add qwen3

vllm-v0.6.2/examples/cambricon_custom_func/expert_parallel/client.sh

@@ -0,0 +1,34 @@
+#/bin/bash
+
+# export EXPERT_PARALLEL_EN=True
+# export VLLM_LATENCY_DEBUG=True
+
+rm output/client -rf
+mkdir -p output/client
+
+PORT=32345
+MODEL_PATH="/data/vllm/sq_per_token_per_channel/deepseek_v2_temp"
+input_sizes=(1024)
+output_sizes=(1)
+# batch_sizes=(1 2 4 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40)
+batch_sizes=(32)
+for input_size in "${input_sizes[@]}"; do
+    for output_size in "${output_sizes[@]}"; do
+        for batch_size in "${batch_sizes[@]}"; do
+            hf_model_name=$(basename "${HF_MODEL}")
+            LOG_FILE=output/client/${hf_model_name}_${input_size}_${output_size}_bs_${batch_size}.log
+            python benchmarks/benchmark_serving.py \
+                --backend vllm \
+                --model ${MODEL_PATH} \
+                --trust-remote-code \
+                --dataset-name random \
+                --num-prompts 1000 \
+                --port ${PORT} \
+                --request-rate inf \
+                --random_input_len $input_size \
+                --random-output-len ${output_size} \
+                --max-concurrency ${batch_size} \
+                2>&1 | tee ${LOG_FILE}
+        done
+    done
+done