def load_trainer(self, model):
""" Load the trainer requested for training """
logger.debug("Loading Trainer")
trainer = PluginLoader.get_trainer(model.trainer)
trainer = trainer(model, self.images, self.args.batch_size)
logger.debug("Loaded Trainer")
return trainer
def load_trainer(self, model):
""" Load the trainer requested for training """
images_a, images_b = self.images
trainer = PluginLoader.get_trainer(self.trainer_name)
trainer = trainer(model, images_a, images_b, self.args.batch_size,
self.args.perceptual_loss)
return trainer
def load_trainer(self, model):
""" Load the trainer requested for training """
logger.debug("Loading Trainer")
trainer = PluginLoader.get_trainer(model.trainer)
trainer = trainer(model,
self.images,
self.args.batch_size)
logger.debug("Loaded Trainer")
return trainer
def _load_trainer(self, model):
trainer = PluginLoader.get_trainer(model.trainer)
if self._model_name == "NN":
use_pipeline = False
else:
use_pipeline = True
if self._feature_name == "date":
feature_index = 0
elif self._feature_name == "time":
feature_index = 1
else:
feature_dict = self._load_feature_name()
feature_index = feature_dict[self._feature_name] + 2
trainer = trainer(model, self._data_dir, self._args.batch_size, use_pipeline, feature_index)
return trainer
def _load_trainer(self, model):
""" Load the trainer requested for training.
Parameters
----------
model: :file:`plugins.train.model` plugin
The requested model plugin
Returns
-------
:file:`plugins.train.trainer` plugin
The requested model trainer plugin
"""
logger.debug("Loading Trainer")
trainer = PluginLoader.get_trainer(model.trainer)
trainer = trainer(model, self._images, self._args.batch_size,
self._args.configfile)
logger.debug("Loaded Trainer")
return trainer
def _load_trainer(self, model):
trainer = PluginLoader.get_trainer(model.trainer)
trainer = trainer(model, self._data_dir, self._args.batch_size)
return trainer