পাবলিক স্ট্যাটিক ফাইনাল ক্লাস RunMetadata.Builder
Metadata output (i.e., non-Tensor) for a single Run() call.Protobuf টাইপ
tensorflow.RunMetadata
পাবলিক পদ্ধতি
RunMetadata.Builder | AddAllFunctionGraphs (Iterable<? RunMetadata.FunctionGraphs > মান প্রসারিত করে) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | AddAllPartitionGraphs (Iterable<? GraphDef > মান প্রসারিত করে) Graphs of the partitions executed by executors. |
RunMetadata.Builder | addFunctionGraphs (int index, RunMetadata.FunctionGraphs মান) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | AddFunctionGraphs (int index, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | addFunctionGraphs ( RunMetadata.FunctionGraphs মান) 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 (int সূচক) 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 | পার্টিশন গ্রাফ যোগ করুন ( GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
RunMetadata.Builder | |
RunMetadata.Builder | পার্টিশন গ্রাফ যোগ করুন (int index, GraphDef. Builder builderForValue) Graphs of the partitions executed by executors. |
GraphDef.Builder | পার্টিশন গ্রাফ বিল্ডার যোগ করুন (int সূচক) Graphs of the partitions executed by executors. |
GraphDef.Builder | পার্টিশন গ্রাফ বিল্ডার যোগ করুন () Graphs of the partitions executed by executors. |
RunMetadata.Builder | addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র, বস্তুর মান) |
মেটাডেটা চালান | নির্মাণ () |
মেটাডেটা চালান | বিল্ড আংশিক () |
RunMetadata.Builder | পরিষ্কার () |
RunMetadata.Builder | সাফ কস্টগ্রাফ () The cost graph for the computation defined by the run call. |
RunMetadata.Builder | clearField (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র) |
RunMetadata.Builder | সাফ ফাংশন গ্রাফ () 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 | সাফ পার্টিশন গ্রাফ () Graphs of the partitions executed by executors. |
RunMetadata.Builder | সাফ ধাপ পরিসংখ্যান () Statistics traced for this step. |
RunMetadata.Builder | ক্লোন () |
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. |
মেটাডেটা চালান | |
চূড়ান্ত স্ট্যাটিক com.google.protobuf.Descriptors.Descriptor | |
com.google.protobuf.Descriptors.Descriptor | |
RunMetadata.FunctionGraphs | getFunctionGraphs (int সূচক) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.FunctionGraphs.Builder | getFunctionGraphsBuilder (int সূচক) This is only populated for graphs that are run as functions in TensorFlow V2. |
তালিকা< 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. |
তালিকা< RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (int সূচক) This is only populated for graphs that are run as functions in TensorFlow V2. |
তালিকা <? RunMetadata.FunctionGraphsOrBuilder > প্রসারিত করে | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
গ্রাফডিফ | GetPartition Graphs (int সূচক) Graphs of the partitions executed by executors. |
GraphDef.Builder | GetPartitionGraphsBuilder (int সূচক) Graphs of the partitions executed by executors. |
তালিকা< GraphDef.Builder > | GetPartitionGraphsBuilderList () Graphs of the partitions executed by executors. |
int | GetPartitionGraphsCount () Graphs of the partitions executed by executors. |
তালিকা< GraphDef > | Get PartitionGraphsList () Graphs of the partitions executed by executors. |
GraphDefOrBuilder | GetPartitionGraphsOrBuilder (int সূচক) Graphs of the partitions executed by executors. |
তালিকা <? GraphDefOrBuilder > প্রসারিত করে | GetPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
ধাপের পরিসংখ্যান | GetStepStats () Statistics traced for this step. |
স্টেপস্ট্যাটস।বিল্ডার | GetStepStatsBuilder () Statistics traced for this step. |
StepStatsOrBuilder | getStepStatsOrBuilder () Statistics traced for this step. |
বুলিয়ান | আছে কস্টগ্রাফ () The cost graph for the computation defined by the run call. |
বুলিয়ান | স্টেপস্ট্যাটস () Statistics traced for this step. |
চূড়ান্ত বুলিয়ান | |
RunMetadata.Builder | |
RunMetadata.Builder | mergeFrom (com.google.protobuf.অন্যান্য বার্তা পাঠান) |
RunMetadata.Builder | mergeFrom (com.google.protobuf.CodedInputStream ইনপুট, com.google.protobuf.ExtensionRegistryLite এক্সটেনশন রেজিস্ট্রি) |
RunMetadata.Builder | |
চূড়ান্ত RunMetadata.Builder | একত্রিত করুন অজানাক্ষেত্র (com.google.protobuf.UnknownFieldSet অজানাক্ষেত্র) |
RunMetadata.Builder | রিমুভ ফাংশনগ্রাফ (int সূচক) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | পার্টিশন গ্রাফ অপসারণ (int সূচক) 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 (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র, বস্তুর মান) |
RunMetadata.Builder | setFunctionGraphs (int index, RunMetadata.FunctionGraphs মান) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | setFunctionGraphs (int index, RunMetadata.FunctionGraphs.Builder builderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
RunMetadata.Builder | সেট পার্টিশন গ্রাফ (int index, GraphDef.Builder builderForValue) Graphs of the partitions executed by executors. |
RunMetadata.Builder | |
RunMetadata.Builder | setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র, int সূচক, অবজেক্ট মান) |
RunMetadata.Builder | |
RunMetadata.Builder | |
চূড়ান্ত RunMetadata.Builder | সেটUnknownFields (com.google.protobuf.UnknownFieldসেট অজানাফিল্ড) |
উত্তরাধিকারসূত্রে প্রাপ্ত পদ্ধতি
পাবলিক পদ্ধতি
সর্বজনীন RunMetadata.Builder addAllFunctionGraphs (Iterable<? RunMetadata.FunctionGraphs > মান প্রসারিত করে)
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;
সর্বজনীন RunMetadata.Builder addAllPartitionGraphs (Iterable<? GraphDef > মান প্রসারিত করে)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন RunMetadata.Builder addFunctionGraphs (int index, RunMetadata.FunctionGraphs মান)
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;
সর্বজনীন RunMetadata.Builder addFunctionGraphs (int index, 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;
সর্বজনীন RunMetadata.Builder addFunctionGraphs ( RunMetadata.FunctionGraphs মান)
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;
সর্বজনীন 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;
সর্বজনীন RunMetadata.FunctionGraphs.Builder addFunctionGraphsBuilder (int index)
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;
