(model)
This adds a few bookkeeping operators that we can inspect later.
    
    These operators do not affect the training procedure: they only collect
    statistics and prints them to file or to logs.
This adds a few bookkeeping operators that we can inspect later.
    
    These operators do not affect the training procedure: they only collect
    statistics and prints them to file or to logs.
This adds a few bookkeeping operators that we can inspect later . These operators do not affect the training procedure : they only collect statistics and prints them to file or to logs .
def AddBookkeepingOperators(model):
    """This adds a few bookkeeping operators that we can inspect later.
    
    These operators do not affect the training procedure: they only collect
    statistics and prints them to file or to logs.
    """    
    # Print basically prints out the content of the blob. to_file=1 routes the
    # printed output to a file. The file is going to be stored under
    #     root_folder/[blob name]
    model.Print('accuracy', [], to_file=1)
    model.Print('loss', [], to_file=1)
    # Summarizes the parameters. Different from Print, Summarize gives some
    # statistics of the parameter, such as mean, std, min and max.
    for param in model.params:
        model.Summarize(param, [], to_file=1)
        model.Summarize(model.param_to_grad[param], [], to_file=1)
def AddBookkeepingOperators ( model ) : # Print basically prints out the content of the blob. to_file=1 routes the # printed output to a file. The file is going to be stored under #     root_folder/[blob name] model . Print ( 'accuracy' , [ ] , to_file = 1 ) model . Print ( 'loss' , [ ] , to_file = 1 ) # Summarizes the parameters. Different from Print, Summarize gives some # statistics of the parameter, such as mean, std, min and max. for param in model . params : model . Summarize ( param , [ ] , to_file = 1 ) model . Summarize ( model . param_to_grad [ param ] , [ ] , to_file = 1 )