Commit Graph
193 Commits
Author SHA1 Message Date
Georgi Gerganov 6036c635e2 ggml : fix ggml_clamp (#27644)
* ggml : fix ggml_clamp

* cont : update ggml-alloc
2026-08-24 10:43:04 +03:00
Xuan-Son Nguyen fe8156f789 ggml: add ggml_rope_set_offset (+ metal support) (#27120)
* add params

* cpu kernel

* metal kernel

* add test backend ops

* gate other backends

* ggml: (cuda) support ggml_rope_set_offset (#27121)

* rm cuda supports_op guard, fix webgpu clang-format

* ggml: support ggml_rope_set_offset on vulkan (#27344)

* ggml: support ggml_rope_set_offset on vulkan

* remove inplace optimization
2026-08-19 14:04:57 +02:00
1692f9e50b ggml : recurrent state rollback for ggml_ssm_scan (#26623)
* Initial changes for Recurrent state rollback for nemotron for cpu and cuda

* Removing CPU RS rollback. Will enable it in subsequent PRs

* addition of test case

* Removing assert and calling runtime API to check if op is supported

* removing extra API and updating the call sites for K

* replace static cuda detection to runtime fused_op api

* address review comments and fallback when SSM rollback not supprted

* Adding changes for supporting RS-rollback in CPU. Also added test-backend-ops for cpu and cuda

* removing memory manipulation as rs rollback is now supported in CPU

* removing the static probe which is not needed now

* correcting the format

* address review comments

* enabling test for all the backends, unsupported backends will fallback to CPU

* Apply suggestions from code review

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* choose different graph based on the result of fused_ssm_op is supported or not and also handled memory->n_rs_seq >1 case incase of op is not supported

* Support K > 1 in ssm_scan for all backends

* Fix CI Issues

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Gaurav Garg <gaugarg@nvidia.com>
2026-08-14 17:20:40 +03:00
Pascal c8e03ce812 mtmd/ggml: add ggml_build_forward_order (#26649)
* ggml: add ggml_build_forward_order

ggml_build_forward_expand marks the tensor and all its ancestors for
compute, so using it as a pure ordering hint (keeping q, k and v
together) defeats ggml_build_forward_select: the unselected branch is
forced to run with inputs that were never uploaded. In the mtmd audio
graph this makes GEN_WAV calls execute the GEN_CODE branch with a
stale inp_code0, hitting the get_rows bound assert on CPU.

Add ggml_build_forward_order, which inserts nodes without the compute
flag; the flag is restored when the branch is actually selected.
Switch the q/k/v hints in clip_graph::build_attn to it.

* nit: reduce comments (AGENTS.md)
2026-08-06 00:47:59 +02:00
da5b448622 ggml : set output of view src (#25729)
* llama-graph: set_outputs to t->view_src

* change set_output to GGML_ASSERT about views not being outputs

* sampler : avoid views in outputs

* cont : fix dist sampler

* cont : consistent logits handling

* ggml : set output of view src

* graph : simplify set_outputs()

* cont : cleanup

Co-authored-by: Gaurav Garg <gaugarg@nvidia.com>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Gaurav Garg <gaugarg@nvidia.com>
2026-07-28 16:23:24 +03:00
Aman Gupta 0dc74e332e DeepseekV4: Add fused hyper-connection ops (#25585)
* dsv4 hc-ops

* add missing files;

* add cparams

* update rpc version

* address review comments

* address review comments
2026-07-17 00:33:33 +08:00
fairydreamingandStanisław Szymczyk a7312ae94f ggml : add a set of functions for checking contiguity of inner tensor dimensions (#25650)
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
2026-07-14 14:37:52 +02:00
JusteLeoandGeorgi Gerganov 47a39665e7 ggml: uniformize im2col dst_type for all conv ops (#23660)
* ggml: uniformize im2col dst_type for all conv ops

* Update ggml/src/ggml.c

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* ggml : uniformize im2col casting logic across all conv ops

* fix : allow im2col_f16 to accept any kernel type

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2026-07-14 13:13:13 +03:00
fairydreamingandStanisław Szymczyk 00f5442cc4 ggml : add GGML_OP_LIGHTNING_INDEXER that implements DeepSeek V3.2/V4 lightning indexer (#24231)
* ggml : add GGML_OP_LIGHTNING_INDEXER that implements DeepSeek V3.2/V4 lightning indexer

