Skip to content

chore: remove old fsdp1 unit test #871

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
terrykong merged 1 commit into from
Aug 8, 2025
Merged

chore: remove old fsdp1 unit test #871

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 5 additions & 14 deletions tests/unit/models/generation/test_vllm_generation.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -918,9 +918,8 @@ def test_vllm_generate_text(cluster, tokenizer):

@pytest.mark.timeout(180)
@pytest.mark.parametrize("tensor_parallel_size", [1, 2])
@pytest.mark.parametrize("enable_dtensor", [True, False])
def test_vllm_weight_update_and_prefix_cache_reset(
cluster, tokenizer, tensor_parallel_size, enable_dtensor
cluster, tokenizer, tensor_parallel_size
):
"""Test that the vLLM prefix cache is correctly reset when weights change."""
from nemo_rl.models.policy.lm_policy import Policy
Expand Down Expand Up @@ -1024,8 +1023,7 @@ def test_vllm_weight_update_and_prefix_cache_reset(
torch.cuda.empty_cache()


@pytest.mark.parametrize("enable_dtensor", [True, False])
def test_vllm_weight_update_memory(cluster, tokenizer, enable_dtensor):
def test_vllm_weight_update_memory(cluster, tokenizer):
"""Test that vLLM streaming weight update and can save memory."""
from nemo_rl.models.policy.lm_policy import Policy

Expand Down Expand Up @@ -1084,23 +1082,16 @@ def test_vllm_weight_update_memory(cluster, tokenizer, enable_dtensor):
assert current_reserved == 0.0, "Memory should be 0 after refit completed"
# memory threshold: memory during non-streaming weight update on 0.6B model on 2 GPUs
# memory during streaming weight update should less than this baseline threshold
if enable_dtensor:
assert peak_allocated < 4005, "Peak allocated memory should < 4005 MB"
assert peak_reserved < 4016, "Peak reserved memory should < 4016 MB"
else:
assert peak_allocated < 5736, "Peak allocated memory should < 5736 MB"
assert peak_reserved < 5748, "Peak reserved memory should < 5748 MB"
assert peak_allocated < 4005, "Peak allocated memory should < 4005 MB"
assert peak_reserved < 4016, "Peak reserved memory should < 4016 MB"

# Clean up
vllm_policy.shutdown()
lm_policy.shutdown()


@pytest.mark.parametrize("is_eval", [True, False])
@pytest.mark.parametrize("enable_dtensor", [True, False])
def test_vllm_generation_with_stop(
cluster, test_input_data, tokenizer, is_eval, enable_dtensor
):
def test_vllm_generation_with_stop(cluster, test_input_data, tokenizer, is_eval):
"""Test vLLM generation with stop."""
from nemo_rl.models.policy.lm_policy import Policy

Expand Down