Sync from v0.13

tests/lora/test_peft_helper.py

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+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import json
+import math
+import shutil
+
+import pytest
+
+from vllm.config.lora import LoRAConfig
+from vllm.lora.peft_helper import PEFTHelper
+
+ERROR_CASES = [
+    (
+        "test_rank",
+        {"r": 1024},
+        "is greater than max_lora_rank",
+    ),
+    ("test_dora", {"use_dora": True}, "does not yet support DoRA"),
+    (
+        "test_modules_to_save",
+        {"modules_to_save": ["lm_head"]},
+        "only supports modules_to_save being None",
+    ),
+]
+
+
+def test_peft_helper_pass(llama32_lora_files, tmp_path):
+    peft_helper = PEFTHelper.from_local_dir(
+        llama32_lora_files, max_position_embeddings=4096
+    )
+    lora_config = LoRAConfig(max_lora_rank=16, max_cpu_loras=3, max_loras=2)
+    peft_helper.validate_legal(lora_config)
+    assert peft_helper.r == 8
+    assert peft_helper.lora_alpha == 32
+    target_modules = sorted(peft_helper.target_modules)
+
+    assert target_modules == [
+        "down_proj",
+        "embed_tokens",
+        "gate_proj",
+        "k_proj",
+        "lm_head",
+        "o_proj",
+        "q_proj",
+        "up_proj",
+        "v_proj",
+    ]
+    assert peft_helper.vllm_max_position_embeddings == 4096
+
+    # test RSLoRA
+    rslora_config = dict(use_rslora=True)
+    test_dir = tmp_path / "test_rslora"
+    shutil.copytree(llama32_lora_files, test_dir)
+
+    # Load and modify configuration
+    config_path = test_dir / "adapter_config.json"
+    with open(config_path) as f:
+        adapter_config = json.load(f)
+    # Apply configuration changes
+    adapter_config.update(rslora_config)
+
+    # Save modified configuration
+    with open(config_path, "w") as f:
+        json.dump(adapter_config, f)
+
+    peft_helper = PEFTHelper.from_local_dir(test_dir, max_position_embeddings=4096)
+    peft_helper.validate_legal(lora_config)
+    scaling = peft_helper.lora_alpha / math.sqrt(peft_helper.r)
+    assert abs(peft_helper.vllm_lora_scaling_factor - scaling) < 1e-3
+
+
+@pytest.mark.parametrize("test_name,config_change,expected_error", ERROR_CASES)
+def test_peft_helper_error(
+    llama32_lora_files,
+    tmp_path,
+    test_name: str,
+    config_change: dict,
+    expected_error: str,
+):
+    test_dir = tmp_path / test_name
+    shutil.copytree(llama32_lora_files, test_dir)
+
+    # Load and modify configuration
+    config_path = test_dir / "adapter_config.json"
+    with open(config_path) as f:
+        adapter_config = json.load(f)
+    # Apply configuration changes
+    adapter_config.update(config_change)
+
+    # Save modified configuration
+    with open(config_path, "w") as f:
+        json.dump(adapter_config, f)
+    lora_config = LoRAConfig(max_lora_rank=16, max_cpu_loras=3, max_loras=2)
+    # Test loading the adapter
+    with pytest.raises(ValueError, match=expected_error):
+        PEFTHelper.from_local_dir(
+            test_dir, max_position_embeddings=4096
+        ).validate_legal(lora_config)