device = d->getDevice();
          break;
        }
      }
      for (auto *operand : operands)
        propagateIfChanged(operand, operand->SetDevice(device));
    }
  }
  void visitBranchOperand(OpOperand &operand) override {}
  void visitCallOperand(OpOperand &operand) override {}
  void setToExitState(Device *lattice) override {}
};

                                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; })) {

// 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<

// If an error occurs, x.mode is set to invalid.
func (check *Checker) matchTypes(x, y *operand) {
	// mayConvert reports whether the operands x and y may
	// possibly have matching types after converting one
	// untyped operand to the type of the other.
	// If mayConvert returns true, we try to convert the
	// operands to each other's types, and if that fails
	// we report a conversion failure.

  });
}

// 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() &&

};

// Rewrites the given op to `OpT` op after adding the given operand at the end.
template <typename OpT>
OpT AddOperandAndRewriteAs(Operation* op, Value operand, NamedAttrList attr,
                           OpBuilder* builder) {
  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(),

// In order to be clustered operation can require its operands to satisfy
// some constraints (e.g. reduction operation can require reduction dimension
// operand to be a constant value).
enum class ValueConstraint {
  // Operand must have statically known rank.
  kRank = 0,
  // Operand must have statically known shape (all dimensions are known at
  // compile time).
  kShape = 1,

	}
	return res
}

func TestErroneous(t *testing.T) {

	type errtest struct {
		pseudo   string
		operands string
		expected string
	}

	nonRuntimeTests := []errtest{
		{"TEXT", "", "expect two or three operands for TEXT"},
		{"TEXT", "%", "expect two or three operands for TEXT"},
		{"TEXT", "1, 1", "TEXT symbol \"<erroneous symbol>\" must be a symbol(SB)"},

// Returns the RankedTensorType for the given operand. TensorFlow constant ops
// may have non-static shape because the shape is not propagated during constant
// folding. If the defining op for the given operand is a constant op, this
// routine uses the constant op's attribute to get the actual shape.
RankedTensorType GetRankedTensorTypeForOperand(Value operand) {
  DenseElementsAttr attr;
  if (matchPattern(operand, m_Constant(&attr))) {

1. Operand ordering

In Go asm, the last operand (right) is the target operand, but with PPC64 asm,
the first operand (left) is the target. The order of the remaining operands is
not consistent: in general opcodes with 3 operands that perform math or logical
operations have their operands in reverse order. Opcodes for vector instructions
and those with more than 3 operands usually have operands in the same order except