/// <summary>
/// This method will create an instance of DisposableNamedOnnxValue that will own ortSequenceValue
/// an all disposable native objects that are elements of the sequence
/// </summary>
/// <param name="name"></param>
/// <param name="ortValueSequence">ortValueElement that has native sequence</param>
/// <param name="allocator"> used allocator</param>
/// <returns>DisposableNamedOnnxValue</returns>
private static DisposableNamedOnnxValue DisposableNamedOnnxValueFromSequence(string name, OrtValue ortValueSequence, OrtAllocator allocator)
{
DisposableNamedOnnxValue result = null;
IntPtr count;
NativeApiStatus.VerifySuccess(NativeMethods.OrtGetValueCount(ortValueSequence.Handle, out count));
var sequence = new DisposableList <DisposableNamedOnnxValue>(count.ToInt32());
try
{
for (int i = 0; i < count.ToInt32(); i++)
{
IntPtr nativeOnnxValueSeq;
NativeApiStatus.VerifySuccess(NativeMethods.OrtGetValue(ortValueSequence.Handle, i, allocator.Pointer, out nativeOnnxValueSeq));
using (var ortValueElement = new OrtValue(nativeOnnxValueSeq))
{
// Will take ownership or throw
sequence.Add(CreateFromOrtValue(string.Empty, ortValueElement, allocator));
}
}
// NativeOrtValueCollectionOwner will take ownership of ortValueSequence and will make sure sequence
// is also disposed.
var nativeCollectionManager = new NativeOrtValueCollectionOwner(ortValueSequence, sequence);
result = new DisposableNamedOnnxValue(name, sequence, OnnxValueType.ONNX_TYPE_SEQUENCE, TensorElementType.DataTypeMax, nativeCollectionManager);
}
catch (Exception)
{
sequence.Dispose();
throw;
}
return(result);
}
/// <summary>
/// This method return a collection of DisposableNamedOnnxValue as in other interfaces
/// Query names from OrtIoBinding object and pair then with the array of OrtValues returned
/// from OrtIoBinding.GetOutputValues()
///
/// </summary>
/// <param name="runOptions">RunOptions</param>
/// <param name="ioBinding">OrtIoBinding instance with bindings</param>
/// <param name="names">optional parameter. If you already know the names of the outputs you can save a native
/// call to retrieve output names. They will be paired with the returned OrtValues and combined into DisposbleNamedOnnxValues.
/// Otherwise, the method will retrieve output names from the OrtIoBinding instance.
/// It is an error if you supply a different number of names than the returned outputs</param>
public IDisposableReadOnlyCollection <DisposableNamedOnnxValue> RunWithBindingAndNames(RunOptions runOptions, OrtIoBinding ioBinding, string[] names = null)
{
NativeApiStatus.VerifySuccess(NativeMethods.OrtRunWithBinding(Handle, runOptions.Handle, ioBinding.Handle));
using (var ortValues = ioBinding.GetOutputValues())
{
string[] outputNames = names;
if (outputNames == null)
{
outputNames = ioBinding.GetOutputNames();
}
if (outputNames.Length != ortValues.Count)
{
throw new OnnxRuntimeException(ErrorCode.InvalidArgument,
"Number of specified names: " + names.Length + " does not match the output number: " +
ortValues.Count);
}
var result = new DisposableList <DisposableNamedOnnxValue>(outputNames.Length);
try
{
for (int i = 0; i < outputNames.Length; ++i)
{
var ortValue = ortValues.ElementAt(i);
result.Add(DisposableNamedOnnxValue.CreateTensorFromOnnxValue(outputNames[i], ortValue.Handle));
ortValue.Disown();
}
} catch (Exception e)
{
result.Dispose();
throw e;
}
return(result);
}
}
internal static DisposableNamedOnnxValue CreateFromOrtValue(string name, OrtValue ortValue, OrtAllocator allocator)
{
DisposableNamedOnnxValue result = null;
