def __init__(self): self.logger = utils.get_logger('Learner') self._embedding_layer_name = 'embedding' self.__monitor = 'val_acc' self.__weights_name = 'weights.h5' self.__architecture_name = 'architecture.json' self.__model_graph_name = 'structure.png' self.model = self.setup()
def __init__(self, name, special_instances=(), keep_growing=True): self.__name = name self.__instance2index = {} self.__instances = [] self.__keep_growing = keep_growing # Index 0 is occupied by default, all else following. self.__next_index = 1 for instance in special_instances: self.add(instance) self.logger = utils.get_logger('Alphabet')
def __init__(self, graph_mode=True): self.logger = utils.get_logger('Learner') self._embedding_layer_name = 'embedding' self._main_input_layer_name = 'input' self._main_output_layer_name = "prediction_output" self._graph_mode = graph_mode self.model = self._get_model() self.__monitor = 'val_acc' self.__weights_name = 'weights.h5' self.__architecture_name = 'architecture.json' self.__model_graph_name = 'structure.png' self.setup()
def __init__(self, name, special_instances=(), keep_growing=True): self.__name = name self.__instance2index = {} self.__instances = [] self.__keep_growing = keep_growing # Index 0 is occupied by default, all else following. self.default_index = 0 self.__next_index = 1 for instance in special_instances: self.add(instance) self.logger = utils.get_logger('Alphabet')
""" A base learner that does not have any architecture. Implementations need to fill that part in. """ import numpy as np from keras.callbacks import EarlyStopping from keras.models import model_from_json import os from finest.utils.callbacks import MonitorLoss import finest.utils.utils as utils from keras.utils.visualize_util import plot from finest.utils.configs import ExperimentConfig logger = utils.get_logger(__name__) class BaseLearner(object): def __init__(self): self.logger = utils.get_logger('Learner') self._embedding_layer_name = 'embedding' self.__monitor = 'val_acc' self.__weights_name = 'weights.h5' self.__architecture_name = 'architecture.json' self.__model_graph_name = 'structure.png' self.model = self.setup() def setup(self): pass
""" A base learner that does not have any architecture. Implementations need to fill that part in. """ import numpy as np from keras.callbacks import EarlyStopping from keras.models import model_from_json from keras.models import Sequential, Graph import os from finest.utils.callbacks import MonitorLoss import finest.utils.utils as utils from keras.utils.visualize_util import plot import json logger = utils.get_logger(__name__) class BaseLearner(object): def __init__(self, graph_mode=True): self.logger = utils.get_logger('Learner') self._embedding_layer_name = 'embedding' self._main_input_layer_name = 'input' self._main_output_layer_name = "prediction_output" self._graph_mode = graph_mode self.model = self._get_model() self.__monitor = 'val_acc' self.__weights_name = 'weights.h5' self.__architecture_name = 'architecture.json' self.__model_graph_name = 'structure.png'