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[CI] Remove profiling from nightly tests (#33832)

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This commit is contained in:
Baizhou Zhang
2026-08-06 01:16:08 -07:00
committed by GitHub
parent c11ce7c514
commit 0e584529f5
65 changed files with 214 additions and 429 deletions
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.github/workflows/nightly-test-nvidia.yml
+4 -108
View File
@@ -204,33 +204,12 @@ jobs:
if: always()
timeout-minutes: 300
env:
TRACE_BASE_URL: https://raw.githubusercontent.com/sglang-bot/sglang-ci-data/main/traces/${{ github.run_id }}
PERFETTO_RELAY_URL: ${{ vars.PERFETTO_RELAY_URL }}
GPU_CONFIG: "8-gpu-h200"
IS_H200: "1"
run: |
cd test
python3 run_suite.py --hw cuda --suite nightly-8-gpu-common --nightly --timeout-per-file=18000 --continue-on-error --auto-partition-id=${{ matrix.partition }} --auto-partition-size=4
- name: Publish traces to storage repo
if: always()
continue-on-error: true
env:
GITHUB_TOKEN: ${{ secrets.GH_PAT_FOR_NIGHTLY_CI_DATA }}
GITHUB_RUN_ID: ${{ github.run_id }}
GITHUB_RUN_NUMBER: ${{ github.run_number }}
run: |
TRACE_ARGS=""
for dir in test/performance_profiles_*/; do
[ -d "$dir" ] && TRACE_ARGS="$TRACE_ARGS --traces-dir $dir"
done
if [ -n "$TRACE_ARGS" ]; then
python3 scripts/ci/utils/publish_traces.py $TRACE_ARGS
find test/performance_profiles_*/ -name '*.json.gz' -delete
else
echo "No trace directories found, skipping publish"
fi
- name: Run test
timeout-minutes: 30
env:
@@ -247,7 +226,7 @@ jobs:
--partition ${{ matrix.partition }} \
--run-id ${{ github.run_id }} \
--output test/metrics-8gpu-h200-partition-${{ matrix.partition }}.json \
--search-dir test/performance_profiles_8_gpu \
--search-dir test/performance_results_8_gpu \
--search-dir test
- name: Upload partition metrics
@@ -318,32 +297,11 @@ jobs:
if: always()
timeout-minutes: 200
env:
TRACE_BASE_URL: https://raw.githubusercontent.com/sglang-bot/sglang-ci-data/main/traces/${{ github.run_id }}
PERFETTO_RELAY_URL: ${{ vars.PERFETTO_RELAY_URL }}
GPU_CONFIG: "8-gpu-b200"
run: |
cd test
python3 run_suite.py --hw cuda --suite nightly-8-gpu-common --nightly --timeout-per-file=12000 --continue-on-error --auto-partition-id=${{ matrix.partition }} --auto-partition-size=4
- name: Publish traces to storage repo
if: always()
continue-on-error: true
env:
GITHUB_TOKEN: ${{ secrets.GH_PAT_FOR_NIGHTLY_CI_DATA }}
GITHUB_RUN_ID: ${{ github.run_id }}
GITHUB_RUN_NUMBER: ${{ github.run_number }}
run: |
TRACE_ARGS=""
for dir in test/performance_profiles_*/; do
[ -d "$dir" ] && TRACE_ARGS="$TRACE_ARGS --traces-dir $dir"
done
if [ -n "$TRACE_ARGS" ]; then
python3 scripts/ci/utils/publish_traces.py $TRACE_ARGS
find test/performance_profiles_*/ -name '*.json.gz' -delete
else
echo "No trace directories found, skipping publish"
fi
- name: Collect performance metrics
if: always()
run: |
@@ -352,7 +310,7 @@ jobs:
--partition ${{ matrix.partition }} \
--run-id ${{ github.run_id }} \
--output test/metrics-8gpu-b200-partition-${{ matrix.partition }}.json \
--search-dir test/performance_profiles_8_gpu \
--search-dir test/performance_results_8_gpu \
--search-dir test
- name: Upload partition metrics
@@ -413,22 +371,12 @@ jobs:
- name: Run performance test for text models
timeout-minutes: 30
env:
TRACE_BASE_URL: https://raw.githubusercontent.com/sglang-bot/sglang-ci-data/main/traces/${{ github.run_id }}
PERFETTO_RELAY_URL: ${{ vars.PERFETTO_RELAY_URL }}
GPU_CONFIG: "2-gpu-h100"
run: |
cd test
rm -rf performance_profiles_text_models/
rm -rf performance_results_text_models/
python3 run_suite.py --hw cuda --suite nightly-perf-text-2-gpu --nightly --continue-on-error --timeout-per-file 3600
- name: Publish traces to storage repo
env:
GITHUB_TOKEN: ${{ secrets.GH_PAT_FOR_NIGHTLY_CI_DATA }}
GITHUB_RUN_ID: ${{ github.run_id }}
GITHUB_RUN_NUMBER: ${{ github.run_number }}
run: |
python3 scripts/ci/utils/publish_traces.py --traces-dir test/performance_profiles_text_models
- uses: ./.github/actions/upload-cuda-coredumps
if: failure()
@@ -476,22 +424,12 @@ jobs:
- name: Run perf test for VLM models (MMMU)
timeout-minutes: 30
env:
TRACE_BASE_URL: https://raw.githubusercontent.com/sglang-bot/sglang-ci-data/main/traces/${{ github.run_id }}
PERFETTO_RELAY_URL: ${{ vars.PERFETTO_RELAY_URL }}
GPU_CONFIG: "2-gpu-h100"
run: |
cd test
rm -rf performance_profiles_vlms/
rm -rf performance_results_vlms/
python3 run_suite.py --hw cuda --suite nightly-perf-vlm-2-gpu --nightly --continue-on-error --timeout-per-file 3600
- name: Publish traces to storage repo
env:
GITHUB_TOKEN: ${{ secrets.GH_PAT_FOR_NIGHTLY_CI_DATA }}
GITHUB_RUN_ID: ${{ github.run_id }}
GITHUB_RUN_NUMBER: ${{ github.run_number }}
run: |
python3 scripts/ci/utils/publish_traces.py --traces-dir test/performance_profiles_vlms
- uses: ./.github/actions/upload-cuda-coredumps
if: failure()
@@ -514,32 +452,11 @@ jobs:
- name: Run test
timeout-minutes: 200
env:
TRACE_BASE_URL: https://raw.githubusercontent.com/sglang-bot/sglang-ci-data/main/traces/${{ github.run_id }}
PERFETTO_RELAY_URL: ${{ vars.PERFETTO_RELAY_URL }}
GPU_CONFIG: "4-gpu-b200"
run: |
cd test
python3 run_suite.py --hw cuda --suite nightly-4-gpu-b200 --nightly --continue-on-error --timeout-per-file 12000
- name: Publish traces to storage repo
if: always()
continue-on-error: true
env:
GITHUB_TOKEN: ${{ secrets.GH_PAT_FOR_NIGHTLY_CI_DATA }}
GITHUB_RUN_ID: ${{ github.run_id }}
GITHUB_RUN_NUMBER: ${{ github.run_number }}
run: |
TRACE_ARGS=""
for dir in test/performance_profiles_*/; do
[ -d "$dir" ] && TRACE_ARGS="$TRACE_ARGS --traces-dir $dir"
done
if [ -n "$TRACE_ARGS" ]; then
python3 scripts/ci/utils/publish_traces.py $TRACE_ARGS
find test/performance_profiles_*/ -name '*.json.gz' -delete
else
echo "No trace directories found, skipping publish"
fi
- uses: ./.github/actions/upload-cuda-coredumps
if: failure()
@@ -577,32 +494,11 @@ jobs:
- name: Run test
timeout-minutes: 600
env:
TRACE_BASE_URL: https://raw.githubusercontent.com/sglang-bot/sglang-ci-data/main/traces/${{ github.run_id }}
PERFETTO_RELAY_URL: ${{ vars.PERFETTO_RELAY_URL }}
GPU_CONFIG: "4-gpu-gb300"
run: |
cd test
python3 run_suite.py --hw cuda --suite ${{ matrix.suite }} --nightly --continue-on-error --timeout-per-file 7200
- name: Publish traces to storage repo
if: always()
continue-on-error: true
env:
GITHUB_TOKEN: ${{ secrets.GH_PAT_FOR_NIGHTLY_CI_DATA }}
GITHUB_RUN_ID: ${{ github.run_id }}
GITHUB_RUN_NUMBER: ${{ github.run_number }}
run: |
TRACE_ARGS=""
for dir in test/performance_profiles_*/; do
[ -d "$dir" ] && TRACE_ARGS="$TRACE_ARGS --traces-dir $dir"
done
if [ -n "$TRACE_ARGS" ]; then
python3 scripts/ci/utils/publish_traces.py $TRACE_ARGS
find test/performance_profiles_*/ -name '*.json.gz' -delete
else
echo "No trace directories found, skipping publish"
fi
- uses: ./.github/actions/upload-cuda-coredumps
if: failure()
python/sglang/test/nightly_bench_utils.py
+6 -55
View File
@@ -1,12 +1,9 @@
import json
import logging
import os
from typing import List, Optional
from pydantic import BaseModel
logger = logging.getLogger(__name__)
# TODO:
# There is huge redundancy between BenchmarkResult and BenchOneCaseResult, and redundancy between to_markdown_row, generate_markdown_report, get_report_summary.
