classe finale statique publique RunMetadata.Builder
Metadata output (i.e., non-Tensor) for a single Run() call.
tensorflow.RunMetadata Méthodes publiques
| RunMetadata.Builder | addAllFunctionGraphs (Iterable<? étend RunMetadata.FunctionGraphs > valeurs) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | addAllPartitionGraphs (Iterable<? étend GraphDef > valeurs) Graphs of the partitions executed by executors. |
| RunMetadata.Builder | addFunctionGraphs (index int, valeur RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | addFunctionGraphs (index int, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | addFunctionGraphs (valeur RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | addFunctionGraphs ( RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | addFunctionGraphsBuilder (index int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | addFunctionGraphsBuilder () This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | |
| RunMetadata.Builder | addPartitionGraphs ( GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| RunMetadata.Builder | |
| RunMetadata.Builder | addPartitionGraphs (index int, GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| GraphDef.Builder | addPartitionGraphsBuilder (index int) Graphs of the partitions executed by executors. |
| GraphDef.Builder | addPartitionGraphsBuilder () Graphs of the partitions executed by executors. |
| RunMetadata.Builder | addRepeatedField (champ com.google.protobuf.Descriptors.FieldDescriptor, valeur de l'objet) |
| Exécuter les métadonnées | construire () |
| Exécuter les métadonnées | buildPartial () |
| RunMetadata.Builder | clair () |
| RunMetadata.Builder | clearCostGraph () The cost graph for the computation defined by the run call. |
| RunMetadata.Builder | clearField (champ com.google.protobuf.Descriptors.FieldDescriptor) |
| RunMetadata.Builder | clearFunctionGraphs () This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof) |
| RunMetadata.Builder | clearPartitionGraphs () Graphs of the partitions executed by executors. |
| RunMetadata.Builder | clearStepStats () Statistics traced for this step. |
| RunMetadata.Builder | cloner () |
| CoûtGraphDef | getCostGraph () The cost graph for the computation defined by the run call. |
| CostGraphDef.Builder | getCostGraphBuilder () The cost graph for the computation defined by the run call. |
| CostGraphDefOrBuilder | getCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| Exécuter les métadonnées | |
| final statique com.google.protobuf.Descriptors.Descriptor | |
| com.google.protobuf.Descriptors.Descriptor | |
| RunMetadata.FunctionGraphs | getFunctionGraphs (index int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | getFunctionGraphsBuilder (index int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Liste < RunMetadata.FunctionGraphs.Builder > | getFunctionGraphsBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| int | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| Liste < RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (index int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Liste<? étend RunMetadata.FunctionGraphsOrBuilder > | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| GraphDef | getPartitionGraphs (index int) Graphs of the partitions executed by executors. |
| GraphDef.Builder | getPartitionGraphsBuilder (index int) Graphs of the partitions executed by executors. |
| Liste< GraphDef.Builder > | getPartitionGraphsBuilderList () Graphs of the partitions executed by executors. |
| int | getPartitionGraphsCount () Graphs of the partitions executed by executors. |
| Liste< GraphDef > | getPartitionGraphsList () Graphs of the partitions executed by executors. |
| GraphDefOrBuilder | getPartitionGraphsOrBuilder (index int) Graphs of the partitions executed by executors. |
| Liste<? étend GraphDefOrBuilder > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| Statistiques sur les étapes | getStepStats () Statistics traced for this step. |
| StepStats.Builder | getStepStatsBuilder () Statistics traced for this step. |
| StepStatsOrBuilder | getStepStatsOrBuilder () Statistics traced for this step. |
| booléen | hasCostGraph () The cost graph for the computation defined by the run call. |
| booléen | hasStepStats () Statistics traced for this step. |
| booléen final | |
| RunMetadata.Builder | |
| RunMetadata.Builder | mergeFrom (com.google.protobuf.Message autre) |
| RunMetadata.Builder | mergeFrom (entrée com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
| RunMetadata.Builder | |
| RunMetadata.Builder final | mergeUnknownFields (com.google.protobuf.UnknownFieldSet inconnuFields) |
| RunMetadata.Builder | supprimerFunctionGraphs (index int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | supprimerPartitionGraphs (index int) Graphs of the partitions executed by executors. |
| RunMetadata.Builder | |
| RunMetadata.Builder | setCostGraph ( CostGraphDef.Builder builderForValue) The cost graph for the computation defined by the run call. |
| RunMetadata.Builder | setField (champ com.google.protobuf.Descriptors.FieldDescriptor, valeur de l'objet) |
| RunMetadata.Builder | setFunctionGraphs (index int, valeur RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | setFunctionGraphs (index int, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | setPartitionGraphs (index int, GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| RunMetadata.Builder | |
| RunMetadata.Builder | setRepeatedField (champ com.google.protobuf.Descriptors.FieldDescriptor, index int, valeur de l'objet) |
| RunMetadata.Builder | |
| RunMetadata.Builder | |
| RunMetadata.Builder final | setUnknownFields (com.google.protobuf.UnknownFieldSet inconnuFields) |
Méthodes héritées
Méthodes publiques
public RunMetadata.Builder addAllFunctionGraphs (Iterable<? étend RunMetadata.FunctionGraphs > valeurs)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.Builder addAllPartitionGraphs (Iterable <? étend GraphDef > valeurs)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder addFunctionGraphs (index int, valeur RunMetadata.FunctionGraphs )
