74c062162194fa2d89e85f2a99bf4c71e66d5654,examples/tsf/tsf_trainer.py,TSFTrainer,eval_model,#TSFTrainer#Any#Any#Any#Any#Any#Any#,93

Before Change

            logits_ori, logits_tsf = model.decode_step(sess, batch)
            loss, loss_g, ppl_g, loss_d, loss_d0, loss_d1 = model.eval_step(
                sess, batch, self._hparams.rho, self._hparams.gamma_min)
            batch_size = batch["enc_inputs"].shape()[0]
            word_size = np.sum(batch["weights"])
            losses.append(loss, loss_g, ppl_g, loss_d, loss_d0, loss_d1,
                          w_loss=batch_size, w_g=batch_size,

After Change

        data0_ori, data1_ori, data0_tsf, data1_tsf = [], [], [], []
        while True:
            try:
                batch = sess.run(input_tensors,
                                 {tx.global_mode(): tf.estimator.ModeKeys.EVAL})
                logits_ori, logits_tsf = model.decode_step(sess, batch)
                loss, loss_g, ppl_g, loss_d, loss_d0, loss_d1 = model.eval_step(
                    sess, batch, self._hparams.rho, self._hparams.gamma_min)
                batch_size = batch["enc_inputs"].shape[0]
                word_size = np.sum(batch["weights"])
                losses.append(loss, loss_g, ppl_g, loss_d, loss_d0, loss_d1,
                              w_loss=batch_size, w_g=batch_size,
                              w_ppl=word_size, w_d=batch_size,
                              w_d0=batch_size, w_d1=batch_size)
                ori = logits2word(logits_ori, id2word)
                tsf = logits2word(logits_tsf, id2word)
                half = self._hparams.batch_size // 2
                data0_ori += ori[:half]
                data1_ori += ori[half:]
                data0_tsf += tsf[:half]
                data1_tsf += tsf[half:]
            except tf.errors.OutOfRangeError:
                break

        n = dataset._dataset_size
        data0_ori = data0_ori[:n]
        data1_ori = data1_ori[:n]
        data0_tsf = data0_tsf[:n]

Instances