IntPtr valueType;
NativeApiStatus.VerifySuccess(NativeMethods.OrtGetValueType(ortValue.Handle, out valueType));
OnnxValueType onnxValueType = (OnnxValueType)valueType;
switch (onnxValueType)
{
case OnnxValueType.ONNX_TYPE_TENSOR:
result = CreateTensorFromOnnxValue(name, ortValue);
break;
case OnnxValueType.ONNX_TYPE_SEQUENCE:
result = DisposableNamedOnnxValueFromSequence(name, ortValue, allocator);
break;
case OnnxValueType.ONNX_TYPE_MAP:
result = DisposableNamedOnnxValueFromNativeMap(name, ortValue, allocator);
break;
default:
throw new NotSupportedException("OnnxValueType : " + onnxValueType + " is not supported");
}
return(result);
}
public unsafe void Run(
IReadOnlyCollection <NamedOnnxValue> inputs,
IReadOnlyCollection <string> outputNames,
RunOptions options,
IList <DisposableNamedOnnxValue> result)
{
string[] outputNamesArray = GetOutputNames((IReadOnlyList <string>)outputNames);
var outputValueArray = stackalloc IntPtr[outputNamesArray.Length];
Run(inputs, options, outputNamesArray, outputValueArray);
try
{
for (uint i = 0; i < outputNamesArray.Length; i++)
{
result.Add(DisposableNamedOnnxValue.CreateFromOnnxValue(outputNamesArray[i], outputValueArray[i]));
}
}
catch (OnnxRuntimeException e)
{
// clean up the individual output tensors if it is not null;
OrtReleaseValues(outputValueArray, outputNamesArray.Length);
throw e;
}
}
/// <summary>
/// Will extract keys and values from the map and create a DisposableNamedOnnxValue from it
/// </summary>
/// <param name="name">name of the output</param>
/// <param name="ortValueMap">ortValue that represents a map.
/// This function does not take ownership of the map as it we copy all keys an values into a dictionary. We let the caller dispose of it</param>
/// <param name="allocator"></param>
/// <returns>DisposableNamedOnnxValue</returns>
private static DisposableNamedOnnxValue DisposableNamedOnnxValueFromNativeMap(string name, OrtValue ortValueMap, OrtAllocator allocator)
{
DisposableNamedOnnxValue result = null;
// Map processing is currently not recursing. It is assumed to contain
// only primitive types and strings tensors. No sequences or maps.
// The data is being copied to a dictionary and all ortValues are being disposed.
// not mapped for client consumption.
using (var cleanUpList = new DisposableList <IDisposable>())
{
// Take possession of the map ortValueElement
IntPtr nativeOnnxValueMapKeys = IntPtr.Zero;
NativeApiStatus.VerifySuccess(NativeMethods.OrtGetValue(ortValueMap.Handle, 0, allocator.Pointer, out nativeOnnxValueMapKeys));
var ortValueKeys = new OrtValue(nativeOnnxValueMapKeys);
cleanUpList.Add(ortValueKeys);
IntPtr nativeOnnxValueMapValues = IntPtr.Zero;
NativeApiStatus.VerifySuccess(NativeMethods.OrtGetValue(ortValueMap.Handle, 1, allocator.Pointer, out nativeOnnxValueMapValues));
var ortValueValues = new OrtValue(nativeOnnxValueMapValues);
cleanUpList.Add(ortValueValues);
IntPtr typeAndShape = IntPtr.Zero;
NativeApiStatus.VerifySuccess(NativeMethods.OrtGetTensorTypeAndShape(nativeOnnxValueMapKeys, out typeAndShape));
TensorElementType elemType = TensorElementType.DataTypeMax;
try
{
IntPtr el_type;
NativeApiStatus.VerifySuccess(NativeMethods.OrtGetTensorElementType(typeAndShape, out el_type));
elemType = (TensorElementType)el_type;
}
finally
{
NativeMethods.OrtReleaseTensorTypeAndShapeInfo(typeAndShape);
}
/// XXX: This code always assumes that the value type is float and makes no checks
/// similar to that of the key. Also Map type in general can also be another sequence or map,
