[Modular] add different pipeine blocks to init (#13145)

* up

* style + copies

* fix

---------

Co-authored-by: yiyi@huggingface.co <yiyi@ip-26-0-160-103.ec2.internal>

Author: yiyixuxu

src/diffusers/__init__.py

@@ -294,10 +294,17 @@
     )
     _import_structure["modular_pipelines"].extend(
         [
+            "AutoPipelineBlocks",
             "ComponentsManager",
             "ComponentSpec",
+            "ConditionalPipelineBlocks",
+            "ConfigSpec",
+            "InputParam",
+            "LoopSequentialPipelineBlocks",
             "ModularPipeline",
             "ModularPipelineBlocks",
+            "OutputParam",
+            "SequentialPipelineBlocks",
         ]
     )
     _import_structure["optimization"] = [
@@ -1063,7 +1070,19 @@
             ZImageTransformer2DModel,
             attention_backend,
         )
-        from .modular_pipelines import ComponentsManager, ComponentSpec, ModularPipeline, ModularPipelineBlocks
+        from .modular_pipelines import (
+            AutoPipelineBlocks,
+            ComponentsManager,
+            ComponentSpec,
+            ConditionalPipelineBlocks,
+            ConfigSpec,
+            InputParam,
+            LoopSequentialPipelineBlocks,
+            ModularPipeline,
+            ModularPipelineBlocks,
+            OutputParam,
+            SequentialPipelineBlocks,
+        )
         from .optimization import (
             get_constant_schedule,
             get_constant_schedule_with_warmup,

src/diffusers/modular_pipelines/__init__.py

@@ -33,6 +33,7 @@
         "ModularPipeline",
         "AutoPipelineBlocks",
         "SequentialPipelineBlocks",
+        "ConditionalPipelineBlocks",
         "LoopSequentialPipelineBlocks",
         "PipelineState",
         "BlockState",
@@ -105,6 +106,7 @@
         from .modular_pipeline import (
             AutoPipelineBlocks,
             BlockState,
+            ConditionalPipelineBlocks,
             LoopSequentialPipelineBlocks,
             ModularPipeline,
             ModularPipelineBlocks,

src/diffusers/utils/dummy_pt_objects.py

@@ -1905,6 +1905,21 @@ def attention_backend(*args, **kwargs):
     requires_backends(attention_backend, ["torch"])
 
 
+class AutoPipelineBlocks(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+
 class ComponentsManager(metaclass=DummyObject):
     _backends = ["torch"]
 
@@ -1935,6 +1950,66 @@ def from_pretrained(cls, *args, **kwargs):
         requires_backends(cls, ["torch"])
 
 
+class ConditionalPipelineBlocks(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+
+class ConfigSpec(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+
+class InputParam(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+
+class LoopSequentialPipelineBlocks(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+
 class ModularPipeline(metaclass=DummyObject):
     _backends = ["torch"]
 
@@ -1965,6 +2040,36 @@ def from_pretrained(cls, *args, **kwargs):
         requires_backends(cls, ["torch"])
 
 
+class OutputParam(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+
+class SequentialPipelineBlocks(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+
 def get_constant_schedule(*args, **kwargs):
     requires_backends(get_constant_schedule, ["torch"])