/// <inheritdoc/>
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.GetCompressionSpec().SensorCompressionType != SensorCompressionType.None)
{
for (var i = 0; i < m_NumStackedObservations; i++)
{
m_StackedCompressedObservations[i] = m_EmptyCompressedObservation;
}
}
}
public static EventObservationSpec FromSensor(ISensor sensor)
{
var obsSpec = sensor.GetObservationSpec();
var shape = obsSpec.Shape;
var dimProps = obsSpec.DimensionProperties;
var dimInfos = new EventObservationDimensionInfo[shape.Length];
for (var i = 0; i < shape.Length; i++)
{
dimInfos[i].Size = shape[i];
dimInfos[i].Flags = (int)dimProps[i];
}
var builtInSensorType =
(sensor as IBuiltInSensor)?.GetBuiltInSensorType() ?? Sensors.BuiltInSensorType.Unknown;
return(new EventObservationSpec
{
SensorName = sensor.GetName(),
CompressionType = sensor.GetCompressionSpec().SensorCompressionType.ToString(),
BuiltInSensorType = (int)builtInSensorType,
ObservationType = (int)obsSpec.ObservationType,
DimensionInfos = dimInfos,
});
}
/// <summary>
/// Initializes the sensor.
/// </summary>
/// <param name="wrapped">The wrapped sensor.</param>
/// <param name="numStackedObservations">Number of stacked observations to keep.</param>
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_UnstackedObservationSize = wrapped.ObservationSize();
// Set up the cached observation spec for the StackingSensor
var newShape = m_WrappedSpec.Shape;
// TODO support arbitrary stacking dimension
newShape[newShape.Length - 1] *= numStackedObservations;
m_ObservationSpec = new ObservationSpec(
newShape, m_WrappedSpec.DimensionProperties, m_WrappedSpec.ObservationType
);
// 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.GetCompressionSpec().SensorCompressionType != 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.Rank != 1)
{
var wrappedShape = m_WrappedSpec.Shape;
m_tensorShape = new TensorShape(0, wrappedShape[0], wrappedShape[1], wrappedShape[2]);
}
}
/// <summary>
/// Construct stacked CompressedChannelMapping.
/// </summary>
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];
wrappedMapping = wrappedSenesor.GetCompressionSpec().CompressedChannelMapping;
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);
}
/// <summary>
/// Generate an ObservationProto for the sensor using the provided ObservationWriter.
/// This is equivalent to producing an Observation and calling Observation.ToProto(),
/// but avoid some intermediate memory allocations.
/// </summary>
/// <param name="sensor"></param>
/// <param name="observationWriter"></param>
/// <returns></returns>
public static ObservationProto GetObservationProto(this ISensor sensor, ObservationWriter observationWriter)
{
var obsSpec = sensor.GetObservationSpec();
var shape = obsSpec.Shape;
ObservationProto observationProto = null;
var compressionSpec = sensor.GetCompressionSpec();
var compressionType = compressionSpec.SensorCompressionType;
// Check capabilities if we need to concatenate PNGs
if (compressionType == SensorCompressionType.PNG && shape.Length == 3 && shape[2] > 3)
{
var trainerCanHandle = Academy.Instance.TrainerCapabilities == null || Academy.Instance.TrainerCapabilities.ConcatenatedPngObservations;
if (!trainerCanHandle)
{
if (!s_HaveWarnedTrainerCapabilitiesMultiPng)
{
Debug.LogWarning(
$"Attached trainer doesn't support multiple PNGs. Switching to uncompressed observations for sensor {sensor.GetName()}. " +
"Please find the versions that work best together from our release page: " +
"https://github.com/Unity-Technologies/ml-agents/releases"
);
s_HaveWarnedTrainerCapabilitiesMultiPng = true;
}
compressionType = SensorCompressionType.None;
}
}
// Check capabilities if we need mapping for compressed observations
if (compressionType != SensorCompressionType.None && shape.Length == 3 && shape[2] > 3)
{
var trainerCanHandleMapping = Academy.Instance.TrainerCapabilities == null || Academy.Instance.TrainerCapabilities.CompressedChannelMapping;
var isTrivialMapping = compressionSpec.IsTrivialMapping();
if (!trainerCanHandleMapping && !isTrivialMapping)
{
if (!s_HaveWarnedTrainerCapabilitiesMapping)
{
Debug.LogWarning(
$"The sensor {sensor.GetName()} is using non-trivial mapping and " +
"the attached trainer doesn't support compression mapping. " +
"Switching to uncompressed observations. " +
"Please find the versions that work best together from our release page: " +
"https://github.com/Unity-Technologies/ml-agents/releases"
);
s_HaveWarnedTrainerCapabilitiesMapping = true;
}
compressionType = SensorCompressionType.None;
}
}
if (compressionType == SensorCompressionType.None)
{
var numFloats = sensor.ObservationSize();
var floatDataProto = new ObservationProto.Types.FloatData();
// Resize the float array
// TODO upgrade protobuf versions so that we can set the Capacity directly - see https://github.com/protocolbuffers/protobuf/pull/6530
for (var i = 0; i < numFloats; i++)
{
floatDataProto.Data.Add(0.0f);
}
observationWriter.SetTarget(floatDataProto.Data, sensor.GetObservationSpec(), 0);
sensor.Write(observationWriter);
observationProto = new ObservationProto
{
FloatData = floatDataProto,
CompressionType = (CompressionTypeProto)SensorCompressionType.None,
};
}
else
{
var compressedObs = sensor.GetCompressedObservation();
if (compressedObs == null)
{
throw new UnityAgentsException(
$"GetCompressedObservation() returned null data for sensor named {sensor.GetName()}. " +
"You must return a byte[]. If you don't want to use compressed observations, " +
"return CompressionSpec.Default() from GetCompressionSpec()."
);
}
observationProto = new ObservationProto
{
CompressedData = ByteString.CopyFrom(compressedObs),
CompressionType = (CompressionTypeProto)sensor.GetCompressionSpec().SensorCompressionType,
};
if (compressionSpec.CompressedChannelMapping != null)
{
observationProto.CompressedChannelMapping.AddRange(compressionSpec.CompressedChannelMapping);
}
}
// Add the dimension properties to the observationProto
var dimensionProperties = obsSpec.DimensionProperties;
for (int i = 0; i < dimensionProperties.Length; i++)
{
observationProto.DimensionProperties.Add((int)dimensionProperties[i]);
}
// Checking trainer compatibility with variable length observations
if (dimensionProperties == new InplaceArray <DimensionProperty>(DimensionProperty.VariableSize, DimensionProperty.None))
{
var trainerCanHandleVarLenObs = Academy.Instance.TrainerCapabilities == null || Academy.Instance.TrainerCapabilities.VariableLengthObservation;
if (!trainerCanHandleVarLenObs)
{
throw new UnityAgentsException("Variable Length Observations are not supported by the trainer");
}
}
for (var i = 0; i < shape.Length; i++)
{
observationProto.Shape.Add(shape[i]);
}
var sensorName = sensor.GetName();
if (!string.IsNullOrEmpty(sensorName))
{
observationProto.Name = sensorName;
}
observationProto.ObservationType = (ObservationTypeProto)obsSpec.ObservationType;
return(observationProto);
}
