models/mace/scripts/run_mace.sh

#!/usr/bin/env bash
set -euo pipefail

# ----------------------------
# Resolve paths
# ----------------------------
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
MACE_REPO_DIR="$(cd "$SCRIPT_DIR/.." && pwd)"
REPO_ROOT="$(cd "$SCRIPT_DIR/../../.." && pwd)"

# ----------------------------
# User settings
# ----------------------------
NAME="mace"

TRAIN_FILE="$REPO_ROOT/datasets/xyz/train.xyz"
VALID_FILE="$REPO_ROOT/datasets/xyz/val.xyz"
TEST_FILE="$REPO_ROOT/datasets/xyz/test.xyz"

CHECKPOINT_DIR="$MACE_REPO_DIR/checkpoints_mace"

# From the docs screenshot:
CONFIG_TYPE_WEIGHTS='{"Default":1.0}'

# Replace these E0s if needed.
E0S='{1: 2.467478445, 6: 8.0273263225, 8: 3.334308855, 22: 4.879036065}'
ATOMIC_NUMBERS='[1,6,8,22]'

MODEL="MACE"
HIDDEN_IRREPS="128x0e + 128x1o"
R_MAX="6.0"
BATCH_SIZE="2"
VALID_BATCH_SIZE="2"
START_SWA="1200"
EMA_DECAY="0.99"
SEED="11"

DEVICE="cuda"
MAX_NUM_EPOCHS="10"

WAND_PROJECT="mace"

# ----------------------------
# Detect number of visible GPUs
# ----------------------------
if command -v nvidia-smi &> /dev/null; then
  NGPUS="$(nvidia-smi -L | wc -l | tr -d ' ')"
else
  NGPUS="1"
fi

NGPUS="${NGPUS:-1}"

# ----------------------------
# Sanity checks
# ----------------------------
if [ ! -d "$MACE_REPO_DIR/mace" ]; then
  echo "ERROR: MACE package directory not found:"
  echo "$MACE_REPO_DIR/mace"
  exit 1
fi

if [ ! -f "$TRAIN_FILE" ]; then
  echo "ERROR: Training file not found:"
  echo "$TRAIN_FILE"
  exit 1
fi

if [ ! -f "$VALID_FILE" ]; then
  echo "ERROR: Validation file not found:"
  echo "$VALID_FILE"
  exit 1
fi

if [ ! -f "$TEST_FILE" ]; then
  echo "ERROR: Test file not found:"
  echo "$TEST_FILE"
  exit 1
fi

echo "Using NGPUS=${NGPUS}"
echo "MACE_REPO_DIR=${MACE_REPO_DIR}"
echo "REPO_ROOT=${REPO_ROOT}"
echo "Train=${TRAIN_FILE}"
echo "Valid=${VALID_FILE}"
echo "Test=${TEST_FILE}"
echo "Checkpoint_dir=${CHECKPOINT_DIR}"

# ----------------------------
# Go to MACE repo root and expose it to Python
# ----------------------------
cd "$MACE_REPO_DIR"
export PYTHONPATH="$MACE_REPO_DIR:${PYTHONPATH:-}"

unset SLURM_JOB_NODELIST \
      SLURM_NTASKS \
      SLURM_NTASKS_PER_NODE \
      SLURM_NNODES \
      SLURM_LOCALID \
      SLURM_PROCID \
      SLURM_NODEID \
      SLURM_JOB_ID

# ----------------------------
# Per-run output folders
# ----------------------------
RUN_TAG="${NAME}_run-${SEED}"
RUN_DIR="${CHECKPOINT_DIR}/${RUN_TAG}"

RUN_CHECKPOINTS_DIR="${RUN_DIR}/checkpoints"
RUN_MODELS_DIR="${RUN_DIR}/models"
RUN_RESULTS_DIR="${RUN_DIR}/results"
RUN_LOGS_DIR="${RUN_DIR}/logs"
RUN_WANDB_DIR="${RUN_DIR}/wandb"

mkdir -p \
  "$RUN_CHECKPOINTS_DIR" \
  "$RUN_MODELS_DIR" \
  "$RUN_RESULTS_DIR" \
  "$RUN_LOGS_DIR" \
  "$RUN_WANDB_DIR"

echo "RUN_DIR=${RUN_DIR}"

# ----------------------------
# Launch training
# ----------------------------
torchrun --standalone --nproc_per_node="$NGPUS" -m mace.cli.run_train \
  --name="$NAME" \
  --seed="$SEED" \
  --checkpoints_dir="$RUN_CHECKPOINTS_DIR" \
  --model_dir="$RUN_MODELS_DIR" \
  --results_dir="$RUN_RESULTS_DIR" \
  --log_dir="$RUN_LOGS_DIR" \
  \
  --max_num_epochs="$MAX_NUM_EPOCHS" \
  --train_file="$TRAIN_FILE" \
  --valid_file="$VALID_FILE" \
  --test_file="$TEST_FILE" \
  \
  --hidden_irreps="$HIDDEN_IRREPS" \
  --config_type_weights="$CONFIG_TYPE_WEIGHTS" \
  --E0s="$E0S" \
  --model="$MODEL" \
  --r_max="$R_MAX" \
  \
  --batch_size="$BATCH_SIZE" \
  --valid_batch_size="$VALID_BATCH_SIZE" \
  --ema \
  --ema_decay="$EMA_DECAY" \
  --amsgrad \
  --device="$DEVICE" \
  --atomic_numbers "$ATOMIC_NUMBERS" \
  \
  --energy_key "energy" \
  --forces_key "forces" \
  \
  --loss "ours_mae" \
  --forces_weight 1.0 \
  --energy_weight 1.0 \
  --default_dtype "float32" \
  \
  --distributed \
  \
  --wandb \
  --wandb_dir "$RUN_WANDB_DIR" \
  --wandb_project "$WAND_PROJECT" \
  --wandb_name "$NAME" \
  \
  #--swa