431 lines
15 KiB
Python
431 lines
15 KiB
Python
"""Pytest hooks for E2E test collection and validation.
|
|
|
|
This module handles:
|
|
- Test collection: Scanning markers to determine required workers
|
|
- GPU validation: Ensuring sufficient GPUs for test requirements
|
|
- Marker registration: Defining custom pytest markers
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
import logging
|
|
import os
|
|
from typing import TYPE_CHECKING
|
|
|
|
import pytest
|
|
|
|
if TYPE_CHECKING:
|
|
from infra import ConnectionMode, WorkerIdentity, WorkerType
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Test collection state
|
|
# ---------------------------------------------------------------------------
|
|
|
|
# Track max worker counts: (model_id, mode, worker_type) -> max_count
|
|
_worker_counts: dict[tuple["ConnectionMode", "WorkerType"], int] = {}
|
|
|
|
# Track first-seen order to preserve test collection order
|
|
_first_seen_order: list[tuple[str, "ConnectionMode", "WorkerType"]] = []
|
|
|
|
# Track max GPU requirement for any single test (for validation)
|
|
_max_test_gpu_requirement: int = 0
|
|
_max_test_name: str = ""
|
|
|
|
_needs_default_model: bool = False
|
|
|
|
|
|
def reset_collection_state() -> None:
|
|
"""Reset collection state (useful for testing)."""
|
|
global _worker_counts, _first_seen_order
|
|
global _max_test_gpu_requirement, _max_test_name, _needs_default_model
|
|
_worker_counts = {}
|
|
_first_seen_order = []
|
|
_max_test_gpu_requirement = 0
|
|
_max_test_name = ""
|
|
_needs_default_model = False
|
|
|
|
|
|
def get_worker_counts() -> dict:
|
|
"""Get the worker counts dictionary."""
|
|
return _worker_counts
|
|
|
|
|
|
def get_first_seen_order() -> list:
|
|
"""Get the first-seen order list."""
|
|
return _first_seen_order
|
|
|
|
|
|
def get_max_gpu_requirement() -> tuple[int, str]:
|
|
"""Get the max GPU requirement and test name."""
|
|
return _max_test_gpu_requirement, _max_test_name
|
|
|
|
|
|
def needs_default_model() -> bool:
|
|
"""Check if any test needs the default model."""
|
|
return _needs_default_model
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Test collection hook
|
|
# ---------------------------------------------------------------------------
|
|
|
|
|
|
def pytest_collection_modifyitems(
|
|
session: pytest.Session,
|
|
config: pytest.Config,
|
|
items: list[pytest.Item],
|
|
) -> None:
|
|
"""Scan collected tests to determine required workers.
|
|
|
|
This runs after test collection but before tests execute.
|
|
It extracts worker requirements from markers in test collection order,
|
|
tracking the max count needed for each (model, mode, worker_type) combination.
|
|
"""
|
|
global _worker_counts, _first_seen_order, _needs_default_model
|
|
global _max_test_gpu_requirement, _max_test_name
|
|
|
|
from infra import (
|
|
DEFAULT_MODEL,
|
|
LOG_SEPARATOR_WIDTH,
|
|
MODEL_SPECS,
|
|
PARAM_MODEL,
|
|
PARAM_SETUP_BACKEND,
|
|
ConnectionMode,
|
|
WorkerType,
|
|
)
|
|
|
|
def track_worker(
|
|
model_id: str, mode: ConnectionMode, worker_type: WorkerType, count: int
|
|
) -> None:
|
|
"""Track a worker requirement, updating max count if needed."""
|
|
key = (model_id, mode, worker_type)
|
|
if key not in _worker_counts:
|
|
_first_seen_order.append(key)
|
|
_worker_counts[key] = count
|
|
else:
|
|
_worker_counts[key] = max(_worker_counts[key], count)
|
|
|
|
def calculate_test_gpus(
|
|
model_id: str, prefill: int, decode: int, regular: int
|
|
) -> int:
|
|
"""Calculate GPU requirement for a single test."""
