tensorflow源码解析之ConfigProto

message ConfigProto {
  // Map from device type name (e.g., "CPU" or "GPU" ) to maximum
  // number of devices of that type to use.  If a particular device
  // type is not found in the map, the system picks an appropriate
  // number.
  map<string, int32> device_count = 1;

  // The execution of an individual op (for some op types) can be
  // parallelized on a pool of intra_op_parallelism_threads.
  // 0 means the system picks an appropriate number.
  int32 intra_op_parallelism_threads = 2;

  // Nodes that perform blocking operations are enqueued on a pool of
  // inter_op_parallelism_threads available in each process.
  //
  // 0 means the system picks an appropriate number.
  //
  // Note that the first Session created in the process sets the
  // number of threads for all future sessions unless use_per_session_threads is
  // true or session_inter_op_thread_pool is configured.
  int32 inter_op_parallelism_threads = 5;

  // If true, use a new set of threads for this session rather than the global
  // pool of threads. Only supported by direct sessions.
  //
  // If false, use the global threads created by the first session, or the
  // per-session thread pools configured by session_inter_op_thread_pool.
  //
  // This option is deprecated. The same effect can be achieved by setting
  // session_inter_op_thread_pool to have one element, whose num_threads equals
  // inter_op_parallelism_threads.
  bool use_per_session_threads = 9;

  // This option is experimental - it may be replaced with a different mechanism
  // in the future.
  //
  // Configures session thread pools. If this is configured, then RunOptions for
  // a Run call can select the thread pool to use.
  //
  // The intended use is for when some session invocations need to run in a
  // background pool limited to a small number of threads:
  // - For example, a session may be configured to have one large pool (for
  // regular compute) and one small pool (for periodic, low priority work);
  // using the small pool is currently the mechanism for limiting the inter-op
  // parallelism of the low priority work.  Note that it does not limit the
  // parallelism of work spawned by a single op kernel implementation.
  // - Using this setting is normally not needed in training, but may help some
  // serving use cases.
  // - It is also generally recommended to set the global_name field of this
  // proto, to avoid creating multiple large pools. It is typically better to
  // run the non-low-priority work, even across sessions, in a single large
  // pool.
  repeated ThreadPoolOptionProto session_inter_op_thread_pool = 12;

  // Assignment of Nodes to Devices is recomputed every placement_period
  // steps until the system warms up (at which point the recomputation
  // typically slows down automatically).
  int32 placement_period = 3;

  // When any filters are present sessions will ignore all devices which do not
  // match the filters. Each filter can be partially specified, e.g. "/job:ps"
  // "/job:worker/replica:3", etc.
  repeated string device_filters = 4;

  // Options that apply to all GPUs.
  GPUOptions gpu_options = 6;

  // Whether soft placement is allowed. If allow_soft_placement is true,
  // an op will be placed on CPU if
  //   1. there's no GPU implementation for the OP
  // or
  //   2. no GPU devices are known or registered
  // or
  //   3. need to co-locate with reftype input(s) which are from CPU.
  bool allow_soft_placement = 7;

  // Whether device placements should be logged.
  bool log_device_placement = 8;

  // Options that apply to all graphs.
  GraphOptions graph_options = 10;

  // Global timeout for all blocking operations in this session.  If non-zero,
  // and not overridden on a per-operation basis, this value will be used as the
  // deadline for all blocking operations.
  int64 operation_timeout_in_ms = 11;

  // Options that apply when this session uses the distributed runtime.
  RPCOptions rpc_options = 13;

  // Optional list of all workers to use in this session.
  ClusterDef cluster_def = 14;

  // If true, any resources such as Variables used in the session will not be
  // shared with other sessions.
  bool isolate_session_state = 15;

  // Everything inside Experimental is subject to change and is not subject
  // to API stability guarantees in
  // https://www.tensorflow.org/guide/version_compat.
  message Experimental {
    // Task name for group resolution.
    string collective_group_leader = 1;

    // We removed the flag client_handles_error_formatting. Marking the tag
    // number as reserved.
    // TODO(shikharagarwal): Should we just remove this tag so that it can be
    // used in future for other purpose?
    reserved 2;

    // Which executor to use, the default executor will be used
    // if it is an empty string or "DEFAULT"
    string executor_type = 3;

    // Guidance to formatting of large RecvBuf fields for transfer.
    // Any positive value sets the max chunk size.  0 defaults to 4096.
    // Any negative value indicates no max, i.e. one chunk only.
    int32 recv_buf_max_chunk = 4;

    // If true, and supported by the platform, the runtime will attempt to
    // use NUMA affinity where applicable.  One consequence will be the
    // existence of as many CPU devices as there are available NUMA nodes.
    bool use_numa_affinity = 5;
  };

  Experimental experimental = 16;

  // Next: 17
};

 1. // The execution of an individual op (for some op types) can be
  // parallelized on a pool of intra_op_parallelism_threads.
  // 0 means the system picks an appropriate number.

===>每个op可以在多个threads上并行
  int32 intra_op_parallelism_threads = 2;