chore: ruff format

installer/lib/messages.py

@@ -149,7 +149,7 @@ def dest_path(dest=None) -> Path:
             completer=path_completer,
             default=str(browse_start) + os.sep,
             vi_mode=True,
-            complete_while_typing=True
+            complete_while_typing=True,
             # Test that this is not needed on Windows
             # complete_style=CompleteStyle.READLINE_LIKE,
         )

invokeai/app/invocations/baseinvocation.py

@@ -661,9 +661,7 @@ def validate_fields(model_fields: dict[str, FieldInfo], model_type: str) -> None
 
         field_kind = (
             # _field_kind is defined via InputField(), OutputField() or by one of the internal fields defined in this file
-            field.json_schema_extra.get("_field_kind", None)
+            field.json_schema_extra.get("_field_kind", None) if field.json_schema_extra else None
-            if field.json_schema_extra
-            else None
         )
 
         # must have a field_kind

invokeai/app/services/image_records/image_records_common.py

@@ -90,7 +90,9 @@ class ImageRecordDeleteException(Exception):
 
 
 IMAGE_DTO_COLS = ", ".join(
-    ["images." + c for c in [
+    [
+        "images." + c
+        for c in [
             "image_name",
             "image_origin",
             "image_category",
@@ -103,7 +105,8 @@ IMAGE_DTO_COLS = ", ".join(
             "updated_at",
             "deleted_at",
             "starred",
-            ]]
+        ]
+    ]
 )
 
 

invokeai/app/services/images/images_default.py

@@ -217,13 +217,16 @@ class ImageService(ImageServiceABC):
                 board_id,
             )
 
-            image_dtos = [image_record_to_dto(
+            image_dtos = [
+                image_record_to_dto(
                     image_record=r,
                     image_url=self.__invoker.services.urls.get_image_url(r.image_name),
                     thumbnail_url=self.__invoker.services.urls.get_image_url(r.image_name, True),
                     board_id=self.__invoker.services.board_image_records.get_board_for_image(r.image_name),
                     workflow_id=self.__invoker.services.workflow_image_records.get_workflow_for_image(r.image_name),
-                    ) for r in results.items]
+                )
+                for r in results.items
+            ]
 
             return OffsetPaginatedResults[ImageDTO](
                 items=image_dtos,

invokeai/app/services/session_processor/session_processor_default.py

@@ -34,7 +34,9 @@ class DefaultSessionProcessor(SessionProcessorBase):
             name="session_processor",
             target=self.__process,
             kwargs={
-                "stop_event": self.__stop_event, "poll_now_event": self.__poll_now_event, "resume_event": self.__resume_event
+                "stop_event": self.__stop_event,
+                "poll_now_event": self.__poll_now_event,
+                "resume_event": self.__resume_event,
             },
         )
         self.__thread.start()

invokeai/app/services/shared/graph.py

@@ -1053,7 +1053,10 @@ class GraphExecutionState(BaseModel):
             # For every iterator, the parent must either not be a child of that iterator, or must match the prepared iteration for that iterator
             # TODO: Handle a node mapping to none
             eg = self.execution_graph.nx_graph_flat()
-            prepared_parent_mappings = [[(n, self._get_iteration_node(n, g, eg, it)) for n in next_node_parents] for it in iterator_node_prepared_combinations]  # type: ignore
+            prepared_parent_mappings = [
+                [(n, self._get_iteration_node(n, g, eg, it)) for n in next_node_parents]
+                for it in iterator_node_prepared_combinations
+            ]  # type: ignore
 
             # Create execution node for each iteration
             for iteration_mappings in prepared_parent_mappings:

invokeai/backend/ip_adapter/attention_processor.py

@@ -130,7 +130,9 @@ class IPAttnProcessor2_0(torch.nn.Module):
             assert ip_adapter_image_prompt_embeds is not None
             assert len(ip_adapter_image_prompt_embeds) == len(self._weights)
 
