Interface for ops potentially have same operands and results scales.
  }];

  let methods = [
    InterfaceMethod<
      [{Returns whether same operands and results scales are required.}],
      "bool", "RequiredSameOperandsAndResultsScale",
      (ins "bool":$sign, "int":$bit_width), [{}], [{return true;}]
    >,
    InterfaceMethod<
      [{Returns whether operands and results must have the same quantized axis.}],

// RUN: tf-opt -tfl-split-merged-operands %s | FileCheck %s

func.func @testSingleLstm(%arg0: tensor<4x4xf32>, %arg1: tensor<4xf32>, %arg2: tensor<4x4x4xf32>) -> tensor<4x4x4xf32> {
  // CHECK-LABEL: testSingleLstm
  // CHECK-DAG:  %[[CST_0:.*]] = "tfl.pseudo_const"() <{value = dense<0.000000e+00> : tensor<4x4xf32>}> : () -> tensor<4x4xf32>
  // CHECK-DAG:  %[[CST_1:.*]] = "tfl.pseudo_const"() <{value = dense<0.000000e+00> : tensor<4x4xf32>}> : () -> tensor<4x4xf32>

// and have at least one operand, result type can be inferred using the first
// operand's type.

#define INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(Op)                \
  LogicalResult Op::inferReturnTypeComponents(                        \
      MLIRContext* context, std::optional<Location> location,         \
      ValueShapeRange operands, DictionaryAttr attributes,            \

    llvm::SetVector<Value> operands;
    getUsedValuesDefinedAbove(island_op.getBody(), operands);

    SmallVector<Type, 16> func_operand_types;
    func_operand_types.reserve(operands.size());
    for (Value operand : operands)
      func_operand_types.push_back(operand.getType());

    // Function results are the yield operands
    SmallVector<Type, 16> func_result_types;

    TFE_Context* context, llvm::SmallVectorImpl<mlir::Attribute>* results) {
  if (!context) {
    VLOG(1) << "Can't evaluate with null context.";
    return mlir::failure();
  }
  // If any operand is nullptr returns true for a failure.
  // TODO(b/120678030): remove this constraint if we find operators can be
  // evaluated with some unknown operands.

  }
}

// Visits all operands of an op where each operand is an output of an Operation
// in the same tf_executor.graph.
void VisitOpOperands(GraphOp graph, Operation* op,
                     llvm::SmallPtrSetImpl<Operation*>* reachable_ops,
                     llvm::SmallVectorImpl<Operation*>* ops_to_visit) {
  for (Value operand : op->getOperands())
    VisitOpOperand(graph, operand, reachable_ops, ops_to_visit);
}

// TFL op interface for stateful operands.

def TFL_StatefulOp : OpInterface<"StatefulOpInterface"> {
  let description = [{
    Interface for ops that are stateful and need to identify stateful operands.

    Stateful operands correspond to TF's variables semantics. An op that has 1
    or more stateful operands is a stateful op.
  }];

  let methods = [
    InterfaceMethod<

  // core. j-th column holds the operands for j-th replica.
  llvm::SmallVector<llvm::SmallVector<Value, 4>, 4>
      operands_per_replica_per_core(num_cores_per_replica);

  // Collect all operands in the 2D matrix.
  for (auto operand : replicated_input.getInputs()) {
    Operation* pi = operand.getDefiningOp();
    for (unsigned core_id = 0; core_id < num_cores_per_replica; ++core_id) {

                                llvm::SmallVector<Attribute>& results) {
  // If any operand is nullptr returns true for a failure.
  // TODO(b/120678030): remove this constraint if we find operators can be
  // evaluated with some unknown operands.
  if (std::any_of(operands.begin(), operands.end(),
                  [](Attribute operand) { return !operand; })) {

        switch (opType) {
            case "any of":
                def operands = []
                collectOperands(value, operands)
                return "anyOf(${operands.join(', ')})"
            case "all of":
                def operands = []
                collectOperands(value, operands)
                return "allOf(${operands.join(', ')})"
            case "exclude group":