Make repo structure consistent (#1862)

* move files a bit

* more refactors

* fix more

* more fixes

* fix more onnx

* make style

* upload

* fix

* up

* fix more

* up again

* up

* small fix

* Update src/diffusers/__init__.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* correct
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

@@ -23,7 +23,6 @@ from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
 
 from ...configuration_utils import FrozenDict
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline
 from ...schedulers import (
     DDIMScheduler,
     DPMSolverMultistepScheduler,
@@ -33,6 +32,7 @@ from ...schedulers import (
     PNDMScheduler,
 )
 from ...utils import deprecate, logging
+from ..pipeline_utils import DiffusionPipeline
 from . import StableDiffusionPipelineOutput
 from .safety_checker import StableDiffusionSafetyChecker
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_depth2img.py

@@ -26,7 +26,6 @@ from transformers import CLIPTextModel, CLIPTokenizer, DPTFeatureExtractor, DPTF
 
 from ...configuration_utils import FrozenDict
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 from ...schedulers import (
     DDIMScheduler,
     DPMSolverMultistepScheduler,
@@ -36,6 +35,7 @@ from ...schedulers import (
     PNDMScheduler,
 )
 from ...utils import PIL_INTERPOLATION, deprecate, logging
+from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 
 
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_image_variation.py

@@ -24,7 +24,6 @@ from transformers import CLIPFeatureExtractor, CLIPVisionModelWithProjection
 
 from ...configuration_utils import FrozenDict
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline
 from ...schedulers import (
     DDIMScheduler,
     DPMSolverMultistepScheduler,
@@ -34,6 +33,7 @@ from ...schedulers import (
     PNDMScheduler,
 )
 from ...utils import deprecate, logging
+from ..pipeline_utils import DiffusionPipeline
 from . import StableDiffusionPipelineOutput
 from .safety_checker import StableDiffusionSafetyChecker
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py

@@ -25,7 +25,6 @@ from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
 
 from ...configuration_utils import FrozenDict
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline
 from ...schedulers import (
     DDIMScheduler,
     DPMSolverMultistepScheduler,
@@ -35,6 +34,7 @@ from ...schedulers import (
     PNDMScheduler,
 )
 from ...utils import PIL_INTERPOLATION, deprecate, logging
+from ..pipeline_utils import DiffusionPipeline
 from . import StableDiffusionPipelineOutput
 from .safety_checker import StableDiffusionSafetyChecker
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py

@@ -25,9 +25,9 @@ from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
 
 from ...configuration_utils import FrozenDict
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline
 from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ...utils import deprecate, logging
+from ..pipeline_utils import DiffusionPipeline
 from . import StableDiffusionPipelineOutput
 from .safety_checker import StableDiffusionSafetyChecker
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py

@@ -25,7 +25,6 @@ from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
 
 from ...configuration_utils import FrozenDict
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline
 from ...schedulers import (
     DDIMScheduler,
     DPMSolverMultistepScheduler,
@@ -35,6 +34,7 @@ from ...schedulers import (
     PNDMScheduler,
 )
 from ...utils import PIL_INTERPOLATION, deprecate, logging
+from ..pipeline_utils import DiffusionPipeline
 from . import StableDiffusionPipelineOutput
 from .safety_checker import StableDiffusionSafetyChecker
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_k_diffusion.py

@@ -19,7 +19,7 @@ import torch
 
 from k_diffusion.external import CompVisDenoiser, CompVisVDenoiser
 
-from ... import DiffusionPipeline
+from ...pipelines import DiffusionPipeline
 from ...schedulers import LMSDiscreteScheduler
 from ...utils import is_accelerate_available, logging
 from . import StableDiffusionPipelineOutput

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py

@@ -23,9 +23,9 @@ from diffusers.utils import is_accelerate_available
 from transformers import CLIPTextModel, CLIPTokenizer
 
