ConfigProtoOrBuilder

public interface ConfigProtoOrBuilder
Known Indirect Subclasses

Public Methods

abstract boolean
containsDeviceCount (String key)
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
abstract boolean
getAllowSoftPlacement ()
 Whether soft placement is allowed.
abstract ClusterDef
getClusterDef ()
 Optional list of all workers to use in this session.
abstract ClusterDefOrBuilder
getClusterDefOrBuilder ()
 Optional list of all workers to use in this session.
abstract Map<String, Integer>
abstract int
getDeviceCountCount ()
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
abstract Map<String, Integer>
getDeviceCountMap ()
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
abstract int
getDeviceCountOrDefault (String key, int defaultValue)
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
abstract int
getDeviceCountOrThrow (String key)
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
abstract String
getDeviceFilters (int index)
 When any filters are present sessions will ignore all devices which do not
 match the filters.
abstract com.google.protobuf.ByteString
getDeviceFiltersBytes (int index)
 When any filters are present sessions will ignore all devices which do not
 match the filters.
abstract int
getDeviceFiltersCount ()
 When any filters are present sessions will ignore all devices which do not
 match the filters.
abstract List<String>
getDeviceFiltersList ()
 When any filters are present sessions will ignore all devices which do not
 match the filters.
abstract ConfigProto.Experimental
getExperimental ()
.tensorflow.ConfigProto.Experimental experimental = 16;
abstract ConfigProto.ExperimentalOrBuilder
getExperimentalOrBuilder ()
.tensorflow.ConfigProto.Experimental experimental = 16;
abstract GPUOptions
getGpuOptions ()
 Options that apply to all GPUs.
abstract GPUOptionsOrBuilder
getGpuOptionsOrBuilder ()
 Options that apply to all GPUs.
abstract GraphOptions
getGraphOptions ()
 Options that apply to all graphs.
abstract GraphOptionsOrBuilder
getGraphOptionsOrBuilder ()
 Options that apply to all graphs.
abstract int
getInterOpParallelismThreads ()
 Nodes that perform blocking operations are enqueued on a pool of
 inter_op_parallelism_threads available in each process.
abstract int
getIntraOpParallelismThreads ()
 The execution of an individual op (for some op types) can be
 parallelized on a pool of intra_op_parallelism_threads.
abstract boolean
getIsolateSessionState ()
 If true, any resources such as Variables used in the session will not be
 shared with other sessions.
abstract boolean
getLogDevicePlacement ()
 Whether device placements should be logged.
abstract long
getOperationTimeoutInMs ()
 Global timeout for all blocking operations in this session.
abstract int
getPlacementPeriod ()
 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).
abstract RPCOptions
getRpcOptions ()
 Options that apply when this session uses the distributed runtime.
abstract RPCOptionsOrBuilder
getRpcOptionsOrBuilder ()
 Options that apply when this session uses the distributed runtime.
abstract ThreadPoolOptionProto
getSessionInterOpThreadPool (int index)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
abstract int
getSessionInterOpThreadPoolCount ()
 This option is experimental - it may be replaced with a different mechanism
 in the future.
abstract List< ThreadPoolOptionProto >
getSessionInterOpThreadPoolList ()
 This option is experimental - it may be replaced with a different mechanism
 in the future.
abstract ThreadPoolOptionProtoOrBuilder
getSessionInterOpThreadPoolOrBuilder (int index)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
abstract List<? extends ThreadPoolOptionProtoOrBuilder >
getSessionInterOpThreadPoolOrBuilderList ()
 This option is experimental - it may be replaced with a different mechanism
 in the future.
abstract boolean
getShareClusterDevicesInSession ()
 When true, WorkerSessions are created with device attributes from the
 full cluster.
abstract boolean
getUsePerSessionThreads ()
 If true, use a new set of threads for this session rather than the global
 pool of threads.
abstract boolean
hasClusterDef ()
 Optional list of all workers to use in this session.
abstract boolean
hasExperimental ()
.tensorflow.ConfigProto.Experimental experimental = 16;
abstract boolean
hasGpuOptions ()
 Options that apply to all GPUs.
abstract boolean
hasGraphOptions ()
 Options that apply to all graphs.
abstract boolean
hasRpcOptions ()
 Options that apply when this session uses the distributed runtime.

Public Methods

public abstract boolean containsDeviceCount (String key)

 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;

public abstract boolean getAllowSoftPlacement ()

 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;

public abstract ClusterDef getClusterDef ()

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

public abstract ClusterDefOrBuilder getClusterDefOrBuilder ()

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

public abstract Map<String, Integer> getDeviceCount ()

public abstract int getDeviceCountCount ()

 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;

public abstract Map<String, Integer> getDeviceCountMap ()

 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;

public abstract int getDeviceCountOrDefault (String key, int defaultValue)

 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;

public abstract int getDeviceCountOrThrow (String key)

 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;

public abstract String getDeviceFilters (int index)

 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;

public abstract com.google.protobuf.ByteString getDeviceFiltersBytes (int index)

 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;

public abstract int getDeviceFiltersCount ()

 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;

public abstract List<String> getDeviceFiltersList ()

 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;

public abstract ConfigProto.Experimental getExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

public abstract ConfigProto.ExperimentalOrBuilder getExperimentalOrBuilder ()

.tensorflow.ConfigProto.Experimental experimental = 16;

public abstract GPUOptions getGpuOptions ()

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

public abstract GPUOptionsOrBuilder getGpuOptionsOrBuilder ()

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

public abstract GraphOptions getGraphOptions ()

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

public abstract GraphOptionsOrBuilder getGraphOptionsOrBuilder ()

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

public abstract int getInterOpParallelismThreads ()

 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.
 Negative means all operations are performed in caller's thread.
 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;

public abstract int getIntraOpParallelismThreads ()

 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.
 If you create an ordinary session, e.g., from Python or C++,
 then there is exactly one intra op thread pool per process.
 The first session created determines the number of threads in this pool.
 All subsequent sessions reuse/share this one global pool.
 There are notable exceptions to the default behavior describe above:
 1. There is an environment variable  for overriding this thread pool,
    named TF_OVERRIDE_GLOBAL_THREADPOOL.
 2. When connecting to a server, such as a remote `tf.train.Server`
    instance, then this option will be ignored altogether.
 
int32 intra_op_parallelism_threads = 2;

public abstract boolean getIsolateSessionState ()

 If true, any resources such as Variables used in the session will not be
 shared with other sessions. However, when clusterspec propagation is
 enabled, this field is ignored and sessions are always isolated.
 
bool isolate_session_state = 15;

public abstract boolean getLogDevicePlacement ()

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

public abstract long getOperationTimeoutInMs ()

 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;

public abstract int getPlacementPeriod ()

 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;