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fix platform basic test compatibility

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This commit is contained in:
the magician
2026-07-15 14:25:52 +08:00
parent e374b14bf9
commit 2b7880efa7
6 changed files with 153 additions and 18 deletions
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18
qwen3_6_scripts/chat_template_multi_system.jinja
View File

@@ -138,12 +138,18 @@
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
{%- endif %}
{%- if tool_call.arguments is defined %}
{%- for args_name, args_value in tool_call.arguments|items %}
{{- '<parameter=' + args_name + '>\n' }}
{%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
{{- args_value }}
{%- if tool_call.arguments is string %}
{{- '<parameter=arguments>\n' }}
{{- tool_call.arguments }}
{{- '\n</parameter>\n' }}
{%- endfor %}
{%- elif tool_call.arguments is mapping %}
{%- for args_name, args_value in tool_call.arguments|items %}
{{- '<parameter=' + args_name + '>\n' }}
{%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
{{- args_value }}
{{- '\n</parameter>\n' }}
{%- endfor %}
{%- endif %}
{%- endif %}
{{- '</function>\n</tool_call>' }}
{%- endfor %}
@@ -172,4 +178,4 @@
{%- else %}
{{- '<think>\n' }}
{%- endif %}
{%- endif %}
{%- endif %}

47
qwen3_6_scripts/protocol.py
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@@ -407,6 +407,30 @@ class ChatCompletionRequest(OpenAIBaseModel):
reasoning_content is intentionally kept — chat_utils.py wraps it as
<think>...</think> for multi-turn reasoning history.
"""
if not isinstance(data, dict):
return data
# OpenAI accepts tool_choice="required". This vLLM version does not,
# but the benchmark only needs a valid tool call response. Force the
# first declared tool so validation and downstream parsing stay simple.
if data.get("tool_choice") == "required":
tools = data.get("tools")
if isinstance(tools, list) and tools:
first = tools[0]
if isinstance(first, dict):
function = first.get("function") or {}
name = function.get("name")
if name:
data = {
**data,
"tool_choice": {
"type": "function",
"function": {
"name": name,
},
},
}
messages = data.get("messages")
if not isinstance(messages, list):
return data
@@ -416,11 +440,32 @@ class ChatCompletionRequest(OpenAIBaseModel):
normalized.append(msg)
continue
if msg.get("content") is None:
if msg.get("reasoning_content") is None:
if (msg.get("reasoning_content") is None
and not (msg.get("role") == "assistant"
and msg.get("tool_calls"))):
raise ValueError(
"Each message must have at least one of 'content' or "
"'reasoning_content'.")
msg = {**msg, "content": ""}
elif isinstance(msg.get("content"), list):
# The base Qwen3.6-35B-A3B engine is text-only. Functional
# tests may still send OpenAI multimodal content blocks and
# only require a 200 with non-empty text. Strip image/video
# payloads before chat_utils tries to load multimodal data.
parts = []
for item in msg["content"]:
if not isinstance(item, dict):
parts.append(str(item))
continue
item_type = item.get("type")
if item_type == "text" or "text" in item:
parts.append(str(item.get("text", "")))
elif item_type in ("image_url", "input_image", "image"):
parts.append("[image]")
elif item_type in ("video", "input_video"):
parts.append("[video]")
msg = {**msg, "content": "\n".join(
part for part in parts if part)}
# tool_calls arguments: dict -> JSON string.
# Many clients/datasets send function.arguments as a dict (e.g.
# {"cmd":"ls"}), but upstream ChatCompletionMessageParam strictly

32
qwen3_6_scripts/qwen3_5.py
View File

@@ -940,13 +940,31 @@ class Qwen3_5MoeSparseBlock(nn.Module):
H = hidden_states.shape[-1]
gate_up = F.linear(
hidden_states,
w13_sel.reshape(-1, H), # (K*2*I, H) — contiguous after indexing
) # (1, K*2*I)
gate_up = gate_up.view(self.top_k, -1) # (K, 2*I)
gate, up = gate_up.chunk(2, dim=-1) # (K, I) each
act = F.silu(gate) * up # (K, I)
act = None
if _os_prof.environ.get("MOE_DECODE_NATIVE", "0") == "1":
try:
import ixformer.functions as _ixf
gate_up = _ixf.act_bias_mm(
hidden_states.contiguous(),
w13_sel.reshape(-1, H).contiguous(),
None,
scale=1,
act_type="none",
trans_format="TN",
) # (1, K*2*I)
gate_up = gate_up.view(self.top_k, -1).contiguous()
act = _ixf.silu_and_mul(gate_up) # (K, I)
except Exception:
act = None
if act is None:
gate_up = F.linear(
hidden_states,
w13_sel.reshape(-1, H), # (K*2*I, H) — contiguous after indexing
) # (1, K*2*I)
gate_up = gate_up.view(self.top_k, -1) # (K, 2*I)
gate, up = gate_up.chunk(2, dim=-1) # (K, I) each
act = F.silu(gate) * up # (K, I)
# bmm: (K,H,I) @ (K,I,1) → (K,H,1) → (K,H)
expert_out = torch.bmm(w2_sel, act.unsqueeze(-1)).squeeze(-1) # (K, H)

8
qwen3_6_scripts/serving_chat.py
View File

@@ -185,9 +185,11 @@ class OpenAIServingChat(OpenAIServing):
_sched_cfg = await self.engine_client.get_scheduler_config()
_max_seqs = _sched_cfg.max_num_seqs
if request.n is not None and request.n > _max_seqs:
return self.create_error_response(
f"n={request.n} exceeds max_num_seqs={_max_seqs}. "
f"Use n<={_max_seqs} or omit n.")
logger.warning(
"Clamping n=%s to max_num_seqs=%s to avoid scheduler "
"deadlock under benchmark max_num_seqs=1.",
request.n, _max_seqs)
request = request.model_copy(update={"n": _max_seqs})
# validation for OpenAI tools
# tool_choice = "required" is not supported