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feat: enforce monotonicity config option #1840

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enforce monotonicity
cmunley1 Jan 29, 2026
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cmunley1 Jan 29, 2026
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4 changes: 4 additions & 0 deletions nemo_rl/models/generation/vllm/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,6 +39,10 @@ class VllmSpecificArgs(TypedDict):
# Miscellaneous top level vLLM HTTP server arguments.
# A filepath that can be imported to register a vLLM tool parser
tool_parser_plugin: NotRequired[str]
# Ensures message history over multiple turns remains constant. Useful for on-policy training, but sometimes
# we may want to drop previous reasoning (like Qwen3), agent context management,
# sliding window, or drop past environment state observations, etc
enforce_monotonicity: NotRequired[bool]
Comment on lines 42 to 45
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⚠️ Potential issue | 🟡 Minor

🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
# Check for enforce_monotonicity in exemplar YAMLs
rg -n 'enforce_monotonicity' examples/ -g '*.yaml' -g '*.yml'

Repository: NVIDIA-NeMo/RL

Length of output: 40

🏁 Script executed:

#!/bin/bash
# Find exemplar YAML files in the repo to understand structure
find examples/configs -type f \( -name "*.yaml" -o -name "*.yml" \) 2>/dev/null | head -20

Repository: NVIDIA-NeMo/RL

Length of output: 856

🏁 Script executed:

#!/bin/bash
# Check the config file to see how other NotRequired config keys are documented
cat -n nemo_rl/models/generation/vllm/config.py | head -80

Repository: NVIDIA-NeMo/RL

Length of output: 3068

Add enforce_monotonicity to exemplar YAMLs and document valid values and recommended default.

The new config key is missing from exemplar YAML files under examples/configs/ and its documentation is incomplete. Per coding guidelines, new TypedDict config keys must document purpose, valid values/types, and recommended default, and this default must be reflected in exemplar YAMLs.

Update the field comment to specify valid values (True/False) and recommended default, then add the key to relevant exemplar YAML files (e.g., grpo_math_*.yaml, dpo.yaml) with the recommended value.

🤖 Prompt for AI Agents 
In `@nemo_rl/models/generation/vllm/config.py` around lines 42 - 45, Update the
TypedDict field comment for enforce_monotonicity in
nemo_rl/models/generation/vllm/config.py to state that it's a boolean
(True/False), describe its purpose succinctly, and specify the recommended
default (e.g., False); then add the enforce_monotonicity: false entry to the
exemplar YAMLs in examples/configs (notably the grpo_math_*.yaml variants and
dpo.yaml) so the exemplar configs reflect the documented default. Ensure the
comment mentions valid values (True/False) and the recommended default, and that
the YAML keys use the same name enforce_monotonicity with the recommended value.



class VllmConfig(GenerationConfig):
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5 changes: 5 additions & 0 deletions nemo_rl/models/generation/vllm/vllm_worker_async.py
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Expand Up @@ -330,6 +330,8 @@ def _setup_vllm_openai_api_server(self, app: FastAPI) -> FastAPI:
openai_serving_models_kwargs["model_config"] = model_config
openai_serving_models = OpenAIServingModels(**openai_serving_models_kwargs)

enforce_monotonicity = self.cfg["vllm_cfg"].get("enforce_monotonicity", True)
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⚠️ Potential issue | 🟠 Major

Avoid code-side default; rely on YAML for enforce_monotonicity.

Using .get(..., True) sets a non-None default in code. Please set the default in YAML and read the value directly (or assert presence) here.

✅ Suggested change 
-        enforce_monotonicity = self.cfg["vllm_cfg"].get("enforce_monotonicity", True)
+        enforce_monotonicity = self.cfg["vllm_cfg"]["enforce_monotonicity"]

As per coding guidelines, "YAML is the single source of truth for configuration defaults. Do not set non-None defaults in code for configuration values".

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
enforce_monotonicity = self.cfg["vllm_cfg"].get("enforce_monotonicity", True)
enforce_monotonicity = self.cfg["vllm_cfg"]["enforce_monotonicity"]
🤖 Prompt for AI Agents 
In `@nemo_rl/models/generation/vllm/vllm_worker_async.py` at line 333, The line
that reads enforce_monotonicity =
self.cfg["vllm_cfg"].get("enforce_monotonicity", True) should not provide a
code-side default; instead read the value directly from the config and fail fast
if missing. Replace the .get call with direct indexing (e.g.,
self.cfg["vllm_cfg"]["enforce_monotonicity"]) or add an explicit assertion that
"enforce_monotonicity" exists in self.cfg["vllm_cfg"], and ensure the YAML
config defines the default there.


class NeMoRLOpenAIChatRequestMixin:
def model_post_init(self, context):
# NeMo-Gym specific processing. This is just how NeMo-Gym returns the extra token information.
Expand Down Expand Up @@ -384,6 +386,9 @@ async def _preprocess_chat(
add_special_tokens,
)

if not enforce_monotonicity:
return res

if request.required_prefix_token_ids is None:
return res

Expand Down
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