सार्वजनिक स्थैतिक अंतिम वर्ग RunMetadata.Builder
Metadata output (i.e., non-Tensor) for a single Run() call.प्रोटोबफ़ प्रकार
tensorflow.RunMetadata सार्वजनिक तरीके
| रनमेटाडाटा.बिल्डर | addAllFunctionGraphs (Iterable<? RunMetadata.FunctionGraphs > मान बढ़ाता है) This is only populated for graphs that are run as functions in TensorFlow V2. |
| रनमेटाडाटा.बिल्डर | addAllPartitionGraphs (Iterable<? GraphDef > मान बढ़ाता है) Graphs of the partitions executed by executors. |
| रनमेटाडाटा.बिल्डर | addFunctionGraphs (int अनुक्रमणिका, RunMetadata.FunctionGraphs मान) This is only populated for graphs that are run as functions in TensorFlow V2. |
| रनमेटाडाटा.बिल्डर | addFunctionGraphs (int इंडेक्स, RunMetadata.FunctionGraphs.Builder BuilderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| रनमेटाडाटा.बिल्डर | addFunctionGraphs ( RunMetadata.FunctionGraphs मान) This is only populated for graphs that are run as functions in TensorFlow V2. |
| रनमेटाडाटा.बिल्डर | addFunctionGraphs ( RunMetadata.FunctionGraphs.Builder BuilderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | addFunctionGraphsBuilder (int अनुक्रमणिका) 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. |
| रनमेटाडाटा.बिल्डर | |
| रनमेटाडाटा.बिल्डर | addPartitionGraphs ( GraphDef.Builder BuilderForValue) Graphs of the partitions executed by executors. |
| रनमेटाडाटा.बिल्डर | |
| रनमेटाडाटा.बिल्डर | addPartitionGraphs (int अनुक्रमणिका, GraphDef.Builder BuilderForValue) Graphs of the partitions executed by executors. |
| ग्राफ़डेफ़.बिल्डर | addPartitionGraphsBuilder (int अनुक्रमणिका) Graphs of the partitions executed by executors. |
| ग्राफ़डेफ़.बिल्डर | addPartitionGraphsBuilder () Graphs of the partitions executed by executors. |
| रनमेटाडाटा.बिल्डर | addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, ऑब्जेक्ट मान) |
| रनमेटाडेटा | निर्माण () |
| रनमेटाडेटा | बिल्डआंशिक () |
| रनमेटाडेटा.बिल्डर | स्पष्ट () |
| रनमेटाडेटा.बिल्डर | क्लियरकॉस्टग्राफ () The cost graph for the computation defined by the run call. |
| रनमेटाडेटा.बिल्डर | क्लियरफ़ील्ड (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड) |
| रनमेटाडेटा.बिल्डर | क्लियरफंक्शनग्राफ () This is only populated for graphs that are run as functions in TensorFlow V2. |
| रनमेटाडेटा.बिल्डर | ClearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof) |
| रनमेटाडेटा.बिल्डर | स्पष्टविभाजनग्राफ () Graphs of the partitions executed by executors. |
| रनमेटाडेटा.बिल्डर | क्लीयरस्टेपस्टैट्स () Statistics traced for this step. |
| रनमेटाडेटा.बिल्डर | क्लोन () |
| कॉस्टग्राफडिफ़ | getCostGraph () The cost graph for the computation defined by the run call. |
| कॉस्टग्राफ़डेफ़.बिल्डर | getCostGraphBuilder () The cost graph for the computation defined by the run call. |
| कॉस्टग्राफडिफऑरबिल्डर | getCostGraphOrBuilder () The cost graph for the computation defined by the run call. |
| रनमेटाडेटा | |
| अंतिम स्थिर com.google.protobuf.Descriptors.Descriptor | |
| com.google.protobuf.Descriptors.Descriptor | |
| RunMetadata.FunctionGraphs | getFunctionGraphs (int अनुक्रमणिका) This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphs.Builder | getFunctionGraphsBuilder (int अनुक्रमणिका) This is only populated for graphs that are run as functions in TensorFlow V2. |
| सूची < RunMetadata.FunctionGraphs.Builder > | getFunctionGraphsBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| int यहाँ | getFunctionGraphsCount () This is only populated for graphs that are run as functions in TensorFlow V2. |
| सूची < RunMetadata.FunctionGraphs > | getFunctionGraphsList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| RunMetadata.FunctionGraphsOrBuilder | getFunctionGraphsOrBuilder (इंट इंडेक्स) This is only populated for graphs that are run as functions in TensorFlow V2. |
| सूची<? RunMetadata.FunctionGraphsOrBuilder > का विस्तार करता है | getFunctionGraphsOrBuilderList () This is only populated for graphs that are run as functions in TensorFlow V2. |
| ग्राफ़डेफ़ | getPartitionGraphs (int अनुक्रमणिका) Graphs of the partitions executed by executors. |
| ग्राफ़डेफ़.बिल्डर | getPartitionGraphsBuilder (int अनुक्रमणिका) Graphs of the partitions executed by executors. |
| सूची < ग्राफ़डेफ़.बिल्डर > | getPartitionGraphsBuilderList () Graphs of the partitions executed by executors. |
| int यहाँ | GetPartitionGraphsCount () Graphs of the partitions executed by executors. |
| सूची < ग्राफ़डेफ़ > | getPartitionGraphsList () Graphs of the partitions executed by executors. |
