interfaccia pubblica RunMetadataOrBuilder
| Sottoclassi indirette conosciute |
Metodi pubblici
| abstract CostGraphDef | getGraficoCosti () The cost graph for the computation defined by the run call. |
| abstract CostGraphDefOrBuilder | getCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| estratto RunMetadata.FunctionGraphs | getFunctionGraphs (indice int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| astratto int | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| Elenco astratto< RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| astratto RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (indice int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Elenco astratto<? estende RunMetadata.FunctionGraphsOrBuilder > | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| astratto GraphDef | getPartitionGraphs (indice int) Graphs of the partitions executed by executors. |
| astratto int | getPartitionGraphsCount () Graphs of the partitions executed by executors. |
| Lista astratta <GraphDef> | getPartitionGraphsList () Graphs of the partitions executed by executors. |
| astratto GraphDefOrBuilder | getPartitionGraphsOrBuilder (indice int) Graphs of the partitions executed by executors. |
| Elenco astratto<? estende GraphDefOrBuilder > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| StepStats astratte | getStepStats () Statistics traced for this step. |
| astratto StepStatsOrBuilder | getStepStatsOrBuilder () Statistics traced for this step. |
| booleano astratto | hasCostGraph () The cost graph for the computation defined by the run call. |
| booleano astratto | hasStepStats () Statistics traced for this step. |
Metodi pubblici
abstract pubblico CostGraphDef getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public abstract CostGraphDefOrBuilder getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public abstract RunMetadata.FunctionGraphs getFunctionGraphs (indice 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 abstract 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; elenco astratto pubblico < 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 abstract RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (indice 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; Elenco abstract pubblico<? estende 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 abstract GraphDef getPartitionGraphs (indice int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public abstract int getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; Elenco astratto pubblico < GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public abstract GraphDefOrBuilder getPartitionGraphsOrBuilder (indice int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; Elenco abstract pubblico<? estende GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; abstract pubblico 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; estratto pubblico 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; pubblico astratto booleano hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public abstract booleano 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;