builder->setInsertionPoint(op);
  auto operands = llvm::to_vector<4>(op->getOperands());
  operands.push_back(operand);
  auto new_op = builder->create<OpT>(op->getLoc(), op->getResultTypes(),
                                     operands, attr.getAttrs());
  op->replaceAllUsesWith(new_op.getOperation()->getResults());
  op->erase();
  return new_op;
}

// Returns success if the function has at most one op of the template type and

    }
    auto arg_type = cast<func::FuncOp>(op).getArgument(arg_index).getType();
    return VerifyBoundInputArgType(op, arg_type, symbol_op);
  }
  if (named_attr.getName() == kTfSavedModelIndexPathAttr) {
    return VerifyIndexPath(op, named_attr);
  }

  return op->emitError() << "unknown tf_saved_model dialect arg attribute '"
                         << named_attr.getName().getValue() << "'";
}

      return states_[operand_states_[{op, index}]];
    }

    // Returns the state of the index-th result of the op.
    QuantState &GetResultQuantState(Operation *op, int index) {
      return states_[result_states_[{op, index}]];
    }

    // Returns the state of the index-th operand of the op.
    RequantizeState &GetOperandRequantizeState(Operation *op, int index) {

          op->getLoc(), op.getOperand().getType(), adaptor.getOperand());
      rewriter.replaceOpWithNewOp<mlir::stablehlo::BitcastConvertOp>(
          op, op.getResult().getType(), output);
    } else {
      // Both input/output are f32. Convert to no-op.
      rewriter.replaceOp(op, adaptor.getOperand());
    }
    return success();
  }
};
}  // namespace

#define GEN_PASS_DEF_CONVERTFUNCTOBFLOAT16PASS

        op.getLoc(), op.getType(), op.getOperands(),
        builder.getI64ArrayAttr(partition_dims), builder.getBoolAttr(false),
        op.get_XlaShardingAttr());
    op->replaceAllUsesWith(pi);
  } else {
    auto po = builder.create<TF::TPUPartitionedOutputV2Op>(
        op.getLoc(), op.getResultTypes(), op.getOperand(),
        builder.getI64ArrayAttr(partition_dims), op.get_XlaShardingAttr());

LogicalResult ConcatOffsetOp::verify() {
  ConcatOffsetOp op = *this;
  if (op.getN() < 2)
    return op.emitOpError() << "requires N to be at least 2, got " << op.getN();

  if (op.getShape().size() != op.getOffset().size())
    return op.emitOpError()
           << "requires sizes of shapes and offsets to be the same, got sizes "
           << op.getShape().size() << " and " << op.getOffset().size();

  auto ranked_dim =

                                         const Operation& op,
                                         const std::vector<Output>& grad_inputs,
                                         std::vector<Output>* grad_outputs) {
  Input input = Shape(scope, op.input(0));
  Input input_min = op.input(1);
  Input input_max = op.input(2);
  int64_t axis;
  TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "axis", &axis));

BenchmarkLRUGetConcurrent-8      	 1000000	      1984 ns/op	       0 B/op	       0 allocs/op
BenchmarkLRUSet-8                	20000000	        64.7 ns/op	       0 B/op	       0 allocs/op
BenchmarkLRUSetConcurrent-8      	 1000000	      2315 ns/op	       0 B/op	       0 allocs/op
BenchmarkLRUGetSetConcurrent-8   	 1000000	      2299 ns/op	       0 B/op	       0 allocs/op

namespace mlir {
namespace TFL {
namespace tac {

// Returns true if 'op' is non const op. Returns false otherwise or if
// 'op' is null.
inline bool IsNonConstOp(Operation* op) {
  if (!op) return false;
  if (llvm::isa<arith::ConstantOp, mlir::func::ConstantOp>(op)) return false;
  if (op->hasTrait<OpTrait::ConstantLike>()) return false;
  if (llvm::isa<TFL::ConstOp, TFL::QConstOp>(op)) return false;
  return true;
}

  // `op`, and bypass all result transposes.
  Location loc = op->getLoc();

  // Move constant op defining result permutation to the beginning of the block.
  permutation_op.getOperation()->moveBefore(&op->getBlock()->front());

  // Bypass Transpose nodes for all results.
  for (OpResult result : op->getResults()) {
    result.setType(