{"entries":[{"name":"BLAS.csv","mode":"0100644","size":3096121,"lastCommit":{"hash":"2656c0d2652964a66012426f5ec47b283a094cc5","oid":"2656c0d2652964a66012426f5ec47b283a094cc5","parents":["600a36647812a4051e19261026a2186345142e5b"],"author":{"name":"Aaron Teo","email":"aaron.teo1@ibm.com","when":"2026-01-10T18:48:17+08:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-01-10T18:48:17+08:00"},"message":"docs(ggml): update backend ops (#18734)\n\nSigned-off-by: Aaron Teo ","tree":"5e7101609e3d2e51e348a8552190b1710f95aea3"}},{"name":"CANN.csv","mode":"0100644","size":3120164,"lastCommit":{"hash":"6ba6a3c76f1981017bff8a8c0b8857e88db1cdb9","oid":"6ba6a3c76f1981017bff8a8c0b8857e88db1cdb9","parents":["0802d4cfb3e5e5b7340fdd4d41770f2f16379b4e"],"author":{"name":"hipudding","email":"huafengchun@gmail.com","when":"2026-01-16T20:32:17+08:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-01-16T13:32:17+01:00"},"message":"docs : update ops.md for CANN backend (#18654)\n\n","tree":"0b20102e3df6c89d830be9780ae7b2e7a19b5ca7"}},{"name":"CPU.csv","mode":"0100644","size":2050393,"lastCommit":{"hash":"0f1e9d14cc716e3d42728d5181b1b4f93c71bfa3","oid":"0f1e9d14cc716e3d42728d5181b1b4f93c71bfa3","parents":["1274fbee9e185d41447bf6edb739e7240c0319a2"],"author":{"name":"a3894281","email":"a3894281@gmail.com","when":"2026-03-10T15:31:24+02:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-03-10T21:31:24+08:00"},"message":"docs: update CPU backend ops to mark POOL_1D as supported (#20304)","tree":"2b68eff1b4557115ec147c15a0164d48e9a2e5f9"}},{"name":"CUDA.csv","mode":"0100644","size":3118129,"lastCommit":{"hash":"63391852b05ceaba6547dbd1c60ac716474e2798","oid":"63391852b05ceaba6547dbd1c60ac716474e2798","parents":["086a63e3a5d2dbbb7183a74db453459e544eb55a"],"author":{"name":"Sigbjørn Skjæret","email":"sigbjorn.skjaeret@scala.com","when":"2025-12-09T23:31:29+01:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2025-12-09T23:31:29+01:00"},"message":"docs : update cpu and cuda ops (#17890)\n\n* update cuda ops\n\n* update CPU as well","tree":"aae13a2575e2d770d25631c95787dfe34c8e8bd7"}},{"name":"ET.csv","mode":"0100644","size":2492438,"lastCommit":{"hash":"082b326fc76f6e9bbb835b3920a3022bfdb6691c","oid":"082b326fc76f6e9bbb835b3920a3022bfdb6691c","parents":["961e4b26a7dd0e01e20599b27d709a74788ecb55"],"author":{"name":"Martin Chang","email":"marty1885@users.noreply.github.com","when":"2026-07-10T12:38:34+08:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-07-10T12:38:34+08:00"},"message":"ggml-et: Initial ET backend (#24179)\n\n* ggml-et: Add performance logging\n\n* ggml-et: Quants helpers\n\n* ggml-et: Add MUL_MAT kernel\n\n* ggml-et: Add ROPE kernel\n\n* ggml-et: Add RMS_NORM kernel\n\n* ggml-et: Add GLU kernel\n\n* ggml-et: Add SOFT_MAX kernel\n\n* ggml-et: Add GET_ROWS kernel\n\n* ggml-et: Add CONT kernel\n\n* ggml-et: Add SET_ROWS kernel\n\n* ggml-et: Add MUL_MAT_ID kernel\n\n* ggml-et: Build et kernels as part of ggml\n\n* ggml-et: Embed kernels with fs fallback\n\n* ggml-et: Build fixes\n\n* ggml-et: Add MUL_MAT F32xF32 op\n\n* ggml_et: Add MUL_MAT_ID op\n\n* ggml-et: Disable offloading for debug\n\n* ggml-et: Refactor out block ops\n\n* ggml-et: ggml backend API changes\n\n* ggml-et: Add RESHAPE/TRANSPOSE to supported\n\n* ggml-et: Add CONT_F16\n\n* ggml-et: Add supported ops doc\n\n* gglm-et: Initial doc\n\n* ggml-et: Remove runtime import hacks\n\nWe can now import the runtime by a simple find_package(), so we\ncan cleanup the CMakeLists.txt.