|
|
if model_id not in MODEL_SPECS:
|
|
return 0
|
|
tp = MODEL_SPECS[model_id].get("tp", 1)
|
|
return tp * (prefill + decode + regular)
|
|
|
|
for item in items:
|
|
# Extract model from marker or use default
|
|
# First check the class directly (handles inheritance correctly)
|
|
model_id = None
|
|
if hasattr(item, "cls") and item.cls is not None:
|
|
for marker in (
|
|
item.cls.pytestmark if hasattr(item.cls, "pytestmark") else []
|
|
):
|
|
if marker.name == PARAM_MODEL and marker.args:
|
|
model_id = marker.args[0]
|
|
break
|
|
# Fall back to get_closest_marker for method-level markers
|
|
if model_id is None:
|
|
model_marker = item.get_closest_marker(PARAM_MODEL)
|
|
model_id = (
|
|
model_marker.args[0] if model_marker and model_marker.args else None
|
|
)
|
|
|
|
# Check parametrize for model
|
|
if model_id is None:
|
|
for marker in item.iter_markers("parametrize"):
|
|
if marker.args and len(marker.args) >= 2:
|
|
param_name = marker.args[0]
|
|
if param_name == PARAM_MODEL or PARAM_MODEL in param_name:
|
|
param_values = marker.args[1]
|
|
if isinstance(param_values, (list, tuple)) and param_values:
|
|
model_id = param_values[0]
|
|
break
|
|
|
|
# Extract backends from parametrize
|
|
backends: list[str] = []
|
|
for marker in item.iter_markers("parametrize"):
|
|
if marker.args and len(marker.args) >= 2:
|
|
param_name = marker.args[0]
|
|
param_values = marker.args[1]
|
|
if param_name == PARAM_SETUP_BACKEND:
|
|
if isinstance(param_values, (list, tuple)):
|
|
backends.extend(param_values)
|
|
|
|
# Check for workers marker
|
|
workers_marker = item.get_closest_marker("workers")
|
|
prefill_count = 0
|
|
decode_count = 0
|
|
regular_count = 1
|
|
if workers_marker:
|
|
prefill_count = workers_marker.kwargs.get("prefill") or 0
|
|
decode_count = workers_marker.kwargs.get("decode") or 0
|
|
regular_count = workers_marker.kwargs.get("count") or 1
|
|
|
|
# Track if this test needs default model
|
|
is_e2e = item.get_closest_marker("e2e") is not None
|
|
if model_id is None and is_e2e:
|
|
_needs_default_model = True
|
|
model_id = DEFAULT_MODEL
|
|
|
|
# Track worker requirements
|
|
test_gpus = 0
|
|
if model_id and backends:
|
|
for backend in backends:
|
|
if backend == "pd":
|
|
mode = ConnectionMode.HTTP
|
|
p_count = prefill_count if prefill_count > 0 else 1
|
|
d_count = decode_count if decode_count > 0 else 1
|
|
track_worker(model_id, mode, WorkerType.PREFILL, p_count)
|
|
track_worker(model_id, mode, WorkerType.DECODE, d_count)
|
|
test_gpus = max(
|
|
test_gpus, calculate_test_gpus(model_id, p_count, d_count, 0)
|
|
)
|
|
else:
|
|
try:
|
|
mode = ConnectionMode(backend)
|
|
except ValueError:
|
|
continue
|
|
|
|
if prefill_count > 0 or decode_count > 0:
|
|
track_worker(model_id, mode, WorkerType.PREFILL, prefill_count)
|
|
track_worker(model_id, mode, WorkerType.DECODE, decode_count)
|
|
test_gpus = max(
|
|
test_gpus,
|
|
calculate_test_gpus(
|
|
model_id, prefill_count, decode_count, 0
|
|
),
|
|
)
|
|
else:
|
|
track_worker(model_id, mode, WorkerType.REGULAR, regular_count)
|
|
test_gpus = max(
|
|
test_gpus,
|
|
calculate_test_gpus(model_id, 0, 0, regular_count),
|
|
)
|
|
|
|
elif model_id and is_e2e:
|
|
track_worker(model_id, ConnectionMode.HTTP, WorkerType.REGULAR, 1)
|
|
test_gpus = calculate_test_gpus(model_id, 0, 0, 1)
|
|
|
|
if test_gpus > _max_test_gpu_requirement:
|
|
_max_test_gpu_requirement = test_gpus
|
|
_max_test_name = item.nodeid
|
|
|
|
# Log results
|
|
if _worker_counts:
|
|
summary = []
|
|
for key in _first_seen_order:
|
|
model_id, mode, worker_type = key
|
|
count = _worker_counts[key]
|
|
if worker_type == WorkerType.REGULAR:
|
|
summary.append(f"{model_id}:{mode.value}x{count}")
|
|
else:
|
|
summary.append(f"{model_id}:{mode.value}:{worker_type.value}x{count}")
|
|
logger.info("Scanned worker requirements (in test order): %s", summary)
|
|
logger.info(
|
|
"Max GPU requirement for single test: %d (%s)",
|
|
_max_test_gpu_requirement,
|
|
_max_test_name,
|
|
)
|
|
else:
|
|
logger.info("Scanned worker requirements: (none)")
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Pool requirements
|
|
# ---------------------------------------------------------------------------
|
|
|
|
|
|
def get_pool_requirements() -> list["WorkerIdentity"]:
|
|
"""Build pool requirements from scanned test markers.
