antonvice
diff --git a/‎tests/test_llama.py
Copy file name to clipboardExpand all lines: tests/test_llama.py
+3-40Lines changed: 3 additions & 40 deletions b/‎tests/test_llama.py
Copy file name to clipboardExpand all lines: tests/test_llama.py
+3-40Lines changed: 3 additions & 40 deletions
@@ -160,55 +160,18 @@ def test_llama_pickle():
     assert llama.detokenize(llama.tokenize(text)) == text
 
 
-def test_utf8(mock_llama, monkeypatch):
+def test_utf8(mock_llama):
     llama = llama_cpp.Llama(model_path=MODEL, vocab_only=True, logits_all=True)
-    n_ctx = llama.n_ctx()
-    n_vocab = llama.n_vocab()
 
     output_text = "😀"
-    output_tokens = llama.tokenize(
-        output_text.encode("utf-8"), add_bos=True, special=True
-    )
-    token_eos = llama.token_eos()
-    n = 0
-
-    def reset():
-        nonlocal n
-        llama.reset()
-        n = 0
-
-    ## Set up mock function
-    def mock_decode(ctx: llama_cpp.llama_context_p, batch: llama_cpp.llama_batch):
-        nonlocal n
-        assert batch.n_tokens > 0
-        assert llama.n_tokens == n
-        n += batch.n_tokens
-        return 0
-
-    def mock_get_logits(*args, **kwargs):
-        size = n_vocab * n_ctx
-        return (llama_cpp.c_float * size)()
-
-    def mock_sample(*args, **kwargs):
-        nonlocal n
-        if n <= len(output_tokens):
-            return output_tokens[n - 1]
-        else:
-            return token_eos
-
-    monkeypatch.setattr("llama_cpp.llama_cpp.llama_decode", mock_decode)
-    monkeypatch.setattr("llama_cpp.llama_cpp.llama_get_logits", mock_get_logits)
-    monkeypatch.setattr("llama_cpp.llama_cpp.llama_sample_token", mock_sample)
 
     ## Test basic completion with utf8 multibyte
-    # mock_llama(llama, output_text)
-    reset()
+    mock_llama(llama, output_text)
     completion = llama.create_completion("", max_tokens=4)
     assert completion["choices"][0]["text"] == output_text
 
     ## Test basic completion with incomplete utf8 multibyte
-    # mock_llama(llama, output_text)
-    reset()
+    mock_llama(llama, output_text)
     completion = llama.create_completion("", max_tokens=1)
     assert completion["choices"][0]["text"] == ""