RunMetadata.Builder คลาสสุดท้ายแบบคงที่สาธารณะ
Metadata output (i.e., non-Tensor) for a single Run() call.Protobuf ประเภท
tensorflow.RunMetadata วิธีการสาธารณะ
| RunMetadata.Builder | addAllFunctionGraphs (Iterable<? ขยาย RunMetadata.FunctionGraphs > ค่า) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | addAllPartitionGraphs (Iterable<? ขยาย GraphDef > ค่า) Graphs of the partitions executed by executors. |
| RunMetadata.Builder | addFunctionGraphs (ดัชนี int, ค่า RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | addFunctionGraphs (ดัชนี int, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | addFunctionGraphs (ค่า RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | addFunctionGraphs ( RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | addFunctionGraphsBuilder (ดัชนี int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | addFunctionGraphsBuilder () This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | |
| RunMetadata.Builder | addPartitionGraphs ( GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| RunMetadata.Builder | |
| RunMetadata.Builder | addPartitionGraphs (ดัชนี int, GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| GraphDef.Builder | addPartitionGraphsBuilder (ดัชนี int) Graphs of the partitions executed by executors. |
| GraphDef.Builder | addPartitionGraphsBuilder () Graphs of the partitions executed by executors. |
| RunMetadata.Builder | addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ช่อง ค่าอ็อบเจ็กต์) |
| เรียกใช้ Metadata | สร้าง () |
| เรียกใช้ Metadata | สร้างบางส่วน () |
| RunMetadata.Builder | ชัดเจน () |
| RunMetadata.Builder | ล้างกราฟต้นทุน () The cost graph for the computation defined by the run call. |
| RunMetadata.Builder | clearField (ฟิลด์ com.google.protobuf.Descriptors.FieldDescriptor) |
| RunMetadata.Builder | clearFunctionGraphs () This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof) |
| RunMetadata.Builder | clearPartitionGraphs () Graphs of the partitions executed by executors. |
| RunMetadata.Builder | clearStepStats () Statistics traced for this step. |
| RunMetadata.Builder | โคลน () |
| กราฟต้นทุนDef | รับต้นทุนกราฟ () The cost graph for the computation defined by the run call. |
| CostGraphDef.Builder | getCostGraphBuilder () The cost graph for the computation defined by the run call. |
| ราคากราฟDefOrBuilder | getCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| เรียกใช้ Metadata | |
| com.google.protobuf.Descriptors.Descriptor แบบคงที่ขั้นสุดท้าย | รับคำอธิบาย () |
| com.google.protobuf.Descriptors.Descriptor | |
| RunMetadata.FunctionGraphs | getFunctionGraphs (ดัชนี int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | getFunctionGraphsBuilder (ดัชนี int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| รายการ < RunMetadata.FunctionGraphs.Builder > | getFunctionGraphsBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| ภายใน | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| รายการ < RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (ดัชนี int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| รายการ<? ขยาย RunMetadata.FunctionGraphsOrBuilder > | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| กราฟDef | getPartitionGraphs (ดัชนี int) Graphs of the partitions executed by executors. |
| GraphDef.Builder | getPartitionGraphsBuilder (ดัชนี int) Graphs of the partitions executed by executors. |
| รายการ < GraphDef.Builder > | getPartitionGraphsBuilderList () Graphs of the partitions executed by executors. |
| ภายใน | getPartitionGraphsCount () Graphs of the partitions executed by executors. |
| รายการ < GraphDef > | getPartitionGraphsList () Graphs of the partitions executed by executors. |
| GraphDefOrBuilder | getPartitionGraphsOrBuilder (ดัชนี int) Graphs of the partitions executed by executors. |
| รายการ<? ขยาย GraphDefOrBuilder > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| StepStats | getStepStats () Statistics traced for this step. |
| StepStats.Builder | getStepStatsBuilder () Statistics traced for this step. |
| StepStatsOrBuilder | getStepStatsOrBuilder () Statistics traced for this step. |
| บูลีน | มีกราฟต้นทุน () The cost graph for the computation defined by the run call. |
| บูลีน | hasStepStats () Statistics traced for this step. |
| บูลีนสุดท้าย | |
| RunMetadata.Builder | |
| RunMetadata.Builder | mergeFrom (com.google.protobuf.ข้อความ อื่น ๆ ) |
| RunMetadata.Builder | mergeFrom (com.google.protobuf.CodedInputStream อินพุต com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
| RunMetadata.Builder | |
| RunMetadata.Builder สุดท้าย | mergeUnknownFields (com.google.protobuf.UnknownFieldSetknownFields) |
| RunMetadata.Builder | RemoveFunctionGraphs (ดัชนี int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | RemovePartitionGraphs (ดัชนี int) Graphs of the partitions executed by executors. |
| RunMetadata.Builder | |
| RunMetadata.Builder | setCostGraph ( CostGraphDef.Builder builderForValue) The cost graph for the computation defined by the run call. |
| RunMetadata.Builder | setField (ฟิลด์ com.google.protobuf.Descriptors.FieldDescriptor ค่าอ็อบเจ็กต์) |
| RunMetadata.Builder | setFunctionGraphs (ดัชนี int, ค่า RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | setFunctionGraphs (ดัชนี int, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder | setPartitionGraphs (ดัชนี int, GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| RunMetadata.Builder | |
| RunMetadata.Builder | setRepeatedField (ฟิลด์ com.google.protobuf.Descriptors.FieldDescriptor, ดัชนี int, ค่าอ็อบเจ็กต์) |
| RunMetadata.Builder | |
| RunMetadata.Builder | |
| RunMetadata.Builder สุดท้าย | setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields) |
วิธีการสืบทอด
วิธีการสาธารณะ
RunMetadata.Builder สาธารณะ addAllFunctionGraphs (Iterable<? ขยาย RunMetadata.FunctionGraphs > ค่า)
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; RunMetadata.Builder สาธารณะ addAllPartitionGraphs (Iterable <? ขยาย GraphDef > ค่า)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder addFunctionGraphs สาธารณะ (ดัชนี int, ค่า RunMetadata.FunctionGraphs )
