callbacks = Callbacks(model, eval_set=valid_set, **args.callback_args)
# train model
model.fit(train_set,
optimizer=optimizer,
num_epochs=args.epochs,
cost=cost, callbacks=callbacks)
# obtain predictions
shape = (valid_set.nbatches, args.batch_size, time_steps)
if num_beams == 0:
ypred = model.get_outputs(valid_set)
# flip the reversed predictions back to normal sentence order
prediction = ypred.argmax(2).reshape(shape).transpose(1, 0, 2)[:, :, ::-1]
else:
ypred = model.get_outputs_beam(valid_set, num_beams=num_beams)
prediction = ypred.reshape(shape).transpose(1, 0, 2)[:, :, ::-1]
# print some examples
src_dict, tgt_dict = valid_set.s_index_to_token, valid_set.t_index_to_token
for i in range(3):
print_sample(ex_source=valid_set.X[i, 0, :],
ex_reference=valid_set.y[i, 0, :],
ex_prediction=prediction[i, 0, :],
src_dict=src_dict, tgt_dict=tgt_dict)
# compute BLEU scores
inputs = valid_set.X[:, :valid_set.nbatches, :]
source_sentences = bleu_format(inputs, tgt_dict, valid_set.nbatches, args.batch_size)
generated = bleu_format(prediction, tgt_dict, valid_set.nbatches, args.batch_size)
callbacks = Callbacks(model, eval_set=valid_set, **args.callback_args)
# train model
model.fit(train_set,
optimizer=optimizer,
num_epochs=args.epochs,
cost=cost, callbacks=callbacks)
# obtain predictions
shape = (valid_set.nbatches, args.batch_size, time_steps)
if num_beams == 0:
ypred = model.get_outputs(valid_set)
# flip the reversed predictions back to normal sentence order
prediction = ypred.argmax(2).reshape(shape).transpose(1, 0, 2)[:, :, ::-1]
else:
ypred = model.get_outputs_beam(valid_set, num_beams=num_beams)
prediction = ypred.reshape(shape).transpose(1, 0, 2)[:, :, ::-1]
# print some examples
src_dict, tgt_dict = valid_set.s_index_to_token, valid_set.t_index_to_token
for i in range(3):
print_sample(ex_source=valid_set.X[i, 0, :],
ex_reference=valid_set.y[i, 0, :],
ex_prediction=prediction[i, 0, :],
src_dict=src_dict, tgt_dict=tgt_dict)
# compute BLEU scores
inputs = valid_set.X[:, :valid_set.nbatches, :]
source_sentences = bleu_format(inputs, tgt_dict, valid_set.nbatches, args.batch_size)
generated = bleu_format(prediction, tgt_dict, valid_set.nbatches, args.batch_size)
