kelas akhir statis publik RunMetadata.Builder
Metadata output (i.e., non-Tensor) for a single Run() call.Tipe protobuf
tensorflow.RunMetadata Metode Publik
| Jalankan Metadata.Builder | addAllFunctionGraphs (Nilai Iterable<? extends RunMetadata.FunctionGraphs >) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Jalankan Metadata.Builder | addAllPartitionGraphs (Nilai Iterable<? extends GraphDef >) Graphs of the partitions executed by executors. |
| Jalankan Metadata.Builder | addFunctionGraphs (indeks int, nilai RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Jalankan Metadata.Builder | addFunctionGraphs (indeks int, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Jalankan Metadata.Builder | addFunctionGraphs (nilai RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Jalankan Metadata.Builder | addFunctionGraphs ( RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| JalankanMetadata.FunctionGraphs.Builder | addFunctionGraphsBuilder (indeks int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| JalankanMetadata.FunctionGraphs.Builder | tambahkanFunctionGraphsBuilder () This is only populated for graphs that are run as functions in TensorFlow V2. |
| Jalankan Metadata.Builder | |
| Jalankan Metadata.Builder | addPartitionGraphs ( GraphDef.Builder pembangunForValue) Graphs of the partitions executed by executors. |
| Jalankan Metadata.Builder | |
| Jalankan Metadata.Builder | addPartitionGraphs (indeks int, GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| GraphDef.Builder | addPartitionGraphsBuilder (indeks int) Graphs of the partitions executed by executors. |
| GraphDef.Builder | tambahkanPartitionGraphsBuilder () Graphs of the partitions executed by executors. |
| Jalankan Metadata.Builder | addRepeatedField (bidang com.google.protobuf.Descriptors.FieldDescriptor, Nilai objek) |
| Jalankan Metadata | membangun () |
| Jalankan Metadata | |
| Jalankan Metadata.Builder | jernih () |
| Jalankan Metadata.Builder | jelasCostGraph () The cost graph for the computation defined by the run call. |
| Jalankan Metadata.Builder | clearField (bidang com.google.protobuf.Descriptors.FieldDescriptor) |
| Jalankan Metadata.Builder | jelasFunctionGraphs () This is only populated for graphs that are run as functions in TensorFlow V2. |
| Jalankan Metadata.Builder | clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof) |
| Jalankan Metadata.Builder | jelasPartitionGraphs () Graphs of the partitions executed by executors. |
| Jalankan Metadata.Builder | hapusStepStats () Statistics traced for this step. |
| Jalankan Metadata.Builder | klon () |
| BiayaGraphDef | dapatkanCostGraph () The cost graph for the computation defined by the run call. |
| CostGraphDef.Builder | dapatkanCostGraphBuilder () The cost graph for the computation defined by the run call. |
| CostGraphDefOrBuilder | dapatkanCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| Jalankan Metadata | |
| com.google.protobuf.Descriptors.Descriptor statis terakhir | |
| com.google.protobuf.Descriptors.Descriptor | |
| JalankanMetadata.FunctionGraphs | getFunctionGraphs (indeks int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| JalankanMetadata.FunctionGraphs.Builder | getFunctionGraphsBuilder (indeks int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Daftar< JalankanMetadata.FunctionGraphs.Builder > | dapatkanFunctionGraphsBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| ke dalam | dapatkanFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| Daftar< JalankanMetadata.FunctionGraphs > | dapatkanFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| JalankanMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (indeks int) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Daftar<? memperluas RunMetadata.FunctionGraphsOrBuilder > | dapatkanFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| GrafikDef | getPartitionGraphs (indeks int) Graphs of the partitions executed by executors. |
| GraphDef.Builder | getPartitionGraphsBuilder (indeks int) Graphs of the partitions executed by executors. |
| Daftar< GraphDef.Builder > | getPartitionGraphsBuilderList () Graphs of the partitions executed by executors. |
| ke dalam | dapatkanPartitionGraphsCount () Graphs of the partitions executed by executors. |
| Daftar< GraphDef > | dapatkanPartitionGraphsList () Graphs of the partitions executed by executors. |
| GraphDefOrBuilder | getPartitionGraphsOrBuilder (indeks int) Graphs of the partitions executed by executors. |
| Daftar<? memperluas GraphDefOrBuilder > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| Statistik Langkah | dapatkanStepStats () Statistics traced for this step. |
| StepStats.Builder | dapatkanStepStatsBuilder () Statistics traced for this step. |
| StepStatsOrBuilder | dapatkanStepStatsOrBuilder () 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 terakhir | |
| Jalankan Metadata.Builder | |
| Jalankan Metadata.Builder | mergeFrom (com.google.protobuf.Pesan lainnya) |
| Jalankan Metadata.Builder | mergeFrom (com.google.protobuf.CodedInputStream masukan, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
| Jalankan Metadata.Builder | |
| RunMetadata.Builder terakhir | mergeUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields) |
| Jalankan Metadata.Builder | hapusFunctionGraphs (int indeks) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Jalankan Metadata.Builder | hapusPartitionGraphs (indeks int) Graphs of the partitions executed by executors. |
| Jalankan Metadata.Builder | |
| Jalankan Metadata.Builder | setCostGraph ( CostGraphDef.Pembuat pembangunForValue) The cost graph for the computation defined by the run call. |
| Jalankan Metadata.Builder | setField (bidang com.google.protobuf.Descriptors.FieldDescriptor, Nilai objek) |
| Jalankan Metadata.Builder | setFunctionGraphs (indeks int, nilai RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Jalankan Metadata.Builder | setFunctionGraphs (indeks int, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| Jalankan Metadata.Builder | setPartitionGraphs (indeks int, GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
| Jalankan Metadata.Builder | |
| Jalankan Metadata.Builder | setRepeatedField (bidang com.google.protobuf.Descriptors.FieldDescriptor, indeks int, Nilai objek) |
| Jalankan Metadata.Builder | |
| Jalankan Metadata.Builder | |
