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# 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 functools import partial
from typing import Any, Optional
from unittest.mock import patch
import pytest
from invoke.config import Config
from invoke.context import Context
BASE_CHECKPOINT_DIR = "/nemo_run/checkpoints"
class MockContext(Context):
def __init__(self, config: Optional[Config] = None) -> None:
defaults = Config.global_defaults()
defaults["run"]["pty"] = True
defaults["run"]["in_stream"] = False
super().__init__(config=config)
def run(self, command: str, **kwargs: Any):
kwargs["in_stream"] = False
super().run(command, **kwargs)
@pytest.mark.parametrize(
"module, recipe, name",
[
("llama3_8b", "pretrain_recipe", "llama3_8b_pretrain"),
("llama3_8b", "finetune_recipe", "llama3_8b_finetune"),
("llama3_8b_16k", "pretrain_recipe", "llama3_8b_16k_pretrain"),
("llama3_8b_64k", "pretrain_recipe", "llama3_8b_64k_pretrain"),
("llama3_70b", "pretrain_recipe", "llama3_70b_pretrain"),
("llama3_70b", "finetune_recipe", "llama3_70b_finetune"),
("llama3_70b_16k", "pretrain_recipe", "llama3_70b_16k_pretrain"),
("llama3_70b_64k", "pretrain_recipe", "llama3_70b_64k_pretrain"),
("llama31_8b", "pretrain_recipe", "llama31_8b_pretrain"),
("llama31_8b", "finetune_recipe", "llama31_8b_finetune"),
("llama31_70b", "pretrain_recipe", "llama31_70b_pretrain"),
("llama31_70b", "finetune_recipe", "llama31_70b_finetune"),
("llama31_405b", "pretrain_recipe", "llama31_405b_pretrain"),
("llama31_405b", "finetune_recipe", "llama31_405b_finetune"),
("mistral_7b", "pretrain_recipe", "mistral_pretrain"),
("mistral_7b", "finetune_recipe", "mistral_finetune"),
("mixtral_8x7b", "pretrain_recipe", "mixtral_8x7b_pretrain"),
("mixtral_8x7b", "finetune_recipe", "mixtral_8x7b_finetune"),
("mixtral_8x7b_16k", "pretrain_recipe", "mixtral_8x7b_16k_pretrain"),
("mixtral_8x7b_64k", "pretrain_recipe", "mixtral_8x7b_64k_pretrain"),
("mixtral_8x22b", "pretrain_recipe", "mixtral_8x22b_pretrain"),
("mixtral_8x22b", "finetune_recipe", "mixtral_8x22b_finetune"),
("nemotron3_4b", "pretrain_recipe", "nemotron3_4b_pretrain"),
("nemotron3_8b", "pretrain_recipe", "nemotron3_8b_pretrain"),
("nemotron3_8b", "finetune_recipe", "nemotron3_8b_finetune"),
("nemotron3_22b", "pretrain_recipe", "nemotron3_22b_pretrain"),
("nemotron3_22b_16k", "pretrain_recipe", "nemotron3_22b_16k_pretrain"),
("nemotron3_22b_64k", "pretrain_recipe", "nemotron3_22b_64k_pretrain"),
("nemotron4_15b", "pretrain_recipe", "nemotron4_15b_pretrain"),
("nemotron4_15b_16k", "pretrain_recipe", "nemotron4_15b_16k_pretrain"),
("nemotron4_15b_64k", "pretrain_recipe", "nemotron4_15b_64k_pretrain"),
("nemotron4_340b", "pretrain_recipe", "nemotron4_340b_pretrain"),
("nemotron4_340b", "finetune_recipe", "nemotron4_340b_finetune"),
("gpt3_175b", "pretrain_recipe", "gpt3_175b_pretrain"),
],
)
@patch("invoke.context.Context", MockContext)
@patch("nemo_run.core.packaging.git.Context", MockContext)
@patch("nemo_run.core.execution.slurm.Context", MockContext)
def test_recipes_with_nemo_run(module, recipe, name, tmpdir, monkeypatch):
monkeypatch.setenv("NEMORUN_HOME", str(tmpdir))
monkeypatch.setenv("WANDB_API_KEY", "dummy")
import nemo_run as run
from nemo.collections import llm
from nemo.collections.llm.recipes.log.default import wandb_logger
from nemo.lightning.run import plugins
recipe_config = getattr(getattr(llm, module), recipe)(
name=name, dir=BASE_CHECKPOINT_DIR, num_nodes=1, num_gpus_per_node=8
)
run_plugins = [
plugins.PreemptionPlugin(),
plugins.WandbPlugin(name=name, logger_fn=partial(wandb_logger, entity="dummy", project="dummy")),
]
validation_plugin = plugins.ConfigValidationPlugin(validate_wandb=True)
run_plugins.append(validation_plugin)
with run.Experiment(f"{name}-unit-test") as exp:
exp.add(
recipe_config,
executor=run.SlurmExecutor(
account="dummy",
partition="dummy",
nodes=recipe_config.trainer.num_nodes,
ntasks_per_node=recipe_config.trainer.devices,
packager=run.Packager(),
),
name=name,
plugins=run_plugins,
)
exp.dryrun()
with pytest.raises(AssertionError):
with run.Experiment(f"{name}-unit-test-fail-validate-nodes-and-devices") as exp:
exp.add(
recipe_config,
executor=run.SlurmExecutor(
account="dummy",
partition="dummy",
nodes=recipe_config.trainer.num_nodes + 1,
ntasks_per_node=recipe_config.trainer.devices + 1,
packager=run.Packager(),
),
name=name,
plugins=run_plugins,
)
exp.dryrun()
with pytest.raises(AssertionError):
cfg = recipe_config.clone()
cfg.log.log_dir = "/temporary-does-not-exist"
with run.Experiment(f"{name}-unit-test-fail-validate-checkpoint-dir") as exp:
exp.add(
cfg,
executor=run.SlurmExecutor(
account="dummy",
partition="dummy",
nodes=cfg.trainer.num_nodes,
ntasks_per_node=cfg.trainer.devices,
packager=run.Packager(),
),
name=name,
plugins=run_plugins,
)
exp.dryrun()
run_plugins = [plugins.NsysPlugin(start_step=3, end_step=4)] + run_plugins
with run.Experiment(f"{name}-nsys-unit-test") as exp:
exp.add(
recipe_config,
executor=run.SlurmExecutor(
account="dummy",
partition="dummy",
nodes=recipe_config.trainer.num_nodes,
ntasks_per_node=recipe_config.trainer.devices,
packager=run.Packager(),
),
name=name,
plugins=run_plugins,
)
exp.dryrun()
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