/// not just a tensor
switch (elemType)
{
case TensorElementType.Int64:
result = DisposableNamedOnnxValueFromNativeMapElements <Int64, float>(string.Empty, ortValueKeys, ortValueValues);
break;
case TensorElementType.String:
result = DisposableNamedOnnxValueFromNativeMapElements <string, float>(string.Empty, ortValueKeys, ortValueValues);
break;
default:
throw new NotSupportedException("Map of element type: " + elemType + " is not supported");
}
}
return(result);
}
IDisposableReadOnlyCollection <DisposableNamedOnnxValue> CreateDisposableResult(List <OrtValue> ortValues,
IReadOnlyCollection <string> outputNames)
{
var result = new DisposableList <DisposableNamedOnnxValue>(outputNames.Count);
try
{
for (int i = 0; i < ortValues.Count; i++)
{
var ortValue = ortValues[i];
result.Add(DisposableNamedOnnxValue.CreateFromOrtValue(outputNames.ElementAt(i), ortValue));
}
}
catch (OnnxRuntimeException e)
{
result.Dispose();
throw e;
}
return(result);
}
/// <summary>
/// Runs the loaded model for the given inputs, and fetches the specified outputs in <paramref name="outputNames"/>. Uses the given RunOptions for this run.
/// </summary>
/// <param name="inputNames">Specify a collection of string that indicates the input names. Should match <paramref name="inputValues"/>.</param>
/// <param name="inputValues">Specify a collection of <see cref="FixedBufferOnnxValue"/> that indicates the input values.</param>
/// <param name="outputNames">Specify a collection of string that indicates the output names to fetch.</param>
/// <param name="options"></param>
/// <returns>Output Tensors in a Collection of NamedOnnxValue. User must dispose the output.</returns>
public IDisposableReadOnlyCollection <DisposableNamedOnnxValue> Run(
IReadOnlyCollection <string> inputNames,
IReadOnlyCollection <FixedBufferOnnxValue> inputValues,
IReadOnlyCollection <string> outputNames,
RunOptions options)
{
if (inputNames.Count != inputValues.Count)
{
throw new ArgumentException($"Length of {nameof(inputNames)} ({inputNames.Count}) must match that of {nameof(inputValues)} ({inputValues.Count}).");
}
// prepare inputs
string[] inputNamesArray = inputNames as string[] ?? inputNames.ToArray();
IntPtr[] inputValuesArray = new IntPtr[inputNames.Count];
int inputIndex = 0;
foreach (var input in inputValues)
{
inputValuesArray[inputIndex] = input.Value;
inputIndex++;
}
// prepare outputs
string[] outputNamesArray = outputNames as string[] ?? outputNames.ToArray();
IntPtr[] outputValuesArray = new IntPtr[outputNames.Count];
IntPtr status = NativeMethods.OrtRun(
_nativeHandle,
options.Handle,
inputNamesArray,
inputValuesArray,
(UIntPtr)inputNames.Count,
outputNamesArray,
(UIntPtr)outputNames.Count,
outputValuesArray /* Empty array is passed in to receive output OrtValue pointers */
);
try
{
NativeApiStatus.VerifySuccess(status);
var result = new DisposableList <DisposableNamedOnnxValue>(outputValuesArray.Length);
for (int i = 0; i < outputValuesArray.Length; i++)
{
result.Add(DisposableNamedOnnxValue.CreateFromOnnxValue(outputNamesArray[i], outputValuesArray[i]));
}
return(result);
}
catch (OnnxRuntimeException e)
{
//clean up the individual output tensors if it is not null;
for (uint i = 0; i < outputValuesArray.Length; i++)
{
if (outputValuesArray[i] != IntPtr.Zero)
{
NativeMethods.OrtReleaseValue(outputValuesArray[i]);
}
}
throw e;
}
}
/// <summary>
/// Runs the loaded model for the given inputs, and fetches the specified outputs in <paramref name="outputNames"/>. Uses the given RunOptions for this run.
