forked from tensorflow/tensorflow
/
rewriter_config.pb.go
1246 lines (1132 loc) · 64.3 KB
/
rewriter_config.pb.go
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// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.28.1
// protoc v3.21.7
// source: tensorflow/core/protobuf/rewriter_config.proto
package for_core_protos_go_proto
import (
attr_value_go_proto "github.com/galeone/tensorflow/tensorflow/go/core/framework/attr_value_go_proto"
protoreflect "google.golang.org/protobuf/reflect/protoreflect"
protoimpl "google.golang.org/protobuf/runtime/protoimpl"
reflect "reflect"
sync "sync"
)
const (
// Verify that this generated code is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
// Verify that runtime/protoimpl is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
)
type RewriterConfig_Toggle int32
const (
RewriterConfig_DEFAULT RewriterConfig_Toggle = 0
RewriterConfig_ON RewriterConfig_Toggle = 1
RewriterConfig_OFF RewriterConfig_Toggle = 2
// Enable some aggressive optimizations that use assumptions that TF graphs
// may break. For example, assume the shape of a placeholder matches its
// actual feed.
RewriterConfig_AGGRESSIVE RewriterConfig_Toggle = 3
// Run MLIR pass if there's one implemented in TFG, do nothing otherwise.
// I.e., if there's no corresponding TFG pass, it's an OFF. This is supposed
// to be mapped with `ON` and there's no `AGGRESSIVE` in MLIR pass now.
RewriterConfig_EXPERIMENTAL_MLIR RewriterConfig_Toggle = 4
// Run both MLIR and Grappler passes consecutively and MLIR pass will come
// first.
RewriterConfig_EXPERIMENTAL_BOTH RewriterConfig_Toggle = 5
)
// Enum value maps for RewriterConfig_Toggle.
var (
RewriterConfig_Toggle_name = map[int32]string{
0: "DEFAULT",
1: "ON",
2: "OFF",
3: "AGGRESSIVE",
4: "EXPERIMENTAL_MLIR",
5: "EXPERIMENTAL_BOTH",
}
RewriterConfig_Toggle_value = map[string]int32{
"DEFAULT": 0,
"ON": 1,
"OFF": 2,
"AGGRESSIVE": 3,
"EXPERIMENTAL_MLIR": 4,
"EXPERIMENTAL_BOTH": 5,
}
)
func (x RewriterConfig_Toggle) Enum() *RewriterConfig_Toggle {
p := new(RewriterConfig_Toggle)
*p = x
return p
}
func (x RewriterConfig_Toggle) String() string {
return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}
func (RewriterConfig_Toggle) Descriptor() protoreflect.EnumDescriptor {
return file_tensorflow_core_protobuf_rewriter_config_proto_enumTypes[0].Descriptor()
}
func (RewriterConfig_Toggle) Type() protoreflect.EnumType {
return &file_tensorflow_core_protobuf_rewriter_config_proto_enumTypes[0]
}
func (x RewriterConfig_Toggle) Number() protoreflect.EnumNumber {
return protoreflect.EnumNumber(x)
}
// Deprecated: Use RewriterConfig_Toggle.Descriptor instead.
func (RewriterConfig_Toggle) EnumDescriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_rewriter_config_proto_rawDescGZIP(), []int{2, 0}
}
// Enum for layout conversion between NCHW and NHWC on CPU. Default is OFF.
type RewriterConfig_CpuLayout int32
const (
RewriterConfig_NO_CONVERSION_ON_CPU RewriterConfig_CpuLayout = 0
RewriterConfig_NCHW_TO_NHWC RewriterConfig_CpuLayout = 1
RewriterConfig_NHWC_TO_NCHW RewriterConfig_CpuLayout = 2
)
// Enum value maps for RewriterConfig_CpuLayout.
