wire up pipeline parameter, apply lint

api/onnx_web/chain/blend_controlnet.py

@@ -2,11 +2,9 @@ from logging import getLogger
 from typing import Optional
 
 import numpy as np
-import torch
 from PIL import Image
 
 from ..diffusers.load import load_pipeline
-from ..diffusers.pipelines.controlnet import OnnxStableDiffusionControlNetPipeline
 from ..params import ImageParams, StageParams
 from ..server import ServerContext
 from ..worker import ProgressCallback, WorkerContext
@@ -47,7 +45,7 @@ def blend_controlnet(
         image=source,
         negative_prompt=params.negative_prompt,
         num_inference_steps=params.steps,
-        strength=params.strength, # TODO: ControlNet strength
+        strength=params.strength,  # TODO: ControlNet strength
         callback=callback,
     )
 

api/onnx_web/chain/blend_img2img.py

@@ -3,7 +3,6 @@ from typing import Optional
 
 import numpy as np
 import torch
-from diffusers import OnnxStableDiffusionImg2ImgPipeline
 from PIL import Image
 
 from ..diffusers.load import load_pipeline
@@ -33,7 +32,7 @@ def blend_img2img(
 
     pipe = load_pipeline(
         server,
-        params.pipeline,
+        "img2img",
         params.model,
         params.scheduler,
         job.get_device(),

api/onnx_web/chain/blend_inpaint.py

@@ -3,7 +3,6 @@ from typing import Callable, Optional, Tuple
 
 import numpy as np
 import torch
-from diffusers import OnnxStableDiffusionInpaintPipeline
 from PIL import Image
 
 from ..diffusers.load import get_latents_from_seed, load_pipeline
@@ -59,6 +58,14 @@ def blend_inpaint(
         save_image(server, "last-mask.png", stage_mask)
         save_image(server, "last-noise.png", noise)
 
+    pipe = load_pipeline(
+        server,
+        "inpaint",
+        params.model,
+        params.scheduler,
+        job.get_device(),
+    )
+
     def outpaint(tile_source: Image.Image, dims: Tuple[int, int, int]):
         left, top, tile = dims
         size = Size(*tile_source.size)
@@ -69,14 +76,6 @@ def blend_inpaint(
             save_image(server, "tile-mask.png", tile_mask)
 
         latents = get_latents_from_seed(params.seed, size)
-        pipe = load_pipeline(
-            server,
-            OnnxStableDiffusionInpaintPipeline,
-            params.model,
-            params.scheduler,
-            job.get_device(),
-        )
-
         if params.lpw():
             logger.debug("using LPW pipeline for inpaint")
             rng = torch.manual_seed(params.seed)

api/onnx_web/chain/blend_pix2pix.py

@@ -6,7 +6,6 @@ import torch
 from PIL import Image
 
 from ..diffusers.load import load_pipeline
-from ..diffusers.pipelines.pix2pix import OnnxStableDiffusionInstructPix2PixPipeline
 from ..params import ImageParams, StageParams
 from ..server import ServerContext
 from ..worker import ProgressCallback, WorkerContext

api/onnx_web/chain/source_txt2img.py

@@ -3,7 +3,6 @@ from typing import Optional
 
 import numpy as np
 import torch
-from diffusers import OnnxStableDiffusionPipeline
 from PIL import Image
 
 from ..diffusers.load import get_latents_from_seed, load_pipeline

api/onnx_web/chain/upscale_outpaint.py

@@ -3,7 +3,6 @@ from typing import Callable, Optional, Tuple
 
 import numpy as np
 import torch
-from diffusers import OnnxStableDiffusionInpaintPipeline
 from PIL import Image, ImageDraw
 
 from ..diffusers.load import get_latents_from_seed, get_tile_latents, load_pipeline

api/onnx_web/diffusers/load.py

@@ -7,7 +7,6 @@ import torch
 from diffusers import (
     DDIMScheduler,
     DDPMScheduler,
-    DiffusionPipeline,
     DPMSolverMultistepScheduler,
     DPMSolverSinglestepScheduler,
     EulerAncestralDiscreteScheduler,
@@ -41,9 +40,11 @@ except ImportError:
 from ..constants import ONNX_MODEL
 from ..convert.diffusion.lora import blend_loras, buffer_external_data_tensors
 from ..convert.diffusion.textual_inversion import blend_textual_inversions
+from ..diffusers.lpw_stable_diffusion_onnx import (
+    OnnxStableDiffusionLongPromptWeightingPipeline,
+)
 from ..diffusers.pipelines.controlnet import OnnxStableDiffusionControlNetPipeline
 from ..diffusers.pipelines.pix2pix import OnnxStableDiffusionInstructPix2PixPipeline
-from ..diffusers.lpw_stable_diffusion_onnx import OnnxStableDiffusionLongPromptWeightingPipeline
 from ..diffusers.utils import expand_prompt
 from ..params import DeviceParams, Size
 from ..server import ServerContext
@@ -150,7 +151,6 @@ def load_pipeline(
         model,
         device.device,
         device.provider,
-        lpw,
         control_key,
         inversions,
         loras,
@@ -294,7 +294,7 @@ def load_pipeline(
             )
 
