mirror of
https://github.com/saymrwulf/onnxruntime.git
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322237f482
### Description Expose `OrtValue` class API as first-class citizen. Make it simular with C++ API. Enable safe direct native memory access. Make string tensor manipulation more efficient. Avoid intermediate structures such as `NamedOnnxValue`, `DisposableNamedOnnxvalue` and etc. Provide more examples with `IOBinding`, although `OrtValue` API potentially makes `IOBinding` redundant for most of scenarios, since `OrtValue` can be created on top of any memory. Run all the pre-trained models now with `OrtValue` API as well. Obsolete `OrtExternalMemory class`. Obsolete IOBinding API that takes `FixedBufferOnnxValue`. ### Motivation and Context Make the API efficient and uniform with C++. This aspires to address: https://github.com/microsoft/onnxruntime/issues/14918 https://github.com/microsoft/onnxruntime/issues/15381 Cc: @Craigacp
549 lines
25 KiB
C#
549 lines
25 KiB
C#
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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using System;
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using System.IO;
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using Xunit;
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using Xunit.Abstractions;
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#if __TRAINING_ENABLED_NATIVE_BUILD__
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using Microsoft.ML.OnnxRuntime.Tensors;
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using System.Collections.Generic;
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using System.Linq;
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#endif
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// This runs in a separate package built from EndToEndTests
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// and for this reason it can not refer to non-public members
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// of Onnxruntime package
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namespace Microsoft.ML.OnnxRuntime.Tests
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{
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public partial class TrainingTest
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{
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private readonly ITestOutputHelper output;
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public TrainingTest(ITestOutputHelper o)
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{
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this.output = o;
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}
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#if !__TRAINING_ENABLED_NATIVE_BUILD__
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[Fact(DisplayName = "TestLoadCheckpointThrows")]
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public void TestLoadCheckpointThrows()
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{
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string path = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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var ex = Assert.Throws<InvalidOperationException>(() => { var opt = CheckpointState.LoadCheckpoint(path); });
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Assert.Contains("Please install the Microsoft.ML.OnnxRuntime.Training NuGet package.", ex.Message);
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}
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#endif
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#if __TRAINING_ENABLED_NATIVE_BUILD__
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[Fact(DisplayName = "TestLoadCheckpoint")]
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public void TestLoadCheckpoint()
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{
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string path = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var opt = CheckpointState.LoadCheckpoint(path))
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{
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Assert.NotNull(opt);
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}
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}
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[Fact(DisplayName = "TestCreateTrainingSession")]
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public void TestCreateTrainingSession()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, optimizerPath);
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cleanUp.Add(trainingSession);
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}
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}
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[Fact(DisplayName = "TestTrainingSessionTrainStep")]
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public void TestTrainingSessionTrainStep()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, optimizerPath);
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cleanUp.Add(trainingSession);
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float[] expectedOutput = TestDataLoader.LoadTensorFromFile("loss_1.out");
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var expectedOutputDimensions = new int[] { 1 };
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float[] input = TestDataLoader.LoadTensorFromFile("input-0.in");
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Int32[] labels = { 1, 1 };
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// Run inference with pinned inputs and pinned outputs
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using (DisposableListTest<FixedBufferOnnxValue> pinnedInputs = new DisposableListTest<FixedBufferOnnxValue>(),
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pinnedOutputs = new DisposableListTest<FixedBufferOnnxValue>())
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{
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var memInfo = OrtMemoryInfo.DefaultInstance; // CPU
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// Create inputs
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long[] inputShape = { 2, 784 };
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pinnedInputs.Add(FixedBufferOnnxValue.CreateFromMemory<float>(memInfo, input,
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TensorElementType.Float, inputShape, input.Length * sizeof(float)));
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long[] labelsShape = { 2 };
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pinnedInputs.Add(FixedBufferOnnxValue.CreateFromMemory<Int32>(memInfo, labels,
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TensorElementType.Int32, labelsShape, labels.Length * sizeof(Int32)));
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// Prepare output buffer
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long[] outputShape = { };
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float[] outputBuffer = new float[expectedOutput.Length];
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pinnedOutputs.Add(FixedBufferOnnxValue.CreateFromMemory<float>(memInfo, outputBuffer,
