Make sure DDPM and diffusers can be used without Transformers

src/diffusers/loaders.py

@@ -2390,7 +2390,7 @@ def unfuse_text_encoder_lora(text_encoder):
     def set_adapters_for_text_encoder(
         self,
         adapter_names: Union[List[str], str],
-        text_encoder: Optional[PreTrainedModel] = None,
+        text_encoder: Optional["PreTrainedModel"] = None,  # noqa: F821
         text_encoder_weights: List[float] = None,
     ):
         """
@@ -2429,7 +2429,7 @@ def process_weights(adapter_names, weights):
             )
         set_weights_and_activate_adapters(text_encoder, adapter_names, text_encoder_weights)
 
-    def disable_lora_for_text_encoder(self, text_encoder: Optional[PreTrainedModel] = None):
+    def disable_lora_for_text_encoder(self, text_encoder: Optional["PreTrainedModel"] = None):
         """
         Disables the LoRA layers for the text encoder.
 
@@ -2446,7 +2446,7 @@ def disable_lora_for_text_encoder(self, text_encoder: Optional[PreTrainedModel]
             raise ValueError("Text Encoder not found.")
         set_adapter_layers(text_encoder, enabled=False)
 
-    def enable_lora_for_text_encoder(self, text_encoder: Optional[PreTrainedModel] = None):
+    def enable_lora_for_text_encoder(self, text_encoder: Optional["PreTrainedModel"] = None):
         """
         Enables the LoRA layers for the text encoder.
 

src/diffusers/models/lora.py

@@ -18,14 +18,15 @@
 import torch.nn.functional as F
 from torch import nn
 
-from ..loaders import PatchedLoraProjection, text_encoder_attn_modules, text_encoder_mlp_modules
 from ..utils import logging
 
 
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 
 def adjust_lora_scale_text_encoder(text_encoder, lora_scale: float = 1.0):
+    from ..loaders import PatchedLoraProjection, text_encoder_attn_modules, text_encoder_mlp_modules
+
     for _, attn_module in text_encoder_attn_modules(text_encoder):
         if isinstance(attn_module.q_proj, PatchedLoraProjection):
             attn_module.q_proj.lora_scale = lora_scale

src/diffusers/pipelines/latent_consistency_models/__init__.py

@@ -1,19 +1,40 @@
 from typing import TYPE_CHECKING
 
 from ...utils import (
+    DIFFUSERS_SLOW_IMPORT,
+    OptionalDependencyNotAvailable,
     _LazyModule,
+    get_objects_from_module,
+    is_torch_available,
+    is_transformers_available,
 )
 
 
-_import_structure = {
-    "pipeline_latent_consistency_img2img": ["LatentConsistencyModelImg2ImgPipeline"],
-    "pipeline_latent_consistency_text2img": ["LatentConsistencyModelPipeline"],
-}
+_dummy_objects = {}
+_import_structure = {}
 
 
-if TYPE_CHECKING:
-    from .pipeline_latent_consistency_img2img import LatentConsistencyModelImg2ImgPipeline
-    from .pipeline_latent_consistency_text2img import LatentConsistencyModelPipeline
+try:
+    if not (is_transformers_available() and is_torch_available()):
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    from ...utils import dummy_torch_and_transformers_objects  # noqa F403
+
+    _dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
+else:
+    _import_structure["pipeline_latent_consistency_img2img"] = ["LatentConsistencyModelImg2ImgPipeline"]
+    _import_structure["pipeline_latent_consistency_text2img"] = ["LatentConsistencyModelPipeline"]
+
+if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
+    try:
+        if not (is_transformers_available() and is_torch_available()):
+            raise OptionalDependencyNotAvailable()
+
+    except OptionalDependencyNotAvailable:
+        from ...utils.dummy_torch_and_transformers_objects import *
+    else:
+        from .pipeline_latent_consistency_img2img import LatentConsistencyModelImg2ImgPipeline
+        from .pipeline_latent_consistency_text2img import LatentConsistencyModelPipeline
 
 else:
     import sys
@@ -24,3 +45,6 @@
         _import_structure,
         module_spec=__spec__,
     )
+
+    for name, value in _dummy_objects.items():
+        setattr(sys.modules[__name__], name, value)

src/diffusers/pipelines/pixart_alpha/__init__.py

@@ -1 +1,48 @@
-from .pipeline_pixart_alpha import PixArtAlphaPipeline
+from typing import TYPE_CHECKING
+
+from ...utils import (
+    DIFFUSERS_SLOW_IMPORT,
+    OptionalDependencyNotAvailable,
+    _LazyModule,
+    get_objects_from_module,
+    is_torch_available,
+    is_transformers_available,
+)
+
+
+_dummy_objects = {}
+_import_structure = {}
+
+
+try:
+    if not (is_transformers_available() and is_torch_available()):
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    from ...utils import dummy_torch_and_transformers_objects  # noqa F403
+
+    _dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
+else:
+    _import_structure["pipeline_pixart_alpha"] = ["PixArtAlphaPipeline"]
+
+if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
+    try:
+        if not (is_transformers_available() and is_torch_available()):
+            raise OptionalDependencyNotAvailable()
+
+    except OptionalDependencyNotAvailable:
+        from ...utils.dummy_torch_and_transformers_objects import *
+    else:
+        from .pipeline_pixart_alpha import PixArtAlphaPipeline
+
+else:
+    import sys
+
+    sys.modules[__name__] = _LazyModule(
+        __name__,
+        globals()["__file__"],
+        _import_structure,
+        module_spec=__spec__,
+    )
+
+    for name, value in _dummy_objects.items():
+        setattr(sys.modules[__name__], name, value)