xref: /external/tensorflow/tensorflow/compiler/mlir/tensorflow/transforms/passes.h

/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_COMPILER_MLIR_TENSORFLOW_TRANSFORMS_PASSES_H_
#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_TRANSFORMS_PASSES_H_

#include <memory>

#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "mlir/IR/PatternMatch.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.h"

namespace mlir {

// Creates a pass that breaks up an island with multiple ops into multiple
// islands, each with a single op.
std::unique_ptr<OperationPass<ModuleOp>> CreateBreakUpIslandsPass();

// Creates a pass that converts mlir functions consisting of mlir ops into a
// tf_executor dialect as a single island.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateFunctionalToExecutorDialectConversionPass();

// Creates a pass that lifts inner ops of tf_executor.island ops in
// tf_executor.graph into the same block as the tf_executor.graph.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateExecutorDialectToFunctionalConversionPass();

namespace TF {
// Creates a pass that drops `shape_invariant` attribute from While/WhileRegion
// ops.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateDropWhileShapeInvariantPass();

// Creates a pass that drops `shape_invariant` attribute from While/WhileRegion
// ops within device cluster.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateDropWhileShapeInvariantInDeviceClusterPass();

// Creates a pass that moves writes to replicate invariant resource variables
// outside tf_device.replicate op.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateHoistReplicateInvariantResourceWritesPass();

// Transforms functional control flow operations in the TensorFlow dialect to
// MLIR Control Flow Graph (CFG) form.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateTFFunctionalControlFlowToCFG();

// Transforms functional control flow operations in the TensorFlow dialect to
// their region based counterparts.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFFunctionalControlFlowToRegions();

// Transforms region bases control flow operations in the TensorFlow dialect to
// their functional counterparts.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFRegionControlFlowToFunctional();

// Materialize the MlirPassthroughOp by replacing it with the MLIR module
// attached as an attribute.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateMaterializePassthroughOpPass();

// Performs Shape Inference on the TensorFlow dialect using the global registry.
std::unique_ptr<OperationPass<ModuleOp>> CreateTFShapeInferencePass();

// Performs TF.data optimizations.
std::unique_ptr<OperationPass<func::FuncOp>> CreateTFDataOptimizationPass();

std::unique_ptr<OperationPass<func::FuncOp>> CreateMoveTransposesPass();
std::unique_ptr<OperationPass<func::FuncOp>> CreateLayoutAssignmentPass();

// Guarantee that all FuncOp's have a single use.
std::unique_ptr<OperationPass<ModuleOp>> CreateGuaranteeAllFuncsOneUsePass();

// Optional pass which will unroll BatchMatMul and use only MatMul
std::unique_ptr<OperationPass<func::FuncOp>> CreateUnrollBatchMatMulPassPass();

// Optional pass which will map TF BatchMatMul to TF Einsum
std::unique_ptr<OperationPass<func::FuncOp>> CreateBatchMatMulToEinsumPass();

// Pass that transform Einsum to other TF Ops for the supported variants.
std::unique_ptr<OperationPass<func::FuncOp>> CreateTransformEinsumPass();

// Optimizes Tensorflow graph.
std::unique_ptr<OperationPass<func::FuncOp>> CreateTFOptimizePass();
void RegisterTFOptimizePassPipeline();

// Creates pass to rewrite RecvTPUEmbeddingActivationsOp and
// SendTPUEmbeddingGradients ops to internal variants.
std::unique_ptr<OperationPass<func::FuncOp>> CreateRewriteTPUEmbeddingOpsPass();

// Performs specific fusion for GPU targets.
std::unique_ptr<OperationPass<func::FuncOp>> CreateGpuOpFusionPass();

// Creates a pass that decomposes to be compiled ReduceDataset ops into a while
// loop that iterates the dataset and calls the reduction function.
std::unique_ptr<OperationPass<func::FuncOp>> CreateDecomposeReduceDatasetPass();

// Create a pass that convert ops that copy tensors between devices, e.g.
// tf.Identity.
std::unique_ptr<OperationPass<mlir::func::FuncOp>>
CreateTensorDeviceCopyConversionPass();