var (
RewriterConfig_CpuLayout_name = map[int32]string{
0: "NO_CONVERSION_ON_CPU",
1: "NCHW_TO_NHWC",
2: "NHWC_TO_NCHW",
}
RewriterConfig_CpuLayout_value = map[string]int32{
"NO_CONVERSION_ON_CPU": 0,
"NCHW_TO_NHWC": 1,
"NHWC_TO_NCHW": 2,
}
)
func (x RewriterConfig_CpuLayout) Enum() *RewriterConfig_CpuLayout {
p := new(RewriterConfig_CpuLayout)
*p = x
return p
}
func (x RewriterConfig_CpuLayout) String() string {
return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}
func (RewriterConfig_CpuLayout) Descriptor() protoreflect.EnumDescriptor {
return file_tensorflow_core_protobuf_rewriter_config_proto_enumTypes[1].Descriptor()
}
func (RewriterConfig_CpuLayout) Type() protoreflect.EnumType {
return &file_tensorflow_core_protobuf_rewriter_config_proto_enumTypes[1]
}
func (x RewriterConfig_CpuLayout) Number() protoreflect.EnumNumber {
return protoreflect.EnumNumber(x)
}
// Deprecated: Use RewriterConfig_CpuLayout.Descriptor instead.
func (RewriterConfig_CpuLayout) EnumDescriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_rewriter_config_proto_rawDescGZIP(), []int{2, 1}
}
// Enum controlling the number of times to run optimizers. The default is to
// run them twice.
type RewriterConfig_NumIterationsType int32
const (
RewriterConfig_DEFAULT_NUM_ITERS RewriterConfig_NumIterationsType = 0
RewriterConfig_ONE RewriterConfig_NumIterationsType = 1
RewriterConfig_TWO RewriterConfig_NumIterationsType = 2
)
// Enum value maps for RewriterConfig_NumIterationsType.
var (
RewriterConfig_NumIterationsType_name = map[int32]string{
0: "DEFAULT_NUM_ITERS",
1: "ONE",
2: "TWO",
}
RewriterConfig_NumIterationsType_value = map[string]int32{
"DEFAULT_NUM_ITERS": 0,
"ONE": 1,
"TWO": 2,
}
)
func (x RewriterConfig_NumIterationsType) Enum() *RewriterConfig_NumIterationsType {
p := new(RewriterConfig_NumIterationsType)
*p = x
return p
}
func (x RewriterConfig_NumIterationsType) String() string {
return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}
func (RewriterConfig_NumIterationsType) Descriptor() protoreflect.EnumDescriptor {
return file_tensorflow_core_protobuf_rewriter_config_proto_enumTypes[2].Descriptor()
}
func (RewriterConfig_NumIterationsType) Type() protoreflect.EnumType {
return &file_tensorflow_core_protobuf_rewriter_config_proto_enumTypes[2]
}
func (x RewriterConfig_NumIterationsType) Number() protoreflect.EnumNumber {
return protoreflect.EnumNumber(x)
}
// Deprecated: Use RewriterConfig_NumIterationsType.Descriptor instead.
func (RewriterConfig_NumIterationsType) EnumDescriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_rewriter_config_proto_rawDescGZIP(), []int{2, 2}
}
type RewriterConfig_MemOptType int32
const (
// The default setting (SCHEDULING and SWAPPING HEURISTICS only)
RewriterConfig_DEFAULT_MEM_OPT RewriterConfig_MemOptType = 0
// Disabled in the meta-optimizer.
RewriterConfig_NO_MEM_OPT RewriterConfig_MemOptType = 1
// Driven by manual op-level annotations.
RewriterConfig_MANUAL RewriterConfig_MemOptType = 2
// Swapping heuristic will move a tensor from the GPU to the CPU and move
// it back when needed to reduce peak memory usage.
RewriterConfig_SWAPPING_HEURISTICS RewriterConfig_MemOptType = 4
// Recomputation heuristics will recompute ops (such as Relu activation)
// during backprop instead of storing them, reducing peak memory usage.
RewriterConfig_RECOMPUTATION_HEURISTICS RewriterConfig_MemOptType = 5
// Scheduling will split big ops such as AddN and try to enforce a schedule
// of the new computations that decreases peak memory usage.
RewriterConfig_SCHEDULING_HEURISTICS RewriterConfig_MemOptType = 6
// Use any combination of swapping and recomputation heuristics.
RewriterConfig_HEURISTICS RewriterConfig_MemOptType = 3
)
// Enum value maps for RewriterConfig_MemOptType.
var (
RewriterConfig_MemOptType_name = map[int32]string{
0: "DEFAULT_MEM_OPT",
1: "NO_MEM_OPT",
2: "MANUAL",
4: "SWAPPING_HEURISTICS",
5: "RECOMPUTATION_HEURISTICS",
6: "SCHEDULING_HEURISTICS",
3: "HEURISTICS",
}
RewriterConfig_MemOptType_value = map[string]int32{
"DEFAULT_MEM_OPT": 0,
"NO_MEM_OPT": 1,
"MANUAL": 2,
"SWAPPING_HEURISTICS": 4,
"RECOMPUTATION_HEURISTICS": 5,
"SCHEDULING_HEURISTICS": 6,
"HEURISTICS": 3,
}
)
func (x RewriterConfig_MemOptType) Enum() *RewriterConfig_MemOptType {
p := new(RewriterConfig_MemOptType)
*p = x
return p
}
func (x RewriterConfig_MemOptType) String() string {
return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}
func (RewriterConfig_MemOptType) Descriptor() protoreflect.EnumDescriptor {
return file_tensorflow_core_protobuf_rewriter_config_proto_enumTypes[3].Descriptor()
}
func (RewriterConfig_MemOptType) Type() protoreflect.EnumType {
return &file_tensorflow_core_protobuf_rewriter_config_proto_enumTypes[3]
}
func (x RewriterConfig_MemOptType) Number() protoreflect.EnumNumber {
return protoreflect.EnumNumber(x)
}
// Deprecated: Use RewriterConfig_MemOptType.Descriptor instead.
func (RewriterConfig_MemOptType) EnumDescriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_rewriter_config_proto_rawDescGZIP(), []int{2, 3}
}
type AutoParallelOptions struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Enable bool `protobuf:"varint,1,opt,name=enable,proto3" json:"enable,omitempty"`
NumReplicas int32 `protobuf:"varint,2,opt,name=num_replicas,json=numReplicas,proto3" json:"num_replicas,omitempty"`
}
func (x *AutoParallelOptions) Reset() {
*x = AutoParallelOptions{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_rewriter_config_proto_msgTypes[0]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *AutoParallelOptions) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*AutoParallelOptions) ProtoMessage() {}
func (x *AutoParallelOptions) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_rewriter_config_proto_msgTypes[0]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use AutoParallelOptions.ProtoReflect.Descriptor instead.
func (*AutoParallelOptions) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_rewriter_config_proto_rawDescGZIP(), []int{0}
}
func (x *AutoParallelOptions) GetEnable() bool {
if x != nil {
return x.Enable
}
return false
}
func (x *AutoParallelOptions) GetNumReplicas() int32 {
if x != nil {
return x.NumReplicas
}
return 0
}
type ScopedAllocatorOptions struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// If present, only perform optimization for these ops.
EnableOp []string `protobuf:"bytes,1,rep,name=enable_op,json=enableOp,proto3" json:"enable_op,omitempty"`
}
func (x *ScopedAllocatorOptions) Reset() {
*x = ScopedAllocatorOptions{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_rewriter_config_proto_msgTypes[1]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *ScopedAllocatorOptions) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*ScopedAllocatorOptions) ProtoMessage() {}
func (x *ScopedAllocatorOptions) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_rewriter_config_proto_msgTypes[1]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use ScopedAllocatorOptions.ProtoReflect.Descriptor instead.
func (*ScopedAllocatorOptions) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_rewriter_config_proto_rawDescGZIP(), []int{1}
}
func (x *ScopedAllocatorOptions) GetEnableOp() []string {
if x != nil {
return x.EnableOp
}
return nil
}
type RewriterConfig struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// CPU Conversion settings between NHCW and NCHW.
CpuLayoutConversion RewriterConfig_CpuLayout `protobuf:"varint,50,opt,name=cpu_layout_conversion,json=cpuLayoutConversion,proto3,enum=tensorflow.RewriterConfig_CpuLayout" json:"cpu_layout_conversion,omitempty"`
// Optimize tensor layouts (default is ON)
// e.g. This will try to use NCHW layout on GPU which is faster.
