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279 行
10 KiB
279 行
10 KiB
using System;
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using System.Collections.Generic;
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using Unity.Barracuda;
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using Unity.MLAgents.Inference;
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using UnityEngine;
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namespace Unity.MLAgents.Sensors
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{
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/// <summary>
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/// Allows sensors to write to both TensorProxy and float arrays/lists.
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/// </summary>
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public class ObservationWriter
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{
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IList<float> m_Data;
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int m_Offset;
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TensorProxy m_Proxy;
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int m_Batch;
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TensorShape m_TensorShape;
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internal ObservationWriter() { }
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/// <summary>
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/// Set the writer to write to an IList at the given channelOffset.
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/// </summary>
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/// <param name="data">Float array or list that will be written to.</param>
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/// <param name="observationSpec">ObservationSpec of the observation to be written</param>
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/// <param name="offset">Offset from the start of the float data to write to.</param>
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internal void SetTarget(IList<float> data, ObservationSpec observationSpec, int offset)
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{
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// TODO remove int[] version
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SetTarget(data, observationSpec.Shape, offset);
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}
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/// <summary>
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/// Set the writer to write to an IList at the given channelOffset.
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/// </summary>
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/// <param name="data">Float array or list that will be written to.</param>
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/// <param name="shape">Shape of the observations to be written.</param>
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/// <param name="offset">Offset from the start of the float data to write to.</param>
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internal void SetTarget(IList<float> data, InplaceArray<int> shape, int offset)
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{
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m_Data = data;
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m_Offset = offset;
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m_Proxy = null;
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m_Batch = 0;
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if (shape.Length == 1)
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{
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m_TensorShape = new TensorShape(m_Batch, shape[0]);
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}
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else if (shape.Length == 2)
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{
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m_TensorShape = new TensorShape(new[] { m_Batch, 1, shape[0], shape[1] });
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}
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else
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{
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m_TensorShape = new TensorShape(m_Batch, shape[0], shape[1], shape[2]);
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}
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}
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/// <summary>
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/// Set the writer to write to a TensorProxy at the given batch and channel offset.
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/// </summary>
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/// <param name="tensorProxy">Tensor proxy that will be written to.</param>
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/// <param name="batchIndex">Batch index in the tensor proxy (i.e. the index of the Agent).</param>
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/// <param name="channelOffset">Offset from the start of the channel to write to.</param>
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internal void SetTarget(TensorProxy tensorProxy, int batchIndex, int channelOffset)
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{
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m_Proxy = tensorProxy;
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m_Batch = batchIndex;
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m_Offset = channelOffset;
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m_Data = null;
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m_TensorShape = m_Proxy.data.shape;
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}
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/// <summary>
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/// 1D write access at a specified index. Use AddList if possible instead.
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/// </summary>
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/// <param name="index">Index to write to.</param>
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public float this[int index]
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{
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set
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{
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if (m_Data != null)
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{
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m_Data[index + m_Offset] = value;
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}
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else
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{
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m_Proxy.data[m_Batch, index + m_Offset] = value;
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}
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}
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}
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/// <summary>
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/// 3D write access at the specified height, width, and channel.
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/// </summary>
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/// <param name="h"></param>
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/// <param name="w"></param>
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/// <param name="ch"></param>
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public float this[int h, int w, int ch]
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{
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set
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{
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if (m_Data != null)
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{
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if (h < 0 || h >= m_TensorShape.height)
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{
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throw new IndexOutOfRangeException($"height value {h} must be in range [0, {m_TensorShape.height - 1}]");
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}
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if (w < 0 || w >= m_TensorShape.width)
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{
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throw new IndexOutOfRangeException($"width value {w} must be in range [0, {m_TensorShape.width - 1}]");
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}
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if (ch < 0 || ch >= m_TensorShape.channels)
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{
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throw new IndexOutOfRangeException($"channel value {ch} must be in range [0, {m_TensorShape.channels - 1}]");
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}
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var index = m_TensorShape.Index(m_Batch, h, w, ch + m_Offset);
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m_Data[index] = value;
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}
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else
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{
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m_Proxy.data[m_Batch, h, w, ch + m_Offset] = value;
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}
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}
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}
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/// <summary>
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/// Write the list of floats.
