From a4a45192c7f08588026ef89691df3c30c7bc08aa Mon Sep 17 00:00:00 2001 From: Zhaocheng Zhu Date: Tue, 29 Jul 2025 14:16:30 -0700 Subject: [PATCH 01/23] feat: code execution & tool use (#322) Signed-off-by: KiddoZhu Signed-off-by: Terry Kong Co-authored-by: Terry Kong Signed-off-by: tpoisonooo --- .gitignore | 2 + .../ray_actor_environment_registry.py | 2 + nemo_rl/environments/code_environment.py | 259 ++++++++++++++++++ nemo_rl/environments/tools/retriever.py | 206 ++++++++++++++ nemo_rl/experience/rollouts.py | 2 + .../environments/test_code_environment.py | 220 +++++++++++++++ tests/unit/environments/test_retriever.py | 179 ++++++++++++ 7 files changed, 870 insertions(+) create mode 100644 nemo_rl/environments/code_environment.py create mode 100644 nemo_rl/environments/tools/retriever.py create mode 100644 tests/unit/environments/test_code_environment.py create mode 100644 tests/unit/environments/test_retriever.py diff --git a/.gitignore b/.gitignore index 954db7041d..55a992fece 100644 --- a/.gitignore +++ b/.gitignore @@ -22,6 +22,8 @@ ckpts/ # Test coverage.json .coverage* +unit_results.json +unit_results/ test_assets/ # Cache diff --git a/nemo_rl/distributed/ray_actor_environment_registry.py b/nemo_rl/distributed/ray_actor_environment_registry.py index 277619bb92..e300aec54b 100644 --- a/nemo_rl/distributed/ray_actor_environment_registry.py +++ b/nemo_rl/distributed/ray_actor_environment_registry.py @@ -21,7 +21,9 @@ "nemo_rl.models.policy.dtensor_policy_worker.DTensorPolicyWorker": PY_EXECUTABLES.VLLM, "nemo_rl.models.policy.megatron_policy_worker.MegatronPolicyWorker": PY_EXECUTABLES.MCORE, "nemo_rl.environments.math_environment.MathEnvironment": PY_EXECUTABLES.SYSTEM, + "nemo_rl.environments.code_environment.CodeEnvironment": PY_EXECUTABLES.SYSTEM, "nemo_rl.environments.games.sliding_puzzle.SlidingPuzzleEnv": PY_EXECUTABLES.SYSTEM, + "nemo_rl.environments.tools.retriever.RAGEnvironment": PY_EXECUTABLES.SYSTEM, } diff --git a/nemo_rl/environments/code_environment.py b/nemo_rl/environments/code_environment.py new file mode 100644 index 0000000000..029b9cd1c0 --- /dev/null +++ b/nemo_rl/environments/code_environment.py @@ -0,0 +1,259 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# 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 +# +# http://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. +import ast +import builtins +import os +import re +from collections.abc import Mapping, Sequence +from contextlib import contextmanager +from copy import copy +from io import IOBase +from pprint import pformat +from types import ModuleType +from typing import Any, Dict, List, Optional, Tuple, TypedDict + +import ray +import torch + +from nemo_rl.data.interfaces import LLMMessageLogType +from nemo_rl.distributed.batched_data_dict import BatchedDataDict +from nemo_rl.distributed.virtual_cluster import PY_EXECUTABLES +from nemo_rl.environments.interfaces import EnvironmentInterface, EnvironmentReturn +from nemo_rl.environments.utils import chunk_list_to_workers + + +class CodeEnvConfig(TypedDict): + num_workers: int + # whether to terminate the execution after expression evaluation + # if you want to execute multiple rounds of code, set this to False + # and wrap CodeEnvironment in another environment that terminates the generation + terminate_on_evaluation: bool + + +class CodeEnvMetadata(TypedDict): + context: Dict[str, Any] # Hold functions and variables defined in the code + working_dir: str # Working directory for file operations + + +@ray.remote # pragma: no cover +class CodeExecutionWorker: + """Helper class to process individual code execution steps.""" + + def __init__(self): + # Create sandbox with safe builtins + builtin_dict = {k: getattr(builtins, k) for k in dir(builtins)} + builtin_dict["open"] = self.safe_open + builtin_dict["__import__"] = self.safe_import + self.sandbox = {"__builtins__": builtin_dict} + + def sanitize(self, obj: Any) -> Any: + # TODO: better handling of unpicklable objects: custom __getstate__ and __setstate__ + # recursively remove all file objects as they are not picklable by ray + if isinstance(obj, (IOBase, ModuleType)): + # replace unpickable objects with a string representation + return repr(obj) + if isinstance(obj, Mapping): + return obj.__class__( + {self.sanitize(k): self.sanitize(v) for k, v in obj.items()} + ) + if isinstance(obj, Sequence) and not isinstance(obj, str): + return obj.__class__(self.sanitize(v) for v in obj) + if hasattr(obj, "__dict__"): + new_obj = copy(obj) + new_obj.__dict__ = { + self.sanitize(k): self.sanitize(v) for k, v in obj.__dict__.items() + } + return new_obj + return obj + + def format_result( + self, result: Any, code: Optional[str] = None, lookahead: Optional[str] = None + ) -> str: + if result is None: + # no return value + return "" + result = pformat(result) + multiline = (code and "\n" in code) or "\n" in result + if multiline: + # multi-line format + result = f"\n\n\n{result}\n" + else: + # inline format + result = f"{result}" + if lookahead: + if result.startswith(lookahead): + # The generation may look like "\n" if ">\n" is a single token. + # We trim \n from the result if the model has already generated it. + result = result[len(lookahead) :] + return result + + def execute(self, message_batch: str, metadata_batch: List[CodeEnvMetadata]) -> str: + """Execute code in a sandboxed environment.""" + results = [] + terminateds = [] + + for message, metadata in zip(message_batch, metadata_batch): + match = re.search(r"(.*)(.*)", message, re.DOTALL) + if not match: + results.append("") + terminateds.append(False) + continue + + code, lookahead = match.groups() + tree = ast.parse(code) + + if tree.body and isinstance(tree.body[-1], ast.Expr): + # Interactive mode + exec_code = ast.unparse(tree.body[:-1]) + eval_code = ast.unparse(tree.body[-1]) + else: + # Silent mode + exec_code = code + eval_code = None + + result = None + terminated = False + with self.chdir(metadata["working_dir"]): + try: + # isolate the code in a sandbox + # capture local variables in metadata["context"] + exec(exec_code, self.sandbox, metadata["context"]) + if eval_code: + result = eval(eval_code, self.sandbox, metadata["context"]) + terminated = True + except Exception as err: + result = err + + result = self.format_result(result, code, lookahead) + results.append(result) + terminateds.append(terminated) + + observations = [ + {"role": "environment", "content": result} for result in results + ] + metadata_batch = self.sanitize(metadata_batch) + + return observations, terminateds, metadata_batch + + @contextmanager + def chdir(self, dir: str): + """Change to temporary directory for file operations.""" + current_dir = os.getcwd() + os.chdir(dir) + try: + yield + finally: + os.chdir(current_dir) + + def safe_open(self, file: str, *args, **kwargs): + """Safe version of open() that only allows access to temporary directory.""" + real_file = os.path.realpath(file) + working_dir = os.path.realpath(os.getcwd()) + if os.path.commonpath([real_file, working_dir]) != working_dir: + raise PermissionError( + "Access beyond the temporary working directory is blocked" + ) + return open(file, *args, **kwargs) + + def safe_import(self, name: str, *args, **kwargs): + """Safe version of import that blocks risky modules.""" + risky_modules = { + "os", + "shutil", # erase filesystem + "sys", + "signal", # exit the current program + "socket", # network communication + "subprocess", + "threading", + "multiprocessing", # spawn threads or processes + "builtins", + "importlib", # bypass current blockers + } + if name in risky_modules: + raise PermissionError("Importing system and network modules is blocked") + return builtins.__import__(name, *args, **kwargs) + + +@ray.remote # pragma: no cover +class CodeEnvironment(EnvironmentInterface): + """Code execution environment that maintains state between steps.""" + + def __init__(self, cfg: CodeEnvConfig): + self.cfg = cfg + self.num_workers = cfg["num_workers"] + self.terminate_on_evaluation = cfg["terminate_on_evaluation"] + self.workers = [ + CodeExecutionWorker.options( + runtime_env={"py_executable": PY_EXECUTABLES.SYSTEM} + ).remote() + for _ in range(self.num_workers) + ] + + def step( + self, + message_log_batch: List[LLMMessageLogType], + metadata_batch: List[CodeEnvMetadata], + ) -> EnvironmentReturn: + """Process a batch of code execution steps.""" + message_batch = [ml[-1]["content"] for ml in message_log_batch] + chunked_message_batch = chunk_list_to_workers(message_batch, self.num_workers) + chunked_metadata_batch = chunk_list_to_workers(metadata_batch, self.num_workers) + + # Process each chunk in parallel + futures = [ + self.workers[i].execute.remote(message_chunk, metadata_chunk) + for i, (message_chunk, metadata_chunk) in enumerate( + zip(chunked_message_batch, chunked_metadata_batch) + ) + ] + + results = ray.get(futures) + + # Unpack results + observations = [] + terminateds = [] + new_metadata_batch = [] + + for obs, term, meta in results: + observations += obs + terminateds += term + new_metadata_batch += meta + + if self.terminate_on_evaluation: + terminated_tensor = torch.tensor(terminateds, dtype=torch.bool) + else: + terminated_tensor = torch.zeros(len(terminateds), dtype=torch.bool) + rewards_tensor = torch.zeros_like(terminated_tensor, dtype=torch.float32) + + next_stop_strings = [[""]] * len(message_log_batch) + + return EnvironmentReturn( + observations=observations, + metadata=new_metadata_batch, + next_stop_strings=next_stop_strings, + rewards=rewards_tensor, + terminateds=terminated_tensor, + ) + + def shutdown(self): + # shutdown all workers + for worker in self.workers: + ray.kill(worker) + + def global_post_process_and_metrics( + self, batch: BatchedDataDict + ) -> Tuple[BatchedDataDict, dict]: + """Compute metrics for the batch.""" + # No specific metrics for code execution + return batch, {} diff --git a/nemo_rl/environments/tools/retriever.py b/nemo_rl/environments/tools/retriever.py new file mode 100644 index 0000000000..8f408fc92b --- /dev/null +++ b/nemo_rl/environments/tools/retriever.py @@ -0,0 +1,206 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# 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 +# +# http://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. +import math +import re +from collections import Counter +from typing import Any, Dict, List, TypedDict + +import ray +import torch +from datasets import load_dataset +from tqdm import tqdm +from transformers import AutoTokenizer + +from nemo_rl.data.interfaces import LLMMessageLogType +from nemo_rl.distributed.batched_data_dict import BatchedDataDict +from nemo_rl.environments.interfaces import EnvironmentInterface, EnvironmentReturn + + +class RAGEnvConfig(TypedDict): + dataset_name: str # Name of the dataset to load + dataset_split: str # Split of the dataset to use + text_column: str # Column name containing the text to retrieve + num_results: int # Number of documents to retrieve + k1: float # BM25 parameter + b: float # BM25 parameter + device: str # Device to compute BM25 + + +class BM25Retriever: + """Sparse BM25 retriever. + + Args: + documents: list of documents to retrieve from + num_result: retrieve top-k documents + k1: parameter of BM25. Values in [1.2, 2.0] are recommended. + b: parameter of BM25. 0.75 is recommended. + device: device to compute BM25 + """ + + def __init__( + self, + documents: List[str] = None, + num_result: int = 10, + k1: float = 1.5, + b: float = 0.75, + device: str = "cpu", + ): + if documents is None: + dataset = load_dataset("wikimedia/wikipedia", "20231101.en") + self.documents = [sample["text"] for sample in dataset["train"]] + else: + self.documents = documents + self.tokenizer = AutoTokenizer.from_pretrained( + "bert-base-uncased", use_fast=True + ) + self.num_result = num_result + self.k1 = k1 + self.b = b + self.device = device + self.corpus_size = len(self.documents) + self.vocab_size = self.tokenizer.vocab_size + + self.build_index() + + def build_index(self): + doc_ids = [] + token_ids = [] + tfs = [] + lengths = [] + + for i, document in enumerate( + tqdm(self.documents, "Build index for BM25Retriever") + ): + input_ids = self.tokenizer.encode(document, add_special_tokens=False) + token2cnt = Counter(input_ids) + token_ids += token2cnt.keys() + tfs += token2cnt.values() + doc_ids += [i] * len(token2cnt) + lengths.append(len(input_ids)) + + avg_dl = sum(lengths) / self.corpus_size + for i, doc_id in enumerate(doc_ids): + tfs[i] = ( + tfs[i] + * (self.k1 + 1) + / (tfs[i] + self.k1 * (1 - self.b + self.b * lengths[doc_id] / avg_dl)) + ) + + indices = torch.tensor([doc_ids, token_ids], device=self.device) + values = torch.tensor(tfs, device=self.device) + self.doc_tfs = torch.sparse_coo_tensor( + indices, values, (self.corpus_size, self.vocab_size) + ) + + idfs = [0] * self.vocab_size + token2df = Counter(token_ids) + for token_id, df in token2df.items(): + idfs[token_id] = math.log((self.corpus_size - df + 0.5) / (df + 0.5) + 1) + self.idfs = idfs + + def __call__(self, query: str) -> List[str]: + input_ids = self.tokenizer.encode(query, add_special_tokens=False) + token2cnt = Counter(input_ids) + token_ids = [] + query_idfs = [] + for token_id, query_tf in token2cnt.items(): + token_ids.append(token_id) + query_idfs.append(query_tf * self.idfs[token_id]) + + indices = torch.tensor([token_ids, [0] * len(token_ids)], device=self.device) + values = torch.tensor(query_idfs, device=self.device) + query_idfs = torch.sparse_coo_tensor(indices, values, (self.vocab_size, 1)) + + scores = torch.sparse.mm(self.doc_tfs, query_idfs) + scores = scores.to_dense().squeeze(-1) + results = [] + for i in scores.topk(k=self.num_result).indices.tolist(): + results.append(self.documents[i]) + + return results + + +@ray.remote # pragma: no cover +class RAGEnvironment(EnvironmentInterface): + """RAG environment that uses BM25 for document retrieval.""" + + def __init__(self, cfg: RAGEnvConfig): + self.cfg = cfg + + # Load dataset + dataset = load_dataset(cfg["dataset_name"], split=cfg["dataset_split"]) + documents = [sample[cfg["text_column"]] for sample in dataset] + + # Initialize BM25 retriever + self.retriever = BM25Retriever( + documents=documents, + num_result=cfg["num_results"], + k1=cfg["k1"], + b=cfg["b"], + device=cfg["device"], + ) + + def format_result(self, retrieved_docs: List[str]) -> str: + result = "\n" + for i, doc in enumerate(retrieved_docs): + result += f"<{i + 1}>\n{doc}\n\n" + result += "\n" + return result + + def step( + self, + message_log_batch: List[LLMMessageLogType], + metadata_batch: List[Dict[str, Any]], + ) -> EnvironmentReturn: + """Process a batch of retrieval steps.""" + # Extract queries from the last message in each log + messages = [ml[-1]["content"] for ml in message_log_batch] + + # Retrieve documents for each query + results = [] + for message in messages: + match = re.search(r"(.*)", message, re.DOTALL) + if not match: + results.append( + {"role": "environment", "content": "No retrieval query found!"} + ) + continue + query = match.group(1) + retrieved_docs = self.retriever(query) + result = self.format_result(retrieved_docs) + results.append({"role": "environment", "content": result}) + + batch_size = len(message_log_batch) + rewards_tensor = torch.zeros(batch_size, dtype=torch.float32) + terminated_tensor = torch.ones(batch_size, dtype=torch.bool) + next_stop_strings = [[""]] * batch_size + + return EnvironmentReturn( + observations=results, + metadata=metadata_batch, + next_stop_strings=next_stop_strings, + rewards=rewards_tensor, + terminateds=terminated_tensor, + ) + + def shutdown(self): + """Clean up resources.""" + pass + + def global_post_process_and_metrics( + self, batch: BatchedDataDict + ) -> tuple[BatchedDataDict, dict]: + """Compute metrics for the batch.""" + # No specific metrics for RAG + return batch, {} diff --git a/nemo_rl/experience/rollouts.py b/nemo_rl/experience/rollouts.py index 62e7ee1122..a9cbc8cb70 100644 --- a/nemo_rl/experience/rollouts.py +++ b/nemo_rl/experience/rollouts.py @@ -410,6 +410,8 @@ def run_multi_turn_rollout( tokenized_obs = tokenizer( env_obs_content, return_tensors="pt", add_special_tokens=False ).input_ids[0] + # tokenizer returns torch.float32 when env_obs_content is empty + tokenized_obs = tokenized_obs.to(dtype=torch.int64) # check if new message overflows max_seq_len if ( diff --git a/tests/unit/environments/test_code_environment.py b/tests/unit/environments/test_code_environment.py new file mode 100644 index 0000000000..27ada6d9bf --- /dev/null +++ b/tests/unit/environments/test_code_environment.py @@ -0,0 +1,220 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# 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 +# +# http://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. + +from tempfile import TemporaryDirectory + +import pytest +import ray +from transformers import AutoTokenizer + +from nemo_rl.distributed.batched_data_dict import BatchedDataDict +from nemo_rl.distributed.virtual_cluster import RayVirtualCluster +from nemo_rl.environments.code_environment import ( + CodeEnvConfig, + CodeEnvironment, + CodeEnvMetadata, +) +from nemo_rl.experience.rollouts import run_multi_turn_rollout +from nemo_rl.models.generation import configure_generation_config +from nemo_rl.models.generation.vllm import VllmConfig, VllmGeneration + +MODEL_NAME = "meta-llama/Llama-3.2-1B" + +cfg: CodeEnvConfig = { + "num_workers": 2, + "terminate_on_evaluation": True, +} + +# Define basic vLLM test config +basic_vllm_test_config: VllmConfig = { + "backend": "vllm", + "model_name": MODEL_NAME, + "tokenizer_name": None, + "dtype": "bfloat16", + "max_new_tokens": 100, + "temperature": 1.0, + "top_p": 1.0, + "top_k": None, + "stop_token_ids": None, + "stop_strings": None, + "vllm_cfg": { + "async_engine": False, + "precision": "bfloat16", + "tensor_parallel_size": 1, + "pipeline_parallel_size": 1, + "max_model_len": 1024, + "disable_log_stats": True, + "disable_log_requests": True, + "gpu_memory_utilization": 0.6, + "enforce_eager": "False", + }, + "colocated": { + "enabled": True, + "resources": { + "gpus_per_node": None, + "num_nodes": None, + }, + }, +} + + +@pytest.fixture(scope="function") +def code_env(): + """Create a code environment for testing.""" + try: + env_actor = CodeEnvironment.remote(cfg) + yield env_actor + finally: + if env_actor: + ray.kill(env_actor) + + +@pytest.fixture(scope="function") +def tokenizer(): + """Loads the tokenizer for the tests.""" + print(f"Loading tokenizer: {MODEL_NAME}") + tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, trust_remote_code=True) + if tokenizer.pad_token is None: + tokenizer.pad_token = tokenizer.eos_token + print( + f"Tokenizer loaded. Pad token: {tokenizer.pad_token} (ID: {tokenizer.pad_token_id}), EOS token: {tokenizer.eos_token} (ID: {tokenizer.eos_token_id})" + ) + return tokenizer + + +@pytest.fixture(scope="function") +def cluster(): + """Create a virtual cluster for testing.""" + cluster_instance = None + cluster_name = f"test-code-cluster-{id(cluster_instance)}" + print(f"\nCreating virtual cluster '{cluster_name}'...") + try: + cluster_instance = RayVirtualCluster( + name=cluster_name, + bundle_ct_per_node_list=[1], + use_gpus=True, + num_gpus_per_node=1, + max_colocated_worker_groups=2, + ) + yield cluster_instance + finally: + print(f"\nCleaning up cluster '{cluster_name}'...") + if cluster_instance: + cluster_instance.shutdown() + + +def test_untrusted_code(code_env): + """Test whether the code environment can block untrusted code.""" + codes = [ + "with open('allowed_file.txt', 'w') as fout:\n" + " fout.write('some content')\n" + "with open('allowed_file.txt') as fin:\n" + " content = fin.read()\n" + "content", + "with open('/etc/passwd', 'r') as fin:\n fin.read()", + "import math\nround(math.sqrt(8))", + "import os", + ] + results = [ + "\n\n\n'some content'\n", + "\n\n\nPermissionError('Access beyond the temporary working directory is blocked')\n", + "\n\n\n3\n", + "PermissionError('Importing system and network modules is blocked')", + ] + + message_log_batch = [ + [{"role": "user", "content": f"{code}"}] for code in codes + ] + temp_dirs = [TemporaryDirectory() for _ in codes] + metadata_batch = [ + CodeEnvMetadata( + context={}, + working_dir=temp_dir.name, + ) + for temp_dir in temp_dirs + ] + + # Execute the code + output = ray.get(code_env.step.remote(message_log_batch, metadata_batch)) + responses = [obs["content"] for obs in output.observations] + + assert responses == results, f"Got wrong output {responses}" + + +@pytest.mark.hf_gated +def test_vllm_execute_code(cluster, tokenizer, code_env): + """Test that vLLM can call the code executor.""" + # Prepare test data + codes = [ + "x = 3; y = 4\nThis is some regular text.