-        if predict_epsilon is not None:
-            new_config = dict(self.scheduler.config)
-            new_config["prediction_type"] = "epsilon" if predict_epsilon else "sample"
-            self.scheduler._internal_dict = FrozenDict(new_config)
-
-        if generator is not None and generator.device.type != self.device.type and self.device.type != "mps":
-            message = (
-                f"The `generator` device is `{generator.device}` and does not match the pipeline "
-                f"device `{self.device}`, so the `generator` will be ignored. "
-                f'Please use `torch.Generator(device="{self.device}")` instead.'
-            )
-            deprecate(
-                "generator.device == 'cpu'",
-                "0.13.0",
-                message,
-            )
-            generator = None
-
         # Sample gaussian noise to begin loop
         if isinstance(self.unet.sample_size, int):
             image_shape = (batch_size, self.unet.in_channels, self.unet.sample_size, self.unet.sample_size)

src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py

@@ -102,7 +102,7 @@ def __call__(
             True, otherwise a `tuple. When returning a tuple, the first element is a list with the generated images.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         if isinstance(image, PIL.Image.Image):

src/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.py

@@ -623,7 +623,7 @@ def __call__(
             (nsfw) content, according to the `safety_checker`.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         # 1. Check inputs

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_img2img.py

@@ -311,7 +311,7 @@ def __call__(
             (nsfw) content, according to the `safety_checker`.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         if isinstance(prompt, str):

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_inpaint_legacy.py

@@ -303,7 +303,7 @@ def __call__(
             (nsfw) content, according to the `safety_checker`.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         if isinstance(prompt, str):

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py

@@ -616,7 +616,7 @@ def __call__(
             (nsfw) content, according to the `safety_checker`.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         # 1. Check inputs. Raise error if not correct

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py

@@ -556,7 +556,7 @@ def __call__(
             (nsfw) content, according to the `safety_checker`.
         """
         message = "Please use `image` instead of `init_image`."
-        init_image = deprecate("init_image", "0.13.0", message, take_from=kwargs)
+        init_image = deprecate("init_image", "0.14.0", message, take_from=kwargs)
         image = init_image or image
 
         # 1. Check inputs

src/diffusers/schedulers/scheduling_ddim.py

@@ -23,7 +23,7 @@
 import torch
 
 from ..configuration_utils import ConfigMixin, register_to_config
-from ..utils import BaseOutput, deprecate, randn_tensor
+from ..utils import BaseOutput, randn_tensor
 from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
 
 
@@ -113,7 +113,6 @@ class DDIMScheduler(SchedulerMixin, ConfigMixin):
     """
 
     _compatibles = [e.name for e in KarrasDiffusionSchedulers]
-    _deprecated_kwargs = ["predict_epsilon"]
     order = 1
 
     @register_to_config
@@ -128,16 +127,7 @@ def __init__(
         set_alpha_to_one: bool = True,
         steps_offset: int = 0,
         prediction_type: str = "epsilon",
-        **kwargs,
     ):
-        message = (
-            "Please make sure to instantiate your scheduler with `prediction_type` instead. E.g. `scheduler ="
-            " DDIMScheduler.from_pretrained(<model_id>, prediction_type='epsilon')`."
-        )
-        predict_epsilon = deprecate("predict_epsilon", "0.13.0", message, take_from=kwargs)
-        if predict_epsilon is not None:
-            self.register_to_config(prediction_type="epsilon" if predict_epsilon else "sample")
-
         if trained_betas is not None:
             self.betas = torch.tensor(trained_betas, dtype=torch.float32)
         elif beta_schedule == "linear":

src/diffusers/schedulers/scheduling_ddim_flax.py

@@ -22,7 +22,6 @@
 import jax.numpy as jnp
 
 from ..configuration_utils import ConfigMixin, register_to_config
-from ..utils import deprecate
 from .scheduling_utils_flax import (
     CommonSchedulerState,
     FlaxKarrasDiffusionSchedulers,
@@ -103,7 +102,6 @@ class FlaxDDIMScheduler(FlaxSchedulerMixin, ConfigMixin):
     """
 
