Python variables.report_uninitialized_variables方法代码示例

# 需要导入模块: from tensorflow.python.ops import variables [as 别名]
# 或者: from tensorflow.python.ops.variables import report_uninitialized_variables [as 别名]
def _init_ready_op(self,
                     ready_op=USE_DEFAULT,
                     ready_for_local_init_op=USE_DEFAULT):
    """Initializes ready_op.

    Args:
      ready_op: `Tensor` to check if the model is initialized.
        If it's set to USE_DEFAULT, creates an op that checks all
        the variables are initialized.
      ready_for_local_init_op: `Tensor` to check if the model is ready to run
        local_init_op.
        If it's set to USE_DEFAULT, creates an op that checks all
        the global variables are initialized.
    """
    if ready_op is Supervisor.USE_DEFAULT:
      ready_op = self._get_first_op_from_collection(ops.GraphKeys.READY_OP)
      if ready_op is None:
        ready_op = variables.report_uninitialized_variables()
        ops.add_to_collection(ops.GraphKeys.READY_OP, ready_op)
    self._ready_op = ready_op

    # ready_for_local_init_op defaults to None for backward compatibility
    if ready_for_local_init_op is Supervisor.USE_DEFAULT:
      ready_for_local_init_op = self._get_first_op_from_collection(
          ops.GraphKeys.READY_FOR_LOCAL_INIT_OP)
    self._ready_for_local_init_op = ready_for_local_init_op 

# 需要导入模块: from tensorflow.python.ops import variables [as 别名]
# 或者: from tensorflow.python.ops.variables import report_uninitialized_variables [as 别名]
def _get_ready_op():
  ready_op = _get_first_op_from_collection(ops.GraphKeys.READY_OP)
  if ready_op is None:
    ready_op = variables.report_uninitialized_variables()
    ops.add_to_collection(ops.GraphKeys.READY_OP, ready_op)
  return ready_op 

# 需要导入模块: from tensorflow.python.ops import variables [as 别名]
# 或者: from tensorflow.python.ops.variables import report_uninitialized_variables [as 别名]
def finalize(self):
    """Creates operations if needed and finalizes the graph."""
    if self._init_op is None:
      def default_init_op():
        return control_flow_ops.group(
            variables.global_variables_initializer(),
            resources.initialize_resources(resources.shared_resources()))
      self._init_op = Scaffold.get_or_default(
          'init_op',
          ops.GraphKeys.INIT_OP,
          default_init_op)
    if self._ready_op is None:
      def default_ready_op():
        return array_ops.concat(
            0,
            [variables.report_uninitialized_variables(),
             resources.report_uninitialized_resources()])
      self._ready_op = Scaffold.get_or_default(
          'ready_op', ops.GraphKeys.READY_OP,
          default_ready_op)
    if self._local_init_op is None:
      self._local_init_op = Scaffold.get_or_default(
          'local_init_op', ops.GraphKeys.LOCAL_INIT_OP,
          Scaffold._default_local_init_op)
    if self._summary_op is None:
      self._summary_op = Scaffold.get_or_default('summary_op',
                                                 ops.GraphKeys.SUMMARY_OP,
                                                 summary.merge_all)
    # pylint: disable=g-long-lambda
    if self._saver is None:
      self._saver = Scaffold.get_or_default(
          'saver',
          ops.GraphKeys.SAVERS,
          lambda: training_saver.Saver(sharded=True, allow_empty=True,
                                       write_version=saver_pb2.SaverDef.V2))
    # pylint: enable=g-long-lambda
    self._saver.build()

    ops.get_default_graph().finalize()
    return self 

# 需要导入模块: from tensorflow.python.ops import variables [as 别名]
# 或者: from tensorflow.python.ops.variables import report_uninitialized_variables [as 别名]
def __init__(self,
               var_list=None,
               init_uninitialized_variables=False,
               **kwargs):
    kwargs['restore_sequentially'] = False
    kwargs['builder'] = BaseSaverBuilder()
    super(OptimisticRestoreSaver, self).__init__(var_list=var_list, **kwargs)
    self.init_uninitialized_variables = init_uninitialized_variables
    if self.init_uninitialized_variables:
      self.uninit_vars_op = variables.report_uninitialized_variables(
          var_list=self._var_list)
      self.init_ops = dict((v.name, variables.variables_initializer([v]))
                           for v in self._var_list) 

