// inputs.
      SmallVector<Value, 4> inputs;
      inputs.reserve(quantizing_op->getNumOperands());
      for (const auto& operand : quantizing_op->getOperands()) {
        Type operand_type = operand.getType();
        if (operand_type.isa<NoneType>()) {
          inputs.push_back(operand);
          continue;
        }

        Type elem_type = operand_type.cast<TensorType>().getElementType();

//
// Like qcasts, a dcast is allowed to have both its operand and result
// as non quantized types. This facilitates transformations and marks edges
// where the computation must be carried out in the expressed type.
//
// Especially early in transformation, it is common to have dcasts on
// all operands to ops that must operate with the expressed type (typically

  // Look up function definition from module.
  Block& function_block = func.front();

  sharding_for_args.reserve(function_block.getNumArguments());

  // Iterate through operands of `cluster_func`.
  // The computation operand can either be:
  //   1) a TPUPartitionedInput Op if the input has a non-resource type;
  //   2) a ReadVariableOp else.
  //
  // Iterate through input arguments to the entry block of

      Value operand = op->getOperand(i);
      if (Operation* inst = operand.getDefiningOp()) {
        // If the operand comes from a `quantfork::DequantizeCastOp`, we use
        // the quantized input of this `quantfork::DequantizeCastOp` to set the
        // state.
        if (auto dq = dyn_cast<quantfork::DequantizeCastOp>(inst)) {
          operand = dq.getArg();
        }
      }

       << "const std::vector<int32_t>& operands,"
       << "const std::vector<int32_t>& results,"
       << (has_intermediates ? "const std::vector<int32_t>& intermediate_index,"
                             : "")
       << "flatbuffers::FlatBufferBuilder *fbb) {\n";

    // Inputs & outputs
    os << "  auto inputs = fbb->CreateVector(operands);\n"
          "  auto outputs = fbb->CreateVector(results);\n\n";

  });
}

// Propagates the resource IDs from an input operand to a result. Returns true
// if the mapping changed.
bool ResourceAliasAnalysisInfo::PropagateInputToOutput(const Value& operand,
                                                       const OpResult& result) {
  auto operand_it = resource_value_to_ids_.find(operand);
  assert(operand_it != resource_value_to_ids_.end() &&

      call.getNumResults() != yield.getNumOperands())
    return std::nullopt;
  for (auto [arg, operand] :
       llvm::zip(block.getArguments(), call.getOperands())) {
    if (arg != operand) return std::nullopt;
  }
  for (auto [ret, operand] :
       llvm::zip(call.getResults(), yield.getOperands())) {
    if (ret != operand) return std::nullopt;
  }
  SymbolRefAttr symbol = call.getCallableForCallee().get<SymbolRefAttr>();

				x.mode = invalid
				return
			}
			valid = true
			if x.mode == constant_ {
				length = int64(len(constant.StringVal(x.val)))
			}
			// spec: "For untyped string operands the result
			// is a non-constant value of type string."
			if isUntyped(x.typ) {
				x.typ = Typ[String]
			}
		}

	case *Array:
		valid = true
		length = u.len
		if x.mode != variable {

}

// Print formats using the default formats for its operands and writes to standard output.
// Spaces are added between operands when neither is a string.
// It returns the number of bytes written and any write error encountered.
func Print(a ...any) (n int, err error) {
	return Fprint(os.Stdout, a...)
}

// Sprint formats using the default formats for its operands and returns the resulting string.

  if (extra_operands.empty()) return;

  const int operands_size = while_op.getNumOperands() + extra_operands.size();
  SmallVector<Value, 4> operands;
  operands.reserve(operands_size);
  operands.append(while_op.getOperands().begin(), while_op.getOperands().end());
  operands.append(extra_operands.begin(), extra_operands.end());
  SmallVector<Type, 4> new_types;
  new_types.reserve(operands_size);