# We should refactor them to reduce the code duplication.
@@ -33,17 +30,7 @@ class BenchmarkResult(BaseModel):
profile_link_decode: Optional[str] = None
server_args: Optional[List[str]] = None
@staticmethod
def help_str() -> str:
return f"""
Note: To view the traces through perfetto-ui, please:
1. open with Google Chrome
2. allow popup
"""
def to_markdown_row(
self, trace_dir, base_url: str = "", relay_base: str = ""
) -> str:
def to_markdown_row(self) -> str:
"""Convert this benchmark result to a markdown table row."""
hourly_cost_per_gpu = 2 # $2/hour for one H100
@@ -54,42 +41,11 @@ Note: To view the traces through perfetto-ui, please:
input_cost = 1e6 / (self.input_throughput * input_util) / 3600 * hourly_cost
output_cost = 1e6 / self.output_throughput / 3600 * hourly_cost
def get_perfetto_relay_link_from_trace_file(trace_file: str):
from urllib.parse import quote
rel_path = os.path.relpath(trace_file, trace_dir)
raw_file_link = f"{base_url}/{rel_path}"
relay_link = (
f"{relay_base}?src={quote(raw_file_link, safe='')}"
if relay_base
else raw_file_link
)
return relay_link
# Handle profile links
profile_link = "NA | NA"
if self.profile_link_extend or self.profile_link_decode:
# Create a combined link or use the first available one
trace_files = [self.profile_link_extend, self.profile_link_decode]
if any(trace_file is None for trace_file in trace_files):
logger.error("Some trace files are None", f"{trace_files=}")
trace_files_relay_links = [
(
f"[trace]({get_perfetto_relay_link_from_trace_file(trace_file)})"
if trace_file
else "N/A"
)
for trace_file in trace_files
]
profile_link = " | ".join(trace_files_relay_links)
# Build the row
return f"| {self.batch_size} | {self.input_len} | {self.latency:.2f} | {self.input_throughput:.2f} | {self.output_throughput:.2f} | {accept_length} | {itl:.2f} | {input_cost:.2f} | {output_cost:.2f} | {profile_link} |\n"
return f"| {self.batch_size} | {self.input_len} | {self.latency:.2f} | {self.input_throughput:.2f} | {self.output_throughput:.2f} | {accept_length} | {itl:.2f} | {input_cost:.2f} | {output_cost:.2f} |\n"
def generate_markdown_report(
trace_dir, results: List[BenchmarkResult], variant: Optional[str] = None
results: List[BenchmarkResult], variant: Optional[str] = None
) -> str:
"""Generate a markdown report from a list of BenchmarkResult object from a single run."""
# Build model header with run_name if it's not "default"
@@ -107,17 +63,12 @@ def generate_markdown_report(
summary = f"### {model_header}\n"
summary += "| batch size | input len | latency (s) | input throughput (tok/s) | output throughput (tok/s) | acc length | ITL (ms) | input cost ($/1M) | output cost ($/1M) | profile (extend) | profile (decode)|\n"
summary += "| ---------- | --------- | ----------- | ------------------------- | ------------------------- | ---------- | -------- | ----------------- | ------------------ | ---------------- | --------------- |\n"
summary += "| batch size | input len | latency (s) | input throughput (tok/s) | output throughput (tok/s) | acc length | ITL (ms) | input cost ($/1M) | output cost ($/1M) |\n"
summary += "| ---------- | --------- | ----------- | ------------------------- | ------------------------- | ---------- | -------- | ----------------- | ------------------ |\n"
# all results should share the same isl & osl
for result in results:
base_url = os.getenv("TRACE_BASE_URL", "").rstrip("/")
relay_base = os.getenv(
"PERFETTO_RELAY_URL",
"",
).rstrip("/")
summary += result.to_markdown_row(trace_dir, base_url, relay_base)
summary += result.to_markdown_row()
return summary
python/sglang/test/nightly_utils.py
+17 -44
View File
@@ -1,4 +1,4 @@
"""Utilities for running nightly performance benchmarks with profiling."""
"""Utilities for running nightly performance benchmarks."""
import json
import os
@@ -19,16 +19,16 @@ from sglang.test.test_utils import (
class NightlyBenchmarkRunner:
"""Helper class for running nightly performance benchmarks with profiling.
"""Helper class for running nightly performance benchmarks.
This class encapsulates common patterns used across nightly performance tests,
including profile directory management, benchmark command construction,
including result directory management, benchmark command construction,
result parsing, and report generation.
"""
def __init__(
self,
profile_dir: str,
result_dir: str,
test_name: str,
base_url: str,
gpu_config: str = None,
@@ -36,12 +36,12 @@ class NightlyBenchmarkRunner:
"""Initialize the benchmark runner.
Args:
profile_dir: Directory to store performance profiles
result_dir: Directory to store benchmark results
test_name: Name of the test (used for reporting)
base_url: Base URL for the server
gpu_config: Optional GPU configuration string (e.g., "2-gpu-h100", "8-gpu-b200")
"""
self.profile_dir = profile_dir
self.result_dir = result_dir
self.test_name = test_name
self.base_url = base_url
self.gpu_config = gpu_config or os.environ.get("GPU_CONFIG", "")
@@ -51,38 +51,32 @@ class NightlyBenchmarkRunner:
if self.gpu_config:
header += f" ({self.gpu_config})"
header += "\n"
self.full_report = header + BenchmarkResult.help_str()
self.full_report = header
def setup_profile_directory(self) -> None:
"""Create the profile directory if it doesn't exist."""
os.makedirs(self.profile_dir, exist_ok=True)
def setup_result_directory(self) -> None:
"""Create the result directory if it doesn't exist."""
os.makedirs(self.result_dir, exist_ok=True)
def generate_profile_filename(
self, model_path: str, variant: str = ""
) -> Tuple[str, str]:
"""Generate unique profile filename and path for the model.
def generate_result_filename(self, model_path: str, variant: str = "") -> str:
"""Generate a unique result filename for the model.
Args:
model_path: Path to the model (e.g., "deepseek-ai/DeepSeek-V3.1")
variant: Optional variant suffix (e.g., "basic", "mtp", "dsa")
Returns:
Tuple of (profile_path_prefix, json_output_file)
Path to the JSON result file
"""
timestamp = int(time.time())
model_safe_name = model_path.replace("/", "_")
# Build filename with optional variant
if variant:
profile_filename = f"{model_safe_name}_{variant}_{timestamp}"
json_filename = f"results_{model_safe_name}_{variant}_{timestamp}.json"
else:
profile_filename = f"{model_safe_name}_{timestamp}"
json_filename = f"results_{model_safe_name}_{timestamp}.json"
profile_path_prefix = os.path.join(self.profile_dir, profile_filename)
return profile_path_prefix, json_filename
return os.path.join(self.result_dir, json_filename)
def build_benchmark_command(
self,
@@ -90,11 +84,9 @@ class NightlyBenchmarkRunner:
batch_sizes: List[int],
input_lens: Tuple[int, ...],
output_lens: Tuple[int, ...],
profile_path_prefix: str,
json_output_file: str,
extra_args: Optional[List[str]] = None,
server_args: Optional[List[str]] = None,
enable_profile: bool = True,
) -> List[str]:
"""Build the benchmark command with all required arguments.
