def prepare_data(args):
batch_size = args.config.getint('train', 'batch_size')
num_hidden = args.config.getint('arch', 'num_hidden')
num_lstm_layer = args.config.getint('arch', 'num_lstm_layer')
init_c = [('l%d_init_c' % l, (batch_size, num_hidden))
for l in range(num_lstm_layer)]
init_h = [('l%d_init_h' % l, (batch_size, num_hidden))
for l in range(num_lstm_layer)]
init_states = init_c + init_h
file_test = args.config.get('data', 'train')
file_format = args.config.get('data', 'format')
feat_dim = args.config.getint('data', 'xdim')
test_data_args = {
"gpu_chunk": 32768,
"lst_file": file_test,
"file_format": file_format,
"separate_lines": True,
"has_labels": True
}
test_sets = DataReadStream(test_data_args, feat_dim)
return (init_states, test_sets)
def prepare_data(args):
batch_size = args.config.getint('train', 'batch_size')
num_hidden = args.config.getint('arch', 'num_hidden')
num_hidden_proj = args.config.getint('arch', 'num_hidden_proj')
num_lstm_layer = args.config.getint('arch', 'num_lstm_layer')
init_c = [('l%d_init_c' % l, (batch_size, num_hidden))
for l in range(num_lstm_layer)]
if num_hidden_proj > 0:
init_h = [('l%d_init_h' % l, (batch_size, num_hidden_proj))
for l in range(num_lstm_layer)]
else:
init_h = [('l%d_init_h' % l, (batch_size, num_hidden))
for l in range(num_lstm_layer)]
init_states = init_c + init_h
file_train = args.config.get('data', 'train')
file_dev = args.config.get('data', 'dev')
file_format = args.config.get('data', 'format')
feat_dim = args.config.getint('data', 'xdim')
train_data_args = {
"gpu_chunk": 32768,
"lst_file": file_train,
"file_format": file_format,
"separate_lines": True
}
dev_data_args = {
"gpu_chunk": 32768,
"lst_file": file_dev,
"file_format": file_format,
"separate_lines": True
}
train_sets = DataReadStream(train_data_args, feat_dim)
dev_sets = DataReadStream(dev_data_args, feat_dim)
return (init_states, train_sets, dev_sets)