[IR2Vec] Add triplet generation utility script for vocabulary training

llvm/docs/CommandGuide/llvm-ir2vec.rst

@@ -50,6 +50,9 @@ embedding training (see
 <https://github.com/thunlp/OpenKE/tree/OpenKE-PyTorch?tab=readme-ov-file#data-format> 
 for details).
 
+See `llvm/utils/mlgo-utils/IR2Vec/generateTriplets.py` for more details on how
+these two modes are used to generate the triplets and entity mappings.
+
 Triplet Generation Mode
 ~~~~~~~~~~~~~~~~~~~~~~~
 

llvm/utils/mlgo-utils/IR2Vec/generateTriplets.py

@@ -0,0 +1,304 @@
+# Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+# See https://llvm.org/LICENSE.txt for license information.
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+"""IR2Vec Triplet Generator
+
+Generates IR2Vec triplets by applying random optimization levels to LLVM IR files
+and extracting triplets using llvm-ir2vec. Automatically generates preprocessed
+files: entity2id.txt, relation2id.txt, and train2id.txt.
+
+Usage:
+    python generateTriplets.py <llvm_build_dir> <num_optimizations> <ll_file_list> <output_dir>
+"""
+
+import argparse
+import logging
+import os
+import random
+import subprocess
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from pathlib import Path
+from typing import List, Set, Tuple
+
+# Configuration
+OPT_LEVELS = ["O0", "O1", "O2", "O3", "Os", "Oz"]
+DEFAULT_MAX_WORKERS = 100
+
+logger = logging.getLogger(__name__)
+
+
+# TODO: Change this to a dataclass with slots
+# when Python 3.10+ is the minimum version
+# https://docs.python.org/3/library/dataclasses.html#dataclasses.dataclass
+class TripletResult:
+    """Result from processing a single LLVM IR file"""
+
+    __slots__ = ["triplets", "max_relation"]
+
+    def __init__(self, triplets: Set[str], max_relation: int):
+        self.triplets = triplets
+        self.max_relation = max_relation
+
+
+class IR2VecTripletGenerator:
+    """Main class for generating IR2Vec triplets"""
+
+    def __init__(
+        self,
+        llvm_build_dir: Path,
+        num_optimizations: int,
+        output_dir: Path,
+        max_workers: int = DEFAULT_MAX_WORKERS,
+    ):
+        self.llvm_build_dir = llvm_build_dir
+        self.num_optimizations = num_optimizations
+        self.output_dir = output_dir
+        self.max_workers = max_workers
+
+        # Tool paths
+        self.opt_binary = os.path.join(llvm_build_dir, "bin", "opt")
+        self.ir2vec_binary = os.path.join(llvm_build_dir, "bin", "llvm-ir2vec")
+
+        self._validate_setup()
+
+        # Create output directory if it doesn't exist
+        self.output_dir.mkdir(parents=True, exist_ok=True)
+
+    def _validate_setup(self):
+        """Validate that all required tools and paths exist"""
+        if not self.llvm_build_dir.exists():
+            raise FileNotFoundError(
+                f"LLVM build directory not found: {self.llvm_build_dir}"
+            )
+
+        if not os.path.isfile(self.opt_binary) or not os.access(
+            self.opt_binary, os.X_OK
+        ):
+            raise FileNotFoundError(
+                f"opt binary not found or not executable: {self.opt_binary}"
+            )
+
+        if not os.path.isfile(self.ir2vec_binary) or not os.access(
+            self.ir2vec_binary, os.X_OK
+        ):
+            raise FileNotFoundError(
+                f"llvm-ir2vec binary not found or not executable: {self.ir2vec_binary}"
+            )
+
+        if not (1 <= self.num_optimizations <= len(OPT_LEVELS)):
+            raise ValueError(
+                f"Number of optimizations must be between 1-{len(OPT_LEVELS)}"
+            )
+
+    def _select_optimization_levels(self) -> List[str]:
+        """Select unique random optimization levels"""
+        return random.sample(OPT_LEVELS, self.num_optimizations)
+
+    def _process_single_file(self, input_file: Path) -> TripletResult:
+        """Process a single LLVM IR file with multiple optimization levels"""
+        all_triplets = set()
+        max_relation = 1
+        opt_levels = self._select_optimization_levels()
+
+        for opt_level in opt_levels:
+            triplets, file_max_relation = self._run_pipeline(input_file, opt_level)
+            if triplets:
+                all_triplets.update(triplets)
+                max_relation = max(max_relation, file_max_relation)
+                logger.debug(
+                    f"Generated {len(triplets)} triplets for {input_file} with {opt_level}"
+                )
+
+        return TripletResult(all_triplets, max_relation)
+
+    def _run_pipeline(self, input_file: Path, opt_level: str) -> Tuple[Set[str], int]:
+        """Run opt | llvm-ir2vec pipeline using subprocess pipes."""
+        try:
+            # Run opt first
+            opt_proc = subprocess.Popen(
+                [self.opt_binary, f"-{opt_level}", str(input_file), "-o", "-"],
+                stdout=subprocess.PIPE,
+                stderr=subprocess.PIPE,
+                text=True,
+            )
+
+            # Run llvm-ir2vec with opt's output as input
+            ir2vec_proc = subprocess.Popen(
+                [self.ir2vec_binary, "--mode=triplets", "-", "-o", "-"],
+                stdin=opt_proc.stdout,
+                stdout=subprocess.PIPE,
+                stderr=subprocess.PIPE,
+                text=True,
+            )
+
+            opt_proc.stdout.close()
+            stdout, _ = ir2vec_proc.communicate()
+            opt_proc.wait()
+
+            # Check if either process failed
+            if opt_proc.returncode != 0 or ir2vec_proc.returncode != 0:
+                return set(), 1
+
+            return self._parse_triplet_output(stdout)
+        except (subprocess.SubprocessError, OSError):
+            return set(), 1
+
+    def _parse_triplet_output(self, output: str) -> Tuple[Set[str], int]:
