Remove onnx changes from canvas img2img, inpaint, and linear image2image

invokeai/backend/generator/base.py

@@ -458,6 +458,7 @@ class Generator:
             dtype=samples.dtype,
             device=samples.device,
         )
+
         latent_image = samples[0].permute(1, 2, 0) @ v1_5_latent_rgb_factors
         latents_ubyte = (
             ((latent_image + 1) / 2)

invokeai/backend/model_management/models/base.py

@@ -267,18 +267,16 @@ class DiffusersModel(ModelBase):
             try:
                 # TODO: set cache_dir to /dev/null to be sure that cache not used?
                 model = self.child_types[child_type].from_pretrained(
-                    os.path.join(self.model_path, child_type.value),
-                    #subfolder=child_type.value,
+                    self.model_path,
+                    subfolder=child_type.value,
                     torch_dtype=torch_dtype,
                     variant=variant,
                     local_files_only=True,
                 )
                 break
             except Exception as e:
-                print("====ERR LOAD====")
-                print(f"{variant}: {e}")
-                import traceback
-                traceback.print_exc()
+                # print("====ERR LOAD====")
+                # print(f"{variant}: {e}")
                 pass
         else:
             raise Exception(f"Failed to load {self.base_model}:{self.model_type}:{child_type} model")

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasImageToImageGraph.ts

@@ -20,7 +20,6 @@ import {
   LATENTS_TO_IMAGE,
   LATENTS_TO_LATENTS,
   MAIN_MODEL_LOADER,
-  ONNX_MODEL_LOADER,
   METADATA_ACCUMULATOR,
   NEGATIVE_CONDITIONING,
   NOISE,
@@ -63,9 +62,6 @@ export const buildCanvasImageToImageGraph = (
     ? shouldUseCpuNoise
     : initialGenerationState.shouldUseCpuNoise;
 
-  const onnx_model_type = model.model_type.includes('onnx');
-  const model_loader = onnx_model_type ? ONNX_MODEL_LOADER : MAIN_MODEL_LOADER;
-
   /**
    * The easiest way to build linear graphs is to do it in the node editor, then copy and paste the
    * full graph here as a template. Then use the parameters from app state and set friendlier node
@@ -76,18 +72,17 @@ export const buildCanvasImageToImageGraph = (
    */
 
   // copy-pasted graph from node editor, filled in with state values & friendly node ids
-  // TODO: Actually create the graph correctly for ONNX
   const graph: NonNullableGraph = {
     id: IMAGE_TO_IMAGE_GRAPH,
     nodes: {
       [POSITIVE_CONDITIONING]: {
-        type: onnx_model_type ? 'prompt_onnx' : 'compel',
+        type: 'compel',
         id: POSITIVE_CONDITIONING,
         is_intermediate: true,
         prompt: positivePrompt,
       },
       [NEGATIVE_CONDITIONING]: {
-        type: onnx_model_type ? 'prompt_onnx' : 'compel',
+        type: 'compel',
         id: NEGATIVE_CONDITIONING,
         is_intermediate: true,
         prompt: negativePrompt,
@@ -98,9 +93,9 @@ export const buildCanvasImageToImageGraph = (
         is_intermediate: true,
         use_cpu,
       },
-      [model_loader]: {
-        type: model_loader,
-        id: model_loader,
+      [MAIN_MODEL_LOADER]: {
+        type: 'main_model_loader',
+        id: MAIN_MODEL_LOADER,
         is_intermediate: true,
         model,
       },
@@ -111,7 +106,7 @@ export const buildCanvasImageToImageGraph = (
         skipped_layers: clipSkip,
       },
       [LATENTS_TO_LATENTS]: {
-        type: onnx_model_type ? 'l2l_onnx' : 'l2l',
+        type: 'l2l',
         id: LATENTS_TO_LATENTS,
         is_intermediate: true,
         cfg_scale,
@@ -120,7 +115,7 @@ export const buildCanvasImageToImageGraph = (
         strength,
       },
       [IMAGE_TO_LATENTS]: {
-        type: onnx_model_type ? 'i2l_onnx' : 'i2l',
+        type: 'i2l',
         id: IMAGE_TO_LATENTS,
         is_intermediate: true,
         // must be set manually later, bc `fit` parameter may require a resize node inserted
@@ -137,7 +132,7 @@ export const buildCanvasImageToImageGraph = (
     edges: [
       {
         source: {
-          node_id: model_loader,
+          node_id: MAIN_MODEL_LOADER,
           field: 'clip',
         },
         destination: {
@@ -197,7 +192,7 @@ export const buildCanvasImageToImageGraph = (
       },
       {
         source: {
-          node_id: model_loader,
+          node_id: MAIN_MODEL_LOADER,
           field: 'unet',
         },
         destination: {
@@ -329,10 +324,10 @@ export const buildCanvasImageToImageGraph = (
   });
 
   // add LoRA support
-  addLoRAsToGraph(state, graph, LATENTS_TO_LATENTS, model_loader);
+  addLoRAsToGraph(state, graph, LATENTS_TO_LATENTS);
 
   // optionally add custom VAE
-  addVAEToGraph(state, graph, model_loader);
+  addVAEToGraph(state, graph);
 
   // add dynamic prompts - also sets up core iteration and seed
   addDynamicPromptsToGraph(state, graph);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasInpaintGraph.ts

