Add tensorboard monitor

trinity/common/config.py

@@ -6,7 +6,7 @@
 
 from omegaconf import OmegaConf
 
-from trinity.common.constants import AlgorithmType, PromptType, StorageType
+from trinity.common.constants import AlgorithmType, MonitorType, PromptType, StorageType
 from trinity.utils.log import get_logger
 
 logger = get_logger(__name__)
@@ -201,6 +201,7 @@ class MonitorConfig:
     # TODO: add more
     project: str = "trinity"
     name: str = "rft"
+    monitor_type: MonitorType = MonitorType.WANDB
 
     # ! DO NOT SET
     # the root directory for cache and meta files, automatically generated

trinity/common/constants.py

@@ -87,3 +87,10 @@ def is_rollout(self) -> bool:
     def is_dpo(self) -> bool:
         """Check if the algorithm is DPO."""
         return self == AlgorithmType.DPO
+
+
+class MonitorType(CaseInsensitiveEnum):
+    """Monitor Type."""
+
+    WANDB = "wandb"
+    TENSORBOARD = "tensorboard"

trinity/trainer/trainer.py

@@ -12,7 +12,7 @@
 import ray
 
 from trinity.buffer import get_buffer_reader
-from trinity.common.config import Config, TrainerConfig
+from trinity.common.config import Config
 from trinity.common.constants import AlgorithmType
 from trinity.common.experience import Experiences
 from trinity.utils.log import get_logger
@@ -37,7 +37,7 @@ def __init__(self, config: Config) -> None:
             if self.config.trainer.sft_warmup_iteration > 0
             else None
         )
-        self.engine = get_trainer_wrapper(config.trainer)
+        self.engine = get_trainer_wrapper(config)
 
     def prepare(self) -> None:
         """Prepare the trainer."""
@@ -146,9 +146,9 @@ def shutdown(self) -> None:
         """Shutdown the engine."""
 
 
-def get_trainer_wrapper(config: TrainerConfig) -> TrainEngineWrapper:
+def get_trainer_wrapper(config: Config) -> TrainEngineWrapper:
     """Get a trainer wrapper."""
-    if config.trainer_type == "verl":
+    if config.trainer.trainer_type == "verl":
         from trinity.trainer.verl_trainer import VerlPPOTrainerWrapper
 
         return VerlPPOTrainerWrapper(config)

trinity/trainer/verl_trainer.py

@@ -13,7 +13,7 @@
 from verl.utils import hf_tokenizer
 from verl.utils.fs import copy_local_path_from_hdfs
 
-from trinity.common.config import TrainerConfig
+from trinity.common.config import Config
 from trinity.common.constants import AlgorithmType
 from trinity.common.experience import Experiences
 from trinity.trainer.trainer import TrainEngineWrapper
@@ -71,8 +71,9 @@ class VerlPPOTrainerWrapper(RayPPOTrainer, TrainEngineWrapper):
 
     def __init__(
         self,
-        train_config: TrainerConfig,
+        global_config: Config,
     ):
+        train_config = global_config.trainer
         pprint(train_config.trainer_config)
         config = OmegaConf.structured(train_config.trainer_config)
         # download the checkpoint from hdfs
@@ -134,7 +135,7 @@ def __init__(
             project=config.trainer.project_name,
             name=config.trainer.experiment_name,
             role="trainer",
-            config=train_config,
+            config=global_config,
         )
         self.reset_experiences_example_table()
 

trinity/utils/monitor.py

@@ -1,11 +1,13 @@
 """Monitor"""
-
+import os
 from typing import Any, List, Optional, Union
 
 import numpy as np
 import pandas as pd
 import wandb
+from torch.utils.tensorboard import SummaryWriter
 
+from trinity.common.constants import MonitorType
 from trinity.utils.log import get_logger
 
 
@@ -19,19 +21,15 @@ def __init__(
         role: str,
         config: Any = None,
     ) -> None:
-        self.logger = wandb.init(
-            project=project,
-            group=name,
-            name=f"{name}_{role}",
-            tags=[role],
-            config=config,
-            save_code=False,
-        )
-        self.console_logger = get_logger(__name__)
+        if config.monitor.monitor_type == MonitorType.WANDB:
+            self.logger = WandbLogger(project, name, role, config)
+        elif config.monitor.monitor_type == MonitorType.TENSORBOARD:
+            self.logger = TensorboardLogger(project, name, role, config)
+        else:
+            raise ValueError(f"Unknown monitor type: {config.monitor.monitor_type}")
 
     def log_table(self, table_name: str, experiences_table: pd.DataFrame, step: int):
-        experiences_table = wandb.Table(dataframe=experiences_table)
-        self.log(data={table_name: experiences_table}, step=step)
+        self.logger.log_table(table_name, experiences_table, step=step)
 
     def calculate_metrics(
         self, data: dict[str, Union[List[float], float]], prefix: Optional[str] = None
@@ -55,6 +53,46 @@ def calculate_metrics(
     def log(self, data: dict, step: int, commit: bool = False) -> None:
         """Log metrics."""
         self.logger.log(data, step=step, commit=commit)
+
+
+class TensorboardLogger:
+    def __init__(self, project: str, name: str, role: str, config: Any = None) -> None:
+        self.tensorboard_dir = os.path.join(config.monitor.job_dir, "tensorboard")
+        os.makedirs(self.tensorboard_dir, exist_ok=True)
+        self.logger = SummaryWriter(self.tensorboard_dir)
+        self.console_logger = get_logger(__name__)
+
+    def log_table(self, table_name: str, experiences_table: pd.DataFrame, step: int):
+        pass
+
+    def log(self, data: dict, step: int, commit: bool = False) -> None:
+        """Log metrics."""
+        for key in data:
+            self.logger.add_scalar(key, data[key], step)
+
+    def __del__(self) -> None:
+        self.logger.close()
+
+
+class WandbLogger:
+    def __init__(self, project: str, name: str, role: str, config: Any = None) -> None:
+        self.logger = wandb.init(
+            project=project,
+            group=name,
+            name=f"{name}_{role}",
+            tags=[role],
+            config=config,
+            save_code=False,
+        )
+        self.console_logger = get_logger(__name__)
+
+    def log_table(self, table_name: str, experiences_table: pd.DataFrame, step: int):
+        experiences_table = wandb.Table(dataframe=experiences_table)
+        self.log(data={table_name: experiences_table}, step=step)
+
+    def log(self, data: dict, step: int, commit: bool = False) -> None:
+        """Log metrics."""
+        self.logger.log(data, step=step, commit=commit)
         self.console_logger.info(f"Step {step}: {data}")
 
     def __del__(self) -> None: