RewriterConfigOrBuilder

interface pública RewriterConfigOrBuilder

Subclasses indiretas conhecidas 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.

Métodos Públicos

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

Métodos Públicos

resumo público 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;

público abstrato 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;

resumo público 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;

resumo público 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;

público abstrato 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;

público abstrato 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;

público abstrato AutoParallelOptions getAutoParallel ()

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

.tensorflow.AutoParallelOptions auto_parallel = 5;

público abstrato AutoParallelOptionsOrBuilder getAutoParallelOrBuilder ()

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

.tensorflow.AutoParallelOptions auto_parallel = 5;

resumo público 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;

resumo público 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;

resumo público 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;

público abstrato 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;

resumo público RewriterConfig.CpuLayout getCpuLayoutConversion ()

 CPU Conversion settings between NHCW and NCHW.
 

.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

resumo público int getCpuLayoutConversionValue ()

 CPU Conversion settings between NHCW and NCHW.
 

.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

resumo público RewriterConfig.CustomGraphOptimizer getCustomOptimizers (índice int)

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

resumo público int getCustomOptimizersCount ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

lista abstrata pública< RewriterConfig.CustomGraphOptimizer > getCustomOptimizersList ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

resumo público RewriterConfig.CustomGraphOptimizerOrBuilder getCustomOptimizersOrBuilder (índice int)

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

lista abstrata pública<? estende RewriterConfig.CustomGraphOptimizerOrBuilder > getCustomOptimizersOrBuilderList ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

resumo público RewriterConfig.Toggle getDebugStripper ()

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

.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

resumo público int getDebugStripperValue ()

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

.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

resumo público RewriterConfig.Toggle getDependencyOptimization ()

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

.tensorflow.RewriterConfig.Toggle dependency_optimization = 8;

resumo público int getDependencyOptimizationValue ()

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

.tensorflow.RewriterConfig.Toggle dependency_optimization = 8;

público abstrato booleano getDisableMetaOptimizer ()

 Disable the entire meta optimizer (off by default).
 

bool disable_meta_optimizer = 19;

público abstrato booleano getDisableModelPruning ()

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

bool disable_model_pruning = 2;

público abstrato booleano 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;

público abstrato booleano 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;

resumo público RewriterConfig.Toggle getFunctionOptimization ()

 Function optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle function_optimization = 10;

público abstrato int getFunctionOptimizationValue ()

 Function optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle function_optimization = 10;

resumo público RewriterConfig.Toggle getImplementationSelector ()

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

.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

público abstrato int getImplementationSelectorValue ()

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

.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

resumo público VerifierConfig getInterOptimizerVerifierConfig ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

público abstrato VerifierConfigOrBuilder getInterOptimizerVerifierConfigOrBuilder ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

resumo público 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;

resumo público 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;

resumo público RewriterConfig.Toggle getLoopOptimization ()

 Loop optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

resumo público int getLoopOptimizationValue ()

 Loop optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

resumo público 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;

resumo público 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;

cadeia abstrata pública 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;

resumo público 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;

resumo público RewriterConfig.NumIterationsType getMetaOptimizerIterations ()

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

.tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;

público abstrato int getMetaOptimizerIterationsValue ()

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

.tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;

público abstrato longo 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;

resumo público 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;

string abstrata pública getOptimizers (índice 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;

resumo público com.google.protobuf.ByteString getOptimizersBytes (índice 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;

resumo público 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;

lista abstrata pública<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;

resumo público RewriterConfig.Toggle getPinToHostOptimization ()

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

.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

resumo público int getPinToHostOptimizationValue ()

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

.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

público abstrato VerifierConfig getPostOptimizationVerifierConfig ()

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

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

público abstrato VerifierConfigOrBuilder getPostOptimizationVerifierConfigOrBuilder ()

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

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

resumo público RewriterConfig.Toggle getRemapping ()

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

.tensorflow.RewriterConfig.Toggle remapping = 14;

público abstrato int getRemappingValue ()

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

.tensorflow.RewriterConfig.Toggle remapping = 14;

resumo público 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;

público abstrato 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;

público abstrato ScopedAllocatorOptions getScopedAllocatorOpts ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

público abstrato ScopedAllocatorOptionsOrBuilder getScopedAllocatorOptsOrBuilder ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

resumo público RewriterConfig.Toggle getShapeOptimization ()

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

.tensorflow.RewriterConfig.Toggle shape_optimization = 13;

resumo público int getShapeOptimizationValue ()

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

.tensorflow.RewriterConfig.Toggle shape_optimization = 13;

público abstrato booleano hasAutoParallel ()

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

.tensorflow.AutoParallelOptions auto_parallel = 5;

público abstrato booleano hasInterOptimizerVerifierConfig ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

público abstrato booleano hasPostOptimizationVerifierConfig ()

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

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

público abstrato booleano hasScopedAllocatorOpts ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;