Resolve WES-90 "Integrate signpredictor in courses"
This commit is contained in:
Louis Adriaens
committed by
Jerome Coudron
Jerome Coudron
parent
1a75791d62
commit
746906294b
@@ -0,0 +1,530 @@
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using System;
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using System.Collections.Generic;
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using System.IO;
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using UnityEngine;
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using UnityEngine.Assertions;
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using System.IO.Compression;
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namespace Unity.Barracuda {
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/// <summary>
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/// Test set loading utility
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/// </summary>
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public class TestSet
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{
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private RawTestSet rawTestSet;
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private JSONTestSet jsonTestSet;
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/// <summary>
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/// Create with raw test set
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/// </summary>
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/// <param name="rawTestSet">raw test set</param>
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public TestSet(RawTestSet rawTestSet)
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{
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this.rawTestSet = rawTestSet;
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}
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/// <summary>
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/// Create with JSON test set
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/// </summary>
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/// <param name="jsonTestSet">JSON test set</param>
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public TestSet(JSONTestSet jsonTestSet)
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{
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this.jsonTestSet = jsonTestSet;
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}
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/// <summary>
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/// Create `TestSet`
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/// </summary>
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public TestSet()
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{
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}
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/// <summary>
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/// Check if test set supports named tensors
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/// </summary>
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/// <returns>`true` if named tensors are supported</returns>
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public bool SupportsNames()
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{
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if (rawTestSet != null)
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return false;
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return true;
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}
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/// <summary>
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/// Get output tensor count
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/// </summary>
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/// <returns></returns>
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public int GetOutputCount()
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{
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if (rawTestSet != null)
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return 1;
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return jsonTestSet.outputs.Length;
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}
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/// <summary>
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/// Get output tensor data
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/// </summary>
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/// <param name="idx">tensor index</param>
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/// <returns>tensor data</returns>
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public float[] GetOutputData(int idx = 0)
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{
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if (rawTestSet != null)
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return rawTestSet.labels;
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return jsonTestSet.outputs[idx].data;
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}
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/// <summary>
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/// Get output tensor name
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/// </summary>
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/// <param name="idx">tensor index</param>
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/// <returns>tensor name</returns>
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public string GetOutputName(int idx = 0)
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{
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if (rawTestSet != null)
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return null;
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string name = jsonTestSet.outputs[idx].name;
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return name.EndsWith(":0") ? name.Remove(name.Length - 2) : name;
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}
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/// <summary>
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/// Get input tensor count
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/// </summary>
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/// <returns></returns>
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public int GetInputCount()
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{
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if (rawTestSet != null)
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return 1;
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return jsonTestSet.inputs.Length;
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}
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/// <summary>
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/// Get input tensor name
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/// </summary>
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/// <param name="idx">input tensor index</param>
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/// <returns>tensor name</returns>
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public string GetInputName(int idx = 0)
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{
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if (rawTestSet != null)
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return "";
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string name = jsonTestSet.inputs[idx].name;
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return name.EndsWith(":0") ? name.Remove(name.Length - 2) : name;
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}
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/// <summary>
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/// Get input tensor data
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/// </summary>
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/// <param name="idx">input tensor index</param>
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/// <returns>tensor data</returns>
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public float[] GetInputData(int idx = 0)
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{
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if (rawTestSet != null)
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return rawTestSet.input;
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return jsonTestSet.inputs[idx].data;
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}
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/// <summary>
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/// Get input shape
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/// </summary>
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/// <param name="idx">input tensor index</param>
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/// <returns>input shape</returns>
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public TensorShape GetInputShape(int idx = 0)
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{
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if (rawTestSet != null)
