interface publique RunMetadataOrBuilder
| Sous-classes indirectes connues |
Méthodes publiques
| résumé CostGraphDef | getCostGraph () The cost graph for the computation defined by the run call. |
| résumé CostGraphDefOrBuilder | getCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| résumé RunMetadata.FunctionGraphs | getFunctionGraphs (index int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| abstrait entier | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| Liste abstraite < RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| résumé RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (index int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Liste abstraite <? étend RunMetadata.FunctionGraphsOrBuilder > | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| résumé GraphDef | getPartitionGraphs (index int) Graphs of the partitions executed by executors. |
| abstrait entier | getPartitionGraphsCount () Graphs of the partitions executed by executors. |
| Liste abstraite< GraphDef > | getPartitionGraphsList () Graphs of the partitions executed by executors. |
| résumé GraphDefOrBuilder | getPartitionGraphsOrBuilder (index int) Graphs of the partitions executed by executors. |
| Liste abstraite <? étend GraphDefOrBuilder > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| Résumé StepStats | getStepStats () Statistics traced for this step. |
| résumé StepStatsOrBuilder | getStepStatsOrBuilder () Statistics traced for this step. |
| booléen abstrait | hasCostGraph () The cost graph for the computation defined by the run call. |
| booléen abstrait | hasStepStats () Statistics traced for this step. |
Méthodes publiques
résumé public CostGraphDef getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; résumé public CostGraphDefOrBuilder getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; résumé 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 abstrait 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 abstraite 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; résumé 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 des résumés publics<? 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; résumé public GraphDef getPartitionGraphs (index int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public abstrait int getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; Liste abstraite publique< GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; résumé public GraphDefOrBuilder getPartitionGraphsOrBuilder (index int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; Liste des résumés publics<? étend GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; résumé public StepStats 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; résumé 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 abstrait booléen hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public abstrait 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;