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142 行
4.7 KiB
142 行
4.7 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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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="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, 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
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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 AddRange 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. Only usable with a TensorProxy target.
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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 range of floats
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/// </summary>
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/// <param name="data"></param>
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/// <param name="writeOffset">Optional write offset.</param>
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public void AddRange(IEnumerable<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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int index = 0;
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foreach (var val in data)
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{
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m_Data[index + m_Offset + writeOffset] = val;
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index++;
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}
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}
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else
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{
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int index = 0;
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foreach (var val in data)
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{
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m_Proxy.data[m_Batch, index + m_Offset + writeOffset] = val;
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index++;
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}
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}
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}
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}
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}
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