Updated

Author: SahilCarterr

src/diffusers/pipelines/bria/__init__.py

@@ -12,7 +12,7 @@
 
 _dummy_objects = {}
 _additional_imports = {}
-#_import_structure = {"pipeline_output": ["FluxPipelineOutput", "FluxPriorReduxPipelineOutput"]}
+_import_structure = {"pipeline_output": ["BriaPipelineOutput"]}
 
 try:
     if not (is_transformers_available() and is_torch_available()):

src/diffusers/pipelines/bria/pipeline_bria.py

@@ -11,7 +11,7 @@
 from ...loaders import FluxLoraLoaderMixin
 from ...models import AutoencoderKL, BriaTransformer2DModel
 from ...pipelines.flux.pipeline_flux import FluxPipeline, calculate_shift, retrieve_timesteps
-from ...pipelines.flux.pipeline_output import FluxPipelineOutput
+from .pipeline_output import BriaPipelineOutput
 from ...schedulers import (
     DDIMScheduler,
     EulerAncestralDiscreteScheduler,

src/diffusers/pipelines/bria/pipeline_output.py

@@ -0,0 +1,22 @@
+from dataclasses import dataclass
+from typing import List, Union
+
+import numpy as np
+import PIL.Image
+import torch
+
+from ...utils import BaseOutput
+
+
+@dataclass
+class BriaPipelineOutput(BaseOutput):
+    """
+    Output class for Stable Diffusion pipelines.
+
+    Args:
+        images (`List[PIL.Image.Image]` or `np.ndarray`)
+            List of denoised PIL images of length `batch_size` or numpy array of shape `(batch_size, height, width,
+            num_channels)`. PIL images or numpy array present the denoised images of the diffusion pipeline.
+    """
+
+    images: Union[List[PIL.Image.Image], np.ndarray]