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Merged
merged 13 commits into from
Sep 11, 2019
Merged

Reducing complexity on a number of classes. #2480

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24ef79e
Inprovements to Utilities.cs
Aug 31, 2019
3deab68
Clean-up to UnityAgentsException.cs
Aug 31, 2019
75ad25e
Improvements to Startup.cs
Aug 31, 2019
fa68317
Adding team-wide settings file
Aug 31, 2019
b86c24d
Clean up to RandomNormal
Aug 31, 2019
64862f1
Decouples DiscreteActionOutputApplier from Multinomial
Sep 1, 2019
0551584
Minor formatting to TensorProxy
Sep 1, 2019
fa820bd
Adding new line to EOF for TensorProxy
Sep 1, 2019
a502e08
Adding missing meta files.
Sep 1, 2019
d9bfe42
Removing three unused methods from TensorProxy
Sep 1, 2019
a48cb98
(Big) Rename of TensorProxy fields
Sep 1, 2019
5744a7d
Additional cosmetic changes to a number of files previously modified
Sep 1, 2019
03a8f63
Improvements to Multinomial(Test).cs
Sep 9, 2019
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(Big) Rename of TensorProxy fields 
Changed Name —> name; ValueType —> valueType; Shape —> shape; Data —> data
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Marwan Mattar committed Sep 1, 2019
commit a48cb988d99bdd93c757c7c2dcd428bc472fb636
60 changes: 30 additions & 30 deletions UnitySDK/Assets/ML-Agents/Editor/Tests/DiscreteActionOutputApplierTest.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -16,22 +16,22 @@ public void TestEvalP()

var src = new TensorProxy
{
Data = new Tensor(1, 3, new[] {0.1f, 0.2f, 0.7f}),
ValueType = TensorProxy.TensorType.FloatingPoint
data = new Tensor(1, 3, new[] {0.1f, 0.2f, 0.7f}),
valueType = TensorProxy.TensorType.FloatingPoint
};

var dst = new TensorProxy
{
Data = new Tensor(1, 3),
ValueType = TensorProxy.TensorType.FloatingPoint
data = new Tensor(1, 3),
valueType = TensorProxy.TensorType.FloatingPoint
};

DiscreteActionOutputApplier.Eval(src, dst, m);

float[] reference = {2, 2, 1};
for (var i = 0; i < dst.Data.length; i++)
for (var i = 0; i < dst.data.length; i++)
{
Assert.AreEqual(reference[i], dst.Data[i]);
Assert.AreEqual(reference[i], dst.data[i]);
++i;
}
}
Expand All @@ -43,22 +43,22 @@ public void TestEvalLogits()

var src = new TensorProxy
{
Data = new Tensor(1, 3, new[] {Mathf.Log(0.1f) - 50, Mathf.Log(0.2f) - 50, Mathf.Log(0.7f) - 50}),
ValueType = TensorProxy.TensorType.FloatingPoint
data = new Tensor(1, 3, new[] {Mathf.Log(0.1f) - 50, Mathf.Log(0.2f) - 50, Mathf.Log(0.7f) - 50}),
valueType = TensorProxy.TensorType.FloatingPoint
};

var dst = new TensorProxy
{
Data = new Tensor(1, 3),
ValueType = TensorProxy.TensorType.FloatingPoint
data = new Tensor(1, 3),
valueType = TensorProxy.TensorType.FloatingPoint
};

DiscreteActionOutputApplier.Eval(src, dst, m);

float[] reference = {2, 2, 2};
for (var i = 0; i < dst.Data.length; i++)
for (var i = 0; i < dst.data.length; i++)
{
Assert.AreEqual(reference[i], dst.Data[i]);
Assert.AreEqual(reference[i], dst.data[i]);
++i;
}
}
Expand All @@ -70,27 +70,27 @@ public void TestEvalBatching()

var src = new TensorProxy
{
Data = new Tensor(2, 3, new []
data = new Tensor(2, 3, new []
{
Mathf.Log(0.1f) - 50, Mathf.Log(0.2f) - 50, Mathf.Log(0.7f) - 50,
Mathf.Log(0.3f) - 25, Mathf.Log(0.4f) - 25, Mathf.Log(0.3f) - 25

}),
ValueType = TensorProxy.TensorType.FloatingPoint
valueType = TensorProxy.TensorType.FloatingPoint
};

var dst = new TensorProxy
{
Data = new Tensor(2, 3),
ValueType = TensorProxy.TensorType.FloatingPoint
data = new Tensor(2, 3),
valueType = TensorProxy.TensorType.FloatingPoint
};

DiscreteActionOutputApplier.Eval(src, dst, m);

float[] reference = {2, 2, 2, 0, 1, 0};
for (var i = 0; i < dst.Data.length; i++)
for (var i = 0; i < dst.data.length; i++)
{
Assert.AreEqual(reference[i], dst.Data[i]);
Assert.AreEqual(reference[i], dst.data[i]);
++i;
}
}
Expand All @@ -102,7 +102,7 @@ public void TestSrcInt()

var src = new TensorProxy
{
ValueType = TensorProxy.TensorType.Integer
valueType = TensorProxy.TensorType.Integer
};

Assert.Throws<NotImplementedException>(() => DiscreteActionOutputApplier.Eval(src, null, m));
Expand All @@ -115,12 +115,12 @@ public void TestDstInt()

var src = new TensorProxy
{
ValueType = TensorProxy.TensorType.FloatingPoint
valueType = TensorProxy.TensorType.FloatingPoint
};

var dst = new TensorProxy
{
ValueType = TensorProxy.TensorType.Integer
valueType = TensorProxy.TensorType.Integer
};

Assert.Throws<ArgumentException>(() => DiscreteActionOutputApplier.Eval(src, dst, m));
Expand All @@ -133,12 +133,12 @@ public void TestSrcDataNull()

var src = new TensorProxy
{
ValueType = TensorProxy.TensorType.FloatingPoint
valueType = TensorProxy.TensorType.FloatingPoint
};

var dst = new TensorProxy
{
ValueType = TensorProxy.TensorType.FloatingPoint
valueType = TensorProxy.TensorType.FloatingPoint
};

Assert.Throws<ArgumentNullException>(() => DiscreteActionOutputApplier.Eval(src, dst, m));
Expand All @@ -151,13 +151,13 @@ public void TestDstDataNull()

var src = new TensorProxy
{
ValueType = TensorProxy.TensorType.FloatingPoint,
Data = new Tensor(0,1)
valueType = TensorProxy.TensorType.FloatingPoint,
data = new Tensor(0,1)
};

var dst = new TensorProxy
{
ValueType = TensorProxy.TensorType.FloatingPoint
valueType = TensorProxy.TensorType.FloatingPoint
};

Assert.Throws<ArgumentNullException>(() => DiscreteActionOutputApplier.Eval(src, dst, m));
Expand All @@ -170,14 +170,14 @@ public void TestUnequalBatchSize()

var src = new TensorProxy
{
ValueType = TensorProxy.TensorType.FloatingPoint,
Data = new Tensor(1, 1)
valueType = TensorProxy.TensorType.FloatingPoint,
data = new Tensor(1, 1)
};

var dst = new TensorProxy
{
ValueType = TensorProxy.TensorType.FloatingPoint,
Data = new Tensor(2, 1)
valueType = TensorProxy.TensorType.FloatingPoint,
data = new Tensor(2, 1)
};

Assert.Throws<ArgumentException>(() => DiscreteActionOutputApplier.Eval(src, dst, m));
Expand Down
16 changes: 8 additions & 8 deletions UnitySDK/Assets/ML-Agents/Editor/Tests/EditModeTestInternalBrainTensorApplier.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -47,8 +47,8 @@ public void ApplyContinuousActionOutput()
{
var inputTensor = new TensorProxy()
{
Shape = new long[] {2, 3},
Data = new Tensor (2, 3, new float[] {1, 2, 3,
shape = new long[] {2, 3},
data = new Tensor (2, 3, new float[] {1, 2, 3,
4, 5, 6})
};
var agentInfos = GetFakeAgentInfos();
Expand All @@ -73,8 +73,8 @@ public void ApplyDiscreteActionOutput()
{
var inputTensor = new TensorProxy()
{
Shape = new long[] {2, 5},
Data = new Tensor (2, 5, new[] {0.5f, 22.5f, 0.1f, 5f, 1f,
shape = new long[] {2, 5},
data = new Tensor (2, 5, new[] {0.5f, 22.5f, 0.1f, 5f, 1f,
4f, 5f, 6f, 7f, 8f})
};
var agentInfos = GetFakeAgentInfos();
Expand All @@ -98,8 +98,8 @@ public void ApplyMemoryOutput()
{
var inputTensor = new TensorProxy()
{
Shape = new long[] {2, 5},
Data = new Tensor (2, 5, new[] {0.5f, 22.5f, 0.1f, 5f, 1f,
shape = new long[] {2, 5},
data = new Tensor (2, 5, new[] {0.5f, 22.5f, 0.1f, 5f, 1f,
4f, 5f, 6f, 7f, 8f})
};
var agentInfos = GetFakeAgentInfos();
Expand All @@ -122,8 +122,8 @@ public void ApplyValueEstimate()
{
var inputTensor = new TensorProxy()
{
Shape = new long[] {2, 1},
Data = new Tensor (2, 1, new[]{0.5f, 8f})
shape = new long[] {2, 1},
data = new Tensor (2, 1, new[]{0.5f, 8f})
};
var agentInfos = GetFakeAgentInfos();

Expand Down
60 changes: 30 additions & 30 deletions UnitySDK/Assets/ML-Agents/Editor/Tests/EditModeTestInternalBrainTensorGenerator.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -58,8 +58,8 @@ public void GenerateBatchSize()
var batchSize = 4;
var generator = new BatchSizeGenerator(alloc);
generator.Generate(inputTensor, batchSize, null);
Assert.IsNotNull(inputTensor.Data);
Assert.AreEqual(inputTensor.Data[0], batchSize);
Assert.IsNotNull(inputTensor.data);
Assert.AreEqual(inputTensor.data[0], batchSize);
alloc.Dispose();
}

Expand All @@ -71,8 +71,8 @@ public void GenerateSequenceLength()
var batchSize = 4;
var generator = new SequenceLengthGenerator(alloc);
generator.Generate(inputTensor, batchSize, null);
Assert.IsNotNull(inputTensor.Data);
Assert.AreEqual(inputTensor.Data[0], 1);
Assert.IsNotNull(inputTensor.data);
Assert.AreEqual(inputTensor.data[0], 1);
alloc.Dispose();
}

Expand All @@ -81,18 +81,18 @@ public void GenerateVectorObservation()
{
var inputTensor = new TensorProxy()
{
Shape = new long[] {2, 3}
shape = new long[] {2, 3}
};
var batchSize = 4;
var agentInfos = GetFakeAgentInfos();
var alloc = new TensorCachingAllocator();
var generator = new VectorObservationGenerator(alloc);
generator.Generate(inputTensor, batchSize, agentInfos);
Assert.IsNotNull(inputTensor.Data);
Assert.AreEqual(inputTensor.Data[0, 0], 1);
Assert.AreEqual(inputTensor.Data[0, 2], 3);
Assert.AreEqual(inputTensor.Data[1, 0], 4);
Assert.AreEqual(inputTensor.Data[1, 2], 6);
Assert.IsNotNull(inputTensor.data);
Assert.AreEqual(inputTensor.data[0, 0], 1);
Assert.AreEqual(inputTensor.data[0, 2], 3);
Assert.AreEqual(inputTensor.data[1, 0], 4);
Assert.AreEqual(inputTensor.data[1, 2], 6);
alloc.Dispose();
}

Expand All @@ -101,18 +101,18 @@ public void GenerateRecurrentInput()
{
var inputTensor = new TensorProxy()
{
Shape = new long[] {2, 5}
shape = new long[] {2, 5}
};
var batchSize = 4;
var agentInfos = GetFakeAgentInfos();
var alloc = new TensorCachingAllocator();
var generator = new RecurrentInputGenerator(alloc);
generator.Generate(inputTensor, batchSize, agentInfos);
Assert.IsNotNull(inputTensor.Data);
Assert.AreEqual(inputTensor.Data[0, 0], 0);
Assert.AreEqual(inputTensor.Data[0, 4], 0);
Assert.AreEqual(inputTensor.Data[1, 0], 1);
Assert.AreEqual(inputTensor.Data[1, 4], 0);
Assert.IsNotNull(inputTensor.data);
Assert.AreEqual(inputTensor.data[0, 0], 0);
Assert.AreEqual(inputTensor.data[0, 4], 0);
Assert.AreEqual(inputTensor.data[1, 0], 1);
Assert.AreEqual(inputTensor.data[1, 4], 0);
alloc.Dispose();
}

Expand All @@ -121,8 +121,8 @@ public void GeneratePreviousActionInput()
{
var inputTensor = new TensorProxy()
{
Shape = new long[] {2, 2},
ValueType = TensorProxy.TensorType.Integer
shape = new long[] {2, 2},
valueType = TensorProxy.TensorType.Integer

};
var batchSize = 4;
Expand All @@ -131,11 +131,11 @@ public void GeneratePreviousActionInput()
var generator = new PreviousActionInputGenerator(alloc);

generator.Generate(inputTensor, batchSize, agentInfos);
Assert.IsNotNull(inputTensor.Data);
Assert.AreEqual(inputTensor.Data[0, 0], 1);
Assert.AreEqual(inputTensor.Data[0, 1], 2);
Assert.AreEqual(inputTensor.Data[1, 0], 3);
Assert.AreEqual(inputTensor.Data[1, 1], 4);
Assert.IsNotNull(inputTensor.data);
Assert.AreEqual(inputTensor.data[0, 0], 1);
Assert.AreEqual(inputTensor.data[0, 1], 2);
Assert.AreEqual(inputTensor.data[1, 0], 3);
Assert.AreEqual(inputTensor.data[1, 1], 4);
alloc.Dispose();
}

Expand All @@ -144,20 +144,20 @@ public void GenerateActionMaskInput()
{
var inputTensor = new TensorProxy()
{
Shape = new long[] {2, 5},
ValueType = TensorProxy.TensorType.FloatingPoint
shape = new long[] {2, 5},
valueType = TensorProxy.TensorType.FloatingPoint

};
var batchSize = 4;
var agentInfos = GetFakeAgentInfos();
var alloc = new TensorCachingAllocator();
var generator = new ActionMaskInputGenerator(alloc);
generator.Generate(inputTensor, batchSize, agentInfos);
Assert.IsNotNull(inputTensor.Data);
Assert.AreEqual(inputTensor.Data[0, 0], 1);
Assert.AreEqual(inputTensor.Data[0, 4], 1);
Assert.AreEqual(inputTensor.Data[1, 0], 0);
Assert.AreEqual(inputTensor.Data[1, 4], 1);
Assert.IsNotNull(inputTensor.data);
Assert.AreEqual(inputTensor.data[0, 0], 1);
Assert.AreEqual(inputTensor.data[0, 4], 1);
Assert.AreEqual(inputTensor.data[1, 0], 0);
Assert.AreEqual(inputTensor.data[1, 4], 1);
alloc.Dispose();
}
}
Expand Down
12 changes: 6 additions & 6 deletions UnitySDK/Assets/ML-Agents/Editor/Tests/TensorUtilsTest.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ public void RandomNormalTestTensorInt()
var rn = new RandomNormal(1982);
var t = new TensorProxy
{
ValueType = TensorProxy.TensorType.Integer
valueType = TensorProxy.TensorType.Integer
};

Assert.Throws<NotImplementedException>(
Expand All @@ -27,7 +27,7 @@ public void RandomNormalTestDataNull()
var rn = new RandomNormal(1982);
var t = new TensorProxy
{
ValueType = TensorProxy.TensorType.FloatingPoint
valueType = TensorProxy.TensorType.FloatingPoint
};

Assert.Throws<ArgumentNullException>(
Expand All @@ -40,8 +40,8 @@ public void RandomNormalTestTensor()
var rn = new RandomNormal(1982);
var t = new TensorProxy
{
ValueType = TensorProxy.TensorType.FloatingPoint,
Data = new Tensor(1, 3, 4, 2)
valueType = TensorProxy.TensorType.FloatingPoint,
data = new Tensor(1, 3, 4, 2)
};

TensorUtils.FillTensorWithRandomNormal(t, rn);
Expand Down Expand Up @@ -74,9 +74,9 @@ public void RandomNormalTestTensor()
-1.177194f,
};

for (var i = 0; i < t.Data.length; i++)
for (var i = 0; i < t.data.length; i++)
{
Assert.AreEqual(t.Data[i], reference[i], 0.0001);
Assert.AreEqual(t.data[i], reference[i], 0.0001);
}
}
}
Expand Down
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