def __init__(self, graph=None):
self._eager_context = _EagerContext()
if not self.in_eager_mode():
raise ValueError("Trying to create a Context in GRAPH_MODE")
# Create a handle
opts = pywrap_tensorflow.TF_NewSessionOptions(
target=compat.as_bytes(""), config=None)
with errors.raise_exception_on_not_ok_status() as status:
self._handle = pywrap_tensorflow.TFE_NewContext(opts, status)
pywrap_tensorflow.TF_DeleteSessionOptions(opts)
# Store list of devices
self._devices = []
with errors.raise_exception_on_not_ok_status() as status:
device_list = pywrap_tensorflow.TFE_ContextListDevices(
self._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._devices.append(pydev.canonical_name(dev_name))
finally:
pywrap_tensorflow.TF_DeleteDeviceList(device_list)
self._summary_writer_resource = None
self._graph = graph or tf_ops.get_default_graph()
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)
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_NewSession(opts, status)
finally:
tf_session.TF_DeleteSessionOptions(opts)
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:
RuntimeError: If an error occurs while creating the TensorFlow
session.
"""
if graph is None:
self._graph = ops.get_default_graph()
else:
self._graph = graph
self._opened = False
self._closed = False
self._current_version = 0
self._extend_lock = threading.Lock()
self._target = target
self._delete_lock = threading.Lock()
self._dead_handles = []
self._session = None
opts = tf_session.TF_NewSessionOptions(target=target, config=config)
try:
status = tf_session.TF_NewStatus()
try:
self._session = tf_session.TF_NewSession(opts, status)
if tf_session.TF_GetCode(status) != 0:
raise RuntimeError(
compat.as_text(tf_session.TF_Message(status)))
finally:
tf_session.TF_DeleteStatus(status)
finally:
tf_session.TF_DeleteSessionOptions(opts)
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.
"""
if graph is None:
self._graph = ops.get_default_graph()
else:
self._graph = graph
self._opened = False
self._closed = False
self._current_version = 0
self._extend_lock = threading.Lock()
self._target = target
self._delete_lock = threading.Lock()
self._dead_handles = []
self._session = None
self._config = config
self._add_shapes = config.graph_options.infer_shapes if (
config and config.graph_options) else False
try:
opts = tf_session.TF_NewSessionOptions(target=target,
config=config)
with errors.raise_exception_on_not_ok_status() as status:
self._session = tf_session.TF_NewSession(opts, status)
finally:
tf_session.TF_DeleteSessionOptions(opts)
def __init__(self):
self._eager_context = _EagerContext()
# Create a handle
opts = pywrap_tensorflow.TF_NewSessionOptions(
target=compat.as_bytes(""), config=None)
with errors.raise_exception_on_not_ok_status() as status:
self._handle = pywrap_tensorflow.TFE_NewContext(opts, status)
pywrap_tensorflow.TF_DeleteSessionOptions(opts)
# Store list of devices
self._devices = []
with errors.raise_exception_on_not_ok_status() as status:
device_list = pywrap_tensorflow.TFE_ContextListDevices(
self._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._devices.append(pydev.canonical_name(dev_name))
finally:
pywrap_tensorflow.TF_DeleteDeviceList(device_list)
self._summary_writer_resource = None