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TensorElementType.Float, outputShape, outputBuffer.Length * sizeof(float)));
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trainingSession.TrainStep(pinnedInputs, pinnedOutputs);
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Assert.Equal(expectedOutput, outputBuffer, new FloatComparer());
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}
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}
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}
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void RunTrainStep(TrainingSession trainingSession)
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{
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float[] expectedOutput = TestDataLoader.LoadTensorFromFile("loss_1.out");
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var expectedOutputDimensions = new int[] { 1 };
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float[] input = TestDataLoader.LoadTensorFromFile("input-0.in");
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Int32[] labels = { 1, 1 };
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// Run inference with pinned inputs and pinned outputs
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using (DisposableListTest<FixedBufferOnnxValue> pinnedInputs = new DisposableListTest<FixedBufferOnnxValue>())
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{
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var memInfo = OrtMemoryInfo.DefaultInstance; // CPU
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// Create inputs
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long[] inputShape = { 2, 784 };
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pinnedInputs.Add(FixedBufferOnnxValue.CreateFromMemory<float>(memInfo, input,
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TensorElementType.Float, inputShape, input.Length * sizeof(float)));
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long[] labelsShape = { 2 };
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pinnedInputs.Add(FixedBufferOnnxValue.CreateFromMemory<Int32>(memInfo, labels,
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TensorElementType.Int32, labelsShape, labels.Length * sizeof(Int32)));
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var outputs = trainingSession.TrainStep(pinnedInputs);
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trainingSession.LazyResetGrad();
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outputs = trainingSession.TrainStep(pinnedInputs);
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var outputBuffer = outputs.ElementAtOrDefault(0);
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Assert.Equal("onnx::loss::21273", outputBuffer.Name);
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Assert.Equal(OnnxValueType.ONNX_TYPE_TENSOR, outputBuffer.ValueType);
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Assert.Equal(TensorElementType.Float, outputBuffer.ElementType);
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var outLabelTensor = outputBuffer.AsTensor<float>();
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Assert.NotNull(outLabelTensor);
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Assert.Equal(expectedOutput, outLabelTensor.ToArray(), new FloatComparer());
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}
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}
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[Fact(DisplayName = "TestTrainingSessionTrainStepOrtOutput")]
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public void TestTrainingSessionTrainStepOrtOutput()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, optimizerPath);
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cleanUp.Add(trainingSession);
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RunTrainStep(trainingSession);
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}
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}
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[Fact(DisplayName = "TestSaveCheckpoint")]
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public void TestSaveCheckpoint()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, optimizerPath);
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cleanUp.Add(trainingSession);
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// Save checkpoint
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string savedCheckpointPath = Path.Combine(Directory.GetCurrentDirectory(), "saved_checkpoint.ckpt");
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CheckpointState.SaveCheckpoint(state, savedCheckpointPath, true);
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// Load checkpoint and run train step
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var loadedState = CheckpointState.LoadCheckpoint(savedCheckpointPath);
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cleanUp.Add(loadedState);
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var newTrainingSession = new TrainingSession(loadedState, trainingPath, optimizerPath);
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cleanUp.Add(newTrainingSession);
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RunTrainStep(newTrainingSession);
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}
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}
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[Fact(DisplayName = "TestTrainingSessionOptimizerStep")]
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public void TestTrainingSessionOptimizerStep()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, optimizerPath);
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cleanUp.Add(trainingSession);
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float[] expectedOutput_1 = TestDataLoader.LoadTensorFromFile("loss_1.out");
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float[] expectedOutput_2 = TestDataLoader.LoadTensorFromFile("loss_2.out");
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var expectedOutputDimensions = new int[] { 1 };
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float[] input = TestDataLoader.LoadTensorFromFile("input-0.in");
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Int32[] labels = { 1, 1 };
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// Run train step with pinned inputs and pinned outputs
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using (DisposableListTest<FixedBufferOnnxValue> pinnedInputs = new DisposableListTest<FixedBufferOnnxValue>(),
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pinnedOutputs = new DisposableListTest<FixedBufferOnnxValue>())
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{
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var memInfo = OrtMemoryInfo.DefaultInstance; // CPU
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// Create inputs
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long[] inputShape = { 2, 784 };
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pinnedInputs.Add(FixedBufferOnnxValue.CreateFromMemory<float>(memInfo, input,
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TensorElementType.Float, inputShape, input.Length * sizeof(float)));
