+ /// using OrtValue x = OrtValue.CreateTensorValueFromMemory(...);
+ /// using OrtValue label = OrtValue.CreateTensorValueFromMemory(...);
+ /// List inputValues = new List { x, label };
+ /// using (var loss = trainingSession.TrainStep(inputValues))
+ /// {
+ /// // process output values
+ /// }
+ ///
+ ///
+ /// using OrtValue x = OrtValue.CreateTensorValueFromMemory(...);
+ /// using OrtValue label = OrtValue.CreateTensorValueFromMemory(...);
+ /// List inputValues = new List { x, label };
+ /// using (var loss = trainingSession.EvalSteps(inputValues))
+ /// {
+ /// // process output values
+ /// }
+ ///
+ /// Called from JNI.
*
* @param shape The tensor shape.
+ * @param names The dimension names.
* @param typeInt The native type int.
*/
- TensorInfo(long[] shape, int typeInt) {
+ TensorInfo(long[] shape, String[] names, int typeInt) {
this.shape = shape;
+ this.dimensionNames = names;
+ boolean hasNames = false;
+ for (String s : names) {
+ if (!s.isEmpty()) {
+ hasNames = true;
+ break;
+ }
+ }
+ this.hasNames = hasNames;
this.onnxType = OnnxTensorType.mapFromInt(typeInt);
this.type = OnnxJavaType.mapFromOnnxTensorType(this.onnxType);
this.numElements = elementCount(shape);
@@ -206,15 +226,42 @@ public long[] getShape() {
return Arrays.copyOf(shape, shape.length);
}
+ /**
+ * Get a copy of the tensor's named dimensions.
+ *
+ * @return A copof the tensor's named dimensions.
+ */
+ public String[] getDimensionNames() {
+ return Arrays.copyOf(dimensionNames, dimensionNames.length);
+ }
+
@Override
public String toString() {
- return "TensorInfo(javaType="
- + type.toString()
- + ",onnxType="
- + onnxType.toString()
- + ",shape="
- + Arrays.toString(shape)
- + ")";
+ String output =
+ "TensorInfo(javaType="
+ + type.toString()
+ + ",onnxType="
+ + onnxType.toString()
+ + ",shape="
+ + Arrays.toString(shape);
+ if (hasNames) {
+ output =
+ output
+ + ",dimNames=["
+ + Arrays.stream(dimensionNames)
+ .map(
+ a -> {
+ if (a.isEmpty()) {
+ return "\"\"";
+ } else {
+ return a;
+ }
+ })
+ .collect(Collectors.joining(","))
+ + "]";
+ }
+ output = output + ")";
+ return output;
}
/**
diff --git a/java/src/main/java/ai/onnxruntime/providers/CoreMLFlags.java b/java/src/main/java/ai/onnxruntime/providers/CoreMLFlags.java
index eb124decf75f3..cec3fadf446ca 100644
--- a/java/src/main/java/ai/onnxruntime/providers/CoreMLFlags.java
+++ b/java/src/main/java/ai/onnxruntime/providers/CoreMLFlags.java
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2021, 2023, Oracle and/or its affiliates. All rights reserved.
+ * Copyright (c) 2021, 2024, Oracle and/or its affiliates. All rights reserved.
* Licensed under the MIT License.
*/
package ai.onnxruntime.providers;
@@ -14,7 +14,18 @@ public enum CoreMLFlags implements OrtFlags {
/** Enables CoreML on subgraphs. */
ENABLE_ON_SUBGRAPH(2), // COREML_FLAG_ENABLE_ON_SUBGRAPH(0x002)
/** Only enable usage of CoreML if the device has an Apple Neural Engine. */
- ONLY_ENABLE_DEVICE_WITH_ANE(4); // COREML_FLAG_ONLY_ENABLE_DEVICE_WITH_ANE(0x004),
+ ONLY_ENABLE_DEVICE_WITH_ANE(4), // COREML_FLAG_ONLY_ENABLE_DEVICE_WITH_ANE(0x004)
+ /**
+ * Only allow CoreML EP to take nodes with inputs with static shapes. By default it will also
+ * allow inputs with dynamic shapes. However, the performance may be negatively impacted if inputs
+ * have dynamic shapes.
