/dports/science/pybrain/pybrain-0.3.3/pybrain/tools/ |
H A D | neuralnets.py | 77 NetworkWriter.writeToFile(self.Trainer.module, fname) 96 self.Trainer = trainer(FNN, dataset=self.DS, **trnargs) 103 assert isinstance(self.Trainer, Trainer) 119 self.Trainer.trainEpochs(inc) 135 bestweights = self.Trainer.module.params.copy() 155 self.Trainer.module.params[:] = bestweights.copy() 202 self.Trainer = trainer(FNN, dataset=self.DS, **trnargs) 217 self.Trainer = trainer(RNN, dataset=self.DS, **trnargs) 223 assert isinstance(self.Trainer, Trainer) 239 self.Trainer.trainEpochs(inc) [all …]
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/dports/japanese/zinnia/zinnia-0.06/swig/ |
H A D | zinnia.i | 17 %feature("notabstract") zinnia::Trainer; 21 %extend zinnia::Trainer { Trainer(void); } 37 void delete_zinnia_Trainer (zinnia::Trainer *t) { in delete_zinnia_Trainer() 42 zinnia::Trainer* new_zinnia_Trainer () { in new_zinnia_Trainer() 43 return zinnia::Trainer::create(); in new_zinnia_Trainer()
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/dports/misc/py-mxnet/incubator-mxnet-1.9.0/tests/python/unittest/ |
H A D | test_gluon_trainer.py | 40 trainer0 = gluon.Trainer([x], 'sgd') 47 trainer1 = gluon.Trainer([x], 'sgd') 53 trainer = gluon.Trainer([x], 'sgd', {'learning_rate': 1.0, 'momentum': 0.5}) 80 invalid_trainer = gluon.Trainer([x], 'sgd', kvstore=kv, update_on_kvstore=True) 87 trainer = gluon.Trainer([x], 'sgd', {'learning_rate': 1.0, 'momentum': 0.5}) 122 trainer2 = gluon.Trainer([x], 'sgd', {'learning_rate': 1.0, 'momentum': 0.5}, 142 trainer = gluon.Trainer([x], 'sgd', {'learning_rate': 0.1}) 161 trainer = gluon.Trainer([x], 'sgd', {'learning_rate': 0.1}) 196 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 1}) 259 trainer = gluon.Trainer(params, 'sgd', {'learning_rate': 0.1}, [all …]
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H A D | test_gluon_estimator.py | 63 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 93 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 141 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 200 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 239 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 333 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 388 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 406 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 428 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 449 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001})
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/dports/misc/mxnet/incubator-mxnet-1.9.0/tests/python/unittest/ |
H A D | test_gluon_trainer.py | 40 trainer0 = gluon.Trainer([x], 'sgd') 47 trainer1 = gluon.Trainer([x], 'sgd') 53 trainer = gluon.Trainer([x], 'sgd', {'learning_rate': 1.0, 'momentum': 0.5}) 80 invalid_trainer = gluon.Trainer([x], 'sgd', kvstore=kv, update_on_kvstore=True) 87 trainer = gluon.Trainer([x], 'sgd', {'learning_rate': 1.0, 'momentum': 0.5}) 122 trainer2 = gluon.Trainer([x], 'sgd', {'learning_rate': 1.0, 'momentum': 0.5}, 142 trainer = gluon.Trainer([x], 'sgd', {'learning_rate': 0.1}) 161 trainer = gluon.Trainer([x], 'sgd', {'learning_rate': 0.1}) 196 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 1}) 259 trainer = gluon.Trainer(params, 'sgd', {'learning_rate': 0.1}, [all …]
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H A D | test_gluon_estimator.py | 63 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 93 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 141 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 200 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 239 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 333 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 388 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 406 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 428 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001}) 449 trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.001})
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/dports/biology/py-biopython/biopython-1.79/Tests/ |
H A D | test_HMMCasino.py | 29 from Bio.HMM import Trainer 91 known_training_seq = Trainer.TrainingSequence(self.rolls, self.states) 93 trainer = Trainer.KnownStateTrainer(standard_mm) 106 training_seq = Trainer.TrainingSequence(self.rolls, ()) 120 trainer = Trainer.BaumWelchTrainer(baum_welch_mm)
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H A D | test_HMMGeneral.py | 24 from Bio.HMM import Trainer 38 training_seq = Trainer.TrainingSequence(emission_seq, state_seq) 45 training_seq = Trainer.TrainingSequence(emission_seq, state_seq) 53 Trainer.TrainingSequence(emission_seq, state_seq) 369 training_seq = Trainer.TrainingSequence(emission_seq, state_seq) 384 self.test_trainer = Trainer.AbstractTrainer(hmm)
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/dports/emulators/nestopia/nestopia-1.51.1/source/core/board/ |
H A D | NstBoardFfe.hpp | 86 struct Trainer struct in Nes::Core::Boards::Ffe 88 explicit Trainer(const Ram&); 101 const Trainer trainer;
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H A D | NstBoardFfe.cpp | 40 Ffe::Trainer::Trainer(const Ram& ram) in Trainer() function in Nes::Core::Boards::Ffe::Trainer 76 if (trainer.available && board.GetWram() >= 0x1000 + Trainer::SIZE) in SubReset() 77 std::memcpy( wrk.Source().Mem(0x1000), trainer.data, Trainer::SIZE ); in SubReset()
