def generate(model_options_file='model_options.pkl',
model_file='model_best_so_far.npz'):
from_dir = 'model_files/'
print 'preparing reload'
model_options = utils.load_pkl(from_dir+model_options_file)
print 'Loading data'
engine = data_engine.Movie2Caption('attention',
model_options['dataset'],
model_options['video_feature'],
model_options['batch_size'],
model_options['valid_batch_size'],
model_options['maxlen'],
model_options['n_words'],
model_options['K'],
model_options['OutOf'])
feat = numpy.load('datas/vid1715.npy')
ctx = engine.get_sub_frames(feat)
ctx_mask = engine.get_ctx_mask(ctx)
print 'init params'
t0 = time.time()
model = Model()
params = model.init_params(model_options)
model_saved = from_dir + model_file
assert os.path.isfile(model_saved)
print "Reloading model params..."
params = utils.load_params(model_saved, params)
tparams = utils.init_tparams(params)
print tparams.keys
print 'buliding sampler'
use_noise = theano.shared(numpy.float32(0.))
use_noise.set_value(0.)
trng = RandomStreams(1234)
f_init, f_next = model.build_sampler(tparams, model_options, use_noise, trng)
print 'start generate...'
g_t0 = time.time()
sample, sample_score, _, _ = model.gen_sample(None, f_init, f_next, ctx, ctx_mask, model_options,
None, 5, maxlen=model_options['maxlen'])
print sample
# best_one = numpy.argmin(sample_score)
# sample = sample[best_one]
for s in sample:
for kk, ss in enumerate([s]):
for vv in ss:
if vv == 0:
break
if vv in engine.word_idict:
print engine.word_idict[vv],
else:
print 'UNK',
print
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