cell_size=args.mem_size,
sparse_reads=args.sparse_reads,
temporal_reads=args.temporal_reads,
read_heads=args.read_heads,
gpu_id=args.cuda,
debug=args.visdom,
batch_first=True,
independent_linears=False)
elif args.memory_type == 'sam':
rnn = SAM(input_size=args.input_size,
hidden_size=args.nhid,
rnn_type=args.rnn_type,
num_layers=args.nlayer,
num_hidden_layers=args.nhlayer,
dropout=args.dropout,
nr_cells=args.mem_slot,
cell_size=args.mem_size,
sparse_reads=args.sparse_reads,
read_heads=args.read_heads,
gpu_id=args.cuda,
debug=args.visdom,
batch_first=True,
independent_linears=False)
else:
raise Exception('Not recognized type of memory')
if args.cuda != -1:
rnn = rnn.cuda(args.cuda)
print(rnn)
last_save_losses = []
controller_size=args.lstm_size,
memory_units=128,
memory_unit_size=20,
num_heads=1)#task_params['num_heads'])
elif args.model=='dnc':
model = DNC(input_size= input_size,
output_size=output_size,
hidden_size=args.lstm_size,
nr_cells=128,
cell_size=20,
read_heads=1)#task_params['num_heads'])
model.init_param()
elif args.model=='sam':
model = SAM(input_size= input_size,
output_size=output_size,
hidden_size=args.lstm_size,
nr_cells=128,
cell_size=20,
read_heads=1)#read_heads=4???#task_params['num_heads'])
model.init_param()
elif args.model=='lstm':
marnn_config=args
print('marnn_config:\n',marnn_config)
model = MARNN(marnn_config,input_size=input_size,
num_units=marnn_config.lstm_size,
output_size=output_size,
use_zoneout=False,
use_ln=False)
else:
has_tau=1
marnn_config=args
print('marnn_config:\n',marnn_config)
