[CI]【Hackathon 9th Sprint No.14】功能模块 fastdeploy/rl/rollout_model.py 单测补充 (#5552)

* Add rollout model unit tests

* test: update rl rollout_model tests

* test: fix cache_type_branches unsupported platform case

* test: fix rl rollout_model test indent

* Delete tests/spec_decode/test_mtp_proposer.py

* chore: format test_rollout_model

* chore: translate rollout test comments to English

* test: guard rollout_model import by disabling auto registry

* chore: reorder imports in rl rollout test

* test: isolate env for RL rollout tests

* style: format rollout RL tests with black

* update

* test: remove RL rollout unit tests causing collection issues

* test: add lightweight rollout_model RL unit tests

* fix(coverage): filter test file paths and handle collection failures

- Only extract real test file paths (tests/.../test_*.py) from pytest collect output

- Filter out ERROR/collecting prefixes to prevent garbage in failed_tests.log

- Add proper error handling for pytest collection failures

- Exit early if no test files can be extracted

- Preserve collection error output for debugging

* update

* style: fix code style issues in test_rollout_model.py

- Remove unused 'os' import

- Remove trailing blank lines

---------

Co-authored-by: YuBaoku <49938469+EmmonsCurse@users.noreply.github.com>

scripts/coverage_run.sh

@@ -14,9 +14,16 @@ failed_tests_file="failed_tests.log"
 
 ##################################
 # 执行 pytest，每个文件单独跑
-##################################
-# 收集 pytest 文件
-TEST_FILES=$(python -m pytest --collect-only -q -c ${PYTEST_INI} ${tests_path} --rootdir=${run_path} --disable-warnings | grep -Eo '^.*test_.*\.py' | sort | uniq)
+# 使用 pytest 的 --collect-only 输出，并从每行中提取真正的测试文件路径（形如 tests/.../test_*.py）。
+# 注意：pytest 在收集失败时会输出形如 "ERROR tests/xxx/test_xxx.py::test_xxx ..." 的行，
+# 为了避免把前缀 "ERROR"/"FAILED"/"collecting" 等误当成文件名，这里只保留行中出现的
+# "tests/.../test_*.py" 这一段，其他前后内容直接丢弃。
+TEST_FILES=$(
+  python -m pytest --collect-only -q -c "${PYTEST_INI}" "${tests_path}" --rootdir="${run_path}" --disable-warnings 2>&1 \
+    | grep -E 'tests/.+\/test_.*\.py' \
+    | sed -E 's@.*(tests/[^: ]*test_[^: ]*\.py).*@\1@' \
+    | sort -u
+)
 
