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[java][DML EP] Modifying dml_provider_factory.h so it can compile as a C header file (#20157)

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### Description
The dml_provider_factory header file can't be used in C programs as it
defines C++ inline operators. This PR rearranges that header file so
that it looks like valid C when used from C, and also makes a couple of
small modifications to the Java code so it correctly binds to the DML EP
at build time.

I'm having some difficulty testing it as I think it's pulling in the old
version of DirectML on my computer and I can't figure out what the
library loading path is in Java to make it look at the recent version I
downloaded. So the test I added fails with:

```
InferenceTest > testDirectML() FAILED
    ai.onnxruntime.OrtException: Error code - ORT_RUNTIME_EXCEPTION - message: Exception during initialization: <path-to-ort>\onnxruntime\core\providers\dml\DmlExecutionProvider\src\AbiCustomRegistry.cpp(518)\onnxruntime.dll!00007FFF74819333: (caller: 00007FFF74793509) Exception(3) tid(4f58) 80070057 The parameter is incorrect.
        at app//ai.onnxruntime.OrtSession.createSession(Native Method)
        at app//ai.onnxruntime.OrtSession.<init>(OrtSession.java:74)
        at app//ai.onnxruntime.OrtEnvironment.createSession(OrtEnvironment.java:236)
        at app//ai.onnxruntime.OrtEnvironment.createSession(OrtEnvironment.java:221)
        at app//ai.onnxruntime.InferenceTest.openSessionSqueezeNet(InferenceTest.java:1961)
        at app//ai.onnxruntime.InferenceTest.runProvider(InferenceTest.java:665)
        at app//ai.onnxruntime.InferenceTest.testDirectML(InferenceTest.java:657)
```

But it does correctly compile, and this error seems very similar to
other issues with the DML provider when it doesn't like a model due to
the loaded library being old. The test is using the squeezenet file
that's been in the repo since 2019. If someone can help me figure out
how to get the right version of DML in the library path I can test it
more on my end. I tried adding the folder with the new version into the
system path, but I'm not very familiar with Windows' library loading
behaviour.

### Motivation and Context
Fixes #19656 to allow use of the DirectML EP from ORT Java.

cc @martinb35
This commit is contained in:
Adam Pocock 2024-04-02 00:58:50 -04:00 committed by GitHub
parent 3979f53aa4
commit 262b6bd3b7
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
4 changed files with 33 additions and 9 deletions
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30
include/onnxruntime/core/providers/dml/dml_provider_factory.h
View file

@ -27,14 +27,8 @@ typedef struct IDMLDevice IDMLDevice;
#include "onnxruntime_c_api.h"
#ifdef __cplusplus
extern "C" {
#endif
enum OrtDmlPerformancePreference {
Default = 0,
HighPerformance = 1,
MinimumPower = 2
};
extern "C" {
enum OrtDmlDeviceFilter : uint32_t {
#ifdef ENABLE_NPU_ADAPTER_ENUMERATION
@ -54,11 +48,33 @@ inline OrtDmlDeviceFilter& operator|=(OrtDmlDeviceFilter& a, OrtDmlDeviceFilter
inline OrtDmlDeviceFilter& operator&=(OrtDmlDeviceFilter& a, OrtDmlDeviceFilter b) { return (OrtDmlDeviceFilter&)((int&)a &= (int)b); }
inline OrtDmlDeviceFilter& operator^=(OrtDmlDeviceFilter& a, OrtDmlDeviceFilter b) { return (OrtDmlDeviceFilter&)((int&)a ^= (int)b); }
#else
typedef enum OrtDmlDeviceFilter {
#ifdef ENABLE_NPU_ADAPTER_ENUMERATION
Any = 0xffffffff,
Gpu = 1 << 0,
Npu = 1 << 1,
#else
Gpu = 1 << 0,
#endif
} OrtDmlDeviceFilter;
#endif
typedef enum OrtDmlPerformancePreference {
Default = 0,
HighPerformance = 1,
MinimumPower = 2
} OrtDmlPerformancePreference;
struct OrtDmlDeviceOptions {
OrtDmlPerformancePreference Preference;
OrtDmlDeviceFilter Filter;
};
typedef struct OrtDmlDeviceOptions OrtDmlDeviceOptions;
/**
* [[deprecated]]
* This export is deprecated.

2
java/build.gradle
View file

@ -185,7 +185,7 @@ test {
if (cmakeBuildDir != null) {
workingDir cmakeBuildDir
}
systemProperties System.getProperties().subMap(['USE_CUDA', 'USE_ROCM', 'USE_TENSORRT', 'USE_DNNL', 'USE_OPENVINO', 'USE_COREML', 'JAVA_FULL_TEST', 'ENABLE_TRAINING_APIS'])
systemProperties System.getProperties().subMap(['USE_CUDA', 'USE_ROCM', 'USE_TENSORRT', 'USE_DNNL', 'USE_OPENVINO', 'USE_COREML', 'USE_DML', 'JAVA_FULL_TEST', 'ENABLE_TRAINING_APIS'])
testLogging {
events "passed", "skipped", "failed"
showStandardStreams = true

2
java/src/main/native/ai_onnxruntime_OrtSession_SessionOptions.c
View file

@ -630,7 +630,7 @@ JNIEXPORT void JNICALL Java_ai_onnxruntime_OrtSession_00024SessionOptions_addMIG
JNIEXPORT void JNICALL Java_ai_onnxruntime_OrtSession_00024SessionOptions_addDirectML
(JNIEnv * jniEnv, jobject jobj, jlong apiHandle, jlong handle, jint deviceID) {
(void)jobj;
#ifdef USE_DIRECTML
#ifdef USE_DML
checkOrtStatus(jniEnv,(const OrtApi*)apiHandle,OrtSessionOptionsAppendExecutionProvider_DML((OrtSessionOptions*) handle, deviceID));
#else
(void)apiHandle;(void)handle;(void)deviceID; // Parameters used when DirectML is defined.

8
java/src/test/java/ai/onnxruntime/InferenceTest.java
View file

@ -651,6 +651,12 @@ public class InferenceTest {
runProvider(OrtProvider.CORE_ML);
}
@Test
@EnabledIfSystemProperty(named = "USE_DML", matches = "1")
public void testDirectML() throws OrtException {
runProvider(OrtProvider.DIRECT_ML);
}
private void runProvider(OrtProvider provider) throws OrtException {
EnumSet<OrtProvider> providers = OrtEnvironment.getAvailableProviders();
assertTrue(providers.size() > 1);
@ -1926,6 +1932,8 @@ public class InferenceTest {
options.addNnapi();
break;
case DIRECT_ML:
options.setMemoryPatternOptimization(false);
options.setExecutionMode(ExecutionMode.SEQUENTIAL);
options.addDirectML(0);
break;
case ACL: