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Added cross entropy support to validation training, edited metric reporting #5255

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Merged
merged 8 commits into from
Jul 2, 2020
Merged

Added cross entropy support to validation training, edited metric reporting #5255

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f3f3125
Added cross entropy to validation training, simplified metric reporting
mstfbl Jun 24, 2020
bdcddf3
Edited runnerOutputTensorNames for validation runner, and added test …
mstfbl Jun 25, 2020
63058ba
Added more tests to validate learning rate schedulers in validation a…
mstfbl Jun 25, 2020
062458b
Removed learning rate decay from validation phase
mstfbl Jul 1, 2020
76d2a00
Update validationEvalRunner
mstfbl Jul 1, 2020
8ca3f79
Set learning rate scheduler to null during validation, update ToString()
mstfbl Jul 2, 2020
35018d6
Update ToString() for uniform alignment
mstfbl Jul 2, 2020
dbe3baf
Update TensorflowTests.cs
mstfbl Jul 2, 2020
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12 changes: 8 additions & 4 deletions src/Microsoft.ML.Vision/ImageClassificationTrainer.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -170,11 +170,11 @@ public sealed class TrainMetrics
public override string ToString()
{
if (DatasetUsed == ImageClassificationMetrics.Dataset.Train)
return $"Phase: Training, Dataset used: {DatasetUsed.ToString(),10}, Batch Processed Count: {BatchProcessedCount,3}, Learning Rate: {LearningRate,10} " +
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@mstfbl mstfbl Jul 2, 2020 •
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I have added learning rate to the end of the string here for cosmetic reasons. Now there is uniform alignment of columns' statistics between training and validation. :) #Resolved

$"Epoch: {Epoch,3}, Accuracy: {Accuracy,10}, Cross-Entropy: {CrossEntropy,10}";
return $"Phase: Training, Dataset used: {DatasetUsed.ToString(),10}, Batch Processed Count: {BatchProcessedCount,3}, " +
$"Epoch: {Epoch,3}, Accuracy: {Accuracy,10}, Cross-Entropy: {CrossEntropy,10}, Learning Rate: {LearningRate,10}";
else
return $"Phase: Training, Dataset used: {DatasetUsed.ToString(),10}, Batch Processed Count: {BatchProcessedCount,3}, " +
$"Epoch: {Epoch,3}, Accuracy: {Accuracy,10}";
$"Epoch: {Epoch,3}, Accuracy: {Accuracy,10}, Cross-Entropy: {CrossEntropy,10}";
}
}

Expand Down Expand Up @@ -952,7 +952,7 @@ private void TrainAndEvaluateClassificationLayer(string trainBottleneckFilePath,
if (validationNeeded)
{
validationEvalRunner = new Runner(_session, new[] { _bottleneckInput.name, _labelTensor.name },
new[] { _evaluationStep.name });
new[] { _evaluationStep.name, _crossEntropy.name });
}

runner = new Runner(_session, runnerInputTensorNames.ToArray(),
Expand Down Expand Up @@ -1036,14 +1036,18 @@ private void TrainAndEvaluateClassificationLayer(string trainBottleneckFilePath,
(outputTensors, metrics) =>
{
outputTensors[0].ToScalar(ref accuracy);
outputTensors[1].ToScalar(ref crossentropy);
metrics.Train.Accuracy += accuracy;
metrics.Train.CrossEntropy += crossentropy;
outputTensors[0].Dispose();
outputTensors[1].Dispose();
});

if (statisticsCallback != null)
{
metrics.Train.Epoch = epoch;
metrics.Train.Accuracy /= metrics.Train.BatchProcessedCount;
metrics.Train.CrossEntropy /= metrics.Train.BatchProcessedCount;
metrics.Train.DatasetUsed = ImageClassificationMetrics.Dataset.Validation;
statisticsCallback(metrics);
}
Expand Down
28 changes: 26 additions & 2 deletions test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -1489,7 +1489,6 @@ public void TensorFlowImageClassificationWithExponentialLRScheduling()
[TensorFlowFact]
public void TensorFlowImageClassificationWithPolynomialLRScheduling()
{

TensorFlowImageClassificationWithLRScheduling(new PolynomialLRDecay(), 50);
}

Expand Down Expand Up @@ -1521,6 +1520,8 @@ internal void TensorFlowImageClassificationWithLRScheduling(LearningRateSchedule
var (trainSetBottleneckCachedValuesFileName, validationSetBottleneckCachedValuesFileName,
workspacePath, isReuse) = getInitialParameters(ImageClassificationTrainer.Architecture.ResnetV2101, _finalImagesFolderName);

float[] crossEntropyTraining = new float[epoch];
float[] crossEntropyValidation = new float[epoch];
var options = new ImageClassificationTrainer.Options()
{
FeatureColumnName = "Image",
Expand All @@ -1532,7 +1533,30 @@ internal void TensorFlowImageClassificationWithLRScheduling(LearningRateSchedule
Epoch = epoch,
BatchSize = 10,
LearningRate = 0.01f,
MetricsCallback = (metric) => Console.WriteLine(metric),
MetricsCallback = (metric) =>
{
if (metric.Train != null)
{
// Check that cross validation rates during both the training and validation phases are decreasing and are sensible
if (metric.Train.DatasetUsed == ImageClassificationTrainer.ImageClassificationMetrics.Dataset.Train)
{
// Save cross entropy values in training phase
crossEntropyTraining[metric.Train.Epoch] = metric.Train.CrossEntropy;
// Check that cross entropy values over each epoch-per-decay are decreasing in training phase
if (metric.Train.Epoch > 0)
Assert.True(crossEntropyTraining[metric.Train.Epoch - 1] > crossEntropyTraining[metric.Train.Epoch]);
}
else
{
// Save cross entropy values in validation phase
crossEntropyValidation[metric.Train.Epoch] = metric.Train.CrossEntropy;
// Check that cross entropy values over each epoch-per-decay are decreasing in validation phase
if (metric.Train.Epoch > 0)
Assert.True(crossEntropyValidation[metric.Train.Epoch - 1] > crossEntropyValidation[metric.Train.Epoch]);
}
}
Console.WriteLine(metric);
},
ValidationSet = validationSet,
WorkspacePath = workspacePath,
TrainSetBottleneckCachedValuesFileName = trainSetBottleneckCachedValuesFileName,
Expand Down