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### What does this PR do? This PR makes update to the base config in verl: - support +extra.any_key usage for the base config in verl. - allow selective subfields to be frozen - add a auto-generated config yaml file `verl/trainer/config/_generated_ppo_trainer.yaml` for reference purpose, in case the nested inheritance structure makes the config information too scattered ### Checklist Before Starting - [x] Search for similar PRs. Paste at least one query link here: ... - [x] Format the PR title as `[{modules}] {type}: {description}` (This will be checked by the CI) - `{modules}` include `fsdp`, `megatron`, `sglang`, `vllm`, `rollout`, `trainer`, `ci`, `training_utils`, `recipe`, `hardware`, `deployment`, `ray`, `worker`, `single_controller`, `misc`, `perf`, `model`, `algo`, `env`, `tool`, `ckpt`, `doc`, `data` - If this PR involves multiple modules, separate them with `,` like `[megatron, fsdp, doc]` - `{type}` is in `feat`, `fix`, `refactor`, `chore`, `test` - If this PR breaks any API (CLI arguments, config, function signature, etc.), add `[BREAKING]` to the beginning of the title. - Example: `[BREAKING][fsdp, megatron] feat: dynamic batching` ### Test - added frozen field tests ### API and Usage Example > Demonstrate how the API changes if any, and provide usage example(s) if possible. Now you can pass `--xx.profiler.extra.any_new_key=any_plain_value` in command line to a dataclass inheriting `verl.BaseConfig`. This way we can still pass dataclass configs inside verl but allow some flexiblity in accepting new keys from users' adhoc usage. ### Checklist Before Submitting > [!IMPORTANT] > Please check all the following items before requesting a review, otherwise the reviewer might deprioritize this PR for review. - [x] Read the [Contribute Guide](https://github.com/volcengine/verl/blob/main/CONTRIBUTING.md). - [x] Apply [pre-commit checks](https://github.com/volcengine/verl/blob/main/CONTRIBUTING.md#code-linting-and-formatting): `pre-commit install && pre-commit run --all-files --show-diff-on-failure --color=always` - [ ] Add / Update [the documentation](https://github.com/volcengine/verl/tree/main/docs). - [ ] Add unit or end-to-end test(s) to [the CI workflow](https://github.com/volcengine/verl/tree/main/.github/workflows) to cover all the code. If not feasible, explain why: ... - [ ] Once your PR is ready for CI, send a message in [the `ci-request` channel](https://verl-project.slack.com/archives/C091TCESWB1) in [the `verl` Slack workspace](https://join.slack.com/t/verl-project/shared_invite/zt-3855yhg8g-CTkqXu~hKojPCmo7k_yXTQ). --------- Co-authored-by: Lin <haibin@Lins-Laptop.hsd1.wa.comcast.net> Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
96 lines
3.0 KiB
Python
96 lines
3.0 KiB
Python
# Copyright 2025 Bytedance Ltd. and/or its affiliates
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from dataclasses import dataclass
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from omegaconf import OmegaConf
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from verl.utils import omega_conf_to_dataclass
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@dataclass
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class TestDataclass:
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hidden_size: int
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activation: str
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@dataclass
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class TestTrainConfig:
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batch_size: int
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model: TestDataclass
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_cfg_str = """train_config:
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batch_size: 32
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model:
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hidden_size: 768
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activation: relu"""
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class TestConfigOnCPU(unittest.TestCase):
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"""Test cases for configuration utilities on CPU.
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Test Plan:
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1. Test basic OmegaConf to dataclass conversion for simple nested structures
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2. Test nested OmegaConf to dataclass conversion for complex hierarchical configurations
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3. Verify all configuration values are correctly converted and accessible
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"""
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def setUp(self):
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self.config = OmegaConf.create(_cfg_str)
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def test_omega_conf_to_dataclass(self):
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sub_cfg = self.config.train_config.model
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cfg = omega_conf_to_dataclass(sub_cfg, TestDataclass)
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self.assertEqual(cfg.hidden_size, 768)
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self.assertEqual(cfg.activation, "relu")
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assert isinstance(cfg, TestDataclass)
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def test_nested_omega_conf_to_dataclass(self):
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cfg = omega_conf_to_dataclass(self.config.train_config, TestTrainConfig)
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self.assertEqual(cfg.batch_size, 32)
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self.assertEqual(cfg.model.hidden_size, 768)
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self.assertEqual(cfg.model.activation, "relu")
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assert isinstance(cfg, TestTrainConfig)
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assert isinstance(cfg.model, TestDataclass)
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class TestPrintCfgCommand(unittest.TestCase):
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"""Test suite for the print_cfg.py command-line tool."""
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def test_command_with_override(self):
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"""Test that the command runs without error when overriding config values."""
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import subprocess
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# Run the command
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result = subprocess.run(
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["python3", "scripts/print_cfg.py", "critic.profiler.discrete=True", "+critic.profiler.extra.any_key=val"],
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capture_output=True,
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text=True,
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)
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# Verify the command exited successfully
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self.assertEqual(result.returncode, 0, f"Command failed with stderr: {result.stderr}")
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# Verify the output contains expected config information
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self.assertIn("critic", result.stdout)
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self.assertIn("profiler", result.stdout)
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self.assertIn("discrete=True", result.stdout)
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self.assertIn("extra={'any_key': 'val'}", result.stdout)
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if __name__ == "__main__":
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unittest.main()
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