this.setDependencyResolutionRequired(md.getDependencyResolution());
        this.setComponentConfigurator(md.getConfigurator());
        this.setInheritedByDefault(md.isInheritedByDefault());
        this.setPhase(md.getPhase());
        this.setOnlineRequired(md.isOnlineRequired());
        this.setProjectRequired(md.isProjectRequired());
        this.setSince(md.getSince());
        this.setThreadSafe(true);

        if (deprecated != null) {
            mojo.setDeprecated(deprecated.getValue());
        }

        String phase = c.getChild("phase").getValue();

        if (phase != null) {
            mojo.setPhase(phase);
        }

        String executePhase = c.getChild("executePhase").getValue();

        if (executePhase != null) {
            mojo.setExecutePhase(executePhase);
        }

    } // -- void setId( String )

    /**
     * Set the phase mappings for this lifecycle.
     *
     * @param phases a phases object.
     */
    public void setPhases(java.util.List<Phase> phases) {
        this.phases = phases;
    } // -- void setPhases( java.util.List )

        assertTrue(md.isInheritedByDefault());
        assertFalse(md.isOnlineRequired());
        assertTrue(md.isProjectRequired());
        assertFalse(md.isThreadSafe());
        assertEquals("package", md.getPhase());
        assertEquals("org.apache.maven.plugin.jar.JarMojo", md.getImplementation());
        assertEquals("antrun", md.getComponentConfigurator());
        assertEquals("java", md.getLanguage());

	tok = in.Stack.Next()
	if tok != '\n' {
		in.Error("unexpected token at end of #line: ", tok)
	}
	pos := src.MakePos(in.Base(), uint(in.Line())+1, 1) // +1 because #line nnn means line nnn starts on next line
	in.Stack.SetBase(src.NewLinePragmaBase(pos, file, objabi.AbsFile(objabi.WorkingDir(), file, *flags.TrimPath), uint(line), 1))
}

// #undef processing
func (in *Input) undef() {
	name := in.macroName()
	if in.macros[name] == nil {

    return;
  }
  tensorflow::shape_inference::ShapeHandle new_shape =
      tensorflow::ShapeHandleFromDims(ic, num_dims, dims);
  status->status = graph->refiner.SetShape(node, output.index, new_shape);
}

int TF_GraphGetTensorNumDims(TF_Graph* graph, TF_Output output,
                             TF_Status* status) {
  Node* node = &output.oper->node;

  TF_Buffer* buf = TF_GetAllOpList();
  tensorflow::OpList op_list;
  EXPECT_TRUE(op_list.ParseFromArray(buf->data, buf->length));
  EXPECT_GT(op_list.op_size(), 0);
  TF_DeleteBuffer(buf);
}

TEST(CAPI, SetShape) {
  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  TF_Operation* feed = Placeholder(graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_Output feed_out_0 = TF_Output{feed, 0};