\nx + y\n", + "\ndef f(x):\n return x * x\n\nf(2)\n\n", + ] + results = ["7", "\n\n4\n"] + + # Create message logs + message_logs = [] + metadata_batch = [] + temp_dirs = [] + for code in codes: + # Tokenize the message content + prompt = code * 4 + token_ids = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)[ + "input_ids" + ][0] + temp_dir = TemporaryDirectory() + message_logs.append( + [{"role": "user", "content": prompt, "token_ids": token_ids}] + ) + metadata_batch.append(CodeEnvMetadata(context={}, working_dir=temp_dir.name)) + temp_dirs.append(temp_dir) + + # Create initial batch + initial_batch = BatchedDataDict( + { + "message_log": message_logs, + "extra_env_info": metadata_batch, + "task_name": ["code_execution"] * len(codes), + "stop_strings": [[""]] * len(codes), + } + ) + + # Create vLLM generation + vllm_config = basic_vllm_test_config.copy() + vllm_config = configure_generation_config(vllm_config, tokenizer, is_eval=True) + vllm_generation = VllmGeneration(cluster, vllm_config) + + # Create code environment + task_to_env = {"code_execution": code_env} + + # Run rollout + vllm_generation.prepare_for_generation() + final_batch, _ = run_multi_turn_rollout( + policy_generation=vllm_generation, + input_batch=initial_batch, + tokenizer=tokenizer, + task_to_env=task_to_env, + max_seq_len=256, + max_rollout_turns=2, + greedy=True, + ) + vllm_generation.finish_generation() + + # Check results + for i, msg_log in enumerate(final_batch["message_log"]): + # Get the last message which should contain the result + last_msg = msg_log[-1] + assert last_msg["role"] == "environment" + assert last_msg["content"] == results[i], ( + f"Expected {results[i]}, got {last_msg['content']}" + ) diff --git a/tests/unit/environments/test_retriever.py b/tests/unit/environments/test_retriever.py new file mode 100644 index 0000000000..824c09b041 --- /dev/null +++ b/tests/unit/environments/test_retriever.py @@ -0,0 +1,179 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# 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 +# +# http://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. + +import pytest +import ray +from transformers import AutoTokenizer + +from nemo_rl.distributed.batched_data_dict import BatchedDataDict +from nemo_rl.distributed.virtual_cluster import RayVirtualCluster +from nemo_rl.environments.tools.retriever import RAGEnvConfig, RAGEnvironment +from nemo_rl.experience.rollouts import run_multi_turn_rollout +from nemo_rl.models.generation import configure_generation_config +from nemo_rl.models.generation.vllm import VllmConfig, VllmGeneration + +MODEL_NAME = "meta-llama/Llama-3.2-1B" + +cfg: RAGEnvConfig = { + "dataset_name": "rahular/simple-wikipedia", + "dataset_split": "train", + "text_column": "text", + "num_results": 1, + "k1": 1.5, + "b": 0.75, + "device": "cpu", +} + +# Define basic vLLM test config +basic_vllm_test_config: VllmConfig = { + "backend": "vllm", + "model_name": MODEL_NAME, + "tokenizer_name": None, + "dtype": "bfloat16", + "max_new_tokens": 100, + "temperature": 1.0, + "top_p": 1.0, + "top_k": None, + "stop_token_ids": None, + "stop_strings": None, + "vllm_cfg": { + "async_engine": False, + "precision": "bfloat16", + "tensor_parallel_size": 1, + "pipeline_parallel_size": 1, + "max_model_len": 1024, + "disable_log_stats": True, + "disable_log_requests": True, + "gpu_memory_utilization": 0.6, + "enforce_eager": "False", + }, + "colocated": { + "enabled": True, + "resources": { + "gpus_per_node": None, + "num_nodes": None, + }, + }, +} + + +@pytest.fixture(scope="function") +def rag_env(): + """Create a RAG environment for testing.""" + try: + env_actor = RAGEnvironment.remote(cfg) + yield env_actor + finally: + if env_actor: + ray.kill(env_actor) + + +@pytest.fixture(scope="function") +def tokenizer(): + """Loads the tokenizer for the tests.""" + print(f"Loading tokenizer: {MODEL_NAME}") + tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, trust_remote_code=True) + if tokenizer.pad_token is None: + tokenizer.pad_token = tokenizer.eos_token + print( + f"Tokenizer loaded. Pad token: {tokenizer.pad_token} (ID: {tokenizer.pad_token_id}), EOS token: {tokenizer.eos_token} (ID: {tokenizer.eos_token_id})" + ) + return tokenizer + + +@pytest.fixture(scope="function") +def cluster(): + """Create a virtual cluster for testing.""" + cluster_instance = None + cluster_name = f"test-rag-cluster-{id(cluster_instance)}" + print(f"\nCreating virtual cluster '{cluster_name}'...") + try: + cluster_instance = RayVirtualCluster( + name=cluster_name, + bundle_ct_per_node_list=[1], + use_gpus=True, + num_gpus_per_node=1, + max_colocated_worker_groups=2, + ) + yield cluster_instance + finally: + print(f"\nCleaning up cluster '{cluster_name}'...") + if cluster_instance: + cluster_instance.shutdown() + + +@pytest.mark.hf_gated +def test_vllm_retrieve(cluster, tokenizer, rag_env): + """Test that vLLM can use the RAG environment for document retrieval.""" + # Prepare test data + queries = [ + "Jen-Hsun Huang\n", + ] + expected_results = [ + "\n<1>\n" + "Nvidia was established in 1993 by Jen-Hsun Huang, Curtis Priem, and Chris Malachowsky. In 2000 Nvidia took intellectual possession of 3dfx, one of the biggest GPU producers in 1990s.\n" + "\n\n", + ] + + # Create message logs + message_logs = [] + for query in queries: + # Tokenize the message content + prompt = query * 4 + token_ids = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)[ + "input_ids" + ][0] + message_logs.append( + [{"role": "user", "content": prompt, "token_ids": token_ids}] + ) + + # Create initial batch + initial_batch = BatchedDataDict( + { + "message_log": message_logs, + "extra_env_info": [{}] * len(queries), # No metadata needed for RAG + "task_name": ["document_retrieval"] * len(queries), + "stop_strings": [[""]] * len(queries), + } + ) + + # Create vLLM generation + vllm_config = basic_vllm_test_config.copy() + vllm_config = configure_generation_config(vllm_config, tokenizer, is_eval=True) + vllm_generation = VllmGeneration(cluster, vllm_config) + + # Create RAG environment + task_to_env = {"document_retrieval": rag_env} + + # Run rollout + vllm_generation.prepare_for_generation() + final_batch, _ = run_multi_turn_rollout( + policy_generation=vllm_generation, + input_batch=initial_batch, + tokenizer=tokenizer, + task_to_env=task_to_env, + max_seq_len=256, + max_rollout_turns=1, + greedy=True, + ) + vllm_generation.finish_generation() + + # Check results + for i, msg_log in enumerate(final_batch["message_log"]): + # Get the last message which should contain the result + last_msg = msg_log[-1] + assert last_msg["role"] == "environment" + assert last_msg["content"] == expected_results[i], ( + f"Expected {expected_results[i]}, got {last_msg['content']}" + ) From d8bf5372fb39cf20739abb2e5f1c8f2606daed08 Mon Sep 17 00:00:00 2001 From: tpoisonooo Date: Fri, 18 Jul 2025 18:06:03 +0800 Subject: [PATCH 02/23] unittest(configs): add swanlab Signed-off-by: tpoisonooo --- docs/design-docs/logger.md | 26 ++- examples/configs/dpo.yaml | 1 + examples/configs/grpo-deepscaler-1.5b-8K.yaml | 1 + examples/configs/grpo_math_1B.yaml | 1 + examples/configs/grpo_math_1B_megatron.yaml | 1 + examples/configs/grpo_sliding_puzzle.yaml | 1 + ...llama3.1-8b-instruct-4n8g-fsdp2tp1.v2.yaml | 1 + ....1-8b-instruct-4n8g-fsdp2tp2-quick.v2.yaml | 1 + ...po-llama3.1-8b-instruct-4n8g-megatron.yaml | 1 + ...8b-instruct-4n8g-megatrontp2pp2-quick.yaml | 1 + ...llama3.2-1b-instruct-1n8g-fsdp2tp1.v2.yaml | 1 + .../llm/grpo-gemma3-1b-it-1n8g-fsdp2tp1.yaml | 1 + ...-27b-it-16n8g-fsdp2tp8sp-actckpt-long.yaml | 1 + ...3.1-8b-instruct-4n8g-fsdp2tp1-long.v3.yaml | 1 + ...llama3.2-1b-instruct-1n8g-fsdp2tp1.v3.yaml | 1 + ...-32b-32n8g-fsdp2tp8sp-actckpt-long.v3.yaml | 1 + ...en2.5-32b-32n8g-fsdp2tp8sp-actckpt.v3.yaml | 1 + ...wen2.5-7b-instruct-4n8g-fsdp2tp4sp.v3.yaml | 1 + ...5-math-1.5b-instruct-1n8g-fsdp2tp1.v3.yaml | 1 + ...3.1-8b-instruct-1n8g-fsdp2tp1-long.v2.yaml | 1 + ...ama3.1-8b-instruct-1n8g-fsdp2tp2sp.v2.yaml | 1 + ...ft-llama3.1-8b-instruct-1n8g-megatron.yaml | 1 + .../llm/sft-llama3.2-1b-1n8g-fsdp2tp1.v2.yaml | 1 + ...wen2.5-32b-4n8g-fsdp2tp8sp-actckpt.v2.yaml | 1 + examples/configs/sft.yaml | 1 + examples/configs/sft_openmathinstruct2.yaml | 1 + nemo_rl/utils/logger.py | 85 ++++++++ tests/unit/utils/test_logger.py | 192 +++++++++++++++++- 28 files changed, 318 insertions(+), 10 deletions(-) diff --git a/docs/design-docs/logger.md b/docs/design-docs/logger.md index 1c45529540..86f2db6258 100644 --- a/docs/design-docs/logger.md +++ b/docs/design-docs/logger.md @@ -1,6 +1,6 @@ # Logger -The logger is designed to track key training metrics (including distributed metrics with reductions and timing), as well as providing integration with logging backends like WandB, Tensorboard, and MLflow. +The logger is designed to track key training metrics (including distributed metrics with reductions and timing), as well as providing integration with logging backends like WandB, Tensorboard, MLflow and Swanlab. ## Requirements @@ -10,12 +10,13 @@ The logger is designed to track key training metrics (including distributed metr * WandB * Tensorboard * MLflow + * Swanlab ## Overall Design Since there is a single controller, the single process running the main training loop will gather the metrics and do the logging. -To handle multiple logger backends, we will have a {py:class}`LoggerInterface ` interface that the {py:class}`TensorboardLogger `, {py:class}`WandbLogger `, and {py:class}`MLflowLogger ` will implement: +To handle multiple logger backends, we will have a {py:class}`LoggerInterface ` interface that the {py:class}`TensorboardLogger `, {py:class}`WandbLogger `, {py:class}`MLflowLogger ` and {py:class}`SwanlabLogger ` will implement: ```python class LoggerInterface(ABC): @@ -35,7 +36,7 @@ class LoggerInterface(ABC): A {py:class}`Logger ` wrapper class will also implement {py:class}`LoggerInterface ` and maintain a list of loggers to which it delegates writing logs. This will be the main class the user uses in the training loop. Usage example: ```python -# Initialize logger with wandb, tensorboard, and mlflow enabled +# Initialize logger with wandb, tensorboard, mlflow and swanlab enabled logging_config = { "wandb_enabled": True, "tensorboard_enabled": False, @@ -45,6 +46,10 @@ logging_config = { "project": "grpo-dev", "name": "grpo-dev-logging", }, + "swanlab": { + "project": "nemo-rl", + "name": "grpo-dev-logging", + }, "tensorboard": { "log_dir": "logs", }, @@ -74,6 +79,13 @@ The logger supports three main logging backends: - Includes built-in hyperparameter logging - Offers rich visualization and collaboration features +### Swanlab +- Training visualization (Android, iOS, Wechat public account and Web) +- Automatic logging +- Hyperparameter recording +- Experiment comparison +- Multi-user collaboration + ### Tensorboard - Local file-based logging - Standard TensorBoard visualization @@ -121,6 +133,7 @@ The logger supports pretty-formatted logging of validation samples to help visua ```python logger: wandb_enabled: false + swanlab_enabled: false tensorboard_enabled: false mlflow_enabled: false num_val_samples_to_print: 10 @@ -140,7 +153,7 @@ When enabled, the pretty logging will generate formatted text similar to: ## GPU Metric Logging -NeMo RL monitors GPU memory and utilization through [system metrics](https://docs.ray.io/en/latest/ray-observability/reference/system-metrics.html#system-metrics) exposed by Ray nodes. While Ray makes these metrics available for tools like Prometheus, NeMo RL directly polls GPU memory and utilization data and logs them to TensorBoard, WandB, and/or MLflow. +NeMo RL monitors GPU memory and utilization through [system metrics](https://docs.ray.io/en/latest/ray-observability/reference/system-metrics.html#system-metrics) exposed by Ray nodes. While Ray makes these metrics available for tools like Prometheus, NeMo RL directly polls GPU memory and utilization data and logs them to TensorBoard, WandB, MLflow and/or SwanLab. This approach allows us to offer the same GPU metric tracking on all loggers and simplifies the implementation greatly. @@ -149,6 +162,7 @@ This feature is enabled with the `monitor_gpus` configuration parameter. The fre ```python logger: wandb_enabled: false + swanlab_enabled: false tensorboard_enabled: false mlflow_enabled: false monitor_gpus: true @@ -162,8 +176,8 @@ While it is feasible to monitor using remote workers, the implementation require * Logs sent back to the driver do not introduce significant overhead. * Metrics remain clear and interpretable, avoiding issues like double counting caused by colocated workers. * Workers can gracefully flush their logs in case of failure. -* Logging behaves consistently across TensorBoard, WandB, and MLflow. +* Logging behaves consistently across TensorBoard, WandB, MLflow and Swanlab. * Workers that spawn other workers accurately report the total resource usage of any grandchild workers. Due to these complexities, we opted for a simpler approach: collecting metrics exposed by the Ray metrics server from the driver. -::: \ No newline at end of file +::: diff --git a/examples/configs/dpo.yaml b/examples/configs/dpo.yaml index 4524338e4f..84e24e49bf 100755 --- a/examples/configs/dpo.yaml +++ b/examples/configs/dpo.yaml @@ -155,6 +155,7 @@ logger: wandb_enabled: false # Make sure you do a ``wandb login [Your API key]'' before running tensorboard_enabled: false mlflow_enabled: false # Disable MLflow logging + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true # If true, will monitor GPU usage and log to wandb and/or tensorboard num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/grpo-deepscaler-1.5b-8K.yaml b/examples/configs/grpo-deepscaler-1.5b-8K.yaml index 576494b9b9..fdf87ec2d2 100644 --- a/examples/configs/grpo-deepscaler-1.5b-8K.yaml +++ b/examples/configs/grpo-deepscaler-1.5b-8K.yaml @@ -129,6 +129,7 @@ logger: wandb_enabled: false tensorboard_enabled: false mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: false # If true, will monitor GPU usage and log to wandb and/or tensorboard wandb: project: "grpo-dev" diff --git a/examples/configs/grpo_math_1B.yaml b/examples/configs/grpo_math_1B.yaml index b9be32bdda..88ec997350 100644 --- a/examples/configs/grpo_math_1B.yaml +++ b/examples/configs/grpo_math_1B.yaml @@ -138,6 +138,7 @@ logger: wandb_enabled: false tensorboard_enabled: false mlflow_enabled: false # Disable MLflow logging + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true # If true, will monitor GPU usage and log to wandb and/or tensorboard wandb: project: "grpo-dev" diff --git a/examples/configs/grpo_math_1B_megatron.yaml b/examples/configs/grpo_math_1B_megatron.yaml index cf6ba44d75..b9f9739a75 100644 --- a/examples/configs/grpo_math_1B_megatron.yaml +++ b/examples/configs/grpo_math_1B_megatron.yaml @@ -157,6 +157,7 @@ logger: wandb_enabled: false tensorboard_enabled: false mlflow_enabled: false # Disable MLflow logging + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: false # If true, will monitor GPU usage and log to wandb and/or tensorboard wandb: project: "grpo-dev" diff --git a/examples/configs/grpo_sliding_puzzle.yaml b/examples/configs/grpo_sliding_puzzle.yaml index aeb6b48da4..754be91664 100644 --- a/examples/configs/grpo_sliding_puzzle.yaml +++ b/examples/configs/grpo_sliding_puzzle.yaml @@ -53,6 +53,7 @@ logger: wandb_enabled: false tensorboard_enabled: false mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true # If true, will monitor GPU usage and log to wandb and/or tensorboard wandb: project: "grpo-dev" diff --git a/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-fsdp2tp1.v2.yaml b/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-fsdp2tp1.v2.yaml index e7eaef706a..e69ac2ca86 100644 --- a/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-fsdp2tp1.v2.yaml +++ b/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-fsdp2tp1.v2.yaml @@ -79,6 +79,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-fsdp2tp2-quick.v2.yaml b/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-fsdp2tp2-quick.v2.yaml index 4906550001..b7acfbcfbd 100644 --- a/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-fsdp2tp2-quick.v2.yaml +++ b/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-fsdp2tp2-quick.v2.yaml @@ -79,6 +79,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-megatron.yaml b/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-megatron.yaml index 789f4fcbdf..7b4c22c5c2 100644 --- a/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-megatron.yaml +++ b/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-megatron.yaml @@ -112,6 +112,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-megatrontp2pp2-quick.yaml b/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-megatrontp2pp2-quick.yaml index 7d480f58a3..01f36d72c4 100644 --- a/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-megatrontp2pp2-quick.yaml +++ b/examples/configs/recipes/llm/dpo-llama3.1-8b-instruct-4n8g-megatrontp2pp2-quick.yaml @@ -112,6 +112,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/recipes/llm/dpo-llama3.2-1b-instruct-1n8g-fsdp2tp1.v2.yaml b/examples/configs/recipes/llm/dpo-llama3.2-1b-instruct-1n8g-fsdp2tp1.v2.yaml index 8863fad45f..3221626692 100644 --- a/examples/configs/recipes/llm/dpo-llama3.2-1b-instruct-1n8g-fsdp2tp1.v2.yaml +++ b/examples/configs/recipes/llm/dpo-llama3.2-1b-instruct-1n8g-fsdp2tp1.v2.yaml @@ -78,6 +78,7 @@ logger: log_dir: "logs" wandb_enabled: true tensorboard_enabled: true + swanlab_enabled: false # Disable SwanLab logging mlflow_enabled: false monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal diff --git a/examples/configs/recipes/llm/grpo-gemma3-1b-it-1n8g-fsdp2tp1.yaml b/examples/configs/recipes/llm/grpo-gemma3-1b-it-1n8g-fsdp2tp1.yaml index cd63c3ba79..54b50cd9cd 100644 --- a/examples/configs/recipes/llm/grpo-gemma3-1b-it-1n8g-fsdp2tp1.yaml +++ b/examples/configs/recipes/llm/grpo-gemma3-1b-it-1n8g-fsdp2tp1.yaml @@ -108,6 +108,7 @@ logger: num_val_samples_to_print: 0 wandb_enabled: true tensorboard_enabled: true + swanlab_enabled: false # Disable SwanLab logging mlflow_enabled: false monitor_gpus: true wandb: diff --git a/examples/configs/recipes/llm/grpo-gemma3-27b-it-16n8g-fsdp2tp8sp-actckpt-long.yaml b/examples/configs/recipes/llm/grpo-gemma3-27b-it-16n8g-fsdp2tp8sp-actckpt-long.yaml index bdd0361cf8..022f613c76 100644 --- a/examples/configs/recipes/llm/grpo-gemma3-27b-it-16n8g-fsdp2tp8sp-actckpt-long.yaml +++ b/examples/configs/recipes/llm/grpo-gemma3-27b-it-16n8g-fsdp2tp8sp-actckpt-long.yaml @@ -110,6 +110,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true wandb: project: nemo-rl diff --git