@@ -103,11 +95,9 @@ class NightlyBenchmarkRunner:
batch_sizes: List of batch sizes to test
input_lens: Tuple of input lengths to test
output_lens: Tuple of output lengths to test
profile_path_prefix: Prefix for profile output files
json_output_file: Path to JSON output file
extra_args: Optional extra arguments to append to command
server_args: Optional server launch arguments to record in metrics
enable_profile: Whether to enable profiling (default True for NVIDIA)
Returns:
List of command arguments ready for subprocess.run()
@@ -132,17 +122,6 @@ class NightlyBenchmarkRunner:
"--trust-remote-code",
]
# Add profiling flags only if enabled (disabled for AMD tests)
if enable_profile and profile_path_prefix:
command.extend(
[
"--profile",
"--profile-by-stage",
"--profile-output-dir",
profile_path_prefix,
]
)
if extra_args:
command.extend(extra_args)
@@ -227,7 +206,6 @@ class NightlyBenchmarkRunner:
other_args: Optional[List[str]] = None,
variant: str = "",
extra_bench_args: Optional[List[str]] = None,
enable_profile: bool = True,
timeout: Optional[int] = None,
env: Optional[dict] = None,
) -> Tuple[List[BenchmarkResult], bool, Optional[float]]:
@@ -235,7 +213,7 @@ class NightlyBenchmarkRunner:
This method handles:
- Server launch and cleanup
- Profile filename generation
- Result filename generation
- Benchmark command construction and execution
- Result loading and parsing
- Fetching speculative decoding accept length (for MTP/EAGLE)
@@ -248,7 +226,6 @@ class NightlyBenchmarkRunner:
other_args: Arguments to pass to server launch
variant: Optional variant suffix (e.g., "basic", "mtp")
extra_bench_args: Extra arguments for the benchmark command
enable_profile: Whether to enable profiling (default True for NVIDIA)
timeout: Optional timeout for server launch (defaults to DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH)
env: Environment dict for subprocess
@@ -275,9 +252,7 @@ class NightlyBenchmarkRunner:
)
# Generate filenames
profile_path_prefix, json_output_file = self.generate_profile_filename(
model_path, variant
)
json_output_file = self.generate_result_filename(model_path, variant)
# Build and run benchmark command
# Prepare extra args with run_name if variant is specified
@@ -290,11 +265,9 @@ class NightlyBenchmarkRunner:
batch_sizes,
input_lens,
output_lens,
profile_path_prefix,
json_output_file,
extra_args=bench_args,
server_args=other_args,
enable_profile=enable_profile,
)
result, cmd_success = self.run_benchmark_command(command, model_description)
@@ -346,7 +319,7 @@ class NightlyBenchmarkRunner:
results: List of BenchmarkResult objects to add to report
"""
if results:
report_part = generate_markdown_report(self.profile_dir, results, variant)
report_part = generate_markdown_report(results, variant)
self.full_report += report_part + "\n"
def write_final_report(self) -> None:
python/sglang/test/performance_test_runner.py
+7 -8
View File
@@ -13,7 +13,7 @@ class PerformanceTestParams:
batch_sizes: List[int] = field(default_factory=lambda: [1, 8, 16])
input_lens: Tuple[int, ...] = (8192,)
output_lens: Tuple[int, ...] = (512,)
profile_dir: Optional[str] = None # None = auto-generate based on is_vlm
result_dir: Optional[str] = None # None = auto-generate based on is_vlm
dataset_name: str = "mmmu" # For VLM perf test
# MTP/EAGLE speculative decoding: minimum accept length threshold (None = no validation)
spec_accept_length_threshold: Optional[float] = None
@@ -86,9 +86,8 @@ def run_performance_test(
perf_runner.add_report(results, variant=model.variant)
print(f"✓ Performance test succeeded for {model.model_path}")
# The cumulative /server_info accept length is reset by the cache
# flush before the profiling phase, so it can be missing here. Fall
# back to the per-run accept lengths captured during benchmarking.
# Fall back to the per-run accept lengths captured during benchmarking
# when the cumulative /server_info metric is unavailable.
if avg_spec_accept_length is None:
run_accept_lengths = [
r.acc_length
@@ -155,7 +154,7 @@ def run_performance_test(
def run_performance_for_models(
models: List[ModelLaunchSettings],
profile_dir: str,
result_dir: str,
test_name: str,
base_url: Optional[str] = None,
batch_sizes: List[int] = None,
@@ -168,7 +167,7 @@ def run_performance_for_models(
Args:
models: List of ModelLaunchSettings to test
profile_dir: Directory for performance profiles
result_dir: Directory for performance results
test_name: Name for the test (used in reports)
base_url: Server base URL (default: DEFAULT_URL_FOR_TEST)
batch_sizes: Batch sizes for perf test
@@ -188,11 +187,11 @@ def run_performance_for_models(
# Setup performance runner
perf_runner = NightlyBenchmarkRunner(
profile_dir=profile_dir,
result_dir=result_dir,
test_name=test_name,
base_url=base_url,
)
perf_runner.setup_profile_directory()
perf_runner.setup_result_directory()
all_results = []
all_passed = True
python/sglang/test/run_combined_tests.py
+4 -6
View File
@@ -76,18 +76,16 @@ def run_combined_tests(
# Set up performance parameters
if run_perf:
perf = performance_params
profile_dir = perf.profile_dir or (
"performance_profiles_vlms"
if is_vlm
else "performance_profiles_text_models"
result_dir = perf.result_dir or (
"performance_results_vlms" if is_vlm else "performance_results_text_models"
)
perf_runner = NightlyBenchmarkRunner(
profile_dir=profile_dir,
result_dir=result_dir,
test_name=test_name,
base_url=base_url,
)
perf_runner.setup_profile_directory()
perf_runner.setup_result_directory()
else:
perf_runner = None
scripts/ci/utils/save_metrics.py
+4 -4
View File
@@ -1,7 +1,7 @@
#!/usr/bin/env python3
"""Collect and save performance metrics from nightly benchmark results.
This script reads benchmark result JSON files from performance profile directories
This script reads benchmark result JSON files from performance result directories
and saves them with metadata for artifact collection in CI.
