西风逍遥游
cff9bb4d0c
Refactor the tensor module around AITemplate-style static compilation: - Optimizer: DCE, constant folding, elementwise chain fusion, matmul/conv bias+activation epilogue fusion, liveness-based static memory planning, topological group execution order. - KernelGen: shape-baked GLSL per fused group; two-pass softmax/layernorm; shared-memory SDPA; naive + 16x16 tiled matmul templates. - GpuBackend: arena buffer allocation per memory plan, matmul autotuning, single command-buffer submission via the new gpgpu::Sequence (uploads, dispatches and downloads recorded once per run, Kompute-style). - shaderc in-process GLSL->SPIR-V on Windows (no glslc.exe dependency), with glslc spawn fallback. - CPU reference kernels shared by eager and the compiled interpreter; no-Vulkan fallback keeps compiled graphs runnable headless. Neural-network coverage: softmax/logsoftmax, layernorm/rmsnorm (with weight/bias), gelu/silu, conv1d/conv2d, pool, embedding, concat/slice, axis reduces, argmax, cast, fused SDPA (+masked), resize2d, batched matmul, seeded random. Weight-only quantization (activations stay fp32): - fp16 (IEEE half), fp8 (e4m3), fp4 (e2m1), int8, int4 with per-group block scales (MXFP-style: scale = maxAbs / format max magnitude). - Quantized weights capture into graph Const nodes; CPU interpreter dequantizes at materialization; GPU matmul/embedding kernels dequantize inline from packed uint buffers (naive matmul variant). - TF::quantizeWeight API + script binding. Mini-LLM validation (TinyStories-gpt2-3M, 8 layers d=64): - test/tensor_llm.cpp builds the full GPT-2 graph from engine ops and matches numpy reference: probs within 3e-7, greedy generation 24/24 identical (~100 ms/token CPU), compiled path exact. - tensor.llm.quantizedDtypes: fp16/int8/fp8/int4 all keep 16/16 greedy top-1 (fp4 16/16 with proper block scaling), weights 27.6 MB -> 3.3-13 MB. - scripts/export_tiny_gpt2.py converts a PyTorch .bin checkpoint (no torch dependency) plus GPT-2 tokenizer into engine assets + numpy reference. Tests: gpgpu 8/8, tensor 31/31 (original suite) + tensor.llm.* + tensor.quant.* Assets in test/assets/mini_llm are gitignored (regenerate via the script).
8 lines
136 B
Plaintext
8 lines
136 B
Plaintext
config <- {
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width = 800
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height = 600
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title = "EVEngine Tensor (AITemplate-style)"
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debug = true
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hotReload = false
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};
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