a/examples/configs/recipes/llm/grpo-llama3.1-8b-instruct-4n8g-fsdp2tp1-long.v3.yaml b/examples/configs/recipes/llm/grpo-llama3.1-8b-instruct-4n8g-fsdp2tp1-long.v3.yaml index ae1eee46c8..a9dda593fd 100644 --- a/examples/configs/recipes/llm/grpo-llama3.1-8b-instruct-4n8g-fsdp2tp1-long.v3.yaml +++ b/examples/configs/recipes/llm/grpo-llama3.1-8b-instruct-4n8g-fsdp2tp1-long.v3.yaml @@ -110,6 +110,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true wandb: project: nemo-rl diff --git a/examples/configs/recipes/llm/grpo-llama3.2-1b-instruct-1n8g-fsdp2tp1.v3.yaml b/examples/configs/recipes/llm/grpo-llama3.2-1b-instruct-1n8g-fsdp2tp1.v3.yaml index 4571128a9a..f29a560579 100644 --- a/examples/configs/recipes/llm/grpo-llama3.2-1b-instruct-1n8g-fsdp2tp1.v3.yaml +++ b/examples/configs/recipes/llm/grpo-llama3.2-1b-instruct-1n8g-fsdp2tp1.v3.yaml @@ -110,6 +110,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true wandb: project: nemo-rl diff --git a/examples/configs/recipes/llm/grpo-qwen2.5-32b-32n8g-fsdp2tp8sp-actckpt-long.v3.yaml b/examples/configs/recipes/llm/grpo-qwen2.5-32b-32n8g-fsdp2tp8sp-actckpt-long.v3.yaml index 33ecfae6a4..0a3bba5bd1 100644 --- a/examples/configs/recipes/llm/grpo-qwen2.5-32b-32n8g-fsdp2tp8sp-actckpt-long.v3.yaml +++ b/examples/configs/recipes/llm/grpo-qwen2.5-32b-32n8g-fsdp2tp8sp-actckpt-long.v3.yaml @@ -110,6 +110,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true wandb: project: nemo-rl diff --git a/examples/configs/recipes/llm/grpo-qwen2.5-32b-32n8g-fsdp2tp8sp-actckpt.v3.yaml b/examples/configs/recipes/llm/grpo-qwen2.5-32b-32n8g-fsdp2tp8sp-actckpt.v3.yaml index ea862ee9d3..2309a2a414 100644 --- a/examples/configs/recipes/llm/grpo-qwen2.5-32b-32n8g-fsdp2tp8sp-actckpt.v3.yaml +++ b/examples/configs/recipes/llm/grpo-qwen2.5-32b-32n8g-fsdp2tp8sp-actckpt.v3.yaml @@ -110,6 +110,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true wandb: project: nemo-rl diff --git a/examples/configs/recipes/llm/grpo-qwen2.5-7b-instruct-4n8g-fsdp2tp4sp.v3.yaml b/examples/configs/recipes/llm/grpo-qwen2.5-7b-instruct-4n8g-fsdp2tp4sp.v3.yaml index 0961b8f2c7..cd602a280b 100644 --- a/examples/configs/recipes/llm/grpo-qwen2.5-7b-instruct-4n8g-fsdp2tp4sp.v3.yaml +++ b/examples/configs/recipes/llm/grpo-qwen2.5-7b-instruct-4n8g-fsdp2tp4sp.v3.yaml @@ -110,6 +110,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true wandb: project: nemo-rl diff --git a/examples/configs/recipes/llm/grpo-qwen2.5-math-1.5b-instruct-1n8g-fsdp2tp1.v3.yaml b/examples/configs/recipes/llm/grpo-qwen2.5-math-1.5b-instruct-1n8g-fsdp2tp1.v3.yaml index 978832bad0..1e02ff36a6 100644 --- a/examples/configs/recipes/llm/grpo-qwen2.5-math-1.5b-instruct-1n8g-fsdp2tp1.v3.yaml +++ b/examples/configs/recipes/llm/grpo-qwen2.5-math-1.5b-instruct-1n8g-fsdp2tp1.v3.yaml @@ -110,6 +110,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true wandb: project: nemo-rl diff --git a/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-fsdp2tp1-long.v2.yaml b/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-fsdp2tp1-long.v2.yaml index 19fbd99562..2aee79d498 100644 --- a/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-fsdp2tp1-long.v2.yaml +++ b/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-fsdp2tp1-long.v2.yaml @@ -59,6 +59,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-fsdp2tp2sp.v2.yaml b/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-fsdp2tp2sp.v2.yaml index 8f37dc440e..3e2a69f5a4 100644 --- a/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-fsdp2tp2sp.v2.yaml +++ b/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-fsdp2tp2sp.v2.yaml @@ -59,6 +59,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-megatron.yaml b/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-megatron.yaml index ec72f8f454..57d3736a13 100644 --- a/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-megatron.yaml +++ b/examples/configs/recipes/llm/sft-llama3.1-8b-instruct-1n8g-megatron.yaml @@ -103,6 +103,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/recipes/llm/sft-llama3.2-1b-1n8g-fsdp2tp1.v2.yaml b/examples/configs/recipes/llm/sft-llama3.2-1b-1n8g-fsdp2tp1.v2.yaml index 685990ab98..b20b901c3a 100644 --- a/examples/configs/recipes/llm/sft-llama3.2-1b-1n8g-fsdp2tp1.v2.yaml +++ b/examples/configs/recipes/llm/sft-llama3.2-1b-1n8g-fsdp2tp1.v2.yaml @@ -59,6 +59,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/recipes/llm/sft-qwen2.5-32b-4n8g-fsdp2tp8sp-actckpt.v2.yaml b/examples/configs/recipes/llm/sft-qwen2.5-32b-4n8g-fsdp2tp8sp-actckpt.v2.yaml index 2ebadb9670..9e27c789ca 100644 --- a/examples/configs/recipes/llm/sft-qwen2.5-32b-4n8g-fsdp2tp8sp-actckpt.v2.yaml +++ b/examples/configs/recipes/llm/sft-qwen2.5-32b-4n8g-fsdp2tp8sp-actckpt.v2.yaml @@ -59,6 +59,7 @@ logger: wandb_enabled: true tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/sft.yaml b/examples/configs/sft.yaml index a592321cfe..cc065e6f72 100644 --- a/examples/configs/sft.yaml +++ b/examples/configs/sft.yaml @@ -138,6 +138,7 @@ logger: wandb_enabled: true # Make sure you do a ``wandb login [Your API key]'' before running tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: true # If true, will monitor GPU usage and log to wandb and/or tensorboard num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/examples/configs/sft_openmathinstruct2.yaml b/examples/configs/sft_openmathinstruct2.yaml index 1f1b88a8a9..c1ddd4aa4a 100644 --- a/examples/configs/sft_openmathinstruct2.yaml +++ b/examples/configs/sft_openmathinstruct2.yaml @@ -73,6 +73,7 @@ logger: wandb_enabled: true # Make sure you do a ``wandb login [Your API key]'' before running tensorboard_enabled: true mlflow_enabled: false + swanlab_enabled: false # Disable SwanLab logging monitor_gpus: false # If true, will monitor GPU usage and log to wandb and/or tensorboard num_val_samples_to_print: 0 # Number of validation samples to pretty print on terminal wandb: diff --git a/nemo_rl/utils/logger.py b/nemo_rl/utils/logger.py index 4cf2621cd4..05034618f3 100644 --- a/nemo_rl/utils/logger.py +++ b/nemo_rl/utils/logger.py @@ -50,6 +50,9 @@ class WandbConfig(TypedDict): project: NotRequired[str] name: NotRequired[str] +class SwanlabConfig(TypedDict): + project: NotRequired[str] + name: NotRequired[str] class TensorboardConfig(TypedDict): log_dir: NotRequired[str] @@ -69,9 +72,11 @@ class GPUMonitoringConfig(TypedDict): class LoggerConfig(TypedDict): log_dir: str wandb_enabled: bool + swanlab_enabled: bool tensorboard_enabled: bool mlflow_enabled: bool wandb: WandbConfig + swanlab: SwanlabConfig tensorboard: TensorboardConfig mlflow: NotRequired[MLflowConfig] monitor_gpus: bool @@ -323,6 +328,74 @@ def log_plot(self, figure: plt.Figure, step: int, name: str) -> None: """ self.run.log({name: figure}, step=step) +class SwanlabLogger(LoggerInterface): + """Weights & Biases logger backend.""" + + def __init__(self, cfg: SwanlabConfig, log_dir: Optional[str] = None): + import swanlab + self.run = swanlab.init(**cfg) + print( + f"Initialized SwanlabLogger for project {cfg.get('project')}, run {cfg.get('name')} at {log_dir}" + ) + + def define_metric( + self, + name: str, + step_metric: Optional[str] = None, + ) -> None: + """Define a metric with custom step metric. + + Args: + name: Name of the metric or pattern (e.g. 'ray/*') + step_metric: Optional name of the step metric to use + """ + self.run.define_metric(name, step_metric=step_metric) + + def log_metrics( + self, + metrics: dict[str, Any], + step: int, + prefix: Optional[str] = "", + step_metric: Optional[str] = None, + ) -> None: + """Log metrics to wandb. + + Args: + metrics: Dict of metrics to log + step: Global step value + prefix: Optional prefix for metric names + step_metric: Optional name of a field in metrics to use as step instead + of the provided step value + """ + if prefix: + metrics = { + f"{prefix}/{k}" if k != step_metric else k: v + for k, v in metrics.items() + } + + # If step_metric is provided, use the corresponding value from metrics as step + if step_metric and step_metric in metrics: + # commit=False so the step does not get incremented + self.run.log(metrics, commit=False) + else: + self.run.log(metrics, step=step) + + def log_hyperparams(self, params: Mapping[str, Any]) -> None: + """Log hyperparameters to swanlab. + + Args: + params: Dict of hyperparameters to log + """ + self.run.config.update(params) + + def log_plot(self, figure: plt.Figure, step: int, name: str) -> None: + """Log a plot to swanlab. + + Args: + figure: Matplotlib figure to log + step: Global step value + """ + self.run.log({name: figure}, step=step) class GpuMetricSnapshot(TypedDict): step: int @@ -727,6 +800,7 @@ def __init__(self, cfg: LoggerConfig): """ self.loggers: list[LoggerInterface] = [] self.wandb_logger = None + self.swanlab_logger = None self.base_log_dir = cfg["log_dir"] os.makedirs(self.base_log_dir, exist_ok=True) @@ -737,6 +811,12 @@ def __init__(self, cfg: LoggerConfig): self.wandb_logger = WandbLogger(cfg["wandb"], log_dir=wandb_log_dir) self.loggers.append(self.wandb_logger) + if cfg["swanlab_enabled"]: + swanlab_log_dir = os.path.join(self.base_log_dir, "swanlab") + os.makedirs(swanlab_log_dir, exist_ok=True) + self.swanlab_logger = SwanlabLogger(cfg["swanlab"], log_dir=swanlab_log_dir) + self.loggers.append(self.swanlab_logger) + if cfg["tensorboard_enabled"]: tensorboard_log_dir = os.path.join(self.base_log_dir, "tensorboard") os.makedirs(tensorboard_log_dir, exist_ok=True) @@ -761,6 +841,11 @@ def __init__(self, cfg: LoggerConfig): f"{metric_prefix}/*", step_metric=step_metric ) + if cfg["swanlab_enabled"] and self.swanlab_logger: + self.swanlab_logger.define_metric( + f"{metric_prefix}/*", step_metric=step_metric + ) + self.gpu_monitor = RayGpuMonitorLogger( collection_interval=cfg["gpu_monitoring"]["collection_interval"], flush_interval=cfg["gpu_monitoring"]["flush_interval"], diff --git a/tests/unit/utils/test_logger.py b/tests/unit/utils/test_logger.py index e61120f312..9476b67a5b 100644 --- a/tests/unit/utils/test_logger.py +++ b/tests/unit/utils/test_logger.py @@ -25,6 +25,7 @@ RayGpuMonitorLogger, TensorboardLogger, WandbLogger, + SwanlabLogger, flatten_dict, ) @@ -262,6 +263,141 @@ def test_log_hyperparams(self, mock_wandb): mock_run = mock_wandb.init.return_value mock_run.config.update.assert_called_once_with(params) +class TestSwanlabLogger: + """Test the SwanlabLogger class.""" + + @pytest.fixture + def temp_dir(self): + """Create a temporary directory for logs.""" + temp_dir = tempfile.mkdtemp() + yield temp_dir + shutil.rmtree(temp_dir) + + @patch("nemo_rl.utils.logger.swanlab") + def test_init_custom_config(self, mock_swanlab, temp_dir): + """Test initialization of SwanlabLogger with custom config.""" + cfg = { + "project": "custom-project", + "name": "custom-run", + "entity": "custom-entity", + "group": "custom-group", + "tags": ["tag1", "tag2"], + } + SwanlabLogger(cfg, log_dir=temp_dir) + + mock_swanlab.init.assert_called_once_with( + project="custom-project", + name="custom-run", + entity="custom-entity", + group="custom-group", + tags=["tag1", "tag2"], + dir=temp_dir, + ) + + @patch("nemo_rl.utils.logger.swanlab") + def test_log_metrics(self, mock_swanlab): + """Test logging metrics to SwanlabLogger.""" + cfg = {} + logger = SwanlabLogger(cfg) + + metrics = {"loss": 0.5, "accuracy": 0.8} + step = 10 + logger.log_metrics(metrics, step) + + # Check that log was called with metrics and step + mock_run = mock_swanlab.init.return_value + mock_run.log.assert_called_once_with(metrics, step=step) + + @patch("nemo_rl.utils.logger.swanlab") + def test_log_metrics_with_prefix(self, mock_swanlab): + """Test logging metrics with a prefix to SwanlabLogger.""" + cfg = {} + logger = SwanlabLogger(cfg) + + metrics = {"loss": 0.5, "accuracy": 0.8} + step = 10 + prefix = "train" + logger.log_metrics(metrics, step, prefix) + + # Check that log was called with prefixed metrics and step + mock_run = mock_swanlab.init.return_value + expected_metrics = {"train/loss": 0.5, "train/accuracy": 0.8} + mock_run.log.assert_called_once_with(expected_metrics, step=step) + + @patch("nemo_rl.utils.logger.swanlab") + def test_log_metrics_with_step_metric(self, mock_swanlab): + """Test logging metrics with a step metric to SwanlabLogger.""" + cfg = {} + logger = SwanlabLogger(cfg) + + # Define step metric + step_metric = "iteration" + + # Include the step metric in the metrics + metrics = {"loss": 0.5, "accuracy": 0.8, "iteration": 15} + step = 10 # This should be ignored when step_metric is provided + + logger.log_metrics(metrics, step, step_metric=step_metric) + + # Check that log was called with metrics and commit=False + # When using step_metric, step should be ignored and commit=False should be used + mock_run = mock_swanlab.init.return_value + mock_run.log.assert_called_once_with(metrics, commit=False) + + @patch("nemo_rl.utils.logger.swanlab") + def test_log_metrics_with_prefix_and_step_metric(self, mock_swanlab): + """Test logging metrics with both prefix and step metric.""" + cfg = {} + logger = SwanlabLogger(cfg) + + # Define prefix and step metric + prefix = "train" + step_metric = "train/iteration" + + # Include the step metric in the metrics + metrics = {"loss": 0.5, "accuracy": 0.8, "iteration": 15} + step = 10 # This should be ignored when step_metric is provided + + logger.log_metrics(metrics, step, prefix=prefix, step_metric=step_metric) + + # Check that log was called with prefixed metrics and commit=False + # The step_metric key gets prefixed based on the current implementation + mock_run = mock_swanlab.init.return_value + expected_metrics = { + "train/loss": 0.5, + "train/accuracy": 0.8, + "train/iteration": 15, + } + mock_run.log.assert_called_once_with(expected_metrics, commit=False) + + @patch("nemo_rl.utils.logger.swanlab") + def test_define_metric(self, mock_swanlab): + """Test defining a metric with a custom step metric.""" + cfg = {} + logger = SwanlabLogger(cfg) + + # Define metric pattern and step metric + logger.define_metric("ray/*", step_metric="ray/ray_step") + + # Check that define_metric was called + mock_run = mock_swanlab.init.return_value + mock_run.define_metric.assert_called_once_with( + "ray/*", step_metric="ray/ray_step" + ) + + @patch("nemo_rl.utils.logger.swanlab") + def test_log_hyperparams(self, mock_swanlab): + """Test logging hyperparameters to SwanlabLogger.""" + cfg = {} + logger = SwanlabLogger(cfg) + + params = {"lr": 0.001, "batch_size": 32, "model": {"hidden_size": 128}} + logger.log_hyperparams(params) + + # Check that config.update was called with params + mock_run = mock_swanlab.init.return_value + mock_run.config.update.assert_called_once_with(params) + class TestMLflowLogger: """Test the MLflowLogger class.""" @@ -918,6 +1054,7 @@ def test_init_with_gpu_monitoring( "wandb_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": True, "gpu_monitoring": { "collection_interval": 15.0, @@ -964,6 +1101,7 @@ def test_gpu_monitoring_without_wandb( "wandb_enabled": False, "tensorboard_enabled": True, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": True, "gpu_monitoring": { "collection_interval": 15.0, @@ -1055,6 +1193,7 @@ def test_init_no_loggers(self, mock_tb_logger, mock_wandb_logger, temp_dir): "wandb_enabled": False, "tensorboard_enabled": False, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": False, "log_dir": temp_dir, } @@ -1072,6 +1211,7 @@ def test_init_wandb_only(self, mock_tb_logger, mock_wandb_logger, temp_dir): "wandb_enabled": True, "tensorboard_enabled": False, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": False, "wandb": {"project": "test-project"}, "log_dir": temp_dir, @@ -1084,6 +1224,28 @@ def test_init_wandb_only(self, mock_tb_logger, mock_wandb_logger, temp_dir): assert wandb_cfg == {"project": "test-project"} mock_tb_logger.assert_not_called() + @patch("nemo_rl.utils.logger.WandbLogger") + @patch("nemo_rl.utils.logger.SwanlabLogger") + @patch("nemo_rl.utils.logger.TensorboardLogger") + def test_init_swanlab_only(self, mock_tb_logger, mock_swanlab_logger, temp_dir): + """Test initialization with only SwanlabLogger enabled.""" + cfg = { + "wandb_enabled": False, + "tensorboard_enabled": False, + "mlflow_enabled": False, + "swanlab_enabled": True, + "monitor_gpus": False, + "swanlab": {"project": "test-project"}, + "log_dir": temp_dir, + } + logger = Logger(cfg) + + assert len(logger.loggers) == 1 + mock_swanlab_logger.assert_called_once() + swanlab_cfg = mock_swanlab_logger.call_args[0][0] + assert swanlab_cfg == {"project": "test-project"} + mock_tb_logger.assert_not_called() + @patch("nemo_rl.utils.logger.WandbLogger") @patch("nemo_rl.utils.logger.TensorboardLogger") def test_init_tensorboard_only(self, mock_tb_logger, mock_wandb_logger, temp_dir): @@ -1092,6 +1254,7 @@ def test_init_tensorboard_only(self, mock_tb_logger, mock_wandb_logger, temp_dir "wandb_enabled": False, "tensorboard_enabled": True, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": False, "tensorboard": {"log_dir": "test_logs"}, "log_dir": temp_dir, @@ -1112,6 +1275,7 @@ def test_init_both_loggers(self, mock_tb_logger, mock_wandb_logger, temp_dir): "wandb_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": False, "wandb": {"project": "test-project"}, "tensorboard": {"log_dir": "test_logs"}, @@ -1136,6 +1300,7 @@ def test_log_metrics(self, mock_tb_logger, mock_wandb_logger, temp_dir): "wandb_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": False, "wandb": {"project": "test-project"}, "tensorboard": {"log_dir": "test_logs"}, @@ -1163,6 +1328,7 @@ def test_log_hyperparams(self, mock_tb_logger, mock_wandb_logger, temp_dir): "wandb_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": False, "wandb": {"project": "test-project"}, "tensorboard": {"log_dir": "test_logs"}, @@ -1192,6 +1358,7 @@ def test_init_with_gpu_monitoring( "wandb_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": True, "gpu_monitoring": { "collection_interval": 15.0, @@ -1237,6 +1404,7 @@ def test_log_metrics_with_prefix_and_step_metric( "wandb_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": False, "wandb": {"project": "test-project"}, "tensorboard": {"log_dir": "test_logs"}, @@ -1275,6 +1443,7 @@ def test_log_plot_token_mult_prob_error( "wandb_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": False, + "swanlab_enabled": False, "monitor_gpus": False, "wandb": {"project": "test-project"}, "tensorboard": {"log_dir": "test_logs"}, @@ -1329,6 +1498,7 @@ def test_init_mlflow_only(self, mock_tb_logger, mock_wandb_logger, temp_dir): "wandb_enabled": False, "tensorboard_enabled": False, "mlflow_enabled": True, + "swanlab_enabled": False, "monitor_gpus": False, "mlflow": { "experiment_name": "test-experiment", @@ -1346,16 +1516,19 @@ def test_init_mlflow_only(self, mock_tb_logger, mock_wandb_logger, temp_dir): @patch("nemo_rl.utils.logger.WandbLogger") @patch("nemo_rl.utils.logger.TensorboardLogger") @patch("nemo_rl.utils.logger.MLflowLogger") + @patch("nemo_rl.utils.logger.SwanlabLogger") def test_init_all_loggers( - self, mock_mlflow_logger, mock_tb_logger, mock_wandb_logger, temp_dir + self, mock_swanlab_logger, mock_mlflow_logger, mock_tb_logger, mock_wandb_logger, temp_dir ): """Test initialization with all loggers enabled.""" cfg = { "wandb_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": True, + "swanlab_enabled": True, "monitor_gpus": False, "wandb": {"project": "test-project"}, + "swanlab": {"project": "test-project"}, "tensorboard": {"log_dir": "test_logs"}, "mlflow": { "experiment_name": "test-experiment", @@ -1366,24 +1539,28 @@ def test_init_all_loggers( } logger = Logger(cfg) - assert len(logger.loggers) == 3 + assert len(logger.loggers) == 4 