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'
