Variables
	stream

	stdout

	level

	config = configparser.ConfigParser()

	SHUFFLE = ast.literal_eval(config['random']['shuffle'])

	IMAGES_PATH = config['images']['path']

	VIEWS = int(config['images']['views'])

	PLANES = int(config['images']['planes'])

	CELLS = int(config['images']['cells'])

	STANDARDIZE = ast.literal_eval(config['images']['standardize'])

	INTERACTION_LABELS = ast.literal_eval(config['images']['interaction_labels'])

	FILTERED = ast.literal_eval(config['images']['filtered'])

	INTERACTION_TYPES = ast.literal_eval(config['dataset']['interaction_types'])

list	NEUTRINO_LABELS = []

	N_LABELS = len(Counter(INTERACTION_LABELS.values()))

	DATASET_PATH = config['dataset']['path']

	PARTITION_PREFIX = config['dataset']['partition_prefix']

	LABELS_PREFIX = config['dataset']['labels_prefix']

	LOG_PATH = config['log']['path']

	LOG_PREFIX = config['log']['prefix']

	CHECKPOINT_PATH = config['model']['checkpoint_path']

	CHECKPOINT_PREFIX = config['model']['checkpoint_prefix']

	CHECKPOINT_SAVE_MANY = ast.literal_eval(config['model']['checkpoint_save_many'])

	CHECKPOINT_SAVE_BEST_ONLY = ast.literal_eval(config['model']['checkpoint_save_best_only'])

	CHECKPOINT_PERIOD = int(config['model']['checkpoint_period'])

	PRINT_SUMMARY = ast.literal_eval(config['model']['print_summary'])

	RESUME = ast.literal_eval(config['train']['resume'])

	LEARNING_RATE = float(config['train']['lr'])

	MOMENTUM = float(config['train']['momentum'])

	DECAY = float(config['train']['decay'])

	TRAIN_BATCH_SIZE = int(config['train']['batch_size'])

	EPOCHS = int(config['train']['epochs'])

	EARLY_STOPPING_PATIENCE = int(config['train']['early_stopping_patience'])

	WEIGHTED_LOSS_FUNCTION = ast.literal_eval(config['train']['weighted_loss_function'])

	CLASS_WEIGHTS_PREFIX = config['train']['class_weights_prefix']

	VALIDATION_FRACTION = float(config['validation']['fraction'])

	VALIDATION_BATCH_SIZE = int(config['validation']['batch_size'])

dictionary	TRAIN_PARAMS

dictionary	VALIDATION_PARAMS

dictionary	partition = {'train' : [], 'validation' : [], 'test' : []}

dictionary	labels = {}

	partition_file = open(DATASET_PATH + PARTITION_PREFIX + '.p', 'r')

	labels_file = open(DATASET_PATH + LABELS_PREFIX + '.p', 'r')

	class_weights_file = open(DATASET_PATH + CLASS_WEIGHTS_PREFIX + '.p', 'r')

	class_weights = pickle.load(class_weights_file)

	training_generator = DataGenerator(**TRAIN_PARAMS).generate(labels, partition['train'], True)

	validation_generator = DataGenerator(**VALIDATION_PARAMS).generate(labels, partition['validation'], True)

list	files = [f for f in os.listdir(CHECKPOINT_PATH) if os.path.isfile(os.path.join(CHECKPOINT_PATH, f))]

	reverse

	r = re.compile(CHECKPOINT_PREFIX[1:] + '-.-..h5')

	model = load_model(CHECKPOINT_PATH + '/' + fil)

list	input_shape = [PLANES, CELLS, VIEWS]

	opt = optimizers.SGD(lr=LEARNING_RATE, momentum=MOMENTUM, decay=DECAY, nesterov=True)

	loss

	optimizer

	metrics

string	filepath = CHECKPOINT_PATH+CHECKPOINT_PREFIX+'.h5'

string	monitor_acc = 'val_acc'

string	monitor_loss = 'val_loss'

	checkpoint = ModelCheckpoint(filepath, monitor=monitor_acc, verbose=1, save_best_only=CHECKPOINT_SAVE_BEST_ONLY, mode='max', period=CHECKPOINT_PERIOD)

	lr_reducer = ReduceLROnPlateau(monitor=monitor_loss, factor=0.1, cooldown=0, patience=3, min_lr=0.5e-6, verbose=1)

	early_stopping = EarlyStopping(monitor=monitor_acc, patience=EARLY_STOPPING_PATIENCE, mode='auto')

	csv_logger = CSVLogger(LOG_PATH + LOG_PREFIX + '.log', append=RESUME)

	my_callback = my_callbacks.MyCallback()

list	callbacks_list = [lr_reducer, checkpoint, early_stopping, csv_logger]

int	initial_epoch = int(re.search(r'\d+', logfile.read().split('\n')[-2]).group())+1

	generator

	steps_per_epoch

	validation_data

	validation_steps

	epochs

	class_weight

	callbacks

	verbose

Variable Documentation

training.callbacks

Definition at line 378 of file training.py.

