[Bad dependencies] Fix imports (#1382)

* fix imports

* better error

* up

* finish

src/diffusers/pipelines/stable_diffusion/__init__.py

@@ -6,7 +6,14 @@ import numpy as np
 import PIL
 from PIL import Image
 
-from ...utils import BaseOutput, is_flax_available, is_onnx_available, is_torch_available, is_transformers_available
+from ...utils import (
+    BaseOutput,
+    is_flax_available,
+    is_onnx_available,
+    is_torch_available,
+    is_transformers_available,
+    is_transformers_version,
+)
 
 
 @dataclass
@@ -30,12 +37,16 @@ class StableDiffusionPipelineOutput(BaseOutput):
 if is_transformers_available() and is_torch_available():
     from .pipeline_cycle_diffusion import CycleDiffusionPipeline
     from .pipeline_stable_diffusion import StableDiffusionPipeline
-    from .pipeline_stable_diffusion_image_variation import StableDiffusionImageVariationPipeline
     from .pipeline_stable_diffusion_img2img import StableDiffusionImg2ImgPipeline
     from .pipeline_stable_diffusion_inpaint import StableDiffusionInpaintPipeline
     from .pipeline_stable_diffusion_inpaint_legacy import StableDiffusionInpaintPipelineLegacy
     from .safety_checker import StableDiffusionSafetyChecker
 
+if is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0"):
+    from .pipeline_stable_diffusion_image_variation import StableDiffusionImageVariationPipeline
+else:
+    from ...utils.dummy_torch_and_transformers_objects import StableDiffusionImageVariationPipeline
+
 if is_transformers_available() and is_onnx_available():
     from .pipeline_onnx_stable_diffusion import OnnxStableDiffusionPipeline, StableDiffusionOnnxPipeline
     from .pipeline_onnx_stable_diffusion_img2img import OnnxStableDiffusionImg2ImgPipeline

src/diffusers/pipelines/versatile_diffusion/__init__.py

@@ -1,9 +1,16 @@
-from ...utils import is_torch_available, is_transformers_available
+from ...utils import is_torch_available, is_transformers_available, is_transformers_version
 
 
-if is_transformers_available() and is_torch_available():
+if is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0"):
     from .modeling_text_unet import UNetFlatConditionModel
     from .pipeline_versatile_diffusion import VersatileDiffusionPipeline
     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
+else:
+    from ...utils.dummy_torch_and_transformers_objects import (
+        VersatileDiffusionDualGuidedPipeline,
+        VersatileDiffusionImageVariationPipeline,
+        VersatileDiffusionPipeline,
+        VersatileDiffusionTextToImagePipeline,
+    )

src/diffusers/utils/__init__.py

@@ -33,6 +33,7 @@ from .import_utils import (
     is_torch_available,
     is_torch_version,
     is_transformers_available,
+    is_transformers_version,
     is_unidecode_available,
     requires_backends,
 )

src/diffusers/utils/import_utils.py

@@ -303,6 +303,17 @@ def requires_backends(obj, backends):
     if failed:
         raise ImportError("".join(failed))
 
+    if name in [
+        "VersatileDiffusionTextToImagePipeline",
+        "VersatileDiffusionPipeline",
+        "VersatileDiffusionDualGuidedPipeline",
+        "StableDiffusionImageVariationPipeline",
+    ] and is_transformers_version("<", "4.25.0"):
+        raise ImportError(
+            f"You need to install `transformers` from 'main' in order to use {name}: \n```\n pip install"
+            " git+https://github.com/huggingface/transformers \n```"
+        )
+
 
 class DummyObject(type):
     """
@@ -347,3 +358,17 @@ def is_torch_version(operation: str, version: str):
             A string version of PyTorch
     """
     return compare_versions(parse(_torch_version), operation, version)
+
+
+def is_transformers_version(operation: str, version: str):
+    """
+    Args:
+    Compares the current Transformers version to a given reference with an operation.
+        operation (`str`):
+            A string representation of an operator, such as `">"` or `"<="`
+        version (`str`):
+            A string version of PyTorch
+    """
+    if not _transformers_available:
+        return False
+    return compare_versions(parse(_transformers_version), operation, version)