de00082780be884fc90e0113d323bfd63006ffba,main.py,Model,train,#Model#,428

Before Change

                    "train", hparams.BATCH_SIZE * hparams.MAX_N_SIGNAL, shuffle=True)):
                max_len = max(map(len, data_pt[0]))
                spectra = np.stack(
                    [np.pad(x, [(0, (-len(x))%max_len), (0,0)], mode="constant") for x in data_pt[0]])
                spectra = np.reshape(
                    spectra,
                    [hparams.BATCH_SIZE, hparams.MAX_N_SIGNAL, max_len, hparams.FEATURE_SIZE])

After Change

            for i_batch, data_pt in enumerate(dataset.epoch(
                    "train",
                    hparams.BATCH_SIZE * hparams.MAX_N_SIGNAL, shuffle=True)):
                to_feed = dict(
                    zip(self.train_feed_keys, (
                        np.reshape(data_pt[0], [hparams.BATCH_SIZE, hparams.MAX_N_SIGNAL, -1, hparams.FEATURE_SIZE]),
                        hparams.DROPOUT_KEEP_PROB)))
                step_summary, step_fetch = g_sess.run(
                    self.train_fetches, to_feed)[:2]
                self.reset_state()
                train_writer.add_summary(step_summary)

Instances