mock_wandb_logger.assert_called_once() mock_tb_logger.assert_called_once() mock_mlflow_logger.assert_called_once() + mock_swanlab_logger.assert_called_once() @patch("nemo_rl.utils.logger.WandbLogger") @patch("nemo_rl.utils.logger.TensorboardLogger") @patch("nemo_rl.utils.logger.MLflowLogger") + @patch("nemo_rl.utils.logger.SwanlabLogger") def test_log_metrics_with_mlflow( - self, mock_mlflow_logger, mock_tb_logger, mock_wandb_logger, temp_dir + self, mock_swanlab_logger, mock_mlflow_logger, mock_tb_logger, mock_wandb_logger, temp_dir ): """Test logging metrics to all enabled loggers including MLflow.""" cfg = { "wandb_enabled": True, + "swanlab_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": True, "monitor_gpus": False, "wandb": {"project": "test-project"}, + "swanlab": {"project": "test-project"}, "tensorboard": {"log_dir": "test_logs"}, "mlflow": { "experiment_name": "test-experiment", @@ -1398,6 +1575,7 @@ def test_log_metrics_with_mlflow( mock_wandb_instance = mock_wandb_logger.return_value mock_tb_instance = mock_tb_logger.return_value mock_mlflow_instance = mock_mlflow_logger.return_value + mock_swanlab_instance = mock_swanlab_logger.return_value metrics = {"loss": 0.5, "accuracy": 0.8} step = 10 @@ -1405,6 +1583,7 @@ def test_log_metrics_with_mlflow( # Check that log_metrics was called on all loggers mock_wandb_instance.log_metrics.assert_called_once_with(metrics, step, "", None) + moc_swanlab_instance.log_metrics.assert_called_once_with(metrics, step, "", None) mock_tb_instance.log_metrics.assert_called_once_with(metrics, step, "", None) mock_mlflow_instance.log_metrics.assert_called_once_with( metrics, step, "", None @@ -1413,16 +1592,19 @@ def test_log_metrics_with_mlflow( @patch("nemo_rl.utils.logger.WandbLogger") @patch("nemo_rl.utils.logger.TensorboardLogger") @patch("nemo_rl.utils.logger.MLflowLogger") + @patch("nemo_rl.utils.logger.SwanlabLogger") def test_log_hyperparams_with_mlflow( - self, mock_mlflow_logger, mock_tb_logger, mock_wandb_logger, temp_dir + self, mock_swanlab_logger, mock_mlflow_logger, mock_tb_logger, mock_wandb_logger, temp_dir ): """Test logging hyperparameters to all enabled loggers including MLflow.""" cfg = { "wandb_enabled": True, + "swanlab_enabled": True, "tensorboard_enabled": True, "mlflow_enabled": True, "monitor_gpus": False, "wandb": {"project": "test-project"}, + "swanlab": {"project": "test-project"}, "tensorboard": {"log_dir": "test_logs"}, "mlflow": {"experiment_name": "test-experiment"}, "log_dir": temp_dir, @@ -1433,6 +1615,7 @@ def test_log_hyperparams_with_mlflow( mock_wandb_instance = mock_wandb_logger.return_value mock_tb_instance = mock_tb_logger.return_value mock_mlflow_instance = mock_mlflow_logger.return_value + mock_swanlab_instance = mock_swanlab_logger.return_value params = {"lr": 0.001, "batch_size": 32} logger.log_hyperparams(params) @@ -1441,3 +1624,4 @@ def test_log_hyperparams_with_mlflow( mock_wandb_instance.log_hyperparams.assert_called_once_with(params) mock_tb_instance.log_hyperparams.assert_called_once_with(params) mock_mlflow_instance.log_hyperparams.assert_called_once_with(params) + mock_swanlab_instance.log_hyperparams.assert_called_once_with(params) From 232c75153b06e0308f40509ad5316c7494f21f9a Mon Sep 17 00:00:00 2001 From: tpoisonooo Date: Wed, 30 Jul 2025 13:45:41 +0800 Subject: [PATCH 03/23] unittest(logger.py): test passed Signed-off-by: tpoisonooo --- nemo_rl/utils/logger.py | 2 +- tests/unit/utils/test_logger.py | 4 +- uv.lock | 5136 +++++++++++++++---------------- 3 files changed, 2571 insertions(+), 2571 deletions(-) diff --git a/nemo_rl/utils/logger.py b/nemo_rl/utils/logger.py index 05034618f3..ebf9a5df12 100644 --- a/nemo_rl/utils/logger.py +++ b/nemo_rl/utils/logger.py @@ -30,6 +30,7 @@ import requests import torch import wandb +import swanlab from matplotlib import pyplot as plt from prometheus_client.parser import text_string_to_metric_families from prometheus_client.samples import Sample @@ -332,7 +333,6 @@ class SwanlabLogger(LoggerInterface): """Weights & Biases logger backend.""" def __init__(self, cfg: SwanlabConfig, log_dir: Optional[str] = None): - import swanlab self.run = swanlab.init(**cfg) print( f"Initialized SwanlabLogger for project {cfg.get('project')}, run {cfg.get('name')} at {log_dir}" diff --git a/tests/unit/utils/test_logger.py b/tests/unit/utils/test_logger.py index 9476b67a5b..147014d7da 100644 --- a/tests/unit/utils/test_logger.py +++ b/tests/unit/utils/test_logger.py @@ -291,7 +291,6 @@ def test_init_custom_config(self, mock_swanlab, temp_dir): entity="custom-entity", group="custom-group", tags=["tag1", "tag2"], - dir=temp_dir, ) @patch("nemo_rl.utils.logger.swanlab") @@ -1139,6 +1138,7 @@ def test_gpu_monitoring_no_main_loggers( """Test GPU monitoring initialization when no main loggers (wandb/tensorboard) are enabled.""" cfg = { "wandb_enabled": False, + "swanlab_enabled": False, "tensorboard_enabled": False, "mlflow_enabled": False, "monitor_gpus": True, @@ -1583,7 +1583,7 @@ def test_log_metrics_with_mlflow( # Check that log_metrics was called on all loggers mock_wandb_instance.log_metrics.assert_called_once_with(metrics, step, "", None) - moc_swanlab_instance.log_metrics.assert_called_once_with(metrics, step, "", None) + mock_swanlab_instance.log_metrics.assert_called_once_with(metrics, step, "", None) mock_tb_instance.log_metrics.assert_called_once_with(metrics, step, "", None) 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tpoisonooo --- nemo_rl/utils/logger.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/nemo_rl/utils/logger.py b/nemo_rl/utils/logger.py index ebf9a5df12..5cffa69edc 100644 --- a/nemo_rl/utils/logger.py +++ b/nemo_rl/utils/logger.py @@ -333,9 +333,9 @@ class SwanlabLogger(LoggerInterface): """Weights & Biases logger backend.""" def __init__(self, cfg: SwanlabConfig, log_dir: Optional[str] = None): - self.run = swanlab.init(**cfg) + self.run = swanlab.init(**cfg, logdir=log_dir) print( - f"Initialized SwanlabLogger for project {cfg.get('project')}, run {cfg.get('name')} at {log_dir}" + f"Initialized SwanlabLogger for project {cfg.get('project')}, run {cfg.get('name')} (with offline logdir={log_dir})" ) def define_metric( From 420a580cf28b5dedd415991dba488afbb3082f3f Mon Sep 17 00:00:00 2001 From: tpoisonooo Date: Thu, 31 Jul 2025 11:35:37 +0800 Subject: [PATCH 07/23] Update nemo_rl/utils/logger.py Co-authored-by: Terry Kong Signed-off-by: tpoisonooo --- 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size = 261909, upload-time = "2025-06-18T07:36:47.372Z" }, +] + [[package]] name = "sympy" version = "1.14.0" From 95c7ed87c4395c3d18f5cd741f1739887078b6d3 Mon Sep 17 00:00:00 2001 From: Xuehan Xiong Date: Tue, 29 Jul 2025 22:02:38 -0700 Subject: [PATCH 09/23] feat: add AIME-2025 eval dataset. (#777) Signed-off-by: Xuehan Signed-off-by: tpoisonooo --- docs/guides/eval.md | 13 +++++--- nemo_rl/data/eval_datasets/__init__.py | 7 ++++ nemo_rl/data/eval_datasets/aime2025.py | 46 ++++++++++++++++++++++++++ pyrefly.toml | 1 + 4 files changed, 62 insertions(+), 5 deletions(-) create mode 100644 nemo_rl/data/eval_datasets/aime2025.py diff --git a/docs/guides/eval.md b/docs/guides/eval.md index c82b4bff37..31779f3dda 100644 --- a/docs/guides/eval.md +++ b/docs/guides/eval.md @@ -89,9 +89,12 @@ score=0.1000 (3.0/30) ## List of currently supported benchmarks -- [AIME-2024](../../nemo_rl/data/eval_datasets/aime2024.py) -- [GPQA and GPQA-diamond](../../nemo_rl/data/eval_datasets/gpqa.py) -- [MATH and MATH-500](../../nemo_rl/data/eval_datasets/math.py) -- [MMLU](../../nemo_rl/data/eval_datasets/mmlu.py): this also includes MMMLU (Multilingual MMLU), a total of 14 languages. -- [MMLU-Pro](../../nemo_rl/data/eval_datasets/mmlu_pro.py) +- [AIME-2024](../../nemo_rl/data/eval_datasets/aime2024.py): the corresponding `data.dataset_name` is `"aime2024"`. +- [AIME-2025](../../nemo_rl/data/eval_datasets/aime2025.py): the corresponding `data.dataset_name` is `"aime2025"`. +- [GPQA and GPQA-diamond](../../nemo_rl/data/eval_datasets/gpqa.py): the corresponding `data.dataset_name` are `"gpqa"` and `"gpqa-diamond"`. +- [MATH and MATH-500](../../nemo_rl/data/eval_datasets/math.py): the corresponding `data.dataset_name` are `"math"` and `"math500"`. +- [MMLU](../../nemo_rl/data/eval_datasets/mmlu.py): this also includes MMMLU (Multilingual MMLU), a total of 14 languages. When `data.dataset_name` is set to `mmlu`, the English version is used. If one wants to run evaluation on another language, `data.dataset_name` should be set to `mmlu_{language}` where `language` is one of following 14 values, `["AR-XY", "BN-BD", "DE-DE", "ES-LA", "FR-FR", "HI-IN", "ID-ID", "IT-IT", "JA-JP", "KO-KR", "PT-BR", "ZH-CN", "SW-KE", "YO-NG"]`. +- [MMLU-Pro](../../nemo_rl/data/eval_datasets/mmlu_pro.py): the corresponding `data.dataset_name` is `"mmlu_pro"`. + +More details can be found in [load_eval_dataset](../../nemo_rl/data/eval_datasets/__init__.py). diff --git a/nemo_rl/data/eval_datasets/__init__.py b/nemo_rl/data/eval_datasets/__init__.py index e99a7c6af2..c735bf2e18 100644 --- a/nemo_rl/data/eval_datasets/__init__.py +++ b/nemo_rl/data/eval_datasets/__init__.py @@ -13,6 +13,7 @@ # limitations under the License. from nemo_rl.data.eval_datasets.aime2024 import AIME2024Dataset +from nemo_rl.data.eval_datasets.aime2025 import AIME2025Dataset from nemo_rl.data.eval_datasets.gpqa import GPQADataset from nemo_rl.data.eval_datasets.local_math_dataset import LocalMathDataset from nemo_rl.data.eval_datasets.math import MathDataset @@ -41,6 +42,11 @@ def load_eval_dataset(data_config): prompt_file=data_config["prompt_file"], system_prompt_file=data_config["system_prompt_file"], ) + elif dataset_name == "aime2025": + base_dataset = AIME2025Dataset( + prompt_file=data_config["prompt_file"], + system_prompt_file=data_config["system_prompt_file"], + ) elif dataset_name == "gpqa": base_dataset = GPQADataset( variant="main", @@ -88,6 +94,7 @@ def load_eval_dataset(data_config): __all__ = [ "AIME2024Dataset", + "AIME2025Dataset", "GPQADataset", "LocalMathDataset", "MathDataset", diff --git a/nemo_rl/data/eval_datasets/aime2025.py b/nemo_rl/data/eval_datasets/aime2025.py new file mode 100644 index 0000000000..43db69cf1b --- /dev/null +++ b/nemo_rl/data/eval_datasets/aime2025.py @@ -0,0 +1,46 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# 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 +# +# http://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. + +"""AIME 2025 dataset.""" + +from typing import Any, Optional + +from datasets import concatenate_datasets, load_dataset + +from nemo_rl.data import processors +from nemo_rl.data.interfaces import TaskDataSpec + + +class AIME2025Dataset: + def __init__( + self, + prompt_file: Optional[str] = None, + system_prompt_file: Optional[str] = None, + ): + ds0 = load_dataset("opencompass/AIME2025", "AIME2025-I", split="test") + ds1 = load_dataset("opencompass/AIME2025", "AIME2025-II", split="test") + ds = concatenate_datasets([ds0, ds1]) + self.rekeyed_ds = ds.map(self._rekey, remove_columns=ds.column_names) + self.task_spec = TaskDataSpec( + task_name="aime2025", + prompt_file=prompt_file, + system_prompt_file=system_prompt_file, + ) + self.processor = processors.math_data_processor + + def _rekey(self, data: dict[str, Any]): + return { + "problem": data["question"], + "expected_answer": data["answer"], + } diff --git a/pyrefly.toml b/pyrefly.toml index f3bc05a639..2fa6327786 100644 --- a/pyrefly.toml +++ b/pyrefly.toml @@ -43,6 +43,7 @@ project-includes = [ "nemo_rl/data/datasets.py", "nemo_rl/data/eval_datasets/__init__.py", "nemo_rl/data/eval_datasets/aime2024.py", + "nemo_rl/data/eval_datasets/aime2025.py", "nemo_rl/data/eval_datasets/gpqa.py", "nemo_rl/data/eval_datasets/local_math_dataset.py", "nemo_rl/data/eval_datasets/math.py", From a0ab666af3f7f9443722b317e8906c61c418c11f Mon Sep 17 00:00:00 2001 From: Terry Kong Date: Wed, 30 Jul 2025 09:58:59 -0700 Subject: [PATCH 10/23] docs: clarification of where you can find nsys profiles (#771) Signed-off-by: Terry Kong Signed-off-by: tpoisonooo --- docs/nsys-profiling.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/nsys-profiling.md b/docs/nsys-profiling.md index 7fbd7e12bb..db3f6a768a 100644 --- a/docs/nsys-profiling.md +++ b/docs/nsys-profiling.md @@ -80,7 +80,7 @@ When profiling is enabled, it generates the following logs and files: dtensor_policy_worker__.nsys-rep ``` -3. **File Location**: Profile files are saved in `/tmp/ray/session*/logs/nsight/` directory on each worker node. +3. **File Location**: Profile files are saved in `/tmp/ray/session*/logs/nsight/` directory on each worker node. Ensure you check both `ls /tmp/ray/session_[0-9]*/logs/nsight` and `ls /tmp/ray/session_latest/logs/nsight` for the profiles, since the "latest" pointer may be stale. **Note for SLURM users with `ray.sub`**: When using `ray.sub` on SLURM, set `RAY_LOG_SYNC_FREQUENCY=$NUM_SEC` (e.g., `RAY_LOG_SYNC_FREQUENCY=30`) to ensure that the nsight profile files get copied from the container's ephemeral filesystem (`/tmp/ray`) to the persistent `$SLURM_JOB_ID-logs/ray` directory. From 8f35f39d9eacbbfedf19e361e5a4257ee2a12700 Mon Sep 17 00:00:00 2001 From: Zhiyu Li Date: Wed, 30 Jul 2025 10:12:12 -0700 Subject: [PATCH 11/23] feat: refit metadata optimization (#686) Signed-off-by: Zhiyu Li Signed-off-by: Zhiyu Li Signed-off-by: Yuki Huang Co-authored-by: Yuki Huang Co-authored-by: yuki <48991475+yuki-666@users.noreply.github.com> Signed-off-by: tpoisonooo --- .gitmodules | 2 +- 3rdparty/NeMo-workspace/NeMo | 2 +- nemo_rl/algorithms/grpo.py | 83 ++++++++++--------- nemo_rl/models/generation/vllm_backend.py | 47 ++++++----- nemo_rl/models/megatron/refit_utils.py | 1 - .../models/policy/dtensor_policy_worker.py | 5 +- .../models/policy/megatron_policy_worker.py | 81 +++++++++--------- nemo_rl/models/policy/utils.py | 8 ++ pyrefly.toml | 1 + 9 files changed, 124 insertions(+), 106 deletions(-) diff --git a/.gitmodules b/.gitmodules index 2a588f3a89..09342d3495 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,7 +1,7 @@ [submodule "3rdparty/NeMo"] path = 3rdparty/NeMo-workspace/NeMo url = https://github.com/NVIDIA/NeMo.git - branch = ashors/nemorl-qwen3 + branch = zhiyul/yukih/prepare-refit-info shallow = true [submodule "3rdparty/Megatron-LM"] path = 3rdparty/Megatron-LM-workspace/Megatron-LM diff --git a/3rdparty/NeMo-workspace/NeMo b/3rdparty/NeMo-workspace/NeMo index 33259f2540..8ddf438734 160000 --- a/3rdparty/NeMo-workspace/NeMo +++ b/3rdparty/NeMo-workspace/NeMo @@ -1 +1 @@ -Subproject commit 33259f2540af6eef375d43fc48bdcbd7ec490c29 +Subproject commit 8ddf4387344c6423763ec9ee0c9a755cbb5d8d35 diff --git a/nemo_rl/algorithms/grpo.py b/nemo_rl/algorithms/grpo.py index 96faec96cf..9f9273ac8c 100644 --- a/nemo_rl/algorithms/grpo.py +++ b/nemo_rl/algorithms/grpo.py @@ -13,6 +13,7 @@ # limitations under the License. import os import warnings +from contextlib import nullcontext from pathlib import Path from typing import Any, NotRequired, Optional, TypedDict, TypeVar, cast @@ -400,6 +401,7 @@ def refit_policy_generation( policy_generation: GenerationInterface, colocated_inference: bool, _refit_buffer_size_gb: Optional[int] = None, + timer: Optional[Timer] = None, ) -> None: """Refit the policy generation interface with the latest policy weights. @@ -414,43 +416,50 @@ def refit_policy_generation( policy.offload_before_refit() policy_generation.prepare_for_generation(tags=["weights"]) - # update weights - update_success = False - if colocated_inference: - # get model param keys, which is grouped by size - grouped_param_keys = policy.prepare_weights_for_ipc( - _refit_buffer_size_gb=_refit_buffer_size_gb - ) - total_num_keys = sum(len(k) for k in grouped_param_keys) - print( - f"[Refit] Split {total_num_keys} keys into {len(grouped_param_keys)} groups" - ) - # do update - for keys in grouped_param_keys: - ipc_handles = policy.get_weights_ipc_handles(keys) - update_success = policy_generation.update_weights_from_ipc_handles( - ipc_handles + # Create a context manager that does nothing when timer is None + timer_context = ( + timer.time("prepare_for_generation/transfer_and_update_weights") + if timer is not None + else nullcontext() + ) + with timer_context: + # update weights + update_success = False + if colocated_inference: + # get model param keys, which is grouped by size + grouped_param_keys = policy.prepare_weights_for_ipc( + _refit_buffer_size_gb=_refit_buffer_size_gb ) - if not update_success: - break - else: - # update weights through nccl - futures_train = policy.broadcast_weights_for_collective() - futures_inference = policy_generation.update_weights_from_collective() - # wait for all futures to complete - ray.get(futures_train) - results = ray.get(futures_inference) - update_success = all(result for result in results if result is not None) - - # check if update is successful - if not update_success: - error_tag = "cuda-ipc" if colocated_inference else "nccl" - error_message = ( - "❌ Error: Updating weights for the generation policy failed during refit.\n" - f"This often indicates an issue with {error_tag} or " - "a problem within the generation backend (e.g., vLLM worker).\n" - ) - raise RuntimeError(error_message) + total_num_keys = sum(len(k) for k in grouped_param_keys) + print( + f"[Refit] Split {total_num_keys} keys into {len(grouped_param_keys)} groups" + ) + # do update + for keys in grouped_param_keys: + ipc_handles = policy.get_weights_ipc_handles(keys) + update_success = policy_generation.update_weights_from_ipc_handles( + ipc_handles + ) + if not update_success: + break + else: + # update weights through nccl + futures_train = policy.broadcast_weights_for_collective() + futures_inference = policy_generation.update_weights_from_collective() + # wait for all futures to complete + ray.get(futures_train) + results = ray.get(futures_inference) + update_success = all(result for result in results if result is not None) + + # check if update is successful + if not update_success: + error_tag = "cuda-ipc" if colocated_inference else "nccl" + error_message = ( + "❌ Error: Updating weights for the generation policy failed during refit.\n" + f"This often indicates an issue with {error_tag} or " + "a problem within the generation backend (e.g., vLLM worker).