update winml python example (#516)

Author: chemwolf6922

Samples/WindowsML/python/Download-Model.ps1

@@ -11,16 +11,16 @@ function Get-FileFromUri {
     param (
         [Parameter(Mandatory=$true)][string]$Uri,
         [Parameter(Mandatory=$true)][string]$OutFile,
-        [Parameter(Mandatory=$true)][string]$ExpectedMD5
+        [Parameter(Mandatory=$true)][string]$ExpectedHash
     )
 
     $needsDownload = $true
     Write-Host "Downloading $OutFile from $Uri" -ForegroundColor Cyan
 
     if (Test-Path $OutFile -PathType Leaf) {
-        Write-Host "File exists. Verifying MD5 checksum..." -ForegroundColor Yellow
-        $md5 = Get-FileHash -Path $OutFile -Algorithm MD5
-        if ($md5.Hash -eq $ExpectedMD5) {
+        Write-Host "File exists. Verifying checksum..." -ForegroundColor Yellow
+        $hash = Get-FileHash -Path $OutFile -Algorithm SHA256
+        if ($hash.Hash -eq $ExpectedHash) {
             Write-Host "File checksum matches. Using existing file." -ForegroundColor Green
             $needsDownload = $false
         } else {
@@ -44,9 +44,9 @@ function Get-FileFromUri {
 # Download the model file
 $modelPath = Join-Path $targetPath 'SqueezeNet.onnx'
 $modelUri = 'https://github.com/microsoft/Windows-Machine-Learning/blob/02b586811c8beb1ae2208c8605393267051257ae/SharedContent/models/SqueezeNet.onnx?raw=true'
-Get-FileFromUri -Uri $modelUri -OutFile $modelPath -ExpectedMD5 "3EA0D4AECA899A4F99216FC4BEBD9D0D" | Out-Null
+Get-FileFromUri -Uri $modelUri -OutFile $modelPath -ExpectedHash "D95E2191E056F1912A9B8F6000DA3B9C7818441B9EB48137033C2ADBF6398BC8" | Out-Null
 
 # Download the labels file
 $labelsPath = Join-Path $targetPath 'SqueezeNet.Labels.txt'
 $labelsUri = 'https://github.com/microsoft/Windows-Machine-Learning/blob/02b586811c8beb1ae2208c8605393267051257ae/Samples/SqueezeNetObjectDetection/Desktop/cpp/Labels.txt?raw=true'
-Get-FileFromUri -Uri $labelsUri -OutFile $labelsPath -ExpectedMD5 "7317EA720B83CB3CADB75AD91419F6A8" | Out-Null
+Get-FileFromUri -Uri $labelsUri -OutFile $labelsPath -ExpectedHash "DC1FD0D4747096D3AA690BD65EC2F51FDB3E5117535BFBCE46FA91088A8F93A9" | Out-Null

Samples/WindowsML/python/SqueezeNetPython/main.py

@@ -5,21 +5,9 @@
 from PIL import Image
 import numpy as np
 import onnxruntime as ort
-import subprocess
-import sys
-import json
+from winml import WinML
 
-def register_execution_providers():
-    # Run this in another process to avoid a issue where 
-    # the pywinrt module stops the tensorRT execution provider from loading.
-    worker_script = str(Path(__file__).parent / 'winml_worker.py')
-    result = subprocess.check_output([sys.executable, worker_script], text=True)
-    paths = json.loads(result)
-    for item in paths.items():
-        ort.register_execution_provider_library(item[0], item[1])
-        print(f"Registered execution provider: {item[0]} with library path: {item[1]}")
-
-def load_and_preprocess_image(image_path):
+def load_and_preprocess_image(image_path: Path) -> np.ndarray:
     img = Image.open(image_path)    
     if img.mode != 'RGB':
         img = img.convert('RGB')
@@ -32,12 +20,12 @@ def load_and_preprocess_image(image_path):
     img_array = np.expand_dims(img_array, axis=0)
     return img_array.astype(np.float32)
 
-def load_labels(label_file):
+def load_labels(label_file: Path) -> list[str]:
     with open(label_file, 'r') as f:
         labels = [line.strip().split(',')[1] for line in f.readlines()]
     return labels
 
-def print_results(labels, results, is_logit=False):
+def print_results(labels : list[str], results: np.ndarray, is_logit=False) -> None:
     def softmax(x):
         exp_x = np.exp(x - np.max(x))
         return exp_x / exp_x.sum()
@@ -58,36 +46,35 @@ def softmax(x):
 
 if __name__ == "__main__":
     print("Registering execution providers ...")
-    register_execution_providers()
-    
-    print("Creating session ...")
+    registered_eps = WinML().register_execution_providers_to_ort()
+    print(f"Registered execution providers: {registered_eps}")
 
     resource_path = Path(__file__).parent.parent 
-    model_path = resource_path / "Model" / "SqueezeNet.onnx"
-    compiled_model_path = resource_path / "Model" / "SqueezeNet_ctx.onnx"
+
+    print("Setting session options ...")
     session_options = ort.SessionOptions()
     # Change your policy here.
     session_options.set_provider_selection_policy(ort.OrtExecutionProviderDevicePolicy.PREFER_NPU)
-    assert session_options.has_providers()
 
