cache feature (#3857)

tests/model_loader/test_model_cache.py

@@ -0,0 +1,128 @@
+# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import sys
+
+import pytest
+
+current_dir = os.path.dirname(os.path.abspath(__file__))
+project_root = os.path.abspath(os.path.join(current_dir, ".."))
+if project_root not in sys.path:
+    sys.path.insert(0, project_root)
+
+from tests.model_loader.utils import (
+    check_tokens_id_and_text_close,
+    form_model_get_output_topp0,
+    get_paddle_model_path,
+    run_with_timeout,
+)
+
+FD_ENGINE_QUEUE_PORT = int(os.getenv("FD_ENGINE_QUEUE_PORT", 8313))
+FD_CACHE_QUEUE_PORT = int(os.getenv("FD_CACHE_QUEUE_PORT", 8333))
+
+prompts = ["解释下“温故而知新", "Hello, how are you?"]
+
+
+model_param_map = {
+    "ernie-4_5-21b-a3b-bf16-paddle": {
+        "tensor_parallel_size": 2,
+        "quantizations": [
+            {
+                "quant_type": "wint4",
+                "env": {"FD_ENABLE_MODEL_CACHE": "1"},
+            }
+        ],
+    }
+}
+
+
+params = []
+for model, cfg in model_param_map.items():
+    for q in cfg["quantizations"]:
+        if isinstance(q, dict):
+            quant, backend, env = q["quant_type"], q.get("backend", "default"), q.get("env", {})
+        else:
+            quant, backend, env = q, "default", {}
+        params.append(
+            pytest.param(
+                model,
+                cfg.get("tensor_parallel_size", 1),
+                cfg.get("max_model_len", 1024),
+                quant,
+                cfg.get("max_tokens", 32),
+                env,
+                marks=[pytest.mark.core_model],
+                id=f"{model}.{quant}.{backend}",
+            )
+        )
+
+
+@pytest.mark.parametrize(
+    "model_name_or_path,tensor_parallel_size,max_model_len,quantization,max_tokens,env",
+    params,
+)
+def test_model_cache(
+    fd_runner,
+    model_name_or_path: str,
+    tensor_parallel_size: int,
+    max_model_len: int,
+    max_tokens: int,
+    quantization: str,
+    env,
+    monkeypatch,
+) -> None:
+    model_path = get_paddle_model_path(model_name_or_path)
+
+    fd_outputs_v1 = run_with_timeout(
+        target=form_model_get_output_topp0,
+        args=(
+            fd_runner,
+            model_path,
+            tensor_parallel_size,
+            max_model_len,
+            max_tokens,
+            quantization,
+            "default_v1",
+            FD_ENGINE_QUEUE_PORT,
+            prompts,
+            FD_CACHE_QUEUE_PORT,
+        ),
+    )
+
+    if env:
+        for k, v in env.items():
+            monkeypatch.setenv(k, v)
+
+    fd_outputs_v1_with_cache = run_with_timeout(
+        target=form_model_get_output_topp0,
+        args=(
+            fd_runner,
+            model_path,
+            tensor_parallel_size,
+            max_model_len,
+            max_tokens,
+            quantization,
+            "default_v1",
+            FD_ENGINE_QUEUE_PORT,
+            prompts,
+            FD_CACHE_QUEUE_PORT,
+        ),
+    )
+    check_tokens_id_and_text_close(
+        outputs_0_lst=fd_outputs_v1,
+        outputs_1_lst=fd_outputs_v1_with_cache,
+        name_0="default_v1 laoder",
+        name_1="default_v1 loader using cache",
+    )