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; RunMetadata.Builder addFunctionGraphs สาธารณะ (ดัชนี int, RunMetadata.FunctionGraphs.Builder builderForValue)
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; RunMetadata.Builder addFunctionGraphs สาธารณะ (ค่า RunMetadata.FunctionGraphs )
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; RunMetadata.Builder addFunctionGraphs สาธารณะ ( RunMetadata.FunctionGraphs.Builder builderForValue)
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; RunMetadata.FunctionGraphs.Builder สาธารณะ addFunctionGraphsBuilder (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; RunMetadata.FunctionGraphs.Builder สาธารณะ addFunctionGraphsBuilder ()
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; RunMetadata.Builder addPartitionGraphs สาธารณะ (ดัชนี int, ค่า GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;RunMetadata.Builder สาธารณะ addPartitionGraphs ( GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder addPartitionGraphs สาธารณะ (ค่า GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder addPartitionGraphs สาธารณะ (ดัชนี int, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; GraphDef.Builder สาธารณะ addPartitionGraphsBuilder (ดัชนี int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; GraphDef.Builder สาธารณะ addPartitionGraphsBuilder ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder addRepeatedField สาธารณะ (ฟิลด์ com.google.protobuf.Descriptors.FieldDescriptor ค่าอ็อบเจ็กต์)
RunMetadata.Builder สาธารณะ clearCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; RunMetadata.Builder สาธารณะ clearFunctionGraphs ()
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; RunMetadata.Builder สาธารณะ clearPartitionGraphs ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder สาธารณะ clearStepStats ()
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; CostGraphDef สาธารณะ getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; CostGraphDef.Builder สาธารณะ getCostGraphBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; CostGraphDefOrBuilder สาธารณะ getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; สาธารณะคงที่สุดท้าย com.google.protobuf.Descriptors.Descriptor getDescriptor ()
สาธารณะ com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()
RunMetadata.FunctionGraphs สาธารณะ 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; RunMetadata.FunctionGraphs.Builder สาธารณะ getFunctionGraphsBuilder (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; รายการสาธารณะ < RunMetadata.FunctionGraphs.Builder > getFunctionGraphsBuilderList ()
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; สาธารณะ 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; รายการสาธารณะ < 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; RunMetadata.FunctionGraphsOrBuilder สาธารณะ 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; รายการสาธารณะ<? 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 getPartitionGraphs สาธารณะ (ดัชนี int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; GraphDef.Builder สาธารณะ getPartitionGraphsBuilder (ดัชนี int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; รายการสาธารณะ < GraphDef.Builder > getPartitionGraphsBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; int สาธารณะ getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; รายการสาธารณะ < GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; GraphDefOrBuilder สาธารณะ getPartitionGraphsOrBuilder (ดัชนี int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; รายการสาธารณะ<? ขยาย GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; StepStats สาธารณะ 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; StepStats.Builder สาธารณะ getStepStatsBuilder ()
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 สาธารณะ 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; hasCostGraph บูลีนสาธารณะ ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; hasStepStats บูลีนสาธารณะ ()
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; บูลีนสุดท้ายสาธารณะ isInitialized ()
RunMetadata.Builder สาธารณะ ผสานCostGraph (ค่า CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; RunMetadata.Builder สาธารณะ ผสานจาก (com.google.protobuf.CodedInputStream อินพุต com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ขว้าง
| IOข้อยกเว้น |
|---|
RunMetadata.Builder สาธารณะ ผสาน StepStats (ค่า StepStats )
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; RunMetadata.Builder สาธารณะขั้นสุดท้าย ผสาน UnknownFields (com.google.protobuf.UnknownFieldSetknownFields)
RunMetadata.Builder สาธารณะ RemoveFunctionGraphs (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; RunMetadata.Builder สาธารณะ RemovePartitionGraphs (ดัชนี int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder สาธารณะ setCostGraph (ค่า CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; RunMetadata.Builder สาธารณะ setCostGraph ( CostGraphDef.Builder builderForValue)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; RunMetadata.Builder setField สาธารณะ (ฟิลด์ com.google.protobuf.Descriptors.FieldDescriptor ค่าอ็อบเจ็กต์)
RunMetadata.Builder setFunctionGraphs สาธารณะ (ดัชนี int, ค่า RunMetadata.FunctionGraphs )
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; RunMetadata.Builder setFunctionGraphs สาธารณะ (ดัชนี int, RunMetadata.FunctionGraphs.Builder builderForValue)
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; RunMetadata.Builder สาธารณะ setPartitionGraphs (ดัชนี int, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder setPartitionGraphs สาธารณะ (ดัชนี int, ค่า GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder setRepeatedField สาธารณะ (ฟิลด์ com.google.protobuf.Descriptors.FieldDescriptor, ดัชนี int, ค่าอ็อบเจ็กต์)
RunMetadata.Builder setStepStats สาธารณะ ( StepStats.Builder builderForValue)
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; RunMetadata.Builder setStepStats สาธารณะ (ค่า StepStats )
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;