RewriterConfig

classe final pública RewriterConfig

 Graph rewriting is experimental and subject to change, not covered by any
 API stability guarantees.
 

Tipo de protobuf tensorflow.RewriterConfig

Classes aninhadas

aula	RewriterConfig.Builder		Graph rewriting is experimental and subject to change, not covered by any API stability guarantees.
enumeração	RewriterConfig.CpuLayout		Enum for layout conversion between NCHW and NHWC on CPU.
aula	RewriterConfig.CustomGraphOptimizer		Message to describe custom graph optimizer and its parameters Tipo de protobuf tensorflow.RewriterConfig.CustomGraphOptimizer
interface	RewriterConfig.CustomGraphOptimizerOrBuilder
enumeração	RewriterConfig.MemOptType		Protobuf enum tensorflow.RewriterConfig.MemOptType
enumeração	RewriterConfig.NumIterationsType		Enum controlling the number of times to run optimizers.
enumeração	RewriterConfig.Toggle		Protobuf enum tensorflow.RewriterConfig.Toggle

Constantes

interno	ARITHMETIC_OPTIMIZATION_FIELD_NUMBER
interno	AUTO_MIXED_PRECISION_FIELD_NUMBER
interno	AUTO_MIXED_PRECISION_MKL_FIELD_NUMBER
interno	AUTO_PARALLEL_FIELD_NUMBER
interno	COMMON_SUBGRAPH_ELIMINATION_FIELD_NUMBER
interno	CONSTANT_FOLDING_FIELD_NUMBER
interno	CPU_LAYOUT_CONVERSION_FIELD_NUMBER
interno	CUSTOM_OPTIMIZERS_FIELD_NUMBER
interno	DEBUG_STRIPPER_FIELD_NUMBER
interno	DEPENDENCY_OPTIMIZATION_FIELD_NUMBER
interno	DISABLE_META_OPTIMIZER_FIELD_NUMBER
interno	DISABLE_MODEL_PRUNING_FIELD_NUMBER
interno	EXPERIMENTAL_DISABLE_COMPRESSED_TENSOR_OPTIMIZATION_FIELD_NUMBER
interno	FAIL_ON_OPTIMIZER_ERRORS_FIELD_NUMBER
interno	FUNCTION_OPTIMIZATION_FIELD_NUMBER
interno	IMPLEMENTATION_SELECTOR_FIELD_NUMBER
interno	INTER_OPTIMIZER_VERIFIER_CONFIG_FIELD_NUMBER
interno	LAYOUT_OPTIMIZER_FIELD_NUMBER
interno	LOOP_OPTIMIZATION_FIELD_NUMBER
interno	MEMORY_OPTIMIZATION_FIELD_NUMBER
interno	MEMORY_OPTIMIZER_TARGET_NODE_NAME_SCOPE_FIELD_NUMBER
interno	META_OPTIMIZER_ITERATIONS_FIELD_NUMBER
interno	META_OPTIMIZER_TIMEOUT_MS_FIELD_NUMBER
interno	MIN_GRAPH_NODES_FIELD_NUMBER
interno	OPTIMIZERS_FIELD_NUMBER
interno	PIN_TO_HOST_OPTIMIZATION_FIELD_NUMBER
interno	POST_OPTIMIZATION_VERIFIER_CONFIG_FIELD_NUMBER
interno	REMAPPING_FIELD_NUMBER
interno	SCOPED_ALLOCATOR_OPTIMIZATION_FIELD_NUMBER
interno	SCOPED_ALLOCATOR_OPTS_FIELD_NUMBER
interno	SHAPE_OPTIMIZATION_FIELD_NUMBER

