meta-pytorch
diff --git a/‎tritonparse/reproducer/function_extractor.py‎
Lines changed: 220 additions & 0 deletions b/‎tritonparse/reproducer/function_extractor.py‎
Lines changed: 220 additions & 0 deletions
diff --git a/‎tritonparse/reproducer/placeholder_replacer.py‎
Lines changed: 11 additions & 0 deletions b/‎tritonparse/reproducer/placeholder_replacer.py‎
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@@ -0,0 +1,220 @@
+"""
+Function extractor for reproducer utility functions.
+
+This module extracts utility functions from utils.py and load_tensor.py
+using AST parsing, and generates standalone code for reproducers.
+"""
+
+import ast
+from pathlib import Path
+
+
+def extract_utility_functions() -> str:
+    """
+    Extract all utility functions needed for the reproducer template.
+
+    Uses AST parsing to extract functions and constants from source files
+    without importing them (avoiding potential side effects).
+
+    Returns:
+        str: Complete Python code including imports and all utility functions.
+    """
+    # Prepare file paths
+    base_dir = Path(__file__).parent
+    utils_path = base_dir / "utils.py"
+    load_tensor_path = base_dir.parent / "tools" / "load_tensor.py"
+
+    # Parse source files
+    utils_tree, utils_lines = _parse_source_file(utils_path)
+    load_tensor_tree, load_tensor_lines = _parse_source_file(load_tensor_path)
+
+    # Define what to extract (in dependency order)
+    utils_function_names = [
+        "_get_triton_tensor_types",
+        "create_args_from_json_file",
+        "create_args_from_json",
+        "_apply_stride_and_offset",
+        "_create_base_tensor",
+        "_create_tensor",
+        "_create_arg_from_info",
+    ]
+
+    load_tensor_function_names = [
+        "load_tensor",
+    ]
+
+    # Extract content
+    extracted_parts = []
+
+    # Add required imports
+    extracted_parts.append(_generate_imports())
+
+    # Extract constant
+    constant = _extract_assignment(
+        utils_tree, utils_lines, "TRITON_KERNELS_CUSTOM_TYPES"
+    )
+    if constant:
+        extracted_parts.append(constant)
+
+    # Extract load_tensor functions
+    extracted_parts.extend(
+        _extract_functions(
+            load_tensor_tree, load_tensor_lines, load_tensor_function_names
+        )
+    )
+
+    # Extract utils functions
+    extracted_parts.extend(
+        _extract_functions(utils_tree, utils_lines, utils_function_names)
+    )
+
+    # Combine all parts
+    return "\n\n".join(extracted_parts)
+
+
+def _parse_source_file(file_path: Path) -> tuple[ast.Module, list[str]]:
+    """
+    Parse a Python source file and return its AST and source lines.
+
+    Args:
+        file_path: Path to the Python source file
+
+    Returns:
+        tuple: (AST tree, list of source code lines)
+
+    Raises:
+        FileNotFoundError: If the source file doesn't exist
+        SyntaxError: If the source file has syntax errors
+    """
+    try:
+        source_code = file_path.read_text(encoding="utf-8")
+        tree = ast.parse(source_code, filename=str(file_path))
+    except FileNotFoundError as e:
+        raise FileNotFoundError(f"Source file not found: {file_path}") from e
+    except SyntaxError as e:
+        raise SyntaxError(f"Failed to parse {file_path}: {e}") from e
+
+    lines = source_code.splitlines()
+    return tree, lines
+
+
+def _extract_assignment(
+    tree: ast.Module, lines: list[str], var_name: str
+) -> str | None:
+    """
+    Extract a module-level assignment statement by variable name.
+
+    Args:
+        tree: AST tree of the source file
+        lines: Source code lines
+        var_name: Name of the variable to extract
+
+    Returns:
+        Complete assignment statement source code, or None if not found
+
+    Example:
+        Extracts:
+        TRITON_KERNELS_CUSTOM_TYPES = (
+            importlib.util.find_spec("triton_kernels") is not None
+            and importlib.util.find_spec("triton_kernels.tensor") is not None
+        )
+    """
+    # Search only at module level
+    for node in tree.body:
+        if isinstance(node, ast.Assign):
+            for target in node.targets:
+                if isinstance(target, ast.Name) and target.id == var_name:
+                    # Found it! Extract source code using line numbers
+                    start_line = node.lineno - 1  # Convert to 0-based index
+                    end_line = node.end_lineno  # Already suitable for slicing
+                    assignment_lines = lines[start_line:end_line]
+                    return "\n".join(assignment_lines)
+    return None
+
+
+def _extract_function(tree: ast.Module, lines: list[str], func_name: str) -> str | None:
+    """
+    Extract a function definition by name, including decorators.
+
+    Args:
+        tree: AST tree of the source file
+        lines: Source code lines
+        func_name: Name of the function to extract
+
+    Returns:
+        Complete function source code including decorators, or None if not found
+
+    Example:
+        Extracts:
+        @lru_cache(maxsize=1)
+        def _get_triton_tensor_types():
+            '''Docstring'''
+            ...
+    """
+    # Walk the entire tree (handles nested functions if needed)
+    for node in ast.walk(tree):
+        if isinstance(node, ast.FunctionDef) and node.name == func_name:
+            # If function has decorators, start from the first decorator
+            if node.decorator_list:
+                start_line = node.decorator_list[0].lineno - 1
+            else:
+                start_line = node.lineno - 1
+
+            end_line = node.end_lineno
+            func_lines = lines[start_line:end_line]
+            return "\n".join(func_lines)
+    return None
+
+
+def _extract_functions(
+    tree: ast.Module, lines: list[str], func_names: list[str]
+) -> list[str]:
+    """
+    Extract multiple functions from a source file.
+
+    Args:
+        tree: AST tree of the source file
+        lines: Source code lines
+        func_names: List of function names to extract
+
+    Returns:
+        List of function source codes in the same order as func_names
+
+    Raises:
+        ValueError: If any function is not found
+    """
+    extracted = []
+    for func_name in func_names:
+        func_source = _extract_function(tree, lines, func_name)
+        if func_source is None:
+            raise ValueError(
+                f"Function '{func_name}' not found in source. "
+                f"Available functions might have been renamed or removed."
+            )
+        extracted.append(func_source)
+    return extracted
+
+
+def _generate_imports() -> str:
+    """
+    Generate the import statements needed for the extracted functions.
+
+    Returns:
+        str: Import statements as a single string
+    """
+    imports = [
+        "import gzip",
+        "import hashlib",
+        "import importlib",
+        "import importlib.util",
+        "import io",
+        "import json",
+        "import logging",
+        "import sys",
+        "from functools import lru_cache",
+        "from pathlib import Path",
+        "from typing import Union",
+        "",
+        "import torch",
+    ]
+    return "\n".join(imports)
@@ -2,6 +2,7 @@
 
