RewriterConfigOrBuilder

interfaz pública RewriterConfigOrBuilder

Subclases indirectas conocidas RewriterConfig , RewriterConfig.Builder Configuración de reescritura 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

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

Métodos públicos

resumen 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;

resumen público 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;

resumen 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;

resumen 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;

resumen público 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;

resumen público 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;

resumen público AutoParallelOptions getAutoParallel ()

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

.tensorflow.AutoParallelOptions auto_parallel = 5;

resumen público AutoParallelOptionsOrBuilder getAutoParallelOrBuilder ()

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

.tensorflow.AutoParallelOptions auto_parallel = 5;

resumen 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;

resumen 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;

resumen 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;

resumen público 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;

resumen público RewriterConfig.CpuLayout getCpuLayoutConversion ()

 CPU Conversion settings between NHCW and NCHW.
 

.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

resumen público int getCpuLayoutConversionValue ()

 CPU Conversion settings between NHCW and NCHW.
 

.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

resumen público RewriterConfig.CustomGraphOptimizer getCustomOptimizers (índice int)

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

resumen público int getCustomOptimizersCount ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

Lista abstracta pública < RewriterConfig.CustomGraphOptimizer > getCustomOptimizersList ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

resumen público RewriterConfig.CustomGraphOptimizerOrBuilder getCustomOptimizersOrBuilder (índice int)

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

Lista de resúmenes públicos <? extiende RewriterConfig.CustomGraphOptimizerOrBuilder > getCustomOptimizersOrBuilderList ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

resumen público RewriterConfig.Toggle getDebugStripper ()

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

.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

resumen público int getDebugStripperValue ()

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

.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

resumen 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;

resumen público int getDependencyOptimizationValue ()

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

.tensorflow.RewriterConfig.Toggle dependency_optimization = 8;

getDisableMetaOptimizer booleano abstracto público ()

 Disable the entire meta optimizer (off by default).
 

bool disable_meta_optimizer = 19;

getDisableModelPruning booleano abstracto público ()

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

bool disable_model_pruning = 2;

público abstracto 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;

getFailOnOptimizerErrors booleano abstracto público ()

 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;

resumen público RewriterConfig.Toggle getFunctionOptimization ()

 Function optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle function_optimization = 10;

resumen público int getFunctionOptimizationValue ()

 Function optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle function_optimization = 10;

resumen público RewriterConfig.Toggle getImplementationSelector ()

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

.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

resumen público int getImplementationSelectorValue ()

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

.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

resumen público VerifierConfig getInterOptimizerVerifierConfig ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

resumen público VerifierConfigOrBuilder getInterOptimizerVerifierConfigOrBuilder ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

resumen 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;

resumen 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;

resumen público RewriterConfig.Toggle getLoopOptimization ()

 Loop optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

resumen público int getLoopOptimizationValue ()

 Loop optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

resumen 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;

resumen 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;

Cadena abstracta 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;

resumen 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;

resumen 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;

resumen público int getMetaOptimizerIterationsValue ()

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

.tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;

getMetaOptimizerTimeoutMs largo abstracto público ()

 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;

resumen 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;

Cadena abstracta 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;

resumen 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;

resumen 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 abstracta pública<Cadena> 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;

resumen público RewriterConfig.Toggle getPinToHostOptimization ()

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

.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

resumen público int getPinToHostOptimizationValue ()

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

.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

resumen público VerifierConfig getPostOptimizationVerifierConfig ()

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

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

resumen público VerifierConfigOrBuilder getPostOptimizationVerifierConfigOrBuilder ()

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

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

resumen público RewriterConfig.Toggle getRemapping ()

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

.tensorflow.RewriterConfig.Toggle remapping = 14;

resumen público int getRemappingValue ()

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

.tensorflow.RewriterConfig.Toggle remapping = 14;

resumen 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;

resumen público 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;

resumen público ScopedAllocatorOptions getScopedAllocatorOpts ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

resumen público ScopedAllocatorOptionsOrBuilder getScopedAllocatorOptsOrBuilder ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

resumen público RewriterConfig.Toggle getShapeOptimization ()

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

.tensorflow.RewriterConfig.Toggle shape_optimization = 13;

resumen público int getShapeOptimizationValue ()

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

.tensorflow.RewriterConfig.Toggle shape_optimization = 13;

hasAutoParallel booleano abstracto público ()

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

.tensorflow.AutoParallelOptions auto_parallel = 5;

hasInterOptimizerVerifierConfig booleano abstracto público ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

hasPostOptimizationVerifierConfig booleano abstracto público ()

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

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

hasScopedAllocatorOpts booleano abstracto público ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;