Python tensorflow.python.pywrap_tensorflow.PyServer_New() Examples

The following are 5 code examples of tensorflow.python.pywrap_tensorflow.PyServer_New(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module tensorflow.python.pywrap_tensorflow , or try the search function .
Example #1
Source File: server_lib.py    From lambda-packs with MIT License 4 votes vote down vote up 
def __init__(self,
               server_or_cluster_def,
               job_name=None,
               task_index=None,
               protocol=None,
               config=None,
               start=True):
    """Creates a new server with the given definition.

    The `job_name`, `task_index`, and `protocol` arguments are optional, and
    override any information provided in `server_or_cluster_def`.

    Args:
      server_or_cluster_def: A `tf.train.ServerDef` or
        `tf.train.ClusterDef` protocol buffer, or a
        `tf.train.ClusterSpec` object, describing the server to be
        created and/or the cluster of which it is a member.
      job_name: (Optional.) Specifies the name of the job of which the server
        is a member. Defaults to the value in `server_or_cluster_def`, if
        specified.
      task_index: (Optional.) Specifies the task index of the server in its
        job. Defaults to the value in `server_or_cluster_def`, if specified.
        Otherwise defaults to 0 if the server's job has only one task.
      protocol: (Optional.) Specifies the protocol to be used by the server.
        Acceptable values include `"grpc"`. Defaults to the value in
        `server_or_cluster_def`, if specified. Otherwise defaults to `"grpc"`.
      config: (Options.) A `tf.ConfigProto` that specifies default
        configuration options for all sessions that run on this server.
      start: (Optional.) Boolean, indicating whether to start the server
        after creating it. Defaults to `True`.

    Raises:
      tf.errors.OpError: Or one of its subclasses if an error occurs while
        creating the TensorFlow server.
    """
    self._server_def = _make_server_def(server_or_cluster_def,
                                        job_name, task_index, protocol, config)
    with errors.raise_exception_on_not_ok_status() as status:
      self._server = pywrap_tensorflow.PyServer_New(
          self._server_def.SerializeToString(), status)
    if start:
      self.start()
Example #2
Source File: server_lib.py    From auto-alt-text-lambda-api with MIT License 4 votes vote down vote up 
def __init__(self,
               server_or_cluster_def,
               job_name=None,
               task_index=None,
               protocol=None,
               config=None,
               start=True):
    """Creates a new server with the given definition.

    The `job_name`, `task_index`, and `protocol` arguments are optional, and
    override any information provided in `server_or_cluster_def`.

    Args:
      server_or_cluster_def: A `tf.train.ServerDef` or
        `tf.train.ClusterDef` protocol buffer, or a
        `tf.train.ClusterSpec` object, describing the server to be
        created and/or the cluster of which it is a member.
      job_name: (Optional.) Specifies the name of the job of which the server
        is a member. Defaults to the value in `server_or_cluster_def`, if
        specified.
      task_index: (Optional.) Specifies the task index of the server in its
        job. Defaults to the value in `server_or_cluster_def`, if specified.
        Otherwise defaults to 0 if the server's job has only one task.
      protocol: (Optional.) Specifies the protocol to be used by the server.
        Acceptable values include `"grpc"`. Defaults to the value in
        `server_or_cluster_def`, if specified. Otherwise defaults to `"grpc"`.
      config: (Options.) A `tf.ConfigProto` that specifies default
        configuration options for all sessions that run on this server.
      start: (Optional.) Boolean, indicating whether to start the server
        after creating it. Defaults to `True`.

    Raises:
      tf.errors.OpError: Or one of its subclasses if an error occurs while
        creating the TensorFlow server.
    """
    self._server_def = _make_server_def(server_or_cluster_def,
                                        job_name, task_index, protocol, config)
    with errors.raise_exception_on_not_ok_status() as status:
      self._server = pywrap_tensorflow.PyServer_New(
          self._server_def.SerializeToString(), status)
    if start:
      self.start()
Example #3
Source File: server_lib.py    From deep_image_model with Apache License 2.0 4 votes vote down vote up 
def __init__(self,
               server_or_cluster_def,
               job_name=None,
               task_index=None,
               protocol=None,
               config=None,
               start=True):
    """Creates a new server with the given definition.

    The `job_name`, `task_index`, and `protocol` arguments are optional, and
    override any information provided in `server_or_cluster_def`.