 
 failed_pytest=0

tests/rl/test_rollout_model.py

@@ -0,0 +1,215 @@
+"""
+Unit tests for `fastdeploy.rl.rollout_model`.
+
+These tests focus purely on Python-side mapping / quantization logic and
+intentionally avoid any heavy engine or model initialization. They should not
+modify global environment in a way that affects other test modules.
+"""
+
+import types
+
+import pytest  # type: ignore
+
+# Conservative guard: skip locally if paddle is missing; CI has paddle installed.
+try:  # pragma: no cover - env probe
+    import paddle  # noqa: F401
+except Exception as e:  # pragma: no cover - env probe
+    pytest.skip(f"Skip RL rollout tests, paddle import failed: {e}", allow_module_level=True)
+
+
+from fastdeploy.rl.rollout_model import (
+    BaseRLModel,
+    Ernie4_5_MoeForCausalLMRL,
+    Ernie4_5_VLMoeForConditionalGenerationRL,
+    Glm4MoeForCausalLMRL,
+    Qwen2_5_VLForConditionalGenerationRL,
+    Qwen2ForCausalLMRL,
+    Qwen3ForCausalLMRL,
+    Qwen3MoeForCausalLMRL,
+    RolloutModel,
+)
+
+
+def _dummy_instance(
+    cls,
+    model_config_kwargs,
+    state_keys,
+    parallel_config=None,
+    quant_name="wint8",
+):
+    """Create a lightweight instance without running heavy model init."""
+    inst = cls.__new__(cls)
+    BaseRLModel.__init__(inst)
+    inst.fd_config = types.SimpleNamespace(
+        model_config=types.SimpleNamespace(**model_config_kwargs),
+        parallel_config=parallel_config or types.SimpleNamespace(tensor_parallel_size=1),
+        quant_config=types.SimpleNamespace(name=lambda: quant_name),
+    )
+    inst.state_dict = lambda: {k: 0 for k in state_keys}
+    return inst
+
+
+def test_rollout_model_quantization_and_state_dict_fallback():
+    """RolloutModel wrapper should safely delegate to underlying rollout_model."""
+    # Cover default branch when rollout_model lacks quantization/state_dict
+    fallback = RolloutModel.__new__(RolloutModel)
+    fallback.rollout_model = types.SimpleNamespace()
+    assert fallback.get_quantization_infer_keys() == {}
+
+    # Cover delegate branch when rollout_model implements quantization/state_dict
+    forwarded = RolloutModel.__new__(RolloutModel)
+    forwarded.rollout_model = types.SimpleNamespace(
+        get_quantization_infer_keys=lambda: {"k": "v"},
+        state_dict=lambda: {"p": 1},
+    )
+    assert forwarded.get_quantization_infer_keys() == {"k": "v"}
+    assert forwarded.state_dict() == {"p": 1}
+
+
+def test_base_rl_name_and_quantization_keys_and_error():
+    model = BaseRLModel.__new__(BaseRLModel)
+    BaseRLModel.__init__(model)
+
+    # Cover BaseRLModel.name and wint8 branch
+    assert BaseRLModel.name() == "BaseRLModel"
+    model.fd_config = types.SimpleNamespace(quant_config=types.SimpleNamespace(name=lambda: "wint8"))
+    model.state_dict = lambda: {
+        "a.weight_scale": 1,
+        "b.weight_scale": 2,
+        "c.weight": 3,
+    }
+    assert model.get_quantization_infer_keys() == ["a.weight", "b.weight"]
+
+    # Cover non-wint8 branch raising error
+    model.fd_config = types.SimpleNamespace(quant_config=types.SimpleNamespace(name=lambda: "fp16"))
+    with pytest.raises(ValueError):
+        model.get_quantization_infer_keys()
+
+
+def test_complete_missing_mappings_skips_scale():
+    model = BaseRLModel.__new__(BaseRLModel)
+    BaseRLModel.__init__(model)
+    model.state_dict = lambda: {
+        "kept.weight": 1,
+        "ignored.weight_scale": 2,
+    }
+    model._complete_missing_mappings()
+    assert model.infer_to_train_mapping["kept.weight"] == "kept.weight"
+    assert "ignored.weight_scale" not in model.infer_to_train_mapping
+
+
+def test_ernie45_moe_mapping_and_cache():
+    dummy = _dummy_instance(
+        Ernie4_5_MoeForCausalLMRL,
+        {
+            "moe_use_aux_free": True,
+            "moe_num_experts": 2,
+            "moe_layer_start_index": 1,
+            "num_hidden_layers": 3,
+        },
+        [
