(self, data_dir)
Load graph and weight data.

        Args:
            data_dir (:obj:`str`): location of Keras checkpoint (`.hdf5`) files
                and model (in `.json`) structure.  The default behavior
                is to take the latest of each, by OS timestamp.
Load graph and weight data.
Load graph and weight data .
def load(self, data_dir):
        """Load graph and weight data.

        Args:
            data_dir (:obj:`str`): location of Keras checkpoint (`.hdf5`) files
                and model (in `.json`) structure.  The default behavior
                is to take the latest of each, by OS timestamp.
        """
        # for tensorflow compatibility
        K.set_learning_phase(0)

        # find newest ckpt and graph files
        try:
            latest_ckpt = max(glob.iglob(
                os.path.join(data_dir, '*.h*5')), key=os.path.getctime)
            latest_ckpt_name = os.path.basename(latest_ckpt)
            latest_ckpt_time = str(
                datetime.fromtimestamp(os.path.getmtime(latest_ckpt)))
        except ValueError:
            raise FileNotFoundError('No checkpoint (.hdf5 or .h5) files '
                                    'available at {}'.format(data_dir))
        try:
            latest_json = max(glob.iglob(os.path.join(data_dir, '*.json')),
                              key=os.path.getctime)
            with open(latest_json, 'r') as f:
                model_json = json.loads(f.read())
                self._model = model_from_json(model_json)

            self._model.load_weights(latest_ckpt)
        except ValueError:
            try:
                self._model = load_model(latest_ckpt)
            except ValueError:
                raise FileNotFoundError('The (.hdf5 or .h5) files available at'
                                        '{} don\'t have the model'
                                        ' architecture.'
                                        .format(latest_ckpt))

        self._sess = K.get_session()
        self._tf_predict_var = self._model.outputs[0]
        self._tf_input_var = self._model.inputs[0]
        self._model_name = type(self).__name__
        self._latest_ckpt_name = latest_ckpt_name
        self._latest_ckpt_time = latest_ckpt_time
def load ( self , data_dir ) : # for tensorflow compatibility K . set_learning_phase ( 0 ) # find newest ckpt and graph files try : latest_ckpt = max ( glob . iglob ( os . path . join ( data_dir , '*.h*5' ) ) , key = os . path . getctime ) latest_ckpt_name = os . path . basename ( latest_ckpt ) latest_ckpt_time = str ( datetime . fromtimestamp ( os . path . getmtime ( latest_ckpt ) ) ) except ValueError : raise FileNotFoundError ( 'No checkpoint (.hdf5 or .h5) files ' 'available at {}' . format ( data_dir ) ) try : latest_json = max ( glob . iglob ( os . path . join ( data_dir , '*.json' ) ) , key = os . path . getctime ) with open ( latest_json , 'r' ) as f : model_json = json . loads ( f . read ( ) ) self . _model = model_from_json ( model_json ) self . _model . load_weights ( latest_ckpt ) except ValueError : try : self . _model = load_model ( latest_ckpt ) except ValueError : raise FileNotFoundError ( 'The (.hdf5 or .h5) files available at' '{} don\'t have the model' ' architecture.' . format ( latest_ckpt ) ) self . _sess = K . get_session ( ) self . _tf_predict_var = self . _model . outputs [ 0 ] self . _tf_input_var = self . _model . inputs [ 0 ] self . _model_name = type ( self ) . __name__ self . _latest_ckpt_name = latest_ckpt_name self . _latest_ckpt_time = latest_ckpt_time