    Args:
      server_or_cluster_def: A `tf.train.ServerDef` or
        `tf.train.ClusterDef` protocol buffer, or a
        `tf.train.ClusterSpec` object, describing the server to be
        created and/or the cluster of which it is a member.
      job_name: (Optional.) Specifies the name of the job of which the server
        is a member. Defaults to the value in `server_or_cluster_def`, if
        specified.
      task_index: (Optional.) Specifies the task index of the server in its
        job. Defaults to the value in `server_or_cluster_def`, if specified.
        Otherwise defaults to 0 if the server's job has only one task.
      protocol: (Optional.) Specifies the protocol to be used by the server.
        Acceptable values include `"grpc"`. Defaults to the value in
        `server_or_cluster_def`, if specified. Otherwise defaults to `"grpc"`.
      config: (Options.) A `tf.ConfigProto` that specifies default
        configuration options for all sessions that run on this server.
      start: (Optional.) Boolean, indicating whether to start the server
        after creating it. Defaults to `True`.

    Raises:
      tf.errors.OpError: Or one of its subclasses if an error occurs while
        creating the TensorFlow server.
    """
    self._server_def = _make_server_def(server_or_cluster_def,
                                        job_name, task_index, protocol, config)
    with errors.raise_exception_on_not_ok_status() as status:
      self._server = pywrap_tensorflow.PyServer_New(
          self._server_def.SerializeToString(), status)
    if start:
      self.start()
Example #4
Source File: server_lib.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 4 votes vote down vote up 
def __init__(self,
               server_or_cluster_def,
               job_name=None,
               task_index=None,
               protocol=None,
               config=None,
               start=True):
    """Creates a new server with the given definition.

    The `job_name`, `task_index`, and `protocol` arguments are optional, and
    override any information provided in `server_or_cluster_def`.

    Args:
      server_or_cluster_def: A `tf.train.ServerDef` or
        `tf.train.ClusterDef` protocol buffer, or a
        `tf.train.ClusterSpec` object, describing the server to be
        created and/or the cluster of which it is a member.
      job_name: (Optional.) Specifies the name of the job of which the server
        is a member. Defaults to the value in `server_or_cluster_def`, if
        specified.
      task_index: (Optional.) Specifies the task index of the server in its
        job. Defaults to the value in `server_or_cluster_def`, if specified.
        Otherwise defaults to 0 if the server's job has only one task.
      protocol: (Optional.) Specifies the protocol to be used by the server.
        Acceptable values include `"grpc"`. Defaults to the value in
        `server_or_cluster_def`, if specified. Otherwise defaults to `"grpc"`.
      config: (Options.) A `tf.ConfigProto` that specifies default
        configuration options for all sessions that run on this server.
      start: (Optional.) Boolean, indicating whether to start the server
        after creating it. Defaults to `True`.

    Raises:
      tf.errors.OpError: Or one of its subclasses if an error occurs while
        creating the TensorFlow server.
    """
    self._server_def = _make_server_def(server_or_cluster_def,
                                        job_name, task_index, protocol, config)
    with errors.raise_exception_on_not_ok_status() as status:
      self._server = pywrap_tensorflow.PyServer_New(
          self._server_def.SerializeToString(), status)
    if start:
      self.start()
Example #5
Source File: server_lib.py    From keras-lambda with MIT License 4 votes vote down vote up 
def __init__(self,
               server_or_cluster_def,
               job_name=None,
               task_index=None,
               protocol=None,
               config=None,
               start=True):
    """Creates a new server with the given definition.

    The `job_name`, `task_index`, and `protocol` arguments are optional, and
    override any information provided in `server_or_cluster_def`.

    Args:
      server_or_cluster_def: A `tf.train.ServerDef` or
        `tf.train.ClusterDef` protocol buffer, or a
        `tf.train.ClusterSpec` object, describing the server to be
        created and/or the cluster of which it is a member.
      job_name: (Optional.) Specifies the name of the job of which the server
        is a member. Defaults to the value in `server_or_cluster_def`, if
        specified.
      task_index: (Optional.) Specifies the task index of the server in its
        job. Defaults to the value in `server_or_cluster_def`, if specified.
        Otherwise defaults to 0 if the server's job has only one task.
      protocol: (Optional.) Specifies the protocol to be used by the server.
        Acceptable values include `"grpc"`. Defaults to the value in
        `server_or_cluster_def`, if specified. Otherwise defaults to `"grpc"`.
      config: (Options.) A `tf.ConfigProto` that specifies default
        configuration options for all sessions that run on this server.
      start: (Optional.) Boolean, indicating whether to start the server
        after creating it. Defaults to `True`.

    Raises:
      tf.errors.OpError: Or one of its subclasses if an error occurs while
        creating the TensorFlow server.
    """
    self._server_def = _make_server_def(server_or_cluster_def,
                                        job_name, task_index, protocol, config)
    with errors.raise_exception_on_not_ok_status() as status:
      self._server = pywrap_tensorflow.PyServer_New(
          self._server_def.SerializeToString(), status)
    if start:
      self.start()