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Convert formatting to use ruff instead of yapf + isort (#26247)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
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159
tests/distributed/test_expert_placement.py
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@@ -6,8 +6,7 @@ import pytest
from vllm.model_executor.layers.fused_moe.layer import determine_expert_map
def verify_round_robin_pattern(expert_map, ep_rank, ep_size,
global_num_experts):
def verify_round_robin_pattern(expert_map, ep_rank, ep_size, global_num_experts):
"""Verify that the expert map follows the round_robin pattern."""
# Calculate expected local experts (supporting non-divisible cases)
base_experts = global_num_experts // ep_size
@@ -30,24 +29,21 @@ def verify_round_robin_pattern(expert_map, ep_rank, ep_size,
if global_expert_id in expected_expert_ids:
local_expert_id = expert_map[global_expert_id]
expected_local_id = expected_expert_ids.index(global_expert_id)
assert (
local_expert_id == expected_local_id
), f"Global expert {global_expert_id} should map to local expert " \
assert local_expert_id == expected_local_id, (
f"Global expert {global_expert_id} should map to local expert "
f"{expected_local_id}, got {local_expert_id}"
)
else:
assert (
expert_map[global_expert_id] == -1
), f"Global expert {global_expert_id} should not be mapped to " \
f"this rank"
assert expert_map[global_expert_id] == -1, (
f"Global expert {global_expert_id} should not be mapped to this rank"
)
# Verify that all local expert IDs are consecutive starting from 0
local_expert_ids = [
expert_map[global_id] for global_id in expected_expert_ids
]
local_expert_ids = [expert_map[global_id] for global_id in expected_expert_ids]
expected_local_ids = list(range(local_num_experts))
assert (
local_expert_ids == expected_local_ids
), f"Expected local expert IDs {expected_local_ids}, got {local_expert_ids}"
assert local_expert_ids == expected_local_ids, (
f"Expected local expert IDs {expected_local_ids}, got {local_expert_ids}"
)
@pytest.mark.parametrize("expert_placement_strategy", ["round_robin"])
@@ -78,8 +74,9 @@ def test_expert_placement_various_sizes(expert_placement_strategy, world_size):
for test_global_experts, test_ep_size in test_cases:
# Ensure ep_size matches world_size
assert (test_ep_size == world_size
), f"ep_size {test_ep_size} must equal world_size {world_size}"
assert test_ep_size == world_size, (
f"ep_size {test_ep_size} must equal world_size {world_size}"
)
# Test each rank
for ep_rank in range(world_size):
@@ -98,21 +95,22 @@ def test_expert_placement_various_sizes(expert_placement_strategy, world_size):
expert_placement_strategy=expert_placement_strategy,
)
assert (
test_local_experts == expected_test_local
), f"For {test_global_experts} experts on {test_ep_size} ranks, " \
f"rank {ep_rank}: expected {expected_test_local} local" \
assert test_local_experts == expected_test_local, (
f"For {test_global_experts} experts on {test_ep_size} ranks, "
f"rank {ep_rank}: expected {expected_test_local} local"
f"experts, got {test_local_experts}"
)
if test_expert_map is not None:
assert test_expert_map.shape == (
test_global_experts,
), f"Expected expert map shape ({test_global_experts},), " \
assert test_expert_map.shape == (test_global_experts,), (
f"Expected expert map shape ({test_global_experts},), "
f"got {test_expert_map.shape}"
)
# Verify round_robin pattern for this test case
verify_round_robin_pattern(test_expert_map, ep_rank,
