def __init__(self, algorithm, data_stream, model=None, log=None, log_backend=None, extensions=None): if log is None: if log_backend is None: log_backend = config.log_backend log = BACKENDS[log_backend]() if extensions is None: extensions = [] self.data_stream = data_stream self.epoch_iterator = None self.algorithm = algorithm self.log = log self.extensions = extensions self.profile = Profile() self._model = model self.status['training_started'] = False self.status['epoch_started'] = False self.status['epoch_interrupt_received'] = False self.status['batch_interrupt_received'] = False
def __init__(self, models, algorithm, data_stream, num_encs=1, num_decs=1, log=None, extensions=None): """ models : dict, mapping cg_name to blocks.model algorithm : SGDMultiCG data_stream : data stream, either MultiSourceStream or MultiEncStream num_encs : int, number of encoders num_decs : int, number of decoders log : blocks.log, the logger object extensions : blocks.extensions, the main loop extensions """ self.models = models self.num_encs = num_encs self.num_decs = num_decs self.num_cgs = len(models) if log is None: log = TrainingLog() if extensions is None: extensions = [] self.data_stream = data_stream self.algorithm = algorithm self.log = log self.extensions = extensions self.profile = Profile() self.status['training_started'] = False self.status['epoch_started'] = False self.status['epoch_interrupt_received'] = False self.status['batch_interrupt_received'] = False
def __init__(self, algorithm, data_stream, model=None, log=None, extensions=None): if log is None: log = TrainingLog() if extensions is None: extensions = [] self.data_stream = data_stream self.algorithm = algorithm self.log = log self.extensions = extensions self.profile = Profile() self._model = model self.status['training_started'] = False self.status['epoch_started'] = False self.status['epoch_interrupt_received'] = False self.status['batch_interrupt_received'] = False