\n\n* ggml-et: Fix GET_ROWS kernel\n\nFix lost batch dimension.\n\nAlso clean vibe-comments.\n\n* ggml-et: Fix SET_ROWS kernel\n\nRemove incorrect broadcasting guard.\n\n* ggml-et: Use custom instruction for fp32->fp16\n\n* ggml-et: Vectorize set_rows fp32->fp16\n\n* ggml-et: Fix ROPE kernel (yarn)\n\nggml-et: fix et_logf\n\nWIP: Fix ramp\n\nWIP: fix ROPE!\n\n* ggml-et: Better sinf\n\n* ggml-et: Fix SOFT_MAX\n\nAdd `max_bias` and `sink` support.\n\n* ggml-et: Fix CONT\n\nReorder from contiguous write to read with atomic stores.\n\n* ggml-et: Fix elmap kernel\n\nRemainder handlin\n\n* ggml-et: Fix MUL_MAT MUL_MAT_ID remainders\n\n* ggml-et: Fix ET-SOC reference\n\n* ggml-et: Fix embed kernels scripts for old python\n\nThis allows GGML-ET to build on pre-3.8 python.\n\n* Add sysemu support with compile time flag `-DGGML_ET_SYSEMU=ON` (#6)\n\n* Example using ET-Soc-1 emulator configuration\n\nExample usage:\n```bash\ncmake -B build -DGGML_CUDA=OFF -DGGML_ET=ON -DLLAMA_CURL=OFF -DGGML_CCACHE=ON\ncmake --build build --config Release -j $(nproc)\n\ntime ./build/bin/test-backend-ops\n\n./build/bin/llama-server \\\n --model Qwen3-0.6B-Q8_0.gguf \\\n --alias Qwen3-0.6B-Q8_0 \\\n -fa 0 \\\n --ctx-size 1024 \\\n --no-warmup \\\n --host 127.0.0.1 \\\n --port 8080\n```\n\n* build: proper dep tracking for kernels\n\n* support host using MOLD linker\n\n* initial multi core GET_ROW F32 implementation\n\n* vectorized q8 dequant\n\n* wip: cland warning clenaups and initial logging refactor\n\n* wip: message default message cleanup\n\n* chore: message cleanups\n\n* cmake cleanup\n\n* migrate to use platform provided functions\n\n* cmake back into subdir\n\n* support et_print() in kernels\n\n* fix: repair kernel building\n\n* perf: operations run async by default\n\n* debug: proper kernel dep tracking and error detection on kenrel launch\n\n* fix: kernel binary dep tracking and fixing get_rows_f32 erroring\n\n* perf: back to doing async kernel runs by default\n\n* perf: vectorize and parallel device memset\n\n* merge matmul work\n\n* misc: align allocation and enable all offload\n\n* misc: delete deadcode and respect memory limits\n\n* fix: repair tensor debug print\n\n* fix: loosen RMS_NORM op percision\n\n* feat: Q4_0 GET_ROWS\n\n* perf: FP32 MUL_MAT using TensorFMA\n\n* update limitations\n\n* perf: redue L1 load in compute_block_dot_product_q8_0\n\n* feat: save kernel mapping (name to id) when profiling is enabled\n\n* chore: memops cleanup\n\n* perf: parallelize softmax by rows\n\n* perf: vectorize 2nd phase of softmax\n\n* perf: ban GET_ROWS from offloaded\n\n* perf: vectorize and non-atomic for eltwise ops and sub support\n\n* perf: vectorize normal rope\n\n* perf: glu runs in parallel\n\n* merge: manually merge saqib's work on kernel fixes\n\n* perf: more vectorized RoPE\n\n* perf: parallelize mul_mat_id\n\n* perf: parallelize set_rows_f32\n\n* perf: vectorize