[Config] Remove diffusion_batch_size and use max_num_seqs instead. (#6484)

Signed-off-by: LyxWxj <yuxuanlou621@foxmail.com>
Signed-off-by: Yuxuan Rho <104440472+LyxWxj@users.noreply.github.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
This commit is contained in:
Yuxuan RhoandHongsheng Liu authored and GitHub committed 2026-09-01 01:02:54 +00:00
1 parent 8e26dce1f4
commit 7992c2213e
16 files changed
+36 -95

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@@ -7,7 +7,7 @@ End-to-end test for diffusion batching via AsyncOmni.
This test fires multiple concurrent ``AsyncOmni.generate()`` calls for a
diffusion model and validates that every caller receives its correct
individual result. When the underlying diffusion stage is configured with
``batch_size > 1`` (via stage config or ``StageDiffusionClient``), the
``max_num_seqs > 1``, the
requests will be batched internally.
Even without explicit batching config this test is useful for verifying
@@ -260,7 +260,7 @@ async def compare_single_vs_parallel(
) -> None:
"""Run the same prompts sequentially then in parallel and print a comparison."""
omni = AsyncOmni(model=model, max_num_seqs=batch_size, diffusion_batch_size=batch_size)
omni = AsyncOmni(model=model, max_num_seqs=batch_size)
try:
await warmup(omni, WARMUP_PROMPTS)
single_time = await run_single(omni, prompts)
@@ -288,7 +288,7 @@ async def main(model: str, num_prompts: int, mode: str, batch_size: int = 1) ->
await compare_single_vs_parallel(model, prompts, batch_size=batch_size)
return
omni = AsyncOmni(model=model, max_num_seqs=batch_size, diffusion_batch_size=batch_size)
omni = AsyncOmni(model=model, max_num_seqs=batch_size)
try:
await warmup(omni, WARMUP_PROMPTS)
@@ -389,7 +389,7 @@ def test_diffusion_batching_async_concurrent(model_name: str):
fired via asyncio.gather. Each request_id must appear in the results."""
async def _inner():
omni = AsyncOmni(model=model_name, diffusion_batch_size=1)
omni = AsyncOmni(model=model_name, max_num_seqs=1)
try:
prompts = TEST_PROMPTS[:4]
sp = _default_sampling_params()
@@ -430,7 +430,7 @@ def test_diffusion_batching_list_prompt_rejected(model_name: str):
"""
async def _inner():
omni = AsyncOmni(model=model_name, diffusion_batch_size=4)
omni = AsyncOmni(model=model_name, max_num_seqs=4)
try:
prompts = TEST_PROMPTS[:4]
sp = _default_sampling_params()
@@ -528,7 +528,7 @@ if __name__ == "__main__":
"--batch-size",
type=int,
default=1,
help="Scheduler in-flight width (--max-num-seqs) and client diffusion_batch_size",
help="Scheduler in-flight width (--max-num-seqs)",
)
parser.add_argument(
"--mode",
@@ -441,7 +441,6 @@ class TestPipelineStreamingOutputToEntrypoint:
model="test_model",
od_config=od_config,
metadata=metadata,
batch_size=1,
)
@staticmethod
@@ -526,6 +525,7 @@ class TestSupportedPipelines:
runner = object.__new__(DiffusionModelRunner)
runner.vllm_config = _make_vllm_config()
runner.od_config = SimpleNamespace(
max_num_seqs=1,
enable_cpu_offload=False,
enable_layerwise_offload=False,
enforce_eager=True,
@@ -47,7 +47,7 @@ def client(mock_engine):
with patch.object(InlineStageDiffusionClient, "_enrich_config"):
od_config = MagicMock(spec=OmniDiffusionConfig)
od_config.streaming_output = False
c = InlineStageDiffusionClient(model="test_model", od_config=od_config, metadata=metadata, batch_size=1)
c = InlineStageDiffusionClient(model="test_model", od_config=od_config, metadata=metadata)
yield c
c.shutdown()
@@ -234,5 +234,4 @@ def test_inline_client_requires_replica_id(mock_engine):
model="test_model",
od_config=od_config,
metadata=metadata,
batch_size=1,
)
@@ -1171,7 +1171,6 @@ class TestStageDiffusionClientErrorPropagation:
metadata,
"tcp://req",
"tcp://resp",
batch_size=1,
)
@pytest.mark.asyncio
-1
View File
@@ -387,7 +387,6 @@ class TestPromptUpdateIntegration:
model="test_model",
od_config=od_config,
metadata=metadata,
batch_size=1,
)
@staticmethod