Métodos Públicos

booleano	é igual (objeto obj)
RewriterConfig.Toggle	getArithmeticOptimization () Arithmetic optimizations (default is ON) e.g.
interno	getArithmeticOptimizationValue () Arithmetic optimizations (default is ON) e.g.
RewriterConfig.Toggle	getAutoMixedPrecision () Optimize data types for CUDA (default is OFF).
RewriterConfig.Toggle	getAutoMixedPrecisionMkl () Optimize data types for MKL (default is OFF).
interno	getAutoMixedPrecisionMklValue () Optimize data types for MKL (default is OFF).
interno	getAutoMixedPrecisionValue () Optimize data types for CUDA (default is OFF).
Opções AutoParallel	getAutoParallel () Configures AutoParallel optimization passes either through the meta-optimizer or when manually specified through the optimizers field.
AutoParallelOptionsOrBuilder	getAutoParallelOrBuilder () Configures AutoParallel optimization passes either through the meta-optimizer or when manually specified through the optimizers field.
RewriterConfig.Toggle	getCommonSubgraphElimination () Common subgraph elimination (default is ON) e.g.
interno	getCommonSubgraphEliminationValue () Common subgraph elimination (default is ON) e.g.
RewriterConfig.Toggle	getConstantFolding () Fold constants (default is ON) Statically infer the value of tensors when possible, and materialize the result using constants.
interno	getConstantFoldingValue () Fold constants (default is ON) Statically infer the value of tensors when possible, and materialize the result using constants.
RewriterConfig.CpuLayout	getCpuLayoutConversion () CPU Conversion settings between NHCW and NCHW.
interno	getCpuLayoutConversionValue () CPU Conversion settings between NHCW and NCHW.
RewriterConfig.CustomGraphOptimizer	getCustomOptimizers (índice interno) list of CustomGraphOptimizers to apply.
interno	getCustomOptimizersCount () list of CustomGraphOptimizers to apply.
Lista< RewriterConfig.CustomGraphOptimizer >	getCustomOptimizersList () list of CustomGraphOptimizers to apply.
RewriterConfig.CustomGraphOptimizerOrBuilder	getCustomOptimizersOrBuilder (índice interno) list of CustomGraphOptimizers to apply.
Lista<? estende RewriterConfig.CustomGraphOptimizerOrBuilder >	getCustomOptimizersOrBuilderList () list of CustomGraphOptimizers to apply.
RewriterConfig.Toggle	getDebugStripper () Strips debug-related nodes from the graph (off by default).
interno	getDebugStripperValue () Strips debug-related nodes from the graph (off by default).
RewriterConfig estático	getDefaultInstance ()
RewriterConfig	getDefaultInstanceForType ()
RewriterConfig.Toggle	getDependencyOptimization () Control dependency optimizations (default is ON).
interno	getDependencyOptimizationValue () Control dependency optimizations (default is ON).
final estático com.google.protobuf.Descriptors.Descriptor	getDescriptor ()
booleano	getDisableMetaOptimizer () Disable the entire meta optimizer (off by default).
booleano	getDisableModelPruning () If true, don't remove unnecessary ops from the graph bool disable_model_pruning = 2;
booleano	getExperimentalDisableCompressedTensorOptimization () Disable optimizations that assume compressed tensors.
booleano	getFailOnOptimizerErrors () If true, any optimization pass failing will cause the MetaOptimizer to stop with an error.
RewriterConfig.Toggle	getFunctionOptimization () Function optimizations (default is ON).
interno	getFunctionOptimizationValue () Function optimizations (default is ON).
RewriterConfig.Toggle	getImplementationSelector () Enable the swap of kernel implementations based on the device placement (default is ON).
interno	getImplementationSelectorValue () Enable the swap of kernel implementations based on the device placement (default is ON).
VerificadorConfig	getInterOptimizerVerifierConfig () VerifierConfig specifying the verifiers to be run after every optimizer.
VerifierConfigOrBuilder	getInterOptimizerVerifierConfigOrBuilder () VerifierConfig specifying the verifiers to be run after every optimizer.
RewriterConfig.Toggle	getLayoutOptimizer () Optimize tensor layouts (default is ON) e.g.
interno	getLayoutOptimizerValue () Optimize tensor layouts (default is ON) e.g.
RewriterConfig.Toggle	getLoopOptimization () Loop optimizations (default is ON).
interno	getLoopOptimizationValue () Loop optimizations (default is ON).
RewriterConfig.MemOptType	getMemoryOptimization () Configures memory optimization passes through the meta-optimizer.
interno	getMemoryOptimizationValue () Configures memory optimization passes through the meta-optimizer.
Corda	getMemoryOptimizerTargetNodeNameScope () A node name scope for node names which are valid outputs of recomputations.
com.google.protobuf.ByteString	getMemoryOptimizerTargetNodeNameScopeBytes () A node name scope for node names which are valid outputs of recomputations.
RewriterConfig.NumIterationsType	getMetaOptimizerIterations () Controls how many times we run the optimizers in meta optimizer (default is once).
interno	getMetaOptimizerIterationsValue () Controls how many times we run the optimizers in meta optimizer (default is once).
longo	getMetaOptimizerTimeoutMs () Maximum number of milliseconds to spend optimizing a single graph before timing out.
interno	getMinGraphNodes () The minimum number of nodes in a graph to optimizer.
Corda	getOptimizers (índice interno) 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).
com.google.protobuf.ByteString	getOptimizersBytes (índice interno) 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).
interno	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).
com.google.protobuf.ProtocolStringList	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).
	getParserForType ()
RewriterConfig.Toggle	getPinToHostOptimization () Force small ops onto the CPU (default is OFF).
interno	getPinToHostOptimizationValue () Force small ops onto the CPU (default is OFF).
VerificadorConfig	getPostOptimizationVerifierConfig () VerifierConfig specifying the verifiers to be run at the end, after all optimizers have run.
VerifierConfigOrBuilder	getPostOptimizationVerifierConfigOrBuilder () VerifierConfig specifying the verifiers to be run at the end, after all optimizers have run.
RewriterConfig.Toggle	getRemapeamento () Remapping (default is ON) Remap subgraphs onto more efficient implementations.
interno	getRemappingValue () Remapping (default is ON) Remap subgraphs onto more efficient implementations.
RewriterConfig.Toggle	getScopedAllocatorOptimization () Try to allocate some independent Op outputs contiguously in order to merge or eliminate downstream Ops (off by default).
interno	getScopedAllocatorOptimizationValue () Try to allocate some independent Op outputs contiguously in order to merge or eliminate downstream Ops (off by default).
Opções de Allocator com Escopo	getScopedAllocatorOpts () .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
ScopedAllocatorOptionsOrBuilder	getScopedAllocatorOptsOrBuilder () .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
interno	getSerializedSize ()
RewriterConfig.Toggle	getShapeOptimization () Shape optimizations (default is ON) Simplify computations made on shapes.
interno	getShapeOptimizationValue () Shape optimizations (default is ON) Simplify computations made on shapes.
final com.google.protobuf.UnknownFieldSet	getUnknownFields ()
booleano	hasAutoParallel () Configures AutoParallel optimization passes either through the meta-optimizer or when manually specified through the optimizers field.
booleano	hasInterOptimizerVerifierConfig () VerifierConfig specifying the verifiers to be run after every optimizer.
booleano	hasPostOptimizationVerifierConfig () VerifierConfig specifying the verifiers to be run at the end, after all optimizers have run.
booleano	hasScopedAllocatorOpts () .tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;
interno	código hash ()
booleano final	éinicializado ()
RewriterConfig.Builder estático	novoConstrutor ()
RewriterConfig.Builder estático	newBuilder (protótipo RewriterConfig )
RewriterConfig.Builder	novoBuilderForType ()
RewriterConfig estático	parseDelimitedFrom (entrada InputStream)
RewriterConfig estático	parseDelimitedFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RewriterConfig estático	parseFrom (dados de ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RewriterConfig estático	parseFrom (entrada com.google.protobuf.CodedInputStream)
RewriterConfig estático	parseFrom (byte[] dados, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RewriterConfig estático	parseFrom (dados de ByteBuffer)
RewriterConfig estático	parseFrom (entrada com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RewriterConfig estático	parseFrom (dados com.google.protobuf.ByteString)
RewriterConfig estático	parseFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RewriterConfig estático	parseFrom (dados com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
estático	analisador ()
RewriterConfig.Builder	paraConstrutor ()
vazio	writeTo (saída com.google.protobuf.CodedOutputStream)

