#!/usr/bin/env python
# -*- coding: UTF-8 -*-

"""
-------------------------------------------------------------------------
This file is part of the MindStudio project.
Copyright (c) 2025 Huawei Technologies Co.,Ltd.

MindStudio is licensed under Mulan PSL v2.
You can use this software according to the terms and conditions of the Mulan PSL v2.
You may obtain a copy of Mulan PSL v2 at:

         http://license.coscl.org.cn/MulanPSL2

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 FIT FOR A PARTICULAR PURPOSE.
See the Mulan PSL v2 for more details.
-------------------------------------------------------------------------
"""
import unittest
from pathlib import Path
from unittest.mock import MagicMock, patch

import torch.nn as nn

from msmodelslim.core.const import DeviceType
from msmodelslim.model.default.model_adapter import DefaultModelAdapter
from msmodelslim.utils.exception import InvalidModelError


class TestDefaultModelAdapter(unittest.TestCase):

    def setUp(self):
        self.model_type = 'DefaultModel'
        self.model_path = Path('.')
        self.trust_remote_code = False

    @patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__')
    def test_initialization_success(self, mock_super_init):
        """测试默认模型适配器成功初始化"""
        mock_super_init.return_value = None

        DefaultModelAdapter(
            model_type=self.model_type,
            model_path=self.model_path,
            trust_remote_code=self.trust_remote_code
        )

        mock_super_init.assert_called_once_with(
            self.model_type,
            self.model_path,
            self.trust_remote_code
        )

    @patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__')
    def test_initialization_failure(self, mock_super_init):
        """测试默认模型适配器初始化失败"""
        mock_super_init.side_effect = Exception("Model loading failed")

        with self.assertRaises(InvalidModelError):
            DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path,
                trust_remote_code=self.trust_remote_code
            )

    def test_get_model_type(self):
        """测试get_model_type方法"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )
            adapter.model_type = self.model_type

            result = adapter.get_model_type()
            self.assertEqual(result, self.model_type)

    def test_get_model_pedigree(self):
        """测试get_model_pedigree方法"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )
            result = adapter.get_model_pedigree()
            self.assertEqual(result, 'default')

    def test_load_model_success(self):
        """测试load_model方法成功情况"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )

            mock_model = nn.Linear(10, 10)
            adapter._load_model = MagicMock(return_value=mock_model)

            result = adapter.load_model(device=DeviceType.CPU)

            self.assertIs(result, mock_model)
            adapter._load_model.assert_called_once_with(DeviceType.CPU)

    def test_load_model_failure(self):
        """测试load_model方法失败情况"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )

            adapter._load_model = MagicMock(side_effect=Exception("Loading failed"))

            with self.assertRaises(InvalidModelError):
                adapter.load_model(device=DeviceType.CPU)

    def test_handle_dataset_success(self):
        """测试handle_dataset方法成功情况"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )

            mock_dataset = ['data1', 'data2']
            adapter._get_tokenized_data = MagicMock(return_value=mock_dataset)

            result = adapter.handle_dataset(dataset='test_data', device=DeviceType.CPU)

            self.assertEqual(result, mock_dataset)
            adapter._get_tokenized_data.assert_called_once_with('test_data', DeviceType.CPU)

    def test_handle_dataset_failure(self):
        """测试handle_dataset方法失败情况"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )

            adapter._get_tokenized_data = MagicMock(side_effect=Exception("Processing failed"))

            with self.assertRaises(InvalidModelError):
                adapter.handle_dataset(dataset='test_data', device=DeviceType.CPU)

    def test_handle_dataset_by_batch_success(self):
        """测试handle_dataset_by_batch方法成功情况"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )

            mock_batch_dataset = [['batch1_data1', 'batch1_data2'], ['batch2_data1', 'batch2_data2']]
            adapter._get_batch_tokenized_data = MagicMock(return_value=mock_batch_dataset)

            result = adapter.handle_dataset_by_batch(
                dataset='test_data',
                batch_size=2,
                device=DeviceType.CPU
            )

            self.assertEqual(result, mock_batch_dataset)
            adapter._get_batch_tokenized_data.assert_called_once_with(
                calib_list='test_data',
                batch_size=2,
                device=DeviceType.CPU
            )

    def test_init_model_success(self):
        """测试init_model方法成功情况"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )

            mock_model = nn.Linear(10, 10)
            adapter._load_model = MagicMock(return_value=mock_model)

            result = adapter.init_model(device=DeviceType.NPU)

            self.assertIs(result, mock_model)
            adapter._load_model.assert_called_once_with(DeviceType.NPU)

    def test_enable_kv_cache_success(self):
        """测试enable_kv_cache方法成功情况"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )

            mock_model = nn.Linear(10, 10)
            adapter._enable_kv_cache = MagicMock(return_value=None)

            result = adapter.enable_kv_cache(model=mock_model, need_kv_cache=True)
            adapter._enable_kv_cache.assert_called_once_with(mock_model, True)

    def test_enable_kv_cache_failure(self):
        """测试enable_kv_cache方法失败情况"""
        with patch('msmodelslim.model.default.model_adapter.TransformersModel.__init__', return_value=None):
            adapter = DefaultModelAdapter(
                model_type=self.model_type,
                model_path=self.model_path
            )

            mock_model = nn.Linear(10, 10)
            adapter._enable_kv_cache = MagicMock(side_effect=Exception("Enable KV cache failed"))

            with self.assertRaises(InvalidModelError):
                adapter.enable_kv_cache(model=mock_model, need_kv_cache=True)