RunMetadata.Builder

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
addPartitionGraphs (indeks int, wartość GraphDef )
 Graphs of the partitions executed by executors.
UruchomMetadata.Builder
addPartitionGraphs ( GraphDef.Builder builderForValue)
 Graphs of the partitions executed by executors.
UruchomMetadata.Builder
addPartitionGraphs (wartość GraphDef )
 Graphs of the partitions executed by executors.
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
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
mergeCostGraph (wartość CostGraphDef )
 The cost graph for the computation defined by the run call.
UruchomMetadata.Builder
mergeFrom (com.google.protobuf.Wiadomość inna)
UruchomMetadata.Builder
mergeFrom (wejście com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
UruchomMetadata.Builder
mergeStepStats (wartość StepStats )
 Statistics traced for this step.
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
setCostGraph (wartość CostGraphDef )
 The cost graph for the computation defined by the run call.
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
setPartitionGraphs (indeks int, wartość GraphDef )
 Graphs of the partitions executed by executors.
UruchomMetadata.Builder
setRepeatedField (pole com.google.protobuf.Descriptors.FieldDescriptor, indeks int, wartość obiektu)
UruchomMetadata.Builder
setStepStats ( StepStats.Builder builderForValue)
 Statistics traced for this step.
UruchomMetadata.Builder
setStepStats (wartość StepStats )
 Statistics traced for this step.
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)

publiczna kompilacja RunMetadata ()

public RunMetadata buildPartial ()

publiczne RunMetadata.Builder wyczyść ()

publiczny RunMetadata.Builder clearCostGraph ()

 The cost graph for the computation defined by the run call.
 
.tensorflow.CostGraphDef cost_graph = 2;

publiczne RunMetadata.Builder clearField (pole com.google.protobuf.Descriptors.FieldDescriptor)

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 clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)

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;

publiczny klon RunMetadata.Builder ()

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;

publiczne RunMetadata getDefaultInstanceForType ()

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor ()

publiczny 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 (com.google.protobuf.Message other)

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;

publiczny finał RunMetadata.Builder setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)