remove redundant imports & make fix-copies

Author: ChrisLiu6

src/diffusers/models/transformers/transformer_z_image.py

@@ -20,23 +20,16 @@
 import torch.nn.functional as F
 from torch.nn.utils.rnn import pad_sequence
 
+from diffusers.models.normalization import RMSNorm
+
 from ...configuration_utils import ConfigMixin, register_to_config
 from ...loaders import FromOriginalModelMixin, PeftAdapterMixin
 from ...models.attention_processor import Attention
 from ...models.modeling_utils import ModelMixin
-from ...utils.import_utils import is_flash_attn_available
 from ...utils.torch_utils import maybe_allow_in_graph
 from ..attention_dispatch import dispatch_attention_fn
 
 
-if is_flash_attn_available():
-    from flash_attn import flash_attn_varlen_func
-else:
-    flash_attn_varlen_func = None
-
-from diffusers.models.normalization import RMSNorm
-
-
 ADALN_EMBED_DIM = 256
 SEQ_MULTI_OF = 32
 

src/diffusers/utils/dummy_torch_and_transformers_objects.py

@@ -3645,3 +3645,18 @@ def from_config(cls, *args, **kwargs):
     @classmethod
     def from_pretrained(cls, *args, **kwargs):
         requires_backends(cls, ["torch", "transformers"])
+
+
+class ZImagePipeline(metaclass=DummyObject):
+    _backends = ["torch", "transformers"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch", "transformers"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])