feat(api): add provider for each available CUDA device (#38)

api/onnx_web/device_pool.py

@@ -3,6 +3,10 @@ from logging import getLogger
 from multiprocessing import Value
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
+from .params import (
+    DeviceParams,
+)
+
 logger = getLogger(__name__)
 
 
@@ -10,7 +14,7 @@ class JobContext:
     def __init__(
         self,
         key: str,
-        devices: List[str],
+        devices: List[DeviceParams],
         cancel: bool = False,
         device_index: int = -1,
         progress: int = 0,
@@ -24,7 +28,7 @@ class JobContext:
     def is_cancelled(self) -> bool:
         return self.cancel.value
 
-    def get_device(self) -> str:
+    def get_device(self) -> DeviceParams:
         '''
         Get the device assigned to this job.
         '''
@@ -45,7 +49,8 @@ class JobContext:
             if self.is_cancelled():
                 raise Exception('job has been cancelled')
             else:
-                logger.debug('setting progress for job %s to %s', self.key, step)
+                logger.debug('setting progress for job %s to %s',
+                             self.key, step)
                 self.set_progress(step)
 
         return on_progress
@@ -63,6 +68,7 @@ class Job:
     '''
     Link a future to its context.
     '''
+
     def __init__(
         self,
         key: str,
@@ -88,16 +94,18 @@ class DevicePoolExecutor:
     jobs: List[Job] = None
     pool: Union[ProcessPoolExecutor, ThreadPoolExecutor] = None
 
-    def __init__(self, devices: List[str], pool: Optional[Union[ProcessPoolExecutor, ThreadPoolExecutor]] = None):
+    def __init__(self, devices: List[DeviceParams], pool: Optional[Union[ProcessPoolExecutor, ThreadPoolExecutor]] = None):
         self.devices = devices
         self.jobs = []
 
         device_count = len(devices)
         if pool is None:
-            logger.info('creating thread pool executor for %s devices: %s', device_count, devices)
+            logger.info(
+                'creating thread pool executor for %s devices: %s', device_count, devices)
             self.pool = ThreadPoolExecutor(device_count)
         else:
-            logger.info('using existing pool for %s devices: %s', device_count, devices)
+            logger.info('using existing pool for %s devices: %s',
+                        device_count, devices)
             self.pool = pool
 
     def cancel(self, key: str) -> bool:
@@ -142,4 +150,4 @@ class DevicePoolExecutor:
         future.add_done_callback(job_done)
 
     def status(self) -> Dict[str, Tuple[bool, int]]:
-        return [(job.key, job.future.done(), job.get_progress()) for job in self.jobs]
+        return [(job.key, job.future.done(), job.get_progress()) for job in self.jobs]

api/onnx_web/diffusion/run.py

@@ -50,7 +50,7 @@ def run_txt2img_pipeline(
 ) -> None:
     device = job.get_device()
     pipe = load_pipeline(OnnxStableDiffusionPipeline,
-                         params.model, params.provider, params.scheduler, device=device)
+                         params.model, device.provider, params.scheduler, device=device.torch_device())
 
     latents = get_latents_from_seed(params.seed, size)
     rng = np.random.RandomState(params.seed)
@@ -92,7 +92,7 @@ def run_img2img_pipeline(
 ) -> None:
     device = job.get_device()
     pipe = load_pipeline(OnnxStableDiffusionImg2ImgPipeline,
-                         params.model, params.provider, params.scheduler, device=device)
+                         params.model, device.provider, params.scheduler, device=device.torch_device())
 
     rng = np.random.RandomState(params.seed)
 
@@ -137,8 +137,8 @@ def run_inpaint_pipeline(
     strength: float,
     fill_color: str,
 ) -> None:
-    device = job.get_device()
+    # device = job.get_device()
-    progress = job.get_progress_callback()
+    # progress = job.get_progress_callback()
     stage = StageParams()
 
     # TODO: pass device, progress
@@ -182,8 +182,8 @@ def run_upscale_pipeline(
     upscale: UpscaleParams,
     source_image: Image.Image,
 ) -> None:
-    device = job.get_device()
+    # device = job.get_device()
-    progress = job.get_progress_callback()
+    # progress = job.get_progress_callback()
     stage = StageParams()
 
     # TODO: pass device, progress

api/onnx_web/params.py

@@ -59,6 +59,19 @@ class Size:
         }
 
 
+class DeviceParams:
+    def __init__(self, device: str, provider: str, options: Optional[dict] = None) -> None:
+        self.device = device
+        self.provider = provider
+        self.options = options
+
+    def torch_device(self) -> str:
+        if self.device.startswith('cuda'):
+            return self.device
+        else:
+            return 'cpu'
+
+
 class ImageParams:
     def __init__(
         self,

api/onnx_web/serve.py

@@ -15,7 +15,6 @@ from diffusers import (
 )
 from flask import Flask, jsonify, make_response, request, send_from_directory, url_for
 from flask_cors import CORS
-from flask_executor import Executor
 from glob import glob
 from io import BytesIO
 from jsonschema import validate
@@ -23,7 +22,7 @@ from logging import getLogger
 from PIL import Image
 from onnxruntime import get_available_providers
 from os import makedirs, path
-from typing import Tuple
+from typing import List, Tuple
 
 
 from .chain import (
@@ -69,6 +68,7 @@ from .output import (
 )
 from .params import (
     Border,
+    DeviceParams,
     ImageParams,
     Size,
     StageParams,
@@ -88,6 +88,7 @@ from .utils import (
 
 import gc
 import numpy as np
+import torch
 import yaml
 
 logger = getLogger(__name__)
@@ -147,7 +148,7 @@ chain_stages = {
 }
 
 # Available ORT providers
-available_platforms = []
+available_platforms: List[DeviceParams] = []
 
 # loaded from model_path
 diffusion_models = []
@@ -310,8 +311,16 @@ def load_platforms():
     global available_platforms
 
     providers = get_available_providers()
-    available_platforms = [p for p in platform_providers if (
+
-        platform_providers[p] in providers and p not in context.block_platforms)]
+    for potential in platform_providers:
+        if platform_providers[potential] in providers and potential not in context.block_platforms:
+            if potential == 'cuda':
+                for i in range(torch.cuda.device_count()):
+                    available_platforms.append(DeviceParams('%s:%s' % (potential, i), providers[potential], {
+                        'device_id': i,
+                    }))
+            else:
+                available_platforms.append(DeviceParams(potential, providers[potential]))
 
     logger.info('available acceleration platforms: %s', available_platforms)
 
@@ -404,7 +413,7 @@ def list_params():
 
 @app.route('/api/settings/platforms')
 def list_platforms():
-    return jsonify(list(available_platforms))
+    return jsonify([p.device for p in available_platforms])
 
 
 @app.route('/api/settings/schedulers')

onnx-web.code-workspace

@@ -48,6 +48,7 @@
 			"randn",
 			"realesr",
 			"resrgan",
+			"rocm",
 			"RRDB",
 			"runwayml",
 			"scandir",