using System; using System.Linq; using System.Runtime.CompilerServices; using UnityEngine; using Unity.Barracuda; [assembly: InternalsVisibleTo("Unity.ML-Agents.Editor.Tests")] namespace Unity.MLAgents.Sensors { /// /// Sensor that wraps around another Sensor to provide temporal stacking. /// Conceptually, consecutive observations are stored left-to-right, which is how they're output /// For example, 4 stacked sets of observations would be output like /// | t = now - 3 | t = now -3 | t = now - 2 | t = now | /// Internally, a circular buffer of arrays is used. The m_CurrentIndex represents the most recent observation. /// Currently, observations are stacked on the last dimension. /// public class StackingSensor : ISparseChannelSensor, IBuiltInSensor { /// /// The wrapped sensor. /// ISensor m_WrappedSensor; /// /// Number of stacks to save /// int m_NumStackedObservations; int m_UnstackedObservationSize; string m_Name; private ObservationSpec m_ObservationSpec; private ObservationSpec m_WrappedSpec; /// /// Buffer of previous observations /// float[][] m_StackedObservations; byte[][] m_StackedCompressedObservations; int m_CurrentIndex; ObservationWriter m_LocalWriter = new ObservationWriter(); byte[] m_EmptyCompressedObservation; int[] m_CompressionMapping; TensorShape m_tensorShape; /// /// Initializes the sensor. /// /// The wrapped sensor. /// Number of stacked observations to keep. public StackingSensor(ISensor wrapped, int numStackedObservations) { // TODO ensure numStackedObservations > 1 m_WrappedSensor = wrapped; m_NumStackedObservations = numStackedObservations; m_Name = $"StackingSensor_size{numStackedObservations}_{wrapped.GetName()}"; m_WrappedSpec = wrapped.GetObservationSpec(); m_ObservationSpec = m_WrappedSpec; m_UnstackedObservationSize = wrapped.ObservationSize(); // TODO support arbitrary stacking dimension m_ObservationSpec.Shape[m_ObservationSpec.NumDimensions - 1] *= numStackedObservations; // Initialize uncompressed buffer anyway in case python trainer does not // support the compression mapping and has to fall back to uncompressed obs. m_StackedObservations = new float[numStackedObservations][]; for (var i = 0; i < numStackedObservations; i++) { m_StackedObservations[i] = new float[m_UnstackedObservationSize]; } if (m_WrappedSensor.GetCompressionType() != SensorCompressionType.None) { m_StackedCompressedObservations = new byte[numStackedObservations][]; m_EmptyCompressedObservation = CreateEmptyPNG(); for (var i = 0; i < numStackedObservations; i++) { m_StackedCompressedObservations[i] = m_EmptyCompressedObservation; } m_CompressionMapping = ConstructStackedCompressedChannelMapping(wrapped); } if (m_WrappedSpec.NumDimensions != 1) { var wrappedShape = m_WrappedSpec.Shape; m_tensorShape = new TensorShape(0, wrappedShape[0], wrappedShape[1], wrappedShape[2]); } } /// public int Write(ObservationWriter writer) { // First, call the wrapped sensor's write method. Make sure to use our own writer, not the passed one. m_LocalWriter.SetTarget(m_StackedObservations[m_CurrentIndex], m_WrappedSpec, 0); m_WrappedSensor.Write(m_LocalWriter); // Now write the saved observations (oldest first) var numWritten = 0; if (m_WrappedSpec.NumDimensions == 1) { for (var i = 0; i < m_NumStackedObservations; i++) { var obsIndex = (m_CurrentIndex + 1 + i) % m_NumStackedObservations; writer.AddList(m_StackedObservations[obsIndex], numWritten); numWritten += m_UnstackedObservationSize; } } else { for (var i = 0; i < m_NumStackedObservations; i++) { var obsIndex = (m_CurrentIndex + 1 + i) % m_NumStackedObservations; for (var h = 0; h < m_WrappedSpec.Shape[0]; h++) { for (var w = 0; w < m_WrappedSpec.Shape[1]; w++) { for (var c = 0; c < m_WrappedSpec.Shape[2]; c++) { writer[h, w, i * m_WrappedSpec.Shape[2] + c] = m_StackedObservations[obsIndex][m_tensorShape.Index(0, h, w, c)]; } } } } numWritten = m_WrappedSpec.Shape[0] * m_WrappedSpec.Shape[1] * m_WrappedSpec.Shape[2] * m_NumStackedObservations; } return numWritten; } /// /// Updates the index of the "current" buffer. /// public void Update() { m_WrappedSensor.Update(); m_CurrentIndex = (m_CurrentIndex + 1) % m_NumStackedObservations; } /// public void Reset() { m_WrappedSensor.Reset(); // Zero out the buffer. for (var i = 0; i < m_NumStackedObservations; i++) { Array.Clear(m_StackedObservations[i], 0, m_StackedObservations[i].Length); } if (m_WrappedSensor.GetCompressionType() != SensorCompressionType.None) { for (var i = 0; i < m_NumStackedObservations; i++) { m_StackedCompressedObservations[i] = m_EmptyCompressedObservation; } } } /// public ObservationSpec GetObservationSpec() { return m_ObservationSpec; } /// public string GetName() { return m_Name; } /// public byte[] GetCompressedObservation() { var compressed = m_WrappedSensor.GetCompressedObservation(); m_StackedCompressedObservations[m_CurrentIndex] = compressed; int bytesLength = 0; foreach (byte[] compressedObs in m_StackedCompressedObservations) { bytesLength += compressedObs.Length; } byte[] outputBytes = new byte[bytesLength]; int offset = 0; for (var i = 0; i < m_NumStackedObservations; i++) { var obsIndex = (m_CurrentIndex + 1 + i) % m_NumStackedObservations; Buffer.BlockCopy(m_StackedCompressedObservations[obsIndex], 0, outputBytes, offset, m_StackedCompressedObservations[obsIndex].Length); offset += m_StackedCompressedObservations[obsIndex].Length; } return outputBytes; } /// public int[] GetCompressedChannelMapping() { return m_CompressionMapping; } /// public SensorCompressionType GetCompressionType() { return m_WrappedSensor.GetCompressionType(); } /// /// Create Empty PNG for initializing the buffer for stacking. /// internal byte[] CreateEmptyPNG() { var shape = m_WrappedSpec.Shape; int height = shape[0]; int width = shape[1]; var texture2D = new Texture2D(width, height, TextureFormat.RGB24, false); Color32[] resetColorArray = texture2D.GetPixels32(); Color32 black = new Color32(0, 0, 0, 0); for (int i = 0; i < resetColorArray.Length; i++) { resetColorArray[i] = black; } texture2D.SetPixels32(resetColorArray); texture2D.Apply(); return texture2D.EncodeToPNG(); } /// /// Constrct stacked CompressedChannelMapping. /// internal int[] ConstructStackedCompressedChannelMapping(ISensor wrappedSenesor) { // Get CompressedChannelMapping of the wrapped sensor. If the // wrapped sensor doesn't have one, use default mapping. // Default mapping: {0, 0, 0} for grayscale, identity mapping {1, 2, ..., n} otherwise. int[] wrappedMapping = null; int wrappedNumChannel = m_WrappedSpec.Shape[2]; var sparseChannelSensor = m_WrappedSensor as ISparseChannelSensor; if (sparseChannelSensor != null) { wrappedMapping = sparseChannelSensor.GetCompressedChannelMapping(); } if (wrappedMapping == null) { if (wrappedNumChannel == 1) { wrappedMapping = new[] { 0, 0, 0 }; } else { wrappedMapping = Enumerable.Range(0, wrappedNumChannel).ToArray(); } } // Construct stacked mapping using the mapping of wrapped sensor. // First pad the wrapped mapping to multiple of 3, then repeat // and add offset to each copy to form the stacked mapping. int paddedMapLength = (wrappedMapping.Length + 2) / 3 * 3; var compressionMapping = new int[paddedMapLength * m_NumStackedObservations]; for (var i = 0; i < m_NumStackedObservations; i++) { var offset = wrappedNumChannel * i; for (var j = 0; j < paddedMapLength; j++) { if (j < wrappedMapping.Length) { compressionMapping[j + paddedMapLength * i] = wrappedMapping[j] >= 0 ? wrappedMapping[j] + offset : -1; } else { compressionMapping[j + paddedMapLength * i] = -1; } } } return compressionMapping; } /// public BuiltInSensorType GetBuiltInSensorType() { IBuiltInSensor wrappedBuiltInSensor = m_WrappedSensor as IBuiltInSensor; return wrappedBuiltInSensor?.GetBuiltInSensorType() ?? BuiltInSensorType.Unknown; } } }