本文整理汇总了Python中tensorflow.python.pywrap_tensorflow.TF_NewSessionOptions方法的典型用法代码示例。如果您正苦于以下问题：Python pywrap_tensorflow.TF_NewSessionOptions方法的具体用法？Python pywrap_tensorflow.TF_NewSessionOptions怎么用？Python pywrap_tensorflow.TF_NewSessionOptions使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类tensorflow.python.pywrap_tensorflow的用法示例。
在下文中一共展示了pywrap_tensorflow.TF_NewSessionOptions方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _initialize_handle_and_devices
# 需要导入模块: from tensorflow.python import pywrap_tensorflow [as 别名]
# 或者: from tensorflow.python.pywrap_tensorflow import TF_NewSessionOptions [as 别名]
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) 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:26，代码来源:context.py
示例2: __init__
# 需要导入模块: from tensorflow.python import pywrap_tensorflow [as 别名]
# 或者: from tensorflow.python.pywrap_tensorflow import TF_NewSessionOptions [as 别名]
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)