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 from ...schedulers import DDIMScheduler, DDPMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ...utils import logging
+from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 
 
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name

src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py

@@ -10,7 +10,6 @@ from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
 
 from ...configuration_utils import FrozenDict
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline
 from ...schedulers import (
     DDIMScheduler,
     DPMSolverMultistepScheduler,
@@ -20,6 +19,7 @@ from ...schedulers import (
     PNDMScheduler,
 )
 from ...utils import deprecate, is_accelerate_available, logging
+from ..pipeline_utils import DiffusionPipeline
 from . import StableDiffusionSafePipelineOutput
 from .safety_checker import SafeStableDiffusionSafetyChecker
 

src/diffusers/pipelines/stochastic_karras_ve/pipeline_stochastic_karras_ve.py

@@ -17,8 +17,8 @@ from typing import List, Optional, Tuple, Union
 import torch
 
 from ...models import UNet2DModel
-from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 from ...schedulers import KarrasVeScheduler
+from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 
 
 class KarrasVePipeline(DiffusionPipeline):
@@ -68,12 +68,11 @@ class KarrasVePipeline(DiffusionPipeline):
                 The output format of the generate image. Choose between
                 [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
             return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`~pipeline_utils.ImagePipelineOutput`] instead of a plain tuple.
+                Whether or not to return a [`~pipelines.ImagePipelineOutput`] instead of a plain tuple.
 
         Returns:
-            [`~pipeline_utils.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.
+            [`~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.
         """
 
         img_size = self.unet.config.sample_size

src/diffusers/pipelines/unclip/pipeline_unclip.py

@@ -18,11 +18,11 @@ from typing import List, Optional, Union
 import torch
 from torch.nn import functional as F
 
-from diffusers import PriorTransformer, UNet2DConditionModel, UNet2DModel
-from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
-from diffusers.schedulers import UnCLIPScheduler
 from transformers import CLIPTextModelWithProjection, CLIPTokenizer
 
+from ...models import PriorTransformer, UNet2DConditionModel, UNet2DModel
+from ...pipelines import DiffusionPipeline, ImagePipelineOutput
+from ...schedulers import UnCLIPScheduler
 from ...utils import is_accelerate_available, logging
 from .text_proj import UnCLIPTextProjModel
 
@@ -291,7 +291,7 @@ class UnCLIPPipeline(DiffusionPipeline):
                 The output format of the generated image. Choose between
                 [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
             return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`~pipeline_utils.ImagePipelineOutput`] instead of a plain tuple.
+                Whether or not to return a [`~pipelines.ImagePipelineOutput`] instead of a plain tuple.
         """
         if isinstance(prompt, str):
             batch_size = 1

src/diffusers/pipelines/unclip/pipeline_unclip_image_variation.py

@@ -19,9 +19,6 @@ import torch
 from torch.nn import functional as F
 
 import PIL
-from diffusers import UNet2DConditionModel, UNet2DModel
-from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
-from diffusers.schedulers import UnCLIPScheduler
 from transformers import (
     CLIPFeatureExtractor,
     CLIPTextModelWithProjection,
@@ -29,6 +26,9 @@ from transformers import (
     CLIPVisionModelWithProjection,
 )
 
+from ...models import UNet2DConditionModel, UNet2DModel
+from ...pipelines import DiffusionPipeline, ImagePipelineOutput
+from ...schedulers import UnCLIPScheduler
 from ...utils import is_accelerate_available, logging
 from .text_proj import UnCLIPTextProjModel
 