// Returns a pass that folds tf.BroadcastTo nodes with subsequent nodes if they
// have built in broadcasting support.
std::unique_ptr<OperationPass<func::FuncOp>> CreateBroadcastFoldPass();

void populateTfControlFlowToScfPatterns(MLIRContext* context,
                                        RewritePatternSet* patterns);
// Create a pass to convert TensorFlow control flow to SCF.
std::unique_ptr<OperationPass<ModuleOp>> createConvertTfControlFlowToScfPass();

struct LayoutOptimizationPipelineOptions
    : public PassPipelineOptions<LayoutOptimizationPipelineOptions> {
  Option<std::string> force_data_format{
      *this, "force-data-format",
      llvm::cl::desc("Force data format for all layout sensitive ops")};
  Option<bool> skip_fold_transpose_in_ops{
      *this, "skip-fold-transpose-in-ops",
      llvm::cl::desc("Skip folding transpose operands in Ops which can support "
                     "different layouts.")};
};

// Layout optimization assigns optimal data layout for layout sensitive
// operations, and cancels all redundant transposes.
void CreateLayoutOptimizationPipeline(
    OpPassManager& pm,  // NOLINT - MLIR contract is pass by mutable reference.
    const LayoutOptimizationPipelineOptions& options);

struct StandardPipelineOptions
    : public PassPipelineOptions<StandardPipelineOptions> {
  Option<bool> enable_inliner{*this, "enable-inliner",
                              llvm::cl::desc("Enable inliner."),
                              llvm::cl::init(false)};
  Option<bool> form_clusters{*this, "form-clusters",
                             llvm::cl::desc("Enable Cluster Formation pass."),
                             llvm::cl::init(false)};
};

// Propagates the pass manager with the passes involved in transforming or
// optimizing an MLIR graph without any target specialization.
// NOLINTNEXTLINE - MLIR contract is pass by mutable reference.
void CreateTFStandardPipeline(OpPassManager& pm,
                              const StandardPipelineOptions& options);

// Propagates device attributes of resources from callers to callees.
std::unique_ptr<OperationPass<ModuleOp>> CreateResourceDeviceInferencePass();

// Creates a pass that promotes resource reads/writes in `functions` to inputs
// and outputs of `functions`, assuming that resource operations have already
// been decomposed and function calls have already been inlined. If `functions`
// is empty, the pass is applied to the main function by default. The pass also
// annotates the input arguments for resources with the indices of their
// aliasing output arguments.
std::unique_ptr<OperationPass<ModuleOp>> CreatePromoteResourcesToArgsPass(
    llvm::ArrayRef<std::string> functions = {});

// Creates a pass that promotes tf.VarHandleOp to resource arguments for all
// functions.
std::unique_ptr<OperationPass<ModuleOp>> CreatePromoteVarHandlesToArgsPass();

// Creates a pass that converts readonly reference variables to the
// corresponding resource variables.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateConvertReadonlyReferenceVariablesToResourceVariablesPass();

// Creates a simple device assignment pass on TF dialect for CoreRT use case.
std::unique_ptr<OperationPass<func::FuncOp>> CreateSimpleTFDeviceAssignmentPass(
    llvm::StringRef default_device = "cpu");

// Creates a pass to perform device assignment for TF dialect ops that do not
// have device assignment, by using the device attribute of the function.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateTFDeviceAssignmentByFuncAttrPass();

// Performs resource lifting on the function body to hoist resource variable
// accesses outside all control flow statements.
LogicalResult ResourceLiftingForFunctionalControlFlow(func::FuncOp function);

// Converts stack ops into operations on local variables, which can later be
// removed by resource lifting. Requires known maximum sizes of stacks and
// known element shapes of push ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateStackOpsDecompositionPass();

// Creates a pass to strip the "tf._noinline" attribute from the functions in
// the module.
std::unique_ptr<OperationPass<ModuleOp>> CreateStripNoinlineAttributePass();

// Converts tensor list operations into operations on buffers and sizes. Needs
// static shapes and known max element count.
std::unique_ptr<OperationPass<ModuleOp>> CreateTensorListOpsDecompositionPass();

// Converts tensor array ops into operations on local variables, which can later
// be removed by resource lifting. Requires known sizes and known element shapes
// (either defined in TensorArrayV3 or implied in the first write).
std::unique_ptr<OperationPass<ModuleOp>>
CreateTensorArrayOpsDecompositionPass();

// Create a pass that legalize HLO to TF dialect.
std::unique_ptr<OperationPass<func::FuncOp>> CreateLegalizeHloToTfPass();

// Create a pass that legalize TFG to TF dialect.
std::unique_ptr<Pass> CreateLegalizeTFGToTFEPass();

// Addds the HLO to TF rewrite patterns to the specified pattern list.
void PopulateLegalizeHloToTfPatterns(RewritePatternSet* patterns,
                                     MLIRContext* context);

// Matches sequence of ops to TensorFlow fused kernels. This pass should not be
// generally used beyond exporting to runtimes that supports these ops. In the
// future these fusions may be codegen'd automatically.
std::unique_ptr<OperationPass<func::FuncOp>> CreateFusedKernelMatcherPass();