\n" + ) + raise RuntimeError(error_message) if colocated_inference: policy.offload_after_refit() @@ -544,7 +553,7 @@ def grpo_train( with timer.time("prepare_for_generation"): if NEED_REFIT and POLICY_GENERATION_STALE: refit_policy_generation( - policy, policy_generation, colocated_inference + policy, policy_generation, colocated_inference, timer=timer ) POLICY_GENERATION_STALE = False else: diff --git a/nemo_rl/models/generation/vllm_backend.py b/nemo_rl/models/generation/vllm_backend.py index af7e69d046..090393c0a3 100644 --- a/nemo_rl/models/generation/vllm_backend.py +++ b/nemo_rl/models/generation/vllm_backend.py @@ -12,9 +12,11 @@ # See the License for the specific language governing permissions and # limitations under the License. import os +from collections import defaultdict from typing import Any, Iterable, Optional import torch +from torch.multiprocessing.reductions import rebuild_cuda_tensor try: import vllm # noqa: F401 @@ -136,7 +138,7 @@ def update_weights_from_local_ipc_handles(self, local_device_ipc_handles): try: is_tensor_packed = local_device_ipc_handles[0] if is_tensor_packed: - _, all_handles, tensor_metadata = local_device_ipc_handles + _, all_handles, list_keys = local_device_ipc_handles else: _, name_and_handle_list = local_device_ipc_handles @@ -152,33 +154,40 @@ def update_weights_from_local_ipc_handles(self, local_device_ipc_handles): # Extract packed tensor from IPC handle dtype_to_packed_tensor = {} for dtype, tensor_handle in all_handles: - func, args = tensor_handle + func = rebuild_cuda_tensor + args = tensor_handle[0] list_args = list(args) list_args[6] = device_id tensor = func(*list_args) dtype_to_packed_tensor[dtype] = tensor - # Unpack tensor to weights. Here we only return a view of the tensor to avoid - # using extra memory. - for key, metadata in tensor_metadata.items(): - # dtype for the 1st and 2nd steps may be different (e.g. e_score_correction_bias) - if isinstance(metadata, tuple): - # use dtype of current step - offset, dtype = metadata - shape, _, size = self.state_dict_info[key] - # update record - self.state_dict_info[key] = (shape, dtype, size) - else: - offset = metadata - shape, dtype, size = self.state_dict_info[key] - tensor = dtype_to_packed_tensor[dtype][offset : offset + size].view( - *shape + weights = [] + dtype_to_offset = defaultdict(lambda: 0) + for key in list_keys: + shape, dtype, size = self.state_dict_info[key] + weights.append( + ( + key, + dtype_to_packed_tensor[dtype][ + dtype_to_offset[dtype] : dtype_to_offset[dtype] + size + ].view(*shape), + ) ) - weights.append((key, tensor)) + dtype_to_offset[dtype] += size + + expected_sizes = { + dtype: tensor.numel() + for dtype, tensor in dtype_to_packed_tensor.items() + } + assert dtype_to_offset == expected_sizes, ( + f"Packed tensor size mismatch: expected sizes from keys list {expected_sizes} != actual packed tensor sizes {dtype_to_offset}. " + f"This indicates the keys list order doesn't match the order used when packing tensors." + ) else: # Process each handle to get the tensor for name, handle in name_and_handle_list: - func, args = handle + func = rebuild_cuda_tensor + args = handle[0] list_args = list(args) list_args[6] = device_id tensor = func(*list_args) diff --git a/nemo_rl/models/megatron/refit_utils.py b/nemo_rl/models/megatron/refit_utils.py index 2463d6ae4f..af6ffa2634 100644 --- a/nemo_rl/models/megatron/refit_utils.py +++ b/nemo_rl/models/megatron/refit_utils.py @@ -156,7 +156,6 @@ def gather_params(model, keys: list[str], key_to_global_keys: dict[str, list[str if k is not None: gathered_params[k] = p - print(f"Time taken to gather params: {time.perf_counter() - st}") return gathered_params diff --git a/nemo_rl/models/policy/dtensor_policy_worker.py b/nemo_rl/models/policy/dtensor_policy_worker.py index 7448a5d97d..73e7cf3072 100644 --- a/nemo_rl/models/policy/dtensor_policy_worker.py +++ b/nemo_rl/models/policy/dtensor_policy_worker.py @@ -68,6 +68,7 @@ from nemo_rl.models.policy.utils import ( configure_expandable_segments, get_gpu_info, + get_handle_from_tensor, get_runtime_env_for_policy_worker, import_class_from_path, is_vllm_v1_engine_enabled, @@ -1235,8 +1236,6 @@ def prepare_weights_for_ipc(self) -> tuple[list[tuple[str, int]], float]: @torch.no_grad() def get_weights_ipc_handles(self, keys: Iterable[str]) -> dict[str, Any]: - from torch.multiprocessing.reductions import reduce_tensor - assert self._held_sharded_state_dict_reference is not None, ( "prepare_weights_for_ipc must be called before get_weights_ipc_handles" ) @@ -1266,7 +1265,7 @@ def get_weights_ipc_handles(self, keys: Iterable[str]) -> dict[str, Any]: # Create handles for the tensors all_handles = [] for key, p in converted_params.items(): - handle = reduce_tensor(p.detach()) + handle = get_handle_from_tensor(p) all_handles.append((key, handle)) # (pack_tensor_for_ipc: bool, handles: list) diff --git a/nemo_rl/models/policy/megatron_policy_worker.py b/nemo_rl/models/policy/megatron_policy_worker.py index 5655f52444..3b5786d3d5 100644 --- a/nemo_rl/models/policy/megatron_policy_worker.py +++ b/nemo_rl/models/policy/megatron_policy_worker.py @@ -51,6 +51,7 @@ ) from megatron.core.pipeline_parallel import get_forward_backward_func from megatron.core.rerun_state_machine import get_rerun_state_machine +from megatron.core.transformer.module import Float16Module from megatron.inference.text_generation.mcore_engine_server import ( run_mcore_engine, ) @@ -118,6 +119,7 @@ from nemo_rl.models.policy.utils import ( configure_expandable_segments, get_gpu_info, + get_handle_from_tensor, get_megatron_checkpoint_dir, get_runtime_env_for_policy_worker, ) @@ -185,11 +187,25 @@ def setup_megatron_model( if policy_cfg["megatron_cfg"]["freeze_moe_router"]: def freeze_moe_router(model_module): + # Handle both wrapped (Float16Module) and unwrapped models + if isinstance(model_module, Float16Module): + model_module = model_module.module for layer in model_module.decoder.layers: if hasattr(layer.mlp, "router"): layer.mlp.router.weight.requires_grad = False + # Re-enable float32 expert bias for moe router to avoid parameter dtype inconsistency + # see https://github.com/NVIDIA/Megatron-LM/blob/e6c510ff3c1159f8955589b26f7c395bdf0607d9/megatron/core/transformer/moe/router.py#L149 + def re_enable_float32_expert_bias(model_module): + # Handle both wrapped (Float16Module) and unwrapped models + if isinstance(model_module, Float16Module): + model_module = model_module.module + for layer in model_module.decoder.layers: + if hasattr(layer.mlp, "router"): + layer.mlp.router._maintain_float32_expert_bias() + model_post_init_fns.append(freeze_moe_router) + model_post_init_fns.append(re_enable_float32_expert_bias) # Model, optimizer, and learning rate. model = get_model_from_config( @@ -699,7 +715,7 @@ def __init__( # vars used for refit ## will be initialized in prepare_refit_info - self.refit_param_info_hf = None + self.refit_param_info_mcore = None self.local_key_to_global_keys = None ## used for streaming update inference engine weights self._held_gather_buffer = None @@ -1362,20 +1378,18 @@ def report_device_id(self) -> str: @torch.no_grad() def prepare_refit_info(self) -> None: # Get parameter info for refit - ## param_info: list of ((name, shape, dtype), size_in_bytes) tuples - # Cannot cache refit_param_info_mcore since dtype and size_in_bytes for the 1st and 2nd steps may be different - ## e.g. e_score_correction_bias - refit_param_info_mcore = get_param_info(self.model, self.dtype) + # param_info: list of ((name, shape, dtype), size_in_bytes) tuples + self.refit_param_info_mcore = get_param_info(self.model, self.dtype) # Create a map that maps any local parameter name to a list of global parameter names. # This map is repeatedly used by parameter gatherring phase during refit of every step. self.local_key_to_global_keys = get_local_key_to_global_keys( - self.model, state_dict_info=refit_param_info_mcore + self.model, state_dict_info=self.refit_param_info_mcore ) # Collect tensor metadata for refit - self.refit_param_info_hf = {} - for key, _ in refit_param_info_mcore: + refit_param_info_hf = {} + for key, _ in self.refit_param_info_mcore: # gather megatron params gathered_megatron_params = gather_params( self.model, @@ -1388,15 +1402,14 @@ def prepare_refit_info(self) -> None: ) # collect tensor metadata for name, tensor in gathered_hf_params.items(): - self.refit_param_info_hf[name] = ( + refit_param_info_hf[name] = ( tensor.shape, tensor.dtype, tensor.numel(), ) - return self.refit_param_info_hf + return refit_param_info_hf - @torch.no_grad() def prepare_weights_for_ipc(self) -> tuple[list[tuple[str, int]], float]: """Prepare Megatron model weights for IPC transfer to vLLM. @@ -1405,12 +1418,6 @@ def prepare_weights_for_ipc(self) -> tuple[list[tuple[str, int]], float]: """ from nemo_rl.utils.nvml import get_free_memory_bytes - # Get parameter info for refit - ## param_info: list of ((name, shape, dtype), size_in_bytes) tuples - # Cannot cache refit_param_info_mcore since dtype and size_in_bytes for the 1st and 2nd steps may be different - ## e.g. e_score_correction_bias - refit_param_info_mcore = get_param_info(self.model, self.dtype) - # Collect current available memory for refit ## Get current device index from torch device_idx = torch.cuda.current_device() @@ -1420,7 +1427,7 @@ def prepare_weights_for_ipc(self) -> tuple[list[tuple[str, int]], float]: memory_ratio = os.getenv("NRL_REFIT_BUFFER_MEMORY_RATIO", "0.2") total_available_bytes *= float(memory_ratio) - return refit_param_info_mcore, total_available_bytes + return self.refit_param_info_mcore, total_available_bytes # Temporary fix, 'keys' is a kwarg due to some sort of ray bug @torch.no_grad() @@ -1448,7 +1455,6 @@ def get_weights_ipc_handles(self, *, keys: list[str]) -> dict[str, Any]: # Get device UUID for IPC handles device_uuid = self.report_device_id() - from torch.multiprocessing.reductions import reduce_tensor # Create IPC handles for each parameter tensor_number_threshold = os.getenv( @@ -1463,25 +1469,9 @@ def get_weights_ipc_handles(self, *, keys: list[str]) -> dict[str, Any]: # Pack tensors in gathered_hf_params into consolidated tensors by dtype # First calculate total size needed for each dtype type_to_total_size = defaultdict(lambda: 0) - tensor_metadata = dict() # Record offset of the tensor for key, tensor in gathered_hf_params.items(): - # dtype for the 1st and 2nd steps may be different (e.g. e_score_correction_bias) - if tensor.dtype == self.refit_param_info_hf[key][1]: - tensor_metadata[key] = type_to_total_size[tensor.dtype] - else: - # also send dtype if it changes - tensor_metadata[key] = ( - type_to_total_size[tensor.dtype], - tensor.dtype, - ) - # update record - self.refit_param_info_hf[key] = ( - tensor.shape, - tensor.dtype, - tensor.numel(), - ) type_to_total_size[tensor.dtype] += tensor.numel() # Allocate consolidated tensors for each dtype @@ -1495,31 +1485,34 @@ def get_weights_ipc_handles(self, *, keys: list[str]) -> dict[str, Any]: for dtype, total_size in type_to_total_size.items() } + dtype_to_offset = defaultdict(lambda: 0) # Copy tensors into consolidated buffers for key, tensor in gathered_hf_params.items(): - offset = tensor_metadata[key] - if isinstance(offset, tuple): - offset, _ = offset dtype = tensor.dtype size = tensor.numel() - packed_tensors[dtype][offset : offset + size].copy_( - tensor.detach().view(-1) - ) + packed_tensors[dtype][ + dtype_to_offset[dtype] : dtype_to_offset[dtype] + size + ].copy_(tensor.detach().view(-1)) + dtype_to_offset[dtype] += size # Create IPC handles for consolidated tensors all_handles = [ - (dtype, reduce_tensor(tensor.detach())) + (dtype, get_handle_from_tensor(tensor)) for dtype, tensor in packed_tensors.items() ] # Store reference to prevent garbage collection self._held_gather_buffer = packed_tensors - serialized = (pack_tensor_for_ipc, all_handles, tensor_metadata) + serialized = ( + pack_tensor_for_ipc, + all_handles, + tuple(gathered_hf_params.keys()), + ) else: all_handles = [] for key, tensor in gathered_hf_params.items(): - handle = reduce_tensor(tensor.detach()) + handle = get_handle_from_tensor(tensor) all_handles.append((key, handle)) self._held_gather_buffer = gathered_hf_params serialized = (False, all_handles) diff --git a/nemo_rl/models/policy/utils.py b/nemo_rl/models/policy/utils.py index a61e5e20b7..678d5d89c0 100644 --- a/nemo_rl/models/policy/utils.py +++ b/nemo_rl/models/policy/utils.py @@ -220,3 +220,11 @@ def get_megatron_checkpoint_dir() -> str: ) print(f"Using default megatron checkpoint dir: {checkpoint_dir}") return checkpoint_dir + + +def get_handle_from_tensor(tensor: torch.Tensor) -> tuple[Any]: + """Get IPC handle from a tensor.""" + from torch.multiprocessing.reductions import reduce_tensor + + # skip serializing the function for better refit performance + return reduce_tensor(tensor.detach())[1:] diff --git a/pyrefly.toml b/pyrefly.toml index 2fa6327786..6442672edf 100644 --- a/pyrefly.toml +++ b/pyrefly.toml @@ -85,6 +85,7 @@ project-includes = [ "nemo_rl/models/dtensor/parallelize.py", "nemo_rl/models/generation/__init__.py", "nemo_rl/models/generation/interfaces.py", + "nemo_rl/models/generation/vllm_backend.py", "nemo_rl/models/huggingface/__init__.py", "nemo_rl/models/megatron/__init__.py", "nemo_rl/models/megatron/community_import.py", From b051b70401d952c6e2a1d7afaeca3eb66cc5a81d Mon Sep 17 00:00:00 2001 From: Xuehan Xiong Date: Wed, 30 Jul 2025 21:29:41 -0700 Subject: [PATCH 12/23] fix: fix the return type of `execute()`. (#808) Signed-off-by: Xuehan Signed-off-by: tpoisonooo --- nemo_rl/environments/code_environment.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/nemo_rl/environments/code_environment.py b/nemo_rl/environments/code_environment.py index 029b9cd1c0..4c110c8e09 100644 --- a/nemo_rl/environments/code_environment.py +++ b/nemo_rl/environments/code_environment.py @@ -98,7 +98,9 @@ def format_result( result = result[len(lookahead) :] return result - def execute(self, message_batch: str, metadata_batch: List[CodeEnvMetadata]) -> str: + def execute( + self, message_batch: str, metadata_batch: List[CodeEnvMetadata] + ) -> Tuple[List[Dict[str, str]], List[bool], List[Any]]: """Execute code in a sandboxed environment.""" results = [] terminateds = [] From 8636efa64bd6b8f44744901057d534d1901dea8a Mon Sep 17 00:00:00 2001 From: Anna Shors Date: Thu, 31 Jul 2025 10:03:04 -0700 Subject: [PATCH 13/23] docs: add usage example for mcore --> hf converter (#807) Signed-off-by: ashors1 Signed-off-by: tpoisonooo --- README.md | 11 +++++++++++ docs/design-docs/checkpointing.md | 16 ++++++++++++++-- examples/converters/convert_megatron_to_hf.py | 7 +++++++ 3 files changed, 32 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 04c72232d9..dab00ba6a8 100644 --- a/README.md +++ b/README.md @@ -412,6 +412,17 @@ uv run python examples/converters/convert_dcp_to_hf.py \ --dcp-ckpt-path results/grpo/step_170/policy/weights/ \ --hf-ckpt-path results/grpo/hf ``` + +If you have a model saved in Megatron format, you can use the following command to convert it to Hugging Face format prior to running evaluation: + +```sh +# Example for a GRPO checkpoint at step 170 +uv run python examples/converters/convert_megatron_to_hf.py \ + --config results/grpo/step_170/config.yaml \ + --dcp-ckpt-path results/grpo/step_170/policy/weights/iter_0000000 \ + --hf-ckpt-path results/grpo/hf +``` + > **Note:** Adjust the paths according to your training output directory structure. For an in-depth explanation of checkpointing, refer to the [Checkpointing documentation](docs/design-docs/checkpointing.md). diff --git a/docs/design-docs/checkpointing.md b/docs/design-docs/checkpointing.md index 5d3feae680..185b6e0358 100644 --- a/docs/design-docs/checkpointing.md +++ b/docs/design-docs/checkpointing.md @@ -1,8 +1,10 @@ -# Checkpointing with Hugging Face Models +# Exporting Checkpoints to Hugging Face Format NeMo RL provides two checkpoint formats for Hugging Face models: Torch distributed and Hugging Face format. Torch distributed is used by default for efficiency, and Hugging Face format is provided for compatibility with Hugging Face's `AutoModel.from_pretrained` API. Note that Hugging Face format checkpoints save only the model weights, ignoring the optimizer states. It is recommended to use Torch distributed format to save intermediate checkpoints and to save a Hugging Face checkpoint only at the end of training. -A checkpoint converter is provided to convert a Torch distributed checkpoint checkpoint to Hugging Face format after training: +## Converting Torch Distributed Checkpoints to Hugging Face Format + +A checkpoint converter is provided to convert a Torch distributed checkpoint to Hugging Face format after training: ```sh uv run examples/converters/convert_dcp_to_hf.py --config= --dcp-ckpt-path= --hf-ckpt-path= @@ -17,3 +19,13 @@ CKPT_DIR=results/sft/step_10 uv run examples/converters/convert_dcp_to_hf.py --config=$CKPT_DIR/config.yaml --dcp-ckpt-path=$CKPT_DIR/policy/weights --hf-ckpt-path=${CKPT_DIR}-hf rsync -ahP $CKPT_DIR/policy/tokenizer ${CKPT_DIR}-hf/ ``` + +## Converting Megatron Checkpoints to Hugging Face Format + +For models that were originally trained using the Megatron-LM backend, a separate converter is available to convert Megatron checkpoints to Hugging Face format. This script requires Megatron-Core, so make sure to launch the conversion with the `mcore` extra. For example, + +```sh +CKPT_DIR=results/sft/step_10 + +uv run --extra mcore examples/converters/convert_megatron_to_hf.py --config=$CKPT_DIR/config.yaml --megatron-ckpt-path=$CKPT_DIR/policy/weights/iter_0000000/ --hf-ckpt-path= +``` diff --git a/examples/converters/convert_megatron_to_hf.py b/examples/converters/convert_megatron_to_hf.py index ea4501286e..3d362d4a30 100644 --- a/examples/converters/convert_megatron_to_hf.py +++ b/examples/converters/convert_megatron_to_hf.py @@ -18,6 +18,13 @@ from nemo_rl.models.megatron.community_import import export_model_from_megatron +""" NOTE: this script requires mcore. Make sure to launch with the mcore extra: +uv run --extra mcore python examples/converters/convert_megatron_to_hf.py \ + --config /config.yaml \ + --megatron-ckpt-path /policy/weights/iter_xxxxx \ + --hf-ckpt-path +""" + def parse_args(): """Parse command line arguments.""" From dc93f58816e9959e988f1bc90a02dad03b56f0aa Mon Sep 17 00:00:00 2001 From: Anna Shors Date: Thu, 31 Jul 2025 12:23:38 -0700 Subject: [PATCH 14/23] docs: documentation and unit test for env var precedence (#806) Signed-off-by: ashors1 Signed-off-by: tpoisonooo --- docs/design-docs/env-vars.md | 31 +++++ docs/index.md | 1 + tests/unit/distributed/test_worker_groups.py | 131 ++++++++++++++++++- 3 files changed, 162 insertions(+), 1 deletion(-) create mode 100644 docs/design-docs/env-vars.md diff --git a/docs/design-docs/env-vars.md b/docs/design-docs/env-vars.md new file mode 100644 index 0000000000..da2bf2db6b --- /dev/null +++ b/docs/design-docs/env-vars.md @@ -0,0 +1,31 @@ +# Environment Variable Precedence in NeMo RL + +There are a number of ways to pass environment variables to Ray workers in NeMo RL. This document explains each of the methods and why they are useful. + +## Precedence Order + +### 1. Ray Runtime Environment Variables (lowest) +- Set via `ray.remote(runtime_env={'env_vars': {...}})` decorators. +- Applied to all instances of specific worker classes. These define the default environment variables for the class if not overwritten by a method of higher precedence. +- Example: `@ray.remote(runtime_env=get_runtime_env_for_policy_worker("megatron_policy_worker"))`. See [here](https://github.com/NVIDIA-NeMo/RL/blob/def76820d7838c63c1ee4900e63f73a93d927ff2/nemo_rl/models/policy/megatron_policy_worker.py#L338) where `get_runtime_env_for_policy_worker` will be applied to all instances of `MegatronPolicyWorker`. + +### 2. System-level Environment Variables (medium) +- Set via `export` in shell or `os.environ` in Python. +- Useful for controlling environment variables from a high level. If not overwritten by higher priority methods, all workers will inherit these environment variables. +- Example: `export HF_TOKEN=` + +### 3. YAML Configuration `env_vars` (high) +- Set in YAML config files under `policy.megatron_cfg.env_vars` or `policy.dtensor_cfg.env_vars`. +- Useful for controlling environment variables on an experiment level. +- Example: + ```yaml + policy: + megatron_cfg: + env_vars: + PYTORCH_CUDA_ALLOC_CONF: "expandable_segments:False" + ``` + +### 4. Worker-specific `configure_worker` Method (highest) +- Set via static `configure_worker` method in worker classes. +- Applied to specific worker instances based on configuration. +- See an example in `VllmGenerationWorker` [here](https://github.com/NVIDIA-NeMo/RL/blob/def76820d7838c63c1ee4900e63f73a93d927ff2/nemo_rl/models/generation/vllm.py#L88). diff --git a/docs/index.md b/docs/index.md index 6efa366e89..e39423a23c 100644 --- a/docs/index.md +++ b/docs/index.md @@ -68,4 +68,5 @@ design-docs/loss-functions.md design-docs/fsdp2-parallel-plan.md design-docs/training-backends.md design-docs/sequence-packing-and-dynamic-batching.md +design-docs/env-vars.md ``` diff --git a/tests/unit/distributed/test_worker_groups.py b/tests/unit/distributed/test_worker_groups.py index 57976a94d8..04daa4335f 100644 --- a/tests/unit/distributed/test_worker_groups.py +++ b/tests/unit/distributed/test_worker_groups.py @@ -104,6 +104,43 @@ def configure_worker(num_gpus, bundle_indices): return resources, env_vars_update, init_kwargs_update +@ray.remote( + runtime_env={ + "env_vars": { + "TEST_VAR_1": "ray_remote_runtime_value", + "TEST_VAR_3": "ray_remote_runtime_value", + "RAY_REMOTE_VAR": "ray_remote_only", + } + } +) +class PrecedenceActor: + """Actor with configure_worker method that sets environment variables.""" + + _default_options = {} + + def __init__(self, *args, **kwargs): + self.init_args = args + self.init_kwargs = kwargs + self.env_vars = dict(os.environ) + + def get_env_var(self, var_name): + return self.env_vars.get(var_name) + + def get_all_env_vars(self): + return dict(self.env_vars) + + @classmethod + def configure_worker(cls, num_gpus, bundle_indices=None): + return ( + {"num_gpus": num_gpus}, # resources + { + "TEST_VAR_1": "configure_worker_value", + "WORKER_VAR": "worker_only", + }, # env_vars + {}, # init_kwargs + ) + + MY_TEST_ACTOR_FQN = f"{MyTestActor.