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return new TensorShape(1,rawTestSet.input.Length);
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return new TensorShape(jsonTestSet.inputs[idx].shape.sequenceLength,
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jsonTestSet.inputs[idx].shape.numberOfDirections,
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jsonTestSet.inputs[idx].shape.batch,
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jsonTestSet.inputs[idx].shape.extraDimension,
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jsonTestSet.inputs[idx].shape.depth,
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jsonTestSet.inputs[idx].shape.height,
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jsonTestSet.inputs[idx].shape.width,
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jsonTestSet.inputs[idx].shape.channels);
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}
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/// <summary>
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/// Get output tensor shape
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/// </summary>
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/// <param name="idx">output tensor index</param>
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/// <returns>tensor shape</returns>
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public TensorShape GetOutputShape(int idx = 0)
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{
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if (rawTestSet != null)
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return new TensorShape(1,rawTestSet.labels.Length);
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return new TensorShape(jsonTestSet.outputs[idx].shape.sequenceLength,
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jsonTestSet.outputs[idx].shape.numberOfDirections,
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jsonTestSet.outputs[idx].shape.batch,
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jsonTestSet.outputs[idx].shape.extraDimension,
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jsonTestSet.outputs[idx].shape.depth,
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jsonTestSet.outputs[idx].shape.height,
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jsonTestSet.outputs[idx].shape.width,
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jsonTestSet.outputs[idx].shape.channels);
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}
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/// <summary>
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/// Get inputs as `Tensor` dictionary
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/// </summary>
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/// <param name="inputs">dictionary to store results</param>
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/// <param name="batchCount">max batch count</param>
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/// <param name="fromBatch">start from batch</param>
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/// <returns>dictionary with input tensors</returns>
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/// <exception cref="Exception">thrown if called on raw test set (only JSON test set is supported)</exception>
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public Dictionary<string, Tensor> GetInputsAsTensorDictionary(Dictionary<string, Tensor> inputs = null, int batchCount = -1, int fromBatch = 0)
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{
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if (rawTestSet != null)
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throw new Exception("GetInputsAsTensorDictionary is not supported for RAW test suites");
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if (inputs == null)
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inputs = new Dictionary<string, Tensor>();
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for (var i = 0; i < GetInputCount(); i++)
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inputs[GetInputName(i)] = GetInputAsTensor(i, batchCount, fromBatch);
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return inputs;
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}
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/// <summary>
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/// Get outputs as `Tensor` dictionary
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/// </summary>
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/// <param name="outputs">dictionary to store results</param>
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/// <param name="batchCount">max batch count</param>
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/// <param name="fromBatch">start from batch</param>
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/// <returns>dictionary with input tensors</returns>
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/// <exception cref="Exception">thrown if called on raw test set (only JSON test set is supported)</exception>
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public Dictionary<string, Tensor> GetOutputsAsTensorDictionary(Dictionary<string, Tensor> outputs = null, int batchCount = -1, int fromBatch = 0)
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{
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if (rawTestSet != null)
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throw new Exception("GetOutputsAsTensorDictionary is not supported for RAW test suites");
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if (outputs == null)
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outputs = new Dictionary<string, Tensor>();
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for (var i = 0; i < GetOutputCount(); i++)
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outputs[GetOutputName(i)] = GetOutputAsTensor(i, batchCount, fromBatch);
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return outputs;
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}
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/// <summary>
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/// Get input as `Tensor`
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/// </summary>
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/// <param name="idx">input index</param>
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/// <param name="batchCount">max batch count</param>
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/// <param name="fromBatch">start from batch</param>
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/// <returns>`Tensor`</returns>
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/// <exception cref="Exception">thrown if called on raw test set (only JSON test set is supported)</exception>
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public Tensor GetInputAsTensor(int idx = 0, int batchCount = -1, int fromBatch = 0)
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{
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if (rawTestSet != null)
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throw new Exception("GetInputAsTensor is not supported for RAW test suites");
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TensorShape shape = GetInputShape(idx);
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Assert.IsTrue(shape.sequenceLength==1 && shape.numberOfDirections==1);
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var array = GetInputData(idx);
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var maxBatchCount = array.Length / shape.flatWidth;
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fromBatch = Math.Min(fromBatch, maxBatchCount - 1);
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if (batchCount < 0)
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batchCount = maxBatchCount - fromBatch;
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// pad data with 0s, if test-set doesn't have enough batches
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var shapeArray = shape.ToArray();
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shapeArray[TensorShape.DataBatch] = batchCount;
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var tensorShape = new TensorShape(shapeArray);
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var managedBufferStartIndex = fromBatch * tensorShape.flatWidth;
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var count = Math.Min(batchCount, maxBatchCount - fromBatch) * tensorShape.flatWidth;
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float[] dataToUpload = new float[tensorShape.length];
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Array.Copy(array, managedBufferStartIndex, dataToUpload, 0, count);
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var data = new ArrayTensorData(tensorShape.length);
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data.Upload(dataToUpload, tensorShape, 0);
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var res = new Tensor(tensorShape, data);
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res.name = GetInputName(idx);
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res.name = res.name.EndsWith(":0") ? res.name.Remove(res.name.Length - 2) : res.name;
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return res;
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}
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/// <summary>
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/// Get output as `Tensor`
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/// </summary>
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/// <param name="idx">output index</param>
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/// <param name="batchCount">max batch count</param>
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/// <param name="fromBatch">start from batch</param>
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/// <returns>`Tensor`</returns>
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/// <exception cref="Exception">thrown if called on raw test set (only JSON test set is supported)</exception>
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public Tensor GetOutputAsTensor(int idx = 0, int batchCount = -1, int fromBatch = 0)
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{
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if (rawTestSet != null)
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throw new Exception("GetOutputAsTensor is not supported for RAW test suites");
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TensorShape shape = GetOutputShape(idx);
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Assert.IsTrue(shape.sequenceLength==1 && shape.numberOfDirections==1);
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var barracudaArray = new BarracudaArrayFromManagedArray(GetOutputData(idx));
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var maxBatchCount = barracudaArray.Length / shape.flatWidth;
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fromBatch = Math.Min(fromBatch, maxBatchCount - 1);
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if (batchCount < 0)
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batchCount = maxBatchCount - fromBatch;
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batchCount = Math.Min(batchCount, maxBatchCount - fromBatch);
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var shapeArray = shape.ToArray();
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shapeArray[TensorShape.DataBatch] = batchCount;
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var tensorShape = new TensorShape(shapeArray);
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var offset = fromBatch * tensorShape.flatWidth;
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var res = new Tensor(tensorShape, new SharedArrayTensorData(barracudaArray, tensorShape, offset));
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res.name = GetOutputName(idx);
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res.name = res.name.EndsWith(":0") ? res.name.Remove(res.name.Length - 2) : res.name;
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return res;
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}
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}
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/// <summary>
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/// Raw test structure
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/// </summary>
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public class RawTestSet
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{
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/// <summary>
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/// Input data
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/// </summary>
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public float[] input;
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/// <summary>
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/// Output data
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/// </summary>
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public float[] labels;
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}
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/// <summary>
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/// JSON test structure
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/// </summary>
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[Serializable]
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public class JSONTestSet
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{
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/// <summary>
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/// Inputs
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/// </summary>
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public JSONTensor[] inputs;
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/// <summary>
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/// Outputs
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/// </summary>
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public JSONTensor[] outputs;
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}
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/// <summary>
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/// JSON tensor shape
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/// </summary>
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[Serializable]
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public class JSONTensorShape
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{
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/// <summary>
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/// Sequence length
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/// </summary>
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public int sequenceLength;
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/// <summary>
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/// Number of directions
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/// </summary>
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public int numberOfDirections;
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/// <summary>
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/// Batch
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/// </summary>
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public int batch;
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/// <summary>
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/// Extra dimension
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/// </summary>
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public int extraDimension;
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/// <summary>
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/// Depth
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/// </summary>
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public int depth;
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/// <summary>
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/// Height
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/// </summary>
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public int height;
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/// <summary>
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/// Width
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/// </summary>
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public int width;
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/// <summary>
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/// Channels
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/// </summary>
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public int channels;
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}
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/// <summary>
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/// JSON tensor
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/// </summary>
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[Serializable]
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public class JSONTensor
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{
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/// <summary>
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/// Name
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/// </summary>
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public string name;
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/// <summary>
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/// Shape
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/// </summary>
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public JSONTensorShape shape;
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/// <summary>
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/// Tensor type
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/// </summary>
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public string type;
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/// <summary>
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/// Tensor data
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/// </summary>
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public float[] data;