Métodos herdados

Da classe java.lang.Object

booleano	é igual (objeto arg0)
aula final<?>	getClass ()
interno	código hash ()
vazio final	notificar ()
vazio final	notificar todos ()
Corda	toString ()
vazio final	espere (long arg0, int arg1)
vazio final	espere (arg0 longo)
vazio final	espere ()

Da interface org.tensorflow.proto.framework.RewriterConfigOrBuilder

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

Constantes

público estático final int ARITHMETIC_OPTIMIZATION_FIELD_NUMBER

Valor Constante: 7

público estático final int AUTO_MIXED_PRECISION_FIELD_NUMBER

Valor Constante: 23

público estático final int AUTO_MIXED_PRECISION_MKL_FIELD_NUMBER

Valor Constante: 25

público estático final int AUTO_PARALLEL_FIELD_NUMBER

Valor Constante: 5

int final estático público COMMON_SUBGRAPH_ELIMINATION_FIELD_NUMBER

Valor Constante: 24

int final estático público CONSTANT_FOLDING_FIELD_NUMBER

Valor Constante: 3

público estático final int CPU_LAYOUT_CONVERSION_FIELD_NUMBER

Valor Constante: 50

público estático final int CUSTOM_OPTIMIZERS_FIELD_NUMBER

Valor Constante: 200

público estático final int DEBUG_STRIPPER_FIELD_NUMBER

Valor Constante: 11

público estático final int DEPENDENCY_OPTIMIZATION_FIELD_NUMBER

Valor Constante: 8

público estático final int DISABLE_META_OPTIMIZER_FIELD_NUMBER

Valor Constante: 19

público estático final int DISABLE_MODEL_PRUNING_FIELD_NUMBER

Valor Constante: 2

público estático final int EXPERIMENTAL_DISABLE_COMPRESSED_TENSOR_OPTIMIZATION_FIELD_NUMBER

