/// <summary>
/// Generates the Tensor inputs that are expected to be present in the Model.
/// </summary>
/// <param name="model">
/// The Barracuda engine model for loading static parameters.
/// </param>
/// <returns>TensorProxy IEnumerable with the expected Tensor inputs.</returns>
public static IReadOnlyList <TensorProxy> GetInputTensors(Model model)
{
var tensors = new List <TensorProxy>();
if (model == null)
{
return(tensors);
}
foreach (var input in model.inputs)
{
tensors.Add(new TensorProxy
{
name = input.name,
valueType = TensorProxy.TensorType.FloatingPoint,
data = null,
shape = input.shape.Select(i => (long)i).ToArray()
});
}
foreach (var mem in model.memories)
{
tensors.Add(new TensorProxy
{
name = mem.input,
valueType = TensorProxy.TensorType.FloatingPoint,
data = null,
shape = TensorUtils.TensorShapeFromBarracuda(mem.shape)
});
}
tensors.Sort((el1, el2) => el1.name.CompareTo(el2.name));
return(tensors);
}
List <TensorProxy> FetchBarracudaOutputs(string[] names)
{
var outputs = new List <TensorProxy>();
foreach (var n in names)
{
var output = m_Engine.PeekOutput(n);
outputs.Add(TensorUtils.TensorProxyFromBarracuda(output, n));
}
return(outputs);
}
public void Generate(TensorProxy tensorProxy, int batchSize, IEnumerable <AgentInfoSensorsPair> infos)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var maskSize = tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var infoSensorPair in infos)
{
var agentInfo = infoSensorPair.agentInfo;
var maskList = agentInfo.discreteActionMasks;
for (var j = 0; j < maskSize; j++)
{
var isUnmasked = (maskList != null && maskList[j]) ? 0.0f : 1.0f;
tensorProxy.data[agentIndex, j] = isUnmasked;
}
agentIndex++;
}
}
public void Generate(TensorProxy tensorProxy, int batchSize, IEnumerable <AgentInfoSensorsPair> infos)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var actionSize = tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var infoSensorPair in infos)
{
var info = infoSensorPair.agentInfo;
var pastAction = info.storedVectorActions;
if (pastAction != null)
{
for (var j = 0; j < actionSize; j++)
{
tensorProxy.data[agentIndex, j] = pastAction[j];
}
}
agentIndex++;
}
}
public void Generate(TensorProxy tensorProxy, int batchSize, IEnumerable <AgentInfoSensorsPair> infos)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var agentIndex = 0;
foreach (var infoSensorPair in infos)
{
var sensor = infoSensorPair.sensors[m_SensorIndex];
if (infoSensorPair.agentInfo.done)
{
// If the agent is done, we might have a stale reference to the sensors
// e.g. a dependent object might have been disposed.
// To avoid this, just fill observation with zeroes instead of calling sensor.Write.
TensorUtils.FillTensorBatch(tensorProxy, agentIndex, 0.0f);
}
else
{
m_WriteAdapter.SetTarget(tensorProxy, agentIndex, 0);
sensor.Write(m_WriteAdapter);
}
agentIndex++;
}
}
public void Generate(TensorProxy tensorProxy, int batchSize, IEnumerable <AgentInfoSensorsPair> infos)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var memorySize = (int)tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var infoSensorPair in infos)
{
var info = infoSensorPair.agentInfo;
var offset = memorySize * m_MemoryIndex;
List <float> memory;
if (info.done)
{
m_Memories.Remove(info.episodeId);
}
if (!m_Memories.TryGetValue(info.episodeId, out memory))
{
for (var j = 0; j < memorySize; j++)
{
tensorProxy.data[agentIndex, j] = 0;
}
agentIndex++;
continue;
}
for (var j = 0; j < memorySize; j++)
{
if (j >= memory.Count)
{
break;
}
tensorProxy.data[agentIndex, j] = memory[j + offset];
}
agentIndex++;
}
}
public void Generate(TensorProxy tensorProxy, int batchSize, IEnumerable <AgentInfoSensorsPair> infos)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var vecObsSizeT = tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var info in infos)
{
if (info.agentInfo.done)
{
// If the agent is done, we might have a stale reference to the sensors
// e.g. a dependent object might have been disposed.
// To avoid this, just fill observation with zeroes instead of calling sensor.Write.
TensorUtils.FillTensorBatch(tensorProxy, agentIndex, 0.0f);
}
else
{
var tensorOffset = 0;
// Write each sensor consecutively to the tensor
foreach (var sensorIndex in m_SensorIndices)
{
var sensor = info.sensors[sensorIndex];
m_WriteAdapter.SetTarget(tensorProxy, agentIndex, tensorOffset);
var numWritten = sensor.Write(m_WriteAdapter);
tensorOffset += numWritten;
}
Debug.AssertFormat(
tensorOffset == vecObsSizeT,
"mismatch between vector observation size ({0}) and number of observations written ({1})",
vecObsSizeT, tensorOffset
);
}
agentIndex++;
}
}
public void Generate(TensorProxy tensorProxy, int batchSize, IEnumerable <AgentInfoSensorsPair> infos)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
TensorUtils.FillTensorWithRandomNormal(tensorProxy, m_RandomNormal);
}
public void Generate(TensorProxy tensorProxy, int batchSize, IEnumerable <AgentInfoSensorsPair> infos)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
}