Method export_quantization_config

ppq/parser/tengine_exporter.py:91–125

(self, config_path: str, graph: BaseGraph)

                file.write(f"{k} {scale} {zp}\n")

    def export_quantization_config(self, config_path: str, graph: BaseGraph):

        render_buffer = {"configs": {}, "dispatchings": {}, "values": {}}

        # Render quantization config.
        for operation in graph.operations.values():
            if isinstance(operation, QuantableOperation):
                op_dict = {
                    var.name: {
                        "bit_width": config.num_of_bits,
                        "policy": config.policy.to_dict(),
                        "state": config.state.name,
                        "quant_min": config.quant_min,
                        "quant_max": config.quant_max,
                        "hash": config.__hash__(),
                        "dominator": config.dominated_by.__hash__(),
                    }
                    for config, var in operation.config_with_variable
                }

                for config, _ in operation.config_with_variable:
                    if config.policy.has_property(QuantizationProperty.PER_CHANNEL):
                        raise PermissionError('Tengine does not support per channel quantization.')

                    if config.dominated_by == config:
                        render_buffer["values"][config.__hash__()] = {
                            "scale": config.scale.item(),
                            "zero_point": config.offset.item(),
                        }

                render_buffer["configs"][operation.name] = op_dict
                render_buffer["dispatchings"][operation.name] = operation.platform.name

        with open(file=config_path, mode="w") as file:
            json.dump(render_buffer, file, indent=4)

    def export_operation(self, operation: Operation) -> onnx.OperatorProto:
        if operation.type in OPERATION_EXPORTERS: