Package org.tensorflow.framework

Interface RewriterConfigOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
RewriterConfig, RewriterConfig.Builder
public interface RewriterConfigOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Details

    • getCpuLayoutConversionValue

      int getCpuLayoutConversionValue()
       CPU Conversion settings between NHCW and NCHW.
      .tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;
      Returns:
      The enum numeric value on the wire for cpuLayoutConversion.

    • getCpuLayoutConversion

      RewriterConfig.CpuLayout getCpuLayoutConversion()
       CPU Conversion settings between NHCW and NCHW.
      .tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;
      Returns:
      The cpuLayoutConversion.

    • getLayoutOptimizerValue

      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;
      Returns:
      The enum numeric value on the wire for layoutOptimizer.

    • getLayoutOptimizer

      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;
      Returns:
      The layoutOptimizer.

    • getConstantFoldingValue

      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;
      Returns:
      The enum numeric value on the wire for constantFolding.

    • getConstantFolding

      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;
      Returns:
      The constantFolding.

    • getShapeOptimizationValue

      int getShapeOptimizationValue()
       Shape optimizations (default is ON)
 Simplify computations made on shapes.
      .tensorflow.RewriterConfig.Toggle shape_optimization = 13;
      Returns:
      The enum numeric value on the wire for shapeOptimization.

    • getShapeOptimization

      RewriterConfig.Toggle getShapeOptimization()
       Shape optimizations (default is ON)
 Simplify computations made on shapes.
      .tensorflow.RewriterConfig.Toggle shape_optimization = 13;
      Returns:
      The shapeOptimization.

    • getRemappingValue

      int getRemappingValue()
       Remapping (default is ON)
 Remap subgraphs onto more efficient implementations.
      .tensorflow.RewriterConfig.Toggle remapping = 14;
      Returns:
      The enum numeric value on the wire for remapping.

    • getRemapping

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

    • getCommonSubgraphEliminationValue

      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;
      Returns:
      The enum numeric value on the wire for commonSubgraphElimination.

    • getCommonSubgraphElimination

      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;
      Returns:
      The commonSubgraphElimination.

    • getArithmeticOptimizationValue

      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;
      Returns:
      The enum numeric value on the wire for arithmeticOptimization.

    • getArithmeticOptimization

      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;
      Returns:
      The arithmeticOptimization.

    • getDependencyOptimizationValue

      int getDependencyOptimizationValue()
       Control dependency optimizations (default is ON).
 Remove redundant control dependencies, which may enable other optimization.
      .tensorflow.RewriterConfig.Toggle dependency_optimization = 8;
      Returns:
      The enum numeric value on the wire for dependencyOptimization.

    • getDependencyOptimization

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

    • getLoopOptimizationValue

      int getLoopOptimizationValue()
       Loop optimizations (default is ON).
      .tensorflow.RewriterConfig.Toggle loop_optimization = 9;
      Returns:
      The enum numeric value on the wire for loopOptimization.

    • getLoopOptimization

      RewriterConfig.Toggle getLoopOptimization()
       Loop optimizations (default is ON).
      .tensorflow.RewriterConfig.Toggle loop_optimization = 9;
      Returns:
      The loopOptimization.

    • getFunctionOptimizationValue

      int getFunctionOptimizationValue()
       Function optimizations (default is ON).
      .tensorflow.RewriterConfig.Toggle function_optimization = 10;
      Returns:
      The enum numeric value on the wire for functionOptimization.

    • getFunctionOptimization

      RewriterConfig.Toggle getFunctionOptimization()
       Function optimizations (default is ON).
      .tensorflow.RewriterConfig.Toggle function_optimization = 10;
      Returns:
      The functionOptimization.

    • getDebugStripperValue

      int getDebugStripperValue()
       Strips debug-related nodes from the graph (off by default).
      .tensorflow.RewriterConfig.Toggle debug_stripper = 11;
      Returns:
      The enum numeric value on the wire for debugStripper.

    • getDebugStripper

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

    • getDisableModelPruning

      boolean getDisableModelPruning()
       If true, don't remove unnecessary ops from the graph
      bool disable_model_pruning = 2;
      Returns:
      The disableModelPruning.

    • getScopedAllocatorOptimizationValue

      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;
      Returns:
      The enum numeric value on the wire for scopedAllocatorOptimization.

    • getScopedAllocatorOptimization

      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;
      Returns:
      The scopedAllocatorOptimization.

    • getPinToHostOptimizationValue

      int getPinToHostOptimizationValue()
       Force small ops onto the CPU (default is OFF).
      .tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;
      Returns:
      The enum numeric value on the wire for pinToHostOptimization.

    • getPinToHostOptimization

      RewriterConfig.Toggle getPinToHostOptimization()
       Force small ops onto the CPU (default is OFF).
      .tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;
      Returns:
      The pinToHostOptimization.

    • getImplementationSelectorValue

      int getImplementationSelectorValue()
       Enable the swap of kernel implementations based on the device placement
 (default is ON).
      .tensorflow.RewriterConfig.Toggle implementation_selector = 22;
      Returns:
      The enum numeric value on the wire for implementationSelector.

    • getImplementationSelector

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

    • getAutoMixedPrecisionValue

      int getAutoMixedPrecisionValue()
       Optimize data types for CUDA/oneDNN (default is OFF).
 This will try to use float16 on GPU/CPU 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;
      Returns:
      The enum numeric value on the wire for autoMixedPrecision.

    • getAutoMixedPrecision

      RewriterConfig.Toggle getAutoMixedPrecision()
       Optimize data types for CUDA/oneDNN (default is OFF).
 This will try to use float16 on GPU/CPU 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;
      Returns:
      The autoMixedPrecision.

    • getAutoMixedPrecisionMklValue

      int getAutoMixedPrecisionMklValue()
       Optimize data types for oneDNN (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.
 Note: this is deprecated.
 It is replaced by auto_mixed_precision_onednn_bfloat16
      .tensorflow.RewriterConfig.Toggle auto_mixed_precision_mkl = 25;
      Returns:
      The enum numeric value on the wire for autoMixedPrecisionMkl.

    • getAutoMixedPrecisionMkl

      RewriterConfig.Toggle getAutoMixedPrecisionMkl()
       Optimize data types for oneDNN (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.
 Note: this is deprecated.
 It is replaced by auto_mixed_precision_onednn_bfloat16
      .tensorflow.RewriterConfig.Toggle auto_mixed_precision_mkl = 25;
      Returns:
      The autoMixedPrecisionMkl.

    • getAutoMixedPrecisionOnednnBfloat16Value

      int getAutoMixedPrecisionOnednnBfloat16Value()
       Optimize data types for oneDNN (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.
 Note: this is equivalent to the deprecated option auto_mixed_precision_mkl
      .tensorflow.RewriterConfig.Toggle auto_mixed_precision_onednn_bfloat16 = 31;
      Returns:
      The enum numeric value on the wire for autoMixedPrecisionOnednnBfloat16.

    • getAutoMixedPrecisionOnednnBfloat16

      RewriterConfig.Toggle getAutoMixedPrecisionOnednnBfloat16()
       Optimize data types for oneDNN (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.
 Note: this is equivalent to the deprecated option auto_mixed_precision_mkl
      .tensorflow.RewriterConfig.Toggle auto_mixed_precision_onednn_bfloat16 = 31;
      Returns:
      The autoMixedPrecisionOnednnBfloat16.

    • getAutoMixedPrecisionCpuValue

      int getAutoMixedPrecisionCpuValue()
       Emulate a model using data type float16 on CPU (default is OFF).
 This will try to emulate the float16 inputs and outputs of an operator
 on CPU to have better correlation with float16 on GPU; however the
 computation in the operator is based on float32.
 Note that this can change the numerical stability of the graph.
      .tensorflow.RewriterConfig.Toggle auto_mixed_precision_cpu = 29;
      Returns:
      The enum numeric value on the wire for autoMixedPrecisionCpu.

    • getAutoMixedPrecisionCpu

      RewriterConfig.Toggle getAutoMixedPrecisionCpu()
       Emulate a model using data type float16 on CPU (default is OFF).
 This will try to emulate the float16 inputs and outputs of an operator
 on CPU to have better correlation with float16 on GPU; however the
 computation in the operator is based on float32.
 Note that this can change the numerical stability of the graph.
      .tensorflow.RewriterConfig.Toggle auto_mixed_precision_cpu = 29;
      Returns:
      The autoMixedPrecisionCpu.

    • getDisableMetaOptimizer

      boolean getDisableMetaOptimizer()
       Disable the entire meta optimizer (off by default).
      bool disable_meta_optimizer = 19;
      Returns:
      The disableMetaOptimizer.

    • getDisableTfgOptimizer

      boolean getDisableTfgOptimizer()
       Disable the TFG optimizer (off by default).
      bool disable_tfg_optimizer = 32;
      Returns:
      The disableTfgOptimizer.

    • getUsePluginOptimizersValue

      int getUsePluginOptimizersValue()
       Optimizers registered by plugin (default is ON)
      .tensorflow.RewriterConfig.Toggle use_plugin_optimizers = 28;
      Returns:
      The enum numeric value on the wire for usePluginOptimizers.

    • getUsePluginOptimizers

      RewriterConfig.Toggle getUsePluginOptimizers()
       Optimizers registered by plugin (default is ON)
      .tensorflow.RewriterConfig.Toggle use_plugin_optimizers = 28;
      Returns:
      The usePluginOptimizers.

    • getExperimentalConditionalCodeMotionValue

      int getExperimentalConditionalCodeMotionValue()
       Conditional code motion (default is ON).
      .tensorflow.RewriterConfig.Toggle experimental_conditional_code_motion = 30;
      Returns:
      The enum numeric value on the wire for experimentalConditionalCodeMotion.

    • getExperimentalConditionalCodeMotion

      RewriterConfig.Toggle getExperimentalConditionalCodeMotion()
       Conditional code motion (default is ON).
      .tensorflow.RewriterConfig.Toggle experimental_conditional_code_motion = 30;
      Returns:
      The experimentalConditionalCodeMotion.

    • getMetaOptimizerIterationsValue

      int getMetaOptimizerIterationsValue()
       Controls how many times we run the optimizers in meta optimizer (default
 is once).
      .tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;
      Returns:
      The enum numeric value on the wire for metaOptimizerIterations.

    • getMetaOptimizerIterations

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

    • getMinGraphNodes

      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;
      Returns:
      The minGraphNodes.

    • getExperimentalDisableCompressedTensorOptimization

      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;
      Returns:
      The experimentalDisableCompressedTensorOptimization.

    • getExperimentalDisableFoldingQuantizationEmulation

      boolean getExperimentalDisableFoldingQuantizationEmulation()
       Disable folding quantization emulation ops such as FakeQuantWithMinMax* and
 QuantizeAndDequantize*. Some compilers (e.g. the TF-to-tflite converter)
 have to extract quantization configs (e.g. min/max range, number of bits,
 and per-channel) from the quantization emulation ops. Note that this flag
 is experimental and may be removed in the future. See b/174138564 for more
 details.
      bool experimental_disable_folding_quantization_emulation = 27;
      Returns:
      The experimentalDisableFoldingQuantizationEmulation.

    • getMemoryOptimizationValue

      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;
      Returns:
      The enum numeric value on the wire for memoryOptimization.

    • getMemoryOptimization

      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;
      Returns:
      The memoryOptimization.

    • getMemoryOptimizerTargetNodeNameScope

      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;
      Returns:
      The memoryOptimizerTargetNodeNameScope.

    • getMemoryOptimizerTargetNodeNameScopeBytes

      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;
      Returns:
      The bytes for memoryOptimizerTargetNodeNameScope.

    • getMetaOptimizerTimeoutMs

      long getMetaOptimizerTimeoutMs()
       Maximum number of milliseconds to spend optimizing a single graph before
 timing out. If less than or equal to 0 (default value) the optimizer will
 never time out.
      int64 meta_optimizer_timeout_ms = 20;
      Returns:
      The metaOptimizerTimeoutMs.

    • hasAutoParallel

      boolean hasAutoParallel()
       Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
      .tensorflow.AutoParallelOptions auto_parallel = 5;
      Returns:
      Whether the autoParallel field is set.

    • getAutoParallel

      AutoParallelOptions getAutoParallel()
       Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
      .tensorflow.AutoParallelOptions auto_parallel = 5;
      Returns:
      The autoParallel.

    • getAutoParallelOrBuilder

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

    • getFailOnOptimizerErrors

      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;
      Returns:
      The failOnOptimizerErrors.

    • hasScopedAllocatorOpts

      boolean hasScopedAllocatorOpts()
      .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
      Returns:
      Whether the scopedAllocatorOpts field is set.

    • getScopedAllocatorOpts

      ScopedAllocatorOptions getScopedAllocatorOpts()
      .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
      Returns:
      The scopedAllocatorOpts.

    • getScopedAllocatorOptsOrBuilder

      ScopedAllocatorOptionsOrBuilder getScopedAllocatorOptsOrBuilder()
      .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

    • getOptimizersList

      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;
      Returns:
      A list containing the optimizers.

    • getOptimizersCount

      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;
      Returns:
      The count of optimizers.

    • getOptimizers

      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;
      Parameters:
      index - The index of the element to return.
      Returns:
      The optimizers at the given index.

    • getOptimizersBytes

      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;
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the optimizers at the given index.

    • getCustomOptimizersList

      List<RewriterConfig.CustomGraphOptimizer> getCustomOptimizersList()
       list of CustomGraphOptimizers to apply.
      repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

    • getCustomOptimizers

      RewriterConfig.CustomGraphOptimizer getCustomOptimizers(int index)
       list of CustomGraphOptimizers to apply.
      repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

    • getCustomOptimizersCount

      int getCustomOptimizersCount()
       list of CustomGraphOptimizers to apply.
      repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

    • getCustomOptimizersOrBuilderList

      List<? extends RewriterConfig.CustomGraphOptimizerOrBuilder> getCustomOptimizersOrBuilderList()
       list of CustomGraphOptimizers to apply.
      repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

    • getCustomOptimizersOrBuilder

      RewriterConfig.CustomGraphOptimizerOrBuilder getCustomOptimizersOrBuilder(int index)
       list of CustomGraphOptimizers to apply.
      repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

    • hasInterOptimizerVerifierConfig

      boolean hasInterOptimizerVerifierConfig()
       VerifierConfig specifying the verifiers to be run after every optimizer.
      .tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;
      Returns:
      Whether the interOptimizerVerifierConfig field is set.

    • getInterOptimizerVerifierConfig

      VerifierConfig getInterOptimizerVerifierConfig()
       VerifierConfig specifying the verifiers to be run after every optimizer.
      .tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;
      Returns:
      The interOptimizerVerifierConfig.

    • getInterOptimizerVerifierConfigOrBuilder

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

    • hasPostOptimizationVerifierConfig

      boolean hasPostOptimizationVerifierConfig()
       VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
      .tensorflow.VerifierConfig post_optimization_verifier_config = 301;
      Returns:
      Whether the postOptimizationVerifierConfig field is set.

    • getPostOptimizationVerifierConfig

      VerifierConfig getPostOptimizationVerifierConfig()
       VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
      .tensorflow.VerifierConfig post_optimization_verifier_config = 301;
      Returns:
      The postOptimizationVerifierConfig.

    • getPostOptimizationVerifierConfigOrBuilder

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