types.SetType(sym.STYPE)
	types.SetSize(8)
	ldr.SetAttrSpecial(types.Sym(), false)

	etypes := ldr.CreateSymForUpdate("runtime.etypes", 0)
	etypes.SetType(sym.SFUNCTAB)
	ldr.SetAttrSpecial(etypes.Sym(), false)

	if ctxt.HeadType == objabi.Haix {
		rodata := ldr.CreateSymForUpdate("runtime.rodata", 0)
		rodata.SetType(sym.SSTRING)
		rodata.SetSize(8)

						IP:       "100.101.102.103",
						Port:     3001,
						Protocol: strings.ToLower(string(v1.ProtocolSCTP)),
						SetType:  utilipset.HashIPPort,
					},
					{
						IP:       "100.101.102.104",
						Port:     3001,
						Protocol: strings.ToLower(string(v1.ProtocolSCTP)),
						SetType:  utilipset.HashIPPort,
					},
					{
						IP:       "100.101.102.105",
						Port:     3001,

        cast_op = InsertCast(b, op->getLoc(), result.getType(), result);
        if (!cast_op) return false;
      }
      use.set(Value(cast_op->getResult(0)));
    }
  }

  result.setType(new_type);
  if (enqueue_callers)
    EnqueueCallers(result.getDefiningOp()->getParentOfType<func::FuncOp>());
  return true;
}

bool ShapeInference::RefineResultType(Operation* op, Value result,

      auto rt = std::get<1>(it);
      if (rt == std::get<0>(it).getType()) continue;
      std::get<0>(it).setType(rt);
      all_equal = false;
    }
    if (!all_equal) {
      function.setType(mlir::FunctionType::get(function.getContext(),
                                               func_type.getInputs(),

        RankedTensorType::Builder(
            mlir::cast<RankedTensorType>(q_op.getResult().getType()))
            .setShape(mlir::cast<ShapedType>(new_bias_type).getShape());
    q_op.getResult().setType(new_q_op_type);
    auto attr = TypeAttr::get(q_op.getResult().getType());
    q_op.setQtypeAttr(attr);

    // Update DequantizeOp's output shape
    auto new_dq_op_type =
        RankedTensorType::Builder(

  auto shuffled_paddings_op = builder.create<TF::ConstOp>(getLoc(), values);

  // Use new paddings.
  setOperand(1, shuffled_paddings_op);

  // Change the result type.
  getResult().setType(ShuffleRankedTensorType(getResult().getType(),
                                              ReversePermutation(permutation))
                          .cast<TensorType>());

  return success();
}

artifactId; private String type; private String version; public void ComponentDependency(); public String getArtifactId(); public void setArtifactId(String); public String getGroupId(); public void setGroupId(String); public String getType(); public void setType(String); public String getVersion(); public void setVersion(String); public String toString(); } org/codehaus/plexus/component/repository/ComponentDescriptor.class package org.codehaus.plexus.component.repository; public synchronized class ComponentDescriptor...

artifactId; private String type; private String version; public void ComponentDependency(); public String getArtifactId(); public void setArtifactId(String); public String getGroupId(); public void setGroupId(String); public String getType(); public void setType(String); public String getVersion(); public void setVersion(String); public String toString(); } org/codehaus/plexus/component/repository/ComponentDescriptor.class package org.codehaus.plexus.component.repository; public synchronized class ComponentDescriptor...

		return r
	}
	return t
}

func (t *Typed) GoString() string {
	return t.goString(0, "")
}

func (t *Typed) goString(indent int, field string) string {
	return fmt.Sprintf("%*s%sTyped:\n%s\n%s", indent, "", field,
		t.Name.goString(indent+2, "Name: "),
		t.Type.goString(indent+2, "Type: "))
}

// Qualified is a name in a scope.
type Qualified struct {
	Scope AST
	Name  AST