Usage:
@@ -223,9 +223,9 @@ def main():
# Default search directories if none specified
search_dirs = args.search_dirs or [
"test/performance_profiles_8_gpu",
"test/performance_profiles_text_models",
"test/performance_profiles_vlms",
"test/performance_results_8_gpu",
"test/performance_results_text_models",
"test/performance_results_vlms",
"test",
".",
]
test/manual/nightly/test_deepseek_v31_perf.py
+3 -3
View File
@@ -4,7 +4,7 @@ from sglang.test.nightly_utils import NightlyBenchmarkRunner
from sglang.test.test_utils import DEFAULT_URL_FOR_TEST, _parse_int_list_env
DEEPSEEK_V31_MODEL_PATH = "deepseek-ai/DeepSeek-V3.1"
PROFILE_DIR = "performance_profiles_deepseek_v31"
RESULT_DIR = "performance_results_deepseek_v31"
class TestNightlyDeepseekV31Performance(unittest.TestCase):
@@ -50,8 +50,8 @@ class TestNightlyDeepseekV31Performance(unittest.TestCase):
},
]
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
def test_bench_one_batch(self):
failed_variants = []
test/manual/nightly/test_deepseek_v32_perf.py
+3 -3
View File
@@ -4,7 +4,7 @@ from sglang.test.nightly_utils import NightlyBenchmarkRunner
from sglang.test.test_utils import DEFAULT_URL_FOR_TEST, _parse_int_list_env
DEEPSEEK_V32_MODEL_PATH = "deepseek-ai/DeepSeek-V3.2"
PROFILE_DIR = "performance_profiles_deepseek_v32"
RESULT_DIR = "performance_results_deepseek_v32"
class TestNightlyDeepseekV32Performance(unittest.TestCase):
@@ -91,8 +91,8 @@ class TestNightlyDeepseekV32Performance(unittest.TestCase):
},
]
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
def test_bench_one_batch(self):
failed_variants = []
test/manual/nightly/test_text_models_perf.py
+3 -3
View File
@@ -8,7 +8,7 @@ from sglang.test.test_utils import (
parse_models,
)
PROFILE_DIR = "performance_profiles_text_models"
RESULT_DIR = "performance_results_text_models"
class TestNightlyTextModelsPerformance(unittest.TestCase):
@@ -28,8 +28,8 @@ class TestNightlyTextModelsPerformance(unittest.TestCase):
cls.batch_sizes = [1, 1, 8, 16, 64]
cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_INPUT_LENS", "4096"))
cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_OUTPUT_LENS", "512"))
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
def test_bench_one_batch(self):
all_model_succeed = True
test/manual/nightly/test_vlms_perf.py
+3 -3
View File
@@ -10,7 +10,7 @@ from sglang.test.test_utils import (
parse_models,
)
PROFILE_DIR = "performance_profiles_vlms"
RESULT_DIR = "performance_results_vlms"
MODEL_DEFAULTS = [
# Keep conservative defaults. Can be overridden by env NIGHTLY_VLM_MODELS
@@ -49,8 +49,8 @@ class TestNightlyVLMModelsPerformance(unittest.TestCase):
cls.batch_sizes = _parse_int_list_env("NIGHTLY_VLM_BATCH_SIZES", "1,1,2,8,16")
cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_VLM_INPUT_LENS", "4096"))
cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_VLM_OUTPUT_LENS", "512"))
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
def test_bench_one_batch(self):
all_model_succeed = True
test/manual/test_deepseek_v31.py
+1 -1
View File
@@ -61,7 +61,7 @@ class TestDeepseekV31(unittest.TestCase):
dataset="gsm8k", baseline_accuracy=0.935
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_deepseek_v31",
result_dir="performance_results_deepseek_v31",
),
)
test/manual/test_glm_46_fp8.py
+1 -1
View File
@@ -50,7 +50,7 @@ class TestGLM46FP8(unittest.TestCase):
test_name="GLM-4.6-FP8",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.80),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_glm_4_6_fp8",
result_dir="performance_results_glm_4_6_fp8",
),
)
test/manual/test_qwen3_235b.py
+1 -1
View File
@@ -61,7 +61,7 @@ class TestQwen3235BFP8(unittest.TestCase):
test_name="Qwen3-235B-FP8",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.88),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_qwen3_235b_fp8",
result_dir="performance_results_qwen3_235b_fp8",
),
)
test/registered/8-gpu-models/test_glm52_fp8.py
+1 -1
View File
@@ -59,7 +59,7 @@ class TestGlm52Fp8(unittest.TestCase):
test_name="GLM-5.2-FP8",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.92),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_glm_52_fp8",
result_dir="performance_results_glm_52_fp8",
),
)
test/registered/8-gpu-models/test_glm_46.py
+1 -1
View File
@@ -43,7 +43,7 @@ class TestGLM46(unittest.TestCase):
test_name="GLM-4.6",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.80),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_glm_4_6",
result_dir="performance_results_glm_4_6",
),
)
test/registered/8-gpu-models/test_gpt_oss_120b.py
+1 -1
View File
@@ -74,7 +74,7 @@ class TestGptOss120B(unittest.TestCase):
test_name="GPT-OSS-120B",
accuracy_params=None,
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_gpt_oss_120b",
result_dir="performance_results_gpt_oss_120b",
),
)
test/registered/8-gpu-models/test_inkling_nvfp4_nightly.py
+1 -1
View File
@@ -70,7 +70,7 @@ class TestInklingNVFP4Nightly(unittest.TestCase):
repeat=1,
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_inkling_nvfp4",
result_dir="performance_results_inkling_nvfp4",
),
)
test/registered/8-gpu-models/test_kimi_k25.py
+1 -1
View File
@@ -54,7 +54,7 @@ class TestKimiK25(unittest.TestCase):
test_name="Kimi-K2.5",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.92),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_kimi_k25",
result_dir="performance_results_kimi_k25",
),
)
test/registered/8-gpu-models/test_llama4.py
+1 -1
View File
@@ -47,7 +47,7 @@ class TestLlama4(unittest.TestCase):
test_name="Llama-4-Scout",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.9),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_llama4",
result_dir="performance_results_llama4",
),
)
test/registered/8-gpu-models/test_longcat_flash_lite_fp8.py
+1 -1
View File
@@ -58,7 +58,7 @@ class TestLongCatFlashLiteFp8(unittest.TestCase):
num_examples=200,
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_longcat_flash_lite_fp8",
result_dir="performance_results_longcat_flash_lite_fp8",
),
)
test/registered/8-gpu-models/test_minimax_m25.py
+1 -1
View File
@@ -54,7 +54,7 @@ class TestMiniMaxM25(unittest.TestCase):
test_name="MiniMax-M2.5",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.80),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_minimax_m25",
result_dir="performance_results_minimax_m25",
),
)
test/registered/8-gpu-models/test_mistral_large3.py
+1 -1
View File
@@ -89,7 +89,7 @@ class TestMistralLarge3(unittest.TestCase):
test_name="Mistral-Large-3",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.85),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_mistral_large3",
result_dir="performance_results_mistral_large3",
),
)
test/registered/8-gpu-models/test_nvidia_nemotron_3_super_nightly.py
+2 -2
View File
@@ -92,7 +92,7 @@ class TestNvidiaNemotron3SuperNightly(unittest.TestCase):
repeat=1,
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_nemotron_3_super_bf16",
result_dir="performance_results_nemotron_3_super_bf16",
),
)
@@ -129,7 +129,7 @@ class TestNvidiaNemotron3SuperNightly(unittest.TestCase):
repeat=1,
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_nemotron_3_super_nvfp4",
result_dir="performance_results_nemotron_3_super_nvfp4",
),
)
test/registered/8-gpu-models/test_qwen35.py
+1 -1
View File
@@ -71,7 +71,7 @@ class TestQwen35(unittest.TestCase):
num_examples=200,
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_qwen35",
result_dir="performance_results_qwen35",
),
)
test/registered/amd/perf/mi30x/test_deepseek_v31_perf.py
+6 -7
View File
@@ -22,7 +22,7 @@ register_amd_ci(est_time=18000, suite="nightly-perf-8-gpu-deepseek-v31", nightly
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -56,7 +56,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
DEEPSEEK_V31_MODEL_PATH = os.environ.get(
"DEEPSEEK_V31_MODEL_PATH", "deepseek-ai/DeepSeek-V3.1"
)
PROFILE_DIR = "performance_profiles_deepseek_v31"
RESULT_DIR = "performance_results_deepseek_v31"
class TestNightlyDeepseekV31Performance(unittest.TestCase):
@@ -109,9 +109,9 @@ class TestNightlyDeepseekV31Performance(unittest.TestCase):
},
]
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
# Override full_report to remove traces help text
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
# Set the report header for this test
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -129,7 +129,6 @@ class TestNightlyDeepseekV31Performance(unittest.TestCase):
other_args=variant_config["other_args"],
variant=variant_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
@@ -137,7 +136,7 @@ class TestNightlyDeepseekV31Performance(unittest.TestCase):
if not success:
failed_variants.append(variant_config["name"])
# Use simplified report format without traces
# Use the simplified report format
if results:
self.runner.full_report += (
generate_simple_markdown_report(results) + "\n"
test/registered/amd/perf/mi30x/test_deepseek_v32_basic_perf_amd.py
+6 -7
View File
@@ -26,7 +26,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -60,7 +60,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
DEEPSEEK_V32_MODEL_PATH = os.environ.get(
"DEEPSEEK_V32_MODEL_PATH", "deepseek-ai/DeepSeek-V3.2"
)
PROFILE_DIR = "performance_profiles_deepseek_v32_basic_mi325"
RESULT_DIR = "performance_results_deepseek_v32_basic_mi325"
class TestNightlyDeepseekV32BasicPerformance(unittest.TestCase):
@@ -99,9 +99,9 @@ class TestNightlyDeepseekV32BasicPerformance(unittest.TestCase):
"env_vars": {"SGLANG_USE_AITER": "1"},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
# Override full_report to remove traces help text
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
# Set the report header for this test
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -115,7 +115,6 @@ class TestNightlyDeepseekV32BasicPerformance(unittest.TestCase):
other_args=self.variant_config["other_args"],
variant=self.variant_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
@@ -125,7 +124,7 @@ class TestNightlyDeepseekV32BasicPerformance(unittest.TestCase):
if avg_spec_accept_length is not None:
print(f" avg_spec_accept_length={avg_spec_accept_length:.2f}")
# Use simplified report format without traces
# Use the simplified report format
if results:
self.runner.full_report += (
generate_simple_markdown_report(results) + "\n"
test/registered/amd/perf/mi30x/test_deepseek_v32_mtp_perf_amd.py
+6 -7
View File
@@ -27,7 +27,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -61,7 +61,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
DEEPSEEK_V32_MODEL_PATH = os.environ.get(
"DEEPSEEK_V32_MODEL_PATH", "deepseek-ai/DeepSeek-V3.2"
)
PROFILE_DIR = "performance_profiles_deepseek_v32_mtp_mi325"
RESULT_DIR = "performance_results_deepseek_v32_mtp_mi325"
class TestNightlyDeepseekV32MTPPerformance(unittest.TestCase):
@@ -108,9 +108,9 @@ class TestNightlyDeepseekV32MTPPerformance(unittest.TestCase):
"env_vars": {"SGLANG_USE_AITER": "1"},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
# Override full_report to remove traces help text
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
# Set the report header for this test
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -124,7 +124,6 @@ class TestNightlyDeepseekV32MTPPerformance(unittest.TestCase):
other_args=self.variant_config["other_args"],
variant=self.variant_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
@@ -134,7 +133,7 @@ class TestNightlyDeepseekV32MTPPerformance(unittest.TestCase):
if avg_spec_accept_length is not None:
print(f" avg_spec_accept_length={avg_spec_accept_length:.2f}")
# Use simplified report format without traces
# Use the simplified report format
if results:
self.runner.full_report += (
generate_simple_markdown_report(results) + "\n"
test/registered/amd/perf/mi30x/test_deepseek_v3_perf.py
+6 -7
View File
@@ -22,7 +22,7 @@ register_amd_ci(est_time=18000, suite="nightly-perf-8-gpu-deepseek-v3", nightly=
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns."""
