// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/core/protobuf/rewriter_config.proto
package org.tensorflow.framework;
public interface RewriterConfigOrBuilder extends
// @@protoc_insertion_point(interface_extends:tensorflow.RewriterConfig)
org.nd4j.shade.protobuf.MessageOrBuilder {
/**
*
* 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;
* @return The enum numeric value on the wire for layoutOptimizer.
*/
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;
* @return The layoutOptimizer.
*/
org.tensorflow.framework.RewriterConfig.Toggle getLayoutOptimizer();
/**
*
* 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;
* @return The enum numeric value on the wire for constantFolding.
*/
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;
* @return The constantFolding.
*/
org.tensorflow.framework.RewriterConfig.Toggle getConstantFolding();
/**
*
* Shape optimizations (default is ON)
* Simplify computations made on shapes.
*
*
* .tensorflow.RewriterConfig.Toggle shape_optimization = 13;
* @return The enum numeric value on the wire for shapeOptimization.
*/
int getShapeOptimizationValue();
/**
*
* Shape optimizations (default is ON)
* Simplify computations made on shapes.
*
*
* .tensorflow.RewriterConfig.Toggle shape_optimization = 13;
* @return The shapeOptimization.
*/
org.tensorflow.framework.RewriterConfig.Toggle getShapeOptimization();
/**
*
* Remapping (default is ON)
* Remap subgraphs onto more efficient implementations.
*
*
* .tensorflow.RewriterConfig.Toggle remapping = 14;
* @return The enum numeric value on the wire for remapping.
*/
int getRemappingValue();
/**
*
* Remapping (default is ON)
* Remap subgraphs onto more efficient implementations.
*
*
* .tensorflow.RewriterConfig.Toggle remapping = 14;
* @return The remapping.
*/
org.tensorflow.framework.RewriterConfig.Toggle getRemapping();
/**
*
* Arithmetic optimizations (default is ON)
* e.g. Simplify arithmetic ops; merge ops with same value (like constants).
*
*
* .tensorflow.RewriterConfig.Toggle arithmetic_optimization = 7;
* @return The enum numeric value on the wire for arithmeticOptimization.
*/
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;
* @return The arithmeticOptimization.
*/
org.tensorflow.framework.RewriterConfig.Toggle getArithmeticOptimization();
/**
*
* Control dependency optimizations (default is ON).
* Remove redundant control dependencies, which may enable other optimization.
*
*
* .tensorflow.RewriterConfig.Toggle dependency_optimization = 8;
* @return The enum numeric value on the wire for dependencyOptimization.
*/
int getDependencyOptimizationValue();
/**
*
* Control dependency optimizations (default is ON).
* Remove redundant control dependencies, which may enable other optimization.
*
*
* .tensorflow.RewriterConfig.Toggle dependency_optimization = 8;
* @return The dependencyOptimization.
*/
org.tensorflow.framework.RewriterConfig.Toggle getDependencyOptimization();
/**
*
* Loop optimizations (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle loop_optimization = 9;
* @return The enum numeric value on the wire for loopOptimization.
*/
int getLoopOptimizationValue();
/**
*
* Loop optimizations (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle loop_optimization = 9;
* @return The loopOptimization.
*/
org.tensorflow.framework.RewriterConfig.Toggle getLoopOptimization();
/**
*
* Function optimizations (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle function_optimization = 10;
* @return The enum numeric value on the wire for functionOptimization.
*/
int getFunctionOptimizationValue();
/**
*
* Function optimizations (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle function_optimization = 10;
* @return The functionOptimization.
*/
org.tensorflow.framework.RewriterConfig.Toggle getFunctionOptimization();
/**
*
* Strips debug-related nodes from the graph (off by default).
*
*
* .tensorflow.RewriterConfig.Toggle debug_stripper = 11;
* @return The enum numeric value on the wire for debugStripper.
*/
int getDebugStripperValue();
/**
*
* Strips debug-related nodes from the graph (off by default).
*
*
* .tensorflow.RewriterConfig.Toggle debug_stripper = 11;
* @return The debugStripper.
*/
org.tensorflow.framework.RewriterConfig.Toggle getDebugStripper();
/**
*
* If true, don't remove unnecessary ops from the graph
*
*
* bool disable_model_pruning = 2;
* @return The disableModelPruning.
*/
boolean getDisableModelPruning();
/**
*
* 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;
* @return The enum numeric value on the wire for scopedAllocatorOptimization.
*/
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;
* @return The scopedAllocatorOptimization.
*/
org.tensorflow.framework.RewriterConfig.Toggle getScopedAllocatorOptimization();
/**
*
* Controls how many times we run the optimizers in meta optimizer (default
* is once).
*
*
* .tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;
* @return The enum numeric value on the wire for metaOptimizerIterations.
*/
int getMetaOptimizerIterationsValue();
/**
*
* Controls how many times we run the optimizers in meta optimizer (default
* is once).
*
*
* .tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;
* @return The metaOptimizerIterations.
*/
org.tensorflow.framework.RewriterConfig.NumIterationsType getMetaOptimizerIterations();
/**
*
* 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;
* @return The enum numeric value on the wire for memoryOptimization.
*/
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;
* @return The memoryOptimization.
*/
org.tensorflow.framework.RewriterConfig.MemOptType getMemoryOptimization();
/**
*
* A node name scope for node names which are valid outputs of recompuations.
* 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;
* @return The memoryOptimizerTargetNodeNameScope.
*/
java.lang.String getMemoryOptimizerTargetNodeNameScope();
/**
*
* A node name scope for node names which are valid outputs of recompuations.
* 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;
* @return The bytes for memoryOptimizerTargetNodeNameScope.
*/
org.nd4j.shade.protobuf.ByteString
getMemoryOptimizerTargetNodeNameScopeBytes();
/**
*
* Configures AutoParallel optimization passes either through the
* meta-optimizer or when manually specified through the optimizers field.
*
*
* .tensorflow.AutoParallelOptions auto_parallel = 5;
* @return Whether the autoParallel field is set.
*/
boolean hasAutoParallel();
/**
*
* Configures AutoParallel optimization passes either through the
* meta-optimizer or when manually specified through the optimizers field.
*
*
* .tensorflow.AutoParallelOptions auto_parallel = 5;
* @return The autoParallel.
*/
org.tensorflow.framework.AutoParallelOptions getAutoParallel();
/**
*
* Configures AutoParallel optimization passes either through the
* meta-optimizer or when manually specified through the optimizers field.
*
*
* .tensorflow.AutoParallelOptions auto_parallel = 5;
*/
org.tensorflow.framework.AutoParallelOptionsOrBuilder getAutoParallelOrBuilder();
/**
* .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
* @return Whether the scopedAllocatorOpts field is set.
*/
boolean hasScopedAllocatorOpts();
/**
* .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
* @return The scopedAllocatorOpts.
*/
org.tensorflow.framework.ScopedAllocatorOptions getScopedAllocatorOpts();
/**
* .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
*/
org.tensorflow.framework.ScopedAllocatorOptionsOrBuilder getScopedAllocatorOptsOrBuilder();
/**
*
* 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 registered optimizers will be run after the base optimizers, in
* the order that they are specified.
*
*
* repeated string optimizers = 100;
* @return A list containing the optimizers.
*/
java.util.List
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 registered optimizers will be run after the base optimizers, in
* the order that they are specified.
*
*
* repeated string optimizers = 100;
* @return The count of optimizers.
*/
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 registered optimizers will be run after the base optimizers, in
* the order that they are specified.
*
*
* repeated string optimizers = 100;
* @param index The index of the element to return.
* @return The optimizers at the given index.
*/
java.lang.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 registered optimizers will be run after the base optimizers, in
* the order that they are specified.
*
*
* repeated string optimizers = 100;
* @param index The index of the value to return.
* @return The bytes of the optimizers at the given index.
*/
org.nd4j.shade.protobuf.ByteString
getOptimizersBytes(int index);
/**
*
* list of CustomGraphOptimizers to apply.
*
*
* repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;
*/
java.util.List
getCustomOptimizersList();
/**
*
* list of CustomGraphOptimizers to apply.
*
*
* repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;
*/
org.tensorflow.framework.RewriterConfig.CustomGraphOptimizer getCustomOptimizers(int index);
/**
*
* list of CustomGraphOptimizers to apply.
*
*
* repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;
*/
int getCustomOptimizersCount();
/**
*
* list of CustomGraphOptimizers to apply.
*
*
* repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;
*/
java.util.List
getCustomOptimizersOrBuilderList();
/**
*
* list of CustomGraphOptimizers to apply.
*
*
* repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;
*/
org.tensorflow.framework.RewriterConfig.CustomGraphOptimizerOrBuilder getCustomOptimizersOrBuilder(
int index);
}
