Method export

ppq/samples/Tutorial/targetPlatform.py:131–149

(self, file_path: str, graph: BaseGraph, config_path: str, **kwargs)

            return value.tolist()
    
    def export(self, file_path: str, graph: BaseGraph, config_path: str, **kwargs):
        # ------------------------------------------------------------
        # 接下来我们将导出量化信息，在 PPQ 中所有的量化信息都绑定在 Op 上
        # 因此我们需要遍历图中所有的 Op, 将绑定在其上的量化信息导出到文件
        # ------------------------------------------------------------
        with open(config_path, 'w') as file:
            for name, op in graph.operations.items():
                if not isinstance(op, QuantableOperation): continue

                for cfg, var in op.config_with_variable:
                    file.write(f"{name}: {var.name}\n")
                    file.write(f"Quant State: {cfg.state.name}\n")
                    file.write(f"Scale:  {self.convert_value(cfg.scale)}\n")
                    file.write(f"Offset: {self.convert_value(cfg.offset)}\n")

        # ------------------------------------------------------------
        # 最后我们导出完整的计算图到 onnx
        # ------------------------------------------------------------
        onnx.save(self.export_graph(graph=graph), file_path)


# ------------------------------------------------------------