| /dports/misc/mxnet/incubator-mxnet-1.9.0/scala-package/core/src/main/scala/org/apache/mxnet/module/ |
| H A D | SequentialModule.scala | 223 forTraining: Boolean = true, inputsNeedGrad: Boolean = false,
230 require(forTraining, "inputsNeedGrad can be set only for training")
236 this.forTraining = forTraining
253 val myInputsNeedGrad = if (inputsNeedGrad || (forTraining && iLayer > 0)) true else false
263 module.bind(myDataShapes, myLabelShapes, forTraining, myInputsNeedGrad,
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| H A D | BucketingModule.scala | 206 forTraining: Boolean = true, inputsNeedGrad: Boolean = false,
224 this.forTraining = forTraining
231 module.bind(dataShapes, labelShapes, forTraining, inputsNeedGrad,
257 module.bind(dataShapes, labelShapes, this._currModule.forTraining,
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| H A D | DataParallelExecutorGroup.scala | 127 private var forTraining: Boolean = true
165 def setForTraining(forTraining: Boolean): Builder = {
166 this.forTraining = forTraining
226 symbol, contexts, workLoadList, dataShapes, labelShapes, paramNames, forTraining,
274 forTraining: Boolean,
288 if (!forTraining) {
409 if (forTraining) {
493 val isTrainOpt = isTrain.getOrElse(this.forTraining)
571 require(forTraining, "re-bind with forTraining = true to run backward")
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| H A D | BaseModule.scala | 139 private[module] var forTraining: Boolean = false
415 forTraining = true, forceRebind = fitParams.forceRebind)
572 forTraining: Boolean = true, inputsNeedGrad: Boolean = false,
590 @varargs def bind(forTraining: Boolean, inputsNeedGrad: Boolean,
592 bind(dataShape.toVector, None, forTraining, inputsNeedGrad, forceRebind, None)
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| H A D | Module.scala | 238 forTraining: Boolean = true, inputsNeedGrad: Boolean = false,
249 this.forTraining = forTraining
253 if (!forTraining) {
279 .setForTraining(forTraining)
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| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/scala-package/core/src/main/scala/org/apache/mxnet/module/ |
| H A D | SequentialModule.scala | 223 forTraining: Boolean = true, inputsNeedGrad: Boolean = false,
230 require(forTraining, "inputsNeedGrad can be set only for training")
236 this.forTraining = forTraining
253 val myInputsNeedGrad = if (inputsNeedGrad || (forTraining && iLayer > 0)) true else false
263 module.bind(myDataShapes, myLabelShapes, forTraining, myInputsNeedGrad,
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| H A D | BucketingModule.scala | 206 forTraining: Boolean = true, inputsNeedGrad: Boolean = false,
224 this.forTraining = forTraining
231 module.bind(dataShapes, labelShapes, forTraining, inputsNeedGrad,
257 module.bind(dataShapes, labelShapes, this._currModule.forTraining,
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| H A D | DataParallelExecutorGroup.scala | 127 private var forTraining: Boolean = true
165 def setForTraining(forTraining: Boolean): Builder = {
166 this.forTraining = forTraining
226 symbol, contexts, workLoadList, dataShapes, labelShapes, paramNames, forTraining,
274 forTraining: Boolean,
288 if (!forTraining) {
409 if (forTraining) {
493 val isTrainOpt = isTrain.getOrElse(this.forTraining)
571 require(forTraining, "re-bind with forTraining = true to run backward")
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| H A D | BaseModule.scala | 139 private[module] var forTraining: Boolean = false
415 forTraining = true, forceRebind = fitParams.forceRebind)
572 forTraining: Boolean = true, inputsNeedGrad: Boolean = false,
590 @varargs def bind(forTraining: Boolean, inputsNeedGrad: Boolean,
592 bind(dataShape.toVector, None, forTraining, inputsNeedGrad, forceRebind, None)
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| H A D | Module.scala | 238 forTraining: Boolean = true, inputsNeedGrad: Boolean = false,
249 this.forTraining = forTraining
253 if (!forTraining) {
279 .setForTraining(forTraining)
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| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/scala-package/infer/src/main/scala/org/apache/mxnet/infer/ |
| H A D | Predictor.scala | 183 forTraining = false))
197 mxNetHandler.execute(mod.bind(inputDescriptors, forTraining = false, forceRebind = true))
238 forTraining = false))
246 forTraining = false))
258 mxNetHandler.execute(mod.bind(inputDescriptors, forTraining = false))
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/scala-package/infer/src/main/scala/org/apache/mxnet/infer/ |
| H A D | Predictor.scala | 183 forTraining = false))
197 mxNetHandler.execute(mod.bind(inputDescriptors, forTraining = false, forceRebind = true))
238 forTraining = false))
246 forTraining = false))
258 mxNetHandler.execute(mod.bind(inputDescriptors, forTraining = false))
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| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/end2end/ |
| H A D | GenV4.scala | 61 val (dataShapes, forTraining, inputsNeedGrad) = {
69 forTraining = forTraining, inputsNeedGrad = inputsNeedGrad)
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| H A D | GenV3.scala | 73 val (dataShapes, forTraining, inputsNeedGrad) = {
81 forTraining = forTraining, inputsNeedGrad = inputsNeedGrad)
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| H A D | Basic.scala | 64 initializer = init, forTraining = false)
102 initializer = init, forTraining = false)
115 initializer = init, forTraining = true,
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| H A D | Module.scala | 28 forTraining: Boolean = true,
77 this.executor.forward(isTrain = forTraining)
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| /dports/misc/mxnet/incubator-mxnet-1.9.0/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/end2end/ |
| H A D | GenV4.scala | 61 val (dataShapes, forTraining, inputsNeedGrad) = {
69 forTraining = forTraining, inputsNeedGrad = inputsNeedGrad)
|
| H A D | GenV3.scala | 73 val (dataShapes, forTraining, inputsNeedGrad) = {
81 forTraining = forTraining, inputsNeedGrad = inputsNeedGrad)
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| H A D | Basic.scala | 64 initializer = init, forTraining = false)
102 initializer = init, forTraining = false)
115 initializer = init, forTraining = true,
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| H A D | Module.scala | 28 forTraining: Boolean = true,
77 this.executor.forward(isTrain = forTraining)
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| /dports/misc/mnn/MNN-1.2.0/tools/converter/include/ |
| H A D | PostConverter.hpp | 27 …ique_ptr<MNN::NetT> optimizeNet(std::unique_ptr<MNN::NetT>& netT, bool forTraining, modelConfig& c…
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| H A D | config.hpp | 41 bool forTraining = false; member in modelConfig
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| /dports/misc/mnn/MNN-1.2.0/tools/converter/source/common/ |
| H A D | cli.cpp | 187 modelPath.forTraining = true; in initializeMNNConvertArgs()
247 std::unique_ptr<MNN::NetT> newNet = optimizeNet(netT, modelPath.forTraining, modelPath); in convertModel()
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| /dports/misc/mnn/MNN-1.2.0/tools/converter/source/optimizer/ |
| H A D | PostConverter.cpp | 484 std::unique_ptr<MNN::NetT> optimizeNet(std::unique_ptr<MNN::NetT>& originNet, bool forTraining, mod… in optimizeNet() argument
495 ctx.is_training = forTraining; in optimizeNet()
|