"""Generate a simplified markdown report without cost columns."""
model_header = results[0].model_path
if results[0].run_name and results[0].run_name != "default":
model_header += f" ({results[0].run_name})"
@@ -46,7 +46,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
DEEPSEEK_V3_MODEL_PATH = os.environ.get(
"DEEPSEEK_V3_MODEL_PATH", "deepseek-ai/DeepSeek-V3-0324"
)
PROFILE_DIR = "performance_profiles_deepseek_v3"
RESULT_DIR = "performance_results_deepseek_v3"
class TestNightlyDeepseekV3Performance(unittest.TestCase):
@@ -99,9 +99,9 @@ class TestNightlyDeepseekV3Performance(unittest.TestCase):
},
]
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
# Override full_report to remove traces help text
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
# Set the report header for this test
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -119,7 +119,6 @@ class TestNightlyDeepseekV3Performance(unittest.TestCase):
other_args=variant_config["other_args"],
variant=variant_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
@@ -127,7 +126,7 @@ class TestNightlyDeepseekV3Performance(unittest.TestCase):
if not success:
failed_variants.append(variant_config["name"])
# Use simplified report format without traces
# Use the simplified report format
if results:
self.runner.full_report += (
generate_simple_markdown_report(results) + "\n"
test/registered/amd/perf/mi30x/test_glm51_perf_amd.py
+3 -4
View File
@@ -47,7 +47,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
GLM51_MODEL_PATH = os.environ.get("GLM51_MODEL_PATH", "zai-org/GLM-5.1-FP8")
PROFILE_DIR = "performance_profiles_glm51"
RESULT_DIR = "performance_results_glm51"
class TestNightlyGLM51Performance(unittest.TestCase):
@@ -94,8 +94,8 @@ class TestNightlyGLM51Performance(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_glm51(self):
@@ -113,7 +113,6 @@ class TestNightlyGLM51Performance(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi30x/test_glm5_perf_amd.py
+3 -4
View File
@@ -48,7 +48,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
GLM5_MODEL_PATH = os.environ.get("GLM5_MODEL_PATH", "zai-org/GLM-5-FP8")
PROFILE_DIR = "performance_profiles_glm5"
RESULT_DIR = "performance_results_glm5"
class TestNightlyGLM5Performance(unittest.TestCase):
@@ -95,8 +95,8 @@ class TestNightlyGLM5Performance(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_glm5(self):
@@ -115,7 +115,6 @@ class TestNightlyGLM5Performance(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi30x/test_grok1_fp8_perf.py
+4 -5
View File
@@ -24,7 +24,7 @@ register_amd_ci(est_time=1500, suite="nightly-perf-8-gpu-grok1-fp8", nightly=Tru
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns."""
"""Generate a simplified markdown report without cost columns."""
model_header = results[0].model_path
if results[0].run_name and results[0].run_name != "default":
model_header += f" ({results[0].run_name})"
@@ -47,7 +47,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
# Model and tokenizer paths can be overridden via environment variables
GROK1_MODEL_PATH = os.environ.get("GROK1_MODEL_PATH", "lmzheng/grok-1")
GROK1_TOKENIZER_PATH = os.environ.get("GROK1_TOKENIZER_PATH", "Xenova/grok-1-tokenizer")
PROFILE_DIR = "performance_profiles_grok1_fp8"
RESULT_DIR = "performance_results_grok1_fp8"
class TestNightlyGrok1FP8Performance(unittest.TestCase):
@@ -87,8 +87,8 @@ class TestNightlyGrok1FP8Performance(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_grok1_fp8(self):
@@ -109,7 +109,6 @@ class TestNightlyGrok1FP8Performance(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi30x/test_grok1_int4_perf.py
+4 -5
View File
@@ -24,7 +24,7 @@ register_amd_ci(est_time=1500, suite="nightly-perf-8-gpu-grok1-int4", nightly=Tr
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -57,7 +57,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
# Model and tokenizer paths can be overridden via environment variables
GROK1_MODEL_PATH = os.environ.get("GROK1_MODEL_PATH", "amd/grok-1-W4A8KV8")
GROK1_TOKENIZER_PATH = os.environ.get("GROK1_TOKENIZER_PATH", "Xenova/grok-1-tokenizer")
PROFILE_DIR = "performance_profiles_grok1_int4"
RESULT_DIR = "performance_results_grok1_int4"
class TestNightlyGrok1INT4Performance(unittest.TestCase):
@@ -97,8 +97,8 @@ class TestNightlyGrok1INT4Performance(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_grok1_int4(self):
@@ -119,7 +119,6 @@ class TestNightlyGrok1INT4Performance(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi30x/test_grok2_perf.py
+4 -5
View File
@@ -24,7 +24,7 @@ register_amd_ci(est_time=1500, suite="nightly-perf-8-gpu-grok2", nightly=True)
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -59,7 +59,7 @@ GROK2_MODEL_PATH = os.environ.get("GROK2_MODEL_PATH", "xai-org/grok-2")
GROK2_TOKENIZER_PATH = os.environ.get(
"GROK2_TOKENIZER_PATH", "alvarobartt/grok-2-tokenizer"
)
PROFILE_DIR = "performance_profiles_grok2"
RESULT_DIR = "performance_results_grok2"
class TestNightlyGrok2Performance(unittest.TestCase):
@@ -99,8 +99,8 @@ class TestNightlyGrok2Performance(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_grok2(self):
@@ -121,7 +121,6 @@ class TestNightlyGrok2Performance(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi30x/test_kimi_k26_perf_amd.py
+4 -5
View File
@@ -28,7 +28,7 @@ register_amd_ci(est_time=5400, suite="nightly-perf-8-gpu-kimi-k26", nightly=True
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -58,7 +58,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
KIMI_K26_MODEL_PATH = os.environ.get("KIMI_K26_MODEL_PATH", "moonshotai/Kimi-K2.6")
PROFILE_DIR = "performance_profiles_kimi_k26"
RESULT_DIR = "performance_results_kimi_k26"
class TestNightlyKimiK26Performance(unittest.TestCase):
@@ -101,8 +101,8 @@ class TestNightlyKimiK26Performance(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_kimi_k26(self):
@@ -121,7 +121,6 @@ class TestNightlyKimiK26Performance(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi30x/test_minimax_m25_perf_amd.py
+4 -5
View File
@@ -23,7 +23,7 @@ register_amd_ci(est_time=5400, suite="nightly-perf-8-gpu-minimax-m25", nightly=T
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -55,7 +55,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
MINIMAX_M25_MODEL_PATH = os.environ.get(
"MINIMAX_M25_MODEL_PATH", "MiniMaxAI/MiniMax-M2.5"
)
PROFILE_DIR = "performance_profiles_minimax_m25"
RESULT_DIR = "performance_results_minimax_m25"
class TestNightlyMiniMaxM25Performance(unittest.TestCase):
@@ -94,8 +94,8 @@ class TestNightlyMiniMaxM25Performance(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_minimax_m25(self):
@@ -115,7 +115,6 @@ class TestNightlyMiniMaxM25Performance(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi30x/test_minimax_m27_perf_amd.py
+4 -5
View File
@@ -23,7 +23,7 @@ register_amd_ci(est_time=5400, suite="nightly-perf-8-gpu-minimax-m27", nightly=T
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -55,7 +55,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
MINIMAX_M27_MODEL_PATH = os.environ.get(
"MINIMAX_M27_MODEL_PATH", "MiniMaxAI/MiniMax-M2.7"
)
PROFILE_DIR = "performance_profiles_minimax_m27"
RESULT_DIR = "performance_results_minimax_m27"
class TestNightlyMiniMaxM27Performance(unittest.TestCase):
@@ -94,8 +94,8 @@ class TestNightlyMiniMaxM27Performance(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_minimax_m27(self):
