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[CI] Enable all hf transformers baselines in test_hybrid #23936

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Merged
heheda12345 merged 6 commits into from
Sep 2, 2025
Merged

[CI] Enable all hf transformers baselines in test_hybrid #23936

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af077fd
Enable all hf baselines in test_hybrid
tdoublep Aug 29, 2025
22b7cb0
Add min_transformers_version for GraniteMoeHybrid and Mamba2
tdoublep Aug 29, 2025
f608a19
Merge branch 'main' into hybrid-test-fix-hf
tdoublep Aug 29, 2025
3fcc3d0
Fix typo
tdoublep Aug 29, 2025
9ba4908
Remove checks on hf_outputs.
tdoublep Sep 1, 2025
851d009
Merge branch 'main' into hybrid-test-fix-hf
tdoublep Sep 1, 2025
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74 changes: 22 additions & 52 deletions tests/models/language/generation/test_hybrid.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,17 +34,6 @@
"LiquidAI/LFM2-1.2B",
]

HF_UNSUPPORTED_MODELS = [
# The HF transformers implementation of
# Mamba2 is buggy for Codestral as it doesn't handle n_groups, so the test
# doesn't compare vLLM output with HF output.
# See https://github.com/huggingface/transformers/pull/35943
"yujiepan/mamba2-codestral-v0.1-tiny-random",
# transformers 4.55 is still producing garbage for this model
# TODO(tdoublep): follow-up on transformers side
"ibm-granite/granite-4.0-tiny-preview"
]

V1_SUPPORTED_MODELS = [
"state-spaces/mamba-130m-hf",
"ai21labs/Jamba-tiny-dev",
Expand Down Expand Up @@ -85,20 +74,13 @@ def test_models(
try:
model_info = HF_EXAMPLE_MODELS.find_hf_info(model)
model_info.check_available_online(on_fail="skip")
hf_version_check = model_info.check_transformers_version(
on_fail="return")
model_info.check_transformers_version(on_fail="skip")
except ValueError:
hf_version_check = None

if hf_version_check is not None:
print(f"Skipping transformers comparison because: {hf_version_check}")
pass

with hf_runner(model) as hf_model:
if model not in HF_UNSUPPORTED_MODELS and hf_version_check is None:
hf_outputs = hf_model.generate_greedy_logprobs_limit(
example_prompts, max_tokens, num_logprobs)
else:
hf_outputs = None
hf_outputs = hf_model.generate_greedy_logprobs_limit(
example_prompts, max_tokens, num_logprobs)

with monkeypatch.context() as m:
m.setenv("VLLM_USE_V1", "0")
Expand All @@ -116,7 +98,7 @@ def test_models(
else:
vllm_v1_outputs = None

if hf_outputs is not None and vllm_v0_outputs is not None:
if vllm_v0_outputs is not None:
check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v0_outputs,
Expand All @@ -125,12 +107,10 @@ def test_models(
)

if model in V1_SUPPORTED_MODELS:
ref_outputs = hf_outputs if hf_outputs is not None else vllm_v0_outputs
assert ref_outputs is not None
check_logprobs_close(
outputs_0_lst=ref_outputs,
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v1_outputs,
name_0="hf" if hf_outputs is not None else "vllm-v0",
name_0="hf",
name_1="vllm-v1",
)

Expand Down Expand Up @@ -397,11 +377,8 @@ def test_full_cuda_graph(
pass

with hf_runner(model) as hf_model:
if model not in HF_UNSUPPORTED_MODELS:
hf_outputs = hf_model.generate_greedy_logprobs_limit(
example_prompts, max_tokens, num_logprobs)
else:
hf_outputs = None
hf_outputs = hf_model.generate_greedy_logprobs_limit(
example_prompts, max_tokens, num_logprobs)

with monkeypatch.context() as m:
m.setenv("VLLM_USE_V1", "0")
Expand All @@ -416,20 +393,18 @@ def test_full_cuda_graph(
vllm_v1_outputs = vllm_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)

if hf_outputs is not None and vllm_v0_outputs is not None:
if vllm_v0_outputs is not None:
check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v0_outputs,
name_0="hf",
name_1="vllm-v0",
)

ref_outputs = hf_outputs if hf_outputs is not None else vllm_v0_outputs
assert ref_outputs is not None
check_logprobs_close(
outputs_0_lst=ref_outputs,
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v1_outputs,
name_0="hf" if hf_outputs is not None else "vllm-v0",
name_0="hf",
name_1="vllm-v1",
)