| RunMetadata.Builder terakhir | setUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields) |
Metode Warisan
Metode Publik
public RunMetadata.Builder addAllFunctionGraphs (Nilai Iterable<? extends 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 (nilai Iterable<? extends GraphDef >)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder addFunctionGraphs publik (indeks int, nilai RunMetadata.FunctionGraphs )
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; RunMetadata.Builder addFunctionGraphs publik (int indeks, RunMetadata.FunctionGraphs.Builder builderForValue)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; RunMetadata.Builder addFunctionGraphs publik (nilai RunMetadata.FunctionGraphs )
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; RunMetadata.Builder addFunctionGraphs publik ( 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; publik RunMetadata.FunctionGraphs.Builder addFunctionGraphsBuilder (int indeks)
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; publik 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; RunMetadata.Builder addPartitionGraphs publik (indeks int, nilai GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;RunMetadata.Builder addPartitionGraphs publik ( GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder addPartitionGraphs publik (nilai GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder addPartitionGraphs publik (int indeks, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; publik GraphDef.Builder addPartitionGraphsBuilder (int indeks)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; publik GraphDef.Builder addPartitionGraphsBuilder ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder addRepeatedField (bidang com.google.protobuf.Descriptors.FieldDescriptor, Nilai objek)
RunMetadata.Builder publik clearCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; RunMetadata.Builder publik 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; publik RunMetadata.Builder clearPartitionGraphs ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder publik clearStepStats ()
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; CostGraphDef publik getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; CostGraphDef.Builder publik getCostGraphBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; CostGraphDefOrBuilder publik 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 ()
com.google.protobuf.Descriptors.Descriptor publik getDescriptorForType ()
RunMetadata.FunctionGraphs publik 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; publik RunMetadata.FunctionGraphs.Builder getFunctionGraphsBuilder (int indeks)
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; Daftar publik< 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 publik 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; Daftar publik< 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; publik RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (int indeks)
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; Daftar Publik<? memperluas 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; publik GraphDef getPartitionGraphs (int indeks)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; publik GraphDef.Builder getPartitionGraphsBuilder (int indeks)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; Daftar publik< GraphDef.Builder > getPartitionGraphsBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; int publik getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; Daftar publik< GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; publik GraphDefOrBuilder getPartitionGraphsOrBuilder (int indeks)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; Daftar Publik<? memperluas GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; StepStats publik getStepStats ()
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; StepStats.Builder publik getStepStatsBuilder ()
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; StepStatsOrBuilder publik 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 publik hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; boolean publik 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 akhir publik diinisialisasi ()
RunMetadata.Builder mergeCostGraph publik (nilai CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; RunMetadata.Builder mergeFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Melempar
| Pengecualian IO |
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RunMetadata.Builder mergeStepStats publik (nilai StepStats )
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; RunMetadata.Builder final publik menggabungkanUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)
RunMetadata.Builder publik deleteFunctionGraphs (int indeks)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; RunMetadata.Builder publik deletePartitionGraphs (int indeks)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder setCostGraph publik (nilai CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; RunMetadata.Builder setCostGraph publik ( CostGraphDef.Builder builderForValue)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; public RunMetadata.Builder setField (bidang com.google.protobuf.Descriptors.FieldDescriptor, Nilai objek)
RunMetadata.Builder setFunctionGraphs publik (indeks int, nilai RunMetadata.FunctionGraphs )
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; RunMetadata.Builder setFunctionGraphs publik (int indeks, RunMetadata.FunctionGraphs.Builder builderForValue)
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4; RunMetadata.Builder setPartitionGraphs publik (indeks int, GraphDef.Builder buildForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; RunMetadata.Builder setPartitionGraphs publik (indeks int, nilai GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; public RunMetadata.Builder setRepeatedField (bidang com.google.protobuf.Descriptors.FieldDescriptor, indeks int, Nilai objek)
RunMetadata.Builder setStepStats publik ( StepStats.Builder builderForValue)
Statistics traced for this step. Populated if tracing is turned on via the "RunOptions" proto. EXPERIMENTAL: The format and set of events may change in future versions.
.tensorflow.StepStats step_stats = 1; RunMetadata.Builder setStepStats publik (nilai 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;