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