* ggml : remove scale parameters from lightning indexer OP, add f16 mask parameter

* tests : add GGML_OP_LIGHTNING_INDEXER tests

* ggml : bump RPC version

* chore : check if lightning indexer input tensors are not transposed

* tests : count flops instead of bandwidth in lightning indexer test

* chore : add missing const

* chore : whitespace

* ggml : renamed variables in CPU lightning indexer implementation

* ggml : fix lightning indexer mask broadcasting

* tests : tests for lightning indexer mask broadcasting

* chore : whitespace

* llama : use GGML_OP_LIGHTNING_INDEXER in DeepSeek V3.2 and DeepSeek V4 models

---------

Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
2026-07-11 11:39:07 +02:00
fairydreamingandStanisław Szymczyk 68a521b591 ggml : add support for CPU f16->f16 GGML_OP_SET_ROWS (#25344)
* ggml : add support for CPU f16->f16 GGML_OP_SET_ROWS

* ggml : add missing type checks in f16 GGML_OP_SET_ROWS

* ggml : merge ggml_compute_forward_set_rows_f32() and ggml_compute_forward_set_rows_f16() into ggml_compute_forward_set_rows_impl()

* chore : replace assert() with GGML_ASSERT()

---------

Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
2026-07-08 11:46:28 +08:00
Pasha Khosravi bec4772f6a Add Q2_0 quantization: type definition and CPU backend (#24448) 2026-07-07 12:05:47 -07:00
3899b39ce2 CUDA: Fuse MMVQ post-scale for NVFP4 (#24481)
* CUDA: Fuse MMVQ for NVFP4 and BS 1

TODO:
1. Add tests to test-backend-ops (did verify correctness manually for
   one model)
2. Reorder bias/scale once PRs for NVFP4 are merged/landed

* Add dense MMVQ fusion as well

Perf numbers on B4500. Note qwen35 is FP8->Q8
+ ./scripts/compare-llama-bench.py -b master -c osimons/nvfp4_fuse_mmvq --tool llama-bench -i llama-bench.sqlite
| Model                    | Test         |   t/s master |   t/s osimons/nvfp4_fuse_mmvq |   Speedup |
|:-------------------------|:-------------|-------------:|------------------------------:|----------:|
| qwen35moe 35B.A3B NVFP4  | tg128@d32768 |       150.15 |                        156.29 |      1.04 |
| qwen35moe 35B.A3B Q4_K_M | tg128@d32768 |       157.91 |                        157.64 |      1.00 |

Perf numbers on DGX Spark
+ ./scripts/compare-llama-bench.py -b master -c osimons/nvfp4_fuse_mmvq --tool llama-bench -i llama-bench.sqlite
| Model                    | Test         |   t/s master |   t/s osimons/nvfp4_fuse_mmvq |   Speedup |
|:-------------------------|:-------------|-------------:|------------------------------:|----------:|
| qwen35moe 35B.A3B NVFP4  | tg128@d32768 |        58.31 |                         59.69 |      1.02 |
| qwen35moe 35B.A3B Q4_K_M | tg128@d32768 |        54.94 |                         54.79 |      1.00 |

* Add tests for the added fusion ops

* Cleanup test-backend-ops

* Cleanup ggml-cuda/mmvq

1. Unrestrict post-scale fusion
2. Rename names accordingly
3. Remove env variable to disable fusion

* Merge old mul_mat patterns into the lane-based approach

* Enable fusion for MoE in shared MMVQ

* Restrict scale_view_nodes, enroll MM + ADD into lane-matcher

* Refactor mmvq loads, still does not help non-nvfp4 kernels

* Restrict scale-fusion to NVFP4

This is necessary, as the prolog is quite heavy in GEMV for some
quants/model configs, leading to net perf regression.
We should really be looking to refactor this such that ratio of
prologue/hot-loop/epilogue is better on the hot-loop
front:

