Add continue_from_checkpoint

docs/sphinx_doc/source/tutorial/trinity_configs.md

@@ -11,6 +11,7 @@ project: Trinity-RFT
 name: example
 mode: both
 checkpoint_root_dir: /PATH/TO/CHECKPOINT
+continue_from_checkpoint: true
 
 algorithm:
   # Algorithm-related parameters
@@ -68,6 +69,7 @@ checkpoint_root_dir: /PATH/TO/CHECKPOINT
   - `explore`: Only launches the explorer.
   - `bench`: Used for benchmarking.
 - `checkpoint_root_dir`: Root directory where all checkpoints and logs will be saved. Checkpoints for this experiment will be stored in `<checkpoint_root_dir>/<project>/<name>/`.
+- `continue_from_checkpoint`: If set to `true`, the experiment will continue from the latest checkpoint in the checkpoint path (if any); otherwise, it will rename the current experiment to `<name>_<timestamp>` and start a new experiment.
 - `ray_namespace`: Namespace for the modules launched in the current experiment. If not specified, it will be set to `<project>/<name>`.
 
 ---

tests/common/config_test.py

@@ -1,11 +1,15 @@
 # -*- coding: utf-8 -*-
 """Test cases for Config modules."""
+import datetime
 import os
+import shutil
 import unittest
 
 from tests.tools import get_template_config
 from trinity.common.config import InferenceModelConfig, load_config
 
+CHECKPOINT_ROOT_DIR = os.path.join(os.path.dirname(__file__), "temp_checkpoint_dir")
+
 
 class TestConfig(unittest.TestCase):
     def test_load_default_config(self):
@@ -54,3 +58,26 @@ def test_all_examples_are_valid(self):
                     except Exception as e:
                         print(f"Error loading config {config_path}: {e}")
                         raise e
+
+    def test_continue_from_checkpoint_is_valid(self):
+        config = get_template_config()
+        config.name = "test"
+        config.project = "unittest"
+        config.checkpoint_root_dir = CHECKPOINT_ROOT_DIR
+
+        dir_path = os.path.join(config.checkpoint_root_dir, config.project, config.name)
+        os.makedirs(os.path.join(dir_path, "global_step_1"))
+
+        config.continue_from_checkpoint = True
+        config.check_and_update()
+        self.assertEqual(config.name, "test")
+
+        config.continue_from_checkpoint = False
+        config.check_and_update()
+        self.assertTrue(config.name.startswith("test_"))
+        timestamp = config.name.split("_")[-1]
+        self.assertTrue(datetime.datetime.strptime(timestamp, "%Y%m%d%H%M%S"))
+
+    def tearDown(self):
+        if os.path.exists(CHECKPOINT_ROOT_DIR):
+            shutil.rmtree(CHECKPOINT_ROOT_DIR)

trinity/common/config.py

@@ -2,6 +2,7 @@
 """Configs for RFT."""
 import os
 from dataclasses import dataclass, field
+from datetime import datetime
 from typing import Any, Dict, List, Optional
 
 from omegaconf import OmegaConf
@@ -399,6 +400,8 @@ class Config:
     checkpoint_job_dir: str = ""
     # If not set, automatically generated as f"{config.project}-{config.name}"
     ray_namespace: str = ""
+    # whether to continue training from the last checkpoint in checkpoint_job_dir (if any)
+    continue_from_checkpoint: bool = True
 
     algorithm: AlgorithmConfig = field(default_factory=AlgorithmConfig)
     data_processor: DataProcessorConfig = field(default_factory=DataProcessorConfig)
@@ -713,6 +716,15 @@ def check_and_update(self) -> None:  # noqa: C901
             self.checkpoint_root_dir = os.path.join(os.getcwd(), self.checkpoint_root_dir)
         # create a job dir at checkpoint_root_dir/project/name
         self.checkpoint_job_dir = os.path.join(self.checkpoint_root_dir, self.project, self.name)
+        # rename the experiment when necessary
+        if not self.continue_from_checkpoint and (
+            os.path.exists(self.checkpoint_job_dir) and os.listdir(self.checkpoint_job_dir)
+        ):
+            ori_name = self.name
+            timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
+            self.name = f"{ori_name}_{timestamp}"
+            self.checkpoint_job_dir = f"{self.checkpoint_job_dir}_{timestamp}"
+            logger.warning(f"Experiment [{ori_name}] already exists, renamed as {self.name}.")
         os.makedirs(self.checkpoint_job_dir, exist_ok=True)
 
         # check and update model path

trinity/common/verl_config.py

@@ -293,6 +293,10 @@ def synchronize_config(self, config: Config) -> None:  # noqa: C901
         self.trainer.experiment_name = config.name
         self.trainer.default_local_dir = config.checkpoint_job_dir
         self.trainer.sft_warmup_steps = config.buffer.trainer_input.sft_warmup_steps
+        if not config.continue_from_checkpoint:
+            self.trainer.resume_mode = "disable"
+        else:
+            self.trainer.resume_mode = "auto"
 
         self.buffer = config.buffer
         # TODO: use dynamic read_batch_size to support multi-round scenarios