Python TrainStepWrap Beispiele

Beispiel #1

Datei: train_and_test_multinpu_ci.py Projekt: gerayking/mindsporeAno

def get_WideDeep_net(config):
    WideDeep_net = WideDeepModel(config)
    loss_net = NetWithLossClass(WideDeep_net, config)
    loss_net = VirtualDatasetCellTriple(loss_net)
    train_net = TrainStepWrap(loss_net)
    eval_net = PredictWithSigmoid(WideDeep_net)
    eval_net = VirtualDatasetCellTriple(eval_net)
    return train_net, eval_net

Beispiel #2

Datei: eval.py Projekt: xyg320/mindspore

def get_WideDeep_net(config):
    WideDeep_net = WideDeepModel(config)

    loss_net = NetWithLossClass(WideDeep_net, config)
    train_net = TrainStepWrap(loss_net)
    eval_net = PredictWithSigmoid(WideDeep_net)

    return train_net, eval_net

Beispiel #3

Datei: train_and_eval_distribute.py Projekt: stjordanis/mindspore

def get_WideDeep_net(config):
    """
    Get network of wide&deep model.
    """
    WideDeep_net = WideDeepModel(config)
    loss_net = NetWithLossClass(WideDeep_net, config)
    train_net = TrainStepWrap(loss_net, sparse=config.sparse)
    eval_net = PredictWithSigmoid(WideDeep_net)
    return train_net, eval_net

Beispiel #4

Datei: train_and_eval_parameter_server.py Projekt: zuoshou030/mindspore

def get_WideDeep_net(config):
    """
    Get network of wide&deep model.
    """
    WideDeep_net = WideDeepModel(config)
    loss_net = NetWithLossClass(WideDeep_net, config)
    train_net = TrainStepWrap(loss_net, parameter_server=bool(config.parameter_server))
    eval_net = PredictWithSigmoid(WideDeep_net)
    return train_net, eval_net

Beispiel #5

Datei: train_and_eval_parameter_server_standalone.py Projekt: peng-zhihui/mindspore

def get_wide_deep_net(config):
    """
    Get network of wide&deep model.
    """
    wide_deep_net = WideDeepModel(config)
    loss_net = NetWithLossClass(wide_deep_net, config)
    train_net = TrainStepWrap(loss_net, parameter_server=bool(config.parameter_server),
                              cache_enable=(config.vocab_cache_size > 0))
    eval_net = PredictWithSigmoid(wide_deep_net)
    return train_net, eval_net

Beispiel #6

Datei: train_and_eval_auto_parallel.py Projekt: tristonerRL/mindspore

def get_WideDeep_net(config):
    """
    Get network of wide&deep model.
    """
    WideDeep_net = WideDeepModel(config)
    loss_net = NetWithLossClass(WideDeep_net, config)
    loss_net = VirtualDatasetCellTriple(loss_net)
    train_net = TrainStepWrap(loss_net, host_device_mix=bool(config.host_device_mix))
    eval_net = PredictWithSigmoid(WideDeep_net)
    eval_net = VirtualDatasetCellTriple(eval_net)
    return train_net, eval_net

Beispiel #7

def get_wide_deep_net(config):
    """
    Get network of wide&deep model.
    """
    wide_deep_net = WideDeepModel(config)
    loss_net = NetWithLossClass(wide_deep_net, config)
    if cache_enable:
        loss_net = VirtualDatasetCellTriple(loss_net)
    train_net = TrainStepWrap(loss_net,
                              parameter_server=bool(config.parameter_server),
                              sparse=config.sparse,
                              cache_enable=(config.vocab_cache_size > 0))
    eval_net = PredictWithSigmoid(wide_deep_net)
    if cache_enable:
        eval_net = VirtualDatasetCellTriple(eval_net)
    return train_net, eval_net