+ ./scripts/compare-llama-bench.py -b master -c c1b9381d327e063cc846b46b59708444b66dc4d8 --tool llama-bench -i llama-bench.sqlite
| CPU                         | Model                    | Test         |   t/s master |   t/s c1b9381d3 |   Speedup |
|:----------------------------|:-------------------------|:-------------|-------------:|----------------:|----------:|
| INTEL(R) XEON(R) GOLD 6542Y | gemma4 26B.A4B NVFP4     | tg128@d32768 |       151.70 |          154.32 |      1.02 |
| INTEL(R) XEON(R) GOLD 6542Y | gemma4 26B.A4B Q4_K_M    | tg128@d32768 |       187.95 |          185.73 |      0.99 |
| INTEL(R) XEON(R) GOLD 6542Y | gpt-oss 20B MXFP4 MoE    | tg128@d32768 |       304.62 |          300.69 |      0.99 |
| INTEL(R) XEON(R) GOLD 6542Y | qwen35moe 35B.A3B NVFP4  | tg128@d32768 |       193.72 |          211.99 |      1.09 |
| INTEL(R) XEON(R) GOLD 6542Y | qwen35moe 35B.A3B Q4_K_M | tg128@d32768 |       217.76 |          218.15 |      1.00

* Reorder scale & bias-add to adhere to #24331

* Restrict lane scale to NVFP4

Don't need to test unfused combinations

* Cleanup

* Merge single-lane mm-fusion helpers

* Refactor and clean-up host-side fusion logic

* Move gate_bias and scale into the same active-thread guard

Latest perf numbers:
B6000

build: 5b7d9f272 (9578)
+ ./scripts/compare-llama-bench.py -b master -c osimons/nvfp4_fuse_mmvq --tool llama-bench -i llama-bench.sqlite
| CPU                         | Model                    | Test         |   t/s master |   t/s osimons/nvfp4_fuse_mmvq |   Speedup |
|:----------------------------|:-------------------------|:-------------|-------------:|------------------------------:|----------:|
| INTEL(R) XEON(R) GOLD 6542Y | gemma4 26B.A4B NVFP4     | tg128@d32768 |       151.79 |                        154.10 |      1.02 |
| INTEL(R) XEON(R) GOLD 6542Y | gemma4 26B.A4B Q4_K_M    | tg128@d32768 |       187.90 |                        187.27 |      1.00 |
| INTEL(R) XEON(R) GOLD 6542Y | gpt-oss 20B MXFP4 MoE    | tg128@d32768 |       303.77 |                        306.56 |      1.01 |
| INTEL(R) XEON(R) GOLD 6542Y | qwen35moe 35B.A3B NVFP4  | tg128@d32768 |       193.41 |                        207.99 |      1.08 |
| INTEL(R) XEON(R) GOLD 6542Y | qwen35moe 35B.A3B Q4_K_M | tg128@d32768 |       217.60 |                        218.58 |      1.00 |

DGX Spark

build: 5b7d9f272 (9578)
+ ./scripts/compare-llama-bench.py -b master -c osimons/nvfp4_fuse_mmvq --tool llama-bench -i llama-bench.sqlite
| CPU   | Model                    | Test         |   t/s master |   t/s osimons/nvfp4_fuse_mmvq |   Speedup |
|:------|:-------------------------|:-------------|-------------:|------------------------------:|----------:|
| CPU   | gemma4 26B.A4B NVFP4     | tg128@d32768 |        34.61 |                         34.84 |      1.01 |
| CPU   | gemma4 26B.A4B Q4_K_M    | tg128@d32768 |        46.95 |                         46.90 |      1.00 |
| CPU   | gpt-oss 20B MXFP4 MoE    | tg128@d32768 |        64.84 |                         64.62 |      1.00 |
| CPU   | qwen35moe 35B.A3B NVFP4  | tg128@d32768 |        59.63 |                         60.72 |      1.02 |
| CPU   | qwen35moe 35B.A3B Q4_K_M | tg128@d32768 |        56.53 |                         56.55 |      1.00 |

