#!/usr/bin/env python3
# -*- coding: UTF-8 -*-
# ----------------------------------------------------------------------------
# Copyright (c) 2025 Huawei Technologies Co., Ltd.
# This program is free software, you can redistribute it and/or modify it under the terms and conditions of
# CANN Open Software License Agreement Version 2.0 (the "License").
# Please refer to the License for details. You may not use this file except in compliance with the License.
# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
# INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
# See LICENSE in the root of the software repository for the full text of the License.
# ----------------------------------------------------------------------------

import numpy as np
from ge.es.all import MatMul
from ge.es.graph_builder import GraphBuilder
from ge.ge_global import GeApi
from ge.graph import DumpFormat, Tensor
from ge.graph.types import DataType, Format
from ge.session import Session


def build_matmul_graph():
    # 1、创建图构建器
    builder = GraphBuilder("MakeMatMulGraph")
    # 2、创建图输入节点
    input_tensor_holder = builder.create_input(index=0, name="input", data_type=DataType.DT_FLOAT, shape=[2, 3])
    weight = builder.create_const_float([1.0] * 6, shape=[2, 3])
    # transpose_x1 和 transpose_x2 为 MatMul 的属性
    matmul_tensor_holder = MatMul(weight, input_tensor_holder, None, transpose_x1=True, transpose_x2=False)
    # 3、设置图输出节点
    builder.set_graph_output(matmul_tensor_holder, 0)
    # 4、构建图
    return builder.build_and_reset()


def dump_matmul_graph(graph):
    graph.dump_to_file(format=DumpFormat.kOnnx, suffix="make_matmul_graph")


def run_graph(graph, device_id="0") -> int:
    # 1. 初始化GE环境
    config = {"ge.exec.deviceId": str(device_id), "ge.graphRunMode": "0"}

    ge_api = GeApi()
    ret = ge_api.ge_initialize(config)
    if ret != 0:
        print(f"[Error] GE初始化失败，返回码: {ret}")
        return ret

    print(f"[Info] GE环境初始化成功 (Device ID: {device_id})")

    try:
        # 2. 创建Session
        session = Session()

        # 3. 添加图到Session
        graph_id = 1
        ret = session.add_graph(graph_id, graph)
        if ret != 0:
            print(f"[Error] 添加图失败，返回码: {ret}")
            return ret
        print(f"[Info] 图已添加到Session (Graph ID: {graph_id})")

        # 4. 准备输入数据
        input_data = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32)

        input_tensor = Tensor(
            input_data.flatten().tolist(),
            None,
            DataType.DT_FLOAT,
            Format.FORMAT_ND,
            [2, 3],
        )

        inputs = [input_tensor]
        print(f"[Info] 输入数据已准备，共{len(inputs)}个输入tensor")

        # 5. 运行图
        ret = session.run_graph(graph_id, inputs)
        print("[Info] 图运行成功！")
        for idx, tensor in enumerate(ret, start=1):
            print(f"Tensor{idx}详情：{tensor}")
        return 0

    except Exception as e:
        print(f"[Error] 执行过程中出错: {e}")
        import traceback

        traceback.print_exc()
        return -1

    finally:
        # 6. 清理GE环境
        print("[Info] 清理GE环境...")
        ge_api.ge_finalize()
        print("[Success] GE环境已清理")


if __name__ == "__main__":
    # 构建图
    graph = build_matmul_graph()

    # 先dump图（生成pbtxt文件用于可视化）
    dump_matmul_graph(graph)

    # 运行图（从命令行参数获取device_id，默认为"0"）
    run_graph(graph)