الفئة النهائية العامة الثابتة RunMetadata.Builder
Metadata output (i.e., non-Tensor) for a single Run() call.نوع Protobuf
tensorflow.RunMetadata
الأساليب العامة
RunMetadata.Builder | addAllFunctionGraphs (Iterable<? يمتد RunMetadata.FunctionGraphs > القيم) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | addAllPartitionGraphs (Iterable<؟ يمتد GraphDef > القيم) Graphs of the partitions executed by executors. |
RunMetadata.Builder | addFunctionGraphs (مؤشر int، قيمة RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | addFunctionGraphs (مؤشر int، RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | addFunctionGraphs (قيمة 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 (فهرس كثافة العمليات) 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 (مؤشر int، GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
GraphDef.Builder | addPartitionGraphsBuilder (فهرس كثافة العمليات) Graphs of the partitions executed by executors. |
GraphDef.Builder | addPartitionGraphsBuilder () Graphs of the partitions executed by executors. |
RunMetadata.Builder | addRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن) |
RunMetadata | يبني () |
RunMetadata | بناء جزئي () |
RunMetadata.Builder | واضح () |
RunMetadata.Builder | كليركوستغراف () The cost graph for the computation defined by the run call. |
RunMetadata.Builder | ClearField (حقل 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 | مسح الرسوم البيانية () Graphs of the partitions executed by executors. |
RunMetadata.Builder | كليرستيبستاتس () Statistics traced for this step. |
RunMetadata.Builder | استنساخ () |
CostGraphDef | الحصول على التكلفةالرسم البياني () 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 | |
النهائي الثابت com.google.protobuf.Descriptors.Descriptor | |
com.google.protobuf.Descriptors.Descriptor | |
RunMetadata.FunctionGraphs | getFunctionGraphs (فهرس كثافة العمليات) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.FunctionGraphs.Builder | getFunctionGraphsBuilder (فهرس كثافة العمليات) This is only populated for graphs that are run as functions in TensorFlow V2. |
القائمة< RunMetadata.FunctionGraphs.Builder > | getFunctionGraphsBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
كثافة العمليات | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
القائمة< RunMetadata.FunctionGraphs > | قائمة getFunctionGraphs () This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (فهرس كثافة العمليات) This is only populated for graphs that are run as functions in TensorFlow V2. |
القائمة<؟ يمتد RunMetadata.FunctionGraphsOrBuilder > | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
GraphDef | getPartitionGraphs (فهرس كثافة العمليات) Graphs of the partitions executed by executors. |
GraphDef.Builder | getPartitionGraphsBuilder (فهرس كثافة العمليات) Graphs of the partitions executed by executors. |
القائمة< GraphDef.Builder > | getPartitionGraphsBuilderList () Graphs of the partitions executed by executors. |
كثافة العمليات | الحصول علىPartitionGraphsCount () Graphs of the partitions executed by executors. |
القائمة< GraphDef > | قائمة getPartitionGraphs () Graphs of the partitions executed by executors. |
GraphDefOrBuilder | getPartitionGraphsOrBuilder (فهرس كثافة العمليات) Graphs of the partitions executed by executors. |
القائمة<؟ يمتد GraphDefOrBuilder > | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
ستيبستاتس | الحصول على ستيبستاتس () Statistics traced for this step. |
StepStats.Builder | getStepStatsBuilder () Statistics traced for this step. |
StepStatsOrBuilder | getStepStatsOrBuilder () Statistics traced for this step. |
منطقية | hasCostGraph () The cost graph for the computation defined by the run call. |
منطقية | هاستيبستاتس () Statistics traced for this step. |
منطقية نهائية | تمت التهيئة () |
RunMetadata.Builder | |
RunMetadata.Builder | دمج من (com.google.protobuf.Message أخرى) |
RunMetadata.Builder | دمج من (com.google.protobuf.CodedInputStream input، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry) |
RunMetadata.Builder | |
RunMetadata.Builder النهائي | دمجUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields) |
RunMetadata.Builder | إزالةFunctionGraphs (فهرس كثافة العمليات) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | إزالة PartitionGraphs (فهرس كثافة العمليات) 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 (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن) |
RunMetadata.Builder | setFunctionGraphs (مؤشر int، قيمة RunMetadata.FunctionGraphs ) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | setFunctionGraphs (مؤشر int، RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | setPartitionGraphs (مؤشر int، GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
RunMetadata.Builder | |
RunMetadata.Builder | setRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، فهرس int، قيمة الكائن) |
RunMetadata.Builder | |
RunMetadata.Builder | |
RunMetadata.Builder النهائي | setUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields) |
الطرق الموروثة
الأساليب العامة
RunMetadata.Builder العام addAllFunctionGraphs (Iterable<? يمتد RunMetadata.FunctionGraphs > القيم)
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 العام addAllPartitionGraphs (Iterable <؟ يمتد GraphDef > القيم)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
RunMetadata.Builder addFunctionGraphs العام (مؤشر int، قيمة 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 public addFunctionGraphs (مؤشر 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;