LayoutOptimizer RewriterConfig_Toggle `protobuf:"varint,1,opt,name=layout_optimizer,json=layoutOptimizer,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"layout_optimizer,omitempty"`
// Fold constants (default is ON)
// Statically infer the value of tensors when possible, and materialize the
// result using constants.
ConstantFolding RewriterConfig_Toggle `protobuf:"varint,3,opt,name=constant_folding,json=constantFolding,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"constant_folding,omitempty"`
// Shape optimizations (default is ON)
// Simplify computations made on shapes.
ShapeOptimization RewriterConfig_Toggle `protobuf:"varint,13,opt,name=shape_optimization,json=shapeOptimization,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"shape_optimization,omitempty"`
// Remapping (default is ON)
// Remap subgraphs onto more efficient implementations.
Remapping RewriterConfig_Toggle `protobuf:"varint,14,opt,name=remapping,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"remapping,omitempty"`
// Common subgraph elimination (default is ON)
// e.g. Simplify arithmetic ops; merge ops with same value (like constants).
CommonSubgraphElimination RewriterConfig_Toggle `protobuf:"varint,24,opt,name=common_subgraph_elimination,json=commonSubgraphElimination,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"common_subgraph_elimination,omitempty"`
// Arithmetic optimizations (default is ON)
// e.g. Simplify arithmetic ops; merge ops with same value (like constants).
ArithmeticOptimization RewriterConfig_Toggle `protobuf:"varint,7,opt,name=arithmetic_optimization,json=arithmeticOptimization,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"arithmetic_optimization,omitempty"`
// Control dependency optimizations (default is ON).
// Remove redundant control dependencies, which may enable other optimization.
DependencyOptimization RewriterConfig_Toggle `protobuf:"varint,8,opt,name=dependency_optimization,json=dependencyOptimization,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"dependency_optimization,omitempty"`
// Loop optimizations (default is ON).
LoopOptimization RewriterConfig_Toggle `protobuf:"varint,9,opt,name=loop_optimization,json=loopOptimization,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"loop_optimization,omitempty"`
// Function optimizations (default is ON).
FunctionOptimization RewriterConfig_Toggle `protobuf:"varint,10,opt,name=function_optimization,json=functionOptimization,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"function_optimization,omitempty"`
// Strips debug-related nodes from the graph (off by default).
DebugStripper RewriterConfig_Toggle `protobuf:"varint,11,opt,name=debug_stripper,json=debugStripper,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"debug_stripper,omitempty"`
// If true, don't remove unnecessary ops from the graph
DisableModelPruning bool `protobuf:"varint,2,opt,name=disable_model_pruning,json=disableModelPruning,proto3" json:"disable_model_pruning,omitempty"`
// Try to allocate some independent Op outputs contiguously in order to
// merge or eliminate downstream Ops (off by default).
ScopedAllocatorOptimization RewriterConfig_Toggle `protobuf:"varint,15,opt,name=scoped_allocator_optimization,json=scopedAllocatorOptimization,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"scoped_allocator_optimization,omitempty"`
// Force small ops onto the CPU (default is OFF).
PinToHostOptimization RewriterConfig_Toggle `protobuf:"varint,18,opt,name=pin_to_host_optimization,json=pinToHostOptimization,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"pin_to_host_optimization,omitempty"`
// Enable the swap of kernel implementations based on the device placement
// (default is ON).
ImplementationSelector RewriterConfig_Toggle `protobuf:"varint,22,opt,name=implementation_selector,json=implementationSelector,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"implementation_selector,omitempty"`
// 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.
AutoMixedPrecision RewriterConfig_Toggle `protobuf:"varint,23,opt,name=auto_mixed_precision,json=autoMixedPrecision,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"auto_mixed_precision,omitempty"`
// 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
AutoMixedPrecisionMkl RewriterConfig_Toggle `protobuf:"varint,25,opt,name=auto_mixed_precision_mkl,json=autoMixedPrecisionMkl,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"auto_mixed_precision_mkl,omitempty"`
// 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
AutoMixedPrecisionOnednnBfloat16 RewriterConfig_Toggle `protobuf:"varint,31,opt,name=auto_mixed_precision_onednn_bfloat16,json=autoMixedPrecisionOnednnBfloat16,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"auto_mixed_precision_onednn_bfloat16,omitempty"`
// 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.
