TheRock/rocm-libraries/projects/composablekernel/dispatcher/python/README.md

CK Tile Dispatcher Python Utilities

This directory contains Python utilities used by the dispatcher examples.

Contents

Shared Utilities (used by both GEMM and Grouped Conv)

• dispatcher_common.py - Shared dispatcher infrastructure
  • Path helpers (get_dispatcher_root, get_build_dir, etc.)
  • ValidationResultBase - Structured validation feedback
  • validate_wave_config, validate_warp_tile_config, validate_trait_combo
  • auto_correct_wave, auto_correct_trait - Auto-correction helpers
  • Colors - Cross-platform ANSI color support
  • print_phase, print_success, print_error, print_info - Phased output
  • cleanup_generated_kernels - Cleanup helper

GEMM Utilities

• ctypes_utils.py - Core ctypes utilities for GEMM Python examples
  • KernelConfig - Kernel configuration dataclass
  • setup_gemm_dispatcher() - Setup dispatcher with auto-correction
  • cleanup_gemm() - Cleanup dispatcher resources
  • GemmRunner - GPU execution helper
  • Auto-correction and validation utilities

Grouped Convolution Utilities

• grouped_conv_utils.py - Utilities for grouped convolution
  • GroupedConvValidationResult - Validation result (extends ValidationResultBase)
  • validate_grouped_conv_config - Validate a grouped conv config
  • auto_correct_grouped_conv_config - Auto-correct invalid configs
  • get_grouped_conv_default_config - Get default config for a variant
  • GroupedConvDataType - Data type enum (FP16, BF16, FP32, FP8, BF8, INT8)
  • format_grouped_conv_summary - Human-readable config summary

Usage

GEMM Examples

The GEMM Python examples in dispatcher/examples/gemm/python/ import:

import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent / "python"))

from ctypes_utils import (
    KernelConfig,
    setup_gemm_dispatcher,
    cleanup_gemm,
    GemmRunner,
)

Grouped Conv Usage

import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent / "python"))

from grouped_conv_utils import (
    validate_grouped_conv_config,
    auto_correct_grouped_conv_config,
    get_grouped_conv_default_config,
    GroupedConvDataType,
)

# Get a default config
config = get_grouped_conv_default_config(variant="forward", arch="gfx942")

# Validate
result = validate_grouped_conv_config(config)
print(f"Valid: {result.is_valid}")

Requirements

• Python 3.8+
• NumPy
• HIP runtime (for GPU execution)