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138 行
5.1 KiB
138 行
5.1 KiB
namespace Unity.MLAgents.Sensors
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{
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/// <summary>
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/// A description of the observations that an ISensor produces.
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/// This includes the size of the observation, the properties of each dimension, and how the observation
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/// should be used for training.
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/// </summary>
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public struct ObservationSpec
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{
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internal readonly InplaceArray<int> m_Shape;
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/// <summary>
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/// The size of the observations that will be generated.
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/// For example, a sensor that observes the velocity of a rigid body (in 3D) would use [3].
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/// A sensor that returns an RGB image would use [Height, Width, 3].
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/// </summary>
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public InplaceArray<int> Shape
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{
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get => m_Shape;
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}
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internal readonly InplaceArray<DimensionProperty> m_DimensionProperties;
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/// <summary>
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/// The properties of each dimensions of the observation.
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/// The length of the array must be equal to the rank of the observation tensor.
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/// </summary>
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/// <remarks>
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/// It is generally recommended to use default values provided by helper functions,
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/// as not all combinations of DimensionProperty may be supported by the trainer.
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/// </remarks>
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public InplaceArray<DimensionProperty> DimensionProperties
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{
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get => m_DimensionProperties;
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}
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internal ObservationType m_ObservationType;
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/// <summary>
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/// The type of the observation, e.g. whether they are generic or
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/// help determine the goal for the Agent.
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/// </summary>
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public ObservationType ObservationType
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{
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get => m_ObservationType;
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}
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/// <summary>
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/// The number of dimensions of the observation.
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/// </summary>
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public int Rank
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{
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get { return Shape.Length; }
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}
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/// <summary>
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/// Construct an ObservationSpec for 1-D observations of the requested length.
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/// </summary>
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/// <param name="length"></param>
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/// <param name="obsType"></param>
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/// <returns></returns>
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public static ObservationSpec Vector(int length, ObservationType obsType = ObservationType.Default)
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{
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return new ObservationSpec(
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new InplaceArray<int>(length),
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new InplaceArray<DimensionProperty>(DimensionProperty.None),
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obsType
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);
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}
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/// <summary>
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/// Construct an ObservationSpec for variable-length observations.
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/// </summary>
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/// <param name="obsSize"></param>
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/// <param name="maxNumObs"></param>
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/// <returns></returns>
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public static ObservationSpec VariableLength(int obsSize, int maxNumObs)
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{
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var dimProps = new InplaceArray<DimensionProperty>(
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DimensionProperty.VariableSize,
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DimensionProperty.None
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);
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return new ObservationSpec(
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new InplaceArray<int>(obsSize, maxNumObs),
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dimProps
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);
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}
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/// <summary>
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/// Construct an ObservationSpec for visual-like observations, e.g. observations
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/// with a height, width, and possible multiple channels.
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/// </summary>
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/// <param name="height"></param>
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/// <param name="width"></param>
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/// <param name="channels"></param>
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/// <param name="obsType"></param>
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/// <returns></returns>
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public static ObservationSpec Visual(int height, int width, int channels, ObservationType obsType = ObservationType.Default)
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{
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var dimProps = new InplaceArray<DimensionProperty>(
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DimensionProperty.TranslationalEquivariance,
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DimensionProperty.TranslationalEquivariance,
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DimensionProperty.None
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);
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return new ObservationSpec(
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new InplaceArray<int>(height, width, channels),
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dimProps,
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obsType
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);
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}
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/// <summary>
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/// Create a general ObservationSpec from the shape, dimension properties, and observation type.
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/// </summary>
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/// <remarks>
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/// Note that not all combinations of DimensionProperty may be supported by the trainer.
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/// shape and dimensionProperties must have the same size.
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/// </remarks>
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/// <param name="shape"></param>
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/// <param name="dimensionProperties"></param>
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/// <param name="observationType"></param>
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/// <exception cref="UnityAgentsException"></exception>
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public ObservationSpec(
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InplaceArray<int> shape,
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InplaceArray<DimensionProperty> dimensionProperties,
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ObservationType observationType = ObservationType.Default
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)
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{
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if (shape.Length != dimensionProperties.Length)
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{
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throw new UnityAgentsException("shape and dimensionProperties must have the same length.");
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}
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m_Shape = shape;
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m_DimensionProperties = dimensionProperties;
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m_ObservationType = observationType;
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}
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}
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}
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