list training.callbacks_list = [lr_reducer, checkpoint, early_stopping, csv_logger]

Definition at line 327 of file training.py.

training.CELLS = int(config['images']['cells'])

Definition at line 48 of file training.py.

training.checkpoint = ModelCheckpoint(filepath, monitor=monitor_acc, verbose=1, save_best_only=CHECKPOINT_SAVE_BEST_ONLY, mode='max', period=CHECKPOINT_PERIOD)

Definition at line 300 of file training.py.

training.CHECKPOINT_PATH = config['model']['checkpoint_path']

Definition at line 82 of file training.py.

training.CHECKPOINT_PERIOD = int(config['model']['checkpoint_period'])

Definition at line 86 of file training.py.

training.CHECKPOINT_PREFIX = config['model']['checkpoint_prefix']

Definition at line 83 of file training.py.

training.CHECKPOINT_SAVE_BEST_ONLY = ast.literal_eval(config['model']['checkpoint_save_best_only'])

Definition at line 85 of file training.py.

training.CHECKPOINT_SAVE_MANY = ast.literal_eval(config['model']['checkpoint_save_many'])

Definition at line 84 of file training.py.

training.class_weight

Definition at line 377 of file training.py.

training.class_weights = pickle.load(class_weights_file)

Definition at line 161 of file training.py.

training.class_weights_file = open(DATASET_PATH + CLASS_WEIGHTS_PREFIX + '.p', 'r')

Definition at line 160 of file training.py.

training.CLASS_WEIGHTS_PREFIX = config['train']['class_weights_prefix']

Definition at line 99 of file training.py.

training.config = configparser.ConfigParser()

Definition at line 35 of file training.py.

training.csv_logger = CSVLogger(LOG_PATH + LOG_PREFIX + '.log', append=RESUME)

Definition at line 317 of file training.py.

training.DATASET_PATH = config['dataset']['path']

Definition at line 71 of file training.py.

training.DECAY = float(config['train']['decay'])

Definition at line 94 of file training.py.

training.early_stopping = EarlyStopping(monitor=monitor_acc, patience=EARLY_STOPPING_PATIENCE, mode='auto')

Definition at line 313 of file training.py.

training.EARLY_STOPPING_PATIENCE = int(config['train']['early_stopping_patience'])

Definition at line 97 of file training.py.

training.EPOCHS = int(config['train']['epochs'])

Definition at line 96 of file training.py.

training.epochs

Definition at line 376 of file training.py.

string training.filepath = CHECKPOINT_PATH+CHECKPOINT_PREFIX+'.h5'

Definition at line 278 of file training.py.

list training.files = [f for f in os.listdir(CHECKPOINT_PATH) if os.path.isfile(os.path.join(CHECKPOINT_PATH, f))]

Definition at line 201 of file training.py.

training.FILTERED = ast.literal_eval(config['images']['filtered'])

Definition at line 51 of file training.py.

training.generator

Definition at line 372 of file training.py.

training.IMAGES_PATH = config['images']['path']

Definition at line 45 of file training.py.

int training.initial_epoch = int(re.search(r'\d+', logfile.read().split('\n')[-2]).group())+1

Definition at line 349 of file training.py.

list training.input_shape = [PLANES, CELLS, VIEWS]

Definition at line 230 of file training.py.

training.INTERACTION_LABELS = ast.literal_eval(config['images']['interaction_labels'])

Definition at line 50 of file training.py.

training.INTERACTION_TYPES = ast.literal_eval(config['dataset']['interaction_types'])

Definition at line 53 of file training.py.

training.labels = {}

Definition at line 144 of file training.py.

training.labels_file = open(DATASET_PATH + LABELS_PREFIX + '.p', 'r')

Definition at line 154 of file training.py.

training.LABELS_PREFIX = config['dataset']['labels_prefix']

Definition at line 73 of file training.py.

training.LEARNING_RATE = float(config['train']['lr'])

Definition at line 92 of file training.py.

training.level

Definition at line 33 of file training.py.

training.LOG_PATH = config['log']['path']

Definition at line 77 of file training.py.

training.LOG_PREFIX = config['log']['prefix']

Definition at line 78 of file training.py.

training.loss

Definition at line 252 of file training.py.

training.lr_reducer = ReduceLROnPlateau(monitor=monitor_loss, factor=0.1, cooldown=0, patience=3, min_lr=0.5e-6, verbose=1)

Definition at line 307 of file training.py.

training.metrics

Definition at line 252 of file training.py.

training.model = load_model(CHECKPOINT_PATH + '/' + fil)

Definition at line 208 of file training.py.

training.MOMENTUM = float(config['train']['momentum'])

Definition at line 93 of file training.py.

string training.monitor_acc = 'val_acc'

Definition at line 287 of file training.py.

string training.monitor_loss = 'val_loss'

Definition at line 288 of file training.py.

training.my_callback = my_callbacks.MyCallback()

Definition at line 321 of file training.py.

training.N_LABELS = len(Counter(INTERACTION_LABELS.values()))

Definition at line 60 of file training.py.

training.NEUTRINO_LABELS = []

Definition at line 59 of file training.py.

training.opt = optimizers.SGD(lr=LEARNING_RATE, momentum=MOMENTUM, decay=DECAY, nesterov=True)

Definition at line 246 of file training.py.

training.optimizer

Definition at line 252 of file training.py.

training.partition = {'train' : [], 'validation' : [], 'test' : []}

Definition at line 143 of file training.py.

training.partition_file = open(DATASET_PATH + PARTITION_PREFIX + '.p', 'r')

Definition at line 150 of file training.py.

training.PARTITION_PREFIX = config['dataset']['partition_prefix']

Definition at line 72 of file training.py.

training.PLANES = int(config['images']['planes'])

Definition at line 47 of file training.py.

training.PRINT_SUMMARY = ast.literal_eval(config['model']['print_summary'])

Definition at line 87 of file training.py.

training.r = re.compile(CHECKPOINT_PREFIX[1:] + '-.*-.*.h5')

Definition at line 204 of file training.py.

training.RESUME = ast.literal_eval(config['train']['resume'])

Definition at line 91 of file training.py.

training.reverse

Definition at line 202 of file training.py.

training.SHUFFLE = ast.literal_eval(config['random']['shuffle'])

Definition at line 41 of file training.py.

training.STANDARDIZE = ast.literal_eval(config['images']['standardize'])

Definition at line 49 of file training.py.

training.stdout

Definition at line 33 of file training.py.

training.steps_per_epoch

Definition at line 373 of file training.py.

training.stream

Definition at line 33 of file training.py.

training.TRAIN_BATCH_SIZE = int(config['train']['batch_size'])

Definition at line 95 of file training.py.

dictionary training.TRAIN_PARAMS

Initial value:

 = {'planes': PLANES,
                      'cells': CELLS,
                      'views': VIEWS,
                      'batch_size': TRAIN_BATCH_SIZE,
                      'n_labels': N_LABELS,
                      'interaction_labels': INTERACTION_LABELS,
                      'interaction_types': INTERACTION_TYPES,
                      'filtered': FILTERED,
                      'neutrino_labels': NEUTRINO_LABELS,
                      'images_path': IMAGES_PATH,
                      'standardize': STANDARDIZE,
                      'shuffle': SHUFFLE}

Definition at line 108 of file training.py.

training.training_generator = DataGenerator(**TRAIN_PARAMS).generate(labels, partition['train'], True)

Definition at line 181 of file training.py.

training.VALIDATION_BATCH_SIZE = int(config['validation']['batch_size'])

Definition at line 104 of file training.py.

training.validation_data

Definition at line 374 of file training.py.

training.VALIDATION_FRACTION = float(config['validation']['fraction'])

Definition at line 103 of file training.py.

training.validation_generator = DataGenerator(**VALIDATION_PARAMS).generate(labels, partition['validation'], True)

Definition at line 182 of file training.py.

dictionary training.VALIDATION_PARAMS

Initial value:

 = {'planes': PLANES,
                      'cells': CELLS,
                      'views': VIEWS,
                      'batch_size': VALIDATION_BATCH_SIZE,
                      'n_labels': N_LABELS,
                      'interaction_labels': INTERACTION_LABELS,
                      'interaction_types': INTERACTION_TYPES,
                      'filtered': FILTERED,
                      'neutrino_labels': NEUTRINO_LABELS,
                      'images_path': IMAGES_PATH,
                      'standardize': STANDARDIZE,
                      'shuffle': SHUFFLE}

Definition at line 123 of file training.py.

training.validation_steps

Definition at line 375 of file training.py.

training.verbose

Definition at line 380 of file training.py.

training.VIEWS = int(config['images']['views'])

Definition at line 46 of file training.py.

training.WEIGHTED_LOSS_FUNCTION = ast.literal_eval(config['train']['weighted_loss_function'])

Definition at line 98 of file training.py.

Variables

Variable Documentation