Expand All @@ -455,11 +430,8 @@ def test_fp32_state(
pass

with hf_runner(model) as hf_model:
if model not in HF_UNSUPPORTED_MODELS:
hf_outputs = hf_model.generate_greedy_logprobs_limit(
example_prompts, max_tokens, num_logprobs)
else:
hf_outputs = None
hf_outputs = hf_model.generate_greedy_logprobs_limit(
example_prompts, max_tokens, num_logprobs)

with monkeypatch.context() as m:
m.setenv("VLLM_USE_V1", "0")
Expand All @@ -475,18 +447,16 @@ def test_fp32_state(
vllm_v1_outputs = vllm_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)

if hf_outputs is not None:
check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v0_outputs,
name_0="hf",
name_1="vllm-v0",
)
check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v0_outputs,
name_0="hf",
name_1="vllm-v0",
)

ref_outputs = hf_outputs if hf_outputs is not None else vllm_v0_outputs
check_logprobs_close(
outputs_0_lst=ref_outputs,
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v1_outputs,
name_0="hf" if hf_outputs is not None else "vllm-v0",
name_0="hf",
name_1="vllm-v1",
)
13 changes: 9 additions & 4 deletions tests/models/registry.py
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Original file line number Diff line number Diff line change
Expand Up @@ -154,7 +154,7 @@ def check_available_online(
"BailingMoeForCausalLM": _HfExamplesInfo("inclusionAI/Ling-lite-1.5",
trust_remote_code=True),
"BambaForCausalLM": _HfExamplesInfo("ibm-ai-platform/Bamba-9B-v1",
min_transformers_version="4.56.0",
min_transformers_version="4.55.3",
extras={"tiny": "hmellor/tiny-random-BambaForCausalLM"}), # noqa: E501
"BloomForCausalLM": _HfExamplesInfo("bigscience/bloom-560m",
{"1b": "bigscience/bloomz-1b1"}),
Expand Down Expand Up @@ -208,7 +208,8 @@ def check_available_online(
"GptOssForCausalLM": _HfExamplesInfo("lmsys/gpt-oss-20b-bf16"),
"GraniteForCausalLM": _HfExamplesInfo("ibm/PowerLM-3b"),
"GraniteMoeForCausalLM": _HfExamplesInfo("ibm/PowerMoE-3b"),
"GraniteMoeHybridForCausalLM": _HfExamplesInfo("ibm-granite/granite-4.0-tiny-preview"), # noqa: E501
"GraniteMoeHybridForCausalLM": _HfExamplesInfo("ibm-granite/granite-4.0-tiny-preview", # noqa: E501
min_transformers_version="4.55.3"),
"GraniteMoeSharedForCausalLM": _HfExamplesInfo("ibm-research/moe-7b-1b-active-shared-experts"), # noqa: E501
"Grok1ModelForCausalLM": _HfExamplesInfo("hpcai-tech/grok-1",
trust_remote_code=True),
Expand All @@ -228,7 +229,7 @@ def check_available_online(
trust_remote_code=True),
"JAISLMHeadModel": _HfExamplesInfo("inceptionai/jais-13b-chat"),
"JambaForCausalLM": _HfExamplesInfo("ai21labs/AI21-Jamba-1.5-Mini",
min_transformers_version="4.56.0",
min_transformers_version="4.55.3",
extras={
"tiny": "ai21labs/Jamba-tiny-dev",
"random": "ai21labs/Jamba-tiny-random", # noqa: E501
Expand All @@ -244,7 +245,11 @@ def check_available_online(
"Llama4ForCausalLM": _HfExamplesInfo("meta-llama/Llama-4-Scout-17B-16E-Instruct", # noqa: E501
is_available_online=False),
"MambaForCausalLM": _HfExamplesInfo("state-spaces/mamba-130m-hf"),
"Mamba2ForCausalLM": _HfExamplesInfo("mistralai/Mamba-Codestral-7B-v0.1"),
"Mamba2ForCausalLM": _HfExamplesInfo("mistralai/Mamba-Codestral-7B-v0.1",
min_transformers_version="4.55.3",
extras={
"random": "yujiepan/mamba2-codestral-v0.1-tiny-random", # noqa: E501
}),
"FalconMambaForCausalLM": _HfExamplesInfo("tiiuae/falcon-mamba-7b-instruct"), # noqa: E501
"MiniCPMForCausalLM": _HfExamplesInfo("openbmb/MiniCPM-2B-sft-bf16",
trust_remote_code=True),
Expand Down