本文整理匯總了Python中tensorflow.python.pywrap_tensorflow.TF_DeleteSessionOptions方法的典型用法代碼示例。如果您正苦於以下問題：Python pywrap_tensorflow.TF_DeleteSessionOptions方法的具體用法？Python pywrap_tensorflow.TF_DeleteSessionOptions怎麽用？Python pywrap_tensorflow.TF_DeleteSessionOptions使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類tensorflow.python.pywrap_tensorflow的用法示例。
在下文中一共展示了pywrap_tensorflow.TF_DeleteSessionOptions方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: _initialize_handle_and_devices
# 需要導入模塊: from tensorflow.python import pywrap_tensorflow [as 別名]
# 或者: from tensorflow.python.pywrap_tensorflow import TF_DeleteSessionOptions [as 別名]
def _initialize_handle_and_devices(self):
"""Initialize handle and devices."""
with self._initialize_lock:
if self._context_handle is not None:
return
assert self._context_devices is None
opts = pywrap_tensorflow.TF_NewSessionOptions(
target=compat.as_bytes(""), config=self._config)
with errors.raise_exception_on_not_ok_status() as status:
self._context_handle = pywrap_tensorflow.TFE_NewContext(opts, status)
pywrap_tensorflow.TF_DeleteSessionOptions(opts)
# Store list of devices
self._context_devices = []
with errors.raise_exception_on_not_ok_status() as status:
device_list = pywrap_tensorflow.TFE_ContextListDevices(
self._context_handle, status)
try:
for i in range(pywrap_tensorflow.TF_DeviceListCount(device_list)):
with errors.raise_exception_on_not_ok_status() as status:
dev_name = pywrap_tensorflow.TF_DeviceListName(
device_list, i, status)
self._context_devices.append(pydev.canonical_name(dev_name))
finally:
pywrap_tensorflow.TF_DeleteDeviceList(device_list) 開發者ID:PacktPublishing，項目名稱:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代碼行數:26，代碼來源:context.py
示例2: __init__
# 需要導入模塊: from tensorflow.python import pywrap_tensorflow [as 別名]
# 或者: from tensorflow.python.pywrap_tensorflow import TF_DeleteSessionOptions [as 別名]
def __init__(self, target='', graph=None, config=None):
"""Constructs a new TensorFlow session.
Args:
target: (Optional) The TensorFlow execution engine to connect to.
graph: (Optional) The graph to be used. If this argument is None,
the default graph will be used.
config: (Optional) ConfigProto proto used to configure the session.
Raises:
tf.errors.OpError: Or one of its subclasses if an error occurs while
creating the TensorFlow session.
TypeError: If one of the arguments has the wrong type.
"""
if graph is None:
self._graph = ops.get_default_graph()
else:
if not isinstance(graph, ops.Graph):
raise TypeError('graph must be a tf.Graph, but got %s' % type(graph))
self._graph = graph
self._opened = False
self._closed = False
self._current_version = 0
self._extend_lock = threading.Lock()
if target is not None:
try:
self._target = compat.as_bytes(target)
except TypeError:
raise TypeError('target must be a string, but got %s' % type(target))
else:
self._target = None
self._delete_lock = threading.Lock()
self._dead_handles = []
if config is not None:
if not isinstance(config, config_pb2.ConfigProto):
raise TypeError('config must be a tf.ConfigProto, but got %s'
% type(config))
self._config = config
self._add_shapes = config.graph_options.infer_shapes
else:
self._config = None
self._add_shapes = False
self._session = None
opts = tf_session.TF_NewSessionOptions(target=self._target, config=config)
try:
with errors.raise_exception_on_not_ok_status() as status:
self._session = tf_session.TF_NewDeprecatedSession(opts, status)
finally:
tf_session.TF_DeleteSessionOptions(opts)