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.Builder addFunctionGraphs (index int, RunMetadata.FunctionGraphs.Builder builderForValue)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.Builder addFunctionGraphs (valeur RunMetadata.FunctionGraphs )
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.Builder addFunctionGraphs ( RunMetadata.FunctionGraphs.Builder builderForValue)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.FunctionGraphs.Builder addFunctionGraphsBuilder (index int)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.FunctionGraphs.Builder addFunctionGraphsBuilder ()
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.Builder addPartitionGraphs (index int, valeur GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;public RunMetadata.Builder addPartitionGraphs ( GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder addPartitionGraphs (valeur GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder addPartitionGraphs (index int, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public GraphDef.Builder addPartitionGraphsBuilder (index int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public GraphDef.Builder addPartitionGraphsBuilder ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder addRepeatedField (champ com.google.protobuf.Descriptors.FieldDescriptor, valeur de l'objet)
public RunMetadata.Builder clearCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public RunMetadata.Builder clearFunctionGraphs ()
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.Builder clearPartitionGraphs ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder clearStepStats ()
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; public CostGraphDef getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public CostGraphDef.Builder getCostGraphBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public CostGraphDefOrBuilder getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public statique final com.google.protobuf.Descriptors.Descriptor getDescriptor ()
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()
public RunMetadata.FunctionGraphs getFunctionGraphs (index int)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.FunctionGraphs.Builder getFunctionGraphsBuilder (index int)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; liste publique < RunMetadata.FunctionGraphs.Builder > getFunctionGraphsBuilderList ()
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public int getFunctionGraphsCount ()
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; liste publique < RunMetadata.FunctionGraphs > getFunctionGraphsList ()
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (index int)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; Liste publique <? étend RunMetadata.FunctionGraphsOrBuilder > getFunctionGraphsOrBuilderList ()
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public GraphDef getPartitionGraphs (index int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public GraphDef.Builder getPartitionGraphsBuilder (index int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; Liste publique < GraphDef.Builder > getPartitionGraphsBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public int getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; liste publique < GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public GraphDefOrBuilder getPartitionGraphsOrBuilder (index int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; Liste publique <? étend GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; StepStats publics getStepStats ()
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; public StepStats.Builder getStepStatsBuilder ()
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; public StepStatsOrBuilder getStepStatsOrBuilder ()
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; public booléen hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public booléen hasStepStats ()
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; public final booléen isInitialized ()
public RunMetadata.Builder mergeCostGraph (valeur CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public RunMetadata.Builder mergeFrom (entrée com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Jetés
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public RunMetadata.Builder mergeStepStats (valeur StepStats )
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; public final RunMetadata.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)
public RunMetadata.Builder removeFunctionGraphs (index int)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.Builder removePartitionGraphs (index int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder setCostGraph (valeur CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public RunMetadata.Builder setCostGraph ( CostGraphDef.Builder builderForValue)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public RunMetadata.Builder setField (champ com.google.protobuf.Descriptors.FieldDescriptor, valeur de l'objet)
public RunMetadata.Builder setFunctionGraphs (index int, valeur RunMetadata.FunctionGraphs )
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.Builder setFunctionGraphs (index int, RunMetadata.FunctionGraphs.Builder builderForValue)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; public RunMetadata.Builder setPartitionGraphs (index int, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder setPartitionGraphs (index int, valeur GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder setRepeatedField (champ com.google.protobuf.Descriptors.FieldDescriptor, index int, valeur de l'objet)
public RunMetadata.Builder setStepStats ( StepStats.Builder builderForValue)
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; public RunMetadata.Builder setStepStats (valeur StepStats )
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1;