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long[] labelsShape = { 2 };
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pinnedInputs.Add(FixedBufferOnnxValue.CreateFromMemory<Int32>(memInfo, labels,
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TensorElementType.Int32, labelsShape, labels.Length * sizeof(Int32)));
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// Prepare output buffer
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long[] outputShape = { };
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float[] outputBuffer = new float[expectedOutput_1.Length];
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pinnedOutputs.Add(FixedBufferOnnxValue.CreateFromMemory<float>(memInfo, outputBuffer,
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TensorElementType.Float, outputShape, outputBuffer.Length * sizeof(float)));
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trainingSession.TrainStep(pinnedInputs, pinnedOutputs);
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Assert.Equal(expectedOutput_1, outputBuffer, new FloatComparer());
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trainingSession.LazyResetGrad();
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trainingSession.TrainStep(pinnedInputs, pinnedOutputs);
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Assert.Equal(expectedOutput_1, outputBuffer, new FloatComparer());
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trainingSession.OptimizerStep();
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trainingSession.TrainStep(pinnedInputs, pinnedOutputs);
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Assert.Equal(expectedOutput_2, outputBuffer, new FloatComparer());
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}
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}
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}
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[Fact(DisplayName = "TestTrainingSessionSetLearningRate")]
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public void TestTrainingSessionSetLearningRate()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, optimizerPath);
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cleanUp.Add(trainingSession);
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float learningRate = 0.245f;
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trainingSession.SetLearningRate(learningRate);
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var actualLearningRate = trainingSession.GetLearningRate();
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Assert.Equal(learningRate, actualLearningRate);
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}
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}
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[Fact(DisplayName = "TestTrainingSessionLinearLRScheduler")]
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public void TestTrainingSessionLinearLRScheduler()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, optimizerPath);
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cleanUp.Add(trainingSession);
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float learningRate = 0.1f;
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trainingSession.RegisterLinearLRScheduler(2, 4, learningRate);
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RunTrainStep(trainingSession);
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trainingSession.OptimizerStep();
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trainingSession.SchedulerStep();
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Assert.Equal(0.05f, trainingSession.GetLearningRate());
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trainingSession.OptimizerStep();
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trainingSession.SchedulerStep();
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Assert.Equal(0.1f, trainingSession.GetLearningRate());
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trainingSession.OptimizerStep();
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trainingSession.SchedulerStep();
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Assert.Equal(0.05f, trainingSession.GetLearningRate());
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trainingSession.OptimizerStep();
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trainingSession.SchedulerStep();
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Assert.Equal(0.0f, trainingSession.GetLearningRate());
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}
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}
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[Fact(DisplayName = "TestTrainingSessionExportModelForInferencing")]
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public void TestTrainingSessionExportModelForInferencing()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string evalPath = Path.Combine(Directory.GetCurrentDirectory(), "eval_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, evalPath, optimizerPath);
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cleanUp.Add(trainingSession);
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var graphOutputs = new List<string>(){"output-0"};
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string inferencePath = Path.Combine(Directory.GetCurrentDirectory(), "inference_model.onnx");
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trainingSession.ExportModelForInferencing(inferencePath, graphOutputs);
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Assert.True(File.Exists(inferencePath));
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}
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}
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[Fact(DisplayName = "TestCheckpointStateAddProperty")]
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public void TestCheckpointStateAddProperty()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string propertyName = "days in a week";
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state.AddProperty(propertyName, (long)7);
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var value = state.GetProperty(propertyName);
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Assert.True(value is long);
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Assert.Equal((long)7, value);
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}
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}
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[Fact(DisplayName = "TestCheckpointStateAddFloatProperty")]
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public void TestCheckpointStateAddFloatProperty()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string propertyName = "pi";
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state.AddProperty(propertyName, (float)3.14);
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var value = state.GetProperty(propertyName);
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Assert.True(value is float);
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Assert.Equal((float)3.14, value);
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}
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}