AutoMixedPrecisionCpu RewriterConfig_Toggle `protobuf:"varint,29,opt,name=auto_mixed_precision_cpu,json=autoMixedPrecisionCpu,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"auto_mixed_precision_cpu,omitempty"`
// Disable the entire meta optimizer (off by default).
DisableMetaOptimizer bool `protobuf:"varint,19,opt,name=disable_meta_optimizer,json=disableMetaOptimizer,proto3" json:"disable_meta_optimizer,omitempty"`
// Optimizers registered by plugin (default is ON)
UsePluginOptimizers RewriterConfig_Toggle `protobuf:"varint,28,opt,name=use_plugin_optimizers,json=usePluginOptimizers,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"use_plugin_optimizers,omitempty"`
// Conditional code motion (default is ON).
ExperimentalConditionalCodeMotion RewriterConfig_Toggle `protobuf:"varint,30,opt,name=experimental_conditional_code_motion,json=experimentalConditionalCodeMotion,proto3,enum=tensorflow.RewriterConfig_Toggle" json:"experimental_conditional_code_motion,omitempty"`
// Controls how many times we run the optimizers in meta optimizer (default
// is once).
MetaOptimizerIterations RewriterConfig_NumIterationsType `protobuf:"varint,12,opt,name=meta_optimizer_iterations,json=metaOptimizerIterations,proto3,enum=tensorflow.RewriterConfig_NumIterationsType" json:"meta_optimizer_iterations,omitempty"`
// 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.
MinGraphNodes int32 `protobuf:"varint,17,opt,name=min_graph_nodes,json=minGraphNodes,proto3" json:"min_graph_nodes,omitempty"`
// Disable optimizations that assume compressed tensors. Note that this flag
// is experimental and may be removed in the future.
ExperimentalDisableCompressedTensorOptimization bool `protobuf:"varint,26,opt,name=experimental_disable_compressed_tensor_optimization,json=experimentalDisableCompressedTensorOptimization,proto3" json:"experimental_disable_compressed_tensor_optimization,omitempty"`
// 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.
ExperimentalDisableFoldingQuantizationEmulation bool `protobuf:"varint,27,opt,name=experimental_disable_folding_quantization_emulation,json=experimentalDisableFoldingQuantizationEmulation,proto3" json:"experimental_disable_folding_quantization_emulation,omitempty"`
// Configures memory optimization passes through the meta-optimizer. Has no
// effect on manually requested memory optimization passes in the optimizers
// field.
MemoryOptimization RewriterConfig_MemOptType `protobuf:"varint,4,opt,name=memory_optimization,json=memoryOptimization,proto3,enum=tensorflow.RewriterConfig_MemOptType" json:"memory_optimization,omitempty"`
// 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/"
MemoryOptimizerTargetNodeNameScope string `protobuf:"bytes,6,opt,name=memory_optimizer_target_node_name_scope,json=memoryOptimizerTargetNodeNameScope,proto3" json:"memory_optimizer_target_node_name_scope,omitempty"`
// 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.
MetaOptimizerTimeoutMs int64 `protobuf:"varint,20,opt,name=meta_optimizer_timeout_ms,json=metaOptimizerTimeoutMs,proto3" json:"meta_optimizer_timeout_ms,omitempty"`
// Configures AutoParallel optimization passes either through the
// meta-optimizer or when manually specified through the optimizers field.
AutoParallel *AutoParallelOptions `protobuf:"bytes,5,opt,name=auto_parallel,json=autoParallel,proto3" json:"auto_parallel,omitempty"`
// 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.
FailOnOptimizerErrors bool `protobuf:"varint,21,opt,name=fail_on_optimizer_errors,json=failOnOptimizerErrors,proto3" json:"fail_on_optimizer_errors,omitempty"`
ScopedAllocatorOpts *ScopedAllocatorOptions `protobuf:"bytes,16,opt,name=scoped_allocator_opts,json=scopedAllocatorOpts,proto3" json:"scoped_allocator_opts,omitempty"`
// 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.
Optimizers []string `protobuf:"bytes,100,rep,name=optimizers,proto3" json:"optimizers,omitempty"`
// list of CustomGraphOptimizers to apply.
