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* [fix]Modify follow-up push parameters and Modify the verification method for thinking length (#4086) * 续推参数 generated_token_ids 修改成 completion_token_ids;修改思考长度校验方式 * 续推参数 generated_token_ids 修改成 completion_token_ids;修改思考长度校验方式 * 续推参数 generated_token_ids 修改成 completion_token_ids;修改思考长度校验方式 * 续推参数 generated_token_ids 修改成 completion_token_ids;修改思考长度校验方式 * add completion_token_ids * add logger * fix reasoning_max_tokens ParameterError * add unittest * add unittest * add unittest * add unittest * add unittest * add unit test * fix * [fix]update apply_chat_template (#4137) * update apply_chat_template * fix unittest * fix unittest * fix * fix * fix unit test * fix * fix unit test * add unit test
80 lines
3.1 KiB
Python
80 lines
3.1 KiB
Python
import unittest
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from unittest.mock import MagicMock, patch
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from fastdeploy.input.ernie4_5_processor import Ernie4_5Processor
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class TestErnie4_5ProcessorProcessResponseDictStreaming(unittest.TestCase):
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def setUp(self):
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# 创建 Ernie4_5Processor 实例的模拟对象
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with patch.object(Ernie4_5Processor, "__init__", return_value=None) as mock_init:
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self.processor = Ernie4_5Processor("model_path")
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mock_init.side_effect = lambda *args, **kwargs: print(f"__init__ called with {args}, {kwargs}")
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# 设置必要的属性
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self.processor.tokenizer = MagicMock()
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self.processor.tokenizer.eos_token_id = 1
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self.processor.decode_status = {}
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self.processor.reasoning_end_dict = {}
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self.processor.tool_parser_dict = {}
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self.processor.generation_config = MagicMock()
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self.processor.eos_token_ids = [1]
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# 模拟 ids2tokens 方法
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def mock_ids2tokens(token_ids, task_id):
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return "delta_text", [2, 3], "previous_texts"
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self.processor.ids2tokens = mock_ids2tokens
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def mock_messages2ids(request, **kwargs):
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if "chat_template" in kwargs:
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return [1]
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else:
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return [0]
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def mock_apply_default_parameters(request):
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return request
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self.processor.messages2ids = mock_messages2ids
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self.processor._apply_default_parameters = mock_apply_default_parameters
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# 模拟推理解析器
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self.mock_reasoning_parser = MagicMock()
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self.mock_reasoning_parser.__class__.__name__ = "ErnieX1ReasoningParser"
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self.mock_reasoning_parser.extract_reasoning_content_streaming.return_value = ("reasoning", "text")
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self.processor.reasoning_parser = self.mock_reasoning_parser
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# 模拟工具解析器
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self.mock_tool_parser = MagicMock()
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self.mock_tool_parser.extract_tool_calls_streaming.return_value = None
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self.mock_tool_parser_obj = MagicMock()
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self.mock_tool_parser_obj.return_value = self.mock_tool_parser
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self.processor.tool_parser_obj = self.mock_tool_parser_obj
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def test_process_response_dict_streaming_normal_case(self):
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"""测试正常情况下的流式响应处理"""
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# 准备输入
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response_dict = {"finished": False, "request_id": "req1", "outputs": {"token_ids": [4, 5]}}
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kwargs = {"enable_thinking": True}
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# 调用方法
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result = self.processor.process_response_dict_streaming(response_dict, **kwargs)
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# 验证结果
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self.assertEqual(result["outputs"]["raw_prediction"], "delta_text")
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def test_process_request_dict(self):
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request_dict = {
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"messages": [{"role": "user", "content": "Hello!"}],
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"chat_template_kwargs": {"chat_template": "Hello!"},
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"eos_token_ids": [1],
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"temperature": 1,
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"top_p": 1,
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}
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result = self.processor.process_request_dict(request_dict, 100)
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self.assertEqual(result["prompt_token_ids"], [1])
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if __name__ == "__main__":
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unittest.main()
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