test_ep_size, test_global_experts)
verify_round_robin_pattern(
test_expert_map, ep_rank, test_ep_size, test_global_experts
)
@pytest.mark.parametrize("expert_placement_strategy", ["round_robin"])
@@ -147,28 +145,81 @@ def test_determine_expert_map_comprehensive():
# expert_placement_strategy, expected_local, expected_map_pattern)
test_cases = [
# Round robin placement tests
(2, 0, 8, "round_robin", 4, [0, -1, 1, -1, 2, -1, 3,
-1]), # rank 0 gets even experts
(2, 1, 8, "round_robin", 4, [-1, 0, -1, 1, -1, 2, -1,
3]), # rank 1 gets odd experts
(2, 0, 9, "round_robin", 5, [0, -1, 1, -1, 2, -1, 3, -1, 4
]), # rank 0 gets 5 experts (even + last)
(2, 1, 9, "round_robin", 4, [-1, 0, -1, 1, -1, 2, -1, 3,
-1]), # rank 1 gets 4 experts (odd)
(
2,
0,
8,
"round_robin",
4,
[0, -1, 1, -1, 2, -1, 3, -1],
), # rank 0 gets even experts
(
2,
1,
8,
"round_robin",
4,
[-1, 0, -1, 1, -1, 2, -1, 3],
), # rank 1 gets odd experts
(
2,
0,
9,
"round_robin",
5,
[0, -1, 1, -1, 2, -1, 3, -1, 4],
), # rank 0 gets 5 experts (even + last)
(
2,
1,
9,
"round_robin",
4,
[-1, 0, -1, 1, -1, 2, -1, 3, -1],
), # rank 1 gets 4 experts (odd)
# 4-rank tests
(4, 0, 8, "round_robin", 2, [0, -1, -1, -1, 1, -1, -1,
-1]), # rank 0 gets experts 0, 4
(4, 1, 8, "round_robin", 2, [-1, 0, -1, -1, -1, 1, -1,
-1]), # rank 1 gets experts 1, 5
(4, 2, 8, "round_robin", 2, [-1, -1, 0, -1, -1, -1, 1,
-1]), # rank 2 gets experts 2, 6
(4, 3, 8, "round_robin", 2, [-1, -1, -1, 0, -1, -1, -1,
1]), # rank 3 gets experts 3, 7
(
4,
0,
8,
"round_robin",
2,
[0, -1, -1, -1, 1, -1, -1, -1],
), # rank 0 gets experts 0, 4
(
4,
1,
8,
"round_robin",
2,
[-1, 0, -1, -1, -1, 1, -1, -1],
), # rank 1 gets experts 1, 5
(
4,
2,
8,
"round_robin",
2,
[-1, -1, 0, -1, -1, -1, 1, -1],
), # rank 2 gets experts 2, 6
(
4,
3,
8,
"round_robin",
2,
[-1, -1, -1, 0, -1, -1, -1, 1],
), # rank 3 gets experts 3, 7
]
for ep_size, ep_rank, global_num_experts, expert_placement_strategy, \
expected_local, expected_map_pattern in test_cases:
for (
ep_size,
ep_rank,
global_num_experts,
expert_placement_strategy,
expected_local,
expected_map_pattern,
) in test_cases:
local_num_experts, expert_map = determine_expert_map(
ep_size=ep_size,
ep_rank=ep_rank,
@@ -176,19 +227,21 @@ def test_determine_expert_map_comprehensive():
expert_placement_strategy=expert_placement_strategy,
)
assert local_num_experts == expected_local, \
f"ep_size={ep_size}, ep_rank={ep_rank}, " \
f"global_num_experts={global_num_experts}, " \
f"expert_placement_strategy={expert_placement_strategy}: " \
assert local_num_experts == expected_local, (
f"ep_size={ep_size}, ep_rank={ep_rank}, "
f"global_num_experts={global_num_experts}, "
f"expert_placement_strategy={expert_placement_strategy}: "
f"expected {expected_local} local experts, got {local_num_experts}"
)
if expected_map_pattern is None:
assert expert_map is None, "Expected expert_map to be None"
else:
assert expert_map is not None, "Expected expert_map to not be None"
actual_map = expert_map.tolist()
assert actual_map == expected_map_pattern, \
f"ep_size={ep_size}, ep_rank={ep_rank}, " \
f"global_num_experts={global_num_experts}, " \
f"expert_placement_strategy={expert_placement_strategy}: " \
assert actual_map == expected_map_pattern, (
f"ep_size={ep_size}, ep_rank={ep_rank}, "
f"global_num_experts={global_num_experts}, "
f"expert_placement_strategy={expert_placement_strategy}: "
f"expected map {expected_map_pattern}, got {actual_map}"
)