# 需要导入模块: from tensorflow.python.ops import variables [as 别名]
# 或者: from tensorflow.python.ops.variables import report_uninitialized_variables [as 别名]
def finalize(self):
    """Creates operations if needed and finalizes the graph."""
    if self._init_op is None:
      def default_init_op():
        return control_flow_ops.group(
            variables.global_variables_initializer(),
            resources.initialize_resources(resources.shared_resources()))
      self._init_op = Scaffold.get_or_default(
          'init_op',
          ops.GraphKeys.INIT_OP,
          default_init_op)
    if self._ready_op is None:
      def default_ready_op():
        return array_ops.concat([
            variables.report_uninitialized_variables(),
            resources.report_uninitialized_resources()
        ], 0)
      self._ready_op = Scaffold.get_or_default(
          'ready_op', ops.GraphKeys.READY_OP,
          default_ready_op)
    if self._ready_for_local_init_op is None:
      def default_ready_for_local_init_op():
        return variables.report_uninitialized_variables(
            variables.global_variables())
      self._ready_for_local_init_op = Scaffold.get_or_default(
          'ready_for_local_init_op', ops.GraphKeys.READY_FOR_LOCAL_INIT_OP,
          default_ready_for_local_init_op)
    if self._local_init_op is None:
      self._local_init_op = Scaffold.get_or_default(
          'local_init_op', ops.GraphKeys.LOCAL_INIT_OP,
          Scaffold._default_local_init_op)
    if self._summary_op is None:
      self._summary_op = Scaffold.get_or_default('summary_op',
                                                 ops.GraphKeys.SUMMARY_OP,
                                                 summary.merge_all)
    # pylint: disable=g-long-lambda
    if self._saver is None:
      self._saver = training_saver._get_saver_or_default()  # pylint: disable=protected-access
    # pylint: enable=g-long-lambda
    self._saver.build()

    ops.get_default_graph().finalize()
    return self 

# 需要导入模块: from tensorflow.python.ops import variables [as 别名]
# 或者: from tensorflow.python.ops.variables import report_uninitialized_variables [as 别名]
def finalize(self):
    """Creates operations if needed and finalizes the graph."""
    if self._init_op is None:
      def default_init_op():
        return control_flow_ops.group(
            variables.global_variables_initializer(),
            resources.initialize_resources(resources.shared_resources()))
      self._init_op = Scaffold.get_or_default(
          'init_op',
          ops.GraphKeys.INIT_OP,
          default_init_op)
    if self._ready_op is None:
      def default_ready_op():
        return array_ops.concat([
            variables.report_uninitialized_variables(),
            resources.report_uninitialized_resources()
        ], 0)
      self._ready_op = Scaffold.get_or_default(
          'ready_op', ops.GraphKeys.READY_OP,
          default_ready_op)
    if self._ready_for_local_init_op is None:
      def default_ready_for_local_init_op():
        return variables.report_uninitialized_variables(
            variables.global_variables())
      self._ready_for_local_init_op = Scaffold.get_or_default(
          'ready_for_local_init_op', ops.GraphKeys.READY_FOR_LOCAL_INIT_OP,
          default_ready_for_local_init_op)
    if self._local_init_op is None:
      self._local_init_op = Scaffold.get_or_default(
          'local_init_op', ops.GraphKeys.LOCAL_INIT_OP,
          Scaffold._default_local_init_op)
    if self._summary_op is None:
      self._summary_op = Scaffold.get_or_default('summary_op',
                                                 ops.GraphKeys.SUMMARY_OP,
                                                 summary.merge_all)
    # pylint: disable=g-long-lambda
    if self._saver is None:
      self._saver = Scaffold.get_or_default(
          'saver',
          ops.GraphKeys.SAVERS,
          lambda: training_saver.Saver(sharded=True, allow_empty=True,
                                       write_version=saver_pb2.SaverDef.V2))
    # pylint: enable=g-long-lambda
    self._saver.build()

    ops.get_default_graph().finalize()
    return self