@@ -303,7 +303,7 @@ class UnCLIPImageVariationPipeline(DiffusionPipeline):
                 The output format of the generated image. Choose between
                 [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
             return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`~pipeline_utils.ImagePipelineOutput`] instead of a plain tuple.
+                Whether or not to return a [`~pipelines.ImagePipelineOutput`] instead of a plain tuple.
         """
         if isinstance(image, PIL.Image.Image):
             batch_size = 1

src/diffusers/pipelines/unclip/text_proj.py

@@ -15,9 +15,8 @@
 import torch
 from torch import nn
 
-from diffusers.modeling_utils import ModelMixin
-
 from ...configuration_utils import ConfigMixin, register_to_config
+from ...models import ModelMixin
 
 
 class UnCLIPTextProjModel(ModelMixin, ConfigMixin):

src/diffusers/pipelines/versatile_diffusion/modeling_text_unet.py

@@ -5,7 +5,7 @@ import torch
 import torch.nn as nn
 
 from ...configuration_utils import ConfigMixin, register_to_config
-from ...modeling_utils import ModelMixin
+from ...models import ModelMixin
 from ...models.attention import CrossAttention, DualTransformer2DModel, Transformer2DModel
 from ...models.cross_attention import AttnProcessor, CrossAttnAddedKVProcessor
 from ...models.embeddings import TimestepEmbedding, Timesteps

src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion.py

@@ -7,9 +7,9 @@ import PIL.Image
 from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer, CLIPVisionModel
 
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline
 from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ...utils import logging
+from ..pipeline_utils import DiffusionPipeline
 from .pipeline_versatile_diffusion_dual_guided import VersatileDiffusionDualGuidedPipeline
 from .pipeline_versatile_diffusion_image_variation import VersatileDiffusionImageVariationPipeline
 from .pipeline_versatile_diffusion_text_to_image import VersatileDiffusionTextToImagePipeline

src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_dual_guided.py

@@ -27,11 +27,10 @@ from transformers import (
     CLIPVisionModelWithProjection,
 )
 
-from ...models import AutoencoderKL, UNet2DConditionModel
-from ...models.attention import DualTransformer2DModel, Transformer2DModel
-from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
+from ...models import AutoencoderKL, DualTransformer2DModel, Transformer2DModel, UNet2DConditionModel
 from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ...utils import is_accelerate_available, logging
+from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 from .modeling_text_unet import UNetFlatConditionModel
 
 

src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_image_variation.py

@@ -23,9 +23,9 @@ import PIL
 from transformers import CLIPFeatureExtractor, CLIPVisionModelWithProjection
 
 from ...models import AutoencoderKL, UNet2DConditionModel
-from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ...utils import is_accelerate_available, logging
+from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 
 
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name

src/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py

@@ -20,11 +20,10 @@ import torch.utils.checkpoint
 
 from transformers import CLIPFeatureExtractor, CLIPTextModelWithProjection, CLIPTokenizer
 
-from ...models import AutoencoderKL, UNet2DConditionModel
-from ...models.attention import Transformer2DModel
-from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
+from ...models import AutoencoderKL, Transformer2DModel, UNet2DConditionModel
 from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ...utils import is_accelerate_available, logging
+from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 from .modeling_text_unet import UNetFlatConditionModel
 
 

src/diffusers/pipelines/vq_diffusion/pipeline_vq_diffusion.py

@@ -16,14 +16,13 @@ from typing import Callable, List, Optional, Tuple, Union
 
 import torch
 
-from diffusers import Transformer2DModel, VQModel
-from diffusers.schedulers.scheduling_vq_diffusion import VQDiffusionScheduler
 from transformers import CLIPTextModel, CLIPTokenizer
 
 from ...configuration_utils import ConfigMixin, register_to_config
-from ...modeling_utils import ModelMixin
-from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
+from ...models import ModelMixin, Transformer2DModel, VQModel
+from ...schedulers import VQDiffusionScheduler
 from ...utils import logging
+from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
 
 
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
@@ -212,7 +211,7 @@ class VQDiffusionPipeline(DiffusionPipeline):
                 The output format of the generated image. Choose between
                 [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
             return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`~pipeline_utils.ImagePipelineOutput`] instead of a plain tuple.
+                Whether or not to return a [`~pipelines.ImagePipelineOutput`] instead of a plain tuple.
             callback (`Callable`, *optional*):
                 A function that will be called every `callback_steps` steps during inference. The function will be
                 called with the following arguments: `callback(step: int, timestep: int, latents: torch.FloatTensor)`.
@@ -221,9 +220,8 @@ class VQDiffusionPipeline(DiffusionPipeline):
                 called at every step.
 
