ConfigProto.ExperimentalOrBuilder

パブリック静的インターフェイスConfigProto.ExperimentalOrBuilder
既知の間接サブクラス

パブリックメソッド

抽象ブール値
getCollectiveDeterministicSequentialExecution ()
 If true, make collective op execution order sequential and deterministic
 for potentially concurrent collective instances.
抽象文字列
getCollectiveGroupLeader ()
 Task name for group resolution.
抽象的な com.google.protobuf.ByteString
getCollectiveGroupLeaderBytes ()
 Task name for group resolution.
抽象ブール値
getCollectiveNccl ()
 If true, use NCCL for CollectiveOps.
抽象ブール値
getDisableOutputPartitionGraphs ()
 If true, the session will not store an additional copy of the graph for
 each subgraph.
抽象ブール値
getDisableThreadSpinning ()
 If using a direct session, disable spinning while waiting for work in
 the thread pool.
抽象ブール値
getEnableMlirBridge ()
 This field will eventually be deprecated and replaced by
 mlir_bridge_rollout (b/166038521).
抽象ブール値
getEnableMlirGraphOptimization ()
 Whether to enable the MLIR-based Graph optimizations.
抽象文字列
getExecutorType ()
 Which executor to use, the default executor will be used
 if it is an empty string or "DEFAULT"
 
string executor_type = 3;
抽象的な com.google.protobuf.ByteString
getExecutorTypeBytes ()
 Which executor to use, the default executor will be used
 if it is an empty string or "DEFAULT"
 
string executor_type = 3;
抽象的なConfigProto.Experimental.MlirBridgeRollout
getMlirBridgeRollout ()
 This field is underdevelopment, for now use enable_mlir_bridge
 (b/166038521).
抽象整数
getMlirBridgeRolloutValue ()
 This field is underdevelopment, for now use enable_mlir_bridge
 (b/166038521).
抽象ブール値
getOptimizeForStaticGraph ()
 If true, the session may treat the graph as being static for optimization
 purposes.
抽象整数
getRecvBufMaxChunk ()
 Guidance to formatting of large RecvBuf fields for transfer.
抽象的なセッションメタデータ
getSessionMetadata ()
 Metadata about the session.
抽象的なSessionMetadataOrBuilder
getSessionMetadataOrBuilder ()
 Metadata about the session.
抽象ブール値
getShareClusterDevicesInSession ()
 This was promoted to a non-experimental API.
抽象ブール値
getShareSessionStateInClusterspecPropagation ()
 In the following, session state means the value of a variable, elements
 in a hash table, or any other resource, accessible by worker sessions
 held by a TF server.
抽象ブール値
getUseNumaAffinity ()
 If true, and supported by the platform, the runtime will attempt to
 use NUMA affinity where applicable.
抽象的な長い
getXlaFusionAutotunerThresh ()
 Minimum number of batches run through the XLA graph before XLA fusion
 autotuner is enabled.
抽象ブール値
hasSessionMetadata ()
 Metadata about the session.

パブリックメソッド

public abstract boolean getCollectiveDeterministicSequentialExecution ()

 If true, make collective op execution order sequential and deterministic
 for potentially concurrent collective instances.
 
bool collective_deterministic_sequential_execution = 6;

public abstract String getCollectiveGroupLeader ()

 Task name for group resolution.
 
string collective_group_leader = 1;

パブリック抽象 com.google.protobuf.ByteString getCollectiveGroupLeaderBytes ()

 Task name for group resolution.
 
string collective_group_leader = 1;

パブリック抽象ブール値getCollectiveNccl ()

 If true, use NCCL for CollectiveOps.  This feature is highly
 experimental.
 
bool collective_nccl = 7;

public abstract boolean getDisableOutputPartitionGraphs ()

 If true, the session will not store an additional copy of the graph for
 each subgraph.
 If this option is set to true when a session is created, the
 `RunOptions.output_partition_graphs` options must not be set.
 
bool disable_output_partition_graphs = 14;

public abstract boolean getDisableThreadSpinning ()

 If using a direct session, disable spinning while waiting for work in
 the thread pool. This may result in higher latency for completing ops,
 but in the case where there is a lot of spinning may result in lower
 CPU usage.
 
bool disable_thread_spinning = 9;

パブリック抽象ブール値getEnableMlirBridge ()