সর্বজনীন 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;
সর্বজনীন RunMetadata.Builder addPartitionGraphs (int index, GraphDef মান)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন RunMetadata.Builder addPartitionGraphs ( GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন RunMetadata.Builder add PartitionGraphs ( GraphDef মান)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন RunMetadata.Builder addPartitionGraphs (int index, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
পাবলিক GraphDef.Builder addPartitionGraphsBuilder (int index)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন GraphDef.Builder addPartitionGraphsBuilder ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন RunMetadata.Builder addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র, বস্তুর মান)
সর্বজনীন RunMetadata.Builder clearCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
পাবলিক RunMetadata.Builder clearFunction Graphs ()
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;
পাবলিক RunMetadata.Builder clear Partition Graphs ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন 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;
সর্বজনীন CostGraphDef getCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
সর্বজনীন CostGraphDef.Builder getCostGraphBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
সর্বজনীন CostGraphDefOrBuilder getCostGraphOrBuilder ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
পাবলিক স্ট্যাটিক ফাইনাল com.google.protobuf.Descriptors.Descriptor getDescriptor ()
সর্বজনীন com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()
পাবলিক RunMetadata.FunctionGraphs getFunctionGraphs (int index)
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;
সর্বজনীন RunMetadata.FunctionGraphs.Builder getFunctionGraphsBuilder (int index)
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;
সর্বজনীন তালিকা< 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;
পাবলিক int getFunctionGraphsCount ()
This is only populated for graphs that are run as functions in TensorFlow V2. There will be an entry below for each function that is traced. The main use cases of the post_optimization_graph and the partition_graphs is to give the caller insight into the graphs that were actually run by the runtime. Additional information (such as those in step_stats) will match these graphs. We also include the pre_optimization_graph since it is usually easier to read, and is helpful in situations where the caller wants to get a high level idea of what the built graph looks like (since the various graph optimization passes might change the structure of the graph significantly).
repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
সর্বজনীন তালিকা< 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;
সর্বজনীন RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (int সূচক)
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;
সর্বজনীন তালিকা <? RunMetadata.FunctionGraphsOrBuilder > getFunctionGraphsOrBuilderList () প্রসারিত করে
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;
পাবলিক GraphDef getPartition Graphs (int সূচক)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন GraphDef.Builder getPartitionGraphsBuilder (int index)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন তালিকা< GraphDef.Builder > getPartitionGraphsBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
পাবলিক int getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন তালিকা< GraphDef > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন GraphDefOrBuilder getPartitionGraphsOrBuilder (int সূচক)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন তালিকা <? GraphDefOrBuilder > getPartitionGraphsOrBuilderList () প্রসারিত করে
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
পাবলিক স্টেপস্ট্যাটস 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;
সর্বজনীন 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;
সর্বজনীন 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;
পাবলিক বুলিয়ান আছে কস্টগ্রাফ ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
পাবলিক বুলিয়ান আছে স্টেপস্ট্যাটস ()
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;
সর্বজনীন চূড়ান্ত বুলিয়ান শুরু হয়েছে ()
সর্বজনীন RunMetadata.Builder mergeCostGraph ( CostGraphDef মান)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
সর্বজনীন RunMetadata.Builder mergeFrom (com.google.protobuf.CodedInputStream ইনপুট, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
নিক্ষেপ করে
IO ব্যতিক্রম |
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সর্বজনীন RunMetadata.Builder mergeStepStats ( StepStats মান)
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;
সর্বজনীন চূড়ান্ত RunMetadata.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)
সর্বজনীন RunMetadata.Builder removeFunctionGraphs (int index)
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;
পাবলিক RunMetadata.Builder remove PartitionGraphs (int index)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন RunMetadata.Builder setCostGraph ( CostGraphDef মান)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
সর্বজনীন RunMetadata.Builder setCostGraph ( CostGraphDef.Builder builderForValue)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2;
সর্বজনীন RunMetadata.Builder setField (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র, বস্তুর মান)
সর্বজনীন RunMetadata.Builder setFunctionGraphs (int index, RunMetadata.FunctionGraphs মান)
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;
সর্বজনীন RunMetadata.Builder setFunctionGraphs (int index, 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;
সর্বজনীন RunMetadata.Builder setPartitionGraphs (int index, GraphDef.Builder builderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন RunMetadata.Builder setPartitionGraphs (int index, GraphDef মান)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;
সর্বজনীন RunMetadata.Builder setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র, int সূচক, অবজেক্ট মান)
সর্বজনীন 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;
সর্বজনীন RunMetadata.Builder setStepStats ( StepStats মান)
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;