struct TensorDeviceCopyConversionPass
    : public impl::TensorDeviceCopyConversionPassBase<
          TensorDeviceCopyConversionPass> {
  void runOnOperation() override;
};

// Folds tf.IdentityOp and tf.IdentityNOp if op device and the argument devices
// from the defining ops match.
void TensorDeviceCopyConversionPass::runOnOperation() {
  func::FuncOp func_op = getOperation();

    auto identity = builder.create<TF::IdentityOp>(island.getLoc(),
                                                   operand.getType(), operand);
    yield.setOperand(0, identity.getOutput());
  } else {
    auto identity_n = builder.create<TF::IdentityNOp>(
        island.getLoc(), yield.getOperandTypes(), yield.getOperands());
    for (const auto& it : llvm::enumerate(identity_n.getResults()))

class IdentityOp;
class IdentityNOp;

// Returns if a value corresponds to a constant, returns the matched constant
// as an attribute.
template <typename AttrT>
bool GetValueAsConstant(Value val, AttrT &attr) {
  while (auto result = mlir::dyn_cast<OpResult>(val)) {
    Operation *op = result.getOwner();
    if (!isa<IdentityOp>(op) && !isa<IdentityNOp>(op)) break;

          // clang-format off
          // go/keep-sorted start
          TF::AvgPoolOp,
          TF::ConcatOp,
          TF::ConcatV2Op,
          TF::ExpandDimsOp,
          TF::IdentityNOp,
          TF::IdentityOp,
          TF::MaxPoolOp,
          TF::PadV2Op,
          TF::RankOp,
          TF::ReshapeOp,
          TF::SelectOp,
          TF::SelectV2Op,
          TF::ShapeNOp,

}

// Removes Identity/IdentityN ops from a region and forwards its operands to its
// results.
void RemoveIdentityFromRegion(Region& region) {
  region.walk([](Operation* op) {
    if (isa<TF::IdentityOp, TF::IdentityNOp>(op)) {
      op->replaceAllUsesWith(op->getOperands());
      op->erase();
    }
  });
}

void TPUIdentityPruning::runOnOperation() {
  SmallVector<tf_device::ClusterOp, 4> clusters;

// CHECK: %[[IDENTITY_1:.*]] = "tf.Identity"(%[[W_1]]) : (tensor<2x3x3x1024xi8>) -> tensor<2x3x3x1024xi8>
// CHECK: %[[DEQUANTIZED_1:.*]] = "tf.PartitionedCall"(%[[IDENTITY_1]]) <{config = "", config_proto = "", executor_type = "", f = @composite_dequantize_uniform__}> : (tensor<2x3x3x1024xi8>) -> tensor<2x3x3x1024xf32>

template <typename T>
std::tuple<T, llvm::SmallVector<mlir::TF::IdentityOp, 4>> GetSingleUserOfType(
    OpResult result) {
  llvm::SmallVector<mlir::TF::IdentityOp, 4> identity_ops;

  do {
    Operation* user = result.hasOneUse() ? *result.getUsers().begin() : nullptr;
    if (auto t = llvm::dyn_cast_or_null<T>(user)) {
      return std::make_tuple(t, identity_ops);
    } else if (auto identity =

    auto identity = builder.create<TF::IdentityOp>(island.getLoc(),
                                                   operand.getType(), operand);
    yield.setOperand(0, identity.getOutput());
  } else {
    auto identity_n = builder.create<TF::IdentityNOp>(
        island.getLoc(), yield.getOperandTypes(), yield.getOperands());
    for (auto it : llvm::enumerate(identity_n.getResults()))

func.func @while_main(%arg0: tensor<?x256x256xf32>) -> (tensor<i32>, tensor<256x256xf32>, tensor<?x256x256xf32>) attributes {tf.entry_function = {inputs = "input", outputs = "Identity,Identity_1,Identity_2"}} {
  %cst = arith.constant dense<1.000000e+00> : tensor<256x256xf32>
  %cst_0 = arith.constant dense<0> : tensor<i32>
  %cst_1 = arith.constant dense<-1> : tensor<i32>

#include "mlir/IR/Matchers.h"  // from @llvm-project
#include "mlir/IR/TypeUtilities.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project

namespace mlir {
namespace TF {

class IdentityOp;
class IdentityNOp;

// Returns the RankedTensorType for the given operand. TensorFlow constant ops
// may have non-static shape because the shape is not propagated during constant