CustomOptimizers []*RewriterConfig_CustomGraphOptimizer `protobuf:"bytes,200,rep,name=custom_optimizers,json=customOptimizers,proto3" json:"custom_optimizers,omitempty"`
// VerifierConfig specifying the verifiers to be run after every optimizer.
InterOptimizerVerifierConfig *VerifierConfig `protobuf:"bytes,300,opt,name=inter_optimizer_verifier_config,json=interOptimizerVerifierConfig,proto3" json:"inter_optimizer_verifier_config,omitempty"`
// VerifierConfig specifying the verifiers to be run at the end, after all
// optimizers have run.
PostOptimizationVerifierConfig *VerifierConfig `protobuf:"bytes,301,opt,name=post_optimization_verifier_config,json=postOptimizationVerifierConfig,proto3" json:"post_optimization_verifier_config,omitempty"`
}
func (x *RewriterConfig) Reset() {
*x = RewriterConfig{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_rewriter_config_proto_msgTypes[2]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *RewriterConfig) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*RewriterConfig) ProtoMessage() {}
func (x *RewriterConfig) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_rewriter_config_proto_msgTypes[2]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use RewriterConfig.ProtoReflect.Descriptor instead.
func (*RewriterConfig) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_rewriter_config_proto_rawDescGZIP(), []int{2}
}
func (x *RewriterConfig) GetCpuLayoutConversion() RewriterConfig_CpuLayout {
if x != nil {
return x.CpuLayoutConversion
}
return RewriterConfig_NO_CONVERSION_ON_CPU
}
func (x *RewriterConfig) GetLayoutOptimizer() RewriterConfig_Toggle {
if x != nil {
return x.LayoutOptimizer
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetConstantFolding() RewriterConfig_Toggle {
if x != nil {
return x.ConstantFolding
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetShapeOptimization() RewriterConfig_Toggle {
if x != nil {
return x.ShapeOptimization
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetRemapping() RewriterConfig_Toggle {
if x != nil {
return x.Remapping
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetCommonSubgraphElimination() RewriterConfig_Toggle {
if x != nil {
return x.CommonSubgraphElimination
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetArithmeticOptimization() RewriterConfig_Toggle {
if x != nil {
return x.ArithmeticOptimization
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetDependencyOptimization() RewriterConfig_Toggle {
if x != nil {
return x.DependencyOptimization
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetLoopOptimization() RewriterConfig_Toggle {
if x != nil {
return x.LoopOptimization
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetFunctionOptimization() RewriterConfig_Toggle {
if x != nil {
return x.FunctionOptimization
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetDebugStripper() RewriterConfig_Toggle {
if x != nil {
return x.DebugStripper
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetDisableModelPruning() bool {
if x != nil {
return x.DisableModelPruning
}
return false
}
func (x *RewriterConfig) GetScopedAllocatorOptimization() RewriterConfig_Toggle {
if x != nil {
return x.ScopedAllocatorOptimization
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetPinToHostOptimization() RewriterConfig_Toggle {
if x != nil {
return x.PinToHostOptimization
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetImplementationSelector() RewriterConfig_Toggle {
if x != nil {
return x.ImplementationSelector
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetAutoMixedPrecision() RewriterConfig_Toggle {
if x != nil {
return x.AutoMixedPrecision
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetAutoMixedPrecisionMkl() RewriterConfig_Toggle {
if x != nil {
return x.AutoMixedPrecisionMkl
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetAutoMixedPrecisionOnednnBfloat16() RewriterConfig_Toggle {
if x != nil {
return x.AutoMixedPrecisionOnednnBfloat16
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetAutoMixedPrecisionCpu() RewriterConfig_Toggle {