RunMetadata.Builder العامة addFunctionGraphs (قيمة 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 العامة 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;
RunMetadata.FunctionGraphs.Builder العام addFunctionGraphsBuilder (فهرس كثافة العمليات)
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.FunctionGraphs.Builder العامة 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 العامة addPartitionGraphs (مؤشر int، قيمة GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
RunMetadata.Builder addPartitionGraphs العام ( GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
RunMetadata.Builder العامة addPartitionGraphs (قيمة GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
RunMetadata.Builder public addPartitionGraphs (مؤشر int، GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
GraphDef.Builder العام addPartitionGraphsBuilder (مؤشر int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
GraphDef.Builder العام addPartitionGraphsBuilder ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
RunMetadata.Builder العام addRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)
RunMetadata.Builder العام ClearCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
RunMetadata.Builder العام 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;
RunMetadata.Builder العام ClearPartitionGraphs ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
RunMetadata.Builder العام 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;
getCostGraph العامة CostGraphDef ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
CostGraphDef.Builder العامة getCostGraphBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
getCostGraphDefOrBuilder العامة getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
النهائي العام الثابت com.google.protobuf.Descriptors.Descriptor getDescriptor ()
com.google.protobuf.Descriptors.Descriptor getDescriptorForType () العام
RunMetadata.FunctionGraphs العام getFunctionGraphs (مؤشر 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;
RunMetadata.FunctionGraphs.Builder العام getFunctionGraphsBuilder (فهرس كثافة العمليات)
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;
القائمة العامة< 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 public 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;
القائمة العامة< 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;
RunMetadata.FunctionGraphsOrBuilder العام getFunctionGraphsOrBuilder (فهرس كثافة العمليات)
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;
القائمة العامة <؟ يمتد 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 getPartitionGraphs العام (مؤشر int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
GraphDef.Builder العام getPartitionGraphsBuilder (مؤشر int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
القائمة العامة< GraphDef.Builder > getPartitionGraphsBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
int public getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
القائمة العامة< GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
GraphDefOrBuilder العام getPartitionGraphsOrBuilder (مؤشر int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
القائمة العامة <؟ يمتد GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
StepStats العامة 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 العامة 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;
GetStepStatsOrBuilder العامة 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;
hasCostGraph () المنطقي العام
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
hasStepStats المنطقية العامة ()
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;
تمت تهيئة القيمة المنطقية النهائية العامة ()
RunMetadata.Builder العام mergeCostGraph (قيمة CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
RunMetadata.Builder العام mergeFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
رميات
IOEException |
---|
RunMetadata.Builder العام mergeStepStats (قيمة 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 النهائي العام mergeUnknownFields (com.google.protobuf.UnknownFieldSetUnknownFields)
RunMetadata.Builder العام RemoveFunctionGraphs (مؤشر 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;
RunMetadata.Builder العام RemovePartitionGraphs (مؤشر int)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
RunMetadata.Builder العامة setCostGraph (قيمة CostGraphDef )
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
RunMetadata.Builder العام setCostGraph ( CostGraphDef.Builder builderForValue)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
RunMetadata.Builder setField العام (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)
RunMetadata.Builder العامة setFunctionGraphs (مؤشر int، قيمة 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 العام setFunctionGraphs (مؤشر 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;
RunMetadata.Builder العام setPartitionGraphs (مؤشر int، GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
RunMetadata.Builder العامة setPartitionGraphs (مؤشر int، قيمة GraphDef )
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
RunMetadata.Builder العام setRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، مؤشر int، قيمة الكائن)
RunMetadata.Builder العام 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;
RunMetadata.Builder العامة setStepStats (قيمة 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;