 This field will eventually be deprecated and replaced by
 mlir_bridge_rollout (b/166038521).
 Whether to enable the MLIR-based TF->XLA bridge.
 This is a replacement to the existing bridge, and not ready for
 production usage yet.
 If this option is set to true when a session is created, MLIR is used to
 perform the set of graph transformations to put the graph in a form that
 can be executed with delegation of some computations to an accelerator.
 This builds on the model of XLA where a subset of the graph is
 encapsulated and attached to a "compile" operation, whose result is fed
 to an "execute" operation. The kernel for these operations is responsible
 to lower the encapsulated graph to a particular device.
 
bool enable_mlir_bridge = 13;

public abstract boolean getEnableMlirGraphOptimization ()

 Whether to enable the MLIR-based Graph optimizations.
 This will become a part of standard Tensorflow graph optimization
 pipeline, currently this is only used for gradual migration and testing
 new passes that are replacing existing optimizations in Grappler.
 
bool enable_mlir_graph_optimization = 16;

パブリック抽象 String getExecutorType ()

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

パブリック抽象 com.google.protobuf.ByteString getExecutorTypeBytes ()

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

パブリック抽象ConfigProto.Experimental.MlirBridgeRollout getMlirBridgeRollout ()

 This field is underdevelopment, for now use enable_mlir_bridge
 (b/166038521).
 Whether to enable the MLIR-based TF->XLA bridge.
 
.tensorflow.ConfigProto.Experimental.MlirBridgeRollout mlir_bridge_rollout = 17;

public abstract int getMlirBridgeRolloutValue ()

 This field is underdevelopment, for now use enable_mlir_bridge
 (b/166038521).
 Whether to enable the MLIR-based TF->XLA bridge.
 
.tensorflow.ConfigProto.Experimental.MlirBridgeRollout mlir_bridge_rollout = 17;

public abstract boolean getOptimizeForStaticGraph ()

 If true, the session may treat the graph as being static for optimization
 purposes.
 If this option is set to true when a session is created, the full
 GraphDef must be passed in a single call to Session::Create(), and
 Session::Extend() may not be supported.
 
bool optimize_for_static_graph = 12;

public abstract int getRecvBufMaxChunk ()

 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;

パブリック抽象セッションメタデータgetSessionMetadata ()

 Metadata about the session.
 If set, this can be used by the runtime and the Ops for debugging,
 monitoring, etc.
 NOTE: This is currently used and propagated only by the direct session.
 
.tensorflow.SessionMetadata session_metadata = 11;

パブリック抽象SessionMetadataOrBuilder getSessionMetadataOrBuilder ()

 Metadata about the session.
 If set, this can be used by the runtime and the Ops for debugging,
 monitoring, etc.
 NOTE: This is currently used and propagated only by the direct session.
 
.tensorflow.SessionMetadata session_metadata = 11;

public abstract boolean getShareClusterDevicesInSession ()

 This was promoted to a non-experimental API. Please use
 ConfigProto.share_cluster_devices_in_session instead.
 
bool share_cluster_devices_in_session = 10;

public abstract boolean getShareSessionStateInClusterspecPropagation ()

 In the following, session state means the value of a variable, elements
 in a hash table, or any other resource, accessible by worker sessions
 held by a TF server.
 When ClusterSpec propagation is enabled, the value of
 isolate_session_state is ignored when deciding whether to share session
 states in a TF server (for backwards compatibility reasons).
 - If share_session_state_in_clusterspec_propagation is true, the session
 states are shared.
 - If share_session_state_in_clusterspec_propagation is false, session
 states are isolated.
 When clusterspec propagation is not used, the value of
 share_session_state_in_clusterspec_propagation is ignored when deciding
 whether to share session states in a TF server.
 - If isolate_session_state is true, session states are isolated.
 - If isolate_session_state is false, session states are shared.
 TODO(b/129330037): Add a single API that consistently treats
 isolate_session_state and ClusterSpec propagation.
 
bool share_session_state_in_clusterspec_propagation = 8;

public abstract boolean getUseNumaAffinity ()

 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;

パブリック抽象ロングgetXlaFusionAutotunerThresh ()

 Minimum number of batches run through the XLA graph before XLA fusion
 autotuner is enabled. Default value of zero disables the autotuner.
 The XLA fusion autotuner can improve performance by executing a heuristic
 search on the compiler parameters.
 
int64 xla_fusion_autotuner_thresh = 15;

public abstract boolean hasSessionMetadata ()

 Metadata about the session.
 If set, this can be used by the runtime and the Ops for debugging,
 monitoring, etc.
 NOTE: This is currently used and propagated only by the direct session.
 