+            "ernie.layers.1.mlp.experts.0.up_gate_proj.weight",
+            "ernie.layers.1.mlp.experts.0.down_proj.weight",
+            "some.weight",
+            "scale.weight_scale",
+        ],
+    )
+    first = dummy.get_name_mappings_to_training()
+    # Cover gate/gate_correction_bias mapping and MoE experts aggregation
+    assert "ernie.layers.1.mlp.experts.gate_correction_bias" in first
+    assert first["some.weight"] == "some.weight"
+    assert "scale.weight_scale" not in first
+    # Cover cached path
+    assert dummy.get_name_mappings_to_training() is first
+
+
+def test_ernie45_vl_moe_text_and_image_mappings():
+    dummy = _dummy_instance(
+        Ernie4_5_VLMoeForConditionalGenerationRL,
+        {
+            "moe_use_aux_free": False,
+            "moe_num_experts": [8, 8],
+            "moe_layer_start_index": (0, 1),
+            "moe_layer_end_index": (1, 2),
+            "num_hidden_layers": 2,
+        },
+        [
+            "ernie.layers.0.mlp.experts.0.up_gate_proj.weight",
+            "ernie.layers.1.mlp.experts.2.down_proj.weight",
+        ],
+        parallel_config=types.SimpleNamespace(tensor_parallel_size=4),
+    )
+    mappings = dummy.get_name_mappings_to_training()
+    # Cover fused MoE text/image expert mappings
+    assert "ernie.layers.0.mlp.text_fused_moe.experts.up_gate_proj_weight" in mappings
+    assert "ernie.layers.1.mlp.image_fused_moe.experts.down_proj_weight" in mappings
+
+
+def test_qwen2_mapping_builds_and_completes():
+    dummy = _dummy_instance(
+        Qwen2ForCausalLMRL,
+        {"num_hidden_layers": 2},
+        ["qwen2.layers.0.mlp.gate_up_fused_proj.weight"],
+    )
+    mappings = dummy.get_name_mappings_to_training()
+    # Cover up_gate_proj -> gate_up_fused_proj mapping
+    assert "qwen2.layers.0.mlp.up_gate_proj.weight" in mappings
+    assert mappings["qwen2.layers.0.mlp.up_gate_proj.weight"] == "qwen2.layers.0.mlp.gate_up_fused_proj.weight"
+
+
+def test_qwen3moe_mapping_aux_free():
+    dummy = _dummy_instance(
+        Qwen3MoeForCausalLMRL,
+        {"moe_use_aux_free": True, "num_experts": 1, "num_hidden_layers": 1},
+        [
+            "model.layers.0.mlp.experts.0.up_gate_proj.weight",
+            "model.layers.0.mlp.experts.0.down_proj.weight",
+        ],
+    )
+    mappings = dummy.get_name_mappings_to_training()
+    # Cover gate/gate_correction_bias handling and expert merge
+    assert "model.layers.0.mlp.gate.weight" in mappings
+
+
+def test_qwen3_mapping_basic():
+    dummy = _dummy_instance(
+        Qwen3ForCausalLMRL,
+        {"num_hidden_layers": 1},
+        ["model.layers.0.mlp.gate_up_fused_proj.weight"],
+    )
+    mappings = dummy.get_name_mappings_to_training()
+    assert "model.layers.0.mlp.up_gate_proj.weight" in mappings
+
+
+def test_qwen25_vl_mapping_basic():
+    dummy = _dummy_instance(
+        Qwen2_5_VLForConditionalGenerationRL,
+        {"num_hidden_layers": 1},
+        ["model.layers.0.mlp.gate_up_fused_proj.weight"],
+    )
+    mappings = dummy.get_name_mappings_to_training()
+    assert "model.layers.0.mlp.up_gate_proj.weight" in mappings
+
+
+def test_glm4moe_mapping_removes_gate_correction():
+    dummy = _dummy_instance(
+        Glm4MoeForCausalLMRL,
+        {
+            "n_routed_experts": 1,
+            "first_k_dense_replace": 0,
+            "num_hidden_layers": 1,
+        },
+        [
+            "model.layers.0.mlp.experts.0.up_gate_proj.weight",
+            "model.layers.0.mlp.experts.0.down_proj.weight",
+            "model.layers.0.mlp.experts.gate_correction_bias",
+        ],
+    )
+    mappings = dummy.get_name_mappings_to_training()
+    # Cover gate/experts aggregation and dropping gate_correction_bias
+    assert "model.layers.0.mlp.experts.up_gate_proj_weight" in mappings
+    assert "model.layers.0.mlp.experts.gate_correction_bias" not in mappings
+
+
+if __name__ == "__main__":
+    pytest.main()