RewriterConfigOrBuilder

public interface RewriterConfigOrBuilder
Known Indirect Subclasses

Public Methods

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

Public Methods

public abstract 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;

public abstract 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;

public abstract 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;

public abstract 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;

public abstract 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;

public abstract AutoParallelOptions getAutoParallel () 

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
.tensorflow.AutoParallelOptions auto_parallel = 5;

public abstract AutoParallelOptionsOrBuilder getAutoParallelOrBuilder () 

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
.tensorflow.AutoParallelOptions auto_parallel = 5;

public abstract 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;

public abstract 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;

public abstract 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;

public abstract RewriterConfig.CpuLayout getCpuLayoutConversion () 

 CPU Conversion settings between NHCW and NCHW.
.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

public abstract int getCpuLayoutConversionValue () 

 CPU Conversion settings between NHCW and NCHW.
.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

public abstract RewriterConfig.CustomGraphOptimizer getCustomOptimizers (int index) 

 list of CustomGraphOptimizers to apply.
repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

public abstract int getCustomOptimizersCount () 

 list of CustomGraphOptimizers to apply.
repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

public abstract List<RewriterConfig.CustomGraphOptimizer> getCustomOptimizersList () 

 list of CustomGraphOptimizers to apply.
repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

public abstract RewriterConfig.CustomGraphOptimizerOrBuilder getCustomOptimizersOrBuilder (int index) 

 list of CustomGraphOptimizers to apply.
repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

public abstract List<? extends RewriterConfig.CustomGraphOptimizerOrBuilder> getCustomOptimizersOrBuilderList () 

 list of CustomGraphOptimizers to apply.
repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

public abstract RewriterConfig.Toggle getDebugStripper () 

 Strips debug-related nodes from the graph (off by default).
.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

public abstract int getDebugStripperValue () 

 Strips debug-related nodes from the graph (off by default).
.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

public abstract RewriterConfig.Toggle getDependencyOptimization () 

 Control dependency optimizations (default is ON).
 Remove redundant control dependencies, which may enable other optimization.
.tensorflow.RewriterConfig.Toggle dependency_optimization = 8;

public abstract int getDependencyOptimizationValue () 

 Control dependency optimizations (default is ON).
 Remove redundant control dependencies, which may enable other optimization.
.tensorflow.RewriterConfig.Toggle dependency_optimization = 8;

public abstract boolean getDisableMetaOptimizer () 

 Disable the entire meta optimizer (off by default).
bool disable_meta_optimizer = 19;

public abstract boolean getDisableModelPruning () 

 If true, don't remove unnecessary ops from the graph
bool disable_model_pruning = 2;

public abstract boolean 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;

public abstract boolean 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;

public abstract RewriterConfig.Toggle getFunctionOptimization () 

 Function optimizations (default is ON).
.tensorflow.RewriterConfig.Toggle function_optimization = 10;

public abstract int getFunctionOptimizationValue () 

 Function optimizations (default is ON).
.tensorflow.RewriterConfig.Toggle function_optimization = 10;

public abstract RewriterConfig.Toggle getImplementationSelector () 

 Enable the swap of kernel implementations based on the device placement
 (default is ON).
.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

public abstract int getImplementationSelectorValue () 

 Enable the swap of kernel implementations based on the device placement
 (default is ON).
.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

public abstract VerifierConfig getInterOptimizerVerifierConfig () 

 VerifierConfig specifying the verifiers to be run after every optimizer.
.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

public abstract VerifierConfigOrBuilder getInterOptimizerVerifierConfigOrBuilder () 

 VerifierConfig specifying the verifiers to be run after every optimizer.
.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

public abstract 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;

public abstract 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;

public abstract RewriterConfig.Toggle getLoopOptimization () 

 Loop optimizations (default is ON).
.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

public abstract int getLoopOptimizationValue () 

 Loop optimizations (default is ON).
.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

public abstract 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;

public abstract 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;

public abstract String 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;

public abstract 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;

public abstract RewriterConfig.NumIterationsType getMetaOptimizerIterations () 

 Controls how many times we run the optimizers in meta optimizer (default
 is once).
.tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;

public abstract int getMetaOptimizerIterationsValue () 

 Controls how many times we run the optimizers in meta optimizer (default
 is once).
.tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;

public abstract long 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;

public abstract 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;

public abstract String getOptimizers (int index) 

 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;

public abstract com.google.protobuf.ByteString getOptimizersBytes (int index) 

 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;

public abstract 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;

public abstract List<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;

public abstract RewriterConfig.Toggle getPinToHostOptimization () 

 Force small ops onto the CPU (default is OFF).
.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

public abstract int getPinToHostOptimizationValue () 

 Force small ops onto the CPU (default is OFF).
.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

public abstract VerifierConfig getPostOptimizationVerifierConfig () 

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

public abstract VerifierConfigOrBuilder getPostOptimizationVerifierConfigOrBuilder () 

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

public abstract RewriterConfig.Toggle getRemapping () 

 Remapping (default is ON)
 Remap subgraphs onto more efficient implementations.
.tensorflow.RewriterConfig.Toggle remapping = 14;

public abstract int getRemappingValue () 

 Remapping (default is ON)
 Remap subgraphs onto more efficient implementations.
.tensorflow.RewriterConfig.Toggle remapping = 14;

public abstract 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;

public abstract ScopedAllocatorOptions getScopedAllocatorOpts ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

public abstract ScopedAllocatorOptionsOrBuilder getScopedAllocatorOptsOrBuilder ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

public abstract 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;

public abstract boolean hasAutoParallel () 

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
.tensorflow.AutoParallelOptions auto_parallel = 5;

public abstract boolean hasInterOptimizerVerifierConfig () 

 VerifierConfig specifying the verifiers to be run after every optimizer.
.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

public abstract boolean hasPostOptimizationVerifierConfig () 

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

public abstract boolean hasScopedAllocatorOpts ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;