mirror of
https://git.datalinker.icu/vllm-project/vllm.git
synced 2025-12-10 05:15:42 +08:00
[CI] Enable all hf transformers baselines in test_hybrid (#23936)
Signed-off-by: Thomas Parnell <tpa@zurich.ibm.com>
This commit is contained in:
Thomas Parnell
GitHub
parent
98aee612aa
commit
d328f7894f
@ -34,17 +34,6 @@ HYBRID_MODELS = [
|
||||
"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",
|
||||
@ -90,20 +79,13 @@ 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
|
||||
|
||||
with monkeypatch.context() as m:
|
||||
m.setenv("VLLM_USE_V1", "0")
|
||||
@ -121,7 +103,7 @@ 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,
|
||||
@ -130,12 +112,10 @@ 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",
|
||||
)
|
||||
|
||||
@ -402,11 +382,8 @@ 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
|
||||
|
||||
with monkeypatch.context() as m:
|
||||
m.setenv("VLLM_USE_V1", "0")
|
||||
@ -421,7 +398,7 @@ 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,
|
||||
@ -429,12 +406,10 @@ def test_full_cuda_graph(
|
||||
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",
|
||||
)
|
||||
|
||||
@ -460,11 +435,8 @@ 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
|
||||
|
||||
with monkeypatch.context() as m:
|
||||
m.setenv("VLLM_USE_V1", "0")
|
||||
@ -480,7 +452,6 @@ 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,
|
||||
@ -488,10 +459,9 @@ def test_fp32_state(
|
||||
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",
|
||||
)
|
||||
|
||||
@ -154,7 +154,7 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
|
||||
"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"}),
|
||||
@ -208,7 +208,8 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
|
||||
"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),
|
||||
@ -228,7 +229,7 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
|
||||
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
|
||||
@ -244,7 +245,11 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
|
||||
"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),
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user