fix importing diffusers without transformers installed

src/diffusers/__init__.py

@@ -178,10 +178,10 @@ else:
     from .pipelines import AudioDiffusionPipeline, Mel
 
 try:
-    if not (is_torch_available() and is_note_seq_available()):
+    if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
         raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
-    from .utils.dummy_torch_and_note_seq_objects import *  # noqa F403
+    from .utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
 else:
     from .pipelines import SpectrogramDiffusionPipeline
 

src/diffusers/loaders.py

@@ -306,7 +306,7 @@ class TextualInversionLoaderMixin:
     Mixin class for loading textual inversion tokens and embeddings to the tokenizer and text encoder.
     """
 
-    def maybe_convert_prompt(self, prompt: Union[str, List[str]], tokenizer: PreTrainedTokenizer):
+    def maybe_convert_prompt(self, prompt: Union[str, List[str]], tokenizer: "PreTrainedTokenizer"):
         r"""
         Maybe convert a prompt into a "multi vector"-compatible prompt. If the prompt includes a token that corresponds
         to a multi-vector textual inversion embedding, this function will process the prompt so that the special token
@@ -334,7 +334,7 @@ class TextualInversionLoaderMixin:
 
         return prompts
 
-    def _maybe_convert_prompt(self, prompt: str, tokenizer: PreTrainedTokenizer):
+    def _maybe_convert_prompt(self, prompt: str, tokenizer: "PreTrainedTokenizer"):
         r"""
         Maybe convert a prompt into a "multi vector"-compatible prompt. If the prompt includes a token that corresponds
         to a multi-vector textual inversion embedding, this function will process the prompt so that the special token

src/diffusers/pipelines/__init__.py

@@ -26,7 +26,6 @@ else:
     from .pndm import PNDMPipeline
     from .repaint import RePaintPipeline
     from .score_sde_ve import ScoreSdeVePipeline
-    from .spectrogram_diffusion import SpectrogramDiffusionPipeline
     from .stochastic_karras_ve import KarrasVePipeline
 
 try:
@@ -132,9 +131,9 @@ else:
         FlaxStableDiffusionPipeline,
     )
 try:
-    if not (is_note_seq_available()):
+    if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
         raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
-    from ..utils.dummy_note_seq_objects import *  # noqa F403
+    from ..utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
 else:
-    from .spectrogram_diffusion import MidiProcessor
+    from .spectrogram_diffusion import SpectrogramDiffusionPipeline

src/diffusers/pipelines/spectrogram_diffusion/__init__.py

 # flake8: noqa
-from ...utils import is_note_seq_available
+from ...utils import is_note_seq_available, is_transformers_available
+from ...utils import OptionalDependencyNotAvailable
 
-from .notes_encoder import SpectrogramNotesEncoder
-from .continous_encoder import SpectrogramContEncoder
-from .pipeline_spectrogram_diffusion import (
+
+try:
+    if not (is_transformers_available() and is_torch_available()):
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
+else:
+    from .notes_encoder import SpectrogramNotesEncoder
+    from .continous_encoder import SpectrogramContEncoder
+    from .pipeline_spectrogram_diffusion import (
         SpectrogramContEncoder,
         SpectrogramDiffusionPipeline,
         T5FilmDecoder,
-)
+    )
 
-if is_note_seq_available():
+try:
+    if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    from ...utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
+else:
     from .midi_utils import MidiProcessor

src/diffusers/utils/dummy_torch_and_note_seq_objects.py → src/diffusers/utils/dummy_transformers_and_torch_and_note_seq_objects.py

@@ -3,15 +3,15 @@ from ..utils import DummyObject, requires_backends
 
 
 class SpectrogramDiffusionPipeline(metaclass=DummyObject):
-    _backends = ["torch", "note_seq"]
+    _backends = ["transformers", "torch", "note_seq"]
 
     def __init__(self, *args, **kwargs):
-        requires_backends(self, ["torch", "note_seq"])
+        requires_backends(self, ["transformers", "torch", "note_seq"])
 
     @classmethod
     def from_config(cls, *args, **kwargs):
-        requires_backends(cls, ["torch", "note_seq"])
+        requires_backends(cls, ["transformers", "torch", "note_seq"])
 
     @classmethod
     def from_pretrained(cls, *args, **kwargs):
-        requires_backends(cls, ["torch", "note_seq"])
+        requires_backends(cls, ["transformers", "torch", "note_seq"])