RunMetadata.Builder

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
পার্টিশন গ্রাফ যোগ করুন (int সূচক, GraphDef মান)
 Graphs of the partitions executed by executors.
RunMetadata.Builder
পার্টিশন গ্রাফ যোগ করুন ( GraphDef.Builder builderForValue)
 Graphs of the partitions executed by executors.
RunMetadata.Builder
পার্টিশন গ্রাফ যোগ করুন ( গ্রাফডিফ মান)
 Graphs of the partitions executed by executors.
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
RunMetadata.Builder
addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র, বস্তুর মান)
মেটাডেটা চালান
মেটাডেটা চালান
RunMetadata.Builder
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
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
mergeCostGraph ( CostGraphDef মান)
 The cost graph for the computation defined by the run call.
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
setCostGraph ( CostGraphDef মান)
 The cost graph for the computation defined by the run call.
RunMetadata.Builder
setCostGraph ( CostGraphDef.Builder builderForValue)
 The cost graph for the computation defined by the run call.
RunMetadata.Builder
setField (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
সেট পার্টিশন গ্রাফ (int সূচক, GraphDef মান)
 Graphs of the partitions executed by executors.
RunMetadata.Builder
setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র, int সূচক, অবজেক্ট মান)
RunMetadata.Builder
setStepStats ( StepStats.Builder builderForValue)
 Statistics traced for this step.
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 রানমেটাডেটা বিল্ড ()

পাবলিক রানমেটাডেটা বিল্ড আংশিক ()

সর্বজনীন RunMetadata.Builder clear ()

সর্বজনীন RunMetadata.Builder clearCostGraph ()

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

সর্বজনীন RunMetadata.Builder clearField (com.google.protobuf.Descriptors.FieldDescriptor ক্ষেত্র)

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;

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

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;

পাবলিক RunMetadata.Builder ক্লোন ()

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;

সর্বজনীন RunMetadata getDefaultInstanceForType ()

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.অন্যান্য বার্তা)

সর্বজনীন RunMetadata.Builder mergeFrom (com.google.protobuf.CodedInputStream ইনপুট, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

নিক্ষেপ করে
IO ব্যতিক্রম

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;

সর্বজনীন চূড়ান্ত RunMetadata.Builder setUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)