パブリック インターフェイスRunMetadataOrBuilder
| 既知の間接サブクラス |
パブリックメソッド
| 抽象コストグラフ定義 | getコストグラフ() The cost graph for the computation defined by the run call. |
| 抽象CostGraphDefOrBuilder | getCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| 抽象的なRunMetadata.FunctionGraphs | getFunctionGraphs (int インデックス) This is only populated for graphs that are run as functions in TensorFlow V2. |
| 抽象整数 | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| 抽象リスト< RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| 抽象RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (int インデックス) This is only populated for graphs that are run as functions in TensorFlow V2. |
| 抽象リスト<? RunMetadata.FunctionGraphsOrBuilderを拡張 > | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| 抽象的なグラフ定義 | getPartitionGraphs (int インデックス) Graphs of the partitions executed by executors. |
| 抽象整数 | getPartitionGraphsCount () Graphs of the partitions executed by executors. |
| 抽象 List< GraphDef > | getPartitionGraphsList () Graphs of the partitions executed by executors. |
| 抽象的なGraphDefOrBuilder | getPartitionGraphsOrBuilder (int インデックス) Graphs of the partitions executed by executors. |
| 抽象リスト<? GraphDefOrBuilderを拡張 > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| 抽象的なStepStats | getStepStats () Statistics traced for this step. |
| 抽象StepStatsOrBuilder | getStepStatsOrBuilder () Statistics traced for this step. |
| 抽象ブール値 | hasCostGraph () The cost graph for the computation defined by the run call. |
| 抽象ブール値 | hasStepStats () Statistics traced for this step. |
パブリックメソッド
パブリック抽象CostGraphDef getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; パブリック抽象CostGraphDefOrBuilder getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public abstract RunMetadata.FunctionGraphs getFunctionGraphs (int インデックス)
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; public abstract List< 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; パブリック抽象RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (int インデックス)
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; 公開抄録リスト<? extends 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; パブリック抽象GraphDef getPartitionGraphs (int インデックス)
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; public abstract List< GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; パブリック抽象GraphDefOrBuilder getPartitionGraphsOrBuilder (int インデックス)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; 公開抄録リスト<? extends GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; パブリック抽象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; パブリック抽象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 abstract boolean hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public abstract boolean 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;