ayo
7c5d3c9157
Add native K/M/RR inference engines, HIP kernels, replay and validation harnesses, and Windows DLSS setup and runtime support. Include GPU profiling tools, build and packaging scripts, platform integration patches, and implementation documentation.
47 lines
1.6 KiB
Python
47 lines
1.6 KiB
Python
#!/usr/bin/env python3
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"""Pack a denoiser stage's weights (engine/rr/enc1_ref.py --extract) for the native stage shaders.
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usage: native_pack.py WEIGHTS.npz OUT.bin OUT.h
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Every FP8 matrix W (K x N, rows in NVIDIA's k order) becomes 16x16 tiles, tile (kt, nt) at
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256 * (kt * N/16 + nt) bytes, row-major inside the tile (stride 16): a B operand of the cooperative matrix loads.
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Every f16 matrix is stored as is (row-major); an f16 bias vector (a 1-D entry whose name starts with 'b') as 16
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equal rows, so that it loads as an accumulator tile. OUT.h lists the byte offset of every entry as a #define,
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for the shader's include.
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"""
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import sys
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import numpy as np
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def tiles(w):
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k, n = w.shape
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assert k % 16 == 0 and n % 16 == 0, w.shape
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return w.reshape(k // 16, 16, n // 16, 16).transpose(0, 2, 1, 3).reshape(-1)
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def main():
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src, out_bin, out_h = sys.argv[1:4]
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w = dict(np.load(src))
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blob = bytearray()
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defines = []
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for name in sorted(w):
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a = w[name]
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while len(blob) % 256:
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blob.append(0)
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off = len(blob)
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if a.dtype == np.uint8:
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blob += tiles(a).tobytes()
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elif a.ndim == 1 and name.startswith('b'):
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blob += np.tile(np.asarray(a, np.float16), (16, 1)).tobytes()
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else:
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blob += np.asarray(a, np.float16).tobytes()
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defines.append(f'#define W_{name.upper()} {off}u // {a.dtype} {a.shape}')
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open(out_bin, 'wb').write(bytes(blob))
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open(out_h, 'w').write('// generated by engine/rr/native_pack.py\n' + '\n'.join(defines) + '\n')
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print(f'{len(blob)} bytes, {len(w)} entries')
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if __name__ == '__main__':
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main()
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