общедоступный интерфейс RunMetadataOrBuilder
| Известные косвенные подклассы |
Публичные методы
| абстрактный CostGraphDef | getCostGraph () The cost graph for the computation defined by the run call. |
| абстрактный CostGraphDefOrBuilder | getCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| абстрактный RunMetadata.FunctionGraphs | getFunctionGraphs (индекс целого числа) This is only populated for graphs that are run as functions in TensorFlow V2. |
| абстрактный int | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| абстрактный список < RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| абстрактный RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (индекс int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| абстрактный список<? расширяет RunMetadata.FunctionGraphsOrBuilder > | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| абстрактный GraphDef | getPartitionGraphs (индекс int) Graphs of the partitions executed by executors. |
| абстрактный int | getPartitionGraphsCount () Graphs of the partitions executed by executors. |
| абстрактный список < GraphDef > | getPartitionGraphsList () Graphs of the partitions executed by executors. |
| абстрактный GraphDefOrBuilder | getPartitionGraphsOrBuilder (индекс int) Graphs of the partitions executed by executors. |
| абстрактный список<? расширяет GraphDefOrBuilder > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| абстрактная статистика StepStats | getStepStats () Statistics traced for this step. |
| абстрактный StepStatsOrBuilder | getStepStatsOrBuilder () Statistics traced for this step. |
| абстрактное логическое значение | имеетCostGraph () The cost graph for the computation defined by the run call. |
| абстрактное логическое значение | имеетСтепстатс () Statistics traced for this step. |
Публичные методы
публичный абстрактный CostGraphDef getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; публичный абстрактный CostGraphDefOrBuilder getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; публичный абстрактный RunMetadata.FunctionGraphs getFunctionGraphs (индекс 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; публичный абстрактный 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; общедоступный абстрактный список < 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; публичный абстрактный RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (индекс 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; публичный абстрактный список<? расширяет 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; общедоступный абстрактный GraphDef getPartitionGraphs (индекс int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; общедоступный абстрактный int getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; общедоступный абстрактный список < GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; общедоступный абстрактный GraphDefOrBuilder getPartitionGraphsOrBuilder (индекс int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; публичный абстрактный список<? расширяет GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; публичный абстрактный 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; общедоступный абстрактный 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; общедоступное абстрактное логическое значение hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; общедоступное абстрактное логическое значение 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;