RunMetadata

RunMetadata kelas akhir publik

 Metadata output (i.e., non-Tensor) for a single Run() call.
 
Tipe protobuf tensorflow.RunMetadata

Kelas Bersarang

kelas Jalankan Metadata.Builder
 Metadata output (i.e., non-Tensor) for a single Run() call. 
kelas JalankanMetadata.FunctionGraphs Tipe protobuf tensorflow.RunMetadata.FunctionGraphs
antarmuka JalankanMetadata.FunctionGraphsOrBuilder

Konstanta

ke dalam COST_GRAPH_FIELD_NUMBER
ke dalam FUNCTION_GRAPHS_FIELD_NUMBER
ke dalam PARTITION_GRAPHS_FIELD_NUMBER
ke dalam STEP_STATS_FIELD_NUMBER

Metode Publik

boolean
sama dengan (Objek objek)
BiayaGraphDef
dapatkanCostGraph ()
 The cost graph for the computation defined by the run call.
CostGraphDefOrBuilder
dapatkanCostGraphOrBuilder ()
 The cost graph for the computation defined by the run call.
RunMetadata statis
Jalankan Metadata
com.google.protobuf.Descriptors.Descriptor statis terakhir
JalankanMetadata.FunctionGraphs
getFunctionGraphs (indeks int)
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
ke dalam
dapatkanFunctionGraphsCount ()
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
Daftar< JalankanMetadata.FunctionGraphs >
dapatkanFunctionGraphsList ()
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
JalankanMetadata.FunctionGraphsOrBuilder
getFunctionGraphsOrBuilder (indeks int)
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
Daftar<? memperluas RunMetadata.FunctionGraphsOrBuilder >
dapatkanFunctionGraphsOrBuilderList ()
 This is only populated for graphs that are run as functions in TensorFlow
 V2.
GrafikDef
getPartitionGraphs (indeks int)
 Graphs of the partitions executed by executors.
ke dalam
dapatkanPartitionGraphsCount ()
 Graphs of the partitions executed by executors.
Daftar< GraphDef >
dapatkanPartitionGraphsList ()
 Graphs of the partitions executed by executors.
GraphDefOrBuilder
getPartitionGraphsOrBuilder (indeks int)
 Graphs of the partitions executed by executors.
Daftar<? memperluas GraphDefOrBuilder >
getPartitionGraphsOrBuilderList ()
 Graphs of the partitions executed by executors.
ke dalam
Statistik Langkah
dapatkanStepStats ()
 Statistics traced for this step.
StepStatsOrBuilder
dapatkanStepStatsOrBuilder ()
 Statistics traced for this step.
final com.google.protobuf.UnknownFieldSet
boolean
hasCostGraph ()
 The cost graph for the computation defined by the run call.
boolean
hasStepStats ()
 Statistics traced for this step.
ke dalam
boolean terakhir
RunMetadata.Builder statis
newBuilder (prototipe RunMetadata )
RunMetadata.Builder statis
Jalankan Metadata.Builder
RunMetadata statis
parseDelimitedFrom (masukan Aliran Masukan)
RunMetadata statis
parseDelimitedFrom (masukan InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RunMetadata statis
parseFrom (data ByteBuffer)
RunMetadata statis
parseFrom (com.google.protobuf.CodedInputStream masukan, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RunMetadata statis
parseFrom (data ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RunMetadata statis
parseFrom (com.google.protobuf.CodedInputStream masukan)
RunMetadata statis
parseFrom (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RunMetadata statis
parseFrom (com.google.protobuf.ByteString data)
RunMetadata statis
parseFrom (masukan InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RunMetadata statis
parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statis
Jalankan Metadata.Builder
ruang kosong
writeTo (com.google.protobuf.CodedOutputStream keluaran)

Metode Warisan

Konstanta

int akhir statis publik COST_GRAPH_FIELD_NUMBER

Nilai Konstan: 2

int akhir statis publik FUNCTION_GRAPHS_FIELD_NUMBER

Nilai Konstan: 4

int final statis publik PARTITION_GRAPHS_FIELD_NUMBER

Nilai Konstan: 3

int akhir statis publik STEP_STATS_FIELD_NUMBER

Nilai Konstan: 1

Metode Publik

boolean publik sama (Obj objek)

CostGraphDef publik getCostGraph ()

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

CostGraphDefOrBuilder publik getCostGraphOrBuilder ()

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

RunMetadata statis publik getDefaultInstance ()

RunMetadata publik getDefaultInstanceForType ()

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor ()

RunMetadata.FunctionGraphs publik getFunctionGraphs (indeks 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;

int publik 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;

Daftar publik< 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;

publik RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (int indeks)

 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;

Daftar Publik<? memperluas 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;

publik dapatkanParserForType ()

publik GraphDef getPartitionGraphs (int indeks)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

int publik getPartitionGraphsCount ()

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

Daftar publik< GraphDef > getPartitionGraphsList ()

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

publik GraphDefOrBuilder getPartitionGraphsOrBuilder (int indeks)

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

Daftar Publik<? memperluas GraphDefOrBuilder > getPartitionGraphsOrBuilderList ()

 Graphs of the partitions executed by executors.
 
repeated .tensorflow.GraphDef partition_graphs = 3;

publik int getSerializedSize ()

StepStats publik 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;

StepStatsOrBuilder publik 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;

public final com.google.protobuf.UnknownFieldSet getUnknownFields ()

boolean publik hasCostGraph ()

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

boolean publik 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;

kode hash int publik ()

boolean akhir publik diinisialisasi ()

RunMetadata.Builder statis publik newBuilder (prototipe RunMetadata )

RunMetadata.Builder statis publik newBuilder ()

publik RunMetadata.Builder newBuilderForType ()

parseDelimitedFrom RunMetadata statis publik (input InputStream)

Melempar
Pengecualian IO

parseDelimitedFrom RunMetadata statis publik (input InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
Pengecualian IO

parseFrom RunMetadata statis publik (data ByteBuffer)

Melempar
ProtokolBufferException Tidak Valid

parseFrom RunMetadata statis publik (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
Pengecualian IO

parseFrom RunMetadata statis publik (data ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
ProtokolBufferException Tidak Valid

parseFrom RunMetadata statis publik (com.google.protobuf.CodedInputStream masukan)

Melempar
Pengecualian IO

parseFrom RunMetadata statis publik (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
ProtokolBufferException Tidak Valid

parseFrom RunMetadata statis publik (com.google.protobuf.ByteString data)

Melempar
ProtokolBufferException Tidak Valid

parseFrom RunMetadata statis publik (input InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
Pengecualian IO

parseFrom RunMetadata statis publik (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
ProtokolBufferException Tidak Valid

statis publik pengurai ()

RunMetadata.Builder toBuilder publik ()

public void writeTo (com.google.protobuf.CodedOutputStream keluaran)

Melempar
Pengecualian IO