PPL values for 5 chunks:
this PR

model                                                                                                       mode             ppl         uncertainty  log
/mnt/share/gguf/unsloth/Qwen3.6-35B-A3B-GGUF/Qwen3.6-35B-A3B-UD-Q4_K_M.gguf                                 fusion_enabled   5.2892      0.35389      ppl-value-checks/Qwen3.6-35B-A3B-UD-Q4_K_M.fusion_enabled.log
/mnt/share/gguf/unsloth/Qwen3.6-35B-A3B-GGUF/Qwen3.6-35B-A3B-UD-Q4_K_M.gguf                                 fusion_disabled  5.2742      0.35215      ppl-value-checks/Qwen3.6-35B-A3B-UD-Q4_K_M.fusion_disabled.log
/mnt/share/gguf/nvidia/Qwen3.6-35B-A3B-2.06GB-per-token-CT/Qwen3.6-35B-A3B-2.06GB-per-token-CT_fp8_q8.gguf  fusion_enabled   5.4487      0.36866      ppl-value-checks/Qwen3.6-35B-A3B-2.06GB-per-token-CT_fp8_q8.fusion_enabled.log
/mnt/share/gguf/nvidia/Qwen3.6-35B-A3B-2.06GB-per-token-CT/Qwen3.6-35B-A3B-2.06GB-per-token-CT_fp8_q8.gguf  fusion_disabled  5.4403      0.36782      ppl-value-checks/Qwen3.6-35B-A3B-2.06GB-per-token-CT_fp8_q8.fusion_disabled.log
/mnt/share/gguf/nvidia/Gemma-4-26B-A4B-NVFP4/Gemma-4-26B-A4B-NVFP4_fp8_q8.gguf                              fusion_enabled   17342.4348  3703.13932   ppl-value-checks/Gemma-4-26B-A4B-NVFP4_fp8_q8.fusion_enabled.log
/mnt/share/gguf/nvidia/Gemma-4-26B-A4B-NVFP4/Gemma-4-26B-A4B-NVFP4_fp8_q8.gguf                              fusion_disabled  18627.0624  3998.42475   ppl-value-checks/Gemma-4-26B-A4B-NVFP4_fp8_q8.fusion_disabled.log
/mnt/share/gguf/ggml-org/gpt-oss-20b-GGUF/gpt-oss-20b-mxfp4.gguf                                            fusion_enabled   363.8913    33.14007     ppl-value-checks/gpt-oss-20b-mxfp4.fusion_enabled.log
/mnt/share/gguf/ggml-org/gpt-oss-20b-GGUF/gpt-oss-20b-mxfp4.gguf                                            fusion_disabled  363.8913    33.14007     ppl-value-checks/gpt-oss-20b-mxfp4.fusion_disabled.log
/mnt/share/gguf/unsloth/gemma-4-26B-A4B-it-GGUF/gemma-4-26B-A4B-it-UD-Q4_K_XL.gguf                          fusion_enabled   17330.3926  3716.70472   ppl-value-checks/gemma-4-26B-A4B-it-UD-Q4_K_XL.fusion_enabled.log
/mnt/share/gguf/unsloth/gemma-4-26B-A4B-it-GGUF/gemma-4-26B-A4B-it-UD-Q4_K_XL.gguf                          fusion_disabled  17933.9524  3883.17066   ppl-value-checks/gemma-4-26B-A4B-it-UD-Q4_K_XL.fusion_disabled.log

master:
summary: ppl-value-checks/summary.tsv
model                                                                                                       mode             ppl         uncertainty  log
/mnt/share/gguf/unsloth/Qwen3.6-35B-A3B-GGUF/Qwen3.6-35B-A3B-UD-Q4_K_M.gguf                                 fusion_enabled   5.2892      0.35389      ppl-value-checks/Qwen3.6-35B-A3B-UD-Q4_K_M.fusion_enabled.log
/mnt/share/gguf/unsloth/Qwen3.6-35B-A3B-GGUF/Qwen3.6-35B-A3B-UD-Q4_K_M.gguf                                 fusion_disabled  5.2742      0.35215      ppl-value-checks/Qwen3.6-35B-A3B-UD-Q4_K_M.fusion_disabled.log
/mnt/share/gguf/nvidia/Qwen3.6-35B-A3B-2.06GB-per-token-CT/Qwen3.6-35B-A3B-2.06GB-per-token-CT_fp8_q8.gguf  fusion_enabled   5.4487      0.36866      ppl-value-checks/Qwen3.6-35B-A3B-2.06GB-per-token-CT_fp8_q8.fusion_enabled.log
/mnt/share/gguf/nvidia/Qwen3.6-35B-A3B-2.06GB-per-token-CT/Qwen3.6-35B-A3B-2.06GB-per-token-CT_fp8_q8.gguf  fusion_disabled  5.4403      0.36782      ppl-value-checks/Qwen3.6-35B-A3B-2.06GB-per-token-CT_fp8_q8.fusion_disabled.log
/mnt/share/gguf/nvidia/Gemma-4-26B-A4B-NVFP4/Gemma-4-26B-A4B-NVFP4_fp8_q8.gguf                              fusion_enabled   17342.4348  3703.13932   ppl-value-checks/Gemma-4-26B-A4B-NVFP4_fp8_q8.fusion_enabled.log
/mnt/share/gguf/nvidia/Gemma-4-26B-A4B-NVFP4/Gemma-4-26B-A4B-NVFP4_fp8_q8.gguf                              fusion_disabled  18627.0624  3998.42475   ppl-value-checks/Gemma-4-26B-A4B-NVFP4_fp8_q8.fusion_disabled.log
/mnt/share/gguf/ggml-org/gpt-oss-20b-GGUF/gpt-oss-20b-mxfp4.gguf                                            fusion_enabled   363.8913    33.14007     ppl-value-checks/gpt-oss-20b-mxfp4.fusion_enabled.log
/mnt/share/gguf/ggml-org/gpt-oss-20b-GGUF/gpt-oss-20b-mxfp4.gguf                                            fusion_disabled  363.8913    33.14007     ppl-value-checks/gpt-oss-20b-mxfp4.fusion_disabled.log
/mnt/share/gguf/unsloth/gemma-4-26B-A4B-it-GGUF/gemma-4-26B-A4B-it-UD-Q4_K_XL.gguf                          fusion_enabled   17330.3926  3716.70472   ppl-value-checks/gemma-4-26B-A4B-it-UD-Q4_K_XL.fusion_enabled.log
/mnt/share/gguf/unsloth/gemma-4-26B-A4B-it-GGUF/gemma-4-26B-A4B-it-UD-Q4_K_XL.gguf                          fusion_disabled  17933.9524  3883.17066   ppl-value-checks/gemma-4-26B-A4B-it-UD-Q4_K_XL.fusion_disabled.log