softmax\n\n* feat: support kernel fusion and fuse RMS_NORM + MUL\n\n* fix: mostly resolve test-backend-ops failure in SOFT_MAX and ROPE\n\n* fix: bump max rope dims for gemma\n\n* feat: GeGLU and SCALE support to fully offload Gemma\n\n* perf: faster device memset\n\n* feat: get_rows supporting Q4_K and avoid cont cache coherent issues\n\n* better F32 MM\n\n* feat: NORM for ET backend\n\n* feat: SQR for ET backend\n\n* feat: UNARY on ET\n\n* feat: el_map support broadcasting for ET\n\n* feat: SUM_ROWS in ET backend\n\n* feat: more ops in ET backend\n\n* feat: WKV* operators in ET backend\n\n* perf: parallelize operators across cacheline instead of row\n\n* perf: parallelize get_rows on cacheline\n\n* wip: baseline FlashAttention for ET backend\n\n* wip: enough FA and CPY f32->f16 to run llama 3.1 fully offloaded with FA on\n\n* feat: f16 x f16 -> f32 MM using matrix engine\n\n* wip: f16 FlashAttention using matrix engine\n\n* wip: clean up\n\n* feat: barriers\n\n* perf: optimize FA_F16 in ET\n\n* perf: vectorize pack_k_for_transpose16\n\n* perf: prefetch next loop matrix tile\n\n* perf: FlashAttention 2nd MM uses TensorFMA and optimizations\n\n* cleanup: flashattention reorg\n\n* perf: optimizations and fixes\n\n* feat: L2SCP API and make FlashAttention support DV = 256 for gemma\n\n* perf: parallelize norms beyond single row\n\n* feat: GATED_DELTA_NET support and relaxed L2_NORM requirment\n\n* feat: loosen RMS_NORM, NORM, ROPE contingous req too\n\n* feat: repeat supports brocasting on dim 0 and loosen cont check\n\n* feat: FILL and DIAG operator\n\n* feat: loosen UNARY support chcek\n\n* feat: TRI support\n\n* feat: SOLVE_TRI support\n\n* feat: basic SET support\n\n* feat: loosen CONT req\n\n* perf: fp16_to_fp32 use ASM\n\n* feat: IMROPE support\n\n* feat: PAD support\n\n* feat: global barrier\n\n* fix: view must live on the same backend as backing tensor\n\n* feat: relax CONCAT in ET backend\n\n* feat: dead simple CUMSUM implementation\n\n* feat: basic SSM_CONV support\n\n* feat: loosen CONCAT req\n\n* feat: relax GATED_DELTA_NET and add SET support proper\n\n* cleanup: cleanup LCM math\n\n* feat: SWIGLU single input\n\n* feat: SSM_SCAN support\n\n* feat: el_map supports non aligned tensors in best effort\n\n* feat: basic GROUP_NORM support\n\n* feat: loosen MUL_MAT capablities slightly\n\n* feat: loosen MUL_MAT and GET_ROWS and add IM2COL\n\n* feat: special case for softmax 1x1x1x1\n\n* feat: loosen SOFT_MAX req in ET backend\n\n* fix: el_map unaligned acse fixes\n\n* perf: optimize zero_acc_vec in flash_attn_ext_f16_me\n\n* perf: use hart 1 for packing in MM and FA for FP16\n\n* feat: kernel semaphore\n\n* perf: better instruction sequence in FlashAttention\n\n* fix: gated_delta_net with proper masking\n\n* perf: better parallelization for GATED_DELTA_NET\n\n* perf: parallelize SSM_CONV over nr\n\n* perf: vectorize SSM_CONV\n\n* perf: optimize MUL_MAT for q8\n\n* feat: support Gemma 4\n\n* fix: support multi-device\n\n* feat: broader GLU support\n\n* feat: unary ops supports view\n\n* fix: repair fp16 MM using matrix engine\n\n* perf: handle large N GEMV better\n\n* perf: better q8_0 MM\n\n* perf: better set_rows\n\n* add back deleted