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83 lines
2.5 KiB
Markdown
83 lines
2.5 KiB
Markdown
# CK Tile Dispatcher Python Utilities
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This directory contains Python utilities used by the dispatcher examples.
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## Contents
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### Shared Utilities (used by both GEMM and Grouped Conv)
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- `dispatcher_common.py` - Shared dispatcher infrastructure
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- Path helpers (`get_dispatcher_root`, `get_build_dir`, etc.)
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- `ValidationResultBase` - Structured validation feedback
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- `validate_wave_config`, `validate_warp_tile_config`, `validate_trait_combo`
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- `auto_correct_wave`, `auto_correct_trait` - Auto-correction helpers
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- `Colors` - Cross-platform ANSI color support
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- `print_phase`, `print_success`, `print_error`, `print_info` - Phased output
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- `cleanup_generated_kernels` - Cleanup helper
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### GEMM Utilities
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- `ctypes_utils.py` - Core ctypes utilities for GEMM Python examples
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- `KernelConfig` - Kernel configuration dataclass
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- `setup_gemm_dispatcher()` - Setup dispatcher with auto-correction
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- `cleanup_gemm()` - Cleanup dispatcher resources
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- `GemmRunner` - GPU execution helper
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- Auto-correction and validation utilities
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### Grouped Convolution Utilities
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- `grouped_conv_utils.py` - Utilities for grouped convolution
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- `GroupedConvValidationResult` - Validation result (extends `ValidationResultBase`)
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- `validate_grouped_conv_config` - Validate a grouped conv config
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- `auto_correct_grouped_conv_config` - Auto-correct invalid configs
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- `get_grouped_conv_default_config` - Get default config for a variant
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- `GroupedConvDataType` - Data type enum (FP16, BF16, FP32, FP8, BF8, INT8)
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- `format_grouped_conv_summary` - Human-readable config summary
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## Usage
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### GEMM Examples
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The GEMM Python examples in `dispatcher/examples/gemm/python/` import:
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```python
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent / "python"))
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from ctypes_utils import (
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KernelConfig,
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setup_gemm_dispatcher,
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cleanup_gemm,
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GemmRunner,
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)
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```
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### Grouped Conv Usage
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```python
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent / "python"))
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from grouped_conv_utils import (
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validate_grouped_conv_config,
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auto_correct_grouped_conv_config,
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get_grouped_conv_default_config,
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GroupedConvDataType,
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)
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# Get a default config
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config = get_grouped_conv_default_config(variant="forward", arch="gfx942")
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# Validate
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result = validate_grouped_conv_config(config)
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print(f"Valid: {result.is_valid}")
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```
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## Requirements
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- Python 3.8+
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- NumPy
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- HIP runtime (for GPU execution)
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