     _compatibles = [e.name for e in FlaxKarrasDiffusionSchedulers]
-    _deprecated_kwargs = ["predict_epsilon"]
 
     dtype: jnp.dtype
 
@@ -123,16 +121,7 @@ def __init__(
         steps_offset: int = 0,
         prediction_type: str = "epsilon",
         dtype: jnp.dtype = jnp.float32,
-        **kwargs,
     ):
-        message = (
-            "Please make sure to instantiate your scheduler with `prediction_type` instead. E.g. `scheduler ="
-            f" {self.__class__.__name__}.from_pretrained(<model_id>, prediction_type='epsilon')`."
-        )
-        predict_epsilon = deprecate("predict_epsilon", "0.13.0", message, take_from=kwargs)
-        if predict_epsilon is not None:
-            self.register_to_config(prediction_type="epsilon" if predict_epsilon else "sample")
-
         self.dtype = dtype
 
     def create_state(self, common: Optional[CommonSchedulerState] = None) -> DDIMSchedulerState:

src/diffusers/schedulers/scheduling_ddpm.py

@@ -21,8 +21,8 @@
 import numpy as np
 import torch
 
-from ..configuration_utils import ConfigMixin, FrozenDict, register_to_config
-from ..utils import BaseOutput, deprecate, randn_tensor
+from ..configuration_utils import ConfigMixin, register_to_config
+from ..utils import BaseOutput, randn_tensor
 from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
 
 
@@ -106,7 +106,6 @@ class DDPMScheduler(SchedulerMixin, ConfigMixin):
     """
 
     _compatibles = [e.name for e in KarrasDiffusionSchedulers]
-    _deprecated_kwargs = ["predict_epsilon"]
     order = 1
 
     @register_to_config
@@ -120,16 +119,7 @@ def __init__(
         variance_type: str = "fixed_small",
         clip_sample: bool = True,
         prediction_type: str = "epsilon",
-        **kwargs,
     ):
-        message = (
-            "Please make sure to instantiate your scheduler with `prediction_type` instead. E.g. `scheduler ="
-            " DDPMScheduler.from_pretrained(<model_id>, prediction_type='epsilon')`."
-        )
-        predict_epsilon = deprecate("predict_epsilon", "0.13.0", message, take_from=kwargs)
-        if predict_epsilon is not None:
-            self.register_to_config(prediction_type="epsilon" if predict_epsilon else "sample")
-
         if trained_betas is not None:
             self.betas = torch.tensor(trained_betas, dtype=torch.float32)
         elif beta_schedule == "linear":
@@ -239,7 +229,6 @@ def step(
         sample: torch.FloatTensor,
         generator=None,
         return_dict: bool = True,
-        **kwargs,
     ) -> Union[DDPMSchedulerOutput, Tuple]:
         """
         Predict the sample at the previous timestep by reversing the SDE. Core function to propagate the diffusion
@@ -259,16 +248,6 @@ def step(
             returning a tuple, the first element is the sample tensor.
 
         """
-        message = (
-            "Please make sure to instantiate your scheduler with `prediction_type` instead. E.g. `scheduler ="
-            " DDPMScheduler.from_pretrained(<model_id>, prediction_type='epsilon')`."
-        )
-        predict_epsilon = deprecate("predict_epsilon", "0.13.0", message, take_from=kwargs)
-        if predict_epsilon is not None:
-            new_config = dict(self.config)
-            new_config["prediction_type"] = "epsilon" if predict_epsilon else "sample"
-            self._internal_dict = FrozenDict(new_config)
-
         t = timestep
 
         if model_output.shape[1] == sample.shape[1] * 2 and self.variance_type in ["learned", "learned_range"]: