interfaz pública RewriterConfigOrBuilder
Subclases indirectas conocidas |
Métodos públicos
resumen RewriterConfig.Toggle | getArithmeticOptimization () Arithmetic optimizations (default is ON) e.g. |
int abstracto | 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). |
int abstracto | getAutoMixedPrecisionMklValue () Optimize data types for MKL (default is OFF). |
int abstracto | getAutoMixedPrecisionValue () Optimize data types for CUDA (default is OFF). |
abstractas 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. |
resumen RewriterConfig.Toggle | getCommonSubgraphElimination () Common subgraph elimination (default is ON) e.g. |
int abstracto | 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. |
int abstracto | 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. |
int abstracto | getCpuLayoutConversionValue () CPU Conversion settings between NHCW and NCHW. |
resumen RewriterConfig.CustomGraphOptimizer | getCustomOptimizers (índice int) list of CustomGraphOptimizers to apply. |
int abstracto | getCustomOptimizersCount () list of CustomGraphOptimizers to apply. |
Lista abstracta < RewriterConfig.CustomGraphOptimizer > | getCustomOptimizersList () list of CustomGraphOptimizers to apply. |
resumen RewriterConfig.CustomGraphOptimizerOrBuilder | getCustomOptimizersOrBuilder (índice int) list of CustomGraphOptimizers to apply. |
Resumen Lista <? extiende RewriterConfig.CustomGraphOptimizerOrBuilder > | getCustomOptimizersOrBuilderList () list of CustomGraphOptimizers to apply. |
resumen RewriterConfig.Toggle | getDebugStripper () Strips debug-related nodes from the graph (off by default). |
int abstracto | getDebugStripperValue () Strips debug-related nodes from the graph (off by default). |
resumen RewriterConfig.Toggle | getDependencyOptimization () Control dependency optimizations (default is ON). |
int abstracto | 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 | getFunctionOptimization () Function optimizations (default is ON). |
int abstracto | getFunctionOptimizationValue () Function optimizations (default is ON). |
resumen RewriterConfig.Toggle | getImplementationSelector () Enable the swap of kernel implementations based on the device placement (default is ON). |
int abstracto | getImplementationSelectorValue () Enable the swap of kernel implementations based on the device placement (default is ON). |
VerifierConfig abstracto | getInterOptimizerVerifierConfig () VerifierConfig specifying the verifiers to be run after every optimizer. |
VerifierConfigOrBuilder abstracto | getInterOptimizerVerifierConfigOrBuilder () VerifierConfig specifying the verifiers to be run after every optimizer. |
resumen RewriterConfig.Toggle | getLayoutOptimizer () Optimize tensor layouts (default is ON) e.g. |
int abstracto | getLayoutOptimizerValue () Optimize tensor layouts (default is ON) e.g. |
resumen RewriterConfig.Toggle | getLoopOptimization () Loop optimizations (default is ON). |
int abstracto | getLoopOptimizationValue () Loop optimizations (default is ON). |
resumen RewriterConfig.MemOptType | getMemoryOptimization () Configures memory optimization passes through the meta-optimizer. |
int abstracto | 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). |
int abstracto | getMetaOptimizerIterationsValue () Controls how many times we run the optimizers in meta optimizer (default is once). |
abstracto largo | getMetaOptimizerTimeoutMs () Maximum number of milliseconds to spend optimizing a single graph before timing out. |
int abstracto | 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). |
int abstracto | 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 <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). |
resumen RewriterConfig.Toggle | getPinToHostOptimization () Force small ops onto the CPU (default is OFF). |
int abstracto | getPinToHostOptimizationValue () Force small ops onto the CPU (default is OFF). |
VerifierConfig abstracto | getPostOptimizationVerifierConfig () VerifierConfig specifying the verifiers to be run at the end, after all optimizers have run. |
VerifierConfigOrBuilder abstracto | getPostOptimizationVerifierConfigOrBuilder () VerifierConfig specifying the verifiers to be run at the end, after all optimizers have run. |
resumen RewriterConfig.Toggle | getRemapping () Remapping (default is ON) Remap subgraphs onto more efficient implementations. |
int abstracto | getRemappingValue () Remapping (default is ON) Remap subgraphs onto more efficient implementations. |
resumen RewriterConfig.Toggle | getScopedAllocatorOptimization () Try to allocate some independent Op outputs contiguously in order to merge or eliminate downstream Ops (off by default). |
int abstracto | 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; |
resumen ScopedAllocatorOptionsOrBuilder | getScopedAllocatorOptsOrBuilder () .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16; |
resumen RewriterConfig.Toggle | getShapeOptimization () Shape optimizations (default is ON) Simplify computations made on shapes. |
int abstracto | getShapeOptimizationValue () Shape optimizations (default is ON) Simplify computations made on shapes. |
booleano abstracto | hasAutoParallel () 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 | hasPostOptimizationVerifierConfig () 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;
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;
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;
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;
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;
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;
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;
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;
resumen público 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;
resumen público RewriterConfig.CustomGraphOptimizer getCustomOptimizers (índice int)
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;
Lista pública abstracta < 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 resumen público <? 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;
public abstract 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;
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;
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;
getExperimentalDisableCompressedTensorOptimization () booleano abstracto público
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;
resumen público 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;
resumen público RewriterConfig.Toggle getImplementationSelector ()
Enable the swap of kernel implementations based on the device placement (default is ON)..tensorflow.RewriterConfig.Toggle
.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
.tensorflow.RewriterConfig.Toggle implementation_selector = 22;
VerifierConfig abstracto público 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;
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;
resumen público 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;
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;
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;
público abstracto 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;
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;
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;
getOptimizers de cadena abstracta pública (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;
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;
Lista pública abstracta <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;
resumen público 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;
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
.tensorflow.RewriterConfig.Toggle remapping = 14;
public abstract int getRemappingValue ()
Remapping (default is ON) Remap subgraphs onto more efficient implementations..tensorflow.RewriterConfig.Toggle
.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;
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;
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;
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;
público abstracto booleano hasInterOptimizerVerifierConfig ()
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;
público abstracto booleano hasScopedAllocatorOpts ()
.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;