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[Fact(DisplayName = "TestCheckpointStateAddStringProperty")]
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public void TestCheckpointStateAddStringProperty()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string propertyName = "best ai framework";
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state.AddProperty(propertyName, "onnxruntime");
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var value = state.GetProperty(propertyName);
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Assert.True(value is string);
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Assert.Equal("onnxruntime", value);
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}
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}
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[Fact(DisplayName = "TestTrainModelInputNames")]
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public void TestTrainModelInputNames()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, optimizerPath);
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cleanUp.Add(trainingSession);
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var inputNames = trainingSession.InputNames(true);
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Assert.True(inputNames.Count == 2);
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Assert.Equal("input-0", inputNames[0]);
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Assert.Equal("labels", inputNames[1]);
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}
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}
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[Fact(DisplayName = "TestEvalModelInputNames")]
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public void TestEvalModelInputNames()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string evalPath = Path.Combine(Directory.GetCurrentDirectory(), "eval_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, evalPath, optimizerPath);
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cleanUp.Add(trainingSession);
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var inputNames = trainingSession.InputNames(false);
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Assert.True(inputNames.Count == 2);
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Assert.Equal("input-0", inputNames[0]);
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Assert.Equal("labels", inputNames[1]);
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}
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}
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[Fact(DisplayName = "TestTrainModelOutputNames")]
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public void TestTrainModelOutputNames()
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{
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string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
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using (var cleanUp = new DisposableListTest<IDisposable>())
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{
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var state = CheckpointState.LoadCheckpoint(checkpointPath);
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cleanUp.Add(state);
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Assert.NotNull(state);
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string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
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string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
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var trainingSession = new TrainingSession(state, trainingPath, optimizerPath);
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cleanUp.Add(trainingSession);
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var outputNames = trainingSession.OutputNames(true);
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Assert.Single(outputNames);
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Assert.Equal("onnx::loss::21273", outputNames[0]);
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}
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}
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[Fact(DisplayName = "TestEvalModelOutputNames")]
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public void TestEvalModelOutputNames()
|
|
{
|
|
string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
|
|
using (var cleanUp = new DisposableListTest<IDisposable>())
|
|
{
|
|
var state = CheckpointState.LoadCheckpoint(checkpointPath);
|
|
cleanUp.Add(state);
|
|
Assert.NotNull(state);
|
|
string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
|
|
string evalPath = Path.Combine(Directory.GetCurrentDirectory(), "eval_model.onnx");
|
|
string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
|
|
|
|
var trainingSession = new TrainingSession(state, trainingPath, evalPath, optimizerPath);
|
|
cleanUp.Add(trainingSession);
|
|
|
|
var outputNames = trainingSession.OutputNames(false);
|
|
|
|
Assert.Single(outputNames);
|
|
Assert.Equal("onnx::loss::21273", outputNames[0]);
|
|
}
|
|
}
|
|
|
|
[Fact(DisplayName = "TestToBuffer")]
|
|
public void TestToBuffer()
|
|
{
|
|
string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
|
|
using (var cleanUp = new DisposableListTest<IDisposable>())
|
|
{
|
|
var state = CheckpointState.LoadCheckpoint(checkpointPath);
|
|
cleanUp.Add(state);
|
|
Assert.NotNull(state);
|
|
string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
|
|
string evalPath = Path.Combine(Directory.GetCurrentDirectory(), "eval_model.onnx");
|
|
string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
|
|
|
|
var trainingSession = new TrainingSession(state, trainingPath, evalPath, optimizerPath);
|
|
cleanUp.Add(trainingSession);
|
|
|
|
var buffer = trainingSession.ToBuffer(true);
|
|
cleanUp.Add(buffer);
|
|
}
|
|
}
|
|
|
|
[Fact(DisplayName = "TestFromBuffer")]
|
|
public void TestFromBuffer()
|
|
{
|
|
string checkpointPath = Path.Combine(Directory.GetCurrentDirectory(), "checkpoint.ckpt");
|
|
using (var cleanUp = new DisposableListTest<IDisposable>())
|
|
{
|
|
var state = CheckpointState.LoadCheckpoint(checkpointPath);
|
|
cleanUp.Add(state);
|
|
Assert.NotNull(state);
|
|
string trainingPath = Path.Combine(Directory.GetCurrentDirectory(), "training_model.onnx");
|
|
string evalPath = Path.Combine(Directory.GetCurrentDirectory(), "eval_model.onnx");
|
|
string optimizerPath = Path.Combine(Directory.GetCurrentDirectory(), "adamw.onnx");
|
|
|
|
var trainingSession = new TrainingSession(state, trainingPath, evalPath, optimizerPath);
|
|
cleanUp.Add(trainingSession);
|
|
|
|
var buffer = trainingSession.ToBuffer(true);
|
|
cleanUp.Add(buffer);
|
|
|
|
trainingSession.FromBuffer(buffer);
|
|
}
|
|
}
|
|
|
|
[Fact(DisplayName = "TestSetSeed")]
|
|
public void TestSetSeed()
|
|
{
|
|
TrainingUtils.SetSeed(8888);
|
|
}
|
|
|
|
internal class FloatComparer : IEqualityComparer<float>
|
|
{
|
|
private float atol = 1e-3f;
|
|
private float rtol = 1.7e-2f;
|
|
|
|
public bool Equals(float x, float y)
|
|
{
|
|
return Math.Abs(x - y) <= (atol + rtol * Math.Abs(y));
|
|
}
|
|
public int GetHashCode(float x)
|
|
{
|
|
return x.GetHashCode();
|
|
}
|
|
}
|
|
#endif
|
|
}
|
|
}
|