// Creates function pass to select device index/fold tf.DeviceIndex.
std::unique_ptr<OperationPass<func::FuncOp>> CreateDeviceIndexSelectorPass();

// Creates function pass to replace InitializeTableFromTextFileV2Ops with
// LookupTableImportV2Op ops.
std::unique_ptr<OperationPass<func::FuncOp>> CreateInitTextFileToImportPass(
    std::string saved_model_dir = "");

// Creates function pass to cluster TensorFlow ops by host. The program
// generated by this pass will have one function per host where all operations
// in the same function are placed on the same host. Each result of the per-host
// function will have a "tf.device" attribute which specifies the device
// assignment of the result.
std::unique_ptr<OperationPass<mlir::ModuleOp>> CreateClusterTFOpsByHostPass();

// Creates a pass to insert tf_device.send and tf_device.receive ops to make
// sure any argument of any op is on the same host of the op itself.
std::unique_ptr<OperationPass<mlir::ModuleOp>> CreateCrossHostTransferPass();

// Creates a pass that adds the device attribute to every tf.Const op based on
// the device attribute of the operations that read its result. If the result of
// a tf.Const op is read by operations placed on multiple devices, then the pass
// will replicate the tf.Const op once for each device.
std::unique_ptr<OperationPass<ModuleOp>> CreateConstantOpDeviceAssignmentPass();

// Populates the supplied passmanager with the passes required to export
// to TensorFlow Graph.
void AddGraphExportLoweringPasses(OpPassManager& pm);

// Returns pass that verifies whether all functions in module are of single
// tf_executor.graph and each tf_executor.island in tf_executor.graph only has a
// single op.
std::unique_ptr<OperationPass<ModuleOp>> CreateVerifySuitableForExportPass();

// Returns pass that prepares TPU computation to be legal for export to
// TensorFlow.
std::unique_ptr<OperationPass<ModuleOp>>
CreatePrepareTpuComputationForTfExportPass();

// Rewrites ops that require quantized inputs or outputs to ops that allow
// non-quantized inputs and outputs.
std::unique_ptr<OperationPass<func::FuncOp>> CreateLowerQuantizedPass();

// Reorders ops so ops of the same dialect are next to each other.
std::unique_ptr<Pass> CreateOrderByDialectPass();

// Groups ops into functions that only contain one dialect.
std::unique_ptr<Pass> CreateGroupByDialectPass();
}  // namespace TF

namespace tf_executor {

// Creates a pass to chain control outputs of while loop body.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFExecutorConvertControlToDataOutputsPass();

// Creates a pass to merge IslandOps from TFExecutor dialect.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateTFExecutorIslandCoarseningPass();

// Creates a pass to merge IslandOps for operation marked for execution on TPU.
// This is a V1 backward compatibility.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFExecutorTPUV1IslandCoarseningPass();

// Creates a pass to outlining TPU clusters from single IslandOp into a nested
// module suitable for being processed as-if it was a V2 module.
// This is a V1 backward compatibility.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFExecutorTPUV1IslandOutliningPass();

// Creates a pass to inline calls to the nested TPU module, this reverses the
// effect of the `TFExecutorTPUV1IslandOutlining` pass above.
// This is a V1 backward compatibility.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFExecutorTPUV1IslandInliningPass();

// Creates a pass to prune tf_executor.graph from dead nodes.
std::unique_ptr<OperationPass<func::FuncOp>> CreateTFExecutorGraphPruningPass(
    llvm::ArrayRef<std::string> ops_to_preserve = {});
}  // namespace tf_executor

namespace TFDevice {
// Creates a pass that forms clusters from instructions that are assigned to
// same device.
std::unique_ptr<OperationPass<func::FuncOp>> CreateClusterFormationPass();

// Sinks `tf.Const` operations in the ClusterOp region using them. This is
// performed in order to limit the number of values implicitly captured in this
// region before outlining.
std::unique_ptr<OperationPass<func::FuncOp>> CreateClusterConstantSinkingPass(
    llvm::function_ref<bool(tf_device::ClusterOp, ElementsAttr)> filter = {});

// Creates a pass that outlines regions of tf_device.cluster operations.
std::unique_ptr<OperationPass<ModuleOp>> CreateClusterOutliningPass();

// Creates a pass that outlines regions of tf_device.launch operations.
std::unique_ptr<OperationPass<ModuleOp>> CreateLaunchOutliningPass();

