RunMetadataOrBuilder

পাবলিক ইন্টারফেস RunMetadataOrBuilder

পরিচিত পরোক্ষ উপশ্রেণী

পাবলিক পদ্ধতি

বিমূর্ত CostGraphDef	getCostGraph () The cost graph for the computation defined by the run call.
বিমূর্ত CostGraphDefOrBuilder	getCostGraphOrBuilder () The cost graph for the computation defined by the run call.
বিমূর্ত RunMetadata.FunctionGraphs	getFunctionGraphs (int সূচক) This is only populated for graphs that are run as functions in TensorFlow V2.
বিমূর্ত int	getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2.
বিমূর্ত তালিকা< RunMetadata.FunctionGraphs >	getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2.
বিমূর্ত RunMetadata.FunctionGraphsOrBuilder	getFunctionGraphsOrBuilder (int সূচক) This is only populated for graphs that are run as functions in TensorFlow V2.
বিমূর্ত তালিকা<? RunMetadata.FunctionGraphsOrBuilder > প্রসারিত করে	getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2.
বিমূর্ত গ্রাফডিফ	GetPartition Graphs (int সূচক) Graphs of the partitions executed by executors.
বিমূর্ত int	GetPartitionGraphsCount () Graphs of the partitions executed by executors.
বিমূর্ত তালিকা< GraphDef >	Get PartitionGraphsList () Graphs of the partitions executed by executors.
বিমূর্ত GraphDefOrBuilder	GetPartitionGraphsOrBuilder (int সূচক) Graphs of the partitions executed by executors.
বিমূর্ত তালিকা<? GraphDefOrBuilder > প্রসারিত করে	GetPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors.
বিমূর্ত ধাপের পরিসংখ্যান	GetStepStats () Statistics traced for this step.
বিমূর্ত StepStatsOrBuilder	GetStepStatsOrBuilder () Statistics traced for this step.
বিমূর্ত বুলিয়ান	আছে কস্টগ্রাফ () The cost graph for the computation defined by the run call.
বিমূর্ত বুলিয়ান	স্টেপস্ট্যাটস () Statistics traced for this step.

পাবলিক পদ্ধতি

সর্বজনীন বিমূর্ত CostGraphDef getCostGraph ()

 The cost graph for the computation defined by the run call.

.tensorflow.CostGraphDef cost_graph = 2;

সর্বজনীন বিমূর্ত CostGraphDefOrBuilder getCostGraphOrBuilder ()

 The cost graph for the computation defined by the run call.

.tensorflow.CostGraphDef cost_graph = 2;

সর্বজনীন বিমূর্ত 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;

পাবলিক বিমূর্ত 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 বিমূর্ত 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 বিমূর্ত RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (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 বিমূর্ত 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;