files\n\n* fix: repair after merge\n\n* feat: POC version of uberkernel\n\n* feat: RMS_NORM in uberkernel\n\n* feat: add more kernels into usage\n\n* chore: clean up uberkernel compilation\n\n* perf: faster flash attention\n\n* perf: opt flash attention for large seq length\n\n* feat: loosen op bounds. clamp and mean support\n\n* perf: vectorize ssm_scan\n\n* perf: slightly faster FA\n\n* perf: FlashAttention parallel MM and load\n\n* perf: fuse Q8 MM and ADD\n\n* feat: basic conv kernel for ET\n\n* softMAx_test\n\n* set_rows_f32\n\n* get_rows and cont\n\n* testing\n\n* set_rows_exp\n\n* Junk addition\n\n* Narrowing the issue\n\n* Update flash_attn_ext_f16_me.c\n\nFocusing FA_ext_f16_me\n\n* test\n\n* Eviction updated\n\n* Detailed cache eviction debug\n\n* mulmat\n\n* removeal of `BUILD_FOR_UBERKERNEL` flag\n\n* cleaning...\n\n* fix: balance FCC0 count\n\n* feat: implement mul_mat and mul_mat_id for Q4_0 type\n\n* optimize uberkernel plan upload\n\n* add mul_mat q4 into uberkernel\n\n* enable gating flush to just uberkernel\n\n* update docs for ET\n\n* update op support for ET\n\n* et-backend: optimize Q4_0 and Q8_0 mul_mat_id row accumulations\n\n* et-backend: specialize mul_mat_id kernels for Q4_0 and Q8_0\n\n* et-backend: fix RoPE YaRN corr_dim formula and handle degenerate inputs\n\n* test-backend-ops: add DeepSeek-V2-Lite RoPE test coverage\n\n* et-backend: add Q4_0 mul_mat matrix-engine kernel using TensorFMA32\n\n* et-backend: vectorize Q4_0 matrix-engine dequantization\n\n* et-backend: support hybrid matrix/vector engine execution for Q4_0 mul_mat tail\n\n* et-backend: run partial-N tiles on matrix engine for Q4_0 mul_mat\n\n* et-backend: route Q4_0 mul_mat N < 53 to vecdot for better prefill latency\n\n* Update uberkernel.c\n\n* Update unary_f32.c\n\n* gemma 4\n\n* bisect gemma4: enable scale_f32 only\n\n* bisect gemma4: +rms_norm_f32\n\n* bisect gemma4: +rms_norm_mul_f32\n\n* bisect gemma4: disable rms_norm_mul_f32 -- BREAKS OUTPUT\n\n* bisect gemma4: +rope_f32 (skip rms_norm_mul)\n\n* bisect gemma4: +el_map_f32\n\n* bisect gemma4: +softmax_f32\n\n* bisect gemma4: +get_rows_f32\n\n* bisect gemma4: +glu_f32\n\n* bisect gemma4: +mul_mat_f32 +mul_mat_f32_matrix_engine\n\n* bisect gemma4: +mul_mat_f16 +mul_mat_f16_matrix_engine\n\n* bisect gemma4: +mul_mat_Q8_0 +mul_mat_Q4_0\n\n* bisect gemma4: +flash_attn_ext_f32 +flash_attn_ext_f16_me\n\n* bisect gemma4: +mul_mat_id_f32\n\n* bisect gemma4: +sum_rows_f32\n\n* bisect gemma4: +cont_f16\n\n* bisect gemma4: +fill_f32\n\n* bisect gemma4: +unary_f32 (all ops re-enabled except rms_norm_mul)\n\n* Update rms_norm_mul_f32.c\n\n* bisect2 gemma4 n64: +scale_f32 only\n\n* bisect2 gemma4 n64: +rms_norm_f32 +rope_f32\n\n* bisect2 gemma4 n64: +rms_norm_mul_f32 (with ET_UBERKERNEL eviction fix)\n\n* bisect2 gemma4 n64: +el_map +get_rows +glu +softmax (skip rms_norm_mul)\n\n* bisect2 gemma4 n64: all ops enabled except rms_norm_mul\n\n* bisect2 n64: test unary+cont+fill+sum_rows (no mul_mat/flash_attn)\n\n* bisect2 n64: +mul_mat_f32 +mul_mat_f32_matrix_engine\n\n* bisect2 n64: +mul_mat_f16 +mul_mat_f16_matrix_engine\n\n* bisect2 n64: +mul_mat_Q8_0 +mul_mat_Q4_0\n\n* bisect2 n64: +mul_mat_Q8_0 only (disable Q4_0)\n\n* bisect2 n64: +mul_mat_Q4_0 only (Q8_0 breaks)\n\n* bisect2 n64: +mul_mat_id +flash_attn_ext (skip Q8_0)\n\n* run-3: matmul + rms_norm_mul\n\n* run-4\n\n* Revert \"run-4\"\n\n* run5\n\n* changes after cleanup\n\n* cleanup before upstream\n\n* restrict changes into ET backend\n\n* move kernel embedding from Python to CMake\n\n* move uberkernel gen into CMake\n\n* apply clang format\n\n* update CMake style\n\n* update to match C and C++ style\n\n* use source ggml and quant headers instead of ET's\n\n* MROPE support\n\n* absorb view ops into same branch as none\n\n* fix bad rebase\n\n* add marty1885 to codeowners\n\n* oops\n\n* remove redundant newline\n\n* fix CI editor warnings\n\n---------\n\nCo-authored-by: Vidas \nCo-authored-by: Gianluca Guida \nCo-authored-by: Gianluca Guida \nCo-authored-by: ubergarm \nCo-authored-by: SaqibAkram-10xE \nCo-authored-by: Rehan Qasim ","tree":"485b354647fb331cffd439b06b05b0a6b0460e5b"}},{"name":"Metal.csv","mode":"0100644","size":2461893,"lastCommit":{"hash":"ae2d34899e2a9a172c7f2090ed4dd366bbf25d0d","oid":"ae2d34899e2a9a172c7f2090ed4dd366bbf25d0d","parents":["1e796eb41fb51950ada45811a303e57a5f4ea974"],"author":{"name":"Kusha Gharahi","email":"3326002+kushagharahi@users.noreply.github.com","when":"2026-04-16T03:54:37-05:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-04-16T11:54:37+03:00"},"message":"metal: Implement ROLL op (#21946)\n\n* nix: support unified apple-sdk\n\n* Impl roll op for Metal\n\n* Revert \"nix: support unified apple-sdk\"\n\nThis reverts commit abfa473360471532c547de8b202c780507924d4b.\n\n* update ops.md\n\n* update op docs","tree":"56e054d12790b012dbaea0a524ea6c23e31f5edb"}},{"name":"OpenCL.csv","mode":"0100644","size":3167812,"lastCommit":{"hash":"2d2e1030e3183f7d86f0f194297cd9a75aa707cf","oid":"2d2e1030e3183f7d86f0f194297cd9a75aa707cf","parents":["17f7f4baad8b3a716ee139da7bb56ae984e8c0fa"],"author":{"name":"lhez","email":"lih@qti.qualcomm.com","when":"2025-12-10T06:20:00-08:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2025-12-10T15:20:00+01:00"},"message":"docs : update opencl ops (#17904)\n\n","tree":"5234a7d3c3bc669890370a53215dbf691241f4e9"}},{"name":"SYCL.csv","mode":"0100644","size":3117173,"lastCommit":{"hash":"37a215c9e909822fb8ebb72b5bd37623b0b9611f","oid":"37a215c9e909822fb8ebb72b5bd37623b0b9611f","parents":["4df29be4f4c3673f428170fda944a5b19f743bb8"],"author":{"name":"Neo Zhang","email":"zhang.jianyu@outlook.com","when":"2026-08-17T12:31:29+08:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-08-17T07:31:29+03:00"},"message":"[SYCL] support OP OPT_STEP_ADAMW, OPT_STEP_SGD (#25268)\n\n* fix conflict\n\n* fix conflict of ops.md\n\n* fix conflict of ops.md\n\n* update the ops.md\n\n---------\n\nCo-authored-by: Neo Zhang Jianyu ","tree":"32d61b4a5011fb1731285247489917e1b01749bc"}},{"name":"Vulkan.csv","mode":"0100644","size":3174197,"lastCommit":{"hash":"f26efa02a77dc3660f94ac90efee59394f3bc74d","oid":"f26efa02a77dc3660f94ac90efee59394f3bc74d","parents":["cf06ad7dfe79e7bf2934150d4fefe1ce8db05490"],"author":{"name":"Pranav Uttarkar","email":"122235768+PranavUttarkar@users.noreply.github.com","when":"2026-08-04T03:40:54-05:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-08-04T11:40:54+03:00"},"message":"vulkan