อินเทอร์เฟซสาธารณะ RunMetadataOrBuilder
| คลาสย่อยทางอ้อมที่รู้จัก |
วิธีการสาธารณะ
| CostGraphDef แบบนามธรรม | รับต้นทุนกราฟ () The cost graph for the computation defined by the run call. |
| นามธรรม CostGraphDefOrBuilder | getCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| บทคัดย่อ RunMetadata.FunctionGraphs | getFunctionGraphs (ดัชนี int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| บทคัดย่อ | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| รายการนามธรรม < RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| บทคัดย่อ RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (ดัชนี int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| รายการนามธรรม<? ขยาย RunMetadata.FunctionGraphsOrBuilder > | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| GraphDef แบบนามธรรม | getPartitionGraphs (ดัชนี int) Graphs of the partitions executed by executors. |
| บทคัดย่อ | getPartitionGraphsCount () Graphs of the partitions executed by executors. |
| รายการนามธรรม < GraphDef > | getPartitionGraphsList () Graphs of the partitions executed by executors. |
| GraphDefOrBuilder แบบนามธรรม | getPartitionGraphsOrBuilder (ดัชนี int) Graphs of the partitions executed by executors. |
| รายการนามธรรม<? ขยาย GraphDefOrBuilder > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| StepStats แบบนามธรรม | getStepStats () Statistics traced for this step. |
| StepStatsOrBuilder แบบนามธรรม | getStepStatsOrBuilder () Statistics traced for this step. |
| บูลีนนามธรรม | มีกราฟต้นทุน () The cost graph for the computation defined by the run call. |
| บูลีนนามธรรม | hasStepStats () Statistics traced for this step. |
วิธีการสาธารณะ
นามธรรมสาธารณะ CostGraphDef getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; นามธรรมสาธารณะ CostGraphDefOrBuilder getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; RunMetadata.FunctionGraphs นามธรรมสาธารณะ getFunctionGraphs (ดัชนี 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; บทคัดย่อสาธารณะ 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; รายการนามธรรมสาธารณะ < 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; บทคัดย่อสาธารณะ RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (ดัชนี 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; รายการบทคัดย่อสาธารณะ<? ขยาย 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; GraphDef นามธรรมสาธารณะ getPartitionGraphs (ดัชนี int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; นามธรรมสาธารณะ int getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; รายการนามธรรมสาธารณะ < GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; GraphDefOrBuilder นามธรรมสาธารณะ getPartitionGraphsOrBuilder (ดัชนี int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; รายการบทคัดย่อสาธารณะ<? ขยาย GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; StepStats นามธรรมสาธารณะ 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; StepStatsOrBuilder นามธรรมสาธารณะ 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; บูลีนนามธรรมสาธารณะ hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; บูลีนนามธรรมสาธารณะ 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;