public static final class
RunMetadata.Builder
Metadata output (i.e., non-Tensor) for a single Run() call.
tensorflow.RunMetadata
Public Methods
| RunMetadata.Builder |
addAllFunctionGraphs(Iterable<? extends RunMetadata.FunctionGraphs> values)
This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder |
addAllPartitionGraphs(Iterable<? extends GraphDef> values)
Graphs of the partitions executed by executors. |
| RunMetadata.Builder |
addFunctionGraphs(int index, RunMetadata.FunctionGraphs value)
This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder |
addFunctionGraphs(int index, RunMetadata.FunctionGraphs.Builder builderForValue)
This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder |
addFunctionGraphs(RunMetadata.FunctionGraphs value)
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(int index)
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(int index, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors. |
| GraphDef.Builder |
addPartitionGraphsBuilder(int index)
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 field, Object value)
|
| RunMetadata |
build()
|
| RunMetadata | |
| RunMetadata.Builder |
clear()
|
| RunMetadata.Builder |
clearCostGraph()
The cost graph for the computation defined by the run call. |
| RunMetadata.Builder |
clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
|
| 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 |
clone()
|
| CostGraphDef |
getCostGraph()
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. |
| RunMetadata | |
| final static com.google.protobuf.Descriptors.Descriptor | |
| com.google.protobuf.Descriptors.Descriptor | |
| RunMetadata.FunctionGraphs |
getFunctionGraphs(int index)
This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder |
getFunctionGraphsBuilder(int index)
This is only populated for graphs that are run as functions in TensorFlow V2. |
| List<RunMetadata.FunctionGraphs.Builder> |
getFunctionGraphsBuilderList()
This is only populated for graphs that are run as functions in TensorFlow V2. |
| int |
getFunctionGraphsCount()
This is only populated for graphs that are run as functions in TensorFlow V2. |
| List<RunMetadata.FunctionGraphs> |
getFunctionGraphsList()
This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphsOrBuilder |
getFunctionGraphsOrBuilder(int index)
This is only populated for graphs that are run as functions in TensorFlow V2. |
| List<? extends RunMetadata.FunctionGraphsOrBuilder> |
getFunctionGraphsOrBuilderList()
This is only populated for graphs that are run as functions in TensorFlow V2. |
| GraphDef |
getPartitionGraphs(int index)
Graphs of the partitions executed by executors. |
| GraphDef.Builder |
getPartitionGraphsBuilder(int index)
Graphs of the partitions executed by executors. |
| List<GraphDef.Builder> |
getPartitionGraphsBuilderList()
Graphs of the partitions executed by executors. |
| int |
getPartitionGraphsCount()
Graphs of the partitions executed by executors. |
| List<GraphDef> |
getPartitionGraphsList()
Graphs of the partitions executed by executors. |
| GraphDefOrBuilder |
getPartitionGraphsOrBuilder(int index)
Graphs of the partitions executed by executors. |
| List<? extends 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. |
| boolean |
hasCostGraph()
The cost graph for the computation defined by the run call. |
| boolean |
hasStepStats()
Statistics traced for this step. |
| final boolean | |
| RunMetadata.Builder | |
| RunMetadata.Builder |
mergeFrom(com.google.protobuf.Message other)
|
| RunMetadata.Builder |
mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
|
| RunMetadata.Builder | |
| final RunMetadata.Builder |
mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
|
| RunMetadata.Builder |
removeFunctionGraphs(int index)
This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder |
removePartitionGraphs(int index)
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(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
|
| RunMetadata.Builder |
setFunctionGraphs(int index, RunMetadata.FunctionGraphs value)
This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder |
setFunctionGraphs(int index, RunMetadata.FunctionGraphs.Builder builderForValue)
This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.Builder |
setPartitionGraphs(int index, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors. |
| RunMetadata.Builder | |
| RunMetadata.Builder |
setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
|
| RunMetadata.Builder | |
| RunMetadata.Builder | |
| final RunMetadata.Builder |
setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
|
Inherited Methods
Public Methods
public RunMetadata.Builder addAllFunctionGraphs (Iterable<? extends RunMetadata.FunctionGraphs> values)
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<? extends GraphDef> values)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
public RunMetadata.Builder addFunctionGraphs (int index, RunMetadata.FunctionGraphs value)
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 (int index, 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 (RunMetadata.FunctionGraphs value)
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 (int index)
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 (int index, GraphDef value)
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 (GraphDef value)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
public RunMetadata.Builder addPartitionGraphs (int index, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
public GraphDef.Builder addPartitionGraphsBuilder (int index)
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 (com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
public 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 (int index)
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 (int index)
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 (int index)
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<? 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;
public GraphDef getPartitionGraphs (int index)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
public GraphDef.Builder getPartitionGraphsBuilder (int index)
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 (int index)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
public List<? extends GraphDefOrBuilder> getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
public 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;
public boolean hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
public 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;
public final boolean isInitialized ()
public RunMetadata.Builder mergeCostGraph (CostGraphDef value)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
public RunMetadata.Builder mergeFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Throws
| IOException |
|---|
public RunMetadata.Builder mergeStepStats (StepStats value)
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 final RunMetadata.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)
public RunMetadata.Builder removeFunctionGraphs (int index)
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 removePartitionGraphs (int index)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
public RunMetadata.Builder setCostGraph (CostGraphDef value)
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 (com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
public RunMetadata.Builder setFunctionGraphs (int index, RunMetadata.FunctionGraphs value)
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 (int index, 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 (int index, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
public RunMetadata.Builder setPartitionGraphs (int index, GraphDef value)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
public RunMetadata.Builder setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
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 (StepStats value)
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;