def train(input_dir, batch_size, max_steps, output_dir, checkpoint):
    """Train model locally."""
    from google.datalab.utils import LambdaJob

    if checkpoint is None:
      checkpoint = _util._DEFAULT_CHECKPOINT_GSURL

    labels = _util.get_labels(input_dir)
    model = _model.Model(labels, 0.5, checkpoint)
    task_data = {'type': 'master', 'index': 0}
    task = type('TaskSpec', (object,), task_data)
    job = LambdaJob(lambda: _trainer.Trainer(input_dir, batch_size, max_steps, output_dir,
                                             model, None, task).run_training(), 'training')
    return job
def train ( input_dir , batch_size , max_steps , output_dir , checkpoint ) : from google . datalab . utils import LambdaJob if checkpoint is None : checkpoint = _util . _DEFAULT_CHECKPOINT_GSURL labels = _util . get_labels ( input_dir ) model = _model . Model ( labels , 0.5 , checkpoint ) task_data = { 'type' : 'master' , 'index' : 0 } task = type ( 'TaskSpec' , ( object , ) , task_data ) job = LambdaJob ( lambda : _trainer . Trainer ( input_dir , batch_size , max_steps , output_dir , model , None , task ) . run_training ( ) , 'training' ) return job
Train model locally.