publiczna statyczna klasa końcowa RunMetadata.Builder
Metadata output (i.e., non-Tensor) for a single Run() call.Protobuf typu
tensorflow.RunMetadata Metody publiczne
| UruchomMetadata.Builder | addAllFunctionGraphs (Iterable<? rozszerza wartości RunMetadata.FunctionGraphs >) This is only populated for graphs that are run as functions in TensorFlow V2. |
| UruchomMetadata.Builder | addAllPartitionGraphs (Iterable<? rozszerza GraphDef > wartości) Graphs of the partitions executed by executors. |
| UruchomMetadata.Builder | addFunctionGraphs (indeks int, wartość RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| UruchomMetadata.Builder | addFunctionGraphs (indeks int, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| UruchomMetadata.Builder | addFunctionGraphs (wartość RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| UruchomMetadata.Builder | addFunctionGraphs ( RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | addFunctionGraphsBuilder (indeks 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. |
| UruchomMetadata.Builder | |
| UruchomMetadata.Builder | addPartitionGraphs ( GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| UruchomMetadata.Builder | |
| UruchomMetadata.Builder | addPartitionGraphs (indeks int, GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| Konstruktor GraphDef | addPartitionGraphsBuilder (indeks int) Graphs of the partitions executed by executors. |
| Konstruktor GraphDef | addPartitionGraphsBuilder () Graphs of the partitions executed by executors. |
| UruchomMetadata.Builder | addRepeatedField (pole com.google.protobuf.Descriptors.FieldDescriptor, wartość obiektu) |
| UruchomMetadane | zbudować () |
| UruchomMetadane | |
| UruchomMetadata.Builder | jasne () |
| UruchomMetadata.Builder | wyczyśćWykresKosztów () The cost graph for the computation defined by the run call. |
| UruchomMetadata.Builder | clearField (pole com.google.protobuf.Descriptors.FieldDescriptor) |
| UruchomMetadata.Builder | jasneWykresyFunkcji () This is only populated for graphs that are run as functions in TensorFlow V2. |
| UruchomMetadata.Builder | clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof) |
| UruchomMetadata.Builder | clearPartitionGraphs () Graphs of the partitions executed by executors. |
| UruchomMetadata.Builder | jasneStepStats () Statistics traced for this step. |
| UruchomMetadata.Builder | klon () |
| Wykres kosztówDef | pobierzWykresKosztów () 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. |
| CostGraphDefOrBuilder | getCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| UruchomMetadane | |
| końcowy statyczny com.google.protobuf.Descriptors.Descriptor | |
| com.google.protobuf.Descriptors.Descriptor | |
| RunMetadata.FunctionGraphs | getFunctionGraphs (indeks int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | getFunctionGraphsBuilder (indeks int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Lista< RunMetadata.FunctionGraphs.Builder > | getFunctionGraphsBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| wew | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| Lista< RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (indeks int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Lista<? rozszerza RunMetadata.FunctionGraphsOrBuilder > | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| WykresDef | getPartitionGraphs (indeks int) Graphs of the partitions executed by executors. |
| Konstruktor GraphDef | getPartitionGraphsBuilder (indeks int) Graphs of the partitions executed by executors. |
| Lista< GraphDef.Builder > | getPartitionGraphsBuilderList () Graphs of the partitions executed by executors. |
| wew | getPartitionGraphsCount () Graphs of the partitions executed by executors. |
| Lista <GraphDef> | getPartitionGraphsList () Graphs of the partitions executed by executors. |
| GraphDefOrBuilder | getPartitionGraphsOrBuilder (indeks int) Graphs of the partitions executed by executors. |
| Lista<? rozszerza GraphDefOrBuilder > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| Statystyki kroków | pobierz statystyki kroków () Statistics traced for this step. |
| StepStats.Builder | getStepStatsBuilder () Statistics traced for this step. |
| StepStatsOrBuilder | getStepStatsOrBuilder () Statistics traced for this step. |
| wartość logiczna | maWykresKosztów () The cost graph for the computation defined by the run call. |
| wartość logiczna | maStepStats () Statistics traced for this step. |
| końcowa wartość logiczna | |
| UruchomMetadata.Builder | |
| UruchomMetadata.Builder | mergeFrom (com.google.protobuf.Wiadomość inna) |
| UruchomMetadata.Builder | mergeFrom (wejście com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry) |
| UruchomMetadata.Builder | |
| końcowy RunMetadata.Builder | mergeUnknownFields (com.google.protobuf.UnknownFieldUstaw nieznane pola) |
| UruchomMetadata.Builder | usuńFunctionGraphs (indeks int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| UruchomMetadata.Builder | usuńPartitionGraphs (indeks int) Graphs of the partitions executed by executors. |
| UruchomMetadata.Builder | |
| UruchomMetadata.Builder | setCostGraph ( CostGraphDef.Builder builderForValue) The cost graph for the computation defined by the run call. |
| UruchomMetadata.Builder | setField (pole com.google.protobuf.Descriptors.FieldDescriptor, wartość obiektu) |
| UruchomMetadata.Builder | setFunctionGraphs (indeks int, wartość RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| UruchomMetadata.Builder | setFunctionGraphs (indeks int, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| UruchomMetadata.Builder | setPartitionGraphs (indeks int, GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| UruchomMetadata.Builder | |
| UruchomMetadata.Builder | setRepeatedField (pole com.google.protobuf.Descriptors.FieldDescriptor, indeks int, wartość obiektu) |
| UruchomMetadata.Builder | |
| UruchomMetadata.Builder | |
