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[AMD] Add model to AMD nightly test (#14442)

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michael-amd
2025-12-10 11:59:44 -08:00
committed by GitHub
parent c032b559a8
commit c97ce39181
1 changed files with 23 additions and 0 deletions
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test/srt/nightly/test_gsm8k_eval_amd.py
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@@ -27,6 +27,7 @@ MODEL_SCORE_THRESHOLDS = {
"meta-llama/Llama-3.1-70B-Instruct": 0.95, "meta-llama/Llama-3.1-70B-Instruct": 0.95,
"mistralai/Mixtral-8x7B-Instruct-v0.1": 0.64, "mistralai/Mixtral-8x7B-Instruct-v0.1": 0.64,
"Qwen/Qwen2-57B-A14B-Instruct": 0.86, "Qwen/Qwen2-57B-A14B-Instruct": 0.86,
"Qwen/Qwen3-30B-A3B-Thinking-2507": 0.84, # MoE model from sanity_check.py - TP2 verified on MI300X
"neuralmagic/Meta-Llama-3.1-8B-Instruct-FP8": 0.83, "neuralmagic/Meta-Llama-3.1-8B-Instruct-FP8": 0.83,
"neuralmagic/Mistral-7B-Instruct-v0.3-FP8": 0.54, "neuralmagic/Mistral-7B-Instruct-v0.3-FP8": 0.54,
"neuralmagic/Meta-Llama-3.1-70B-Instruct-FP8": 0.94, "neuralmagic/Meta-Llama-3.1-70B-Instruct-FP8": 0.94,
@@ -63,6 +64,11 @@ DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_FP8_TP2 = remove_failing_models(
DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_FP8_TP2 DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_FP8_TP2
) )
# AMD-specific models verified on MI300X with tp=2
AMD_MODEL_NAME_FOR_NIGHTLY_EVAL_TP2 = remove_failing_models(
"Qwen/Qwen3-30B-A3B-Thinking-2507"
)
NO_MOE_PADDING_MODELS = {"neuralmagic/Mixtral-8x7B-Instruct-v0.1-FP8"} NO_MOE_PADDING_MODELS = {"neuralmagic/Mixtral-8x7B-Instruct-v0.1-FP8"}
DISABLE_HF_XET_MODELS = { DISABLE_HF_XET_MODELS = {
"Qwen/Qwen2-57B-A14B-Instruct", "Qwen/Qwen2-57B-A14B-Instruct",
@@ -74,6 +80,10 @@ TRITON_MOE_MODELS = {
"mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mixtral-8x7B-Instruct-v0.1",
"mistralai/Mistral-7B-Instruct-v0.3", "mistralai/Mistral-7B-Instruct-v0.3",
} }
# AMD-specific models that need special launch config (matching in-house CI sanity_check.py)
# AMD_SPECIAL_CONFIG_MODELS = {
# "Qwen/Qwen3-30B-A3B-Thinking-2507", # default config works
# }
def popen_launch_server_wrapper(base_url, model, is_tp2): def popen_launch_server_wrapper(base_url, model, is_tp2):
@@ -81,6 +91,17 @@ def popen_launch_server_wrapper(base_url, model, is_tp2):
if is_tp2: if is_tp2:
other_args.extend(["--tp", "2"]) other_args.extend(["--tp", "2"])
# Use same config as sanity_check.py for AMD-specific models (scaled for tp=2)
# Original tp=8: chunked-prefill-size=130172, max-running-requests=128
# Scaled tp=2: chunked-prefill-size=32543, max-running-requests=32
# if model in AMD_SPECIAL_CONFIG_MODELS:
# other_args.extend([
# "--chunked-prefill-size", "32543",
# "--max-running-requests", "32",
# "--mem-fraction-static", "0.85",
# "--attention-backend", "aiter",
# ])
process = popen_launch_server( process = popen_launch_server(
model, model,
base_url, base_url,
@@ -128,6 +149,8 @@ class TestNightlyGsm8KEval(unittest.TestCase):
(parse_models(DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_TP2), False, True), (parse_models(DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_TP2), False, True),
(parse_models(DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_FP8_TP1), True, False), (parse_models(DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_FP8_TP1), True, False),
(parse_models(DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_FP8_TP2), True, True), (parse_models(DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_FP8_TP2), True, True),
# AMD-specific models verified on MI300X
(parse_models(AMD_MODEL_NAME_FOR_NIGHTLY_EVAL_TP2), False, True),
] ]
cls.base_url = DEFAULT_URL_FOR_TEST cls.base_url = DEFAULT_URL_FOR_TEST