本文整理汇总了Python中tensorflow.python.pywrap_tensorflow.TF_GetBuffer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_GetBuffer方法的具体用法？Python pywrap_tensorflow.TF_GetBuffer怎么用？Python pywrap_tensorflow.TF_GetBuffer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_GetBuffer方法的3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: tf_buffer
# 需要导入模块: from tensorflow.python import pywrap_tensorflow [as 别名]
# 或者: from tensorflow.python.pywrap_tensorflow import TF_GetBuffer [as 别名]
def tf_buffer():
"""Context manager that creates and deletes TF_Buffer.
Example usage:
wtih tf_buffer() as buf:
# get serialized graph def into buf
...
proto_data = c_api.TF_GetBuffer(buf)
graph_def.ParseFromString(compat.as_bytes(proto_data))
# buf has been deleted
Yields:
Created TF_Buffer
"""
buf = c_api.TF_NewBuffer()
try:
yield buf
finally:
c_api.TF_DeleteBuffer(buf) 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:21，代码来源:c_api_util.py
示例2: sync
# 需要导入模块: from tensorflow.python import pywrap_tensorflow [as 别名]
# 或者: from tensorflow.python.pywrap_tensorflow import TF_GetBuffer [as 别名]
def sync():
p_buffer = c_api.TF_GetAllOpList()
cpp_op_list = op_def_pb2.OpList()
cpp_op_list.ParseFromString(c_api.TF_GetBuffer(p_buffer))
registered_ops = op_def_registry.get_registered_ops()
for op_def in cpp_op_list.op:
# If an OpList is registered from a gen_*_ops.py, it does not any
# descriptions. Strip them here as well to satisfy validation in
# register_op_list.
_remove_non_deprecated_descriptions(op_def)
registered_ops[op_def.name] = op_def 示例3: definition
# 需要导入模块: from tensorflow.python import pywrap_tensorflow [as 别名]
# 或者: from tensorflow.python.pywrap_tensorflow import TF_GetBuffer [as 别名]
def definition(self):
"""Function definition proto."""
self._create_definition_if_needed()
if self._c_func:
with c_api_util.tf_buffer() as buf:
with errors.raise_exception_on_not_ok_status() as status:
c_api.TF_FunctionToFunctionDef(self._c_func, buf, status)
fdef = function_pb2.FunctionDef()
proto_data = c_api.TF_GetBuffer(buf)
fdef.ParseFromString(compat.as_bytes(proto_data))
return fdef
return self._definition 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:14，代码来源:function.py