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/// </summary>
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/// <param name="data">The actual list of floats to write.</param>
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/// <param name="writeOffset">Optional write offset to start writing from.</param>
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public void AddList(IList<float> data, int writeOffset = 0)
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{
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if (m_Data != null)
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{
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for (var index = 0; index < data.Count; index++)
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{
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var val = data[index];
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m_Data[index + m_Offset + writeOffset] = val;
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}
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}
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else
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{
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for (var index = 0; index < data.Count; index++)
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{
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var val = data[index];
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m_Proxy.data[m_Batch, index + m_Offset + writeOffset] = val;
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}
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}
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}
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/// <summary>
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/// Write the Vector3 components.
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/// </summary>
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/// <param name="vec">The Vector3 to be written.</param>
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/// <param name="writeOffset">Optional write offset.</param>
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public void Add(Vector3 vec, int writeOffset = 0)
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{
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if (m_Data != null)
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{
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m_Data[m_Offset + writeOffset + 0] = vec.x;
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m_Data[m_Offset + writeOffset + 1] = vec.y;
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m_Data[m_Offset + writeOffset + 2] = vec.z;
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}
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else
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{
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 0] = vec.x;
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 1] = vec.y;
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 2] = vec.z;
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}
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}
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/// <summary>
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/// Write the Vector4 components.
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/// </summary>
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/// <param name="vec">The Vector4 to be written.</param>
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/// <param name="writeOffset">Optional write offset.</param>
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public void Add(Vector4 vec, int writeOffset = 0)
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{
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if (m_Data != null)
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{
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m_Data[m_Offset + writeOffset + 0] = vec.x;
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m_Data[m_Offset + writeOffset + 1] = vec.y;
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m_Data[m_Offset + writeOffset + 2] = vec.z;
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m_Data[m_Offset + writeOffset + 3] = vec.w;
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}
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else
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{
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 0] = vec.x;
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 1] = vec.y;
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 2] = vec.z;
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 3] = vec.w;
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}
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}
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/// <summary>
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/// Write the Quaternion components.
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/// </summary>
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/// <param name="quat">The Quaternion to be written.</param>
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/// <param name="writeOffset">Optional write offset.</param>
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public void Add(Quaternion quat, int writeOffset = 0)
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{
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if (m_Data != null)
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{
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m_Data[m_Offset + writeOffset + 0] = quat.x;
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m_Data[m_Offset + writeOffset + 1] = quat.y;
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m_Data[m_Offset + writeOffset + 2] = quat.z;
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m_Data[m_Offset + writeOffset + 3] = quat.w;
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}
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else
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{
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 0] = quat.x;
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 1] = quat.y;
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 2] = quat.z;
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m_Proxy.data[m_Batch, m_Offset + writeOffset + 3] = quat.w;
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}
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}
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}
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/// <summary>
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/// Provides extension methods for the ObservationWriter.
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/// </summary>
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public static class ObservationWriterExtension
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{
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/// <summary>
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/// Writes a Texture2D into a ObservationWriter.
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/// </summary>
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/// <param name="obsWriter">
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/// Writer to fill with Texture data.
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/// </param>
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/// <param name="texture">
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/// The texture to be put into the tensor.
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/// </param>
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/// <param name="grayScale">
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/// If set to <c>true</c> the textures will be converted to grayscale before
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/// being stored in the tensor.
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/// </param>
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/// <returns>The number of floats written</returns>
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public static int WriteTexture(
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this ObservationWriter obsWriter,
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Texture2D texture,
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bool grayScale)
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{
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var width = texture.width;
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var height = texture.height;
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var texturePixels = texture.GetPixels32();
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// During training, we convert from Texture to PNG before sending to the trainer, which has the
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// effect of flipping the image. We need another flip here at inference time to match this.
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for (var h = height - 1; h >= 0; h--)
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{
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for (var w = 0; w < width; w++)
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{
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var currentPixel = texturePixels[(height - h - 1) * width + w];
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if (grayScale)
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{
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obsWriter[h, w, 0] =
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(currentPixel.r + currentPixel.g + currentPixel.b) / 3f / 255.0f;
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}
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else
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{
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// For Color32, the r, g and b values are between 0 and 255.
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obsWriter[h, w, 0] = currentPixel.r / 255.0f;
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obsWriter[h, w, 1] = currentPixel.g / 255.0f;
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obsWriter[h, w, 2] = currentPixel.b / 255.0f;
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}
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}
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}
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return height * width * (grayScale ? 1 : 3);
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}
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}
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}
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