add script to run evals for adaptors

run_checkpoints_adapters.sh

@@ -0,0 +1,70 @@
+#!/bin/zsh
+
+model_names=("sqlcoder_8b_bf16_r64_ds_013_sqlite_600_b24_lr8e-5")
+base_model_path="defog/sqlcoder-8b-padded-sorry"
+db_type="sqlite"
+PORT=8084 # avoid 8081 as it's used by nginx
+export CUDA_VISIBLE_DEVICES=1 # set gpu you want to use (just 1 will do)
+preprocess_adapters=true # set to false if you have already preprocessed the adapters
+
+for model_name in "${model_names[@]}"; do
+  # list the folder names in /models/combined/${model_name}
+  adapter_dir="${HOME}/finetuning/models/${model_name}"
+  echo "Adapter directory: ${adapter_dir}"
+  checkpoints=($(ls $adapter_dir))
+  echo "Checkpoints: ${checkpoints}"
+  if [ "$preprocess_adapters" = true ]; then
+    # Preprocess the adapters
+    for checkpoint in "${checkpoints[@]}"; do
+      # skip if does not start with "checkpoint-"
+      if [[ ! $checkpoint == checkpoint-* ]]; then
+        continue
+      fi
+      checkpoint_num=$(echo $checkpoint | cut -d'-' -f2)
+      echo "Preprocessing adapter ${model_name}/checkpoint-${checkpoint_num}"
+      python3 ${HOME}/finetuning/preprocess_adapters.py -f ${adapter_dir}/checkpoint-${checkpoint_num}/adapter_model.safetensors
+    done
+  else
+    echo "Skipping preprocessing adapters..."
+  fi
+
+  # Loop over checkpoints to run sql-eval
+  for checkpoint in "${checkpoints[@]}"; do
+    # skip if does not start with "checkpoint-"
+    if [[ ! $checkpoint == checkpoint-* ]]; then
+      continue
+    fi
+    checkpoint_num=$(echo $checkpoint | cut -d'-' -f2)
+    echo "Running adapter ${model_name} checkpoint ${checkpoint_num}"
+    # first, get the API up
+    python3 utils/api_server.py --model "$base_model_path" --tensor-parallel-size 1 --dtype float16 --max-model-len 4096 --gpu-memory-utilization 0.90 --block-size 16 --disable-log-requests --port "${PORT}" --enable-lora --max-lora-rank 64 &
+
+    # run a loop to check if the http://localhost:8084/health endpoint returns a valid 200 result
+    while true; do
+      http_status=$(curl -s -o /dev/null -w "%{http_code}" "http://localhost:${PORT}/health")
+      if [ "$http_status" -eq 200 ]; then
+        echo "API server is up and running"
+        break
+      else
+        echo "Waiting for API server to be up..."
+        sleep 1
+      fi
+    done
+
+    # then run sql-eval
+    python3 main.py -db ${db_type} \
+      -f prompts/prompt.md \
+      -q "data/instruct_basic_${db_type}.csv" "data/instruct_advanced_${db_type}.csv" "data/questions_gen_${db_type}.csv" "data/idk.csv" \
+      -o "results/${model_name}/c${checkpoint_num}_${db_type}_api_basic.csv" "results/${model_name}/c${checkpoint_num}_${db_type}_api_advanced.csv" "results/${model_name}/c${checkpoint_num}_${db_type}_api_v1.csv" "results/${model_name}/c${checkpoint_num}_${db_type}_api_idk.csv" \
+      -g api \
+      -b 1 \
+      -c 0 \
+      --api_url "http://localhost:${PORT}/generate" \
+      --api_type "vllm" \
+      -p 10 \
+      -a ${adapter_dir}/checkpoint-${checkpoint_num}\
+      --logprobs
+    # finally, kill the api server
+    pkill -9 -f "python3 utils/api_server.py.*--port ${PORT}"
+  done
+done