RunMetadata.Builder

lớp cuối cùng tĩnh công khai RunMetadata.Builder

 Metadata output (i.e., non-Tensor) for a single Run() call.
 
Loại protobuf tensorflow.RunMetadata

Phương pháp công khai

RunMetadata.Builder
addAllFunctionGraphs (Iterable<? mở rộng các giá trị RunMetadata.FunctionGraphs >)
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
RunMetadata.Builder
addAllPartitionGraphs (Iterable<? mở rộng các giá trị GraphDef >)
 Graphs of the partitions executed by executors.
RunMetadata.Builder
addFunctionGraphs (chỉ mục int, giá trị RunMetadata.FunctionGraphs )
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
RunMetadata.Builder
addFunctionGraphs (chỉ mục int, RunMetadata.FunctionGraphs.Builder builderForValue)
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
RunMetadata.Builder
addFunctionGraphs (giá trị 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 (chỉ mục 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
addPartitionGraphs (chỉ số int, giá trị GraphDef )
 Graphs of the partitions executed by executors.
RunMetadata.Builder
addPartitionGraphs ( GraphDef.Builder builderForValue)
 Graphs of the partitions executed by executors.
RunMetadata.Builder
addPartitionGraphs (giá trị GraphDef )
 Graphs of the partitions executed by executors.
RunMetadata.Builder
addPartitionGraphs (chỉ mục int, GraphDef.Builder builderForValue)
 Graphs of the partitions executed by executors.
GraphDef.Builder
addPartitionGraphsBuilder (chỉ mục int)
 Graphs of the partitions executed by executors.
GraphDef.Builder
addPartitionGraphsBuilder ()
 Graphs of the partitions executed by executors.
RunMetadata.Builder
addRepeatedField (trường com.google.protobuf.Descriptors.FieldDescriptor, Giá trị đối tượng)
ChạySiêu dữ liệu
ChạySiêu dữ liệu
RunMetadata.Builder
RunMetadata.Builder
ClearCostGraph ()
 The cost graph for the computation defined by the run call.
RunMetadata.Builder
ClearField (trường 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
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.
ChạySiêu dữ liệu
com.google.protobuf.Descriptors.Descriptor tĩnh cuối cùng
com.google.protobuf.Descriptors.Descriptor
RunMetadata.FunctionGraphs
getFunctionGraphs (chỉ mục int)
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
RunMetadata.FunctionGraphs.Builder
getFunctionGraphsBuilder (chỉ mục int)
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
Danh sách< 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.
Danh sách< RunMetadata.FunctionGraphs >
getFunctionGraphsList ()
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
RunMetadata.FunctionGraphsOrBuilder
getFunctionGraphsOrBuilder (chỉ mục int)
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
Danh sách<? mở rộng RunMetadata.FunctionGraphsOrBuilder >
getFunctionGraphsOrBuilderList ()
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
GraphDef
getPartitionGraphs (chỉ mục int)
 Graphs of the partitions executed by executors.
GraphDef.Builder
getPartitionGraphsBuilder (chỉ mục int)
 Graphs of the partitions executed by executors.
Danh sách< GraphDef.Builder >
getPartitionGraphsBuilderList ()
 Graphs of the partitions executed by executors.
int
getPartitionGraphsCount ()
 Graphs of the partitions executed by executors.
Danh sách< GraphDef >
getPartitionGraphsList ()
 Graphs of the partitions executed by executors.
GraphDefOrBuilder
getPartitionGraphsOrBuilder (chỉ mục int)
 Graphs of the partitions executed by executors.
Danh sách<? mở rộng GraphDefOrBuilder >
getPartitionGraphsOrBuilderList ()
 Graphs of the partitions executed by executors.
Thống kê bước
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.
boolean cuối cùng
RunMetadata.Builder
mergeCostGraph (giá trị CostGraphDef )
 The cost graph for the computation defined by the run call.
RunMetadata.Builder
mergeFrom (com.google.protobuf.Message other)
RunMetadata.Builder
mergeFrom (đầu vào com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
RunMetadata.Builder
mergeStepStats (giá trị StepStats )
 Statistics traced for this step.
RunMetadata.Builder cuối cùng
hợp nhấtUnknownFields (com.google.protobuf.UnknownFieldSet knownFields)
RunMetadata.Builder
RemoveFunctionGraphs (chỉ mục int)
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
RunMetadata.Builder
RemovePartitionGraphs (chỉ mục int)
 Graphs of the partitions executed by executors.
RunMetadata.Builder
setCostGraph (giá trị CostGraphDef )
 The cost graph for the computation defined by the run call.
RunMetadata.Builder
setCostGraph ( CostGraphDef.Builder builderForValue)
 The cost graph for the computation defined by the run call.
RunMetadata.Builder
setField (trường com.google.protobuf.Descriptors.FieldDescriptor, Giá trị đối tượng)
RunMetadata.Builder
setFunctionGraphs (chỉ mục int, giá trị RunMetadata.FunctionGraphs )
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
RunMetadata.Builder
setFunctionGraphs (chỉ mục int, RunMetadata.FunctionGraphs.Builder builderForValue)
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
RunMetadata.Builder
setPartitionGraphs (chỉ mục int, GraphDef.Builder builderForValue)
 Graphs of the partitions executed by executors.
RunMetadata.Builder
setPartitionGraphs (chỉ số int, giá trị GraphDef )
 Graphs of the partitions executed by executors.
RunMetadata.Builder
setRepeatedField (trường com.google.protobuf.Descriptors.FieldDescriptor, chỉ mục int, giá trị đối tượng)
RunMetadata.Builder
setStepStats ( StepStats.Builder builderForValue)
 Statistics traced for this step.
RunMetadata.Builder
setStepStats (giá trị StepStats )
 Statistics traced for this step.
RunMetadata.Builder cuối cùng
setUnknownFields (com.google.protobuf.UnknownFieldSet knownFields)