/// </summary>
/// <param name="inputs">Specify a collection of <see cref="NamedOnnxValue"/> that indicates the input values.</param>
/// <param name="outputNames">Specify a collection of string that indicates the output names to fetch.</param>
/// <param name="options"></param>
/// <returns>Output Tensors in a Collection of NamedOnnxValue. User must dispose the output.</returns>
public IDisposableReadOnlyCollection <DisposableNamedOnnxValue> Run(IReadOnlyCollection <NamedOnnxValue> inputs, IReadOnlyCollection <string> outputNames, RunOptions options)
{
// prepare inputs
var inputNamesArray = new string[inputs.Count];
var inputValuesArray = new IntPtr[inputs.Count];
var pinnedInputBufferHandles = new System.Buffers.MemoryHandle[inputs.Count];
var disposeInputs = new bool[inputs.Count];
int inputIndex = 0;
foreach (var input in inputs)
{
inputNamesArray[inputIndex] = input.Name;
// create Tensor from the input if feasible, else throw notsupported exception for now
input.ToNativeOnnxValue(
out inputValuesArray[inputIndex],
out pinnedInputBufferHandles[inputIndex],
out disposeInputs[inputIndex]);
inputIndex++;
}
// prepare outputs
string[] outputNamesArray = outputNames as string[] ?? outputNames.ToArray();
IntPtr[] outputValuesArray = new IntPtr[outputNames.Count];
IntPtr status = NativeMethods.OrtRun(
_nativeHandle,
options.Handle,
inputNamesArray,
inputValuesArray,
(UIntPtr)inputs.Count,
outputNamesArray,
(UIntPtr)outputNames.Count,
outputValuesArray /* Empty array is passed in to receive output OrtValue pointers */
);
try
{
NativeApiStatus.VerifySuccess(status);
var result = new DisposableList <DisposableNamedOnnxValue>(outputValuesArray.Length);
for (int i = 0; i < outputValuesArray.Length; i++)
{
result.Add(DisposableNamedOnnxValue.CreateFromOnnxValue(outputNamesArray[i], outputValuesArray[i]));
}
return(result);
}
catch (OnnxRuntimeException e)
{
//clean up the individual output tensors if it is not null;
for (int i = 0; i < outputValuesArray.Length; i++)
{
if (outputValuesArray[i] != IntPtr.Zero)
{
NativeMethods.OrtReleaseValue(outputValuesArray[i]);
}
}
throw e;
}
finally
{
for (int i = 0; i < inputs.Count; i++)
{
if (disposeInputs[i])
{
NativeMethods.OrtReleaseValue(inputValuesArray[i]); // For elementary type Tensors, this should not release the buffer, but should delete the native tensor object.
// For string tensors, this releases the native memory allocated for the tensor, including the buffer
pinnedInputBufferHandles[i].Dispose();
}
}
}
}
/// <summary>
/// Creates an instance of DisposableNamedOnnxValue and takes ownership of ortValueElement
/// on success.