.tensorflow.SessionMetadata session_metadata = 11;

パブリック静的インターフェイスConfigProto.ExperimentalOrBuilder
既知の間接サブクラス

パブリックメソッド

抽象ブール値
getCollectiveDeterministicSequentialExecution ()
 If true, make collective op execution order sequential and deterministic
 for potentially concurrent collective instances.
抽象文字列
getCollectiveGroupLeader ()
 Task name for group resolution.
抽象的な com.google.protobuf.ByteString
getCollectiveGroupLeaderBytes ()
 Task name for group resolution.
抽象ブール値
getCollectiveNccl ()
 If true, use NCCL for CollectiveOps.
抽象ブール値
getDisableOutputPartitionGraphs ()
 If true, the session will not store an additional copy of the graph for
 each subgraph.
抽象ブール値
getDisableThreadSpinning ()
 If using a direct session, disable spinning while waiting for work in
 the thread pool.
抽象ブール値
getEnableMlirBridge ()
 This field will eventually be deprecated and replaced by
 mlir_bridge_rollout (b/166038521).
抽象ブール値
getEnableMlirGraphOptimization ()
 Whether to enable the MLIR-based Graph optimizations.
抽象文字列
getExecutorType ()
 Which executor to use, the default executor will be used
 if it is an empty string or "DEFAULT"
 
string executor_type = 3;
抽象的な com.google.protobuf.ByteString
getExecutorTypeBytes ()
 Which executor to use, the default executor will be used
 if it is an empty string or "DEFAULT"
 
string executor_type = 3;
抽象的なConfigProto.Experimental.MlirBridgeRollout
getMlirBridgeRollout ()
 This field is underdevelopment, for now use enable_mlir_bridge
 (b/166038521).
抽象整数
getMlirBridgeRolloutValue ()
 This field is underdevelopment, for now use enable_mlir_bridge
 (b/166038521).
抽象ブール値
getOptimizeForStaticGraph ()
 If true, the session may treat the graph as being static for optimization
 purposes.
抽象整数
getRecvBufMaxChunk ()
 Guidance to formatting of large RecvBuf fields for transfer.
抽象的なセッションメタデータ
getSessionMetadata ()
 Metadata about the session.
抽象的なSessionMetadataOrBuilder
getSessionMetadataOrBuilder ()
 Metadata about the session.
抽象ブール値
getShareClusterDevicesInSession ()
 This was promoted to a non-experimental API.
抽象ブール値
getShareSessionStateInClusterspecPropagation ()
 In the following, session state means the value of a variable, elements
 in a hash table, or any other resource, accessible by worker sessions
 held by a TF server.
抽象ブール値
getUseNumaAffinity ()
 If true, and supported by the platform, the runtime will attempt to
 use NUMA affinity where applicable.
抽象的な長い
getXlaFusionAutotunerThresh ()
 Minimum number of batches run through the XLA graph before XLA fusion
 autotuner is enabled.
抽象ブール値
hasSessionMetadata ()
 Metadata about the session.

パブリックメソッド

public abstract boolean getCollectiveDeterministicSequentialExecution ()

 If true, make collective op execution order sequential and deterministic
 for potentially concurrent collective instances.
 
bool collective_deterministic_sequential_execution = 6;

public abstract String getCollectiveGroupLeader ()

 Task name for group resolution.
 
string collective_group_leader = 1;

パブリック抽象 com.google.protobuf.ByteString getCollectiveGroupLeaderBytes ()

 Task name for group resolution.
 
string collective_group_leader = 1;

パブリック抽象ブール値getCollectiveNccl ()

 If true, use NCCL for CollectiveOps.  This feature is highly
 experimental.
 
bool collective_nccl = 7;

public abstract boolean getDisableOutputPartitionGraphs ()

 If true, the session will not store an additional copy of the graph for
 each subgraph.
 If this option is set to true when a session is created, the
 `RunOptions.output_partition_graphs` options must not be set.
 
bool disable_output_partition_graphs = 14;

public abstract boolean getDisableThreadSpinning ()

 If using a direct session, disable spinning while waiting for work in
 the thread pool. This may result in higher latency for completing ops,
 but in the case where there is a lot of spinning may result in lower
 CPU usage.
 
bool disable_thread_spinning = 9;

パブリック抽象ブール値getEnableMlirBridge ()