+    print("Compiling model ...")
+    model_path = resource_path / "Model" / "SqueezeNet.onnx"
+    compiled_model_path = resource_path / "Model" / "SqueezeNet_ctx.onnx"
+    if not compiled_model_path.exists():
+        model_compiler = ort.ModelCompiler(session_options, model_path)
+        model_compiler.compile_to_file(str(compiled_model_path))
+    else:
+        print("Using existing compiled model.")
     if compiled_model_path.exists():
-        print("Using compiled model")
+        print("Using compiled model.")
+        model_path_to_use = compiled_model_path
     else:
-        print("No compiled model found, attempting to create compiled model at ", compiled_model_path)  
-        model_compiler = ort.ModelCompiler(session_options, model_path)
-        print("Starting compile, this may take a few moments..." )
-        try:
-            model_compiler.compile_to_file(compiled_model_path)
-            print("Model compiled successfully")
-        except Exception as e:
-            print("Model compilation failed:", e)
-            print("Falling back to uncompiled model")
-
-    model_path_to_use = compiled_model_path if compiled_model_path.exists() else model_path
+        print("No compile output. Using original model.")
+        model_path_to_use = model_path
 
+    print("Creating session ...")
     session = ort.InferenceSession(
         model_path_to_use,
-        sess_options=session_options,
+        sess_options=session_options
     )
 
     labels = load_labels(resource_path / "Model" / "SqueezeNet.Labels.txt")
@@ -100,4 +87,6 @@ def softmax(x):
         print("Running inference ...")
         input_name = session.get_inputs()[0].name
         results = session.run(None, {input_name: img_array})[0]
+        if not isinstance(results, np.ndarray):
+            raise TypeError("Unexpected output type from model.")
         print_results(labels, results, is_logit=False)

Samples/WindowsML/python/SqueezeNetPython/readme.md

@@ -12,13 +12,21 @@ extendedZipContent:
   target: LICENSE
 ---
 
-## Prerequisites
-* Python 3.10 - 3.13 on Windows
-* Download model file
+## Steps
+### Download test model
 ```PowerShell
 ..\Download-Model.ps1
 ```
-* Install dependencies
+### Prepare the python environment
+* Create a python environment with Python 3.10 - 3.13
+* Install the latest WinML python packages
 ```PowerShell
-pip install -r requirements.txt
-```
+pip install --upgrade --pre -r requirements.txt 
+```
+### Install WindowsAppRuntime
+Please install the WindowsAppRuntime that matches the version of the python package `wasdk-Microsoft.Windows.ApplicationModel.DynamicDependency.Bootstrap`
+> For experimental or preview WASDK. The version tags `-xxxN` are changed to `.devN` to fit Python's version requirements.
+### Run the example
+```PowerShell
+python main.py
+```

Samples/WindowsML/python/SqueezeNetPython/requirements.txt

@@ -1,11 +1,5 @@
---index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple
---extra-index-url https://pypi.org/simple
-
 pillow
 numpy
-onnxruntime-winml==1.22.0.post2
-winrt-runtime~=3.2.1.0
-winrt-Windows.Foundation~=3.2.1.0
-winrt-Windows.Foundation.Collections~=3.2.1.0
-winui3-Microsoft.Windows.AI.MachineLearning==1!1.8.250702007.dev4
-winui3-Microsoft.Windows.ApplicationModel.DynamicDependency.Bootstrap==1!1.8.250702007.dev4
+onnxruntime-winml
+wasdk-Microsoft.Windows.AI.MachineLearning[all]
+wasdk-Microsoft.Windows.ApplicationModel.DynamicDependency.Bootstrap

Samples/WindowsML/python/SqueezeNetPython/winml.py

@@ -0,0 +1,68 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+import sys
+from pathlib import Path
+import traceback
+
+# This needs to be alive throughout the lifetime of the application
+_instance = None
+
+class WinML:
+    def __new__(cls, *args, **kwargs):
+        global _instance
+        if _instance is None:
+            _instance = super(WinML, cls).__new__(cls, *args, **kwargs)
+            _instance._initialized = False
+        return _instance
+
+    def __init__(self):
+        if self._initialized:
+            return
+        self._initialized = True
+
+        self._fix_winrt_runtime()
+        from winui3.microsoft.windows.applicationmodel.dynamicdependency.bootstrap import (
+            InitializeOptions,
+            initialize
+        )
+        import winui3.microsoft.windows.ai.machinelearning as winml
+        self._win_app_sdk_handle = initialize(options=InitializeOptions.ON_NO_MATCH_SHOW_UI)
+        self._win_app_sdk_handle.__enter__()
+        catalog = winml.ExecutionProviderCatalog.get_default()
+        self._providers = catalog.find_all_providers()
+        self._ep_paths : dict[str, str] = {}
+        for provider in self._providers:
+            provider.ensure_ready_async().get()
+            if provider.library_path == '':
+                continue
+            self._ep_paths[provider.name] = provider.library_path
+        self._registered_eps : list[str] = []
+
+    def __del__(self):
+        self._providers = None
+        self._win_app_sdk_handle.__exit__(None, None, None)
+
+    def _fix_winrt_runtime(self):
+        """
+        This function removes the msvcp140.dll from the winrt-runtime package.
+        So it does not cause issues with other libraries.
+        """
+        from importlib import metadata
+        site_packages_path = Path(str(metadata.distribution('winrt-runtime').locate_file('')))
+        dll_path = site_packages_path / 'winrt' / 'msvcp140.dll'
+        if dll_path.exists():
+            dll_path.unlink()
+
+    def register_execution_providers_to_ort(self) -> list[str]:
+        import onnxruntime as ort
+        for name, path in self._ep_paths.items():
+            if name not in self._registered_eps:
+                try:
+                    ort.register_execution_provider_library(name, path)
+                    self._registered_eps.append(name)
+                except Exception as e:
+                    print(f"Failed to register execution provider {name}: {e}", file=sys.stderr)
+                    traceback.print_exc()
+        return self._registered_eps
+