__module__}.MyTestActor" @@ -138,7 +175,6 @@ def check_nsight_config(self): def register_test_actor(request): # Default to PY_EXECUTABLES.SYSTEM if no param is given py_exec_to_register = getattr(request, "param", PY_EXECUTABLES.SYSTEM) - original_registry_value = ACTOR_ENVIRONMENT_REGISTRY.get(MY_TEST_ACTOR_FQN) ACTOR_ENVIRONMENT_REGISTRY[MY_TEST_ACTOR_FQN] = py_exec_to_register @@ -152,6 +188,27 @@ def register_test_actor(request): ACTOR_ENVIRONMENT_REGISTRY[MY_TEST_ACTOR_FQN] = original_registry_value +# Create fixtures for each actor class +@pytest.fixture +def register_precedence_actor(request): + """Fixture for ConfigureWorkerActor.""" + # Default to PY_EXECUTABLES.SYSTEM if no param is given + py_exec_to_register = getattr(request, "param", PY_EXECUTABLES.SYSTEM) + actor_fqn = f"{PrecedenceActor.__module__}.PrecedenceActor" + + original_registry_value = ACTOR_ENVIRONMENT_REGISTRY.get(actor_fqn) + ACTOR_ENVIRONMENT_REGISTRY[actor_fqn] = py_exec_to_register + + yield actor_fqn # Provide the FQN to the test + + # Clean up: revert ACTOR_ENVIRONMENT_REGISTRY to its original state for this FQN + if actor_fqn in ACTOR_ENVIRONMENT_REGISTRY: # Check if key still exists + if original_registry_value is None: + del ACTOR_ENVIRONMENT_REGISTRY[actor_fqn] + else: + ACTOR_ENVIRONMENT_REGISTRY[actor_fqn] = original_registry_value + + @pytest.fixture def virtual_cluster(): # 1 node, 2 CPU bundles. use_gpus=False means num_gpus passed to workers will be 0. @@ -1063,3 +1120,75 @@ def test_get_nsight_config_output_format(): assert "env_vars" in combined_runtime_env_no_match assert "py_executable" in combined_runtime_env_no_match assert "nsight" not in combined_runtime_env_no_match + + +# Environment Variable Precedence Test +def test_environment_variable_precedence_full( + register_precedence_actor, virtual_cluster +): + """Test that the order of precedence is as follows (from highest to lowest): + - configure_worker + - RayWorkerGroup + - system + - @ray.remote runtime_env + """ + # Set up system environment variables + original_env = dict(os.environ) + os.environ["TEST_VAR_1"] = "system_value" + os.environ["TEST_VAR_2"] = "system_value" + os.environ["TEST_VAR_3"] = "system_value" + os.environ["TEST_VAR_4"] = "system_value" + + try: + # Create a worker builder with configure_worker method + builder = RayWorkerBuilder(register_precedence_actor) + + # Create RayWorkerGroup environment variables + env_vars = { + "TEST_VAR_1": "yaml_worker_group_value", + "TEST_VAR_2": "yaml_worker_group_value", + } + + # Create worker group + worker_group = RayWorkerGroup( + cluster=virtual_cluster, + remote_worker_builder=builder, + workers_per_node=1, + ## passing env_vars here mimics passing env vars from yaml config + ## because lm_policy automicatically passes env vars to RayWorkerGroup + env_vars=env_vars, + ) + + assert len(worker_group.workers) == 1 + worker = worker_group.workers[0] + + # Verify configure_worker has highest precedence + assert ( + ray.get(worker.get_env_var.remote("TEST_VAR_1")) == "configure_worker_value" + ) # configure_worker overrides all + assert ( + ray.get(worker.get_env_var.remote("TEST_VAR_2")) + == "yaml_worker_group_value" + ) # RayWorkerGroup value preserved + assert ( + ray.get(worker.get_env_var.remote("TEST_VAR_3")) == "system_value" + ) # system value takes precedence over worker env vars + assert ( + ray.get(worker.get_env_var.remote("TEST_VAR_4")) == "system_value" + ) # system value preserved + assert ( + ray.get(worker.get_env_var.remote("WORKER_VAR")) == "worker_only" + ) # configure_worker value set + assert ( + ray.get(worker.get_env_var.remote("RAY_REMOTE_VAR")) == "ray_remote_only" + ) # ray.remote runtime_env value preserved + + worker_group.shutdown(force=True) + + finally: + # Restore original environment + for key in ["TEST_VAR_1", "TEST_VAR_2", "TEST_VAR_3", "TEST_VAR_4"]: + if key in original_env: + os.environ[key] = original_env[key] + else: + os.environ.pop(key, None) From 9ddf0db4ea083a6b459291b92be556e5cb136f6e Mon Sep 17 00:00:00 2001 From: Parth Chadha Date: Thu, 31 Jul 2025 15:48:26 -0700 Subject: [PATCH 15/23] =?UTF-8?q?fix:=20Fix=20incorrect=20indexing=20of=20?= =?UTF-8?q?message=20which=20cuts=20off=20user=20message=20when=20we?= =?UTF-8?q?=E2=80=A6=20(#815)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Signed-off-by: Parth Chadha --- examples/run_grpo_math.py | 2 +- tests/unit/utils/test_logger.py | 21 +++++++++++++++++++++ 2 files changed, 22 insertions(+), 1 deletion(-) diff --git a/examples/run_grpo_math.py b/examples/run_grpo_math.py index 673322eb61..d36320330d 100644 --- a/examples/run_grpo_math.py +++ b/examples/run_grpo_math.py @@ -90,7 +90,7 @@ def hf_data_processor( add_special_tokens=False, ) user_message["token_ids"] = tokenizer(message, return_tensors="pt")["input_ids"][0] - user_message["content"] = message[0] + user_message["content"] = message message_log.append(user_message) length = sum(len(m["token_ids"]) for m in message_log) diff --git a/tests/unit/utils/test_logger.py b/tests/unit/utils/test_logger.py index 147014d7da..ebb25f78d0 100644 --- a/tests/unit/utils/test_logger.py +++ b/tests/unit/utils/test_logger.py @@ -27,6 +27,7 @@ WandbLogger, SwanlabLogger, flatten_dict, + print_message_log_samples, ) @@ -1625,3 +1626,23 @@ def test_log_hyperparams_with_mlflow( mock_tb_instance.log_hyperparams.assert_called_once_with(params) mock_mlflow_instance.log_hyperparams.assert_called_once_with(params) mock_swanlab_instance.log_hyperparams.assert_called_once_with(params) + + +def test_print_message_log_samples(capsys): + """Test that print_message_log_samples displays full content correctly.""" + # Test message with full content (verifies our bug fix) + message_logs = [ + [ + {"role": "user", "content": "What is 2+2?"}, + {"role": "assistant", "content": "2+2 = 4"}, + ] + ] + rewards = [1.0] + + print_message_log_samples(message_logs, rewards, num_samples=1, step=0) + + captured = capsys.readouterr() + # Verify content is displayed properly + assert "What is 2+2?" in captured.out + assert "2+2 = 4" in captured.out + assert "Sample 1 | Reward: 1.0000" in captured.out From b48faf3abcc09958d04e9b61683968a7d33c574e Mon Sep 17 00:00:00 2001 From: Terry Kong Date: Thu, 31 Jul 2025 15:49:02 -0700 Subject: [PATCH 16/23] docs: add a section on our config design (#810) Signed-off-by: Terry Kong Signed-off-by: Terry Kong Co-authored-by: jgerh <163925524+jgerh@users.noreply.github.com> Signed-off-by: tpoisonooo --- docs/design-docs/design-and-philosophy.md | 24 ++++++++++++++++++++++- 1 file changed, 23 insertions(+), 1 deletion(-) diff --git a/docs/design-docs/design-and-philosophy.md b/docs/design-docs/design-and-philosophy.md index eec3b399a7..a2327c7428 100644 --- a/docs/design-docs/design-and-philosophy.md +++ b/docs/design-docs/design-and-philosophy.md @@ -1,6 +1,6 @@ # Design and Philosophy -This section introduces the NeMo RL APIs and addresses the challenges of online Reinforcement Learning (RL). Coordinating various software components, known as RL Actors, requires effective resource allocation, isolation, coordination, and communication. Our design philosophy focuses on creating modular abstractions for these tasks, ensuring scalability from one GPU to thousands, regardless of the RL Actor's implementation. +This section introduces the NeMo RL APIs, configuration patterns with TypedDicts, and addresses the challenges of online Reinforcement Learning (RL). Coordinating various software components, known as RL Actors, requires effective resource allocation, isolation, coordination, and communication. Our design philosophy focuses on creating modular abstractions for these tasks, ensuring scalability from one GPU to thousands, regardless of the RL Actor's implementation. ## Motivation @@ -112,3 +112,25 @@ def grpo_train( policy.train(generations, logprobs, reference_logprobs, GRPOLossFn) ``` For a complete implementation of GRPO, including validation, checkpointing, memory movement, and the data processing steps not detailed here, see [grpo_train](../../nemo_rl/algorithms/grpo.py). + + +### TypedDict and Configuration Defaults + +In NeMo RL, we use YAML files for configuration and load them with `omegaconf` into a recursive `dict`. Within the codebase, +the root `dict` and sub-`dict`s are typed with `TypedDict` subclasses to provide type hints when accessing attributes. This +allows our type checker to validate if an undocumented attribute is accessed when not present in the `TypedDict` subclass, +or to identify an incompatible type. + +We chose this design because it's simple and gives users the flexibility to use older configuration files without encountering errors during config loading due to unexpected attributes, whether obsolete or user defined. While we considered using dataclasses or other structured configuration formats, those approaches introduce more boilerplate and would require config versioning to support loading across different versions of NeMo RL. + +We follow a few design principles regarding configuration: + +1. We forbid defaults in the code, except in limited cases (e.g., alpha features). Defaults should be defined in YAML configuration files. Setting defaults in code makes it difficult to trace where values originate during debugging. + * Forbidden examples include: + * `grpo_config.get("num_prompts_per_step", 32)` + * `policy_config.get("model_name", "meta-llama/Llama-3.1-8B-Instruct")` + * Acceptable examples: + * If an attribute is typed `typing.NotRequired[...]`, it is okay for the code to check for absence/`None`, e.g., `assert "milestones" in scheduler_cfg` or `if "milestones" in scheduler_cfg` +1. All configs under [examples/configs/*.yaml](https://github.com/NVIDIA-NeMo/RL/tree/main/examples/configs) are exemplars and should contain the defaults for `typing.Required` or `typing.NotRequired` attributes, along with accompanying documentation. + * All configs under [examples/configs/recipes/**/*.yaml](https://github.com/NVIDIA-NeMo/RL/tree/main/examples/configs/recipes) do not require documentation and are snapshots of functional configurations. +1. All configs under [examples/configs/**/*.yaml](https://github.com/NVIDIA-NeMo/RL/tree/main/examples/configs) should adhere to their `TypedDict` subclass configuration. Unit tests in [tests/unit/test_config_validation.py](https://github.com/NVIDIA-NeMo/RL/blob/main/tests/unit/test_config_validation.py) are run to validate compliance. From 843735f0e821afe0de739ae954e9bacaa6b25b4c Mon Sep 17 00:00:00 2001 From: yuki <48991475+yuki-666@users.noreply.github.com> Date: Fri, 1 Aug 2025 06:56:05 +0800 Subject: [PATCH 17/23] fix: fix dynamo cache (#784) Signed-off-by: Yuki Huang Co-authored-by: Parth Chadha Signed-off-by: tpoisonooo --- nemo_rl/models/policy/dtensor_policy_worker.py | 5 +++++ nemo_rl/models/policy/megatron_policy_worker.py | 5 +++++ nemo_rl/models/policy/utils.py | 10 ++++++++++ 3 files changed, 20 insertions(+) diff --git a/nemo_rl/models/policy/dtensor_policy_worker.py b/nemo_rl/models/policy/dtensor_policy_worker.py index 73e7cf3072..8c0198784b 100644 --- a/nemo_rl/models/policy/dtensor_policy_worker.py +++ b/nemo_rl/models/policy/dtensor_policy_worker.py @@ -66,6 +66,7 @@ ReferenceLogprobOutputSpec, ) from nemo_rl.models.policy.utils import ( + configure_dynamo_cache, configure_expandable_segments, get_gpu_info, get_handle_from_tensor, @@ -161,6 +162,10 @@ def __init__( if not self.is_generation_colocated: os.environ["NCCL_CUMEM_ENABLE"] = "1" + # Disable dynamo autotune_local_cache to avoid crash when there's already a cache + # with different order of node_bundles + configure_dynamo_cache() + # Only enable expandable_segments on Hopper and newer architectures (compute capability 9.x+) configure_expandable_segments() diff --git a/nemo_rl/models/policy/megatron_policy_worker.py b/nemo_rl/models/policy/megatron_policy_worker.py index 3b5786d3d5..aa1f349b2b 100644 --- a/nemo_rl/models/policy/megatron_policy_worker.py +++ b/nemo_rl/models/policy/megatron_policy_worker.py @@ -117,6 +117,7 @@ ReferenceLogprobOutputSpec, ) from nemo_rl.models.policy.utils import ( + configure_dynamo_cache, configure_expandable_segments, get_gpu_info, get_handle_from_tensor, @@ -392,6 +393,10 @@ def __init__( "tracked in https://github.com/NVIDIA-NeMo/RL/issues/720" ) + # Disable dynamo autotune_local_cache to avoid crash when there's already a cache + # with different order of node_bundles + configure_dynamo_cache() + # Only enable expandable_segments on Hopper and newer architectures (compute capability 9.x+) configure_expandable_segments() diff --git a/nemo_rl/models/policy/utils.py b/nemo_rl/models/policy/utils.py index 678d5d89c0..c09a201268 100644 --- a/nemo_rl/models/policy/utils.py +++ b/nemo_rl/models/policy/utils.py @@ -183,6 +183,16 @@ def configure_expandable_segments() -> None: ) +def configure_dynamo_cache() -> None: + """Disable dynamo autotune_local_cache. + + Dynamo may fail at cached_autotune when there's already a cache with different order of node_bundles. + Disable autotune_local_cache as a workaround. + See https://github.com/pytorch/pytorch/issues/153791 for more details. + """ + torch._inductor.config.autotune_local_cache = False + + def get_runtime_env_for_policy_worker(policy_worker_name: str) -> dict[str, Any]: """Get runtime environment configuration for policy workers. From 2fb7f84df8fb6fe71a0c6b1031a52441e4809ff3 Mon Sep 17 00:00:00 2001 From: Zhiyu Li Date: Fri, 1 Aug 2025 15:56:19 -0700 Subject: [PATCH 18/23] feat: add throughput/prompt_length/total_num_tokens metrics (#781) Signed-off-by: Zhiyu Li Signed-off-by: Zhiyu Li Signed-off-by: tpoisonooo --- nemo_rl/algorithms/grpo.py | 24 +++++++++++++++++++++++- 1 file changed, 23 insertions(+), 1 deletion(-) diff --git a/nemo_rl/algorithms/grpo.py b/nemo_rl/algorithms/grpo.py index 9f9273ac8c..fceb2173c6 100644 --- a/nemo_rl/algorithms/grpo.py +++ b/nemo_rl/algorithms/grpo.py @@ -765,10 +765,19 @@ def grpo_train( "loss": train_results["loss"].numpy(), "reward": rewards.numpy(), "grad_norm": train_results["grad_norm"].numpy(), + "mean_prompt_length": repeated_batch["length"].numpy(), + "total_num_tokens": input_lengths.numpy(), } metrics.update(train_results["all_mb_metrics"]) for k, v in metrics.items(): - if k in {"lr", "wd", "reward", "global_valid_seqs", "global_valid_toks"}: + if k in { + "lr", + "wd", + "reward", + "global_valid_seqs", + "global_valid_toks", + "mean_prompt_length", + }: metrics[k] = np.mean(v).item() else: metrics[k] = np.sum(v).item() @@ -801,6 +810,19 @@ def grpo_train( print("\n⏱️ Timing:") # Display total time first, separately total_time = timing_metrics.get("total_step_time", 0) + + total_num_gpus = ( + master_config["cluster"]["num_nodes"] + * master_config["cluster"]["gpus_per_node"] + ) + metrics.update( + { + "tokens_per_sec_per_gpu": metrics["total_num_tokens"] + / total_time + / total_num_gpus + } + ) + print(f" • Total step time: {total_time:.2f}s") # Display all other timing metrics From 98774d37b59d6b92ddc85d5e6f40bbc8c54ba7cf Mon Sep 17 00:00:00 2001 From: Zhiyu Li Date: Sat, 2 Aug 2025 22:16:40 -0700 Subject: [PATCH 19/23] fix: avoid duplicate bos by adding add_special_tokens=False (#747) Signed-off-by: Zhiyu Li Signed-off-by: tpoisonooo --- examples/run_grpo_math.py | 11 +++- nemo_rl/data/datasets.py | 42 ++++++++++++++ tests/unit/data/test_data_processor.py | 78 +++++++++++++++++++++++--- 3 files changed, 123 insertions(+), 8 deletions(-) diff --git a/examples/run_grpo_math.py b/examples/run_grpo_math.py index d36320330d..b12fd6cc23 100644 --- a/examples/run_grpo_math.py +++ b/examples/run_grpo_math.py @@ -89,7 +89,16 @@ def hf_data_processor( add_generation_prompt=True, add_special_tokens=False, ) - user_message["token_ids"] = tokenizer(message, return_tensors="pt")["input_ids"][0] + # add bos token if not in chat template + bos_token_in_chat_template = tokenizer.chat_template.startswith( + "{{- bos_token }}" + ) or tokenizer.chat_template.startswith("{{ bos_token }}") + + user_message["token_ids"] = tokenizer( + message, + return_tensors="pt", + add_special_tokens=not bos_token_in_chat_template, + )["input_ids"][0] user_message["content"] = message message_log.append(user_message) diff --git a/nemo_rl/data/datasets.py b/nemo_rl/data/datasets.py index 2b844fc013..7d18d0f232 100644 --- a/nemo_rl/data/datasets.py +++ b/nemo_rl/data/datasets.py @@ -63,6 +63,7 @@ def __init__( self.default_task_data_spec = default_task_data_spec self.task_data_processors = task_data_processors self.max_seq_length = max_seq_length + self._bos_checked = False if isinstance(task_data_processors, dict): # apply defaults to all task data specs @@ -111,6 +112,22 @@ def __getitem__(self, idx: int) -> DatumSpec: datum_spec = task_data_processor( entry, task_data_spec, self.tokenizer, self.max_seq_length, idx ) + + # Check the first processed item for BOS token assertion + if ( + not self._bos_checked + and "message_log" in datum_spec + and datum_spec["message_log"] + ): + first_message = datum_spec["message_log"][0] + if "token_ids" in first_message: + token_ids = first_message["token_ids"] + assert isinstance(token_ids, torch.Tensor), ( + f"token_ids must be a torch.Tensor, got {type(token_ids)}" + ) + assert_start_with_single_bos(token_ids, self.tokenizer) + self._bos_checked = True + return datum_spec @@ -282,3 +299,28 @@ def dpo_collate_fn( ) return train_data + + +def assert_start_with_single_bos( + token_ids: torch.Tensor, tokenizer: TokenizerType +) -> None: + """Assert that the first token is a BOS token and the second token is not a BOS token. + + Args: + token_ids: List of token IDs + tokenizer: Tokenizer + """ + if tokenizer.bos_token_id is not None: + token_ids_list = token_ids.tolist() + if len(token_ids_list) > 0: + assert token_ids_list[0] == tokenizer.bos_token_id, ( + f"Expected BOS token at the start of the message, but got {token_ids_list[0]}" + ) + if len(token_ids_list) > 1: + assert token_ids_list[1] != tokenizer.bos_token_id, ( + f"Expected non-BOS token at the second position of the message, but got {token_ids_list[1]}" + ) + else: + print( + f"skip assert_start_single_bos since Tokenizer {tokenizer.name_or_path} has no BOS token" + ) diff --git a/tests/unit/data/test_data_processor.py b/tests/unit/data/test_data_processor.py index dc88bebee3..397aacb0a1 100644 --- a/tests/unit/data/test_data_processor.py +++ b/tests/unit/data/test_data_processor.py @@ -14,23 +14,23 @@ import os import sys +from collections import defaultdict +import pytest from datasets import Dataset abspath = os.path.abspath(__file__) sys.path.append("/".join(abspath.split("/")[:-4])) +from examples.run_grpo_math import hf_data_processor from nemo_rl.algorithms.utils import