Raw MLIR bench

tools/mlir_bench/ov_model_gen.py

@@ -7,6 +7,7 @@
 import argparse
 import string
 import sys
+import os
 
 import torch
 import torch.nn as nn
@@ -243,4 +244,4 @@ def main():
 
 
 if __name__ == '__main__':
-    sys.exit(main())
+    os._exit(main())

tools/mlir_bench/ov_raw_mlir_bench.sh

@@ -0,0 +1,97 @@
+#!/bin/bash
+#
+# Runs pure MLIR part of MLP benchmarks using TPP-MLIR
+# This approach assumes that only one MLIR op is generated.
+# For example, the whole graph is outlined to MLIR.
+
+die_syntax() {
+  echo "Syntax: $0 [-t (f32|f16|bf16|...)] [-b (mlp)] [-D]"
+  echo ""
+  echo "  -t: Optional data type"
+  echo "  -b: Optional baseline model"
+  echo "  -D: Set model shapes to dynamic"
+  exit 1
+}
+
+# Cmd-line opts
+while getopts "t:b:D" arg; do
+  case ${arg} in
+    t)
+      DATA_TYPE=${OPTARG}
+      ;;
+    b)
+      BASELINE_MODEL=${OPTARG}
+      ;;
+    D)
+      IS_DYNAMIC=true
+      ;;
+    ?)
+      echo "Invalid option: ${OPTARG}"
+      die_syntax
+      ;;
+  esac
+done
+
+OV_ROOT=$(git rev-parse --show-toplevel)
+BENCH_ROOT=$(realpath ${OV_ROOT}/tools/mlir_bench)
+
+MODEL_GEN=$(realpath ${BENCH_ROOT}/ov_model_gen.py)
+BENCH_RUNNER=tpp-run
+
+# Initial validation.
+if ! [ -d ${OV_ROOT} ]; then
+  echo "Missing OV repo"
+  exit 1
+fi
+if ! [ -d ${BENCH_ROOT} ]; then
+  echo "Missing MLIR benchmark directory"
+  exit 1
+fi
+if ! [ -f ${MODEL_GEN} ]; then
+  echo "Missing model generator"
+  exit 1
+fi
+if ! [ "$(command -v ${BENCH_RUNNER})" ]; then
+  echo "Missing benchmark runner ${BENCH_RUNNER}"
+  exit 1
+fi
+if [ ${IS_DYNAMIC} ]; then
+  echo "Dynamic shapes are not supported by ${BENCH_RUNNER}"
+  exit 1
+fi
+
+# Kernel config.
+INPUT_SIZES=( 1024 2048 4096 8192 )
+OUTPUT_SIZES=( 128 256 512 )
+if [ ! "${DATA_TYPE}" ]; then
+    DATA_TYPE="f32"
+fi
+MODEL_NAME="TPP_BENCH.xml"
+
+for OUT_SIZE in "${OUTPUT_SIZES[@]}"; do
+  echo "MLP - OUT: ${OUT_SIZE} INS: ${INPUT_SIZES[@]}"
+  for IN_SIZE in "${INPUT_SIZES[@]}"; do
+    # Generate model.
+    # Generate model.
+    if [ "${BASELINE_MODEL}" ]; then
+        # Enable baseline model flag.
+        MODEL_CONFIG=(-b="${BASELINE_MODEL}[${OUT_SIZE},${OUT_SIZE},${IN_SIZE}]")
+    else
+        # Generate default PyTorch MLP.
+        MODEL_CONFIG=(-l="linear[${IN_SIZE},${OUT_SIZE}] relu[]")
+    fi
+    GEN_FLAGS=(-t ${DATA_TYPE} -n ${MODEL_NAME})
+    GEN_FLAGS+=(-p)
+    MODEL_OUT=$(python3 ${MODEL_GEN} "${MODEL_CONFIG[@]}" "${GEN_FLAGS[@]}" 2>&1)
+    if [ $? != 0 ]; then
+        echo "Failed to generate model"
+        exit 1
+    fi
+    # Run benchmark.
+    MLIR_IR=$(echo "${MODEL_OUT}" \
+        | awk '/Source MLIR:/{flag=1; next} /Target LLVM:/{flag=0} flag' \
+        | grep -vE '^[-]+$')
+    BENCH_FLAGS="-entry-point-result=void -e entry -seed 123 -n 10000"
+    echo "${MLIR_IR}" | ${BENCH_RUNNER} ${BENCH_FLAGS}
+  done
+done