robocars/robocar-tools
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feat(training): add flag toconfigure model type training

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This commit is contained in:
Cyrille Nofficial
2022-10-06 14:05:07 +02:00
parent b7b4bd76a0
commit c4ff4b46b0
2 changed files with 46 additions and 14 deletions
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13
cmd/rc-tools/rc-tools.go
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@@ -102,7 +102,7 @@ func main() {
fmt.Printf(" run\n \tRun training job\n")
}
var modelPath, roleArn, trainJobName string
var modelPath, roleArn, trainJobName, modelType string
var horizon int
var withFlipImage bool
var trainImageHeight, trainImageWidth int
@@ -120,6 +120,7 @@ func main() {
trainingRunFlags.IntVar(&trainImageHeight, "image-height", 128, "Pixels image height")
trainingRunFlags.IntVar(&trainImageWidth, "image-width", 160, "Pixels image width")
trainingRunFlags.IntVar(&horizon, "horizon", 0, "Upper zone image to crop (in pixels)")
trainingRunFlags.StringVar(&modelType, "model-type", train.ModelTypeCategorical.String(), "Type model to build")
trainingRunFlags.BoolVar(&enableSpotTraining, "enable-spot-training", true, "Train models using managed spot training")
trainingListJobFlags := flag.NewFlagSet("list", flag.ExitOnError)
@@ -237,7 +238,7 @@ func main() {
trainingRunFlags.PrintDefaults()
os.Exit(0)
}
runTraining(bucket, ociImage, roleArn, trainJobName, recordsPath, trainSliceSize, trainImageWidth, trainImageHeight, horizon, withFlipImage, modelPath, enableSpotTraining)
runTraining(bucket, ociImage, roleArn, trainJobName, recordsPath, train.ParseModelType(modelType), trainSliceSize, trainImageWidth, trainImageHeight, horizon, withFlipImage, modelPath, enableSpotTraining)
case trainArchiveFlags.Name():
if err := trainArchiveFlags.Parse(os.Args[3:]); err == flag.ErrHelp {
trainArchiveFlags.PrintDefaults()
@@ -355,7 +356,7 @@ func runDisplay(client mqtt.Client, framePath string, frameTopic string, fps int
}
}
func runTraining(bucketName, ociImage, roleArn, jobName, dataDir string, sliceSize, imgWidth, imgHeight int, horizon int, withFlipImage bool, outputModel string, enableSpotTraining bool) {
func runTraining(bucketName, ociImage, roleArn, jobName, dataDir string, modelType train.ModelType, sliceSize, imgWidth, imgHeight int, horizon int, withFlipImage bool, outputModel string, enableSpotTraining bool) {
l := zap.S()
if bucketName == "" {
@@ -378,8 +379,12 @@ func runTraining(bucketName, ociImage, roleArn, jobName, dataDir string, sliceSi
l.Fatalf("invalid value for sie-slice, only '0' or '2' are allowed")
}
if modelType == train.ModelTypeUnknown {
l.Fatalf("invalid model type: %v", modelType)
}
training := train.New(bucketName, ociImage, roleArn)
err := training.TrainDir(context.Background(), jobName, dataDir, imgWidth, imgHeight, sliceSize, horizon, withFlipImage, outputModel, enableSpotTraining)
err := training.TrainDir(context.Background(), jobName, dataDir, modelType, imgWidth, imgHeight, sliceSize, horizon, withFlipImage, outputModel, enableSpotTraining)
if err != nil {
l.Fatalf("unable to run training: %v", err)