Valor Constante: 26

int final estático público FAIL_ON_OPTIMIZER_ERRORS_FIELD_NUMBER

Valor Constante: 21

público estático final int FUNCTION_OPTIMIZATION_FIELD_NUMBER

Valor Constante: 10

público estático final int IMPLEMENTATION_SELECTOR_FIELD_NUMBER

Valor Constante: 22

público estático final int INTER_OPTIMIZER_VERIFIER_CONFIG_FIELD_NUMBER

Valor Constante: 300

público estático final int LAYOUT_OPTIMIZER_FIELD_NUMBER

Valor Constante: 1

público estático final int LOOP_OPTIMIZATION_FIELD_NUMBER

Valor Constante: 9

público estático final int MEMORY_OPTIMIZATION_FIELD_NUMBER

Valor Constante: 4

público estático final int MEMORY_OPTIMIZER_TARGET_NODE_NAME_SCOPE_FIELD_NUMBER

Valor Constante: 6

público estático final int META_OPTIMIZER_ITERATIONS_FIELD_NUMBER

Valor Constante: 12

público estático final int META_OPTIMIZER_TIMEOUT_MS_FIELD_NUMBER

Valor Constante: 20

público estático final int MIN_GRAPH_NODES_FIELD_NUMBER

Valor Constante: 17

público estático final int OPTIMIZERS_FIELD_NUMBER

Valor Constante: 100

público estático final int PIN_TO_HOST_OPTIMIZATION_FIELD_NUMBER

Valor Constante: 18

público estático final int POST_OPTIMIZATION_VERIFIER_CONFIG_FIELD_NUMBER

Valor Constante: 301

público estático final int REMAPPING_FIELD_NUMBER

Valor Constante: 14

público estático final int SCOPED_ALLOCATOR_OPTIMIZATION_FIELD_NUMBER

Valor Constante: 15

público estático final int SCOPED_ALLOCATOR_OPTS_FIELD_NUMBER

Valor Constante: 16

público estático final int SHAPE_OPTIMIZATION_FIELD_NUMBER

Valor Constante: 13

Métodos Públicos

booleano público é igual (Object obj)

public 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;

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;

public 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;

public 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;

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;

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;

public AutoParallelOptionsgetAutoParallel ( )

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

.tensorflow.AutoParallelOptions auto_parallel = 5;

public AutoParallelOptionsOrBuilder getAutoParallelOrBuilder ()

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

.tensorflow.AutoParallelOptions auto_parallel = 5;

public 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 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;

public 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;

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;

public RewriterConfig.CpuLayout getCpuLayoutConversion ()

 CPU Conversion settings between NHCW and NCHW.
 

.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

público int getCpuLayoutConversionValue ()

 CPU Conversion settings between NHCW and NCHW.
 

.tensorflow.RewriterConfig.CpuLayout cpu_layout_conversion = 50;

público RewriterConfig.CustomGraphOptimizer getCustomOptimizers (índice int)

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

público int getCustomOptimizersCount ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

Lista pública< RewriterConfig.CustomGraphOptimizer > getCustomOptimizersList ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

público RewriterConfig.CustomGraphOptimizerOrBuilder getCustomOptimizersOrBuilder (índice int)

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

Lista pública<? estende RewriterConfig.CustomGraphOptimizerOrBuilder > getCustomOptimizersOrBuilderList ()

 list of CustomGraphOptimizers to apply.
 

repeated .tensorflow.RewriterConfig.CustomGraphOptimizer custom_optimizers = 200;

public RewriterConfig.Toggle getDebugStripper ()

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

.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

público int getDebugStripperValue ()

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

.tensorflow.RewriterConfig.Toggle debug_stripper = 11;

público estático RewriterConfig getDefaultInstance ()

public RewriterConfig getDefaultInstanceForType ()

public RewriterConfig.Toggle getDependencyOptimization ()

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

.tensorflow.RewriterConfig.Toggle dependency_optimization = 8;

público int getDependencyOptimizationValue ()

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

.tensorflow.RewriterConfig.Toggle dependency_optimization = 8;

final estático público com.google.protobuf.Descriptors.Descriptor getDescriptor ()

getDisableMetaOptimizer booleano público ()

 Disable the entire meta optimizer (off by default).
 

bool disable_meta_optimizer = 19;

getDisableModelPruning booleano público ()

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

bool disable_model_pruning = 2;

público 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 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;

public RewriterConfig.Toggle getFunctionOptimization ()

 Function optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle function_optimization = 10;

public int getFunctionOptimizationValue ()

 Function optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle function_optimization = 10;

public RewriterConfig.Toggle getImplementationSelector ()

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

.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

público int getImplementationSelectorValue ()

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

.tensorflow.RewriterConfig.Toggle implementation_selector = 22;

public VerifierConfig getInterOptimizerVerifierConfig ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

public VerifierConfigOrBuilder getInterOptimizerVerifierConfigOrBuilder ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

public 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;

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;

public RewriterConfig.Toggle getLoopOptimization ()

 Loop optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

público int getLoopOptimizationValue ()

 Loop optimizations (default is ON).
 

.tensorflow.RewriterConfig.Toggle loop_optimization = 9;

public 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;

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;

String 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;

public 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;

public RewriterConfig.NumIterationsType getMetaOptimizerIterations ()

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

.tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;

público int getMetaOptimizerIterationsValue ()

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

.tensorflow.RewriterConfig.NumIterationsType meta_optimizer_iterations = 12;

público longo 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;

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;

string 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;

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;

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;

público com.google.protobuf.ProtocolStringList 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;

público getParserForType ()

public RewriterConfig.Toggle getPinToHostOptimization ()

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

.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

público int getPinToHostOptimizationValue ()

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

.tensorflow.RewriterConfig.Toggle pin_to_host_optimization = 18;

public VerifierConfig getPostOptimizationVerifierConfig ()

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

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

public VerifierConfigOrBuilder getPostOptimizationVerifierConfigOrBuilder ()

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

.tensorflow.VerifierConfig post_optimization_verifier_config = 301;

public RewriterConfig.Toggle getRemapping ()

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

.tensorflow.RewriterConfig.Toggle remapping = 14;

public int getRemappingValue ()

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

.tensorflow.RewriterConfig.Toggle remapping = 14;

public 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;

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;

public ScopedAllocatorOptionsgetScopedAllocatorOpts ( )

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

public ScopedAllocatorOptionsOrBuilder getScopedAllocatorOptsOrBuilder ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

público int getSerializedSize ()

public RewriterConfig.Toggle getShapeOptimization ()

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

.tensorflow.RewriterConfig.Toggle shape_optimization = 13;

público int getShapeOptimizationValue ()

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

.tensorflow.RewriterConfig.Toggle shape_optimization = 13;

final público com.google.protobuf.UnknownFieldSet getUnknownFields ()

público booleano hasAutoParallel ()

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

.tensorflow.AutoParallelOptions auto_parallel = 5;

hasInterOptimizerVerifierConfig booleano público ()

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

.tensorflow.VerifierConfig inter_optimizer_verifier_config = 300;

hasPostOptimizationVerifierConfig booleano 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 público ()

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

hashCode int público ()

público final booleano isInitialized ()

público estático RewriterConfig.Builder newBuilder ()

public static RewriterConfig.Builder newBuilder (protótipo RewriterConfig )

público RewriterConfig.Builder newBuilderForType ()

public static RewriterConfig parseDelimitedFrom (entrada InputStream)

Lança

IOException

public static RewriterConfig parseDelimitedFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança

IOException

public static RewriterConfig parseFrom (dados ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança

InvalidProtocolBufferException

public static RewriterConfig parseFrom (entrada com.google.protobuf.CodedInputStream)

Lança

IOException

public static RewriterConfig parseFrom (byte[] dados, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança

InvalidProtocolBufferException

public static RewriterConfig parseFrom (dados ByteBuffer)

Lança

InvalidProtocolBufferException

public static RewriterConfig parseFrom (entrada com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança

IOException

public static RewriterConfig parseFrom (dados com.google.protobuf.ByteString)

Lança

InvalidProtocolBufferException

public static RewriterConfig parseFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança

IOException

public static RewriterConfig parseFrom (dados com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança

InvalidProtocolBufferException

estática pública analisador ()

público RewriterConfig.Builder toBuilder ()

public void writeTo (saída com.google.protobuf.CodedOutputStream)

Lança

IOException