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[V1] Remove V0 code paths for Hybrid models (#25400)

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Signed-off-by: Thomas Parnell <tpa@zurich.ibm.com>
This commit is contained in:
Thomas Parnell
2025-09-23 17:26:13 +02:00
committed by GitHub
parent 2c58742dff
commit a903669e10
31 changed files with 352 additions and 2296 deletions
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55
tests/models/language/generation/test_hybrid.py
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@@ -20,7 +20,9 @@ pytestmark = pytest.mark.hybrid_model
SSM_MODELS = [
"state-spaces/mamba-130m-hf",
"tiiuae/falcon-mamba-tiny-dev",
"yujiepan/mamba2-codestral-v0.1-tiny-random",
# mamba2-codestral in transformers is broken pending:
# https://github.com/huggingface/transformers/pull/40861
#"yujiepan/mamba2-codestral-v0.1-tiny-random",
]
HYBRID_MODELS = [
@@ -31,18 +33,7 @@ HYBRID_MODELS = [
"ibm-granite/granite-4.0-tiny-preview",
"tiiuae/Falcon-H1-0.5B-Base",
"LiquidAI/LFM2-1.2B",
]
V1_SUPPORTED_MODELS = [
"state-spaces/mamba-130m-hf",
"ai21labs/Jamba-tiny-dev",
"pfnet/plamo-2-1b",
"yujiepan/mamba2-codestral-v0.1-tiny-random",
"Zyphra/Zamba2-1.2B-instruct",
"hmellor/tiny-random-BambaForCausalLM",
"ibm-granite/granite-4.0-tiny-preview",
"tiiuae/Falcon-H1-0.5B-Base",
"LiquidAI/LFM2-1.2B",
"tiny-random/qwen3-next-moe",
]
FULL_CUDA_GRAPH_MODELS = [
@@ -51,10 +42,6 @@ FULL_CUDA_GRAPH_MODELS = [
"Zyphra/Zamba2-1.2B-instruct",
]
V0_UNSUPPORTED_MODELS = [
"LiquidAI/LFM2-1.2B",
]
FP32_STATE_MODELS = [
"state-spaces/mamba-130m-hf",
"Zyphra/Zamba2-1.2B-instruct",
@@ -88,20 +75,16 @@ def test_models(
hf_outputs = hf_model.generate_greedy_logprobs_limit(
example_prompts, max_tokens, num_logprobs)
if model in V1_SUPPORTED_MODELS:
with vllm_runner(model, max_num_seqs=MAX_NUM_SEQS) as vllm_model:
vllm_v1_outputs = vllm_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)
else:
vllm_v1_outputs = None
with vllm_runner(model, max_num_seqs=MAX_NUM_SEQS) as vllm_model:
vllm_outputs = vllm_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)
if model in V1_SUPPORTED_MODELS:
check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v1_outputs,
name_0="hf",
name_1="vllm-v1",
)
check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_outputs,
name_0="hf",
name_1="vllm",
)
@pytest.mark.parametrize("model", [SSM_MODELS[0], HYBRID_MODELS[0]])
@@ -299,14 +282,14 @@ def test_full_cuda_graph(
example_prompts, max_tokens, num_logprobs)
with vllm_runner(model, max_num_seqs=MAX_NUM_SEQS) as vllm_model:
vllm_v1_outputs = vllm_model.generate_greedy_logprobs(
vllm_outputs = vllm_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)
check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v1_outputs,
outputs_1_lst=vllm_outputs,
name_0="hf",
name_1="vllm-v1",
name_1="vllm",
)
@@ -340,12 +323,12 @@ def test_fp32_cache_state(
with vllm_runner(model,
max_num_seqs=MAX_NUM_SEQS,
**{cache_dtype_param: "float32"}) as vllm_model:
vllm_v1_outputs = vllm_model.generate_greedy_logprobs(
vllm_outputs = vllm_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)
check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_v1_outputs,
outputs_1_lst=vllm_outputs,
name_0="hf",
name_1="vllm-v1",
name_1="vllm",
)