Add example_async_mode

README.md

@@ -260,7 +260,8 @@ More example config files can be found in `examples`.
 
 For more detailed examples about how to use Trinity-RFT, please refer to the following tutorials:
 + [A quick example with GSM8k](./docs/sphinx_doc/source/tutorial/example_reasoning_basic.md);
-+ [Off-policy / asynchronous modes of RFT](./docs/sphinx_doc/source/tutorial/example_reasoning_advanced.md);
++ [Off-policy mode of RFT](./docs/sphinx_doc/source/tutorial/example_reasoning_advanced.md);
++ [Asynchronous mode of RFT](./docs/sphinx_doc/source/tutorial/example_async_mode.md);
 + [Multi-turn tasks](./docs/sphinx_doc/source/tutorial/example_multi_turn.md);
 + [Data processing pipelines](./docs/sphinx_doc/source/tutorial/example_data_functionalities.md);
 + [Offline learning by DPO](./docs/sphinx_doc/source/tutorial/example_dpo.md).

docs/sphinx_doc/source/main.md

@@ -240,7 +240,8 @@ More example config files can be found in `examples`.
 
 For more detailed examples about how to use Trinity-RFT, please refer to the following documents:
 + [A quick example with GSM8k](tutorial/example_reasoning_basic.md);
-+ [Off-policy / asynchronous modes of RFT](tutorial/example_reasoning_advanced.md);
++ [Off-policy mode of RFT](tutorial/example_reasoning_advanced.md);
++ [Asynchronous mode of RFT](tutorial/example_async_mode.md);
 + [Multi-turn tasks](tutorial/example_multi_turn.md);
 + [Data processing pipelines](tutorial/example_data_functionalities.md);
 + [Offline learning by DPO](tutorial/example_dpo.md).

docs/sphinx_doc/source/tutorial/example_async_mode.md

@@ -0,0 +1,41 @@
+# A quick example for asynchronous mode
+
+This example shows how to run RFT in asynchronous mode with the GRPO algorithm, Qwen-2.5-1.5B-Instruct model and GSM8K dataset.
+
+Trinity-RFT supports an asynchronous mode by running the trainer and explorer in separate processes.
+
+For this purpose, we prepare two main config files: `trainer.yaml` and `explorer.yaml`.
+The main difference between them is that in `trainer.yaml` we set `mode=train`, while in `explorer.yaml` we set `mode=explore`.
+In addition, we need to configure the following parameters in both files.
+The model weights of the explorer and trainer are synchronized once every `sync_iteration_interval * batch_size` tasks.
+
+```yaml
+data:
+  batch_size: <batch_size>
+# The same checkpoint path
+model:
+  checkpoint_path: /PATH/TO/CHECKPOINT
+
+# The same data_base path
+buffer:
+  train_dataset:
+    name: gsm8k_buffer
+    storage_type: queue
+    path: 'sqlite:///gsm8k.db'
+
+synchronizer:
+  sync_method: 'checkpoint'
+  sync_iteration_interval: <sync_iteration_interval>
+```
+
+You may run this example with the following command:
+
+```bash
+bash examples/async_gsm8k/run.sh
+```
+
+The following plot shows the learning curve of GRPO in the asynchronous mode.
+> This result should be regarded merely as a baseline, since GRPO is supposed to be an on-policy algorithm.
+> We are continuously investigating other RL algorithms (e.g., [OPMD](./example_reasoning_advanced.md)) in the asynchronous mode.
+
+![async](../../assets/async-curve.png)

docs/sphinx_doc/source/tutorial/example_reasoning_advanced.md

@@ -1,4 +1,4 @@
-# Example: off-policy / asynchronous RFT mode
+# Example: off-policy RFT mode
 
 
 Let's continue with the [previous GSM8k example](./example_reasoning_basic.md) and show some advanced features provided by Trinity-RFT, namely, off-policy or asynchronous RFT mode.
@@ -35,17 +35,3 @@ A similar performance boost is shown at step 21, which leads to a converged scor
 