/// </summary>
/// <param name="name">name of the value</param>
/// <param name="ortValue">underlying OrtValue</param>
/// <returns></returns>
internal static DisposableNamedOnnxValue CreateTensorFromOnnxValue(string name, OrtValue ortValue)
{
DisposableNamedOnnxValue result = null;
/* Get Tensor element type */ //TODO: Assumed value is Tensor, need to support non-tensor types in future
IntPtr typeAndShape = IntPtr.Zero;
NativeApiStatus.VerifySuccess(NativeMethods.OrtGetTensorTypeAndShape(ortValue.Handle, out typeAndShape));
TensorElementType elemType = TensorElementType.DataTypeMax;
try
{
IntPtr el_type;
NativeApiStatus.VerifySuccess(NativeMethods.OrtGetTensorElementType(typeAndShape, out el_type));
elemType = (TensorElementType)el_type;
}
finally
{
NativeMethods.OrtReleaseTensorTypeAndShapeInfo(typeAndShape);
}
switch (elemType)
{
case TensorElementType.Float:
result = DisposableNamedOnnxValueFromNativeTensor <float>(name, ortValue);
break;
case TensorElementType.Double:
result = DisposableNamedOnnxValueFromNativeTensor <double>(name, ortValue);
break;
case TensorElementType.Int16:
result = DisposableNamedOnnxValueFromNativeTensor <short>(name, ortValue);
break;
case TensorElementType.UInt16:
result = DisposableNamedOnnxValueFromNativeTensor <ushort>(name, ortValue);
break;
case TensorElementType.Int32:
result = DisposableNamedOnnxValueFromNativeTensor <int>(name, ortValue);
break;
case TensorElementType.UInt32:
result = DisposableNamedOnnxValueFromNativeTensor <uint>(name, ortValue);
break;
case TensorElementType.Int64:
result = DisposableNamedOnnxValueFromNativeTensor <long>(name, ortValue);
break;
case TensorElementType.UInt64:
result = DisposableNamedOnnxValueFromNativeTensor <ulong>(name, ortValue);
break;
case TensorElementType.UInt8:
result = DisposableNamedOnnxValueFromNativeTensor <byte>(name, ortValue);
break;
case TensorElementType.Int8:
result = DisposableNamedOnnxValueFromNativeTensor <sbyte>(name, ortValue);
break;
case TensorElementType.String:
result = DisposableNamedOnnxValueFromNativeTensor <string>(name, ortValue);
break;
case TensorElementType.Bool:
result = DisposableNamedOnnxValueFromNativeTensor <bool>(name, ortValue);
break;
case TensorElementType.Float16:
result = DisposableNamedOnnxValueFromNativeTensor <Float16>(name, ortValue);
break;
case TensorElementType.BFloat16:
result = DisposableNamedOnnxValueFromNativeTensor <BFloat16>(name, ortValue);
break;
default:
throw new NotSupportedException("Tensor of element type: " + elemType + " is not supported");
}
return(result);
}
/// <summary>
/// Runs the loaded model for the given inputs, and fetches the specified outputs in <paramref name="outputNames"/>.
/// </summary>
/// <param name="inputs"></param>
/// <param name="outputNames"></param>
/// <param name="options"></param>
/// <returns>Output Tensors in a Collection of NamedOnnxValue</returns>
//TODO: kept internal until RunOptions is made public
internal IDisposableReadOnlyCollection <DisposableNamedOnnxValue> Run(IReadOnlyCollection <NamedOnnxValue> inputs, IReadOnlyCollection <string> outputNames, RunOptions options)
{
var inputNames = new string[inputs.Count];
var inputTensors = new IntPtr[inputs.Count];
var pinnedBufferHandles = new System.Buffers.MemoryHandle[inputs.Count];
int inputIndex = 0;
foreach (var input in inputs)
{
inputNames[inputIndex] = input.Name;
// create Tensor from the input if feasible, else throw notsupported exception for now
input.ToNativeOnnxValue(out inputTensors[inputIndex], out pinnedBufferHandles[inputIndex]);
inputIndex++;
}
string[] outputNamesArray = outputNames.ToArray();
IntPtr[] outputValueArray = new IntPtr[outputNames.Count];
IntPtr status = NativeMethods.OrtRun(
this._nativeHandle,