* Allow views to weights in ggml_can_fuse_subgraph

* Remove gate_first from test_mul_mat_vec_fusion

* Ditch lane-parsing approach in favor of hard-coded patterns

* Apply suggestions from code review

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Rename ggml_is_constant_view_src to ggml_is_constant

* Finish renaming of 0905129e9d12e2bc6f16d6d3cc4e6b40606fc893

* Readd descriptive prints for fusion debugging

* Add weight-buffer pre-allocation to `test_case`

This is required so we correctly test fusion of NVFP4.

* Update ggml/src/ggml.c

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Add 2nd context for weights as suggested by @JohannesGaessler

This reflects more natural use of ggml compared to artifically
pre-allocating weights into the same context

* Exclude fused tests from gradient mode

I'm unsure of the current state, but naively every fusion pattern
should require its own backpropagation implementation. I don't see these
implemented for the CUDA backend, so we can disable tests to avoid
triggering GGML_ASSERT for

    ggml_tensor * build_graph(ggml_context * ctx) override {
        GGML_ASSERT(!use_weight_context());
        return build_graph(ctx, nullptr);
    }

* Apply suggestions from code review

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2026-07-07 17:12:19 +02:00
An Long 1a7c25bfdb ggml : make ggml_time_init idempotent (#24422) 2026-07-07 10:29:17 +03:00
Xuan-Son Nguyen e475fa2b5f mtmd, arg: fix utf8 handling on windows (#24779)
* mtmd, arg: fix utf8 handling on windows

* also fix ggml_fopen

* fix build fail

* also fix CLI
2026-06-19 22:28:38 +02:00
Gaurav Garg e95dae18d6 Remove padding and multiple D2D copies for MTP (#24086)
* Make ggml_gated_delta_net take only the initial recurrent state (D, 1, n_seqs) and passes the snapshot count K as an op parameter instead of inferring it from state->ne[1].

Remove the padding hack and copy all emitted snapshots into the recurrent cache with a single strided ggml_cpy

* Make GDN changes in all backends. Address review comments.

* Fix CI build errors
2026-06-10 23:21:16 +05:30
Pascal 26021699bc ggml : add GGML_OP_COL2IM_1D (#24206)
* cpu: add GGML_OP_COL2IM_1D

Add the overlap-add (scatter-add) step of a 1D transposed convolution.
A ConvTranspose1d factorizes as a GEMM followed by col2im: a weight
pre-permuted to [IC, K*OC] is contracted against the [IC, T_in] input
with mul_mat to produce a column matrix [K*OC, T_in], and col2im_1d
scatters those columns back into the [T_out, OC] signal, with
T_out = (T_in - 1)*s0 + K - 2*p0.

Keeping the contraction as a plain mul_mat leaves the heavy work on the
optimized (and quantizable) matmul kernels, so col2im_1d only does the
cheap overlap-add.

CPU uses a gather formulation parallelized over output channels,
supporting F32, F16 and BF16 with an F32 accumulator.

* tests: add backend coverage for GGML_OP_COL2IM_1D

Add test_col2im_1d next to the conv_transpose_1d cases, covering F32,
F16 and BF16 across eight geometries: the canonical kernel = 2*stride
DAC upsampling shape, overlap, no overlap, cropping (p0 = 1 and
p0 = stride/2), kernel < stride with zeroed gaps, kernel not a
multiple of stride, and a single column unfold.

Perf mode gets three real vocoder stage shapes reporting memory
bandwidth. max_nmse_err relaxes to 5e-4 for F16 and BF16.

* cpu: harden GGML_OP_COL2IM_1D

ggml_col2im_1d validates s0, oc, p0 and input contiguity at graph
build time, before the oc division, protecting every backend at once.
The kernel asserts the contiguity its flat indexing assumes and its
doc states the full output length including the crop term.

The kernel parallelizes over the time axis: the split stays balanced
down to OC = 1, where the previous channel split was single threaded.
Values are bit identical on the three real vocoder chains, two out of
three improve.

* tests: extend the GGML_OP_COL2IM_1D grid

The eval grid grows to eleven geometries: OC = 1 (mono output stage),
K = 1 with stride > 1 (sparse scatter, every gap position zeroed) and
a crop down to T_out = 2 where all the gather bounds act at once.

* tests: add col2im_1d equivalence test

tests/test-col2im-1d.cpp proves mul_mat + col2im_1d matches the
native ggml_conv_transpose_1d on the CPU backend, F32 bit exact, F16
and BF16 through casts of the column matrix. test-backend-ops cannot
cover this for a CPU only op since the CPU backend is its own
reference there.

* rpc: bump protocol patch version for GGML_OP_COL2IM_1D

GGML_OP_COUNT goes from 96 to 97 with the new op, which trips the
static_assert in ggml-rpc.h. Bump RPC_PROTO_PATCH_VERSION since the
op is appended and no existing op code shifts.
2026-06-09 12:01:37 +03:00
1f0aa2a696 model : support for DeepseekV32ForCausalLM with generic DeepSeek Sparse Attention (DSA) implementation (#23346)
* llama : support DeepSeek V3.2 model family (with DSA lightning indexer)

* convert : handle DeepseekV32ForCausalLM architecture

* ggml : support for f16 GGML_OP_FILL

* memory : separate hparams argument in llama_kv_cache constructor

* memory : add llama_kv_cache_dsa memory (KV cache + lightning indexer cache)

* llama : support for LLM_ARCH_DEEPSEEK32

* model : llama_model_deepseek32 implementation

* model : merge two scale operations into one in DSA lightning indexer implementation

* chore : remove unused code

* model : support NVFP4 in DeepSeek V3.2

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* memory : refactoring TODO

Co-authored-by: ggerganov <ggerganov@users.noreply.github.com>

---------

Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: ggerganov <ggerganov@users.noreply.github.com>
2026-05-29 10:15:17 +02:00
Aman GuptaandGeorgi Gerganov 255582687b llama + spec: MTP Support (#22673)
* spec: support MTP

* fix batch size

* rename files

* cont : simplify (#7)

* MTP: clean-up (#9)

* MTP: clean-up

* review: use llama_context_type instead of llama_graph_type

* review: remove llama_model_has_mtp

* review: fix convert issues

* convert: fix pycheck

* review: formatting

* use `mtp-` for identifying mtp models

* convert: fix mtp conversion

* mtp -> draft-mtp

* remove unused llama_arch

* add need_embd in speculative

* llama: allow partial seq_rm for GDN models for speculative decoding

Currently speculative checkpoint needs to restart from a checkpoint
after some draft tokens are not accepted, this leads to some wastage in
running the target again. This PR adds the ability to rollback upto
`draft_max` by storing the GDN intermediates.

* fix pending state

* vulkan: add GDN partial rollback

* meta: extend check to axis 1

* metal: add GDN partial rollback

Extend the gated delta net kernel to store intermediate states for
partial rollback support on the Metal backend.

- Add K (snapshot slot count) as a function constant
- Read input state from slot 0 of the 3D state tensor
- Write intermediate states to different slots during token loop
- For K=1, maintain backward-compatible single-slot behavior

Ref: https://github.com/ggml-org/llama.cpp/commit/8c05923630110223669f069af2000e9cf10c02bc

Assisted-by: llama.cpp:local pi

* delta_net_base: use ggml_pad instead of new_tensor

* review: add need_rs_seq

* review: rename part_bounded to n_rs

* review: deslop comments

* review: rename, add asserts

* server : adjust checkpoint logic (#11)

* server : adjust checkpoint logic

* cont : rm asserts

* server-context: fix early exit

* spec : fix compatibility with n-gram and add TODOs (#13)

* metal : cleanup

* llama : fix faulty bitwise check in recurrent memory

* server : disable RS-based MTP in combination with other spec types

* spec : add TODOs

* cont : fix comment

* cont : update comment

* common : fix logic for ngram + mtp compat

* llama-memory: enable checkpointing with partial rollback

* cont: add test-case for loading into a dirty ctx

* llama-memory-recurrent: clear rs_idx in clear

* download: fix mtp path

* llama-arch: fix enorm op

* docs: update docs

* conversion: fix type annotations

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2026-05-16 20:06:23 +08:00
Ismail a817a22bc6 ggml : implement fast walsh-hadamard transform for kv rotation (#21352) (#22631) 2026-05-05 10:05:05 +08:00
Georgi Gerganov e8ec7ab058 ggml : try fix win32 build (whisper/0) 2026-05-02 07:22:35 +03:00
Georgi Gerganov e583f3b4f5 ggml : minor coding style (#22308) 2026-04-24 11:02:00 +03:00
Aman Gupta 3f7c29d318 ggml: add graph_reused (#21764)
* ggml: add graph_reused

* use versioning instead of reuse flag

* increment version with atomic

* use top bits for split numbering

* add assert

* move counter to ggml.c

* set uid in split_graph only

* fix windows

* address further review comments

* get next_uid rather than doing bit manipulation

* rename + add comment about uid
2026-04-16 17:21:28 +08:00
Pasha KhosraviandSigbjørn Skjæret 2e1f0a889e ggml: add Q1_0 1-bit quantization support (CPU) (#21273)
* ggml: add Q1_0 and Q1_0_g128 1-bit quantization support (CPU)

* add generic fallback for x86

* remove Q1_0 (group size 32)

* rename Q1_0_g128 => Q1_0

* fix Q1_0 LlamaFileType Enum

* Fix trailing spaces; add generic fallback for othre backends

* Apply suggestions from code review

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* fix /r/n spacing + arch-fallback

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
2026-04-06 20:55:21 +02:00
a970515bdb mtmd: Add DeepSeekOCR Support (#17400)
* mtmd: llama.cpp DeepSeekOCR support
init commit

* loading sam tensors

* mtmd: fix vision model processing

* deepseek-ocr clip-vit model impl

* mtmd: add DeepSeek-OCR LM support with standard attention

* mtmd: successfully runs DeepSeek-OCR LM in llama-cli

* mtmd: Fix RoPE type for DeepSeek-OCR LM.

* loading LM
testing Vision model loading

* sam warmup working

* sam erroneous return corrected

* clip-vit:  corrected cls_embd concat

* clip-vit: model convert  qkv_proj split

* corrected combining of image encoders' results

* fix: update callback for ffn_moe_weighted and add callback for attn_out in deepseek2 model

* concat image_newline and image_seperator tokens

* visual_model warmup (technically) works

* window partitioning using standard ggml ops

* sam implementation without using CPU only ops

* clip: fixed warnings

* Merge branch 'sf/deepseek-ocr' of github.com:sfallah/llama.cpp into sf/deepseek-ocr

* mtmd: fix get_rel_pos

* mtmd: fixed the wrong scaler for get_rel_pos

* image encoding technically works but the output can't be checked singe image decoding fails

* mtmd: minor changed

* mtmd: add native resolution support

* - image encoding debugged
- issues fixed mainly related wrong config like n_patches etc.
- configs need to be corrected in the converter

* mtmd: correct token order

* - dynamic resizing
- changes are concerning PR https://github.com/sfallah/llama.cpp/pull/4

* mtmd: quick fix token order

* mtmd: fix danling pointer

* mtmd: SAM numerically works

* mtmd: debug CLIP-L (vit_pre_ln)