 
 ![opmd](../../assets/opmd-curve.png)
-
-
-
-
-
-## Asynchronous mode
-
-
-Trinity-RFT supports the asynchronous and decoupled mode of RFT, where explorer and trainer act independently and asynchronously.
-To run this mode, the explorer and trainer need to be launched separately, with the `mode` parameter in the config file set to `explore` and `train` respectively.
-
-
-
-*We are still testing this mode more thoroughly. A concrete example is coming soon!*

examples/async_gsm8k/README.md

@@ -0,0 +1,13 @@
+# Asynchronous mode on GSM8K dataset
+
+This example shows the usage of GRPO on the GSM8K dataset in an asynchronous mode.
+
+For more detailed information, please refer to the [documentation](../../docs/sphinx_doc/source/tutorial/example_async_mode.md).
+
+The config files are located in [`trainer.yaml`](trainer.yaml), [`explorer.yaml`](explorer.yaml), and [`verl_config.yaml`](verl_config.yaml).
+
+You can run this example by the following command:
+
+```bash
+bash examples/async_gsm8k/run.sh
+```

examples/async_gsm8k/explorer.yaml

@@ -0,0 +1,58 @@
+mode: explore
+data:
+  # basic info
+  dataset_path: /PATH/TO/DATASET/
+  subset_name: ''
+  train_split: 'train'
+  eval_split: 'test'
+  format_config:
+    prompt_key: 'question'
+    response_key: 'answer'
+  # downstream loading related
+  total_epochs: 20
+  batch_size: 96
+  default_workflow_type: 'math_workflow'
+model:
+  model_path: /PATH/TO/MODEL/
+  max_prompt_tokens: 256
+  max_response_tokens: 1024
+  checkpoint_path: 'checkpoints/qwen2.5-1.5B-gsm8k'
+cluster:
+  node_num: 1
+  gpu_per_node: 8
+buffer:
+  max_retry_times: 3
+  max_retry_interval: 1
+  train_dataset:
+    name: gsm8k_buffer
+    storage_type: queue
+    path: 'sqlite:///gsm8k.db'
+explorer:
+  engine_type: vllm_async
+  engine_num: 2
+  runner_num: 32
+  tensor_parallel_size: 1
+  enable_prefix_caching: false
+  enforce_eager: true
+  dtype: bfloat16
+  temperature: 1.0
+  seed: 42
+  logprobs: 0
+  repeat_times: 8
+  use_ray: false
+  backend: 'nccl'
+  max_pending_requests: 32
+  max_waiting_steps: 4
+synchronizer:
+  sync_method: 'checkpoint'
+  sync_iteration_interval: 10
+trainer:
+  trainer_type: 'verl'
+  algorithm_type: ppo
+  trainer_config_path: examples/async_gsm8k/verl_config.yaml
+  sft_warmup_iteration: 0 # Set to integer to enable sft warmup
+  eval_interval: 10
+monitor:
+  cache_root_dir: ""
+  project: "Trinity-RFT-gsm8k"
+  name: "async-qwen2.5-1.5B-gsm8k"

examples/async_gsm8k/run.sh

@@ -0,0 +1,4 @@
+#!/bin/bash
+trinity run --config examples/async_gsm8k/explorer.yaml 2>&1 | tee explorer.log &
+sleep 30
+trinity run --config examples/async_gsm8k/trainer.yaml 2>&1 | tee trainer.log &

examples/async_gsm8k/trainer.yaml

@@ -0,0 +1,58 @@
+mode: train
+data:
+  # basic info
+  dataset_path: /PATH/TO/DATASET/
+  subset_name: ''
+  train_split: 'train'
+  eval_split: 'test'
+  format_config:
+    prompt_key: 'question'
+    response_key: 'answer'
+  # downstream loading related
+  total_epochs: 20
+  batch_size: 96
+  default_workflow_type: 'math_workflow'
+model:
+  model_path: /PATH/TO/MODEL/
+  max_prompt_tokens: 256
+  max_response_tokens: 1024
+  checkpoint_path: ""
+cluster:
+  node_num: 1
+  gpu_per_node: 8
+buffer:
+  max_retry_times: 3
+  max_retry_interval: 1
+  train_dataset:
+    name: gsm8k_buffer
+    storage_type: queue
+    path: 'sqlite:///gsm8k.db'
+explorer:
+  engine_type: vllm_async
+  engine_num: 2
+  runner_num: 32
+  tensor_parallel_size: 1
+  enable_prefix_caching: false
+  enforce_eager: true
+  dtype: bfloat16
+  temperature: 1.0
+  seed: 42
+  logprobs: 0
+  repeat_times: 8
+  use_ray: false
+  backend: 'nccl'
+  max_pending_requests: 32
+  max_waiting_steps: 4
+synchronizer:
+  sync_method: 'checkpoint'
+  sync_iteration_interval: 10
+trainer:
+  trainer_type: 'verl'
+  algorithm_type: ppo
+  trainer_config_path: examples/async_gsm8k/verl_config.yaml
+  sft_warmup_iteration: 0 # Set to integer to enable sft warmup
+  eval_interval: 10
+monitor:
+  cache_root_dir: ""
+  project: "Trinity-RFT-gsm8k"
+  name: "async-qwen2.5-1.5B-gsm8k"