 from typing import Any, Dict, Protocol
 
+from tritonparse.reproducer.function_extractor import extract_utility_functions
 from tritonparse.reproducer.ingestion.ndjson import ContextBundle
 from tritonparse.reproducer.types import KernelImportMode
 from tritonparse.reproducer.utils import (
@@ -82,6 +83,9 @@ def __init__(self):
         )
         self.register("# {{KERNEL_SYSPATH_PLACEHOLDER}}", self._replace_kernel_syspath)
         self.register("# {{KERNEL_IMPORT_PLACEHOLDER}}", self._replace_kernel_import)
+        self.register(
+            "# {{UTILITY_FUNCTIONS_PLACEHOLDER}}", self._replace_utility_functions
+        )
         self.register(
             "# {{KERNEL_INVOCATION_PLACEHOLDER}}", self._replace_kernel_invocation
         )
@@ -217,6 +221,13 @@ def _replace_kernel_import(
         else:
             raise ValueError(f"Unknown kernel_import mode: {kernel_import}")
 
+    def _replace_utility_functions(
+        self, code: str, context_bundle: ContextBundle, **kwargs
+    ) -> str:
+        """Replace the utility functions placeholder with extracted functions."""
+        utility_code = extract_utility_functions()
+        return code.replace("# {{UTILITY_FUNCTIONS_PLACEHOLDER}}", utility_code)
+
     def _replace_kernel_invocation(
         self, code: str, context_bundle: ContextBundle, **kwargs
     ) -> str: