Source code for deeppavlov.core.models.tf_backend

# Copyright 2017 Neural Networks and Deep Learning lab, MIPT
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from abc import ABCMeta
from functools import wraps

import tensorflow as tf
from six import with_metaclass


def _graph_wrap(func, graph):
    """Constructs function encapsulated in the graph."""
    @wraps(func)
    def _wrapped(*args, **kwargs):
        with graph.as_default():
            return func(*args, **kwargs)
    return _wrapped


def _keras_wrap(func, graph, session):
    """Constructs function encapsulated in the graph and the session."""
    import keras.backend as K

    @wraps(func)
    def _wrapped(*args, **kwargs):
        with graph.as_default():
            K.set_session(session)
            return func(*args, **kwargs)
    return _wrapped


[docs]class TfModelMeta(with_metaclass(type, ABCMeta)): """Metaclass that helps all child classes to have their own graph and session.""" def __call__(cls, *args, **kwargs): obj = cls.__new__(cls) from .keras_model import KerasModel if issubclass(cls, KerasModel): import keras.backend as K if K.backend() != 'tensorflow': obj.__init__(*args, **kwargs) return obj K.clear_session() obj.graph = tf.Graph() with obj.graph.as_default(): if hasattr(cls, '_config_session'): obj.sess = cls._config_session() else: obj.sess = tf.Session() else: obj.graph = tf.Graph() for meth in dir(obj): if meth == '__class__': continue attr = getattr(obj, meth) if callable(attr): if issubclass(cls, KerasModel): wrapped_attr = _keras_wrap(attr, obj.graph, obj.sess) else: wrapped_attr = _graph_wrap(attr, obj.graph) setattr(obj, meth, wrapped_attr) obj.__init__(*args, **kwargs) return obj