1 files changed, 69 insertions, 0 deletions
diff --git a/collaborativeagents/slurm/scale_contextual_forget.sbatch b/collaborativeagents/slurm/scale_contextual_forget.sbatch
new file mode 100644
index 0000000..4942a4d
--- /dev/null
+++ b/collaborativeagents/slurm/scale_contextual_forget.sbatch
@@ -0,0 +1,69 @@
+#!/bin/bash
+#SBATCH --job-name=ctx_forget
+#SBATCH --account=bfqt-delta-gpu
+#SBATCH --partition=gpuH200x8-interactive
+#SBATCH --gres=gpu:4
+#SBATCH --time=01:00:00
+#SBATCH --mem=200G
+#SBATCH --cpus-per-task=32
+#SBATCH --output=%x-%j.out
+#SBATCH --error=%x-%j.err
+
+cd /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model
+
+source ~/miniforge3/etc/profile.d/conda.sh
+conda activate eval
+
+export HF_HOME=/projects/bfqt/users/yurenh2/hf_cache/huggingface
+export TRANSFORMERS_CACHE=/projects/bfqt/users/yurenh2/hf_cache/huggingface
+export PYTHONPATH=/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model:$PYTHONPATH
+
+PROFILE_PATH="collaborativeagents/data/complex_profiles_v2/profiles_200.jsonl"
+AGENT_MODEL="/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/models/llama-3.1-8b-instruct"
+USER_MODEL="meta-llama/Llama-3.1-70B-Instruct"
+
+echo "=== Starting vLLM servers ==="
+date
+
+# User simulator on GPUs 0,1 (70B)
+CUDA_VISIBLE_DEVICES=0,1 python -m vllm.entrypoints.openai.api_server \
+    --model $USER_MODEL \
+    --port 8004 --tensor-parallel-size 2 --gpu-memory-utilization 0.90 \
+    --max-model-len 16384 --dtype bfloat16 --download-dir $HF_HOME &
+
+# Agent on GPUs 2,3 (8B)
+CUDA_VISIBLE_DEVICES=2,3 python -m vllm.entrypoints.openai.api_server \
+    --model $AGENT_MODEL \
+    --port 8003 --tensor-parallel-size 2 --gpu-memory-utilization 0.90 \
+    --max-model-len 16384 --dtype bfloat16 &
+
+# Wait for servers
+echo "Waiting for vLLM servers..."
+for i in {1..200}; do
+    if curl -s http://localhost:8004/health > /dev/null 2>&1; then
+        echo "User simulator (8004) ready after $((i*5)) seconds"
+        break
+    fi
+    sleep 5
+done
+for i in {1..60}; do
+    if curl -s http://localhost:8003/health > /dev/null 2>&1; then
+        echo "Agent (8003) ready after $((i*5)) seconds"
+        break
+    fi
+    sleep 5
+done
+echo "Both vLLM servers ready"
+sleep 10
+
+# Run contextual with reduced memory limits (4000 tokens, 15 turns)
+CUDA_VISIBLE_DEVICES=2,3 python collaborativeagents/scripts/run_experiments.py \
+    --methods contextual \
+    --n-profiles 5 \
+    --n-sessions 15 \
+    --output-dir results/scale_test_contextual_forget \
+    --profile-path $PROFILE_PATH \
+    --datasets math-hard \
+    --use-vllm --parallel-profiles 30 --no-batch-processing
+
+pkill -f "vllm.entrypoints" 2>/dev/null || true