Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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123 行
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using System;
namespace Unity.MLAgents.Sensors
{
/// <summary>
/// A Sensor that allows to observe a variable number of entities.
/// </summary>
public class BufferSensor : ISensor, IDimensionPropertiesSensor, IBuiltInSensor
{
private string m_Name;
private int m_MaxNumObs;
private int m_ObsSize;
float[] m_ObservationBuffer;
int m_CurrentNumObservables;
static DimensionProperty[] s_DimensionProperties = new DimensionProperty[]{
DimensionProperty.VariableSize,
DimensionProperty.None
};
/// <summary>
/// Creates the BufferSensor.
/// </summary>
/// <param name="maxNumberObs">The maximum number of observations to be appended to this BufferSensor.</param>
/// <param name="obsSize">The size of each observation appended to the BufferSensor.</param>
/// <param name="name">The name of the sensor.</param>
public BufferSensor(int maxNumberObs, int obsSize, string name)
{
m_Name = name;
m_MaxNumObs = maxNumberObs;
m_ObsSize = obsSize;
m_ObservationBuffer = new float[m_ObsSize * m_MaxNumObs];
m_CurrentNumObservables = 0;
}
/// <inheritdoc/>
public int[] GetObservationShape()
{
return new int[] { m_MaxNumObs, m_ObsSize };
}
/// <inheritdoc/>
public DimensionProperty[] GetDimensionProperties()
{
return s_DimensionProperties;
}
/// <summary>
/// Appends an observation to the buffer. If the buffer is full (maximum number
/// of observation is reached) the observation will be ignored. the length of
/// the provided observation array must be equal to the observation size of
/// the buffer sensor.
/// </summary>
/// <param name="obs"> The float array observation</param>
public void AppendObservation(float[] obs)
{
if (obs.Length != m_ObsSize)
{
throw new UnityAgentsException(
"The BufferSensor was expecting an observation of size " +
$"{m_ObsSize} but received {obs.Length} observations instead."
);
}
if (m_CurrentNumObservables >= m_MaxNumObs)
{
return;
}
for (int i = 0; i < obs.Length; i++)
{
m_ObservationBuffer[m_CurrentNumObservables * m_ObsSize + i] = obs[i];
}
m_CurrentNumObservables++;
}
/// <inheritdoc/>
public int Write(ObservationWriter writer)
{
for (int i = 0; i < m_ObsSize * m_MaxNumObs; i++)
{
writer[i] = m_ObservationBuffer[i];
}
return m_ObsSize * m_MaxNumObs;
}
/// <inheritdoc/>
public virtual byte[] GetCompressedObservation()
{
return null;
}
/// <inheritdoc/>
public void Update()
{
Reset();
}
/// <inheritdoc/>
public void Reset()
{
m_CurrentNumObservables = 0;
Array.Clear(m_ObservationBuffer, 0, m_ObservationBuffer.Length);
}
/// <inheritdoc/>
public SensorCompressionType GetCompressionType()
{
return SensorCompressionType.None;
}
/// <inheritdoc/>
public string GetName()
{
return m_Name;
}
/// <inheritdoc/>
public BuiltInSensorType GetBuiltInSensorType()
{
return BuiltInSensorType.BufferSensor;
}
}
}