-            for ipa_embed, ipa_weights, scale in zip(ip_adapter_image_prompt_embeds, self._weights, self._scales, strict=True):
+            for ipa_embed, ipa_weights, scale in zip(
+                ip_adapter_image_prompt_embeds, self._weights, self._scales, strict=True
+            ):
                 # The batch dimensions should match.
                 assert ipa_embed.shape[0] == encoder_hidden_states.shape[0]
                 # The token_len dimensions should match.

invokeai/backend/model_management/model_cache.py

@@ -66,11 +66,13 @@ class CacheStats(object):
 
 class ModelLocker(object):
     "Forward declaration"
+
     pass
 
 
 class ModelCache(object):
     "Forward declaration"
+
     pass
 
 

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -193,6 +193,7 @@ class InvokeAIStableDiffusionPipelineOutput(StableDiffusionPipelineOutput):
         attention_map_saver (`AttentionMapSaver`): Object containing attention maps that can be displayed to the user
          after generation completes. Optional.
     """
+
     attention_map_saver: Optional[AttentionMapSaver]
 
 

invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py

@@ -642,7 +642,9 @@ class InvokeAIDiffuserComponent:
 
         deltas = None
         uncond_latents = None
-        weighted_cond_list = c_or_weighted_c_list if isinstance(c_or_weighted_c_list, list) else [(c_or_weighted_c_list, 1)]
+        weighted_cond_list = (
+            c_or_weighted_c_list if isinstance(c_or_weighted_c_list, list) else [(c_or_weighted_c_list, 1)]
+        )
 
         # below is fugly omg
         conditionings = [uc] + [c for c, weight in weighted_cond_list]

invokeai/backend/util/hotfixes.py

@@ -732,7 +732,9 @@ class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalControlnetMixin):
 
         controlnet_down_block_res_samples = ()
 
-        for down_block_res_sample, controlnet_block in zip(down_block_res_samples, self.controlnet_down_blocks, strict=True):
+        for down_block_res_sample, controlnet_block in zip(
+            down_block_res_samples, self.controlnet_down_blocks, strict=True
+        ):
             down_block_res_sample = controlnet_block(down_block_res_sample)
             controlnet_down_block_res_samples = controlnet_down_block_res_samples + (down_block_res_sample,)
 
@@ -745,7 +747,9 @@ class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalControlnetMixin):
             scales = torch.logspace(-1, 0, len(down_block_res_samples) + 1, device=sample.device)  # 0.1 to 1.0
 
             scales = scales * conditioning_scale
-            down_block_res_samples = [sample * scale for sample, scale in zip(down_block_res_samples, scales, strict=True)]
+            down_block_res_samples = [
+                sample * scale for sample, scale in zip(down_block_res_samples, scales, strict=True)
+            ]
             mid_block_res_sample = mid_block_res_sample * scales[-1]  # last one
         else:
             down_block_res_samples = [sample * conditioning_scale for sample in down_block_res_samples]

invokeai/backend/util/util.py

@@ -229,7 +229,11 @@ def rand_perlin_2d(shape, res, device, fade=lambda t: 6 * t**5 - 15 * t**4 + 10
     gradients = torch.stack((torch.cos(angles), torch.sin(angles)), dim=-1).to(device)
 
     def tile_grads(slice1, slice2):
-        return gradients[slice1[0]:slice1[1], slice2[0]:slice2[1]].repeat_interleave(d[0], 0).repeat_interleave(d[1], 1)
+        return (
+            gradients[slice1[0] : slice1[1], slice2[0] : slice2[1]]
+            .repeat_interleave(d[0], 0)
+            .repeat_interleave(d[1], 1)
+        )
 
     def dot(grad, shift):
         return (

scripts/configure_invokeai.py

@@ -6,5 +6,7 @@ import warnings
 from invokeai.frontend.install.invokeai_configure import invokeai_configure as configure
 
 if __name__ == "__main__":
-    warnings.warn("configure_invokeai.py is deprecated, running 'invokeai-configure'...", DeprecationWarning, stacklevel=2)
+    warnings.warn(
+        "configure_invokeai.py is deprecated, running 'invokeai-configure'...", DeprecationWarning, stacklevel=2
+    )
     configure()