def cycle(): objective_func = array([10, -57, -9, -24]) constraint_lhs = array([[1 / 2, -11 / 2, -5 / 2, 9], [1 / 2, -3 / 2, -1 / 2, 1], [1, 0, 0, 0]]) constraint_rhs = array([0, 0, 1]) return StandardLinearProgram(objective_func, constraint_lhs, constraint_rhs)
def make_sample_from_input_sent(sent, vocab_word_corpus, vocab_word_emb): sent = [w.lower() for w in sent] x = [] if vocab_word_corpus: word_ids_corpus = array([ w for w in convert_str_to_id( sent=sent, vocab=vocab_word_corpus, unk=UNK) ]) x.append([word_ids_corpus]) if vocab_word_emb: word_ids_emb = array([ w for w in convert_str_to_id( sent=sent, vocab=vocab_word_emb, unk=UNK) ]) x.append([word_ids_emb]) return x
def make_batches(self, samples): """ :param samples: 1D: n_samples, 2D: [x, m, y] :return 1D: n_batches, 2D: batch_size; elem=[x, m, y] """ np.random.shuffle(samples) samples.sort(key=lambda sample: len(sample[0])) batches = [] batch = [] prev_n_words = len(samples[0][0]) for sample in samples: n_words = len(sample[0]) if len(batch) == self.argv.batch_size or prev_n_words != n_words: batches.append(map(lambda b: array(b), zip(*batch))) batch = [] prev_n_words = n_words batch.append(sample) if batch: batches.append(map(lambda b: array(b), zip(*batch))) return batches
def add_mark_to_sample(sample, mark): x = [x_i[0] for x_i in sample] prd_indices = [i for i, m in enumerate(mark[0]) if m] n_words = len(x[0]) n_prds = len(prd_indices) mark_ids = [[0 for _ in xrange(n_words)] for _ in xrange(n_prds)] for i, prd_index in enumerate(prd_indices): mark_ids[i][prd_index] = 1 mark_ids = array(mark_ids) batch = map(lambda m: x + [m], mark_ids) batch = map(lambda b: b, zip(*batch)) return batch
def makeObservations(x,y,ripl): xString = genSamples(x) ripl.observe(xString, array(y))
def basic(): objective_func = array([5, 4, 3]) constraint_lhs = array([[2, 3, 1], [4, 1, 2], [3, 4, 2]]) constraint_rhs = array([5, 11, 8]) return StandardLinearProgram(objective_func, constraint_lhs, constraint_rhs)
def unbounded(): objective_func = array([1, -1]) constraint_lhs = array([[-2, 3], [0, 4], [0, -1]]) constraint_rhs = array([5, 7, 0]) return StandardLinearProgram(objective_func, constraint_lhs, constraint_rhs)
def klee_minty2(): objective_func = array([4, 2, 1]) constraint_lhs = array([[1, 0, 0], [4, 1, 0], [8, 4, 1]]) constraint_rhs = array([5, 25, 125]) return StandardLinearProgram(objective_func, constraint_lhs, constraint_rhs)
def klee_minty(): objective_func = array([100, 10, 1]) constraint_lhs = array([[1, 0, 0], [20, 1, 0], [200, 20, 1]]) constraint_rhs = array([1, 100, 10000]) return StandardLinearProgram(objective_func, constraint_lhs, constraint_rhs)
def need_init(): objective_func = array([-2, -1]) constraint_lhs = array([[-1, 1], [-1, -2], [0, 1]]) constraint_rhs = array([-1, -2, 1]) return StandardLinearProgram(objective_func, constraint_lhs, constraint_rhs)