| końcowy RunMetadata.Builder | setUnknownFields (com.google.protobuf.UnknownFieldUstaw nieznane pola) |
Metody dziedziczone
Metody publiczne
public RunMetadata.Builder addAllFunctionGraphs (Iterable<? rozszerza wartości 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; public RunMetadata.Builder addAllPartitionGraphs (Iterable<? rozszerza GraphDef > wartości)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder addFunctionGraphs (indeks int, wartość 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; public RunMetadata.Builder addFunctionGraphs (indeks 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; public RunMetadata.Builder addFunctionGraphs (wartość 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; public RunMetadata.Builder addFunctionGraphs ( 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; public RunMetadata.FunctionGraphs.Builder addFunctionGraphsBuilder (indeks 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; public RunMetadata.FunctionGraphs.Builder 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; public RunMetadata.Builder addPartitionGraphs (indeks int, wartość GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;public RunMetadata.Builder addPartitionGraphs ( GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder addPartitionGraphs (wartość GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder addPartitionGraphs (indeks int, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public GraphDef.Builder addPartitionGraphsBuilder (indeks int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public GraphDef.Builder addPartitionGraphsBuilder ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder addRepeatedField (pole com.google.protobuf.Descriptors.FieldDescriptor, wartość obiektu)
publiczny RunMetadata.Builder clearCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public RunMetadata.Builder 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; public RunMetadata.Builder clearPartitionGraphs ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder 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; public CostGraphDef getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public CostGraphDef.Builder getCostGraphBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public CostGraphDefOrBuilder getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public static final com.google.protobuf.Descriptors.Descriptor getDescriptor ()
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()
public RunMetadata.FunctionGraphs getFunctionGraphs (indeks 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; public RunMetadata.FunctionGraphs.Builder getFunctionGraphsBuilder (indeks 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; public List< 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; public 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 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; public RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (indeks 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; lista publiczna<? rozszerza 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; public GraphDef getPartitionGraphs (indeks int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public GraphDef.Builder getPartitionGraphsBuilder (indeks int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public List< GraphDef.Builder > getPartitionGraphsBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public int getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public List< GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public GraphDefOrBuilder getPartitionGraphsOrBuilder (indeks int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; lista publiczna<? rozszerza GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; publiczne 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; public StepStats.Builder 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; public 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; publiczna wartość logiczna hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; publiczna wartość logiczna 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; publiczna końcowa wartość logiczna isInitialized ()
public RunMetadata.Builder mergeCostGraph (wartość CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public RunMetadata.Builder mergeFrom (wejście com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
Rzuca
| Wyjątek IO |
|---|
public RunMetadata.Builder mergeStepStats (wartość 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; publiczny finał RunMetadata.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)
public RunMetadata.Builder usuńFunctionGraphs (indeks 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; public RunMetadata.Builder usuńPartitionGraphs (indeks int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder setCostGraph (wartość CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public RunMetadata.Builder setCostGraph ( CostGraphDef.Builder builderForValue)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public RunMetadata.Builder setField (pole com.google.protobuf.Descriptors.FieldDescriptor, wartość obiektu)
public RunMetadata.Builder setFunctionGraphs (indeks int, wartość 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; public RunMetadata.Builder setFunctionGraphs (indeks 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; public RunMetadata.Builder setPartitionGraphs (indeks int, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder setPartitionGraphs (indeks int, wartość GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder setRepeatedField (pole com.google.protobuf.Descriptors.FieldDescriptor, indeks int, wartość obiektu)
public RunMetadata.Builder setStepStats ( 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; public RunMetadata.Builder setStepStats (wartość 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;