@@ -17,7 +17,6 @@ import {
   INPAINT_GRAPH,
   ITERATE,
   MAIN_MODEL_LOADER,
-  ONNX_MODEL_LOADER,
   NEGATIVE_CONDITIONING,
   POSITIVE_CONDITIONING,
   RANDOM_INT,
@@ -69,11 +68,6 @@ export const buildCanvasInpaintGraph = (
     shouldAutoSave,
   } = state.canvas;
 
-  const model_loader = model.model_type.includes('onnx')
-    ? ONNX_MODEL_LOADER
-    : MAIN_MODEL_LOADER;
-
-  // TODO: Actually create the graph correctly for ONNX
   const graph: NonNullableGraph = {
     id: INPAINT_GRAPH,
     nodes: {
@@ -121,9 +115,9 @@ export const buildCanvasInpaintGraph = (
         is_intermediate: true,
         prompt: negativePrompt,
       },
-      [model_loader]: {
-        type: model_loader,
-        id: model_loader,
+      [MAIN_MODEL_LOADER]: {
+        type: 'main_model_loader',
+        id: MAIN_MODEL_LOADER,
         is_intermediate: true,
         model,
       },
@@ -151,7 +145,7 @@ export const buildCanvasInpaintGraph = (
     edges: [
       {
         source: {
-          node_id: model_loader,
+          node_id: MAIN_MODEL_LOADER,
           field: 'unet',
         },
         destination: {
@@ -161,7 +155,7 @@ export const buildCanvasInpaintGraph = (
       },
       {
         source: {
-          node_id: model_loader,
+          node_id: MAIN_MODEL_LOADER,
           field: 'clip',
         },
         destination: {

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearImageToImageGraph.ts

@@ -19,7 +19,6 @@ import {
   LATENTS_TO_IMAGE,
   LATENTS_TO_LATENTS,
   MAIN_MODEL_LOADER,
-  ONNX_MODEL_LOADER,
   METADATA_ACCUMULATOR,
   NEGATIVE_CONDITIONING,
   NOISE,
@@ -85,17 +84,13 @@ export const buildLinearImageToImageGraph = (
     ? shouldUseCpuNoise
     : initialGenerationState.shouldUseCpuNoise;
 
-  const onnx_model_type = model.model_type.includes('onnx');
-  const model_loader = onnx_model_type ? ONNX_MODEL_LOADER : MAIN_MODEL_LOADER;
-
   // copy-pasted graph from node editor, filled in with state values & friendly node ids
-  // TODO: Actually create the graph correctly for ONNX
   const graph: NonNullableGraph = {
     id: IMAGE_TO_IMAGE_GRAPH,
     nodes: {
-      [model_loader]: {
-        type: model_loader,
-        id: model_loader,
+      [MAIN_MODEL_LOADER]: {
+        type: 'main_model_loader',
+        id: MAIN_MODEL_LOADER,
         model,
       },
       [CLIP_SKIP]: {
@@ -104,12 +99,12 @@ export const buildLinearImageToImageGraph = (
         skipped_layers: clipSkip,
       },
       [POSITIVE_CONDITIONING]: {
-        type: onnx_model_type ? 'prompt_onnx' : 'compel',
+        type: 'compel',
         id: POSITIVE_CONDITIONING,
         prompt: positivePrompt,
       },
       [NEGATIVE_CONDITIONING]: {
-        type: onnx_model_type ? 'prompt_onnx' : 'compel',
+        type: 'compel',
         id: NEGATIVE_CONDITIONING,
         prompt: negativePrompt,
       },
@@ -119,12 +114,12 @@ export const buildLinearImageToImageGraph = (
         use_cpu,
       },
       [LATENTS_TO_IMAGE]: {
-        type: onnx_model_type ? 'l2i_onnx' : 'l2i',
+        type: 'l2i',
         id: LATENTS_TO_IMAGE,
         fp32: vaePrecision === 'fp32' ? true : false,
       },
       [LATENTS_TO_LATENTS]: {
-        type: onnx_model_type ? 'l2l_onnx' : 'l2l',
+        type: 'l2l',
         id: LATENTS_TO_LATENTS,
         cfg_scale,
         scheduler,
@@ -132,7 +127,7 @@ export const buildLinearImageToImageGraph = (
         strength,
       },
       [IMAGE_TO_LATENTS]: {
-        type: onnx_model_type ? 'i2l_onnx' : 'i2l',
+        type: 'i2l',
         id: IMAGE_TO_LATENTS,
         // must be set manually later, bc `fit` parameter may require a resize node inserted
         // image: {
@@ -144,7 +139,7 @@ export const buildLinearImageToImageGraph = (
     edges: [
       {
         source: {
-          node_id: model_loader,
+          node_id: MAIN_MODEL_LOADER,
           field: 'unet',
         },
         destination: {
@@ -154,7 +149,7 @@ export const buildLinearImageToImageGraph = (
       },
       {
         source: {
-          node_id: model_loader,
+          node_id: MAIN_MODEL_LOADER,
           field: 'clip',
         },
         destination: {
@@ -339,10 +334,10 @@ export const buildLinearImageToImageGraph = (
   });
 
   // add LoRA support
-  addLoRAsToGraph(state, graph, LATENTS_TO_LATENTS, model_loader);
+  addLoRAsToGraph(state, graph, LATENTS_TO_LATENTS);
 
   // optionally add custom VAE
-  addVAEToGraph(state, graph, model_loader);
+  addVAEToGraph(state, graph);
 
   // add dynamic prompts - also sets up core iteration and seed
   addDynamicPromptsToGraph(state, graph);