Phương pháp kế thừa

Phương pháp công khai

công khai RunMetadata.Builder addAllFunctionGraphs (Iterable<? mở rộng các giá trị 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 (Có thể lặp lại các giá trị GraphDef >)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

public RunMetadata.Builder addFunctionGraphs (chỉ mục int, giá trị 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;

công khai RunMetadata.Builder addFunctionGraphs (chỉ mục 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;

công khai RunMetadata.Builder addFunctionGraphs (giá trị 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;

công khai 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;

công khai RunMetadata.FunctionGraphs.Builder addFunctionGraphsBuilder (chỉ mục 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;

công khai 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 (chỉ mục int, giá trị GraphDef )

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

công khai RunMetadata.Builder addPartitionGraphs ( GraphDef.Builder builderForValue)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

công khai RunMetadata.Builder addPartitionGraphs (giá trị GraphDef )

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

công khai RunMetadata.Builder addPartitionGraphs (chỉ mục int, GraphDef.Builder builderForValue)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

GraphDef.Builder công khai addPartitionGraphsBuilder (chỉ mục int)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

GraphDef.Builder công khai addPartitionGraphsBuilder ()

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

công khai RunMetadata.Builder addRepeatedField (trường com.google.protobuf.Descriptors.FieldDescriptor, Giá trị đối tượng)

bản dựng RunMetadata công khai ()

công khai RunMetadata buildPartial ()

công khai RunMetadata.Builder rõ ràng ()

công khai RunMetadata.Builder clearCostGraph ()

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

công khai RunMetadata.Builder clearField (trường com.google.protobuf.Descriptors.FieldDescriptor)

công khai 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;

công khai RunMetadata.Builder clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)

công khai RunMetadata.Builder clearPartitionGraphs ()

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

công khai 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;

bản sao RunMetadata.Builder công khai ()

CostGraphDef công khai getCostGraph ()

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

CostGraphDef.Builder công khai getCostGraphBuilder ()

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

CostGraphDefOrBuilder công khai getCostGraphOrBuilder ()

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

công khai RunMetadata getDefaultInstanceForType ()

công khai tĩnh cuối cùng com.google.protobuf.Descriptors.Descriptor getDescriptor ()

com.google.protobuf.Descriptors.Descriptor công khai getDescriptorForType ()

công khai RunMetadata.FunctionGraphs getFunctionGraphs (chỉ mục 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;

công khai RunMetadata.FunctionGraphs.Builder getFunctionGraphsBuilder (chỉ mục 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;

Danh sách công khai< 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;

int công khai 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;

Danh sách công khai< 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;

công khai RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (chỉ mục 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;

Danh sách công khai<? mở rộng 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 công khai getPartitionGraphs (chỉ mục int)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

GraphDef.Builder công khai getPartitionGraphsBuilder (chỉ mục int)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

Danh sách công khai< GraphDef.Builder > getPartitionGraphsBuilderList ()

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

int công khai getPartitionGraphsCount ()

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

Danh sách công khai< GraphDef > getPartitionGraphsList ()

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

GraphDefOrBuilder công khai getPartitionGraphsOrBuilder (chỉ mục int)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

Danh sách công khai<? mở rộng GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

StepStats công khai 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;

công khai 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;

công khai 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;

boolean công khai hasCostGraph ()

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

boolean công khai 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;

boolean cuối cùng công khai được khởi tạo ()

công khai RunMetadata.Builder mergeCostGraph (giá trị CostGraphDef )

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

công khai RunMetadata.Builder mergeFrom (com.google.protobuf.Message other)

công khai RunMetadata.Builder mergeFrom (đầu vào com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Ném
IOException

công khai RunMetadata.Builder mergeStepStats (giá trị 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;

trận chung kết công khai RunMetadata.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet knownFields)

công khai RunMetadata.Builder RemoveFunctionGraphs (chỉ mục 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;

công khai RunMetadata.Builder RemovePartitionGraphs (chỉ mục int)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

công khai RunMetadata.Builder setCostGraph (giá trị CostGraphDef )

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

công khai RunMetadata.Builder setCostGraph ( CostGraphDef.Builder builderForValue)

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

công khai RunMetadata.Builder setField (trường com.google.protobuf.Descriptors.FieldDescriptor, Giá trị đối tượng)

public RunMetadata.Builder setFunctionGraphs (chỉ mục int, giá trị 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;

công khai RunMetadata.Builder setFunctionGraphs (chỉ mục 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;

công khai RunMetadata.Builder setPartitionGraphs (chỉ mục int, GraphDef.Builder builderForValue)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

public RunMetadata.Builder setPartitionGraphs (chỉ mục int, giá trị GraphDef )

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

công khai RunMetadata.Builder setRepeatedField (trường com.google.protobuf.Descriptors.FieldDescriptor, chỉ mục int, giá trị đối tượng)

công khai 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;

công khai RunMetadata.Builder setStepStats (giá trị 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;

trận chung kết công khai RunMetadata.Builder setUnknownFields (com.google.protobuf.UnknownFieldSet knownFields)