public void ApplyContinuousActionOutput()
{
var inputTensor = new TensorProxy()
{
shape = new long[] { 2, 3 },
data = new Tensor(2, 3, new float[] { 1, 2, 3, 4, 5, 6 })
};
var applier = new ContinuousActionOutputApplier();
var agentIds = new List<int>() { 0, 1 };
// Dictionary from AgentId to Action
var actionDict = new Dictionary<int, float[]>() { { 0, null }, { 1, null } };
applier.Apply(inputTensor, agentIds, actionDict);
Assert.AreEqual(actionDict[0][0], 1);
Assert.AreEqual(actionDict[0][1], 2);
Assert.AreEqual(actionDict[0][2], 3);
Assert.AreEqual(actionDict[1][0], 4);
Assert.AreEqual(actionDict[1][1], 5);
Assert.AreEqual(actionDict[1][2], 6);
}
public void ApplyContinuousActionOutput()
{
var inputTensor = new TensorProxy()
{
shape = new long[] { 2, 3 },
data = new Tensor(2, 3, new float[] { 1, 2, 3, 4, 5, 6 })
};
var agentInfos = GetFakeAgentInfos();
var applier = new ContinuousActionOutputApplier();
applier.Apply(inputTensor, agentInfos);
var agents = agentInfos;
var agent = agents[0] as TestAgent;
Assert.NotNull(agent);
var action = agent.GetAction();
Assert.AreEqual(action.vectorActions[0], 1);
Assert.AreEqual(action.vectorActions[1], 2);
Assert.AreEqual(action.vectorActions[2], 3);
agent = agents[1] as TestAgent;
Assert.NotNull(agent);
action = agent.GetAction();
Assert.AreEqual(action.vectorActions[0], 4);
Assert.AreEqual(action.vectorActions[1], 5);
Assert.AreEqual(action.vectorActions[2], 6);
}
public void ApplyContinuousActionOutput()
{
var actionSpec = ActionSpec.MakeContinuous(3);
var inputTensor = new TensorProxy()
{
shape = new long[] { 2, 3 },
data = new Tensor(2, 3, new float[] { 1, 2, 3, 4, 5, 6 })
};
var applier = new ContinuousActionOutputApplier(actionSpec);
var agentIds = new List <int>()
{
0, 1
};
// Dictionary from AgentId to Action
var actionDict = new Dictionary <int, ActionBuffers>()
{
{ 0, ActionBuffers.Empty }, { 1, ActionBuffers.Empty }
};
applier.Apply(inputTensor, agentIds, actionDict);
Assert.AreEqual(actionDict[0].ContinuousActions[0], 1);
Assert.AreEqual(actionDict[0].ContinuousActions[1], 2);
Assert.AreEqual(actionDict[0].ContinuousActions[2], 3);
Assert.AreEqual(actionDict[1].ContinuousActions[0], 4);
Assert.AreEqual(actionDict[1].ContinuousActions[1], 5);
Assert.AreEqual(actionDict[1].ContinuousActions[2], 6);
}
public void ApplyContinuousActionOutput()
{
var inputTensor = new TensorProxy()
{
shape = new long[] { 2, 3 },
data = new Tensor(2, 3, new float[] { 1, 2, 3, 4, 5, 6 })
};
var applier = new ContinuousActionOutputApplier();
var action0 = new AgentAction();
var action1 = new AgentAction();
var callbacks = new List <AgentIdActionPair>()
{
new AgentIdActionPair {
agentId = 0, action = (a) => action0 = a
},
new AgentIdActionPair {
agentId = 1, action = (a) => action1 = a
}
};
applier.Apply(inputTensor, callbacks);
Assert.AreEqual(action0.vectorActions[0], 1);
Assert.AreEqual(action0.vectorActions[1], 2);
Assert.AreEqual(action0.vectorActions[2], 3);
Assert.AreEqual(action1.vectorActions[0], 4);
Assert.AreEqual(action1.vectorActions[1], 5);
Assert.AreEqual(action1.vectorActions[2], 6);
}
public void ApplyContinuousActionOutput()
{
var inputTensor = new Tensor()
{
Shape = new long[] { 2, 3 },
Data = new float[, ] {
{ 1, 2, 3 }, { 4, 5, 6 }
}
};
var agentInfos = GetFakeAgentInfos();
var applier = new ContinuousActionOutputApplier();
applier.Apply(inputTensor, agentInfos);
var agents = agentInfos.Keys.ToList();
var agent = agents[0] as TestAgent;
var action = agent.GetAction();
Assert.AreEqual(action.vectorActions[0], 1);
Assert.AreEqual(action.vectorActions[1], 2);
Assert.AreEqual(action.vectorActions[2], 3);
agent = agents[1] as TestAgent;
action = agent.GetAction();
Assert.AreEqual(action.vectorActions[0], 4);
Assert.AreEqual(action.vectorActions[1], 5);
Assert.AreEqual(action.vectorActions[2], 6);
}
public void ApplyHybridActionOutput()
{
var actionSpec = new ActionSpec(3, new[] { 2, 3 });
var continuousInputTensor = new TensorProxy()
{
shape = new long[] { 2, 3 },
data = new Tensor(2, 3, new float[] { 1, 2, 3, 4, 5, 6 })
};
var discreteInputTensor = new TensorProxy()
{
shape = new long[] { 2, 2 },
data = new Tensor(
2,
2,
new[] { 1f, 1f, 1f, 2f }),
};
var continuousApplier = new ContinuousActionOutputApplier(actionSpec);
var alloc = new TensorCachingAllocator();
var discreteApplier = new DiscreteActionOutputApplier(actionSpec, 0, alloc);
var agentIds = new List <int>()
{
0, 1
};
// Dictionary from AgentId to Action
var actionDict = new Dictionary <int, ActionBuffers>()
{
{ 0, ActionBuffers.Empty }, { 1, ActionBuffers.Empty }
};
continuousApplier.Apply(continuousInputTensor, agentIds, actionDict);
discreteApplier.Apply(discreteInputTensor, agentIds, actionDict);
Assert.AreEqual(actionDict[0].ContinuousActions[0], 1);
Assert.AreEqual(actionDict[0].ContinuousActions[1], 2);
Assert.AreEqual(actionDict[0].ContinuousActions[2], 3);
Assert.AreEqual(actionDict[0].DiscreteActions[0], 1);
Assert.AreEqual(actionDict[0].DiscreteActions[1], 1);
Assert.AreEqual(actionDict[1].ContinuousActions[0], 4);
Assert.AreEqual(actionDict[1].ContinuousActions[1], 5);
Assert.AreEqual(actionDict[1].ContinuousActions[2], 6);
Assert.AreEqual(actionDict[1].DiscreteActions[0], 1);
Assert.AreEqual(actionDict[1].DiscreteActions[1], 2);
alloc.Dispose();
}