| ग्राफ़डेफ़ऑरबिल्डर | getPartitionGraphsOrBuilder (इंट इंडेक्स) Graphs of the partitions executed by executors. |
| सूची<? GraphDefOrBuilder > का विस्तार करता है | getPartitionGraphsOrBuilderList () Graphs of the partitions executed by executors. |
| स्टेपस्टैट्स | getStepStats () Statistics traced for this step. |
| स्टेपस्टैट्स.बिल्डर | getStepStatsBuilder () Statistics traced for this step. |
| स्टेपस्टैट्सऑरबिल्डर | getStepStatsOrBuilder () Statistics traced for this step. |
| बूलियन | हैकॉस्टग्राफ () The cost graph for the computation defined by the run call. |
| बूलियन | हैस्टेपस्टैट्स () Statistics traced for this step. |
| अंतिम बूलियन | |
| रनमेटाडेटा.बिल्डर | |
| रनमेटाडेटा.बिल्डर | मर्जफ्रॉम (com.google.protobuf.Message अन्य) |
| रनमेटाडेटा.बिल्डर | मर्जफ्रॉम (com.google.protobuf.CodedInputStream इनपुट, com.google.protobuf.ExtensionRegistryLite एक्सटेंशनरजिस्ट्री) |
| रनमेटाडेटा.बिल्डर | |
| अंतिम RunMetadata.Builder | मर्जअज्ञातफ़ील्ड्स (com.google.protobuf.UnknownFieldSet अज्ञातफ़ील्ड्स) |
| रनमेटाडेटा.बिल्डर | रिमूवफंक्शनग्राफ (इंट इंडेक्स) This is only populated for graphs that are run as functions in TensorFlow V2. |
| रनमेटाडेटा.बिल्डर | रिमूवपार्टिशनग्राफ़्स (इंट इंडेक्स) Graphs of the partitions executed by executors. |
| रनमेटाडेटा.बिल्डर | |
| रनमेटाडेटा.बिल्डर | सेटकॉस्टग्राफ ( CostGraphDef.Builder BuilderForValue) The cost graph for the computation defined by the run call. |
| रनमेटाडेटा.बिल्डर | सेटफ़ील्ड (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, ऑब्जेक्ट मान) |
| रनमेटाडेटा.बिल्डर | setFunctionGraphs (int अनुक्रमणिका, RunMetadata.FunctionGraphs मान) This is only populated for graphs that are run as functions in TensorFlow V2. |
| रनमेटाडेटा.बिल्डर | सेटफंक्शनग्राफ (int इंडेक्स, RunMetadata.FunctionGraphs.Builder BuilderForValue) This is only populated for graphs that are run as functions in TensorFlow V2. |
| रनमेटाडेटा.बिल्डर | सेटपार्टिशनग्राफ़्स (इंट इंडेक्स, ग्राफ़डेफ़.बिल्डर बिल्डरफॉरवैल्यू) Graphs of the partitions executed by executors. |
| रनमेटाडेटा.बिल्डर | |
| रनमेटाडेटा.बिल्डर | setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, इंट इंडेक्स, ऑब्जेक्ट वैल्यू) |
| रनमेटाडेटा.बिल्डर | |
| रनमेटाडेटा.बिल्डर | |
| अंतिम RunMetadata.Builder | अज्ञात फ़ील्ड सेट करें (com.google.protobuf. अज्ञात फ़ील्ड सेट अज्ञात फ़ील्ड) |
विरासत में मिली विधियाँ
सार्वजनिक तरीके
सार्वजनिक RunMetadata.Builder addAllFunctionGraphs (Iterable<? RunMetadata.FunctionGraphs > मान बढ़ाता है)
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; सार्वजनिक RunMetadata.Builder addAllPartitionGraphs (Iterable<? विस्तार GraphDef > मान)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक RunMetadata.Builder addFunctionGraphs (int अनुक्रमणिका, RunMetadata.FunctionGraphs मान)
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; सार्वजनिक 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; सार्वजनिक RunMetadata.Builder addFunctionGraphs ( RunMetadata.FunctionGraphs मान)
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; सार्वजनिक 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; सार्वजनिक RunMetadata.FunctionGraphs.Builder addFunctionGraphsBuilder (int अनुक्रमणिका)
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; सार्वजनिक 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; सार्वजनिक RunMetadata.Builder addPartitionGraphs (int अनुक्रमणिका, GraphDef मान)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3;सार्वजनिक RunMetadata.Builder addPartitionGraphs ( GraphDef.Builder BuilderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक RunMetadata.Builder addPartitionGraphs ( ग्राफडिफ़ मान)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक RunMetadata.Builder addPartitionGraphs (int अनुक्रमणिका, GraphDef.Builder BuilderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक GraphDef.Builder addPartitionGraphsBuilder (int अनुक्रमणिका)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक GraphDef.Builder addPartitionGraphsBuilder ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक RunMetadata.Builder addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, ऑब्जेक्ट मान)
सार्वजनिक RunMetadata.Builder ClearCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; सार्वजनिक RunMetadata.Builder क्लियरफंक्शनग्राफ ()
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; सार्वजनिक RunMetadata.Builder क्लियरपार्टिशनग्राफ ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक 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; सार्वजनिक कॉस्टग्राफडिफ गेटकॉस्टग्राफ ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; सार्वजनिक कॉस्टग्राफडिफ.बिल्डर गेटकॉस्टग्राफबिल्डर ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; सार्वजनिक कॉस्टग्राफडिफऑरबिल्डर गेटकॉस्टग्राफऑरबिल्डर ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; सार्वजनिक स्थैतिक अंतिम com.google.protobuf.Descriptors.Descriptor getDescriptor ()
सार्वजनिक com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()
सार्वजनिक RunMetadata.FunctionGraphs getFunctionGraphs (int अनुक्रमणिका)
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; सार्वजनिक RunMetadata.FunctionGraphs.Builder getFunctionGraphsBuilder (int अनुक्रमणिका)
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; सार्वजनिक सूची < 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; सार्वजनिक 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; सार्वजनिक सूची < 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; सार्वजनिक RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder (int अनुक्रमणिका)
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; सार्वजनिक सूची<? RunMetadata.FunctionGraphsOrBuilder > getFunctionGraphsOrBuilderList () का विस्तार करता है
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; सार्वजनिक ग्राफडिफ़ getPartitionGraphs (इंट इंडेक्स)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक GraphDef.Builder getPartitionGraphsBuilder (int अनुक्रमणिका)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक सूची < ग्राफडिफ़.बिल्डर > getPartitionGraphsBuilderList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक पूर्णांक getPartitionGraphsCount ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक सूची < ग्राफ़डिफ़ > getPartitionGraphsList ()
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक GraphDefOrBuilder getPartitionGraphsOrBuilder (int अनुक्रमणिका)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक सूची<? GraphDefOrBuilder > getPartitionGraphsOrBuilderList () का विस्तार करता है
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक स्टेपस्टैट्स 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; सार्वजनिक स्टेपस्टैट्स.बिल्डर 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; सार्वजनिक स्टेपस्टैट्सऑरबिल्डर 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; सार्वजनिक बूलियन hasCostGraph ()
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; सार्वजनिक बूलियन 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; सार्वजनिक अंतिम बूलियन आरंभीकृत है ()
सार्वजनिक RunMetadata.Builder mergeCostGraph ( CostGraphDef मान)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; सार्वजनिक RunMetadata.Builder mergeFrom (com.google.protobuf.CodedInputStream इनपुट, com.google.protobuf.ExtensionRegistryLite एक्सटेंशनरजिस्ट्री)
फेंकता
| आईओ अपवाद |
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सार्वजनिक RunMetadata.Builder mergeStepStats ( स्टेपस्टैट्स मान)
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; सार्वजनिक अंतिम RunMetadata.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet अज्ञातफील्ड्स)
सार्वजनिक रनमेटाडाटा.बिल्डर रिमूवफंक्शनग्राफ (इंट इंडेक्स)
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; सार्वजनिक रनमेटाडेटा.बिल्डर रिमूवपार्टिशनग्राफ़्स (इंट इंडेक्स)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक RunMetadata.Builder setCostGraph ( CostGraphDef मान)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; सार्वजनिक RunMetadata.Builder setCostGraph ( CostGraphDef.Builder BuilderForValue)
The cost graph for the computation defined by the run call.
.tensorflow.CostGraphDef cost_graph = 2; सार्वजनिक RunMetadata.Builder setField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, ऑब्जेक्ट मान)
सार्वजनिक RunMetadata.Builder setFunctionGraphs (int अनुक्रमणिका, RunMetadata.FunctionGraphs मान)
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; सार्वजनिक RunMetadata.Builder setFunctionGraphs (int अनुक्रमणिका, 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; सार्वजनिक RunMetadata.Builder setPartitionGraphs (int अनुक्रमणिका, GraphDef.Builder BuilderForValue)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक RunMetadata.Builder setPartitionGraphs (int अनुक्रमणिका, GraphDef मान)
Graphs of the partitions executed by executors.
repeated .tensorflow.GraphDef partition_graphs = 3; सार्वजनिक RunMetadata.Builder setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, int अनुक्रमणिका, ऑब्जेक्ट मान)
सार्वजनिक 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; सार्वजनिक RunMetadata.Builder सेटस्टेपस्टैट्स ( स्टेपस्टैट्स मान)
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;