import hashlib import json import os import pickle import unittest from unittest.mock import patch from lm_eval.api.instance import Instance from lm_eval.models.gguf import GGUFLM base_url = "https://matthoffner-ggml-llm-api.hf.space" def gguf_completion_mock(base_url=None, **kwargs): # Generate a hash from the parameters hash_kwargs = {"base_url": base_url, **kwargs} hash = hashlib.sha256( json.dumps(hash_kwargs, sort_keys=True).encode("utf-8") ).hexdigest() fname = f"./tests/testdata/gguf_test_{hash}.pkl" if os.path.exists(fname): with open(fname, "rb") as fh: return pickle.load(fh) else: print("The file does not exist, attempting to write...") if "stop" in kwargs: result = { "choices": [ { "text": f"generated text until {kwargs['stop']}", "logprobs": {"token_logprobs": [-1.2345], "text_offset": 0}, "finish_reason": "length", } ] } else: # generated with # curl -X 'POST' 'http://localhost:8000/v1/completions' -H 'accept: application/json' -H 'Content-Type: application/json' -d '{"prompt": "string", "logprobs": 10, "temperature": 0.0, "max_tokens": 1, "echo": true}' result = { "id": "cmpl-4023976b-bc6a-43b0-a5a9-629f4216c7f3", "object": "text_completion", "created": 1700511361, "model": "../llama-2-7b.Q8_0.gguf", "choices": [ { "text": "string(", "index": 0, "logprobs": { "text_offset": [0, 7], "token_logprobs": [None, -1.033263319857306], "tokens": [" string", "("], "top_logprobs": [ None, { "(": -1.033263319857306, "[]": -2.6530743779017394, ".": -3.0377145947291324, "\n": -3.0399156750513976, "_": -3.510376089937872, " =": -3.6957918347193663, ",": -3.9309459866358702, " of": -4.2834550083949035, '("': -4.322762841112799, "()": -4.426229113466925, }, ], }, "finish_reason": "length", } ], "usage": { "prompt_tokens": 2, "completion_tokens": 1, "total_tokens": 3, }, } try: os.makedirs(os.path.dirname(fname), exist_ok=True) print("Writing file at", fname) with open(fname, "wb") as fh: pickle.dump(result, fh) print("File written successfully") except Exception as e: print("File writing failed:", e) return result class GGUFLMTest(unittest.TestCase): @patch( "lm_eval.models.gguf.GGUFLM.gguf_completion", side_effect=gguf_completion_mock ) def test_loglikelihood(self, gguf_completion_mock): lm = GGUFLM(base_url) # Test loglikelihood requests = [ Instance( request_type="loglikelihood", doc=args, arguments=args, idx=i, ) for i, args in enumerate([("str", "ing"), ("str", "ing")]) ] res = lm.loglikelihood(requests) # Assert the loglikelihood response is correct expected_res = [(logprob, True) for logprob in [0, 0]] self.assertEqual(res, expected_res) @patch( "lm_eval.models.gguf.GGUFLM.gguf_completion", side_effect=gguf_completion_mock ) def test_generate_until(self, gguf_completion_mock): lm = GGUFLM(base_url) # Test generate_until requests = [ Instance( request_type="generate_until", doc={"input": doc}, arguments=(doc, {"until": stop}), idx=i, ) for i, (doc, stop) in enumerate([("input1", "stop1"), ("input2", "stop2")]) ] res = lm.generate_until(requests) # Assert the generate_until response is correct expected_res = ["generated text until stop1", "generated text until stop2"] self.assertEqual(res, expected_res) # @patch('lm_eval.models.gguf.GGUFLM.gguf_completion', side_effect=gguf_completion_mock) # def test_loglikelihood_rolling(self, gguf_completion_mock): # lm = GGUFLM(base_url) # # Test loglikelihood_rolling # requests = ["input1", "input2"] # res = lm.loglikelihood_rolling(requests) # # Assert the loglikelihood_rolling response is correct # expected_res = [(-1.2345, True), (-1.2345, True)] # self.assertEqual(res, expected_res) if __name__ == "__main__": unittest.main()