if x != nil {
return x.AutoMixedPrecisionCpu
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetDisableMetaOptimizer() bool {
if x != nil {
return x.DisableMetaOptimizer
}
return false
}
func (x *RewriterConfig) GetUsePluginOptimizers() RewriterConfig_Toggle {
if x != nil {
return x.UsePluginOptimizers
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetExperimentalConditionalCodeMotion() RewriterConfig_Toggle {
if x != nil {
return x.ExperimentalConditionalCodeMotion
}
return RewriterConfig_DEFAULT
}
func (x *RewriterConfig) GetMetaOptimizerIterations() RewriterConfig_NumIterationsType {
if x != nil {
return x.MetaOptimizerIterations
}
return RewriterConfig_DEFAULT_NUM_ITERS
}
func (x *RewriterConfig) GetMinGraphNodes() int32 {
if x != nil {
return x.MinGraphNodes
}
return 0
}
func (x *RewriterConfig) GetExperimentalDisableCompressedTensorOptimization() bool {
if x != nil {
return x.ExperimentalDisableCompressedTensorOptimization
}
return false
}
func (x *RewriterConfig) GetExperimentalDisableFoldingQuantizationEmulation() bool {
if x != nil {
return x.ExperimentalDisableFoldingQuantizationEmulation
}
return false
}
func (x *RewriterConfig) GetMemoryOptimization() RewriterConfig_MemOptType {
if x != nil {
return x.MemoryOptimization
}
return RewriterConfig_DEFAULT_MEM_OPT
}
func (x *RewriterConfig) GetMemoryOptimizerTargetNodeNameScope() string {
if x != nil {
return x.MemoryOptimizerTargetNodeNameScope
}
return ""
}
func (x *RewriterConfig) GetMetaOptimizerTimeoutMs() int64 {
if x != nil {
return x.MetaOptimizerTimeoutMs
}
return 0
}
func (x *RewriterConfig) GetAutoParallel() *AutoParallelOptions {
if x != nil {
return x.AutoParallel
}
return nil
}
func (x *RewriterConfig) GetFailOnOptimizerErrors() bool {
if x != nil {
return x.FailOnOptimizerErrors
}
return false
}
func (x *RewriterConfig) GetScopedAllocatorOpts() *ScopedAllocatorOptions {
if x != nil {
return x.ScopedAllocatorOpts
}
return nil
}
func (x *RewriterConfig) GetOptimizers() []string {
if x != nil {
return x.Optimizers
}
return nil
}
func (x *RewriterConfig) GetCustomOptimizers() []*RewriterConfig_CustomGraphOptimizer {
if x != nil {
return x.CustomOptimizers
}
return nil
}
func (x *RewriterConfig) GetInterOptimizerVerifierConfig() *VerifierConfig {
if x != nil {
return x.InterOptimizerVerifierConfig
}
return nil
}
func (x *RewriterConfig) GetPostOptimizationVerifierConfig() *VerifierConfig {
if x != nil {
return x.PostOptimizationVerifierConfig
}
return nil
}
// Message to describe custom graph optimizer and its parameters
type RewriterConfig_CustomGraphOptimizer struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
ParameterMap map[string]*attr_value_go_proto.AttrValue `protobuf:"bytes,2,rep,name=parameter_map,json=parameterMap,proto3" json:"parameter_map,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
}
func (x *RewriterConfig_CustomGraphOptimizer) Reset() {
*x = RewriterConfig_CustomGraphOptimizer{}
if protoimpl.UnsafeEnabled {
mi := &file_tensorflow_core_protobuf_rewriter_config_proto_msgTypes[3]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *RewriterConfig_CustomGraphOptimizer) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*RewriterConfig_CustomGraphOptimizer) ProtoMessage() {}
func (x *RewriterConfig_CustomGraphOptimizer) ProtoReflect() protoreflect.Message {
mi := &file_tensorflow_core_protobuf_rewriter_config_proto_msgTypes[3]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use RewriterConfig_CustomGraphOptimizer.ProtoReflect.Descriptor instead.
func (*RewriterConfig_CustomGraphOptimizer) Descriptor() ([]byte, []int) {
return file_tensorflow_core_protobuf_rewriter_config_proto_rawDescGZIP(), []int{2, 0}
}
func (x *RewriterConfig_CustomGraphOptimizer) GetName() string {
if x != nil {
return x.Name
}
return ""
}
func (x *RewriterConfig_CustomGraphOptimizer) GetParameterMap() map[string]*attr_value_go_proto.AttrValue {
if x != nil {
return x.ParameterMap
}
return nil
}
var File_tensorflow_core_protobuf_rewriter_config_proto protoreflect.FileDescriptor
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