@@ -115,7 +115,6 @@ class TestNightlyMiniMaxM27Performance(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi30x/test_qwen35_fp8_perf_amd.py
+4 -5
View File
@@ -24,7 +24,7 @@ register_amd_ci(est_time=5400, suite="nightly-perf-8-gpu-qwen35-fp8", nightly=Tr
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -56,7 +56,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
QWEN35_FP8_MODEL_PATH = os.environ.get(
"QWEN35_FP8_MODEL_PATH", "Qwen/Qwen3.5-397B-A17B-FP8"
)
PROFILE_DIR = "performance_profiles_qwen35_fp8"
RESULT_DIR = "performance_results_qwen35_fp8"
class TestNightlyQwen35Fp8Performance(unittest.TestCase):
@@ -94,8 +94,8 @@ class TestNightlyQwen35Fp8Performance(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_qwen35_fp8(self):
@@ -114,7 +114,6 @@ class TestNightlyQwen35Fp8Performance(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi30x/test_text_models_perf_amd.py
+4 -5
View File
@@ -25,11 +25,11 @@ from sglang.test.test_utils import (
# Register for AMD CI - Text models benchmark (~60 min)
register_amd_ci(est_time=3600, suite="nightly-amd-perf-text-2-gpu", nightly=True)
PROFILE_DIR = "performance_profiles_text_models_amd"
RESULT_DIR = "performance_results_text_models_amd"
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -89,8 +89,8 @@ class TestNightlyTextModelsPerfAMD(unittest.TestCase):
cls.batch_sizes = [1, 1, 8, 16, 64]
cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_INPUT_LENS", "4096"))
cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_OUTPUT_LENS", "512"))
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -110,7 +110,6 @@ class TestNightlyTextModelsPerfAMD(unittest.TestCase):
input_lens=self.input_lens,
output_lens=self.output_lens,
other_args=other_args,
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi30x/test_vlms_perf_amd.py
+4 -5
View File
@@ -26,7 +26,7 @@ from sglang.test.test_utils import (
# Register for AMD CI - VLM models benchmark (~120 min)
register_amd_ci(est_time=7200, suite="nightly-amd-perf-vlm-2-gpu", nightly=True)
PROFILE_DIR = "performance_profiles_vlms_amd"
RESULT_DIR = "performance_results_vlms_amd"
# VLM models suitable for AMD
MODEL_DEFAULTS = [
@@ -42,7 +42,7 @@ MODEL_DEFAULTS = [
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -95,8 +95,8 @@ class TestNightlyVLMsPerfAMD(unittest.TestCase):
cls.batch_sizes = _parse_int_list_env("NIGHTLY_VLM_BATCH_SIZES", "1,1,2,8,16")
cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_VLM_INPUT_LENS", "4096"))
cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_VLM_OUTPUT_LENS", "512"))
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -123,7 +123,6 @@ class TestNightlyVLMsPerfAMD(unittest.TestCase):
output_lens=self.output_lens,
other_args=other_args,
extra_bench_args=extra_bench_args,
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi35x/test_deepseek_r1_mxfp4_ar_fusion_perf_mi35x.py
+4 -5
View File
@@ -24,7 +24,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -54,7 +54,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
return summary
PROFILE_DIR = "performance_profiles_deepseek_r1_mxfp4_ar_fusion_mi35x"
RESULT_DIR = "performance_results_deepseek_r1_mxfp4_ar_fusion_mi35x"
class TestDeepseekR1MXFP4ArFusionPerfMI35x(unittest.TestCase):
@@ -90,8 +90,8 @@ class TestDeepseekR1MXFP4ArFusionPerfMI35x(unittest.TestCase):
},
]
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -109,7 +109,6 @@ class TestDeepseekR1MXFP4ArFusionPerfMI35x(unittest.TestCase):
other_args=variant_config["other_args"],
variant=variant_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi35x/test_deepseek_r1_mxfp4_kv_fp8_perf_mi35x.py
+4 -5
View File
@@ -24,7 +24,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -54,7 +54,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
return summary
PROFILE_DIR = "performance_profiles_deepseek_r1_mxfp4_kv_fp8_mi35x"
RESULT_DIR = "performance_results_deepseek_r1_mxfp4_kv_fp8_mi35x"
class TestDeepseekR1MXFP4KvFp8PerfMI35x(unittest.TestCase):
@@ -91,8 +91,8 @@ class TestDeepseekR1MXFP4KvFp8PerfMI35x(unittest.TestCase):
},
]
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -110,7 +110,6 @@ class TestDeepseekR1MXFP4KvFp8PerfMI35x(unittest.TestCase):
other_args=variant_config["other_args"],
variant=variant_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi35x/test_deepseek_r1_mxfp4_perf_mi35x.py
+6 -7
View File
@@ -21,7 +21,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -51,7 +51,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
return summary
PROFILE_DIR = "performance_profiles_deepseek_r1_mxfp4_mi35x"
RESULT_DIR = "performance_results_deepseek_r1_mxfp4_mi35x"
class TestDeepseekR1MXFP4PerfMI35x(unittest.TestCase):
@@ -88,9 +88,9 @@ class TestDeepseekR1MXFP4PerfMI35x(unittest.TestCase):
},
]
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
# Override full_report to remove traces help text
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
# Set the report header for this test
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -108,7 +108,6 @@ class TestDeepseekR1MXFP4PerfMI35x(unittest.TestCase):
other_args=variant_config["other_args"],
variant=variant_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
@@ -116,7 +115,7 @@ class TestDeepseekR1MXFP4PerfMI35x(unittest.TestCase):
if not success:
failed_variants.append(variant_config["name"])
# Use simplified report format without traces
# Use the simplified report format
if results:
self.runner.full_report += (
generate_simple_markdown_report(results) + "\n"
test/registered/amd/perf/mi35x/test_deepseek_v32_basic_perf_mi35x.py
+6 -7
View File
@@ -26,7 +26,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -60,7 +60,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
DEEPSEEK_V32_MODEL_PATH = os.environ.get(
"DEEPSEEK_V32_MODEL_PATH", "deepseek-ai/DeepSeek-V3.2"
)
PROFILE_DIR = "performance_profiles_deepseek_v32_basic"
RESULT_DIR = "performance_results_deepseek_v32_basic"
class TestNightlyDeepseekV32BasicPerformance(unittest.TestCase):
@@ -98,9 +98,9 @@ class TestNightlyDeepseekV32BasicPerformance(unittest.TestCase):
],
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
# Override full_report to remove traces help text
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
# Set the report header for this test
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -114,13 +114,12 @@ class TestNightlyDeepseekV32BasicPerformance(unittest.TestCase):
other_args=self.variant_config["other_args"],
variant=self.variant_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
timeout=5400, # Extended timeout for large model loading
)
results = result_tuple[0]
success = result_tuple[1]
# Use simplified report format without traces
# Use the simplified report format
if results:
self.runner.full_report += (
generate_simple_markdown_report(results) + "\n"
test/registered/amd/perf/mi35x/test_deepseek_v32_mtp_perf_mi35x.py
+7 -11
View File
@@ -32,7 +32,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -82,9 +82,7 @@ def _run_benchmark_with_timeout(
timeout=timeout,
)
try:
profile_path_prefix, json_output_file = runner.generate_profile_filename(
model_path, variant
)
json_output_file = runner.generate_result_filename(model_path, variant)
bench_args = list(extra_bench_args) if extra_bench_args else []
if variant:
