update qwen3 scripts to use yaml configs

examples/rl/grpo/gsm8k/configs/qwen3.yaml

@@ -0,0 +1,89 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+model_config:
+  model_name: "Qwen3-1.7B-base"
+  model_id: "Qwen/Qwen3-1.7B-base"
+  model_source: "huggingface"
+  use_flash_attention: true
+  flash_attention_block_size: 256
+  mesh:
+    shape: "(2,4)"
+    axis_names: "('fsdp','tp')"
+  rng_seed: 42
+
+actor_model_config:
+  lora_config:
+    rank: 64
+    alpha: 64.0
+    module_path: ".*q_proj|.*k_proj|.*v_proj|.*o_proj|.*gate_proj|.*down_proj|.*up_proj"
+  mesh:
+    shape: "(2,4)"
+    axis_names: "('fsdp','tp')"
+
+reference_model_config:
+  mesh: null
+  same_mesh_as: "actor"
+
+rollout_model_config:
+  mesh: null
+  same_mesh_as: "actor"
+
+tokenizer_config:
+  tokenizer_type: "huggingface"
+  add_bos: false
+
+dataset_name: "gsm8k"
+batch_size: 8
+num_test_batches: 100
+num_train_epochs: 1
+
+rl_training_config:
+  actor_optimizer_config:
+    opt_type: "adamw"
+    peak_value: 3e-6
+    schedule_type: "warmup_cosine_decay_schedule"
+    init_value: 0.0
+    end_value: 0.0
+    warmup_ratio: 0.1
+    b1: 0.9
+    b2: 0.99
+    weight_decay: 0.1
+    max_grad_norm: 0.1
+  eval_every_n_steps: 10
+  metrics_logging_options:
+    flush_every_n_steps: 20
+  checkpointing_options:
+    save_interval_steps: 500
+    max_to_keep: 4
+  profiler_options: {}
+
+rollout_config:
+  total_generation_steps: 768
+  max_prompt_length: 256
+  temperature: 0.9
+  top_p: 1.0
+  top_k: 50
+
+rollout_engine: "vanilla"
+offload_to_cpu: false
+
+grpo_config:
+  num_generations: 4
+  num_iterations: 1
+  beta: 0.08
+  epsilon: 0.2
+
+reward_functions:
+  - "tunix/cli/reward_fn/gsm8k.py"

examples/rl/grpo/gsm8k/configs/qwen3_disagg.yaml

@@ -0,0 +1,100 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+model_config:
+  rng_seed: 42
+  model_display: false
+  remat_config: 3
+
+actor_model_config:
+  mesh:
+    shape: "(8,1)"
+    axis_names: "('fsdp','tp')"
+
+rollout_model_config:
+  mesh:
+    shape: "(1,8)"
+    axis_names: "('fsdp','tp')"
+
+reference_model_config:
+  mesh: null
+  same_mesh_as: "actor"
+
+data_source: "huggingface"
+dataset_name: "openai/gsm8k:main"
+prompt_key: "question"
+
+training_mode: "agentic_grpo"
+num_test_batches: 100
+reward_functions:
+  - "tunix/cli/reward_fn/gsm8k.py"
+verl_compatible: false
+
+rollout_engine: "vllm"
+offload_to_cpu: false
+
+rollout_config:
+  max_prompt_length: 256
+  total_generation_steps: 768
+  max_tokens_to_generate: 768
+  temperature: 0.9
+  top_p: 1.0
+  top_k: 50
+  return_logprobs: true
+
+vllm_config:
+  hbm_utilization: 0.4
+  tpu_backend_type: "jax"
+  server_mode: true
+  async_scheduling: true
+  kwargs:
+    kv_cache_metrics: true
+    disable_log_stats: false
+    enable_prefix_caching: true
+
+chat_parser_config:
+  type: "qwen"
+
+tokenizer_config:
+  tokenizer_type: "huggingface"
+  add_bos: false
+  add_eos: false
+
+agentic_grpo_config:
+  num_iterations: 1
+  beta: 0.08
+  epsilon: 0.2
+  system_prompt: "You are given a grade school math problem. Think step by step and respond using <reasoning>...</reasoning> followed by <answer>...</answer> with only the final numeric answer inside <answer>."
+  max_concurrency: 128
+  max_response_length: 768
+  max_turns: 1
+
+rl_training_config:
+  actor_optimizer_config:
+    opt_type: "adamw"
+    learning_rate: 3e-6
+    schedule_type: "warmup_cosine_decay_schedule"
+    init_value: 0.0
+    peak_value: 3e-6
+    end_value: 0.0
+    b1: 0.9
+    b2: 0.99
+    weight_decay: 0.1
+    max_grad_norm: 0.1
+  eval_every_n_steps: 10
+  checkpointing_options:
+    save_interval_steps: 250
+    max_to_keep: 4
+  metrics_logging_options:
+    flush_every_n_steps: 20

examples/rl/grpo/gsm8k/run_qwen3.sh

@@ -31,60 +31,16 @@ echo "  Train Fraction: $train_fraction"
 echo "  Checkpoint Directory: $checkpoint_dir"
 
