RunMetadataOrBuilder

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;

รายการนามธรรมสาธารณะ<? 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;

รายการนามธรรมสาธารณะ<? 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;