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/dports/math/py-optuna/optuna-2.10.0/optuna/integration/ |
H A D | pytorch_lightning.py | 8 from pytorch_lightning import Trainer 14 Trainer = object # type: ignore # NOQA variable 43 def on_validation_end(self, trainer: Trainer, pl_module: LightningModule) -> None: argument
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/dports/games/libretro-nestopia/nestopia-2b0315c/source/core/board/ |
H A D | NstBoardFfe.hpp | 86 struct Trainer struct in Nes::Core::Boards::Ffe 88 explicit Trainer(const Ram&); 101 const Trainer trainer;
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H A D | NstBoardFfe.cpp | 40 Ffe::Trainer::Trainer(const Ram& ram) in Trainer() function in Nes::Core::Boards::Ffe::Trainer 76 if (trainer.available && board.GetWram() >= 0x1000 + Trainer::SIZE) in SubReset() 77 std::memcpy( wrk.Source().Mem(0x1000), trainer.data, Trainer::SIZE ); in SubReset()
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/dports/japanese/zinnia/zinnia-0.06/ |
H A D | libzinnia.cpp | 38 zinnia::Trainer *ptr; 199 trainer->ptr = zinnia::Trainer::create(); in zinnia_trainer_new() 229 return zinnia::Trainer::convert(txt_model, binary_model, in zinnia_trainer_convert_model() 236 return zinnia::Trainer::makeHeader(txt_model, header_file, in zinnia_trainer_make_header() 340 zinnia::scoped_ptr<zinnia::Trainer> trainer(zinnia::Trainer::create()); in zinnia_learn() 394 CHECK_DIE(zinnia::Trainer::makeHeader(text_file.c_str(), model_file.c_str(), in zinnia_convert() 400 CHECK_DIE(zinnia::Trainer::convert(text_file.c_str(), model_file.c_str(), c)); in zinnia_convert()
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H A D | trainer.cpp | 88 class TrainerImpl: public Trainer { 173 bool Trainer::makeHeader(const char *text_filename, in makeHeader() 271 bool Trainer::convert(const char *text_filename, in convert() 333 Trainer *createTrainer() { in createTrainer() 337 Trainer *Trainer::create() { in create()
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/dports/www/chromium-legacy/chromium-88.0.4324.182/chrome/browser/chromeos/power/auto_screen_brightness/ |
H A D | modeller_impl.h | 79 std::unique_ptr<Trainer> trainer); 109 std::unique_ptr<Trainer> trainer, 140 std::unique_ptr<Trainer> trainer, 233 std::unique_ptr<Trainer, base::OnTaskRunnerDeleter> trainer_;
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H A D | trainer.h | 27 class Trainer { 29 virtual ~Trainer() = default;
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/dports/devel/py-naiveBayesClassifier/naiveBayesClassifier-0.1.3/naiveBayesClassifier/ |
H A D | trainer.py | 3 class Trainer(object): class 7 super(Trainer, self).__init__()
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/dports/misc/mxnet/incubator-mxnet-1.9.0/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/util/ |
H A D | Trainer.scala | 25 object Trainer { object 26 private val logger = LoggerFactory.getLogger(classOf[Trainer]) 134 class Trainer class
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/dports/misc/py-mxnet/incubator-mxnet-1.9.0/scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/util/ |
H A D | Trainer.scala | 25 object Trainer { object 26 private val logger = LoggerFactory.getLogger(classOf[Trainer]) 134 class Trainer class
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/dports/games/scourge-data/scourge_data/maps/ |
H A D | library1.cfg | 11 name="Korga the Trainer" 12 display_name=_( "Korga the Trainer" )
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/dports/archivers/zip-ada/zip-ada/trained/ |
H A D | trainer.adb | 47 procedure Trainer is subprogram 91 end Trainer; argument
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/dports/misc/mxnet/incubator-mxnet-1.9.0/perl-package/AI-MXNet/t/ |
H A D | test_gluon_trainer.t | 35 my $trainer0 = gluon->Trainer([$x], 'sgd'); 42 dies_ok(sub { gluon->Trainer([$x], 'sgd') }); 56 my $trainer = gluon->Trainer([$x], 'sgd', {'learning_rate'=> 1.0, 'momentum'=> 0.5}); 112 my $trainer2 = gluon->Trainer([$x], 'sgd', {learning_rate => 1.0, momentum => 0.5}, 136 my $trainer = gluon->Trainer([$x], 'sgd', {learning_rate => 0.1}); 184 my $trainer = gluon->Trainer($net->collect_params(), 'sgd', {learning_rate => 1}); 222 my $trainer = gluon->Trainer($params, 'sgd', {learning_rate => 0.1}, kvstore=>$kv);
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/dports/misc/py-mxnet/incubator-mxnet-1.9.0/perl-package/AI-MXNet/t/ |
H A D | test_gluon_trainer.t | 35 my $trainer0 = gluon->Trainer([$x], 'sgd'); 42 dies_ok(sub { gluon->Trainer([$x], 'sgd') }); 56 my $trainer = gluon->Trainer([$x], 'sgd', {'learning_rate'=> 1.0, 'momentum'=> 0.5}); 112 my $trainer2 = gluon->Trainer([$x], 'sgd', {learning_rate => 1.0, momentum => 0.5}, 136 my $trainer = gluon->Trainer([$x], 'sgd', {learning_rate => 0.1}); 184 my $trainer = gluon->Trainer($net->collect_params(), 'sgd', {learning_rate => 1}); 222 my $trainer = gluon->Trainer($params, 'sgd', {learning_rate => 0.1}, kvstore=>$kv);
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/scripts/depth/ |
H A D | train.py | 13 from trainer import Trainer 33 trainer = Trainer(opts, logger)
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