lớp cuối cùng tĩnh công khai RunMetadata.Builder
Metadata output (i.e., non-Tensor) for a single Run() call.
tensorflow.RunMetadata
Phương pháp công cộng
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 | |
RunMetadata.Builder | addPartitionGraphs ( GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
RunMetadata.Builder | |
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 | xây dựng () |
ChạySiêu dữ liệu | |
RunMetadata.Builder | thông thoáng () |
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 | dòng vô tính () |
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 | |
RunMetadata.Builder | mergeFrom (com.google.protobuf.Message other) |
RunMetadata.Builder | mergeFrom (đầu vào com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry) |
RunMetadata.Builder | |
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 | |
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 | |
RunMetadata.Builder | setRepeatedField (trường com.google.protobuf.Descriptors.FieldDescriptor, chỉ mục int, giá trị đối tượng) |
RunMetadata.Builder | |
RunMetadata.Builder | |
RunMetadata.Builder cuối cùng | setUnknownFields (com.google.protobuf.UnknownFieldSet knownFields) |
Phương pháp kế thừa
Phương pháp công cộng
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;
public 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)
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 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 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;
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 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 (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;