def _pad(self, side, length): """ Pad sequences to given length in the left or right side. """ if self._train_set: self._train_set = pad_dataset(self._train_set, side, length) if self._valid_set: self._valid_set = pad_dataset(self._valid_set, side, length) if self._test_set: self._test_set = pad_dataset(self._test_set, side, length)
def _yield_data(self, subset): for i in xrange(0, len(subset), self.size): x_set, y_set = [], [] batch = pad_dataset(subset[i:i + self.size], PADDING_SIDE, self.padding_length) for x, y in batch: x_set.append(x) y_set.append(y) x_set = np.array(x_set) y_set = np.array(y_set) yield x_set, y_set
def _yield_data(self, subset): for i in xrange(0, len(subset), self.size): x_set, y_set = [], [] batch = pad_dataset(subset[i:i + self.size], PADDING_SIDE, self.padding_length) for x, y in batch: x_set.append(x) y_set.append(y) x_set = np.array(x_set) y_set = np.array(y_set) if self._fix_batch_size and x_set.shape[0] != self.size: continue yield x_set, y_set