def __init__(self,
trainable=True,
name=None,
dtype=dtypes.float32,
**kwargs):
allowed_kwargs = {'_scope', '_reuse'}
for kwarg in kwargs:
if kwarg not in allowed_kwargs:
raise TypeError('Keyword argument not understood:', kwarg)
self.trainable = trainable
self.built = False
self._trainable_weights = []
self._non_trainable_weights = []
self._updates = []
self._losses = []
self._reuse = kwargs.get('_reuse')
self._graph = ops.get_default_graph()
self._per_input_losses = {}
self._per_input_updates = {}
self.dtype = dtypes.as_dtype(dtype)
self.input_spec = None
# Determine layer name
if name is None:
base_name = _to_snake_case(self.__class__.__name__)
self.name = _unique_layer_name(base_name)
else:
base_name = name
self.name = name
self._base_name = base_name
# Determine variable scope.
self._scope = None
def __init__(self, trainable=True, name=None, dtype=dtypes.float32, **kwargs):
allowed_kwargs = {'_scope',
'_reuse'}
for kwarg in kwargs:
if kwarg not in allowed_kwargs:
raise TypeError('Keyword argument not understood:', kwarg)
self.trainable = trainable
self.built = False
self._trainable_weights = []
self._non_trainable_weights = []
self._updates = []
self._losses = []
self._reuse = kwargs.get('_reuse')
self._graph = ops.get_default_graph()
self._per_input_losses = {}
self._per_input_updates = {}
self.dtype = dtypes.as_dtype(dtype)
self.input_spec = None
# Determine layer name
if name is None:
base_name = _to_snake_case(self.__class__.__name__)
self.name = _unique_layer_name(base_name)
else:
base_name = name
self.name = name
self._base_name = base_name
# Determine variable scope.
self._scope = None
def _unique_layer_name(name):
global PER_GRAPH_LAYER_NAME_UIDS
graph = ops.get_default_graph()
if graph not in PER_GRAPH_LAYER_NAME_UIDS:
PER_GRAPH_LAYER_NAME_UIDS[graph] = collections.defaultdict(int)
layer_name_uids = PER_GRAPH_LAYER_NAME_UIDS[graph]
layer_name_uids[name] += 1
return name + '_' + str(layer_name_uids[name])
def __init__(self, target='', graph=None, config=None):
if graph is None:
self._graph = ops.get_default_graph()
else:
self._graph = graph
self._opened = False
self._closed = False
if config is not None:
if not isinstance(config, config_pb2.ConfigProto):
raise TypeError(
'Config should be a tf.ConfigProto, but got {}'.format(
type(config)))
self._config = config
self._add_shapes = config.graph_options.infer_shapes
else:
self._config = None
self._add_shapes = False
def __init__(self, target='', graph=None, config=None):
if graph is None:
self._graph = ops.get_default_graph()
else:
raise NotImplementedError('Session can only use the default graph yet.')
self._opened = False
self._closed = False
if config is not None:
if not isinstance(config, config_pb2.ConfigProto):
raise TypeError('Config should be a tf.ConfigProto, but got {}'.format(type(config)))
self._config = config
self._add_shapes = config.graph_options.infer_shapes
else:
self._config = None
self._add_shapes = False
self._session = None
def _unique_layer_name(name):
graph = ops.get_default_graph()
if graph not in PER_GRAPH_LAYER_NAME_UIDS:
PER_GRAPH_LAYER_NAME_UIDS[graph] = collections.defaultdict(int)
layer_name_uids = PER_GRAPH_LAYER_NAME_UIDS[graph]
layer_name_uids[name] += 1