         Returns:
-            [`~pipeline_utils.ImagePipelineOutput`] or `tuple`: [`~ pipeline_utils.ImagePipelineOutput `] if
-            `return_dict` is True, otherwise a `tuple. When returning a tuple, the first element is a list with the
-            generated images.
+            [`~pipelines.ImagePipelineOutput`] or `tuple`: [`~ pipeline_utils.ImagePipelineOutput `] if `return_dict`
+            is True, otherwise a `tuple. When returning a tuple, the first element is a list with the generated images.
         """
         if isinstance(prompt, str):
             batch_size = 1

src/diffusers/utils/__init__.py

@@ -18,7 +18,22 @@ import os
 from packaging import version
 
 from .. import __version__
+from .constants import (
+    _COMPATIBLE_STABLE_DIFFUSION_SCHEDULERS,
+    CONFIG_NAME,
+    DIFFUSERS_CACHE,
+    DIFFUSERS_DYNAMIC_MODULE_NAME,
+    FLAX_WEIGHTS_NAME,
+    HF_MODULES_CACHE,
+    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
+    ONNX_EXTERNAL_WEIGHTS_NAME,
+    ONNX_WEIGHTS_NAME,
+    SAFETENSORS_WEIGHTS_NAME,
+    WEIGHTS_NAME,
+)
 from .deprecation_utils import deprecate
+from .dynamic_modules_utils import get_class_from_dynamic_module
+from .hub_utils import HF_HUB_OFFLINE, http_user_agent
 from .import_utils import (
     ENV_VARS_TRUE_AND_AUTO_VALUES,
     ENV_VARS_TRUE_VALUES,
@@ -67,36 +82,6 @@ if is_torch_available():
 logger = get_logger(__name__)
 
 
-hf_cache_home = os.path.expanduser(
-    os.getenv("HF_HOME", os.path.join(os.getenv("XDG_CACHE_HOME", "~/.cache"), "huggingface"))
-)
-default_cache_path = os.path.join(hf_cache_home, "diffusers")
-
-
-CONFIG_NAME = "config.json"
-WEIGHTS_NAME = "diffusion_pytorch_model.bin"
-FLAX_WEIGHTS_NAME = "diffusion_flax_model.msgpack"
-ONNX_WEIGHTS_NAME = "model.onnx"
-SAFETENSORS_WEIGHTS_NAME = "diffusion_pytorch_model.safetensors"
-ONNX_EXTERNAL_WEIGHTS_NAME = "weights.pb"
-HUGGINGFACE_CO_RESOLVE_ENDPOINT = "https://huggingface.co"
-DIFFUSERS_CACHE = default_cache_path
-DIFFUSERS_DYNAMIC_MODULE_NAME = "diffusers_modules"
-HF_MODULES_CACHE = os.getenv("HF_MODULES_CACHE", os.path.join(hf_cache_home, "modules"))
-
-_COMPATIBLE_STABLE_DIFFUSION_SCHEDULERS = [
-    "DDIMScheduler",
-    "DDPMScheduler",
-    "PNDMScheduler",
-    "LMSDiscreteScheduler",
-    "EulerDiscreteScheduler",
-    "HeunDiscreteScheduler",
-    "EulerAncestralDiscreteScheduler",
-    "DPMSolverMultistepScheduler",
-    "DPMSolverSinglestepScheduler",
-]
-
-
 def check_min_version(min_version):
     if version.parse(__version__) < version.parse(min_version):
         if "dev" in min_version: