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Java API for TensorFlow protocol buffers.
// 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)
com.google.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;
*/
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;
*/
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;
*/
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;
*/
org.tensorflow.framework.RewriterConfig.Toggle getConstantFolding();
/**
*
* Shape optimizations (default is ON)
* Simplify computations made on shapes.
*
*
* .tensorflow.RewriterConfig.Toggle shape_optimization = 13;
*/
int getShapeOptimizationValue();
/**
*
* Shape optimizations (default is ON)
* Simplify computations made on shapes.
*
*
* .tensorflow.RewriterConfig.Toggle shape_optimization = 13;
*/
org.tensorflow.framework.RewriterConfig.Toggle getShapeOptimization();
/**
*
* Remapping (default is ON)
* Remap subgraphs onto more efficient implementations.
*
*
* .tensorflow.RewriterConfig.Toggle remapping = 14;
*/
int getRemappingValue();
/**
*
* Remapping (default is ON)
* Remap subgraphs onto more efficient implementations.
*
*
* .tensorflow.RewriterConfig.Toggle remapping = 14;
*/
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;
*/
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;
*/
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;
*/
int getDependencyOptimizationValue();
/**
*
* Control dependency optimizations (default is ON).
* Remove redundant control dependencies, which may enable other optimization.
*
*
* .tensorflow.RewriterConfig.Toggle dependency_optimization = 8;
*/
org.tensorflow.framework.RewriterConfig.Toggle getDependencyOptimization();
/**
*
* Loop optimizations (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle loop_optimization = 9;
*/
int getLoopOptimizationValue();
/**
*
* Loop optimizations (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle loop_optimization = 9;
*/
org.tensorflow.framework.RewriterConfig.Toggle getLoopOptimization();
/**
*
* Function optimizations (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle function_optimization = 10;
*/
int getFunctionOptimizationValue();
/**
*
* Function optimizations (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle function_optimization = 10;
*/
org.tensorflow.framework.RewriterConfig.Toggle getFunctionOptimization();
/**
*
* Strips debug-related nodes from the graph (off by default).
*
*
* .tensorflow.RewriterConfig.Toggle debug_stripper = 11;
*/
int getDebugStripperValue();
/**
*
* Strips debug-related nodes from the graph (off by default).
*
*
* .tensorflow.RewriterConfig.Toggle debug_stripper = 11;
*/
org.tensorflow.framework.RewriterConfig.Toggle getDebugStripper();
/**
*
* If true, don't remove unnecessary ops from the graph
*
*
* bool disable_model_pruning = 2;
*/
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;
*/
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;
*/
org.tensorflow.framework.RewriterConfig.Toggle getScopedAllocatorOptimization();
/**
*
* Force small ops onto the CPU (default is OFF).
*
*
* .tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;
*/
int getPinToHostOptimizationValue();
/**
*
* Force small ops onto the CPU (default is OFF).
*
*
* .tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;
*/
org.tensorflow.framework.RewriterConfig.Toggle getPinToHostOptimization();
/**
*
* Enable the swap of kernel implementations based on the device placement
* (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle implementation_selector = 22;
*/
int getImplementationSelectorValue();
/**
*
* Enable the swap of kernel implementations based on the device placement
* (default is ON).
*
*
* .tensorflow.RewriterConfig.Toggle implementation_selector = 22;
*/
org.tensorflow.framework.RewriterConfig.Toggle getImplementationSelector();
/**
*
* Optimize data types (default is OFF).
* e.g., 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;
*/
int getAutoMixedPrecisionValue();
/**
*
* Optimize data types (default is OFF).
* e.g., 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;
*/
org.tensorflow.framework.RewriterConfig.Toggle getAutoMixedPrecision();
/**
*
* Disable the entire meta optimizer (off by default).
*
*
* bool disable_meta_optimizer = 19;
*/
boolean getDisableMetaOptimizer();
/**
*
* Controls how many times we run the optimizers in meta optimizer (default
* is once).
*
*
* .tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;
*/
int getMetaOptimizerIterationsValue();
/**
*
* Controls how many times we run the optimizers in meta optimizer (default
* is once).
*
*
* .tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;
*/
org.tensorflow.framework.RewriterConfig.NumIterationsType getMetaOptimizerIterations();
/**
*
* 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;
*/
int getMinGraphNodes();
/**
*
* 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;
*/
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;
*/
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;
*/
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;
*/
com.google.protobuf.ByteString
getMemoryOptimizerTargetNodeNameScopeBytes();
/**
*
* 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;
*/
long getMetaOptimizerTimeoutMs();
/**
*
* Configures AutoParallel optimization passes either through the
* meta-optimizer or when manually specified through the optimizers field.
*
*
* .tensorflow.AutoParallelOptions auto_parallel = 5;
*/
boolean hasAutoParallel();
/**
*
* 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.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();
/**
*
* 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;
*/
boolean getFailOnOptimizerErrors();
/**
* .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
*/
boolean hasScopedAllocatorOpts();
/**
* .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
*/
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 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;
*/
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 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;
*/
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;
*/
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 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;
*/
com.google.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);
/**
*
* VerifierConfig specifying the verifiers to be run after every optimizer.
*
*
* .tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;
*/
boolean hasInterOptimizerVerifierConfig();
/**
*
* VerifierConfig specifying the verifiers to be run after every optimizer.
*
*
* .tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;
*/
org.tensorflow.framework.VerifierConfig getInterOptimizerVerifierConfig();
/**
*
* VerifierConfig specifying the verifiers to be run after every optimizer.
*
*
* .tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;
*/
org.tensorflow.framework.VerifierConfigOrBuilder getInterOptimizerVerifierConfigOrBuilder();
/**
*
* VerifierConfig specifying the verifiers to be run at the end, after all
* optimizers have run.
*
*
* .tensorflow.VerifierConfig post_optimization_verifier_config = 301;
*/
boolean hasPostOptimizationVerifierConfig();
/**
*
* VerifierConfig specifying the verifiers to be run at the end, after all
* optimizers have run.
*
*
* .tensorflow.VerifierConfig post_optimization_verifier_config = 301;
*/
org.tensorflow.framework.VerifierConfig getPostOptimizationVerifierConfig();
/**
*
* VerifierConfig specifying the verifiers to be run at the end, after all
* optimizers have run.
*
*
* .tensorflow.VerifierConfig post_optimization_verifier_config = 301;
*/
org.tensorflow.framework.VerifierConfigOrBuilder getPostOptimizationVerifierConfigOrBuilder();
}