10 examples of 'history.history keras' in Python

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def test_history(self):
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    attention = SeqSelfAttention(return_attention=True,
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                                 attention_width=3,
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                                 history_only=True,
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                                 name='Attention')
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    self.check_mask_shape(attention)

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def _history(self):
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    pass

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def load_history(self, history_file):
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    """
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    Load benchmark history from file
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    Args:
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        history_file: path to history file
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    Returns:
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    """
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    logging.info("Loading benchmark history data from {}".format(history_file))
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    with open(os.path.join(os.getcwd(), history_file), "rb") as fp:
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        self.history_data = pickle.load(fp)

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def restore_history(self, history):
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    return self._restore_history(history, _called_directly=False)

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def _save_history(historyPath = _history):
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   readline.write_history_file(_history)

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def history(args):
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    with open(HISTORY_PATH, 'r') as history_file:
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        lines = history_file.readlines()
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        # default limit is whole file
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        limit = len(lines)
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        if len(args) > 0:
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            limit = int(args[0])
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        # start history line to print out
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        start = len(lines) - limit
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        for line_num, line in enumerate(lines):
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            if line_num >= start:
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                sys.stdout.write('%d %s' % (line_num + 1, line))
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        sys.stdout.flush()
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    return SHELL_STATUS_RUN

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def do_history(self, line):
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    """ Show the history. """
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    self.print_history()

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def plot_history(history):
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    # summarize history for accuracy
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    plt.plot(history.history['acc'])
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    plt.plot(history.history['val_acc'])
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    plt.title('model accuracy')
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    plt.ylabel('accuracy')
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    plt.xlabel('epoch')
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    plt.legend(['train', 'validation'], loc='upper left')
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    plt.show()
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    # summarize history for loss
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    plt.plot(history.history['loss'])
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    plt.plot(history.history['val_loss'])
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    plt.title('model loss')
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    plt.ylabel('loss')
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    plt.xlabel('epoch')
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    plt.legend(['train', 'validation'], loc='upper left')
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    plt.show()
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    # summarize history for error
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    plt.plot(history.history['mean_absolute_error'])
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    plt.plot(history.history['val_mean_absolute_error'])
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    plt.title('model mean_absolute_error')
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    plt.ylabel('mean_absolute_error')
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    plt.xlabel('epoch')
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    plt.legend(['train', 'validation'], loc='upper left')
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    plt.show()

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def save_history(history, result_dir, name):
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    loss=history.history['loss']
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    acc=history.history['acc']
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    val_loss=history.history['val_loss']
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    val_acc=history.history['val_acc']
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    nb_epoch=len(acc)
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    with open(os.path.join(result_dir, 'result_{}.txt'.format(name)), 'w') as fp:
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        fp.write('epoch\tloss\tacc\tval_loss\tval_acc\n')
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        for i in range(nb_epoch):
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            fp.write('{}\t{}\t{}\t{}\t{}\n'.format(
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                i, loss[i], acc[i], val_loss[i], val_acc[i]))

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def _set_history(self, h):
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    self._history = h
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    self._history_was_set = True