// Creates a pass that converts tf_device::LaunchFuncOp into
// TF::PartitionedCallOp.
std::unique_ptr<OperationPass<ModuleOp>> CreateConvertLaunchFuncToTFCallPass();

// A pass that decomposes composite resource operations into primitive ones like
// ReadVariableOp, AssignVariableOp and other computations to facilitate
// transformations like resource op lifting.
std::unique_ptr<OperationPass<func::FuncOp>> CreateDecomposeResourceOpsPass();

// A pass that decomposes composite resource operations in device cluster
// (tf_device.cluster op) into primitive ones like ReadVariableOp,
// AssignVariableOp and other computations to facilitate transformations like
// resource op lifting.
std::unique_ptr<OperationPass<ModuleOp>>
CreateDecomposeResourceOpsInClusterPass();

// Creates a pass that marks TPU cluster input-output pairs reading and writing
// to same resource variable as aliases.
std::unique_ptr<OperationPass<ModuleOp>> CreateMarkInputOutputAliasesPass();

// Creates a pass that lifts operations on external resource variables from
// device computation nested in `tf_device::LaunchOp` out so that resource
// variable load operations are all before device computation while resource
// variable store operations are all after device computation. After this pass,
// device computation no longer interacts with external resource variables.
std::unique_ptr<OperationPass<ModuleOp>> CreateResourceOpLiftingPass();

// Creates a pass that lifts operations from the main function.
std::unique_ptr<OperationPass<ModuleOp>>
CreateResourceOpLiftingForMainFunctionPass();

// Lifts resource operations from tf_device.launch_func ops nested in `op`
// outside. Returns a failure if there are remaining resource-type values that
// can not be lifted.
LogicalResult LiftResourceOps(Operation* op);

// Creates a pass that hoists invariant operations in a `tf_device.replicate`.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateReplicateInvariantOpHoistingPass();

// Creates a pass that forms replica `tf_executor.island` from a single
// `tf_device.replicate` island.
std::unique_ptr<OperationPass<func::FuncOp>> CreateReplicateToIslandPass();

// Creates a pass that sets the device ordinal attribute of the required op
// using the replica id attribute.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateReplicaIDToDeviceOrdinalPass();

// Creates a pass that creates `tf_executor.island` from a single
// `tf_device.parallel_execute` island.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateParallelExecuteToIslandsPass();

// Creates a pass that annotates whether a LaunchFuncOp's parameters have the
// same data across replicas.
std::unique_ptr<OperationPass<ModuleOp>>
CreateAnnotateParameterReplicationPass();

// Creates a pass that marks unsupported ops in device cluster for outside
// compilation.
std::unique_ptr<OperationPass<ModuleOp>>
CreateMarkOpsForOutsideCompilationPass();

// Creates a pass that merges control flow with similar predicates.
std::unique_ptr<OperationPass<ModuleOp>> CreateMergeControlFlowPass();

// Creates a pass that wraps each TensorFlow dialect with `device` attribute
// in a `tf_device.launch` op with the same `device` attribute.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateDeviceAttributeToLaunchPass();

// Creates a pass that hoists a `tf_device.launch` body and assigns a `device`
// attribute to each TensorFlow dialect op in the body based on the `device`
// attribute on the `tf_device.launch`.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateLaunchToDeviceAttributePass();

// Creates a pass that extracts ops in tf_device.launch op with host device
// assignment and adds an `_xla_outside_compilation` attribute value.
std::unique_ptr<OperationPass<ModuleOp>>
CreateHostLaunchToOutsideCompiledPass();

// Create a pass that encapsulates StatefulPartitionedCallOp within a cluster.
std::unique_ptr<OperationPass<ModuleOp>> CreateXlaClusterFormationPass();

// Create a pass that inlines the StatefulPartitionedCallOp op based in the
// parent region.
std::unique_ptr<OperationPass<ModuleOp>> CreateXlaInlineDeviceOpsPass();

}  // namespace TFDevice

namespace TFTPU {
// Creates a pass that canonicalizes legacy compilation and replication
// attributes.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateCanonicalizeCompileAndReplicateAttributesPass();

// Creates a pass that converts unified compilation and replication
// attributes back to legacy attributes.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateConvertToLegacyCompileAndReplicateAttributesPass();

// Creates a pass that forms clusters from operations of the same
// `_replication_info` attribute.
std::unique_ptr<OperationPass<ModuleOp>> CreateTPUClusterFormationPass();

// Creates a pass that cleans up `_replication_info` attribute on operations
// that are inside a cluster.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTPUClusterCleanupAttributesPass();

// Creates a pass that removes Identity/IdentityN ops from a cluster.
std::unique_ptr<OperationPass<ModuleOp>> CreateTPUIdentityPruningPass();

// Creates a pass that allows TPU program inputs to have layouts determined at
// run time.
std::unique_ptr<OperationPass<ModuleOp>> CreateTPUDynamicLayoutPass();

// Creates a pass that adds `tf.ReadVariableOp` to a TPU cluster for resources
// the cluster only writes to.
std::unique_ptr<OperationPass<ModuleOp>> CreateTPUResourceReadForWritePass();

// Creates a pass that reorders partitiioned resource reads and replicated
// inputs.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateTPUReorderReplicateAndPartitionedInputsPass();

// Creates a pass that partitions unpartitioned resource read/write to
// partitioned resource variables.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateTPUResourceReadsWritesPartitioningPass();

// Creates a pass that rewrites `tf_device.launch_func` on TPUs into TPU runtime
// ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateTPURewritePass();

// Creates a pass that identifies XLASharding ops in launch op for TPU
// computation.
std::unique_ptr<OperationPass<ModuleOp>> CreateTPUShardingIdentificationPass();

// Creates a pass that moves `tf.AssignVariableOp` into a
// `tf_device.parallel_execute` region if the `tf.AssignVariableOp` is the
// only consumer of a `tf_device.parallel_execute` result.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateTPUParallelExecuteSinkResourceWritePass();

// Creates a pass that merges device variable reads/updates into the surrounded
// TPUExecute node. This allows the execute node to perform in-place variable
// updates.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTPUMergeVariablesWithExecutePass();

// Creates a pass that wraps ReadVariableOp/AssignVariable op that consumes a
// packed tensor to have same device placement as underlying TPU device.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateTPUColocateCompositeResourceOps();

// Creates a pass that adds ops which perform formatting on variables at
// run-time according to compilation result.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTPUVariableRuntimeReformattingPass();

// Creates a pass that wraps ops with the same `_xla_outside_compilation`
// attribute value in a tf_device.launch op with host device assignment.
std::unique_ptr<OperationPass<ModuleOp>>
CreateOutsideCompiledToHostLaunchPass();

// Creates a pass that extracts outside compilation (CPU ops inside TPU cluster)
// at head/tail of TPU cluster to run before/after TPU computation.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTPUExtractHeadTailOutsideCompilationPass();

// Creates a pass that expands outside compilation cluster at the head/tail of
// TPU computation by adding outside compilation attribute to identity/cast ops
// that are only used for host computation.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateTPUHostComputationExpansionPass();

// Creates a pass that updates inputs to TPU embedding layer enqueue ops so that
// correct ops are invoked during training and evaluation.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateTPUUpdateEmbeddingEnqueueOpInputsPass();

// Creates a pass that extract outside compilation (CPU ops inside TPU cluster)
// ops to a separate parallel_execute region to run on CPU.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTPUExtractOutsideCompilationPass();

// Creates a pass that propagates TPU devices to users.
std::unique_ptr<OperationPass<func::FuncOp>> CreateTPUDevicePropagationPass();

// Populates the supplied passmanager with the passes required to run the
// bridge.
void CreateTPUBridgePipeline(OpPassManager& pm);

// Populates the supplied passmanager with the passes required to run the
// bridge in V1 mode.
void CreateTPUBridgePipelineV1(OpPassManager& pm);

// Creates a pass that replicates the tf._TPUCompileMlir op on each host that
// needs the compiled program. It helps avoid transferring the compiled binary
// between hosts.
std::unique_ptr<OperationPass<mlir::ModuleOp>>
CreateTPUCompileOpReplicationPass();

// Creates a pass that applies space to depth transform
// for the first or frontier convolutions consume host inputs on TPU.
std::unique_ptr<OperationPass<ModuleOp>> CreateTPUSpaceToDepthPass();

}  // namespace TFTPU

// Define the registrations in a detail namespace, just so that we can overload
// the main entry point `registerTensorFlowPasses` to inject
// RegisterTFOptimizePassPipeline.
namespace detail {
#define GEN_PASS_REGISTRATION
#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.h.inc"
}  // namespace detail
using namespace detail;  // NOLINT
inline void registerTensorFlowPasses() {
  detail::registerTensorFlowPasses();
  TF::RegisterTFOptimizePassPipeline();
}

namespace TFDevice {
#define GEN_PASS_REGISTRATION
#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_device_passes.h.inc"
}  // namespace TFDevice

}  // namespace mlir

#endif  // TENSORFLOW_COMPILER_MLIR_TENSORFLOW_TRANSFORMS_PASSES_H_