|
|
|
|
Returns:
|
|
List of WorkerIdentity objects to pre-launch.
|
|
"""
|
|
from infra import DEFAULT_MODEL, ConnectionMode, WorkerIdentity, WorkerType
|
|
|
|
# Track which models have PD workers as their first requirement
|
|
models_with_pd_first: set[str] = set()
|
|
first_worker_type_per_model: dict[str, WorkerType] = {}
|
|
|
|
for model_id, mode, worker_type in _first_seen_order:
|
|
if model_id not in first_worker_type_per_model:
|
|
first_worker_type_per_model[model_id] = worker_type
|
|
if worker_type in (WorkerType.PREFILL, WorkerType.DECODE):
|
|
models_with_pd_first.add(model_id)
|
|
logger.info(
|
|
"Model %s has PD test first - skipping regular worker pre-launch",
|
|
model_id,
|
|
)
|
|
|
|
# Generate individual WorkerIdentity objects in first-seen order
|
|
requirements: list[WorkerIdentity] = []
|
|
for model_id, mode, worker_type in _first_seen_order:
|
|
if model_id in models_with_pd_first and worker_type == WorkerType.REGULAR:
|
|
continue
|
|
|
|
count = _worker_counts.get((model_id, mode, worker_type), 1)
|
|
for i in range(count):
|
|
requirements.append(WorkerIdentity(model_id, mode, worker_type, i))
|
|
|
|
if not requirements:
|
|
requirements.append(WorkerIdentity(DEFAULT_MODEL, ConnectionMode.HTTP))
|
|
|
|
return requirements
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# GPU validation
|
|
# ---------------------------------------------------------------------------
|
|
|
|
|
|
def _count_gpus_without_cuda() -> int:
|
|
"""Count available GPUs without initializing CUDA.
|
|
|
|
Uses nvidia-smi to avoid CUDA initialization, which is critical for
|
|
pytest-parallel compatibility. CUDA cannot be re-initialized after a fork.
|
|
"""
|
|
import subprocess
|
|
|
|
try:
|
|
result = subprocess.run(
|
|
["nvidia-smi", "--query-gpu=name", "--format=csv,noheader"],
|
|
capture_output=True,
|
|
text=True,
|
|
timeout=10,
|
|
)
|
|
if result.returncode == 0:
|
|
return len([line for line in result.stdout.strip().split("\n") if line])
|
|
except (subprocess.SubprocessError, FileNotFoundError, OSError):
|
|
pass
|
|
return 0
|
|
|
|
|
|
def validate_gpu_requirements() -> tuple[int, int]:
|
|
"""Check if there are enough GPUs for any single test.
|
|
|
|
Uses nvidia-smi instead of torch.cuda to avoid CUDA initialization,
|
|
which would break pytest-parallel (CUDA cannot be re-initialized after fork).
|
|
|
|
Returns:
|
|
Tuple of (max_required_gpus, available_gpus).
|
|
"""
|
|
available_gpus = _count_gpus_without_cuda()
|
|
return _max_test_gpu_requirement, available_gpus
|
|
|
|
|
|
def pytest_collection_finish(session: pytest.Session) -> None:
|
|
"""Validate GPU requirements after test collection."""
|
|
from infra import ENV_SKIP_MODEL_POOL, LOG_SEPARATOR_WIDTH
|
|
|
|
if not _worker_counts:
|
|
return
|
|
|
|
if os.environ.get(ENV_SKIP_MODEL_POOL, "").lower() in ("1", "true", "yes"):
|
|
return
|
|
|
|
max_required, available_gpus = validate_gpu_requirements()
|
|
|
|
if max_required > available_gpus:
|
|
sep = "=" * LOG_SEPARATOR_WIDTH
|
|
raise pytest.UsageError(
|
|
f"\n{sep}\n"
|
|
f"GPU REQUIREMENTS EXCEEDED\n"
|
|
f"{sep}\n"
|
|
f"Test '{_max_test_name}' requires {max_required} GPUs\n"
|
|
f"Available: {available_gpus} GPUs\n"
|
|
f"\nOptions:\n"
|
|
f" 1. Run tests that fit: pytest -k 'not {_max_test_name.split('::')[0]}'\n"
|
|
f" 2. Reduce workers: @pytest.mark.workers(prefill=1, decode=1)\n"
|
|
f" 3. Skip GPU tests: SKIP_MODEL_POOL=1 pytest\n"
|
|
f"{sep}"
|
|
)
|
|
|
|
logger.info(
|
|
"GPU validation passed: max %d required (by %s), %d available",
|
|
max_required,
|
|
_max_test_name,
|
|
available_gpus,
|
|
)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Marker registration
|
|
# ---------------------------------------------------------------------------
|
|
|
|
|
|
def pytest_configure(config: pytest.Config) -> None:
|
|
"""Register custom markers."""
|
|
config.addinivalue_line(
|
|
"markers",
|
|
"model(name): mark test to use a specific model from MODEL_SPECS",
|
|
)
|
|
config.addinivalue_line(
|
|
"markers",
|
|
"backend(name): mark test to use a specific backend (grpc, http, openai, etc.)",
|
|
)
|
|
config.addinivalue_line(
|
|
"markers",
|
|
"workers(count=1, prefill=None, decode=None): "
|
|
"worker configuration - use count for regular workers, "
|
|
"or prefill/decode for PD disaggregation mode",
|
|
)
|
|
config.addinivalue_line(
|
|
"markers",
|
|
"gateway(policy='round_robin', timeout=None, extra_args=None): "
|
|
"gateway/router configuration",
|
|
)
|
|
config.addinivalue_line(
|
|
"markers",
|
|
"e2e: mark test as an end-to-end test requiring GPU workers",
|
|
)
|
|
config.addinivalue_line(
|
|
"markers",
|
|
"slow: mark test as slow-running",
|
|
)
|
|
config.addinivalue_line(
|
|
"markers",
|
|
"thread_unsafe: mark test as incompatible with parallel thread execution",
|
|
)
|
|
config.addinivalue_line(
|
|
"markers",
|
|
"storage(backend): mark test to use a specific history storage backend "
|
|
"(memory, oracle). Default is memory.",
|
|
)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Parallel execution support
|
|
# ---------------------------------------------------------------------------
|
|
|
|
|
|
def is_parallel_execution(config: pytest.Config) -> bool:
|
|
"""Check if tests are running in parallel mode (pytest-parallel).
|
|
|
|
Returns True if --tests-per-worker > 1, indicating concurrent thread execution.
|
|
"""
|
|
# pytest-parallel adds the 'tests_per_worker' option
|
|
tests_per_worker = getattr(config.option, "tests_per_worker", None)
|
|
if tests_per_worker is None:
|
|
return False
|
|
|
|
if tests_per_worker == "auto":
|
|
return True
|
|
|
|
try:
|
|
return int(tests_per_worker) > 1
|
|
except (ValueError, TypeError):
|
|
return False
|
|
|
|
|
|
def pytest_runtest_setup(item: pytest.Item) -> None:
|
|
"""Skip thread_unsafe tests when running in parallel mode."""
|
|
if is_parallel_execution(item.config):
|
|
marker = item.get_closest_marker("thread_unsafe")
|
|
if marker:
|
|
reason = marker.kwargs.get("reason", "Test is not thread-safe")
|
|
pytest.skip(f"Skipping in parallel mode: {reason}")
|