(BinaryOp (TFL_ReshapeOp:$lhs $input, (Arith_ConstantOp:$shape $s)),
              $rhs, $act_fn),
    (BinaryOp $input, $rhs, $act_fn),
    [(AnyStaticShapeTensor $input),
     (AnyStaticShapeTensor $rhs),
     (IsRankLessThanEqualTo $input, $lhs),
     (IsRankLessThanEqualTo $lhs, $rhs),
     (IsReducedTailOfShape $lhs, $input),
     (HasOneUseOrUsedByOnlyBinaryOps $lhs),

		switch p.tok {
		case _AssignOp:
			// lhs op= rhs
			op := p.op
			p.next()
			return p.newAssignStmt(pos, op, lhs, p.expr())

		case _IncOp:
			// lhs++ or lhs--
			op := p.op
			p.next()
			return p.newAssignStmt(pos, op, lhs, nil)

		case _Arrow:
			// lhs <- rhs
			s := new(SendStmt)
			s.pos = pos
			p.next()
			s.Chan = lhs
			s.Value = p.expr()
			return s

ensures that a client sees the actual (run-time) type an untyped value would
have. It also permits type-checking of lhs shift operands "as if the shift
were not present": when updateExprType visits an untyped lhs shift operand
and assigns it it's final type, that type must be an integer type, and a
constant lhs must be representable as an integer.

When an expression gets its final type, either on the way out from rawExpr,

ensures that a client sees the actual (run-time) type an untyped value would
have. It also permits type-checking of lhs shift operands "as if the shift
were not present": when updateExprType visits an untyped lhs shift operand
and assigns it it's final type, that type must be an integer type, and a
constant lhs must be representable as an integer.

When an expression gets its final type, either on the way out from rawExpr,

     * find the containing binary expression and resolve that instead.
     *
     * However, if, say, `+=` resolves to `plusAssign`, then the LHS is self-contained. In this case we do not return the containing binary
     * expression so that the FIR element corresponding to the LHS is used directly.
     */

        op.getLoc(), /*resultType0=*/
        mlir::cast<TensorType>(op.getResult().getType())
            .clone(output_uniform_quantized_type),
        /*lhs=*/op.getLhs(), /*rhs=*/op.getRhs(),
        /*dot_dimension_numbers=*/op.getDotDimensionNumbers(),
        /*precision_config=*/op.getPrecisionConfigAttr());

      return errors::FailedPrecondition(
          "Cluster names mismatch: lhs: ", lhs_cluster_name,
          " rhs: ", rhs_cluster_name);
    }

    if (lhs_cluster_name_parts[2] == rhs_cluster_name_parts[2]) {
      return errors::FailedPrecondition(
          "cluster sequence numbers are the same: lhs: ", lhs_cluster_name,
          " rhs: ", rhs_cluster_name);
    }

				}))),
			}),
			expectCost: map[string]int64{
				"self.objs[0] == self.objs[1]":                7,  // equal even though order is different
				"self.objs[0] + self.objs[2] == self.objs[2]": 11, // rhs overwrites lhs values
				"self.objs[2] + self.objs[0] == self.objs[0]": 11,

				"self.objs[0] == [self.objs[0][0], self.objs[0][1]]": 22, // equal against a declared list
				"self.objs[0] == [self.objs[0][1], self.objs[0][0]]": 22,

                                         RawType expected,
                                         RawType actual) {
  const FloatingPoint<RawType> lhs(expected), rhs(actual);

  if (lhs.AlmostEquals(rhs)) {
    return AssertionSuccess();
  }

  ::std::stringstream expected_ss;
  expected_ss << std::setprecision(std::numeric_limits<RawType>::digits10 + 2)

			"c = 0", "d = 0", "b = d + c", "e = 0", "a = e + c",
		}},
		// emit an initializer for n:1 initializations only once (not for each node
		// on the lhs which may appear in different order in the dependency graph)
		{`package p12; var (a = x; b = 0; x, y = m[0]; m map[int]int)`, []string{
			"b = 0", "x, y = m[0]", "a = x",
		}},