Python get_training_data Beispiele

Beispiel #1

Datei: model_1.0.1.39n.bu.py Projekt: saidbm24/Convnet-for-Mammogram-analysis

# ## Create Model

# config
# If number of epochs has been passed in use that, otherwise default to 50
parser = argparse.ArgumentParser()
parser.add_argument("-e", "--epochs", help="number of epochs to train", type=int)
args = parser.parse_args()

if args.epochs:
    epochs = args.epochs
else:
    epochs = 50

batch_size = 64

train_files, total_records = get_training_data(what=dataset)

## Hyperparameters
# Small epsilon value for the BN transform
epsilon = 1e-8

# learning rate
epochs_per_decay = 5
starting_rate = 0.001
decay_factor = 0.85
staircase = True

# learning rate decay variables
steps_per_epoch = int(total_records / batch_size)
print("Steps per epoch:", steps_per_epoch)

Beispiel #2

Datei: candidate_1.1.0.40.py Projekt: saidbm24/Convnet-for-Mammogram-analysis

# ## Create Model

# config
# If number of epochs has been passed in use that, otherwise default to 50
parser = argparse.ArgumentParser()
parser.add_argument("-e", "--epochs", help="number of epochs to train", type=int)
args = parser.parse_args()

if args.epochs:
    epochs = args.epochs
else:
    epochs = 50

batch_size = 64

train_files, total_records = get_training_data(type="new")

## Hyperparameters
# Small epsilon value for the BN transform
epsilon = 1e-8

# learning rate
epochs_per_decay = 5
starting_rate = 0.001
decay_factor = 0.85
staircase = True

# learning rate decay variables
steps_per_epoch = int(total_records / batch_size)
print("Steps per epoch:", steps_per_epoch)