Testing #356
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Testing #356
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Aug 10, 2022
* Ops dispatch * CI: Fix doc build * memory_efficient_attention raises when no implementation is available * type: ignore * Fix torch.device/str comparison * Make mypy happy Co-authored-by: danthe3rd <danthe3rd@users.noreply.github.com> Co-authored-by: danthe3rd <danthe3rd>
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* Enable masking in memory-efficient attention (#333) * Add attention bias in memory-efficient attention * Add gradient for attn_mask support * Add CPU implementation * clang-format * Add benchmark scripts * Add extra loop in benchmarks * Move zeros array out of helper function * clang-format * Enable dropout in memory-efficient attention (#334) * Merge compute_scaling_coeffs and update_scaling_coeffs into a single function It wasn't needed to break it in two functions to begin with * Add CUDA implementation for dropout * clang-format * Make p be drop probability * Only CUDA supports dropout * Add benchmarks * Remove unused variables * Fix test * Cleanups and comments * Fix masking corner case when full block is masked (#339) * Add cutlass 2.9 - 858c735856a7f17bd33fe438ec76d3c9f0234e7f * Option to load from shared memory for PredicatedTileIterator * Add cutlass include dir * Ignore files in third-party for flake8/coverage * third-party -> third_party * Address comments * Revert some un-needed mods * Add attention_forward_generic.cu * Add tests * Fix duplicate calculations on baseline for mem efficient transformers * Always run all linters in CI * clang-format attention_forward_generic.cu * Benchmark: Add possibility to compare benchmarks * [isort] Ignore third_party * black autoformat * Black again + ignore third_party properly * black * Fix memory leak between the 2 benchmarks in backward * Exclude third_party/ without using pyproject.toml as it imposes isolated build which is a pain * Remove progress bar when finished * mypy * flake8 * Save results to shared folder in home location * run black * clang-format with 'run-clang-format.py' * Fix cutlass build for arch>=75 * Set tests precision for gradient more accurately * Fix precision margin * Revert changes to black * [feat] Fix importing xformers when not built (#351) authored-by: danthe3rd <danthe3rd@users.noreply.github.com> * Update black to 22.3.0 * Tweak precision for mem_eff_attention test * mem-efficient impl for f16 (#352) Co-authored-by: danthe3rd <danthe3rd> * Add support for f16 with tensorcores [sm70/sm75/sm80] (#354) * Add support for f16 with tensorcores * sm75 minimum for tensorcores * Run tests with CUDA_LAUNCH_BLOCKING=1 * Support sm70 properly * Disable tensorcore when not correctly aligned - and use 32bit accessors Co-authored-by: danthe3rd <danthe3rd> Co-authored-by: danthe3rd <danthe3rd@users.noreply.github.com> * Optimize backward of memory-efficient attention by ~20% (#355) * Optimize backward by 15% by using equivalent formulation * Unify everything into single kernel * Remove unused implementation * clang-format * Remove unused tensor * Display results as we progress during benchmark (#357) Co-authored-by: danthe3rd <danthe3rd> * RFC: Ops dispatch (#356) * Ops dispatch * CI: Fix doc build * memory_efficient_attention raises when no implementation is available * type: ignore * Fix torch.device/str comparison * Make mypy happy Co-authored-by: danthe3rd <danthe3rd@users.noreply.github.com> Co-authored-by: danthe3rd <danthe3rd> * [A100/f32] Use TensorCores for Q.K_t matmul with FastF32 (#358) * Use TensorCores for MM0 on Float as well * Use MultiStage MMA when available - change to FastF32 rather than FastF16 * Better alignment calculation * Just use regular f32, no fastf32 * Hackfix to handle alignment * HeuristicsMM0 -> GemmTypeQK * No longer use f16 for matmul * Add some doc * Typo * Fix build <sm80 * Alignment check based on current device compute capability * Use TORCH_INTERNAL_ASSERT Co-authored-by: danthe3rd <danthe3rd> * FlashAttention implem and dispatch (#360) * FlashAttention implem WIP * Fix flashattention forward+backward * Fix forward/backward for FlashAttention * Enable tests (more permissive) for f16 backward * Fix CI * flashattn only supports Sm75 and above * Fix CI2 * Disable K=128 when below sm80 for flashattn Co-authored-by: danthe3rd <danthe3rd> * Misc performance improvements for generic mem-efficient attention (#361) * 3% speedup by calculating mi from registers * Also compute m_prime/s_prime and exponentiate from registers * Support for Simt tiles * Fix TensorOp for V100 * Fix for A100 * Fix Simt alignment calculation * clang-format * WarpReduction before atomic call for Simt Co-authored-by: danthe3rd <danthe3rd> Co-authored-by: danthe3rd <danthe3rd@users.noreply.github.com> * Update flashattention to support bf16 (#363) * Update flashattention to support bf16 * bfloat16 only on sm80 and above Co-authored-by: danthe3rd <danthe3rd> * Flashattn causal (#364) * Implement causal memory-efficient attention with FlashAttention * Update benchmarks * Fix mypy Co-authored-by: danthe3rd <danthe3rd> * Option to disable flashattention (long to build) (#362) * Option to disable flashattention (long to build) * Update setup.py Co-authored-by: danthe3rd <danthe3rd> * Remove code duplicate in attention_scaling_coefs_updater.h (#367) Co-authored-by: danthe3rd <danthe3rd> * Update .gitmodules (#366) * MemoryEff attention forward: Properly fuse matmul and enable TensorCores on the second matmul (#368) * Generic backwards * Guard backward to sm75 only * bounds checking for gradV * clang-format * Fused gemm working for Sm80/Sm75 f16/f32 * WIP * Volta TensorOp for f16 * Working on A100 again * SIMT working * Code cleanup 1 * Code cleanup2 * BUGFIX for shared memory limit * Remove code * clang-format * Remove code again * Remove draft of backward * Enforce alignment for fp16 * Fix tests * Fix constraint on seq length when not using tensorcores * Fix alignment requirements for V100/tensorcores * Clang-format * Update xformers/components/attention/csrc/cuda/attention_forward_generic.cu Co-authored-by: Francisco Massa <fvsmassa@gmail.com> * Address comments from fmassa Co-authored-by: danthe3rd <danthe3rd> Co-authored-by: danthe3rd <danthe3rd@users.noreply.github.com> Co-authored-by: Francisco Massa <fvsmassa@gmail.com> * Update install instructions with submodule (#365) * Generic backward implem with cutlass (#371) * Old bw code * P100: gradV working * gk/gq working (at least for small values of M, and on P100/f16) * Further restrict supported values for bw * Fix storage into smem for Simt * More tooling for pruint/debug * Remove tests we dont need for now * Tests pass on P100 :D * 4 warps per block * Restraint on q length * Use tensorcores on V100 for f16 * Support dynamic smem for bw * Handle alignment and different dtype/arch * Fix NaNS by initializing shared memory * bw.py * Fix launch bounds * Faster 'computeDi' * minus_lse can operate on arrays * Output number of regs used etc... * Code cleanup * Hackfix for alignment check during forward * zFill to avoid nans in Sm80 + fix launch bounds * COde cleanup1 * clang-format * Fix tests * Add benchmark for K=64 Co-authored-by: danthe3rd <danthe3rd@users.noreply.github.com> Co-authored-by: danthe3rd <danthe3rd> * Cutlass as submodule (#375) * Make cutlass be back at 858c735856a7f17bd33fe438ec76d3c9f0234e7f * Remove cutlass * Update submodules * Add submodule (properly) * spaces / tab * Make submodule init be recursive * Fix bad rebase * Bump tolerance for backward (#377) * Add verbose flag to CI builds (#376) * Add verbose flag to CI builds * Spurious change to rebuild cache * Add ninja * Ninja wasn't visible before, install through conda * Debugging * Source env * One more try * Forgot to uncomment a line * Another try * Cleanup * Fix for FlashAttention dispatch It requires device capability >= 7.5 * Remove generated file * Address some reviewer feedback Remove unused function and typo fix * Perf improvement on backward (#378) * Fast again on V100 * Fix correctness - missing syncthreads * Get rid of AttentionInfo Co-authored-by: danthe3rd <danthe3rd@users.noreply.github.com> Co-authored-by: danthe3rd <danthe3rd@users.noreply.github.com> Co-authored-by: dan_the_3rd <43445237+danthe3rd@users.noreply.github.com>
bertmaher
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Dec 20, 2024
* Ops dispatch * CI: Fix doc build * memory_efficient_attention raises when no implementation is available * type: ignore * Fix torch.device/str comparison * Make mypy happy Co-authored-by: danthe3rd <danthe3rd@users.noreply.github.com> Co-authored-by: danthe3rd <danthe3rd>
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