 This field will eventually be deprecated and replaced by
 mlir_bridge_rollout (b/166038521).
 Whether to enable the MLIR-based TF->XLA bridge.
 This is a replacement to the existing bridge, and not ready for
 production usage yet.
 If this option is set to true when a session is created, MLIR is used to
 perform the set of graph transformations to put the graph in a form that
 can be executed with delegation of some computations to an accelerator.
 This builds on the model of XLA where a subset of the graph is
 encapsulated and attached to a "compile" operation, whose result is fed
 to an "execute" operation. The kernel for these operations is responsible
 to lower the encapsulated graph to a particular device.
 
bool enable_mlir_bridge = 13;

public abstract boolean getEnableMlirGraphOptimization ()

 Whether to enable the MLIR-based Graph optimizations.
 This will become a part of standard Tensorflow graph optimization
 pipeline, currently this is only used for gradual migration and testing
 new passes that are replacing existing optimizations in Grappler.
 
bool enable_mlir_graph_optimization = 16;

パブリック抽象 String getExecutorType ()

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

パブリック抽象 com.google.protobuf.ByteString getExecutorTypeBytes ()

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

パブリック抽象ConfigProto.Experimental.MlirBridgeRollout getMlirBridgeRollout ()

 This field is underdevelopment, for now use enable_mlir_bridge
 (b/166038521).
 Whether to enable the MLIR-based TF->XLA bridge.
 
.tensorflow.ConfigProto.Experimental.MlirBridgeRollout mlir_bridge_rollout = 17;

public abstract int getMlirBridgeRolloutValue ()

 This field is underdevelopment, for now use enable_mlir_bridge
 (b/166038521).
 Whether to enable the MLIR-based TF->XLA bridge.
 
.tensorflow.ConfigProto.Experimental.MlirBridgeRollout mlir_bridge_rollout = 17;

public abstract boolean getOptimizeForStaticGraph ()

 If true, the session may treat the graph as being static for optimization
 purposes.
 If this option is set to true when a session is created, the full
 GraphDef must be passed in a single call to Session::Create(), and
 Session::Extend() may not be supported.
 
bool optimize_for_static_graph = 12;

public abstract int getRecvBufMaxChunk ()

 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;

パブリック抽象セッションメタデータgetSessionMetadata ()

 Metadata about the session.
 If set, this can be used by the runtime and the Ops for debugging,
 monitoring, etc.
 NOTE: This is currently used and propagated only by the direct session.
 
.tensorflow.SessionMetadata session_metadata = 11;

パブリック抽象SessionMetadataOrBuilder getSessionMetadataOrBuilder ()

 Metadata about the session.
 If set, this can be used by the runtime and the Ops for debugging,
 monitoring, etc.
 NOTE: This is currently used and propagated only by the direct session.
 
.tensorflow.SessionMetadata session_metadata = 11;

public abstract boolean getShareClusterDevicesInSession ()

 This was promoted to a non-experimental API. Please use
 ConfigProto.share_cluster_devices_in_session instead.
 
bool share_cluster_devices_in_session = 10;

public abstract boolean getShareSessionStateInClusterspecPropagation ()

 In the following, session state means the value of a variable, elements
 in a hash table, or any other resource, accessible by worker sessions
 held by a TF server.
 When ClusterSpec propagation is enabled, the value of
 isolate_session_state is ignored when deciding whether to share session
 states in a TF server (for backwards compatibility reasons).
 - If share_session_state_in_clusterspec_propagation is true, the session
 states are shared.
 - If share_session_state_in_clusterspec_propagation is false, session
 states are isolated.
 When clusterspec propagation is not used, the value of
 share_session_state_in_clusterspec_propagation is ignored when deciding
 whether to share session states in a TF server.
 - If isolate_session_state is true, session states are isolated.
 - If isolate_session_state is false, session states are shared.
 TODO(b/129330037): Add a single API that consistently treats
 isolate_session_state and ClusterSpec propagation.
 
bool share_session_state_in_clusterspec_propagation = 8;

public abstract boolean getUseNumaAffinity ()

 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;

パブリック抽象ロングgetXlaFusionAutotunerThresh ()

 Minimum number of batches run through the XLA graph before XLA fusion
 autotuner is enabled. Default value of zero disables the autotuner.
 The XLA fusion autotuner can improve performance by executing a heuristic
 search on the compiler parameters.
 
int64 xla_fusion_autotuner_thresh = 15;

public abstract boolean hasSessionMetadata ()

 Metadata about the session.
 If set, this can be used by the runtime and the Ops for debugging,
 monitoring, etc.
 NOTE: This is currently used and propagated only by the direct session.
 
.tensorflow.SessionMetadata session_metadata = 11;