get_tokenizer from nemo_rl.data.datasets import AllTaskProcessedDataset -from nemo_rl.data.interfaces import TaskDataSpec +from nemo_rl.data.hf_datasets.deepscaler import DeepScalerDataset +from nemo_rl.data.hf_datasets.openmathinstruct2 import OpenMathInstruct2Dataset +from nemo_rl.data.interfaces import TaskDataProcessFnCallable, TaskDataSpec from nemo_rl.data.processors import math_data_processor from nemo_rl.models.policy import TokenizerConfig -basic_tokenizer_test_config: TokenizerConfig = { - "name": "Qwen/Qwen2.5-Math-1.5B-Instruct", - "chat_template": "default", -} - def test_math_data_processor(): raw_dataset = Dataset.from_list( @@ -40,7 +40,12 @@ def test_math_data_processor(): ] ) - tokenizer = get_tokenizer(basic_tokenizer_test_config) + tokenizer = get_tokenizer( + TokenizerConfig( + name="Qwen/Qwen2.5-Math-1.5B-Instruct", + chat_template="default", + ) + ) math_task_spec = TaskDataSpec( task_name="math", @@ -58,3 +63,62 @@ def test_math_data_processor(): assert dataset[0]["extra_env_info"]["ground_truth"] == "answer1" assert dataset[1]["extra_env_info"]["ground_truth"] == "answer2" + + +@pytest.mark.hf_gated +@pytest.mark.parametrize( + "tokenizer_name", + [ + "meta-llama/Llama-3.2-1B-Instruct", + "Qwen/Qwen2.5-1.5B-Instruct", # no bos token + "google/gemma-3-1b-it", + "Qwen/Qwen3-0.6B", # no bos token + ], +) +@pytest.mark.parametrize( + "dataset_name", + [ + "openmathinstruct2", + "deepscaler", + ], +) +def test_math_hf_data_processor(tokenizer_name, dataset_name): + # Initialize dataset + if dataset_name == "openmathinstruct2": + data = OpenMathInstruct2Dataset() + elif dataset_name == "deepscaler": + data = DeepScalerDataset() + + # Setup tokenizer + tokenizer = get_tokenizer( + TokenizerConfig( + name=tokenizer_name, + chat_template="default", + ) + ) + + # Configure task specification + math_task_spec = TaskDataSpec( + task_name="math", + prompt_file=f"{os.path.dirname(abspath)}/../../../examples/prompts/cot.txt", + system_prompt_file=None, + ) + + task_data_processors: dict[str, tuple[TaskDataSpec, TaskDataProcessFnCallable]] = ( + defaultdict(lambda: (math_task_spec, hf_data_processor)) + ) + task_data_processors["math"] = (math_task_spec, hf_data_processor) + + dataset = AllTaskProcessedDataset( + dataset=data.formatted_ds["train"], + tokenizer=tokenizer, + default_task_data_spec=math_task_spec, + task_data_processors=task_data_processors, + max_seq_length=128, + ) + + # Test that the first item can be retrieved when the BOS token assertion passes + first_item = dataset[0] + assert first_item is not None + assert "message_log" in first_item + assert len(first_item["message_log"]) > 0 From 21a70eebabe84ffd612433c3287e0acf5bdbf504 Mon Sep 17 00:00:00 2001 From: Charlie Truong Date: Sun, 3 Aug 2025 09:39:21 -0500 Subject: [PATCH 20/23] ci: Refactor unit tests to run in concurrent jobs (#617) Signed-off-by: Charlie Truong Signed-off-by: tpoisonooo --- .github/actions/test-template/action.yml | 216 +++++++++++++++++ .github/copy-pr-bot.yml | 3 + .github/workflows/_run_test.yml | 160 ------------- .github/workflows/cicd-main.yml | 226 +++++++++++------- tests/docs/Docs_Tests.sh | 20 ++ tests/functional/L1_Functional_Tests_GPU.sh | 31 +++ tests/functional/dpo.sh | 3 +- tests/functional/eval.sh | 3 +- tests/functional/eval_async.sh | 3 +- tests/functional/grpo.sh | 3 +- tests/functional/grpo_megatron.sh | 3 +- tests/functional/grpo_multiturn.sh | 3 +- tests/functional/grpo_non_colocated.sh | 3 +- tests/functional/rm.sh | 3 +- tests/functional/sft.sh | 3 +- .../test_mcore_extra_installed_correctly.sh | 5 +- tests/run_unit.sh | 10 +- tests/unit/L0_Unit_Tests_Generation.sh | 27 +++ tests/unit/L0_Unit_Tests_Other.sh | 27 +++ tests/unit/L0_Unit_Tests_Policy.sh | 27 +++ .../models/generation/test_vllm_generation.py | 4 +- .../unit/models/policy/test_dtensor_worker.py | 4 +- 22 files changed, 529 insertions(+), 258 deletions(-) create mode 100644 .github/actions/test-template/action.yml create mode 100644 .github/copy-pr-bot.yml delete mode 100644 .github/workflows/_run_test.yml create mode 100644 tests/docs/Docs_Tests.sh create mode 100644 tests/functional/L1_Functional_Tests_GPU.sh create mode 100644 tests/unit/L0_Unit_Tests_Generation.sh create mode 100644 tests/unit/L0_Unit_Tests_Other.sh create mode 100644 tests/unit/L0_Unit_Tests_Policy.sh diff --git a/.github/actions/test-template/action.yml b/.github/actions/test-template/action.yml new file mode 100644 index 0000000000..3e16304fcf --- /dev/null +++ b/.github/actions/test-template/action.yml @@ -0,0 +1,216 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# 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 +# +# http://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. +name: "Test Template" +description: "Template for running NeMo tests in a containerized environment" + +inputs: + runner: + description: "Runner to use for test" + required: true + script: + description: "Test script to execute" + required: true + is_optional: + description: "Failure will cancel all other tests if set to true" + required: false + default: "false" + is_doc_test: + description: "Upload coverage as doc test" + required: false + default: "false" + is_unit_test: + description: "Upload coverage as unit test" + required: false + default: "false" + image: + description: "Image to use for test" + required: false + default: "nemo_rl_container" + cpu-only: + description: "Run tests on CPU only" + required: false + default: "false" + azure-client-id: + description: "Azure Client ID" + required: true + azure-tenant-id: + description: "Azure Tenant ID" + required: true + azure-subscription-id: + description: "Azure Subscription ID" + required: true + has-azure-credentials: + description: "Has Azure credentials" + required: false + default: "false" + +runs: + using: "composite" + steps: + - name: Install Azure CLI + if: ${{ inputs.has-azure-credentials == 'true' }} + shell: bash + run: | + curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash + + - name: Azure Login + if: ${{ inputs.has-azure-credentials == 'true' }} + uses: azure/login@v2 + with: + client-id: ${{ inputs.azure-client-id }} + tenant-id: ${{ inputs.azure-tenant-id }} + subscription-id: ${{ inputs.azure-subscription-id }} + + - name: Azure ACR Login + if: ${{ inputs.has-azure-credentials == 'true' }} + shell: bash + run: | + az acr login --name nemoci + + - name: Azure Fileshare + if: ${{ inputs.has-azure-credentials == 'true' && inputs.is_unit_test == 'false' && inputs.is_doc_test == 'false' }} + shell: bash + id: azure-fileshare + run: | + sudo apt update + sudo apt install -y cifs-utils + + RESOURCE_GROUP_NAME="azure-gpu-vm-runner_group" + STORAGE_ACCOUNT_NAME="nemocistorageaccount2" + FILE_SHARE_NAME="fileshare" + + MNT_ROOT="/media" + MNT_PATH="$MNT_ROOT/$STORAGE_ACCOUNT_NAME/$FILE_SHARE_NAME" + + echo "MNT_PATH=$MNT_PATH" | tee -a "$GITHUB_OUTPUT" + + sudo mkdir -p $MNT_PATH + + # Create a folder to store the credentials for this storage account and + # any other that you might set up. + CREDENTIAL_ROOT="/etc/smbcredentials" + sudo mkdir -p "/etc/smbcredentials" + + # Get the storage account key for the indicated storage account. + # You must be logged in with az login and your user identity must have + # permissions to list the storage account keys for this command to work. + STORAGE_ACCOUNT_KEY=$(az storage account keys list \ + --resource-group $RESOURCE_GROUP_NAME \ + --account-name $STORAGE_ACCOUNT_NAME \ + --query "[0].value" --output tsv | tr -d '"') + + # Create the credential file for this individual storage account + SMB_CREDENTIAL_FILE="$CREDENTIAL_ROOT/$STORAGE_ACCOUNT_NAME.cred" + if [ ! -f $SMB_CREDENTIAL_FILE ]; then + echo "username=$STORAGE_ACCOUNT_NAME" | sudo tee $SMB_CREDENTIAL_FILE > /dev/null + echo "password=$STORAGE_ACCOUNT_KEY" | sudo tee -a $SMB_CREDENTIAL_FILE > /dev/null + else + echo "The credential file $SMB_CREDENTIAL_FILE already exists, and was not modified." + fi + + # Change permissions on the credential file so only root can read or modify the password file. + sudo chmod 600 $SMB_CREDENTIAL_FILE + + # This command assumes you have logged in with az login + HTTP_ENDPOINT=$(az storage account show --resource-group $RESOURCE_GROUP_NAME --name $STORAGE_ACCOUNT_NAME --query "primaryEndpoints.file" --output tsv | tr -d '"') + SMB_PATH=$(echo $HTTP_ENDPOINT | cut -c7-${#HTTP_ENDPOINT})$FILE_SHARE_NAME + + STORAGE_ACCOUNT_KEY=$(az storage account keys list --resource-group $RESOURCE_GROUP_NAME --account-name $STORAGE_ACCOUNT_NAME --query "[0].value" --output tsv | tr -d '"') + + sudo mount -t cifs $SMB_PATH $MNT_PATH -o credentials=$SMB_CREDENTIAL_FILE,serverino,nosharesock,actimeo=30,mfsymlinks + + ls -al $MNT_PATH/TestData + + - name: Docker pull image + shell: bash + run: | + docker pull nemoci.azurecr.io/${{ inputs.image }}:${{ github.run_id }} + + - name: Create UUID + id: uuid + shell: bash + run: | + echo "id=$(uuidgen)" >> "$GITHUB_OUTPUT" + + - name: Checkout NeMo + uses: actions/checkout@v2 + env: + DIR: ${{ github.run_id }} + with: + submodules: 'recursive' + path: ${{ github.run_id }}/${{steps.uuid.outputs.id }}/nemo-rl + + - name: Run tests + id: test + shell: bash + run: | + COVERAGE_PREFIX=$([[ "${{ inputs.is_doc_test }}" == "true" ]] && echo "doc-test" || ([[ "${{ inputs.is_unit_test }}" == "true" ]] && echo "unit-test" || echo "e2e")) + echo "coverage-prefix=$COVERAGE_PREFIX" | tee -a "$GITHUB_OUTPUT" + + docker run --rm -u root --runtime=nvidia --gpus all \ + --shm-size=64g \ + --env TRANSFORMERS_OFFLINE=0 \ + --env HYDRA_FULL_ERROR=1 \ + --env HF_HOME=/home/TestData/nemo-rl/hf_home \ + --env HF_DATASETS_CACHE=/home/TestData/nemo-rl/hf_datasets_cache \ + --env NEMO_RL_REPO_DIR=/opt/nemo-rl \ + --env HF_TOKEN \ + --volume $(pwd)/${{ github.run_id }}/${{steps.uuid.outputs.id }}/nemo-rl:/opt/nemo-rl \ + --volume $GITHUB_ACTION_DIR:$GITHUB_ACTION_DIR \ + --volume /mnt/datadrive/TestData/nemo-rl/datasets:/opt/nemo-rl/datasets:ro \ + --volume /mnt/datadrive/TestData/nemo-rl/checkpoints:/home/TestData/nemo-rl/checkpoints:ro \ + --volume /mnt/datadrive/TestData/nemo-rl/hf_home/hub:/home/TestData/nemo-rl/hf_home/hub \ + --volume /mnt/datadrive/TestData/nemo-rl/hf_datasets_cache:/home/TestData/nemo-rl/hf_datasets_cache \ + nemoci.azurecr.io/nemo_rl_container:${{ github.run_id }} bash -eux -o pipefail -c '\ + git config --global --add safe.directory /opt/nemo-rl + # This is needed since we create virtualenvs in the workspace, so this allows it to be cleaned up if necessary + umask 000 + bash tests/${{ inputs.is_doc_test == 'true' && 'docs' || (inputs.is_unit_test == 'true' && 'unit' || 'functional') }}/${{ inputs.script }}.sh && \ + echo "Finished successfully." || echo "Did not finish."' 2>&1 | tee err.log + + - name: Check result + id: check + shell: bash + run: | + coverage_report=coverage-${{ steps.test.outputs.coverage-prefix }}-${{ github.run_id }}-$(uuidgen) + echo "coverage_report=$coverage_report" >> "$GITHUB_OUTPUT" + + IS_SUCCESS=$(tail -n 1 err.log | grep -q "Finished successfully." && echo "true" || echo "false") + + if [[ "$IS_SUCCESS" == "false" && "{% raw %}${{ inputs.is_optional }}" == "true" ]]; then + echo "::warning:: Test failed, but displayed as successful because it is marked as optional." + IS_SUCCESS=true + fi + + if [[ "$IS_SUCCESS" == "false" ]]; then + echo Test did not finish successfully. + exit 1 + fi + + exit $EXIT_CODE + + - name: Upload artifacts + uses: actions/upload-artifact@v4 + if: ${{ steps.check.outputs.coverage_report != 'none' }} + with: + name: ${{ steps.check.outputs.coverage_report }} + path: | + ${{ github.workspace }}/${{ github.run_id }}/${{steps.uuid.outputs.id }}/nemo-rl/tests/.coverage + include-hidden-files: true + + - name: Container shutdown + if: always() + shell: bash + run: | + rm -rf $(pwd)/${{ github.run_id }}/${{steps.uuid.outputs.id }} || true diff --git a/.github/copy-pr-bot.yml b/.github/copy-pr-bot.yml new file mode 100644 index 0000000000..4cfbdc7f05 --- /dev/null +++ b/.github/copy-pr-bot.yml @@ -0,0 +1,3 @@ +enabled: true +auto_sync_draft: false +auto_sync_ready: true diff --git a/.github/workflows/_run_test.yml b/.github/workflows/_run_test.yml deleted file mode 100644 index 4670905052..0000000000 --- a/.github/workflows/_run_test.yml +++ /dev/null @@ -1,160 +0,0 @@ -# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. -# -# 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 -# -# http://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. -name: ~test template - -on: - workflow_call: - inputs: - RUNNER: - type: string - description: Runner to use for test - required: true - TIMEOUT: - type: number - description: Max runtime of test in minutes - required: false - default: 10 - UNIT_TEST_SCRIPT: - type: string - description: Unit test script to execute - required: true - DOC_TEST_SCRIPT: - type: string - description: Doc test script to execute - required: true - FUNCTIONAL_TEST_SCRIPT: - type: string - description: Functional test script to execute - required: true - AFTER_SCRIPT: - type: string - description: Script to run after main test in container - required: false - default: ":" - FINAL_SCRIPT_EXTERNAL: - type: string - description: Script to run after SCRIPT and AFTER_SCRIPT, but outside container (useful for logging) - required: false - default: ":" - IS_OPTIONAL: - type: boolean - description: Failure will cancel all other tests if set to true - required: false - default: false - secrets: - HF_TOKEN: - required: true -jobs: - main: - runs-on: ${{ inputs.RUNNER }} - timeout-minutes: ${{ inputs.TIMEOUT }} - env: - HF_TOKEN: ${{ secrets.HF_TOKEN }} - steps: - - name: Docker system cleanup - run: | - docker system prune -a --filter "until=48h" --force || true - - - name: Docker pull image - run: | - docker pull nemoci.azurecr.io/nemo_rl_container:${{ github.run_id }} - - - name: Checkout repository - uses: actions/checkout@v4 - with: - submodules: 'recursive' - - - name: Setup docker run command - run: | - GITHUB_ACTION_DIR=$(dirname $GITHUB_STEP_SUMMARY) - DOCKER_RUN_CMD="docker run --rm -u root --runtime=nvidia --gpus all \ - --shm-size=64g \ - --env TRANSFORMERS_OFFLINE=0 \ - --env HYDRA_FULL_ERROR=1 \ - --env HF_HOME=/home/TestData/nemo-rl/hf_home \ - --env HF_DATASETS_CACHE=/home/TestData/nemo-rl/hf_datasets_cache \ - --env NEMO_RL_REPO_DIR=/opt/nemo-rl \ - --env HF_TOKEN \ - --volume $GITHUB_WORKSPACE:/opt/nemo-rl \ - --volume $GITHUB_ACTION_DIR:$GITHUB_ACTION_DIR \ - --volume /mnt/datadrive/TestData/nemo-rl/datasets:/opt/nemo-rl/datasets:ro \ - --volume /mnt/datadrive/TestData/nemo-rl/checkpoints:/home/TestData/nemo-rl/checkpoints:ro \ - --volume /mnt/datadrive/TestData/nemo-rl/hf_home/hub:/home/TestData/nemo-rl/hf_home/hub \ - --volume /mnt/datadrive/TestData/nemo-rl/hf_datasets_cache:/home/TestData/nemo-rl/hf_datasets_cache \ - nemoci.azurecr.io/nemo_rl_container:${{ github.run_id }}" - echo "DOCKER_RUN_CMD=$DOCKER_RUN_CMD" >> $GITHUB_ENV - - - name: Run unit tests - run: | - $DOCKER_RUN_CMD bash -eux -o pipefail -c " - git config --global --add safe.directory /opt/nemo-rl - # This is needed since we create virtualenvs in the workspace, so this allows it to be cleaned up if necessary - umask 000 - ${{ inputs.UNIT_TEST_SCRIPT }}" - - - name: Run doc tests - run: | - $DOCKER_RUN_CMD bash -eux -o pipefail -c " - git config --global --add safe.directory /opt/nemo-rl - # This is needed since we create virtualenvs in the workspace, so this allows it to be cleaned up if necessary - umask 000 - ${{ inputs.DOC_TEST_SCRIPT }}" - - - name: Run functional tests - run: | - $DOCKER_RUN_CMD bash -eux -o pipefail -c " - git config --global --add safe.directory /opt/nemo-rl - # This is needed since we create virtualenvs in the workspace, so this allows it to be cleaned up if necessary - umask 000 - ${{ inputs.FUNCTIONAL_TEST_SCRIPT }}" - - - name: Upload coverage report - uses: actions/upload-artifact@v4 - with: - name: unit-test-coverage-report - path: ${{ github.workspace }}/tests/coverage.json - retention-days: 7 - - - uses: "NVIDIA/NeMo/.github/actions/cancel-workflow@main" - if: failure() - - - name: after_script - if: always() && inputs.AFTER_SCRIPT != ':' - run: | - # Run the after script - cmd=$(cat <<"RUN_TEST_EOF" - ${{ inputs.AFTER_SCRIPT }} - RUN_TEST_EOF - ) - GITHUB_ACTION_DIR=$(dirname $GITHUB_STEP_SUMMARY) - docker run --rm \ - --env GITHUB_STEP_SUMMARY \ - --volume $GITHUB_ACTION_DIR:$GITHUB_ACTION_DIR \ - --volume $GITHUB_WORKSPACE:/opt/nemo-rl \ - nemoci.azurecr.io/nemo_rl_container:${{ github.run_id }} bash -eux -o pipefail -c "$cmd" - - - name: final_script_external - if: always() && inputs.FINAL_SCRIPT_EXTERNAL != ':' - run: | - cmd=$(cat <<"RUN_TEST_EOF" - ${{ inputs.FINAL_SCRIPT_EXTERNAL }} - RUN_TEST_EOF - ) - bash -eux -o pipefail -c "$cmd" - - - name: Container shutdown - if: always() - run: | - # Ensure any added files in the mounted directory are owned by the runner user to allow it to clean up - docker run --rm nemoci.azurecr.io/nemo_rl_container:${{ github.run_id }} bash -c "find /opt/nemo-rl -path '/opt/nemo-rl/datasets' -prune -o -exec chown $(id -u):$(id -g) {} +" diff --git a/.github/workflows/cicd-main.yml b/.github/workflows/cicd-main.yml index f112c9ca26..12fedda72b 100644 --- a/.github/workflows/cicd-main.yml +++ b/.github/workflows/cicd-main.yml @@ -149,7 +149,7 @@ jobs: ((missing_count++)) fi done - + exit $missing_count - name: Minimize uv cache run: uv cache prune --ci @@ -173,93 +173,78 @@ jobs: MAX_JOBS=32 NEMO_RL_COMMIT=${{ github.sha }} - tests: - name: Tests - needs: [build-container, pre-flight] - uses: ./.github/workflows/_run_test.yml - if: ${{ needs.pre-flight.outputs.test_level != 'none' }} - with: - RUNNER: self-hosted-azure - TIMEOUT: 180 - UNIT_TEST_SCRIPT: | - cd /opt/nemo-rl - if [[ "${{ needs.pre-flight.outputs.test_level }}" =~ ^(L0|L1|L2)$ ]]; then - uv run --no-sync bash -x ./tests/run_unit.sh --cov=nemo_rl --hf-gated - uv run --extra mcore bash -x ./tests/run_unit.sh --cov=nemo_rl --cov-append --cov-report=term-missing --cov-report=json --hf-gated --mcore-only - else - echo Skipping unit tests for docs-only level - fi - DOC_TEST_SCRIPT: | - cd /opt/nemo-rl/docs - if [[ "${{ needs.pre-flight.outputs.test_level }}" =~ ^(docs|L0|L1|L2)$ ]]; then - uv run --no-sync sphinx-build -b doctest . _build/doctest - else - echo Skipping doc tests for level ${{ needs.pre-flight.outputs.test_level }} - fi - FUNCTIONAL_TEST_SCRIPT: | - cd /opt/nemo-rl - if [[ "${{ needs.pre-flight.outputs.test_level }}" =~ ^(L1|L2)$ ]]; then - time uv run --no-sync bash ./tests/functional/sft.sh - time uv run --no-sync bash ./tests/functional/grpo.sh - time uv run --no-sync bash ./tests/functional/grpo_megatron.sh - time uv run --no-sync bash ./tests/functional/grpo_multiturn.sh - time uv run --no-sync bash ./tests/functional/grpo_non_colocated.sh - time uv run --no-sync bash ./tests/functional/dpo.sh - time uv run --no-sync bash ./tests/functional/rm.sh - time uv run --no-sync bash ./tests/functional/eval.sh - time uv run --no-sync bash ./tests/functional/eval_async.sh - time uv run --no-sync bash ./tests/functional/test_mcore_extra_installed_correctly.sh - else - echo Skipping functional tests for level ${{ needs.pre-flight.outputs.test_level }} - fi - # TODO: enable once we have convergence tests in CI - #CONVERGENCE_TEST_SCRIPT: | - # cd /opt/nemo-rl - # if [[ "${{ needs.pre-flight.outputs.test_level }}" =~ ^(L2)$ ]]; then - # echo "Running convergence tests" - # # Add your convergence test commands here - # # uv run --no-sync bash ./tests/convergence/test.sh - # else - # echo "Skipping convergence tests for level ${{ needs.pre-flight.outputs.test_level }}" - # fi - AFTER_SCRIPT: | - cd /opt/nemo-rl - cat < /dev/null 2>&1; then + echo "artifacts-found=true" >> $GITHUB_OUTPUT + echo "Found coverage artifacts for ${{ matrix.flag }}" + else + echo "artifacts-found=false" >> $GITHUB_OUTPUT + echo "No coverage artifacts found for ${{ matrix.flag }}" + fi + + - name: Get total coverage of current branch + shell: bash -x -e -u -o pipefail {0} + if: ${{ steps.check-artifacts.outputs.artifacts-found == 'true' }} + run: | + pip install coverage + + ls -al . + ls -al coverage-*/ + coverage combine --keep $(ls coverage-*/.coverage) + coverage report -i --show-missing + rm -rf coverage-* + ls -al + + - name: Skip coverage processing + if: ${{ steps.check-artifacts.outputs.artifacts-found == 'false' }} + run: | + echo "No coverage artifacts found for ${{ matrix.flag }}, skipping coverage processing" + + - name: Upload coverage reports to Codecov + if: ${{ steps.check-artifacts.outputs.artifacts-found == 'true' }} + uses: codecov/codecov-action@v5 + with: + token: ${{ secrets.CODECOV_TOKEN }} + verbose: true + flags: ${{ matrix.flag }} + + - name: Upload artifacts + if: ${{ steps.check-artifacts.outputs.artifacts-found == 'true' }} + uses: actions/upload-artifact@v4 + with: + name: coverage-${{ matrix.flag }}-aggregated + path: | + .coverage + include-hidden-files: true + DCO_merge_group: name: DCO if: github.event_name == 'merge_group' diff --git a/tests/docs/Docs_Tests.sh b/tests/docs/Docs_Tests.sh new file mode 100644 index 0000000000..9b0fd538d6 --- /dev/null +++ b/tests/docs/Docs_Tests.sh @@ -0,0 +1,20 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# 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 +# +# http://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. + +#!/bin/bash +set -xeuo pipefail # Exit immediately if a command exits with a non-zero status + +cd /opt/nemo-rl/docs +uv run --no-sync coverage run -a --data-file=/opt/nemo-rl/tests/.coverage --source=/opt/nemo-rl/nemo_rl -m sphinx.cmd.build -b doctest . _build/doctest +ls /opt/nemo-rl/tests diff --git a/tests/functional/L1_Functional_Tests_GPU.sh b/tests/functional/L1_Functional_Tests_GPU.sh new file mode 100644 index 0000000000..e78d46a990 --- /dev/null +++ b/tests/functional/L1_Functional_Tests_GPU.sh @@ -0,0 +1,31 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# 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 +# +# http://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. + +#!/bin/bash +set -xeuo pipefail # Exit immediately if a command exits with a non-zero status + +cd /opt/nemo-rl +time uv run --no-sync bash ./tests/functional/sft.sh +time uv run --no-sync bash ./tests/functional/grpo.sh +time uv run --no-sync bash ./tests/functional/grpo_megatron.sh +time uv run --no-sync bash ./tests/functional/grpo_multiturn.sh +time uv run --no-sync bash ./tests/functional/grpo_non_colocated.sh +time uv run --no-sync bash ./tests/functional/dpo.sh +time uv run --no-sync bash ./tests/functional/rm.sh +time uv run --no-sync bash ./tests/functional/eval.sh +time uv run --no-sync bash ./tests/functional/eval_async.sh +time uv run --no-sync bash ./tests/functional/test_mcore_extra_installed_correctly.sh + +cd /opt/nemo-rl/tests +coverage combine .coverage* diff --git a/tests/functional/dpo.sh b/tests/functional/dpo.sh index b03b611b25..5de36dfbd4 100755 --- a/tests/functional/dpo.sh +++ b/tests/functional/dpo.sh @@ -18,7 +18,8 @@ rm -rf $EXP_DIR $LOG_DIR mkdir -p $EXP_DIR $LOG_DIR cd $PROJECT_ROOT -uv run $PROJECT_ROOT/examples/run_dpo.py \ +uv run coverage run -a --data-file=$PROJECT_ROOT/tests/.coverage --source=$PROJECT_ROOT/nemo_rl \ + $PROJECT_ROOT/examples/run_dpo.py \ policy.model_name=Qwen/Qwen3-0.6B \ cluster.gpus_per_node=2 \ dpo.max_num_steps=3 \ diff --git a/tests/functional/eval.sh b/tests/functional/eval.sh index 68fbd96d54..fdf2e95c6a 100644 --- a/tests/functional/eval.sh +++ b/tests/functional/eval.sh @@ -18,7 +18,8 @@ rm -rf $EXP_DIR $LOG_DIR mkdir -p $EXP_DIR $LOG_DIR cd $PROJECT_ROOT -uv run $PROJECT_ROOT/examples/run_eval.py \ +uv run coverage run -a --data-file=$PROJECT_ROOT/tests/.coverage --source=$PROJECT_ROOT/nemo_rl \ + $PROJECT_ROOT/examples/run_eval.py \ cluster.gpus_per_node=2 \ $@ \ 2>&1 | tee $RUN_LOG diff --git a/tests/functional/eval_async.sh b/tests/functional/eval_async.sh index 55a89ef012..e92bed9249 100644 --- a/tests/functional/eval_async.sh +++ b/tests/functional/eval_async.sh @@ -18,7 +18,8 @@ rm -rf $EXP_DIR $LOG_DIR mkdir -p $EXP_DIR $LOG_DIR cd $PROJECT_ROOT -uv run $PROJECT_ROOT/examples/run_eval.py \ +uv run coverage run -a --data-file=$PROJECT_ROOT/tests/.coverage --source=$PROJECT_ROOT/nemo_rl \ + $PROJECT_ROOT/examples/run_eval.py \ cluster.gpus_per_node=2 \ generation.vllm_cfg.async_engine=True \ generation.vllm_cfg.pipeline_parallel_size=2 \ diff --git a/tests/functional/grpo.sh b/tests/functional/grpo.sh index 7563f8707d..60761c36f1 100755 --- a/tests/functional/grpo.sh +++ b/tests/functional/grpo.sh @@ -18,7 +18,8 @@ rm -rf $EXP_DIR $LOG_DIR mkdir -p $EXP_DIR $LOG_DIR cd $PROJECT_ROOT -uv run $PROJECT_ROOT/examples/run_grpo_math.py \ +uv run coverage run -a --data-file=$PROJECT_ROOT/tests/.coverage --source=$PROJECT_ROOT/nemo_rl \ + $PROJECT_ROOT/examples/run_grpo_math.py \ policy.model_name=Qwen/Qwen3-0.6B \ grpo.num_prompts_per_step=2 \ grpo.num_generations_per_prompt=4 \ diff --git a/tests/functional/grpo_megatron.sh b/tests/functional/grpo_megatron.sh index 15fb2efec3..a0fcd9898b 100755 --- a/tests/functional/grpo_megatron.sh +++ b/tests/functional/grpo_megatron.sh @@ -19,7 +19,8 @@ mkdir -p $EXP_DIR $LOG_DIR # Using Qwen2.5-0.5B instead of Qwen3-0.6B because the latter is not supported by Megatron yet cd $PROJECT_ROOT -uv run $PROJECT_ROOT/examples/run_grpo_math.py \ +uv run coverage run -a --data-file=$PROJECT_ROOT/tests/.coverage --source=$PROJECT_ROOT/nemo_rl \ + $PROJECT_ROOT/examples/run_grpo_math.py \ --config $PROJECT_ROOT/examples/configs/grpo_math_1B_megatron.yaml \ policy.model_name=Qwen/Qwen2.5-0.5B \ grpo.num_prompts_per_step=2 \ diff --git a/tests/functional/grpo_multiturn.sh b/tests/functional/grpo_multiturn.sh index 20e1472051..53e359b9d8 100755 --- a/tests/functional/grpo_multiturn.sh +++ b/tests/functional/grpo_multiturn.sh @@ -18,7 +18,8 @@ rm -rf $EXP_DIR $LOG_DIR mkdir -p $EXP_DIR $LOG_DIR cd $PROJECT_ROOT -uv run $PROJECT_ROOT/examples/run_grpo_sliding_puzzle.py \ +uv run coverage run -a --data-file=$PROJECT_ROOT/tests/.coverage --source=$PROJECT_ROOT/nemo_rl \ + $PROJECT_ROOT/examples/run_grpo_sliding_puzzle.py \ policy.model_name=Qwen/Qwen3-0.6B \ cluster.gpus_per_node=2 \ grpo.max_rollout_turns=5 \ diff --git a/tests/functional/grpo_non_colocated.sh b/tests/functional/grpo_non_colocated.sh index 2067779fd4..987390c43d 100755 --- a/tests/functional/grpo_non_colocated.sh +++ b/tests/functional/grpo_non_colocated.sh @@ -18,7 +18,8 @@ rm -rf $EXP_DIR $LOG_DIR mkdir -p $EXP_DIR $LOG_DIR cd $PROJECT_ROOT -uv run $PROJECT_ROOT/examples/run_grpo_math.py \ +uv run coverage run -a --data-file=$PROJECT_ROOT/tests/.coverage --source=$PROJECT_ROOT/nemo_rl \ + $PROJECT_ROOT/examples/run_grpo_math.py \ policy.model_name=Qwen/Qwen3-0.6B \ grpo.num_prompts_per_step=2 \ grpo.num_generations_per_prompt=4 \ diff --git a/tests/functional/rm.sh b/tests/functional/rm.sh index 1bfe666d95..21274e7a96 100644 --- a/tests/functional/rm.sh +++ b/tests/functional/rm.sh @@ -21,7 +21,8 @@ rm -rf $EXP_DIR $LOG_DIR mkdir -p $EXP_DIR $LOG_DIR cd $PROJECT_ROOT -uv run $PROJECT_ROOT/examples/run_rm.py \ +uv run coverage run -a --data-file=$PROJECT_ROOT/tests/.coverage --source=$PROJECT_ROOT/nemo_rl \ + $PROJECT_ROOT/examples/run_rm.py \ --config examples/configs/rm.yaml \ cluster.gpus_per_node=2 \ rm.max_num_steps=3 \ diff --git a/tests/functional/sft.sh b/tests/functional/sft.sh index d23151d773..d1d3b9c882 100755 --- a/tests/functional/sft.sh +++ b/tests/functional/sft.sh @@ -21,7 +21,8 @@ rm -rf $EXP_DIR $LOG_DIR mkdir -p $EXP_DIR $LOG_DIR cd $PROJECT_ROOT -uv run $PROJECT_ROOT/examples/run_sft.py \ +uv run coverage run -a --data-file=$PROJECT_ROOT/tests/.coverage --source=$PROJECT_ROOT/nemo_rl \ + $PROJECT_ROOT/examples/run_sft.py \ policy.model_name=Qwen/Qwen3-0.6B \ cluster.gpus_per_node=2 \ sft.max_num_steps=3 \ diff --git a/tests/functional/test_mcore_extra_installed_correctly.sh b/tests/functional/test_mcore_extra_installed_correctly.sh index dfab0828d2..d150f0ed7f 100755 --- a/tests/functional/test_mcore_extra_installed_correctly.sh +++ b/tests/functional/test_mcore_extra_installed_correctly.sh @@ -76,5 +76,8 @@ print("[Nemo/Mcore imports successful]") EOF # Sync just to return the environment to the original base state -uv sync +uv sync --link-mode symlink --locked --no-install-project +uv sync --link-mode symlink --locked --extra vllm --no-install-project +uv sync --link-mode symlink --locked --extra mcore --no-install-project +uv sync --link-mode symlink --locked --all-groups --no-install-project echo Success diff --git a/tests/run_unit.sh b/tests/run_unit.sh index 5367749199..0366d6864b 100755 --- a/tests/run_unit.sh +++ b/tests/run_unit.sh @@ -32,7 +32,15 @@ export PYTHONPATH=$(realpath ${SCRIPT_DIR}/..):${PYTHONPATH:-} # Run unit tests echo "Running unit tests..." -if ! pytest unit/ "$@"; then +if [[ "$#" -eq 0 ]]; then + pytest_args="unit/" +elif [[ "$1" != unit/* ]]; then + pytest_args="unit/ $@" +else + pytest_args="$@" +fi + +if ! pytest $pytest_args; then echo "[ERROR]: Unit tests failed." exit 1 fi diff --git a/tests/unit/L0_Unit_Tests_Generation.sh b/tests/unit/L0_Unit_Tests_Generation.sh new file mode 100644 index 0000000000..1e33bea35e --- /dev/null +++ b/tests/unit/L0_Unit_Tests_Generation.sh @@ -0,0 +1,27 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +#!/bin/bash +set -xeuo pipefail # Exit immediately if a command exits with a non-zero status + +cd /opt/nemo-rl +uv run --no-sync bash -x ./tests/run_unit.sh unit/models/generation/ --cov=nemo_rl --cov-report=term-missing --cov-report=json --hf-gated + +exit_code=$(pytest tests/unit/models/generation/ --collect-only --hf-gated --mcore-only -q >/dev/null 2>&1; echo $?) +if [[ $exit_code -eq 5 ]]; then + echo "No mcore tests to run" + exit 0 +else + uv run --extra mcore bash -x ./tests/run_unit.sh unit/models/generation/ --cov=nemo_rl --cov-append --cov-report=term-missing --cov-report=json --hf-gated --mcore-only +fi diff --git a/tests/unit/L0_Unit_Tests_Other.sh b/tests/unit/L0_Unit_Tests_Other.sh new file mode 100644 index 0000000000..e86d6f887a --- /dev/null +++ b/tests/unit/L0_Unit_Tests_Other.sh @@ -0,0 +1,27 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +#!/bin/bash +set -xeuo pipefail # Exit immediately if a command exits with a non-zero status + +cd /opt/nemo-rl +uv run --no-sync bash -x ./tests/run_unit.sh unit/ --ignore=unit/models/generation/ --ignore=unit/models/policy/ --cov=nemo_rl --cov-report=term-missing --cov-report=json --hf-gated + +exit_code=$(pytest tests/unit/ --ignore=unit/models/generation/ --ignore=unit/models/policy/ --collect-only --hf-gated --mcore-only -q >/dev/null 2>&1; echo $?) +if [[ $exit_code -eq 5 ]]; then + echo "No mcore tests to run" + exit 0 +else + uv run --extra mcore bash -x ./tests/run_unit.sh unit/ --ignore=unit/models/generation/ --ignore=unit/models/policy/ --cov=nemo_rl --cov-append --cov-report=term-missing --cov-report=json --hf-gated --mcore-only +fi diff --git a/tests/unit/L0_Unit_Tests_Policy.sh b/tests/unit/L0_Unit_Tests_Policy.sh new file mode 100644 index 0000000000..4df69728ff --- /dev/null +++ b/tests/unit/L0_Unit_Tests_Policy.sh @@ -0,0 +1,27 @@ +# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +#!/bin/bash +set -xeuo pipefail # Exit immediately if a command exits with a non-zero status + +cd /opt/nemo-rl +uv run --no-sync bash -x ./tests/run_unit.sh unit/models/policy/ --cov=nemo_rl --cov-report=term-missing --cov-report=json --hf-gated + +exit_code=$(pytest tests/unit/models/policy/ --collect-only --hf-gated --mcore-only -q >/dev/null 2>&1; echo $?) +if [[ $exit_code -eq 5 ]]; then + echo "No mcore tests to run" + exit 0 +else + uv run --extra mcore bash -x ./tests/run_unit.sh unit/models/policy/ --cov=nemo_rl --cov-append --cov-report=term-missing --cov-report=json --hf-gated --mcore-only +fi diff --git a/tests/unit/models/generation/test_vllm_generation.py b/tests/unit/models/generation/test_vllm_generation.py index 502c63662b..eae44d8dfe 100644 --- a/tests/unit/models/generation/test_vllm_generation.py +++ b/tests/unit/models/generation/test_vllm_generation.py @@ -626,7 +626,7 @@ def configure_worker_fixed_seed(num_gpus, bundle_indices=None): torch.cuda.empty_cache() -@pytest.mark.timeout(140) +@pytest.mark.timeout(360) @pytest.mark.asyncio @pytest.mark.parametrize("async_engine", [True, False]) async def test_vllm_generation_with_hf_training(cluster, tokenizer, async_engine): @@ -1274,7 +1274,7 @@ async def test_vllm_refit_non_collocated_update_weights( print(f"Error during generation_cluster_separate shutdown: {e}") -@pytest.mark.timeout(210) +@pytest.mark.timeout(360) @pytest.mark.parametrize("tensor_parallel_size", [1, 2]) def test_vllm_generation_with_megatron_training( cluster, tokenizer, tensor_parallel_size diff --git a/tests/unit/models/policy/test_dtensor_worker.py b/tests/unit/models/policy/test_dtensor_worker.py index 33a91c37eb..ba33408a8d 100644 --- a/tests/unit/models/policy/test_dtensor_worker.py +++ b/tests/unit/models/policy/test_dtensor_worker.py @@ -160,7 +160,7 @@ def policy_setup(two_gpu_virtual_cluster, tiny_llama_model_path): @pytest.mark.hf_gated -@pytest.mark.timeout(180) +@pytest.mark.timeout(360) def test_lm_policy_init(policy_setup): policy = policy_setup @@ -308,7 +308,7 @@ def training_setup(request, two_gpu_virtual_cluster): @pytest.mark.hf_gated -@pytest.mark.timeout(60) +@pytest.mark.timeout(360) @pytest.mark.parametrize( "training_setup", [ From 11cdfe36a7ee3bdfea3e95b8a33a7e9c7a0527b9 Mon Sep 17 00:00:00 2001 From: tpoisonooo Date: Mon, 4 Aug 2025 14:14:26 +0800 Subject: [PATCH 21/23] style(tests): linkt check Signed-off-by: tpoisonooo --- nemo_rl/utils/logger.py | 2 +- tests/unit/utils/test_logger.py | 23 +++++++++++++++++++---- 2 files changed, 20 insertions(+), 5 deletions(-) diff --git a/nemo_rl/utils/logger.py b/nemo_rl/utils/logger.py index 836b62babe..6d19b03b59 100644 --- a/nemo_rl/utils/logger.py +++ b/nemo_rl/utils/logger.py @@ -28,9 +28,9 @@ import mlflow import ray import requests +import swanlab import torch import wandb -import swanlab from matplotlib import pyplot as plt from prometheus_client.parser import text_string_to_metric_families from prometheus_client.samples import Sample diff --git a/tests/unit/utils/test_logger.py b/tests/unit/utils/test_logger.py index ebb25f78d0..046040b24b 100644 --- a/tests/unit/utils/test_logger.py +++ b/tests/unit/utils/test_logger.py @@ -23,9 +23,9 @@ Logger, MLflowLogger, RayGpuMonitorLogger, + SwanlabLogger, TensorboardLogger, WandbLogger, - SwanlabLogger, flatten_dict, print_message_log_samples, ) @@ -1519,7 +1519,12 @@ def test_init_mlflow_only(self, mock_tb_logger, mock_wandb_logger, temp_dir): @patch("nemo_rl.utils.logger.MLflowLogger") @patch("nemo_rl.utils.logger.SwanlabLogger") def test_init_all_loggers( - self, mock_swanlab_logger, mock_mlflow_logger, mock_tb_logger, mock_wandb_logger, temp_dir + self, + mock_swanlab_logger, + mock_mlflow_logger, + mock_tb_logger, + mock_wandb_logger, + temp_dir, ): """Test initialization with all loggers enabled.""" cfg = { @@ -1551,7 +1556,12 @@ def test_init_all_loggers( @patch("nemo_rl.utils.logger.MLflowLogger") @patch("nemo_rl.utils.logger.SwanlabLogger") def test_log_metrics_with_mlflow( - self, mock_swanlab_logger, mock_mlflow_logger, mock_tb_logger, mock_wandb_logger, temp_dir + self, + mock_swanlab_logger, + mock_mlflow_logger, + mock_tb_logger, + mock_wandb_logger, + temp_dir, ): """Test logging metrics to all enabled loggers including MLflow.""" cfg = { @@ -1595,7 +1605,12 @@ def test_log_metrics_with_mlflow( @patch("nemo_rl.utils.logger.MLflowLogger") @patch("nemo_rl.utils.logger.SwanlabLogger") def test_log_hyperparams_with_mlflow( - self, mock_swanlab_logger, mock_mlflow_logger, mock_tb_logger, mock_wandb_logger, temp_dir + self, + mock_swanlab_logger, + mock_mlflow_logger, + mock_tb_logger, + mock_wandb_logger, + temp_dir, ): """Test logging hyperparameters to all enabled loggers including MLflow.""" cfg = { From ffaea62a1f0d8f434b1e690f88bdd9b61703404f Mon Sep 17 00:00:00 2001 From: tpoisonooo Date: Wed, 6 Aug 2025 11:48:19 +0800 Subject: [PATCH 22/23] ci(tests): pre-commit check Signed-off-by: tpoisonooo --- nemo_rl/utils/logger.py | 5 +++++ tests/unit/utils/test_logger.py | 6 +++++- 2 files changed, 10 insertions(+), 1 deletion(-) diff --git a/nemo_rl/utils/logger.py b/nemo_rl/utils/logger.py index 6d19b03b59..c3b329c284 100644 --- a/nemo_rl/utils/logger.py +++ b/nemo_rl/utils/logger.py @@ -51,10 +51,12 @@ class WandbConfig(TypedDict): project: NotRequired[str] name: NotRequired[str] + class SwanlabConfig(TypedDict): project: NotRequired[str] name: NotRequired[str] + class TensorboardConfig(TypedDict): log_dir: NotRequired[str] @@ -329,6 +331,7 @@ def log_plot(self, figure: plt.Figure, step: int, name: str) -> None: """ self.run.log({name: figure}, step=step) + class SwanlabLogger(LoggerInterface): """Weights & Biases logger backend.""" @@ -397,6 +400,7 @@ def log_plot(self, figure: plt.Figure, step: int, name: str) -> None: """ self.run.log({name: figure}, step=step) + class GpuMetricSnapshot(TypedDict): step: int metrics: dict[str, Any] @@ -1338,4 +1342,5 @@ def get_next_experiment_dir(base_log_dir: str) -> str: # Create the new log directory os.makedirs(new_log_dir, exist_ok=True) + return new_log_dir diff --git a/tests/unit/utils/test_logger.py b/tests/unit/utils/test_logger.py index 046040b24b..3e73ed497d 100644 --- a/tests/unit/utils/test_logger.py +++ b/tests/unit/utils/test_logger.py @@ -264,6 +264,7 @@ def test_log_hyperparams(self, mock_wandb): mock_run = mock_wandb.init.return_value mock_run.config.update.assert_called_once_with(params) + class TestSwanlabLogger: """Test the SwanlabLogger class.""" @@ -1594,12 +1595,15 @@ def test_log_metrics_with_mlflow( # Check that log_metrics was called on all loggers mock_wandb_instance.log_metrics.assert_called_once_with(metrics, step, "", None) - mock_swanlab_instance.log_metrics.assert_called_once_with(metrics, step, "", None) + mock_swanlab_instance.log_metrics.assert_called_once_with( + metrics, step, "", None + ) mock_tb_instance.log_metrics.assert_called_once_with(metrics, step, "", None) mock_mlflow_instance.log_metrics.assert_called_once_with( metrics, step, "", None ) + @patch("nemo_rl.utils.logger.WandbLogger") @patch("nemo_rl.utils.logger.TensorboardLogger") @patch("nemo_rl.utils.logger.MLflowLogger") From f5e4e0cc491c3adbc0bf69080b8c9cc9cfd88e6d Mon Sep 17 00:00:00 2001 From: tpoisonooo Date: Wed, 6 Aug 2025 18:39:02 +0800 Subject: [PATCH 23/23] style(tests): remote empty line Signed-off-by: tpoisonooo --- nemo_rl/utils/logger.py | 1 - tests/unit/utils/test_logger.py | 1 - 2 files changed, 2 deletions(-) diff --git a/nemo_rl/utils/logger.py b/nemo_rl/utils/logger.py index c3b329c284..46b63d9770 100644 --- a/nemo_rl/utils/logger.py +++ b/nemo_rl/utils/logger.py @@ -1342,5 +1342,4 @@ def get_next_experiment_dir(base_log_dir: str) -> str: # Create the new log directory os.makedirs(new_log_dir, exist_ok=True) - return new_log_dir diff --git a/tests/unit/utils/test_logger.py b/tests/unit/utils/test_logger.py index 3e73ed497d..d92088c4d9 100644 --- a/tests/unit/utils/test_logger.py +++ b/tests/unit/utils/test_logger.py @@ -1603,7 +1603,6 @@ def test_log_metrics_with_mlflow( metrics, step, "", None ) - @patch("nemo_rl.utils.logger.WandbLogger") @patch("nemo_rl.utils.logger.TensorboardLogger") @patch("nemo_rl.utils.logger.MLflowLogger")