bench_args.extend(["--run-name", variant])
@@ -93,10 +91,8 @@ def _run_benchmark_with_timeout(
batch_sizes,
input_lens,
output_lens,
profile_path_prefix,
json_output_file,
extra_args=bench_args,
enable_profile=False, # Disable profiling for AMD tests
)
_, cmd_success = runner.run_benchmark_command(command, model_description)
if not cmd_success:
@@ -113,7 +109,7 @@ def _run_benchmark_with_timeout(
DEEPSEEK_V32_MODEL_PATH = os.environ.get(
"DEEPSEEK_V32_MODEL_PATH", "deepseek-ai/DeepSeek-V3.2"
)
PROFILE_DIR = "performance_profiles_deepseek_v32_mtp"
RESULT_DIR = "performance_results_deepseek_v32_mtp"
SERVER_LAUNCH_TIMEOUT = 5400
@@ -160,9 +156,9 @@ class TestNightlyDeepseekV32MTPPerformance(unittest.TestCase):
],
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
# Override full_report to remove traces help text
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
# Set the report header for this test
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -187,7 +183,7 @@ class TestNightlyDeepseekV32MTPPerformance(unittest.TestCase):
if avg_spec_accept_length is not None:
print(f" avg_spec_accept_length={avg_spec_accept_length:.2f}")
# Use simplified report format without traces
# Use the simplified report format
if results:
self.runner.full_report += (
generate_simple_markdown_report(results) + "\n"
test/registered/amd/perf/mi35x/test_glm51_perf_mi35x.py
+3 -4
View File
@@ -45,7 +45,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
GLM51_MODEL_PATH = os.environ.get("GLM51_MODEL_PATH", "zai-org/GLM-5.1-FP8")
PROFILE_DIR = "performance_profiles_glm51_mi35x"
RESULT_DIR = "performance_results_glm51_mi35x"
class TestGLM51PerfMI35x(unittest.TestCase):
@@ -96,8 +96,8 @@ class TestGLM51PerfMI35x(unittest.TestCase):
}
os.environ.setdefault("SGLANG_BENCH_TIMEOUT", "3600")
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_glm51_perf(self):
@@ -115,7 +115,6 @@ class TestGLM51PerfMI35x(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi35x/test_glm5_mxfp4_perf_mi35x.py
+4 -5
View File
@@ -25,7 +25,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -58,7 +58,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
return summary
PROFILE_DIR = "performance_profiles_glm5_mxfp4_mi35x"
RESULT_DIR = "performance_results_glm5_mxfp4_mi35x"
class TestGLM5MXFP4PerfMI35x(unittest.TestCase):
@@ -99,8 +99,8 @@ class TestGLM5MXFP4PerfMI35x(unittest.TestCase):
},
]
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_one_batch(self):
@@ -124,7 +124,6 @@ class TestGLM5MXFP4PerfMI35x(unittest.TestCase):
other_args=variant_config["other_args"],
variant=variant_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi35x/test_glm5_perf_mi35x.py
+3 -4
View File
@@ -44,7 +44,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
GLM5_MODEL_PATH = os.environ.get("GLM5_MODEL_PATH", "zai-org/GLM-5-FP8")
PROFILE_DIR = "performance_profiles_glm5_mi35x"
RESULT_DIR = "performance_results_glm5_mi35x"
class TestGLM5PerfMI35x(unittest.TestCase):
@@ -94,8 +94,8 @@ class TestGLM5PerfMI35x(unittest.TestCase):
}
os.environ.setdefault("SGLANG_BENCH_TIMEOUT", "3600")
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_glm5_perf(self):
@@ -114,7 +114,6 @@ class TestGLM5PerfMI35x(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi35x/test_grok1_int4_perf_mi35x.py
+4 -5
View File
@@ -21,7 +21,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -54,7 +54,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
# Model and tokenizer paths can be overridden via environment variables
GROK1_MODEL_PATH = os.environ.get("GROK1_MODEL_PATH", "amd/grok-1-W4A8KV8")
GROK1_TOKENIZER_PATH = os.environ.get("GROK1_TOKENIZER_PATH", "Xenova/grok-1-tokenizer")
PROFILE_DIR = "performance_profiles_grok1_int4_mi35x"
RESULT_DIR = "performance_results_grok1_int4_mi35x"
class TestGrok1INT4PerfMI35x(unittest.TestCase):
@@ -90,8 +90,8 @@ class TestGrok1INT4PerfMI35x(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_grok1_int4_perf(self):
@@ -112,7 +112,6 @@ class TestGrok1INT4PerfMI35x(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi35x/test_grok2_perf_mi35x.py
+4 -5
View File
@@ -19,7 +19,7 @@ register_amd_ci(est_time=1500, suite="nightly-perf-8-gpu-mi35x-grok2", nightly=T
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -54,7 +54,7 @@ GROK2_MODEL_PATH = os.environ.get("GROK2_MODEL_PATH", "xai-org/grok-2")
GROK2_TOKENIZER_PATH = os.environ.get(
"GROK2_TOKENIZER_PATH", "alvarobartt/grok-2-tokenizer"
)
PROFILE_DIR = "performance_profiles_grok2_mi35x"
RESULT_DIR = "performance_results_grok2_mi35x"
class TestGrok2PerfMI35x(unittest.TestCase):
@@ -90,8 +90,8 @@ class TestGrok2PerfMI35x(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_grok2_perf(self):
@@ -112,7 +112,6 @@ class TestGrok2PerfMI35x(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False, # Disable profiling for AMD tests
)
results = result_tuple[0]
success = result_tuple[1]
test/registered/amd/perf/mi35x/test_kimi_k26_perf_mi35x.py
+4 -5
View File
@@ -28,7 +28,7 @@ register_amd_ci(est_time=5400, suite="nightly-perf-8-gpu-mi35x-kimi-k26", nightl
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -58,7 +58,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
KIMI_K26_MODEL_PATH = os.environ.get("KIMI_K26_MODEL_PATH", "moonshotai/Kimi-K2.6")
PROFILE_DIR = "performance_profiles_kimi_k26_mi35x"
RESULT_DIR = "performance_results_kimi_k26_mi35x"
class TestNightlyKimiK26PerformanceMI35x(unittest.TestCase):
@@ -101,8 +101,8 @@ class TestNightlyKimiK26PerformanceMI35x(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_kimi_k26(self):
@@ -121,7 +121,6 @@ class TestNightlyKimiK26PerformanceMI35x(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi35x/test_minimax_m25_perf_mi35x.py
+4 -5
View File
@@ -25,7 +25,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -57,7 +57,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
MINIMAX_M25_MODEL_PATH = os.environ.get(
"MINIMAX_M25_MODEL_PATH", "MiniMaxAI/MiniMax-M2.5"
)
PROFILE_DIR = "performance_profiles_minimax_m25_mi35x"
RESULT_DIR = "performance_results_minimax_m25_mi35x"
class TestNightlyMiniMaxM25PerformanceMI35x(unittest.TestCase):
@@ -96,8 +96,8 @@ class TestNightlyMiniMaxM25PerformanceMI35x(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_minimax_m25(self):
@@ -117,7 +117,6 @@ class TestNightlyMiniMaxM25PerformanceMI35x(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi35x/test_minimax_m27_perf_mi35x.py
+4 -5
View File
@@ -25,7 +25,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -57,7 +57,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
MINIMAX_M27_MODEL_PATH = os.environ.get(
"MINIMAX_M27_MODEL_PATH", "MiniMaxAI/MiniMax-M2.7"
)
PROFILE_DIR = "performance_profiles_minimax_m27_mi35x"
RESULT_DIR = "performance_results_minimax_m27_mi35x"
class TestNightlyMiniMaxM27PerformanceMI35x(unittest.TestCase):
@@ -96,8 +96,8 @@ class TestNightlyMiniMaxM27PerformanceMI35x(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_bench_minimax_m27(self):
@@ -117,7 +117,6 @@ class TestNightlyMiniMaxM27PerformanceMI35x(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/amd/perf/mi35x/test_qwen35_fp8_perf_mi35x.py
+4 -5
View File
@@ -21,7 +21,7 @@ register_amd_ci(
def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
"""Generate a simplified markdown report without traces and cost columns.
