omniglot_database = OmniglotDatabase(random_seed=47,
num_train_classes=1200,
num_val_classes=100)
maml_umtra = MAMLUMTRA(database=omniglot_database,
network_cls=SimpleModel,
n=5,
k=1,
k_val_ml=5,
k_val_val=15,
k_val_test=15,
k_test=5,
meta_batch_size=4,
num_steps_ml=5,
lr_inner_ml=0.4,
num_steps_validation=5,
save_after_iterations=1000,
meta_learning_rate=0.001,
report_validation_frequency=200,
log_train_images_after_iteration=200,
number_of_tasks_val=100,
number_of_tasks_test=1000,
clip_gradients=False,
experiment_name='omniglot',
val_seed=42,
val_test_batch_norm_momentum=0.0)
shape = (28, 28, 1)
maml_umtra.visualize_umtra_task(shape, num_tasks_to_visualize=2)
maml_umtra.train(iterations=5000)
# import tensorflow as tf
# tf.config.experimental_run_functions_eagerly(True)
fungi_database = FungiDatabase()
maml_umtra = MAMLUMTRA(database=fungi_database,
network_cls=MiniImagenetModel,
n=5,
k_ml=1,
k_val_ml=1,
k_val=1,
k_val_val=15,
k_test=5,
k_val_test=15,
meta_batch_size=4,
num_steps_ml=5,
lr_inner_ml=0.05,
num_steps_validation=5,
save_after_iterations=15000,
meta_learning_rate=0.001,
report_validation_frequency=250,
log_train_images_after_iteration=1000,
num_tasks_val=100,
clip_gradients=True,
experiment_name='fungi',
val_seed=42,
val_test_batch_norm_momentum=0.0)
shape = (84, 84, 3)
# maml_umtra.visualize_umtra_task(shape, num_tasks_to_visualize=2)
maml_umtra.train(iterations=60000)