public void Generate(TensorProxy tensorProxy, int batchSize, IEnumerable <Agent> agents)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var vecObsSizeT = tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var agent in agents)
{
var tensorOffset = 0;
// Write each sensor consecutively to the tensor
foreach (var sensorIndex in m_SensorIndices)
{
m_WriteAdapter.SetTarget(tensorProxy, agentIndex, tensorOffset);
var sensor = agent.sensors[sensorIndex];
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, Dictionary <Agent, AgentInfo> agentInfo)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var memorySize = tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var agent in agentInfo.Keys)
{
var memory = agentInfo[agent].memories;
if (memory == null)
{
agentIndex++;
continue;
}
for (var j = 0; j < Math.Min(memorySize, memory.Count); j++)
{
if (j >= memory.Count)
{
break;
}
tensorProxy.data[agentIndex, j] = memory[j];
}
agentIndex++;
}
}
public void Generate(
TensorProxy tensorProxy, int batchSize, IEnumerable <Agent> agents)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var memorySize = (int)tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var agent in agents)
{
var agentInfo = agent.Info;
var memory = agentInfo.memories;
var offset = memorySize * m_MemoryIndex;
if (memory == null)
{
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, Dictionary <Agent, AgentInfo> agentInfo)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, _allocator);
var memorySize = (int)tensorProxy.Shape[tensorProxy.Shape.Length - 1];
var agentIndex = 0;
foreach (var agent in agentInfo.Keys)
{
var memory = agentInfo[agent].memories;
int offset = memorySize * memoryIndex;
if (memory == null)
{
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, Dictionary <Agent, AgentInfo> agentInfo)
{
var textures = agentInfo.Keys.Select(
agent => agentInfo[agent].visualObservations[_index]).ToList();
TensorUtils.ResizeTensor(tensorProxy, batchSize, _allocator);
Utilities.TextureToTensorProxy(tensorProxy, textures, _grayScale, _allocator);
}
public void Generate(TensorProxy tensorProxy, int batchSize, IEnumerable <Agent> agents)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var agentIndex = 0;
foreach (var agent in agents)
{
m_WriteAdapter.SetTarget(tensorProxy, agentIndex, 0);
agent.sensors[m_SensorIndex].Write(m_WriteAdapter);
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];
m_WriteAdapter.SetTarget(tensorProxy, agentIndex, 0);
sensor.Write(m_WriteAdapter);
agentIndex++;
}
}
public void Generate(
TensorProxy tensorProxy, int batchSize, IEnumerable <Agent> agents)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var agentIndex = 0;
foreach (var agent in agents)
{
// TODO direct access to sensors list here - should we do it differently?
// TODO m_Index here is the visual observation index. Will work for now but not if we add more sensor types.
agent.m_Sensors[m_Index].WriteToTensor(tensorProxy, agentIndex);
agentIndex++;
}
}
public void Generate(TensorProxy tensorProxy, int batchSize, Dictionary <Agent, AgentInfo> agentInfo)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, _allocator);
var vecObsSizeT = tensorProxy.Shape[tensorProxy.Shape.Length - 1];
var agentIndex = 0;
foreach (var agent in agentInfo.Keys)
{
var vectorObs = agentInfo[agent].stackedVectorObservation;
for (var j = 0; j < vecObsSizeT; j++)
{
tensorProxy.Data[agentIndex, j] = vectorObs[j];
}
agentIndex++;
}
}
public void Generate(TensorProxy tensorProxy, int batchSize, Dictionary <Agent, AgentInfo> agentInfo)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, _allocator);
var maskSize = tensorProxy.Shape[tensorProxy.Shape.Length - 1];
var agentIndex = 0;
foreach (var agent in agentInfo.Keys)
{
var maskList = agentInfo[agent].actionMasks;
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 <Agent> agents)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var vecObsSizeT = tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var agent in agents)
{
var info = agent.Info;
var vectorObs = info.stackedVectorObservation;
for (var j = 0; j < vecObsSizeT; j++)
{
tensorProxy.data[agentIndex, j] = vectorObs[j];
}
agentIndex++;
}
}
public void Generate(TensorProxy tensorProxy, int batchSize, Dictionary <Agent, AgentInfo> agentInfo)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, _allocator);
var actionSize = tensorProxy.Shape[tensorProxy.Shape.Length - 1];
var agentIndex = 0;
foreach (var agent in agentInfo.Keys)
{
var pastAction = agentInfo[agent].storedVectorActions;
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 maskSize = tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var infoSensorPair in infos)
{
var agentInfo = infoSensorPair.agentInfo;
var maskList = agentInfo.actionMasks;
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;
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 <Agent> agents)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
var memorySize = tensorProxy.shape[tensorProxy.shape.Length - 1];
var agentIndex = 0;
foreach (var agent in agents)
{
var info = agent.Info;
List <float> memory;
if (agent.Info.done)
{
m_Memories.Remove(agent.Info.id);
}
if (!m_Memories.TryGetValue(agent.Info.id, out memory))
{
for (var j = 0; j < memorySize; j++)
{
tensorProxy.data[agentIndex, j] = 0;
}
agentIndex++;
continue;
}
for (var j = 0; j < Math.Min(memorySize, memory.Count); j++)
{
if (j >= memory.Count)
{
break;
}
tensorProxy.data[agentIndex, j] = memory[j];
}
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);
}
public void Generate(TensorProxy tensorProxy, int batchSize, Dictionary <Agent, AgentInfo> agentInfo)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
}
public void Generate(TensorProxy tensorProxy, int batchSize, Dictionary <Agent, AgentInfo> agentInfo)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, _allocator);
_randomNormal.FillTensor(tensorProxy);
}
public void Generate(
TensorProxy tensorProxy, int batchSize, Dictionary <Agent, AgentInfo> agentInfo)
{
TensorUtils.ResizeTensor(tensorProxy, batchSize, m_Allocator);
TensorUtils.FillTensorWithRandomNormal(tensorProxy, m_RandomNormal);
}