"""Generate a simplified markdown report without cost columns.
Skips the first result if it's a warmup run (duplicate batch_size).
"""
@@ -53,7 +53,7 @@ def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str:
QWEN35_FP8_MODEL_PATH = os.environ.get(
"QWEN35_FP8_MODEL_PATH", "Qwen/Qwen3.5-397B-A17B-FP8"
)
PROFILE_DIR = "performance_profiles_qwen35_fp8_mi35x"
RESULT_DIR = "performance_results_qwen35_fp8_mi35x"
class TestQwen35Fp8PerfMI35x(unittest.TestCase):
@@ -87,8 +87,8 @@ class TestQwen35Fp8PerfMI35x(unittest.TestCase):
},
}
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
cls.runner.full_report = f"## {cls.__name__}\n"
def test_qwen35_fp8_perf(self):
@@ -107,7 +107,6 @@ class TestQwen35Fp8PerfMI35x(unittest.TestCase):
other_args=self.model_config["other_args"],
variant=self.model_config["name"],
extra_bench_args=["--trust-remote-code"],
enable_profile=False,
timeout=5400,
)
results = result_tuple[0]
test/registered/gb300/test_deepseek_v4_pro_fp4.py
+1 -1
View File
@@ -136,7 +136,7 @@ class TestDeepSeekV4ProFp4(unittest.TestCase):
accuracy_params=accuracy_params,
performance_params=PerformanceTestParams(
batch_sizes=PERFORMANCE_BATCH_SIZES[variant.variant],
profile_dir="performance_profiles_gb300",
result_dir="performance_results_gb300",
),
)
except AssertionError as e:
test/registered/gb300/test_glm52_nvfp4.py
+1 -1
View File
@@ -61,7 +61,7 @@ class TestGlm52Nvfp4(unittest.TestCase):
test_name="GLM-5.2-NVFP4",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.92),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_gb300",
result_dir="performance_results_gb300",
),
)
test/registered/gb300/test_kimi_k25.py
+1 -1
View File
@@ -54,7 +54,7 @@ class TestKimiK25(unittest.TestCase):
dataset="mmmu-pro", baseline_accuracy=0.69, repeat=1, max_tokens=32768
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_gb300",
result_dir="performance_results_gb300",
),
)
test/registered/gb300/test_kimi_k25_nvfp4.py
+1 -1
View File
@@ -69,7 +69,7 @@ class TestKimiK25Nvfp4(unittest.TestCase):
dataset="mmmu-pro", baseline_accuracy=0.69, repeat=1, max_tokens=32768
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_gb300",
result_dir="performance_results_gb300",
),
)
test/registered/gb300/test_qwen35_fp8.py
+1 -1
View File
@@ -65,7 +65,7 @@ class TestQwen35Fp8(unittest.TestCase):
dataset="mmmu-pro", baseline_accuracy=0.76, repeat=1, max_tokens=32768
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_gb300",
result_dir="performance_results_gb300",
),
)
test/registered/gb300/test_qwen35_nvfp4.py
+1 -1
View File
@@ -74,7 +74,7 @@ class TestQwen35Nvfp4(unittest.TestCase):
dataset="mmmu-pro", baseline_accuracy=0.76, repeat=1, max_tokens=32768
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_gb300",
result_dir="performance_results_gb300",
),
)
test/registered/perf/test_dpsk_v3_fp4_4gpu_perf.py
+1 -1
View File
@@ -68,7 +68,7 @@ class TestDeepseekR1FP4Unified(unittest.TestCase):
api="completion",
),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_deepseek_v3_fp4",
result_dir="performance_results_deepseek_v3_fp4",
),
)
test/registered/perf/test_gpt_oss_4gpu_perf.py
+3 -3
View File
@@ -6,7 +6,7 @@ from sglang.test.test_utils import DEFAULT_URL_FOR_TEST
register_cuda_ci(est_time=600, suite="nightly-4-gpu-b200", nightly=True)
PROFILE_DIR = "performance_profiles_gpt_oss_4gpu"
RESULT_DIR = "performance_results_gpt_oss_4gpu"
class TestNightlyGptOss4GpuPerformance(unittest.TestCase):
@@ -29,8 +29,8 @@ class TestNightlyGptOss4GpuPerformance(unittest.TestCase):
cls.batch_sizes = [1, 1, 8, 16, 64]
cls.input_lens = (4096,)
cls.output_lens = (512,)
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
def test_bench_one_batch(self):
all_model_succeed = True
test/registered/perf/test_text_models_perf.py
+3 -3
View File
@@ -11,7 +11,7 @@ from sglang.test.test_utils import (
register_cuda_ci(est_time=3600, suite="nightly-perf-text-2-gpu", nightly=True)
PROFILE_DIR = "performance_profiles_text_models"
RESULT_DIR = "performance_results_text_models"
class TestNightlyTextModelsPerformance(unittest.TestCase):
@@ -31,8 +31,8 @@ class TestNightlyTextModelsPerformance(unittest.TestCase):
cls.batch_sizes = [1, 1, 8, 16, 64]
cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_INPUT_LENS", "4096"))
cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_OUTPUT_LENS", "512"))
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
def test_bench_one_batch(self):
all_model_succeed = True
test/registered/perf/test_vlms_perf.py
+3 -3
View File
@@ -13,7 +13,7 @@ from sglang.test.test_utils import (
register_cuda_ci(est_time=7200, suite="nightly-perf-vlm-2-gpu", nightly=True)
PROFILE_DIR = "performance_profiles_vlms"
RESULT_DIR = "performance_results_vlms"
MODEL_DEFAULTS = [
# Keep conservative defaults. Can be overridden by env NIGHTLY_VLM_MODELS
@@ -52,8 +52,8 @@ class TestNightlyVLMModelsPerformance(unittest.TestCase):
cls.batch_sizes = _parse_int_list_env("NIGHTLY_VLM_BATCH_SIZES", "1,1,2,8,16")
cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_VLM_INPUT_LENS", "4096"))
cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_VLM_OUTPUT_LENS", "512"))
cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url)
cls.runner.setup_profile_directory()
cls.runner = NightlyBenchmarkRunner(RESULT_DIR, cls.__name__, cls.base_url)
cls.runner.setup_result_directory()
def test_bench_one_batch(self):
all_model_succeed = True
test/registered/quant/test_kimi_k25_nvfp4_eagle.py
+1 -1
View File
@@ -59,7 +59,7 @@ class TestKimiK25Nvfp4Eagle(unittest.TestCase):
performance_params=PerformanceTestParams(
batch_sizes=[1, 8, 16],
spec_accept_length_threshold=2.8,
profile_dir="performance_profiles_kimi_k25_nvfp4_eagle",
result_dir="performance_results_kimi_k25_nvfp4_eagle",
),
)
test/registered/quant/test_kimi_k26_nvfp4_dflash.py
+1 -1
View File
@@ -61,7 +61,7 @@ class TestKimiK26Nvfp4Dflash(unittest.TestCase):
performance_params=PerformanceTestParams(
batch_sizes=[1, 8, 16],
spec_accept_length_threshold=2.0,
profile_dir="performance_profiles_kimi_k26_nvfp4_dflash",
result_dir="performance_results_kimi_k26_nvfp4_dflash",
),
)