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}
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/// <summary>
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/// Test set loader
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/// </summary>
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public class TestSetLoader
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{
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/// <summary>
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/// Load test set from file
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/// </summary>
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/// <param name="filename">file name</param>
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/// <returns>`TestSet`</returns>
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public static TestSet Load(string filename)
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{
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if (filename.ToLower().EndsWith(".raw"))
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return LoadRaw(filename);
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else if (filename.ToLower().EndsWith(".gz"))
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return LoadGZ(filename);
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return LoadJSON(filename);
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}
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/// <summary>
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/// Load GZ
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/// </summary>
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/// <param name="filename">file name</param>
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/// <returns>`TestSet`</returns>
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public static TestSet LoadGZ(string filename)
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{
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var jsonFileName = filename.Substring(0, filename.Length - 3);
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var sourceArchiveFileName = Path.Combine(Application.streamingAssetsPath, "TestSet", filename);
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var destinationDirectoryName = sourceArchiveFileName.Substring(0, sourceArchiveFileName.Length - 3);
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FileInfo fileToDecompress = new FileInfo(sourceArchiveFileName);
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using (FileStream originalFileStream = fileToDecompress.OpenRead())
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{
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using (FileStream decompressedFileStream = File.Create(destinationDirectoryName))
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{
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using (GZipStream decompressionStream = new GZipStream(originalFileStream, CompressionMode.Decompress))
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{
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decompressionStream.CopyTo(decompressedFileStream);
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}
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}
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}
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return LoadJSON(jsonFileName);
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}
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/// <summary>
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/// Load JSON
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/// </summary>
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/// <param name="filename">file name</param>
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/// <returns>`TestSet`</returns>
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public static TestSet LoadJSON(string filename)
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{
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string json = "";
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if (filename.EndsWith(".json"))
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json = File.ReadAllText(Path.Combine(Application.streamingAssetsPath, "TestSet", filename));
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else
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json = Resources.Load<TextAsset>($"TestSet/{filename}").text;
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TestSet result = new TestSet(JsonUtility.FromJson<JSONTestSet>(json));
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return result;
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}
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/// <summary>
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/// Load raw test set
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/// </summary>
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/// <param name="filename">file name</param>
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/// <returns>`TestSet`</returns>
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public static TestSet LoadRaw(string filename)
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{
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string fullpath = Path.Combine(Application.streamingAssetsPath, "TestSet", filename);
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using(BinaryReader file = Open(fullpath))
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{
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var rawTestSet = new RawTestSet();
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rawTestSet.input = LoadFloatArray(file);
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rawTestSet.labels = LoadFloatArray(file);
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return new TestSet(rawTestSet);
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}
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}
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/// <summary>
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/// Load image
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/// </summary>
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/// <param name="filename">file name</param>
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/// <returns>`Texture`</returns>
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public static Texture LoadImage(string filename)
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{
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string fullpath = Path.Combine(Application.streamingAssetsPath, "TestSet", filename);
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var bytes = File.ReadAllBytes(fullpath);
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var tex = new Texture2D(2, 2);
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ImageConversion.LoadImage(tex, bytes, false); // LoadImage will auto-resize the texture dimensions
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tex.wrapMode = TextureWrapMode.Clamp;
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return tex;
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}
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/// <summary>
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/// Load float array
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/// </summary>
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/// <param name="file">binary file reader</param>
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/// <returns>float array</returns>
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public static float[] LoadFloatArray(BinaryReader file)
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{
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Int64 dataLength = file.ReadInt64();
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float[] array = new float[dataLength];
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byte[] bytes = file.ReadBytes(Convert.ToInt32(dataLength * sizeof(float))); // @TODO: support larger than MaxInt32 data blocks
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Buffer.BlockCopy(bytes, 0, array, 0, bytes.Length);
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return array;
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}
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/// <summary>
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/// Open file with binary reader
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/// </summary>
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/// <param name="filename">file name</param>
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/// <returns>`BinaryReader`</returns>
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static BinaryReader Open(string filename)
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{
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return new BinaryReader(new FileStream(filename, FileMode.Open, FileAccess.Read));
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}
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}
|
||||
|
||||
|
||||
} // namespace Unity.Barracuda
|
||||
Reference in New Issue
Block a user