args.num_bits_per_vector + 1))
eval_outputs = tf.placeholder(tf.float32,
shape=(args.batch_size, None,
args.num_bits_per_vector))
eval_model = BuildEvalModel(eval_max_seq_len, eval_inputs, eval_outputs)
# training
convergence_on_target_task = None
convergence_on_multi_task = None
performance_on_target_task = None
performance_on_multi_task = None
generalization_from_target_task = None
generalization_from_multi_task = None
if args.task == 'copy':
data_generator = CopyTaskData()
target_point = args.max_seq_len
curriculum_point = 1 if args.curriculum not in ('prediction_gain',
'none') else target_point
progress_error = 1.0
convergence_error = 0.1
if args.curriculum == 'prediction_gain':
exp3s = Exp3S(args.max_seq_len, 0.001, 0, 0.05)
elif args.task == 'associative_recall':
data_generator = AssociativeRecallData()
target_point = args.max_seq_len
curriculum_point = 2 if args.curriculum not in ('prediction_gain',
'none') else target_point
progress_error = 1.0
convergence_error = 0.1
print "# parameters", np.sum([
np.product([xi.value for xi in x.get_shape()])
for x in tf.all_variables()
])
# training
convergence_on_target_task = None
convergence_on_multi_task = None
performance_on_target_task = None
performance_on_multi_task = None
generalization_from_target_task = None
generalization_from_multi_task = None
if args.task == 'copy':
data_generator = CopyTaskData()
target_point = args.max_seq_len
curriculum_point = 1 if args.curriculum not in ('prediction_gain_bandit',
'prediction_gain_teacher',
'none') else target_point
progress_error = 2.0
convergence_error = 0.4
if args.curriculum == 'prediction_gain_bandit':
exp3s = Exp3S(args.max_seq_len, 0.001, 0, 0.05)
if args.curriculum == 'prediction_gain_teacher':
teacher = Teacher([i + 1 for i in range(args.max_seq_len)], 1, 2, 10)
elif args.task == 'repeat_copy':
data_generator = RepeatCopyTaskData(args.max_seq_len, args.max_repeats)
target_point = (args.max_seq_len, args.max_repeats)
curriculum_point = (1, 1) if args.curriculum not in (
performance_on_target_task = None
performance_on_multi_task = None
generalization_from_target_task = None
generalization_from_multi_task = None
multi_task_error = None
target_task_error = None
progress_error = None
convergence_error = None
target_point = None
exp3s = None
data_generator = None
curriculum_point = None
task = None
if args.task == CopyTask.name:
data_generator = CopyTaskData()
target_point = args.max_seq_len
curriculum_point = 1 if args.curriculum not in (
'prediction_gain', 'none') else target_point
progress_error = 1.0
convergence_error = 0.1
if args.curriculum == 'prediction_gain':
exp3s = Exp3S(args.max_seq_len, 0.001, 0, 0.05)
elif args.task == AssociativeRecallTask.name:
data_generator = AssociativeRecallData()
target_point = args.max_seq_len
curriculum_point = 2 if args.curriculum not in (
'prediction_gain', 'none') else target_point
progress_error = 1.0
convergence_error = 0.1