+ */
+ ONLY_ALLOW_STATIC_INPUT_SHAPES(8), // COREML_FLAG_ONLY_ALLOW_STATIC_INPUT_SHAPES(0x008)
+ /**
+ * Create an MLProgram. By default it will create a NeuralNetwork model. Requires Core ML 5 or
+ * later.
+ */
+ CREATE_MLPROGRAM(16); // COREML_FLAG_CREATE_MLPROGRAM(0x010)
/** The native value of the enum. */
public final int value;
diff --git a/java/src/main/java/ai/onnxruntime/providers/StringConfigProviderOptions.java b/java/src/main/java/ai/onnxruntime/providers/StringConfigProviderOptions.java
index 02207b2949e54..961163035c9a6 100644
--- a/java/src/main/java/ai/onnxruntime/providers/StringConfigProviderOptions.java
+++ b/java/src/main/java/ai/onnxruntime/providers/StringConfigProviderOptions.java
@@ -32,6 +32,7 @@ protected StringConfigProviderOptions(long nativeHandle) {
* @throws OrtException If the addition failed.
*/
public void add(String key, String value) throws OrtException {
+ checkClosed();
Objects.requireNonNull(key, "Key must not be null");
Objects.requireNonNull(value, "Value must not be null");
options.put(key, value);
diff --git a/java/src/main/native/OrtJniUtil.c b/java/src/main/native/OrtJniUtil.c
index 879ba8a310618..7b26291581395 100644
--- a/java/src/main/native/OrtJniUtil.c
+++ b/java/src/main/native/OrtJniUtil.c
@@ -342,7 +342,6 @@ jobject convertToTensorInfo(JNIEnv *jniEnv, const OrtApi * api, const OrtTensorT
if (code != ORT_OK) {
return NULL;
}
- //printf("numDim %d\n",numDim);
int64_t* dimensions = (int64_t*) malloc(sizeof(int64_t)*numDim);
code = checkOrtStatus(jniEnv, api, api->GetDimensions(info, dimensions, numDim));
if (code != ORT_OK) {
@@ -358,12 +357,31 @@ jobject convertToTensorInfo(JNIEnv *jniEnv, const OrtApi * api, const OrtTensorT
free(dimensions);
dimensions = NULL;
+ // Create the string array for the names.
+ const char** dimensionNames = (const char**) malloc(sizeof(char*)*numDim);
+ if (dimensionNames == NULL) {
+ throwOrtException(jniEnv, 1, "Not enough memory");
+ return NULL;
+ }
+ code = checkOrtStatus(jniEnv, api, api->GetSymbolicDimensions(info, dimensionNames, numDim));
+ if (code != ORT_OK) {
+ // extraction failed, exception has been thrown, return to Java.
+ free(dimensionNames);
+ return NULL;
+ }
+ jclass stringClazz = (*jniEnv)->FindClass(jniEnv, "java/lang/String");
+ jobjectArray names = (*jniEnv)->NewObjectArray(jniEnv, safecast_size_t_to_jsize(numDim), stringClazz, NULL);
+ for (size_t i = 0; i < numDim; i++) {
+ jobject javaName = (*jniEnv)->NewStringUTF(jniEnv, dimensionNames[i]);
+ (*jniEnv)->SetObjectArrayElement(jniEnv, names, safecast_size_t_to_jsize(i), javaName);
+ }
+ free(dimensionNames);
+
// Create the TensorInfo object
static const char *tensorInfoClassName = "ai/onnxruntime/TensorInfo";
jclass clazz = (*jniEnv)->FindClass(jniEnv, tensorInfoClassName);
- jmethodID tensorInfoConstructor = (*jniEnv)->GetMethodID(jniEnv,clazz, "