RewriterConfigOrBuilder

общедоступный интерфейс RewriterConfigOrBuilder

Известные косвенные подклассы RewriterConfig , RewriterConfig.Builder RewriterConfig Graph rewriting is experimental and subject to change, not covered by any API stability guarantees.  RewriterConfig.Builder Graph rewriting is experimental and subject to change, not covered by any API stability guarantees.

Публичные методы

абстрактный RewriterConfig.Toggle	getАрифметическаяОптимизация () Arithmetic optimizations (default is ON) e.g.
абстрактный int	getАрифметическоеОптимизационногоЗначения () Arithmetic optimizations (default is ON) e.g.
абстрактный RewriterConfig.Toggle	getAutoMixedPrecision () Optimize data types for CUDA (default is OFF).
абстрактный RewriterConfig.Toggle	getAutoMixedPrecisionMkl () Optimize data types for MKL (default is OFF).
абстрактный int	getAutoMixedPrecisionMklValue () Optimize data types for MKL (default is OFF).
абстрактный int	getAutoMixedPrecisionValue () Optimize data types for CUDA (default is OFF).
абстрактные параметры AutoParallelOptions	getAutoParallel () Configures AutoParallel optimization passes either through the meta-optimizer or when manually specified through the optimizers field.
абстрактный AutoParallelOptionsOrBuilder	getAutoParallelOrBuilder () Configures AutoParallel optimization passes either through the meta-optimizer or when manually specified through the optimizers field.
абстрактный RewriterConfig.Toggle	getCommonSubgraphElimination () Common subgraph elimination (default is ON) e.g.
абстрактный int	getCommonSubgraphEliminationValue () Common subgraph elimination (default is ON) e.g.
абстрактный RewriterConfig.Toggle	getConstantFolding () Fold constants (default is ON) Statically infer the value of tensors when possible, and materialize the result using constants.
абстрактный int	getConstantFoldingValue () Fold constants (default is ON) Statically infer the value of tensors when possible, and materialize the result using constants.
абстрактный RewriterConfig.CpuLayout	getCpuLayoutConversion () CPU Conversion settings between NHCW and NCHW.
абстрактный int	getCpuLayoutConversionValue () CPU Conversion settings between NHCW and NCHW.
абстрактный RewriterConfig.CustomGraphOptimizer	getCustomOptimizers (индекс int) list of CustomGraphOptimizers to apply.
абстрактный int	getCustomOptimizersCount () list of CustomGraphOptimizers to apply.
абстрактный список < RewriterConfig.CustomGraphOptimizer >	getCustomOptimizersList () list of CustomGraphOptimizers to apply.
абстрактный RewriterConfig.CustomGraphOptimizerOrBuilder	getCustomOptimizersOrBuilder (индекс int) list of CustomGraphOptimizers to apply.
абстрактный список<? расширяет RewriterConfig.CustomGraphOptimizerOrBuilder >	getCustomOptimizersOrBuilderList () list of CustomGraphOptimizers to apply.
абстрактный RewriterConfig.Toggle	getDebugStripper () Strips debug-related nodes from the graph (off by default).
абстрактный int	getDebugStripperValue () Strips debug-related nodes from the graph (off by default).
абстрактный RewriterConfig.Toggle	getDependencyOptimization () Control dependency optimizations (default is ON).
абстрактный int	getDependencyOptimizationValue () Control dependency optimizations (default is ON).
абстрактное логическое значение	getDisableMetaOptimizer () Disable the entire meta optimizer (off by default).
абстрактное логическое значение	getDisableModelPruning () If true, don't remove unnecessary ops from the graph bool disable_model_pruning = 2;
абстрактное логическое значение	getExperimentalDisableCompressedTensorOptimization () Disable optimizations that assume compressed tensors.
абстрактное логическое значение	getFailOnOptimizerErrors () If true, any optimization pass failing will cause the MetaOptimizer to stop with an error.
абстрактный RewriterConfig.Toggle	getFunctionOptimization () Function optimizations (default is ON).
абстрактный int	getFunctionOptimizationValue () Function optimizations (default is ON).
абстрактный RewriterConfig.Toggle	getImplementationSelector () Enable the swap of kernel implementations based on the device placement (default is ON).
абстрактный int	getImplementationSelectorValue () Enable the swap of kernel implementations based on the device placement (default is ON).
абстрактный VerifierConfig	getInterOptimizerVerifierConfig () VerifierConfig specifying the verifiers to be run after every optimizer.
абстрактный VerifierConfigOrBuilder	getInterOptimizerVerifierConfigOrBuilder () VerifierConfig specifying the verifiers to be run after every optimizer.
абстрактный RewriterConfig.Toggle	getLayoutOptimizer () Optimize tensor layouts (default is ON) e.g.
абстрактный int	getLayoutOptimizerValue () Optimize tensor layouts (default is ON) e.g.
абстрактный RewriterConfig.Toggle	getLoopOptimization () Loop optimizations (default is ON).
абстрактный int	getLoopOptimizationValue () Loop optimizations (default is ON).
абстрактный RewriterConfig.MemOptType	getMemoryOptimization () Configures memory optimization passes through the meta-optimizer.
абстрактный int	getMemoryOptimizationValue () Configures memory optimization passes through the meta-optimizer.
абстрактная строка	getMemoryOptimizerTargetNodeNameScope () A node name scope for node names which are valid outputs of recomputations.
абстрактный com.google.protobuf.ByteString	getMemoryOptimizerTargetNodeNameScopeBytes () A node name scope for node names which are valid outputs of recomputations.
абстрактный RewriterConfig.NumIterationsType	getMetaOptimizerIterations () Controls how many times we run the optimizers in meta optimizer (default is once).
абстрактный int	getMetaOptimizerIterationsValue () Controls how many times we run the optimizers in meta optimizer (default is once).
абстрактный длинный	getMetaOptimizerTimeoutMs () Maximum number of milliseconds to spend optimizing a single graph before timing out.
абстрактный int	getMinGraphNodes () The minimum number of nodes in a graph to optimizer.
абстрактная строка	getOptimizers (индекс int) If non-empty, will use this as an alternative way to specify a list of optimizations to turn on and the order of the optimizations (replacing the meta-optimizer).
абстрактный com.google.protobuf.ByteString	getOptimizersBytes (индекс целого числа) If non-empty, will use this as an alternative way to specify a list of optimizations to turn on and the order of the optimizations (replacing the meta-optimizer).
абстрактный int	getOptimizersCount () If non-empty, will use this as an alternative way to specify a list of optimizations to turn on and the order of the optimizations (replacing the meta-optimizer).
абстрактный список<String>	получитьСписокОптимизаторов () If non-empty, will use this as an alternative way to specify a list of optimizations to turn on and the order of the optimizations (replacing the meta-optimizer).
абстрактный RewriterConfig.Toggle	getPinToHostOptimization () Force small ops onto the CPU (default is OFF).
абстрактный int	getPinToHostOptimizationValue () Force small ops onto the CPU (default is OFF).
абстрактный VerifierConfig	getPostOptimizationVerifierConfig () VerifierConfig specifying the verifiers to be run at the end, after all optimizers have run.
абстрактный VerifierConfigOrBuilder	getPostOptimizationVerifierConfigOrBuilder () VerifierConfig specifying the verifiers to be run at the end, after all optimizers have run.
абстрактный RewriterConfig.Toggle	getRemapping () Remapping (default is ON) Remap subgraphs onto more efficient implementations.
абстрактный int	getRemappingValue () Remapping (default is ON) Remap subgraphs onto more efficient implementations.
абстрактный RewriterConfig.Toggle	getScopedAllocatorOptimization () Try to allocate some independent Op outputs contiguously in order to merge or eliminate downstream Ops (off by default).
абстрактный int	getScopedAllocatorOptimizationValue () Try to allocate some independent Op outputs contiguously in order to merge or eliminate downstream Ops (off by default).
абстрактные параметры ScopedAllocatorOptions	getScopedAllocatorOpts () .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
абстрактный ScopedAllocatorOptionsOrBuilder	getScopedAllocatorOptsOrBuilder () .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
абстрактный RewriterConfig.Toggle	getShapeOptimization () Shape optimizations (default is ON) Simplify computations made on shapes.
абстрактный int	getShapeOptimizationValue () Shape optimizations (default is ON) Simplify computations made on shapes.
абстрактное логическое значение	имеетАвтоПараллель () Configures AutoParallel optimization passes either through the meta-optimizer or when manually specified through the optimizers field.
абстрактное логическое значение	hasInterOptimizerVerifierConfig () VerifierConfig specifying the verifiers to be run after every optimizer.
абстрактное логическое значение	hasPostOptimizationVerifierConfig () VerifierConfig specifying the verifiers to be run at the end, after all optimizers have run.
абстрактное логическое значение	hasScopedAllocatorOpts () .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

Публичные методы

публичный абстрактный RewriterConfig.Toggle getArithmeticOptimization ()

 Arithmetic optimizations (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

.tensorflow.RewriterConfig.Toggle arithmetic_optimization = 7;

public Abstract int getArithmeticOptimizationValue ()

 Arithmetic optimizations (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

.tensorflow.RewriterConfig.Toggle arithmetic_optimization = 7;

публичный абстрактный RewriterConfig.Toggle getAutoMixedPrecision ()

 Optimize data types for CUDA (default is OFF).
 This will try to use float16 on GPU which is faster.
 Note that this can change the numerical stability of the graph and may
 require the use of loss scaling to maintain model convergence.
 

.tensorflow.RewriterConfig.Toggle auto_mixed_precision = 23;

публичный абстрактный RewriterConfig.Toggle getAutoMixedPrecisionMkl ()

 Optimize data types for MKL (default is OFF).
 This will try to use bfloat16 on CPUs, which is faster.
 Note that this can change the numerical stability of the graph.
 

.tensorflow.RewriterConfig.Toggle auto_mixed_precision_mkl = 25;

общедоступный абстрактный int getAutoMixedPrecisionMklValue ()

 Optimize data types for MKL (default is OFF).
 This will try to use bfloat16 on CPUs, which is faster.
 Note that this can change the numerical stability of the graph.
 

.tensorflow.RewriterConfig.Toggle auto_mixed_precision_mkl = 25;

общедоступный абстрактный int getAutoMixedPrecisionValue ()

 Optimize data types for CUDA (default is OFF).
 This will try to use float16 on GPU which is faster.
 Note that this can change the numerical stability of the graph and may
 require the use of loss scaling to maintain model convergence.
 

.tensorflow.RewriterConfig.Toggle auto_mixed_precision = 23;

общедоступные абстрактные AutoParallelOptions getAutoParallel ()

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
 

.tensorflow.AutoParallelOptions auto_parallel = 5;

публичный абстрактный AutoParallelOptionsOrBuilder getAutoParallelOrBuilder ()

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
 

.tensorflow.AutoParallelOptions auto_parallel = 5;

публичный абстрактный RewriterConfig.Toggle getCommonSubgraphElimination ()

 Common subgraph elimination (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

.tensorflow.RewriterConfig.Toggle common_subgraph_elimination = 24;

public Abstract int getCommonSubgraphEliminationValue ()

 Common subgraph elimination (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

.tensorflow.RewriterConfig.Toggle common_subgraph_elimination = 24;

публичный абстрактный RewriterConfig.Toggle getConstantFolding ()

 Fold constants (default is ON)
 Statically infer the value of tensors when possible, and materialize the
 result using constants.
 

.tensorflow.RewriterConfig.Toggle constant_folding = 3;

общедоступный абстрактный int getConstantFoldingValue ()

 Fold constants (default is ON)
 Statically infer the value of tensors when possible, and materialize the
 result using constants.
 

.tensorflow.RewriterConfig.Toggle constant_folding = 3;

публичный абстрактный RewriterConfig.CpuLayout getCpuLayoutConversion ()

 CPU Conversion settings between NHCW and NCHW.
 

.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

общедоступный абстрактный int getCpuLayoutConversionValue ()

 CPU Conversion settings between NHCW and NCHW.
 

.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

общедоступный абстрактный RewriterConfig.CustomGraphOptimizer getCustomOptimizers (индекс int)

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

общедоступный абстрактный int getCustomOptimizersCount ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

общедоступный абстрактный список < RewriterConfig.CustomGraphOptimizer > getCustomOptimizersList ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

общедоступный абстрактный RewriterConfig.CustomGraphOptimizerOrBuilder getCustomOptimizersOrBuilder (индекс int)

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

публичный абстрактный список<? расширяет RewriterConfig.CustomGraphOptimizerOrBuilder > getCustomOptimizersOrBuilderList ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

публичный абстрактный RewriterConfig.Toggle getDebugStripper ()

 Strips debug-related nodes from the graph (off by default).
 

.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

общедоступный абстрактный int getDebugStripperValue ()

 Strips debug-related nodes from the graph (off by default).
 

.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

публичный абстрактный RewriterConfig.Toggle getDependencyOptimization ()

 Control dependency optimizations (default is ON).
 Remove redundant control dependencies, which may enable other optimization.
 

.tensorflow.RewriterConfig.Toggle dependency_optimization = 8;

общедоступный абстрактный int getDependencyOptimizationValue ()

 Control dependency optimizations (default is ON).
 Remove redundant control dependencies, which may enable other optimization.
 

.tensorflow.RewriterConfig.Toggle dependency_optimization = 8;

общедоступное абстрактное логическое значение getDisableMetaOptimizer ()

 Disable the entire meta optimizer (off by default).
 

bool disable_meta_optimizer = 19;

общедоступное абстрактное логическое значение getDisableModelPruning ()

 If true, don't remove unnecessary ops from the graph
 

bool disable_model_pruning = 2;

общедоступное абстрактное логическое значение getExperimentalDisableCompressedTensorOptimization ()

 Disable optimizations that assume compressed tensors. Note that this flag
 is experimental and may be removed in the future.
 

bool experimental_disable_compressed_tensor_optimization = 26;

общедоступное абстрактное логическое значение getFailOnOptimizerErrors ()

 If true, any optimization pass failing will cause the MetaOptimizer to
 stop with an error. By default - or when set to false, failing passes are
 skipped silently.
 

bool fail_on_optimizer_errors = 21;

публичный абстрактный RewriterConfig.Toggle getFunctionOptimization ()

 Function optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle function_optimization = 10;

общедоступный абстрактный int getFunctionOptimizationValue ()

 Function optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle function_optimization = 10;

публичный абстрактный RewriterConfig.Toggle getImplementationSelector ()

 Enable the swap of kernel implementations based on the device placement
 (default is ON).
 

.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

общедоступный абстрактный int getImplementationSelectorValue ()

 Enable the swap of kernel implementations based on the device placement
 (default is ON).
 

.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

общедоступная абстракция VerifierConfig getInterOptimizerVerifierConfig ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

публичный абстрактный VerifierConfigOrBuilder getInterOptimizerVerifierConfigOrBuilder ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

публичный абстрактный RewriterConfig.Toggle getLayoutOptimizer ()

 Optimize tensor layouts (default is ON)
 e.g. This will try to use NCHW layout on GPU which is faster.
 

.tensorflow.RewriterConfig.Toggle layout_optimizer = 1;

общедоступный абстрактный int getLayoutOptimizerValue ()

 Optimize tensor layouts (default is ON)
 e.g. This will try to use NCHW layout on GPU which is faster.
 

.tensorflow.RewriterConfig.Toggle layout_optimizer = 1;

публичный абстрактный RewriterConfig.Toggle getLoopOptimization ()

 Loop optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

общедоступный абстрактный int getLoopOptimizationValue ()

 Loop optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

публичный абстрактный RewriterConfig.MemOptType getMemoryOptimization ()

 Configures memory optimization passes through the meta-optimizer. Has no
 effect on manually requested memory optimization passes in the optimizers
 field.
 

.tensorflow.RewriterConfig.MemOptType memory_optimization = 4;

общедоступный абстрактный int getMemoryOptimizationValue ()

 Configures memory optimization passes through the meta-optimizer. Has no
 effect on manually requested memory optimization passes in the optimizers
 field.
 

.tensorflow.RewriterConfig.MemOptType memory_optimization = 4;

общедоступная абстрактная строка getMemoryOptimizerTargetNodeNameScope ()

 A node name scope for node names which are valid outputs of recomputations.
 Inputs to nodes that match this scope may be recomputed (subject either to
 manual annotation of those input nodes or to manual annotation and
 heuristics depending on memory_optimization), but the nodes themselves will
 not be recomputed. This matches any sub-scopes as well, meaning the scope
 can appear not just as a top-level scope. For example, if the value is
 "gradients/", the default, it will match node name "gradients/foo",
 "foo/gradients/bar", but not "foo_gradients/"
 

string memory_optimizer_target_node_name_scope = 6;

общедоступный абстрактный com.google.protobuf.ByteString getMemoryOptimizerTargetNodeNameScopeBytes ()

 A node name scope for node names which are valid outputs of recomputations.
 Inputs to nodes that match this scope may be recomputed (subject either to
 manual annotation of those input nodes or to manual annotation and
 heuristics depending on memory_optimization), but the nodes themselves will
 not be recomputed. This matches any sub-scopes as well, meaning the scope
 can appear not just as a top-level scope. For example, if the value is
 "gradients/", the default, it will match node name "gradients/foo",
 "foo/gradients/bar", but not "foo_gradients/"
 

string memory_optimizer_target_node_name_scope = 6;

общедоступный абстрактный RewriterConfig.NumIterationsType getMetaOptimizerIterations ()

 Controls how many times we run the optimizers in meta optimizer (default
 is once).
 

.tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;

общедоступный абстрактный int getMetaOptimizerIterationsValue ()

 Controls how many times we run the optimizers in meta optimizer (default
 is once).
 

.tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;

общедоступный абстрактный длинный getMetaOptimizerTimeoutMs ()

 Maximum number of milliseconds to spend optimizing a single graph before
 timing out. If equal to 0 the system picks a default (currently 5 minutes).
 If less than 0 the optimizer will never time out.
 

int64 meta_optimizer_timeout_ms = 20;

общедоступный абстрактный int getMinGraphNodes ()

 The minimum number of nodes in a graph to optimizer. For smaller graphs,
 optimization is skipped.
 0 means the system picks an appropriate number.
 < 0 means do not skip optimization.
 

int32 min_graph_nodes = 17;

общедоступная абстрактная строка getOptimizers (индекс int)

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

repeated string optimizers = 100;

общедоступный абстрактный com.google.protobuf.ByteString getOptimizersBytes (индекс int)

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

repeated string optimizers = 100;

публичный абстрактный int getOptimizersCount ()

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

repeated string optimizers = 100;

общедоступный абстрактный список <String> getOptimizersList ()

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

repeated string optimizers = 100;

публичный абстрактный RewriterConfig.Toggle getPinToHostOptimization ()

 Force small ops onto the CPU (default is OFF).
 

.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

общедоступный абстрактный int getPinToHostOptimizationValue ()

 Force small ops onto the CPU (default is OFF).
 

.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

общедоступная абстракция VerifierConfig getPostOptimizationVerifierConfig ()

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
 

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

публичный абстрактный VerifierConfigOrBuilder getPostOptimizationVerifierConfigOrBuilder ()

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
 

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

публичный абстрактный RewriterConfig.Toggle getRemapping ()

 Remapping (default is ON)
 Remap subgraphs onto more efficient implementations.
 

.tensorflow.RewriterConfig.Toggle remapping = 14;

общедоступный абстрактный int getRemappingValue ()

 Remapping (default is ON)
 Remap subgraphs onto more efficient implementations.
 

.tensorflow.RewriterConfig.Toggle remapping = 14;

публичный абстрактный RewriterConfig.Toggle getScopedAllocatorOptimization ()

 Try to allocate some independent Op outputs contiguously in order to
 merge or eliminate downstream Ops (off by default).
 

.tensorflow.RewriterConfig.Toggle scoped_allocator_optimization = 15;

public Abstract int getScopedAllocatorOptimizationValue ()

 Try to allocate some independent Op outputs contiguously in order to
 merge or eliminate downstream Ops (off by default).
 

.tensorflow.RewriterConfig.Toggle scoped_allocator_optimization = 15;

публичный абстрактный ScopedAllocatorOptions getScopedAllocatorOpts ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

публичный абстрактный ScopedAllocatorOptionsOrBuilder getScopedAllocatorOptsOrBuilder ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

публичный абстрактный RewriterConfig.Toggle getShapeOptimization ()

 Shape optimizations (default is ON)
 Simplify computations made on shapes.
 

.tensorflow.RewriterConfig.Toggle shape_optimization = 13;

public Abstract int getShapeOptimizationValue ()

 Shape optimizations (default is ON)
 Simplify computations made on shapes.
 

.tensorflow.RewriterConfig.Toggle shape_optimization = 13;

общедоступное абстрактное логическое значение hasAutoParallel ()

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
 

.tensorflow.AutoParallelOptions auto_parallel = 5;

общедоступное абстрактное логическое значение hasInterOptimizerVerifierConfig ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

общедоступное абстрактное логическое значение hasPostOptimizationVerifierConfig ()

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
 

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

общедоступное абстрактное логическое значение hasScopedAllocatorOpts ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;