backend ops: implemented GATED_LINEAR_ATTN (#25601)\n\n* vulkan : add GATED_LINEAR_ATTN op\n\n* docs : update Vulkan ops\n\n* vulkan : remove unused GLA spec constant\n\n* Updated ops.md\n\n* ops.md update","tree":"cc3075db6efb221b92ba7d32756dfb9ccc5f026d"}},{"name":"WebGPU.csv","mode":"0100644","size":2974846,"lastCommit":{"hash":"7347430f4466d4f55cfb841974ee64b80fc18d93","oid":"7347430f4466d4f55cfb841974ee64b80fc18d93","parents":["c5a4a0bb832fcdb44487996150b3141490fdff69"],"author":{"name":"m1el","email":"m1el@ya.ru","when":"2026-07-22T03:24:44-05:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-07-22T17:24:44+09:00"},"message":"webgpu : add CONV_2D_DW (depthwise conv2d) kernel (#25847)\n\n* webgpu : add CONV_2D_DW (depthwise conv2d) kernel\n\nImplement GGML_OP_CONV_2D_DW for the WebGPU backend,\nported from the Vulkan backend's conv2d_dw.comp.\n\nAssisted-by: Claude Opus-4.8\n\n* Remove unnecessary comments in webgpu support\n\n* update supported ops tables, triggered by adding webgpu CONV_2D_DW","tree":"ceda2871fb25fe905314848b57f8eb5306109f0e"}},{"name":"ZenDNN.csv","mode":"0100644","size":2231165,"lastCommit":{"hash":"f1ac84119ccc8e72dafd9e9f8fc3b9399917ce11","oid":"f1ac84119ccc8e72dafd9e9f8fc3b9399917ce11","parents":["b069b10ab48f25ba119e59d0b8bf35d4f06e093f"],"author":{"name":"Vishal Singh","email":"vishal@zettabolt.com","when":"2026-04-03T14:49:08+05:30"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-04-03T12:19:08+03:00"},"message":"ggml-zendnn : add MUL_MAT_ID op support for MoE models (#21315)\n\n* ggml-zendnn : add MUL_MAT_ID op support for MoE models\n- Add MUL_MAT_ID op acceleration for Mixture-of-Experts models\n- MUL_MAT_ID op fallback to CPU backend if total experts > 32\n- Point ZenDNN lib to latest bits ZenDNN-2026-WW13\n\n* ggml-zendnn : add braces to sgemm failure condition for consistency\n\nCo-authored-by: Aaron Teo \n\n---------\n\nCo-authored-by: Aaron Teo ","tree":"5cfcaeeafb4eb288f76050ce96caa3a0e1f47457"}},{"name":"zDNN.csv","mode":"0100644","size":3090387,"lastCommit":{"hash":"2656c0d2652964a66012426f5ec47b283a094cc5","oid":"2656c0d2652964a66012426f5ec47b283a094cc5","parents":["600a36647812a4051e19261026a2186345142e5b"],"author":{"name":"Aaron Teo","email":"aaron.teo1@ibm.com","when":"2026-01-10T18:48:17+08:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-01-10T18:48:17+08:00"},"message":"docs(ggml): update backend ops (#18734)\n\nSigned-off-by: Aaron Teo ","tree":"5e7101609e3d2e51e348a8552190b1710f95aea3"}}],"lastCommit":{"hash":"37a215c9e909822fb8ebb72b5bd37623b0b9611f","oid":"37a215c9e909822fb8ebb72b5bd37623b0b9611f","parents":["4df29be4f4c3673f428170fda944a5b19f743bb8"],"author":{"name":"Neo Zhang","email":"zhang.jianyu@outlook.com","when":"2026-08-17T12:31:29+08:00"},"committer":{"name":"GitHub","email":"noreply@github.com","when":"2026-08-17T07:31:29+03:00"},"message":"[SYCL] support OP OPT_STEP_ADAMW, OPT_STEP_SGD (#25268)\n\n* fix conflict\n\n* fix conflict of ops.md\n\n* fix conflict of ops.md\n\n* update the ops.md\n\n---------\n\nCo-authored-by: Neo Zhang Jianyu ","tree":"32d61b4a5011fb1731285247489917e1b01749bc"}}