Improve: Add test code for ONNX inference with DmlExecutionProvider

pyproject.toml

@@ -91,12 +91,14 @@ python = ["3.9", "3.10", "3.11"]
 
 # for ONNX inference (without PyTorch dependency)
 [tool.hatch.envs.test-onnx]
-dependencies = ["coverage[toml]>=6.5", "pytest", "scipy", "onnxruntime-gpu"]
+dependencies = ["coverage[toml]>=6.5", "pytest", "scipy", "onnxruntime-gpu", "onnxruntime-directml; sys_platform == 'win32'"]
 [tool.hatch.envs.test-onnx.scripts]
 # Usage: `hatch run test-onnx:test`
 test = "pytest tests/test_main.py::test_synthesize_onnx_cpu"
 # Usage: `hatch run test-onnx:test-cuda`
 test-cuda = "pytest tests/test_main.py::test_synthesize_onnx_cuda"
+# Usage: `hatch run test-onnx:test-directml`
+test-directml = "pytest tests/test_main.py::test_synthesize_onnx_directml"
 # Usage: `hatch run test-onnx:coverage`
 test-cov = "coverage run -m pytest tests/test_main.py::test_synthesize_onnx_cpu"
 # Usage: `hatch run test-onnx:cov-report`

tests/test_main.py

@@ -37,7 +37,9 @@ def synthesize(
                         if f.endswith(".onnx") and not f.startswith(".")
                     ]
                 if len(model_files) == 0:
-                    pytest.skip(f"音声合成モデル \"{model_info.name}\" のモデルファイルが見つかりませんでした。")
+                    pytest.skip(
+                        f'音声合成モデル "{model_info.name}" のモデルファイルが見つかりませんでした。'
+                    )
 
                 # モデルをロード
                 model = model_holder.get_model(model_info.name, model_files[0])
@@ -100,3 +102,8 @@ def test_synthesize_onnx_cuda():
             ("CUDAExecutionProvider", {"cudnn_conv_algo_search": "DEFAULT"})
         ],
     )
+
+
+def test_synthesize_onnx_directml():
+    pytest.importorskip("onnxruntime_directml")
+    synthesize(inference_type="onnx", onnx_providers=["DmlExecutionProvider"])