 python3 -m tunix.cli.grpo_main \
-  base_config.yaml \
-  model_config.model_name=${model_name} \
-  model_config.model_id=Qwen/${model_name} \
-  model_config.model_source=huggingface \
-  model_config.use_flash_attention=true \
-  model_config.flash_attention_block_size=256 \
+  tunix/cli/base_config.yaml \
+  override_config_file=examples/rl/grpo/gsm8k/configs/qwen3.yaml \
+  model_config.model_name="${model_name}" \
+  model_config.model_id="Qwen/${model_name}" \
   model_config.intermediate_ckpt_dir="/tmp/intermediate_ckpt/${model_name}" \
   model_config.model_download_path="/tmp/models/${model_name}" \
-  model_config.mesh.shape="(2,4)" \
-  model_config.mesh.axis_names="('fsdp','tp')" \
-  model_config.rng_seed=42 \
-  actor_model_config.lora_config.rank=64 \
-  actor_model_config.lora_config.alpha=64.0 \
-  actor_model_config.lora_config.module_path=".*q_proj|.*k_proj|.*v_proj|.*o_proj|.*gate_proj|.*down_proj|.*up_proj" \
-  actor_model_config.mesh.shape="(2,4)" \
-  actor_model_config.mesh.axis_names="('fsdp','tp')" \
-  reference_model_config.mesh=null \
-  reference_model_config.same_mesh_as="actor" \
-  rollout_model_config.mesh=null \
-  rollout_model_config.same_mesh_as="actor" \
-  tokenizer_config.tokenizer_path=Qwen/${model_name} \
-  tokenizer_config.tokenizer_type=huggingface \
-  tokenizer_config.add_bos=false \
-  dataset_name="gsm8k" \
+  tokenizer_config.tokenizer_path="Qwen/${model_name}" \
   batch_size=$batch_size \
-  num_test_batches=100 \
   num_train_epochs=$num_train_epochs \
   train_fraction=$train_fraction \
-  rl_training_config.actor_optimizer_config.opt_type="adamw" \
-  rl_training_config.actor_optimizer_config.peak_value=3e-6 \
-  rl_training_config.actor_optimizer_config.schedule_type="warmup_cosine_decay_schedule" \
-  rl_training_config.actor_optimizer_config.init_value=0.0 \
-  rl_training_config.actor_optimizer_config.end_value=0.0 \
   rl_training_config.actor_optimizer_config.warmup_ratio=$warmup_ratio \
-  rl_training_config.actor_optimizer_config.b1=0.9 \
-  rl_training_config.actor_optimizer_config.b2=0.99 \
-  rl_training_config.actor_optimizer_config.weight_decay=0.1 \
-  rl_training_config.actor_optimizer_config.max_grad_norm=0.1 \
-  rl_training_config.eval_every_n_steps=10 \
   rl_training_config.metrics_logging_options.log_dir="/tmp/tensorboard/${model_name}" \
-  rl_training_config.metrics_logging_options.flush_every_n_steps=20 \
-  rl_training_config.checkpoint_root_directory="$checkpoint_dir" \
-  rl_training_config.checkpointing_options.save_interval_steps=500 \
-  rl_training_config.checkpointing_options.max_to_keep=4 \
-  rl_training_config.profiler_options={} \
-  rollout_config.total_generation_steps=768 \
-  rollout_config.max_prompt_length=256 \
-  rollout_config.temperature=0.9 \
-  rollout_config.top_p=1.0 \
-  rollout_config.top_k=50 \
-  rollout_engine="vanilla" \
-  offload_to_cpu=false \
-  grpo_config.num_generations=4 \
-  grpo_config.num_iterations=1 \
-  grpo_config.beta=0.08 \
-  grpo_config.epsilon=0.2 \
-  reward_functions="['tunix/cli/reward_fn/gsm8k.py']"
+  rl_training_config.checkpoint_root_directory="$checkpoint_dir"

examples/rl/grpo/gsm8k/run_qwen3_8b_disagg.sh

@@ -72,103 +72,28 @@ vllm_max_num_seqs=$(awk "BEGIN {
 
 python -m tunix.cli.grpo_main \
   tunix/cli/base_agentic_config.yaml \
-  \
-  `# -- Model ------------------------------------------------------------` \
+  override_config_file=examples/rl/grpo/gsm8k/configs/qwen3_disagg.yaml \
   model_config.model_name="$model_name" \
   model_config.model_id="$model_id" \
   model_config.model_source="huggingface" \
   model_config.model_download_path="/tmp/models/${model_name}" \
-  model_config.rng_seed=42 \
-  model_config.model_display=false \
-  model_config.remat_config=3 \
+  tokenizer_config.tokenizer_path="$tokenizer_path" \
   actor_model_config.mesh.shape="$train_mesh" \
-  actor_model_config.mesh.axis_names="('fsdp','tp')" \
-  reference_model_config.mesh=null \
-  reference_model_config.same_mesh_as="actor" \
   rollout_model_config.mesh.shape="$rollout_mesh" \
-  rollout_model_config.mesh.axis_names="('fsdp','tp')" \
-  \
-  `# -- Data -------------------------------------------------------------` \
-  data_source="huggingface" \
-  dataset_name="openai/gsm8k:main" \
-  prompt_key="question" \
-  \
-  `# -- Training loop ----------------------------------------------------` \
-  training_mode="agentic_grpo" \
   batch_size="$batch_size" \
   num_batches="$num_batches" \
-  num_test_batches=100 \
   num_train_epochs="$num_train_epochs" \
   train_fraction="$train_fraction" \
-  reward_functions=["tunix/cli/reward_fn/gsm8k.py"] \
-  verl_compatible=false \
-  \
-  `# -- Rollout engine (vanilla | vllm | sglang_jax) ---------------------` \
-  rollout_engine="vllm" \
-  offload_to_cpu=false \
-  \
-  `# -- Rollout config ---------------------------------------------------` \
-  rollout_config.max_prompt_length=256 \
-  rollout_config.total_generation_steps=768 \
-  rollout_config.max_tokens_to_generate=768 \
-  rollout_config.temperature=0.9 \
-  rollout_config.top_p=1.0 \
-  rollout_config.top_k=50 \
-  rollout_config.return_logprobs=true \
-  \
-  `# -- vLLM (used when rollout_engine=vllm) -----------------------------` \
-  vllm_config.hbm_utilization=0.4 \
-  vllm_config.tpu_backend_type="jax" \
-  vllm_config.server_mode=true \
-  vllm_config.async_scheduling=true \
   vllm_config.max_num_seqs="$vllm_max_num_seqs" \
-  vllm_config.kwargs.kv_cache_metrics=true \
-  vllm_config.kwargs.disable_log_stats=false \
-  vllm_config.kwargs.enable_prefix_caching=true \
-  \
-  `# -- Tokenizer / chat parsing ----------------------------------------` \
-  chat_parser_config.type="qwen" \
-  tokenizer_config.tokenizer_type="huggingface" \
-  tokenizer_config.tokenizer_path="$tokenizer_path" \
-  tokenizer_config.add_bos=false \
-  tokenizer_config.add_eos=false \
-  \
-  `# -- GRPO algorithm ---------------------------------------------------` \
   agentic_grpo_config.num_generations="$num_generations" \
-  agentic_grpo_config.num_iterations=1 \
-  agentic_grpo_config.beta=0.08 \
-  agentic_grpo_config.epsilon=0.2 \
-  agentic_grpo_config.system_prompt="You are given a grade school math problem. Think step by step and respond using <reasoning>...</reasoning> followed by <answer>...</answer> with only the final numeric answer inside <answer>." \
-  agentic_grpo_config.max_concurrency=128 \
-  agentic_grpo_config.max_response_length=768 \
-  agentic_grpo_config.max_turns=1 \
-  \
-  `# -- Optimizer --------------------------------------------------------` \
-  rl_training_config.actor_optimizer_config.opt_type="adamw" \
-  rl_training_config.actor_optimizer_config.learning_rate=3e-6 \
-  rl_training_config.actor_optimizer_config.schedule_type="warmup_cosine_decay_schedule" \
-  rl_training_config.actor_optimizer_config.init_value=0.0 \
-  rl_training_config.actor_optimizer_config.peak_value=3e-6 \
-  rl_training_config.actor_optimizer_config.end_value=0.0 \
   rl_training_config.actor_optimizer_config.warmup_ratio="$warmup_ratio" \
   rl_training_config.actor_optimizer_config.warmup_steps="$warmup_steps" \
   rl_training_config.actor_optimizer_config.decay_steps="$max_steps" \
-  rl_training_config.actor_optimizer_config.b1=0.9 \
-  rl_training_config.actor_optimizer_config.b2=0.99 \
-  rl_training_config.actor_optimizer_config.weight_decay=0.1 \
-  rl_training_config.actor_optimizer_config.max_grad_norm=0.1 \
-  \
-  `# -- RL training ------------------------------------------------------` \
-  rl_training_config.eval_every_n_steps=10 \
   rl_training_config.max_steps="$max_steps" \
   rl_training_config.mini_batch_size="$mini_batch_size" \
   rl_training_config.train_micro_batch_size="$train_micro_batch_size" \
   rl_training_config.rollout_micro_batch_size="$rollout_micro_batch_size" \
   rl_training_config.compute_logps_micro_batch_size="$compute_logps_micro_batch_size" \
   rl_training_config.checkpoint_root_directory="$checkpoint_dir" \
-  rl_training_config.checkpointing_options.save_interval_steps=250 \
-  rl_training_config.checkpointing_options.max_to_keep=4 \
   rl_training_config.metrics_logging_options.log_dir="/tmp/tensorboard/gsm8k_qwen3_8b" \
-  rl_training_config.metrics_logging_options.flush_every_n_steps=20 \
-  \
   "$@"