| /third_party/mindspore/tests/ut/python/dataset/ |
| D | test_callbacks.py | 102 def build_test_case_1cb(epochs, steps, step_size=1, repeat=1): argument
118 itr = data.create_tuple_iterator(num_epochs=epochs)
119 for _ in range(epochs):
123 expected_events = generate_expected(epochs, steps, step_size, 1, repeat)
127 def build_test_case_2cbs(epochs, steps): argument
138 itr = data.create_tuple_iterator(num_epochs=epochs)
139 for _ in range(epochs):
143 expected_events = generate_expected(epochs, steps)
148 def build_test_case_2maps(epochs, steps): argument
159 itr = data.create_tuple_iterator(num_epochs=epochs)
[all …]
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| /third_party/mindspore/tests/st/model_zoo_tests/wide_and_deep/python_file_for_ci/ |
| D | datasets.py | 33 def _get_tf_dataset(data_dir, train_mode=True, epochs=1, batch_size=1000, argument
65 data_set = data_set.repeat(epochs)
69 def _get_mindrecord_dataset(directory, train_mode=True, epochs=1, batch_size=1000, argument
106 data_set = data_set.repeat(epochs)
110 def create_dataset(data_dir, train_mode=True, epochs=1, batch_size=1000, argument
116 return _get_tf_dataset(data_dir, train_mode, epochs, batch_size,
118 return _get_mindrecord_dataset(data_dir, train_mode, epochs,
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| D | train_and_test_multinpu_ci.py | 78 epochs = config.epochs
79 print("epochs is {}".format(epochs))
80 ds_train = create_dataset(data_path, train_mode=True, epochs=1, batch_size=batch_size,
82 ds_eval = create_dataset(data_path, train_mode=False, epochs=1, batch_size=batch_size,
99 model.train(epochs, ds_train,
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| D | config.py | 51 self.epochs = 1
81 self.epochs = args.epochs
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| /third_party/mindspore/tests/st/model_zoo_tests/wide_and_deep/ |
| D | train_and_test_multinpu_ci_data_parallel.py | 76 epochs = config.epochs
77 print("epochs is {}".format(epochs))
78 ds_train = create_dataset(data_path, train_mode=True, epochs=1,
80 ds_eval = create_dataset(data_path, train_mode=False, epochs=1,
101 model.train(epochs, ds_train,
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| /third_party/mindspore/tests/st/model_zoo_tests/DeepFM/src/ |
| D | dataset.py | 149 def _get_h5_dataset(directory, train_mode=True, epochs=1, batch_size=1000): argument
176 data_set = data_set.repeat(epochs)
180 def _get_mindrecord_dataset(directory, train_mode=True, epochs=1, batch_size=1000, argument
217 data_set = data_set.repeat(epochs)
221 def _get_tf_dataset(directory, train_mode=True, epochs=1, batch_size=1000, argument
265 data_set = data_set.repeat(epochs)
269 def create_dataset(directory, train_mode=True, epochs=1, batch_size=1000, argument
289 return _get_mindrecord_dataset(directory, train_mode, epochs,
293 return _get_tf_dataset(directory, train_mode, epochs, batch_size,
298 return _get_h5_dataset(directory, train_mode, epochs, batch_size)
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| /third_party/mindspore/mindspore/nn/probability/infer/variational/ |
| D | svi.py | 52 def run(self, train_dataset, epochs=10): argument
63 epochs = Validator.check_positive_int(epochs)
66 for _ in range(1, epochs+1):
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| /third_party/mindspore/mindspore/nn/probability/toolbox/ |
| D | uncertainty_evaluation.py | 85 def __init__(self, model, train_dataset, task_type, num_classes=None, epochs=1, argument
92 self.epochs = Validator.check_positive_int(epochs)
135 keep_checkpoint_max=self.epochs)
139 model.train(self.epochs, self.epi_train_dataset, dataset_sink_mode=False,
142 model.train(self.epochs, self.epi_train_dataset, dataset_sink_mode=False,
187 config_ck = CheckpointConfig(keep_checkpoint_max=self.epochs)
191 model.train(self.epochs, self.ale_train_dataset, dataset_sink_mode=False,
194 model.train(self.epochs, self.ale_train_dataset, dataset_sink_mode=False,
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| D | anomaly_detection.py | 47 def train(self, train_dataset, epochs=5): argument
62 self.vae = vi.run(train_dataset, epochs)
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| /third_party/mindspore/mindspore/lite/java/java/fl_client/src/main/java/com/mindspore/flclient/model/ |
| D | TrainModel.java | 80 public int trainModel(String modelPath, int epochs) { in trainModel() argument
85 if (epochs <= 0) { in trainModel()
94 status = trainLoop(epochs); in trainModel()
107 private int trainLoop(int epochs) { in trainLoop() argument
114 for (int i = 0; i < epochs; i++) { in trainLoop()
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| /third_party/mindspore/tests/st/model_zoo_tests/DeepFM/ |
| D | test_deepfm.py | 46 epochs=1,
64 epochs=1,
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| /third_party/mindspore/mindspore/lite/src/train/ |
| D | train_loop.cc | 38 int TrainLoop::Train(int epochs, Dataset *ds, std::vector<session::TrainLoopCallBack *> cbs, LoadDa… in Train() argument
40 MS_CHECK_GE(epochs, 0, RET_ERROR); in Train()
57 for (int i = 0; i < epochs; i++) { in Train()
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| D | train_loop.h | 57 int Train(int epochs, dataset::Dataset *dataset, std::vector<session::TrainLoopCallBack *> cbs,
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| /third_party/mindspore/mindspore/lite/src/cxx_api/train/ |
| D | model.cc | 30 Status Model::Train(int epochs, std::shared_ptr<dataset::Dataset> ds, std::vector<TrainCallBack *> … in Train() argument
61 auto ret = loop->Train(epochs, ds.get(), cbs); in Train()
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| /third_party/mindspore/mindspore/lite/java/java/fl_client/src/main/java/com/mindspore/flclient/ |
| D | FLLiteClient.java | 59 private int epochs = 1; field in FLLiteClient
86 epochs = flPlan.epochs(); in setGlobalParameters()
104 LOGGER.info(Common.addTag("[startFLJob] GlobalParameters <epochs> from server: " + epochs)); in setGlobalParameters()
313 int tag = alTrainBert.trainModel(flParameter.getTrainModelPath(), epochs); in localTrain()
322 int tag = trainLenet.trainModel(flParameter.getTrainModelPath(), epochs); in localTrain()
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| /third_party/mindspore/mindspore/lite/include/train/ |
| D | train_loop.h | 89 …virtual int Train(int epochs, mindspore::dataset::Dataset *dataset, std::vector<TrainLoopCallBack …
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| /third_party/mindspore/mindspore/lite/tools/benchmark_train/ |
| D | net_train.h | 133 …Network(const std::string &filename, const std::string &bb_filename, int train_session, int epochs,
142 int epochs);
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| D | net_train.cc | 337 … const TrainCfg &train_cfg, int epochs) { in CreateAndRunNetworkForTrain() argument
362 if (epochs > 0) { in CreateAndRunNetworkForTrain()
364 session->SetupVirtualBatch(epochs); in CreateAndRunNetworkForTrain()
404 int epochs, bool check_accuracy) { in CreateAndRunNetwork() argument
419 session = CreateAndRunNetworkForTrain(filename, bb_filename, context, train_cfg, epochs); in CreateAndRunNetwork()
453 if ((epochs > 0) && train_session) { in CreateAndRunNetwork()
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| /third_party/mindspore/mindspore/lite/examples/unified_api/src/ |
| D | net_runner.cc | 84 explicit Measurement(unsigned int epochs) in Measurement() argument
85 : epochs_(epochs), time_avg_(std::chrono::duration<double, std::milli>(0)) {} in Measurement()
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| /third_party/mindspore/mindspore/lite/examples/train_lenet/src/ |
| D | net_runner.cc | 82 explicit Measurement(unsigned int epochs) in Measurement() argument
83 : epochs_(epochs), time_avg_(std::chrono::duration<double, std::milli>(0)) {} in Measurement()
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| /third_party/mindspore/tests/st/gnn/gcn/ |
| D | test_gcn.py | 64 for epoch in range(config.epochs):
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| /third_party/mindspore/tests/st/probability/dpn/ |
| D | test_gpu_svi_vae.py | 107 vae = vi.run(train_dataset=ds_train, epochs=5)
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| D | test_gpu_svi_cvae.py | 118 cvae = vi.run(train_dataset=ds_train, epochs=5)
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| /third_party/mindspore/include/api/ |
| D | model.h | 178 Status Train(int epochs, std::shared_ptr<dataset::Dataset> ds, std::vector<TrainCallBack *> cbs);
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| /third_party/mindspore/mindspore/schema/ |
| D | fl_job.fbs | 75 epochs:int;
|