IntPtr.Zero, // TODO: use Run options when Run options creation API is available
// Passing null uses the default run options in the C-api
inputNames,
inputTensors,
(UIntPtr)(inputTensors.Length),
outputNamesArray,
(UIntPtr)outputNames.Count,
outputValueArray /* An array of output value pointers. Array must be allocated by the caller */
);
try
{
NativeApiStatus.VerifySuccess(status);
var result = new DisposableList <DisposableNamedOnnxValue>();
for (uint i = 0; i < outputValueArray.Length; i++)
{
result.Add(DisposableNamedOnnxValue.CreateFromOnnxValue(outputNamesArray[i], outputValueArray[i]));
}
return(result);
}
catch (OnnxRuntimeException e)
{
//clean up the individual output tensors if it is not null;
for (uint i = 0; i < outputValueArray.Length; i++)
{
if (outputValueArray[i] != IntPtr.Zero)
{
NativeMethods.OrtReleaseValue(outputValueArray[i]);
}
}
throw e;
}
finally
{
// always unpin the input buffers, and delete the native Onnx value objects
for (int i = 0; i < inputs.Count; i++)
{
NativeMethods.OrtReleaseValue(inputTensors[i]); // this should not release the buffer, but should delete the native tensor object
pinnedBufferHandles[i].Dispose();
}
}
}
/// <summary>
/// Runs the loaded model for the given inputs, and fetches the specified outputs in <paramref name="outputNames". Uses the given RunOptions for this run./>.
/// </summary>
/// <param name="inputs"></param>
/// <param name="outputNames"></param>
/// <param name="options"></param>
/// <returns>Output Tensors in a Collection of NamedOnnxValue. User must dispose the output.</returns>
public IDisposableReadOnlyCollection <DisposableNamedOnnxValue> Run(IReadOnlyCollection <NamedOnnxValue> inputs, IReadOnlyCollection <string> outputNames, RunOptions options)
{
var inputNames = new string[inputs.Count];
var inputTensors = new IntPtr[inputs.Count];
var pinnedBufferHandles = new System.Buffers.MemoryHandle[inputs.Count];
int inputIndex = 0;
foreach (var input in inputs)
{
inputNames[inputIndex] = input.Name;
// create Tensor from the input if feasible, else throw notsupported exception for now
input.ToNativeOnnxValue(out inputTensors[inputIndex],
out pinnedBufferHandles[inputIndex]);
inputIndex++;
}
string[] outputNamesArray = outputNames.ToArray();
IntPtr[] outputValueArray = new IntPtr[outputNames.Count];
IntPtr status = NativeMethods.OrtRun(
this._nativeHandle,
options.Handle,
inputNames,
inputTensors,
(UIntPtr)(inputTensors.Length),
outputNamesArray,
(UIntPtr)outputNames.Count,
outputValueArray /* An array of output value pointers. Array must be allocated by the caller */
);
try
{
NativeApiStatus.VerifySuccess(status);
var result = new DisposableList <DisposableNamedOnnxValue>();
for (uint i = 0; i < outputValueArray.Length; i++)
{
result.Add(DisposableNamedOnnxValue.CreateFromOnnxValue(outputNamesArray[i], outputValueArray[i]));
}
return(result);
}
catch (OnnxRuntimeException e)
{
//clean up the individual output tensors if it is not null;
for (uint i = 0; i < outputValueArray.Length; i++)
{
if (outputValueArray[i] != IntPtr.Zero)
{
NativeMethods.OrtReleaseValue(outputValueArray[i]);
}
}
throw e;
}
finally
{
inputIndex = 0;
foreach (var input in inputs)
{
// For NamedOnnxValue, always unpin the input buffers, and delete the native Onnx value objects
// For DisposableNamedOnnxValue, the user needs to do this by invoking Dispose
if (input.GetType() == typeof(NamedOnnxValue))
{
NativeMethods.OrtReleaseValue(inputTensors[inputIndex]); // For elementary type Tensors, this should not release the buffer, but should delete the native tensor object.
// For string tensors, this releases the native memory allocated for the tensor, including the buffer
pinnedBufferHandles[inputIndex].Dispose();
}
inputIndex++;
}
}
}