+        """Parse triplet output and extract max relation"""
+        if not output.strip():
+            return set(), 1
+
+        lines = output.strip().split("\n")
+        max_relation = 1
+
+        # Extract max relation from metadata line
+        if lines and lines[0].startswith("MAX_RELATION="):
+            max_relation = int(lines[0].split("=")[1])
+            lines = lines[1:]
+
+        # Remove duplicate triplets by converting to a set
+        return set(lines), max_relation
+
+    def generate_triplets(self, file_list: Path) -> None:
+        """Main method to generate triplets from a list of LLVM IR files"""
+        input_files = self._read_file_list(file_list)
+        logger.info(
+            f"Processing {len(input_files)} files with {self.num_optimizations} "
+            f"optimization levels using {self.max_workers} workers"
+        )
+
+        all_triplets = set()
+        global_max_relation = 1
+
+        with ThreadPoolExecutor(max_workers=self.max_workers) as executor:
+            future_to_file = {
+                executor.submit(self._process_single_file, file): file
+                for file in input_files
+            }
+
+            for future in as_completed(future_to_file):
+                try:
+                    result = future.result()
+                    all_triplets.update(result.triplets)
+                    global_max_relation = max(global_max_relation, result.max_relation)
+                except (subprocess.SubprocessError, OSError, ValueError) as e:
+                    file_path = future_to_file[future]
+                    logger.error(f"Error processing {file_path}: {e}")
+
+        self._generate_output_files(all_triplets, global_max_relation)
+        logger.info("Processing completed successfully")
+
+    def _read_file_list(self, file_list: Path) -> List[Path]:
+        """Read and validate the list of input files"""
+        input_files = []
+        with open(file_list, "r") as f:
+            for line_num, line in enumerate(f, 1):
+                if line := line.strip():
+                    file_path = Path(line)
+                    if file_path.exists():
+                        input_files.append(file_path)
+                    else:
+                        logger.warning(f"File not found (line {line_num}): {file_path}")
+
+        if not input_files:
+            raise ValueError("No valid input files found")
+        return input_files
+
+    def _generate_output_files(self, all_triplets: Set[str], max_relation: int) -> None:
+        """Generate the final output files"""
+        logger.info(f"Generating output files with {len(all_triplets)} unique triplets")
+
+        # Write all output files -- train2id.txt, entity2id.txt, relation2id.txt
+        train2id_file = os.path.join(self.output_dir, "train2id.txt")
+        entity2id_file = os.path.join(self.output_dir, "entity2id.txt")
+        relation2id_file = os.path.join(self.output_dir, "relation2id.txt")
+
+        with open(train2id_file, "w") as f:
+            f.write(f"{len(all_triplets)}\n")
+            f.writelines(f"{triplet}\n" for triplet in all_triplets)
+
+        self._generate_entity2id(entity2id_file)
+        self._generate_relation2id(relation2id_file, max_relation)
+
+    def _generate_entity2id(self, output_file: Path) -> None:
+        """Generate entity2id.txt using llvm-ir2vec"""
+        subprocess.run(
+            [str(self.ir2vec_binary), "--mode=entities", "-o", str(output_file)],
+            check=True,
+            capture_output=True,
+        )
+
+    def _generate_relation2id(self, output_file: Path, max_relation: int) -> None:
+        """Generate relation2id.txt from max relation"""
+        max_relation = max(max_relation, 1)  # At least Type and Next relations
+        num_relations = max_relation + 1
+
+        with open(output_file, "w") as f:
+            f.write(f"{num_relations}\n")
+            f.write("Type\t0\n")
+            f.write("Next\t1\n")
+            f.writelines(f"Arg{i-2}\t{i}\n" for i in range(2, num_relations))
+
+
+def main():
+    """Main entry point"""
+    parser = argparse.ArgumentParser(
+        description="Generate IR2Vec triplets from LLVM IR files",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+    )
+
+    parser.add_argument(
+        "llvm_build_dir", type=Path, help="Path to LLVM build directory"
+    )
+    parser.add_argument(
+        "num_optimizations",
+        type=int,
+        help="Number of optimization levels to apply (1-6)",
+    )
+    parser.add_argument(
+        "ll_file_list",
+        type=Path,
+        help="File containing list of LLVM IR files to process",
+    )
+    parser.add_argument(
+        "output_dir", type=Path, help="Output directory for generated files"
+    )
+    parser.add_argument(
+        "-j",
+        "--max-workers",
+        type=int,
+        default=DEFAULT_MAX_WORKERS,
+        help=f"Maximum number of parallel workers (default: {DEFAULT_MAX_WORKERS})",
+    )
+    parser.add_argument(
+        "-v", "--verbose", action="store_true", help="Enable debug logging"
+    )
+    parser.add_argument(
+        "-q", "--quiet", action="store_true", help="Suppress all output except errors"
+    )
+
+    args = parser.parse_args()
+
+    # Configure logging
+    level = (
+        logging.ERROR
+        if args.quiet
+        else (logging.DEBUG if args.verbose else logging.INFO)
+    )
+    logging.basicConfig(
+        level=level,
+        format="[%(asctime)s] %(levelname)s: %(message)s",
+        datefmt="%H:%M:%S",
+    )
+
+    generator = IR2VecTripletGenerator(
+        args.llvm_build_dir,
+        args.num_optimizations,
+        args.output_dir,
+        args.max_workers,
+    )
+    generator.generate_triplets(args.ll_file_list)
+
+
+if __name__ == "__main__":
+    main()