Hardcode virtual token count for tests

tests/entrypoints/openai/test_completion.py

@@ -1,6 +1,5 @@
 # imports for guided decoding tests
 import json
-import pathlib
 import re
 from typing import List
 
@@ -22,6 +21,9 @@
 # but we're not testing generation quality here
 LORA_NAME = "typeof/zephyr-7b-beta-lora"
 PA_NAME = "swapnilbp/llama_tweet_ptune"
+# if PA_NAME changes, PA_NUM_VIRTUAL_TOKENS might also
+# need to change to match the prompt adapter
+PA_NUM_VIRTUAL_TOKENS = 8
 
 
 @pytest.fixture(scope="module")
@@ -34,14 +36,6 @@ def zephyr_pa_files():
     return snapshot_download(repo_id=PA_NAME)
 
 
-@pytest.fixture(scope="module")
-def zephyr_pa_num_virtual_tokens(zephyr_pa_files):
-    with pathlib.Path(zephyr_pa_files, "adapter_config.json").open() as f:
-        adapter_config = json.load(f)
-        num_virtual_tokens = adapter_config["num_virtual_tokens"]
-    return num_virtual_tokens
-
-
 @pytest.fixture(scope="module")
 def server(zephyr_lora_files, zephyr_pa_files):
     with RemoteOpenAIServer([
@@ -87,8 +81,8 @@ def client(server):
     # first test base model, then test loras, then test prompt adapters
     "model_name,num_virtual_tokens",
     [(MODEL_NAME, 0), ("zephyr-lora", 0), ("zephyr-lora2", 0),
-     ("zephyr-pa", zephyr_pa_num_virtual_tokens),
-     ("zephyr-pa2", zephyr_pa_num_virtual_tokens)],
+     ("zephyr-pa", PA_NUM_VIRTUAL_TOKENS),
+     ("zephyr-pa2", PA_NUM_VIRTUAL_TOKENS)],
 )
 async def test_single_completion(client: openai.AsyncOpenAI, model_name: str,
                                  num_virtual_tokens: int):