         # ControlNet component
-        if control is not None:
+        if pipeline == "controlnet" and control is not None:
             components["controlnet"] = OnnxRuntimeModel(
                 OnnxRuntimeModel.load_model(
                     path.join(server.model_path, "control", f"{control.name}.onnx"),

api/onnx_web/diffusers/run.py

@@ -3,13 +3,11 @@ from typing import Any, List
 
 import numpy as np
 import torch
-from diffusers import OnnxStableDiffusionImg2ImgPipeline, OnnxStableDiffusionPipeline
 from PIL import Image
 
 from ..chain import blend_mask, upscale_outpaint
 from ..chain.base import ChainProgress
 from ..chain.utils import process_tile_order
-from ..diffusers.pipelines.controlnet import OnnxStableDiffusionControlNetPipeline
 from ..output import save_image, save_params
 from ..params import (
     Border,
@@ -231,7 +229,7 @@ def run_img2img_pipeline(
 
     pipe = load_pipeline(
         server,
-        "img2img",
+        params.pipeline,  # this is one of the only places this can actually vary between different pipelines
         params.model,
         params.scheduler,
         job.get_device(),

api/onnx_web/server/api.py

@@ -145,7 +145,7 @@ def img2img(server: ServerContext, pool: DevicePoolExecutor):
 
     source = Image.open(BytesIO(source_file.read())).convert("RGB")
 
-    device, params, size = pipeline_from_request(server)
+    device, params, size = pipeline_from_request(server, "img2img")
     upscale = upscale_from_request()
 
     strength = get_and_clamp_float(
@@ -177,7 +177,7 @@ def img2img(server: ServerContext, pool: DevicePoolExecutor):
 
 
 def txt2img(server: ServerContext, pool: DevicePoolExecutor):
-    device, params, size = pipeline_from_request(server)
+    device, params, size = pipeline_from_request(server, "txt2img")
     upscale = upscale_from_request()
     highres = highres_from_request()
 
@@ -212,7 +212,7 @@ def inpaint(server: ServerContext, pool: DevicePoolExecutor):
     source = Image.open(BytesIO(source_file.read())).convert("RGB")
     mask = Image.open(BytesIO(mask_file.read())).convert("RGB")
 
-    device, params, size = pipeline_from_request(server)
+    device, params, size = pipeline_from_request(server, "inpaint")
     expand = border_from_request()
     upscale = upscale_from_request()
 

api/onnx_web/server/params.py

@@ -4,7 +4,7 @@ from typing import Tuple
 import numpy as np
 from flask import request
 
-from ..diffusers.load import get_available_pipelines, get_pipeline_schedulers, pipeline_schedulers
+from ..diffusers.load import get_available_pipelines, get_pipeline_schedulers
 from ..params import (
     Border,
     DeviceParams,
@@ -30,7 +30,7 @@ logger = getLogger(__name__)
 
 def pipeline_from_request(
     server: ServerContext,
-    default_pipeline: str,
+    default_pipeline: str = "txt2img",
 ) -> Tuple[DeviceParams, ImageParams, Size]:
     user = request.remote_addr
 
@@ -49,9 +49,10 @@ def pipeline_from_request(
     control = get_from_list(request.args, "control", get_network_models())
 
     # pipeline stuff
-    pipeline = get_from_list(request.args, "pipeline", get_available_pipelines(), default_pipeline)
-    scheduler = get_from_list(
-        request.args, "scheduler", get_pipeline_schedulers())
+    pipeline = get_from_list(
+        request.args, "pipeline", get_available_pipelines(), default_pipeline
+    )
+    scheduler = get_from_list(request.args, "scheduler", get_pipeline_schedulers())
 
     if scheduler is None:
         scheduler = get_config_value("scheduler")
@@ -135,7 +136,6 @@ def pipeline_from_request(
         steps,
         seed,
         eta=eta,
-        lpw=lpw,
         negative_prompt=negative_prompt,
         batch=batch,
         control=control,