* mtmd: debug CLIP-L & first working DeepSeek-OCR model

* mtmd : add --dsocr-mode CLI argument for DeepSeek-OCR resolution control & all native resolution modes work

* mtmd: simplify SAM patch embedding

* mtmd: adapt Pillow image resizing function

* mtmd:  simplify DeepSeek-OCR dynamic resolution preprocessing

* mtmd: remove --dsocr-mode argument

* mtmd: refactor code & remove unused helper functions

* mtmd: fix tensor names for image newlines and view separator

* clean up

* reverting automatically removed spaces

* reverting automatically removed spaces

* mtmd: fixed bad ocr check in Deepseek2 (LM)

* mtmd: support combined QKV projection in buid_vit

* using common build_attn in sam

* corrected code-branch when flash-attn disabled
enabling usage of --flash-attn option

* mtmd: minor fix

* minor formatting and style

* fixed flake8 lint issues

* minor editorconfig-check fixes

* minor editorconfig-check fixes

* mtmd: simplify get_rel_pos

* mtmd: make sam hparams configurable

* mtmd: add detailed comments for resize_bicubic_pillow

* mtmd: fixed wrong input setting

* mtmd: convert model in FP16

* mtmd: minor fix

* mtmd: remove tweak to llama-mtmd-cli & deepseek-ocr template

* fix: test-1.jpg ORC issue with small (640) resolution
setting min-resolution base (1024) max large (1280) for dynamic-resolution

* minor: editconfig-check fix

* merge with changes from https://github.com/ggml-org/llama.cpp/pull/17909
added new opt to tests.sh to disable flash-attn

* minor: editconfig-check fix

* testing deepseek-ocr
quick and dirty test script comparing results of Qwen2.5-VL vs DeepSeek-OCR

* quick and (potential) dirty merge with https://github.com/ggml-org/llama.cpp/pull/17909

* refactoring, one single builder function and static helpers

* added deepseek-ocr test to tests.sh

* minor formatting fixes

* check with fixed expected resutls

* minor formatting

* editorconfig-check fix

* merge with changes from https://github.com/ggml-org/llama.cpp/pull/18042

* minor
- added GLM-4.6V to big tests
- added missing deps for python test

* convert: minor fix

* mtmd: format code

* convert: quick fix

* convert: quick fix

* minor python formatting

* fixed merge build issue

* merge resolved
- fixed issues in convert
- tested several deepseek models

* minor fix

* minor

* Update convert_hf_to_gguf.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* - removed clip_is_deepseekocr
- removed redundant RESIZE_ALGO_BICUBIC_PILLOW resize-algo
- simplified image-preprocessing
- removed/simplified debug functions

* - cleaning commented out code

* fixing instabilities issues reintroducing resize_bicubic_pillow

* - use f16 model for deepseek-ocr test
- ignore llama-arch test for deepseek-ocr

* rename fc_w --> mm_fc_w

* add links to OCR discussion

* cleaner loading code

* add missing .weight to some tensors

* add default jinja template (to be used by server)

* move test model to ggml-org

* rolling back upscale change

* Update convert_hf_to_gguf.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

---------

Co-authored-by: bluebread <hotbread70127@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
2026-03-25 19:57:40 +01:00
Georgi Gerganov 79187f2fb8 ggml : restore ggml_type_sizef() to aboid major version bump (ggml/1441) 2026-03-18 15:17:28 +02:00
Richard DavisonandSigbjørn Skjæret 5eae9cb1d9 ggml : add NVFP4 quantization type support (#19769)
* WIP: add NVFP4 quantization support

* tests

* improve NVFP4 dot product implementation performance and fix bad super call

* typo

* Use nvfp4 kvalues

* vulkan : fix NVFP4 shader compilation by including kvalues_mxfp4 lookup table

* vulcal and perf fixes

* wip

* Fix metal

* fix vulcan

* Rename threshold & fix wrong scale

* Fix MOE

* Shelf backend implementations (CUDA, Metal, Vulkan, arch-specific SIMD)

Remove NVFP4 support from GPU backends and architecture-specific
optimized dot products. These should be added in separate PRs so
backend specialists can review them independently.

Reverted files:
- ggml-cuda: common.cuh, convert.cu, mmq.cu/cuh, mmvq.cu, vecdotq.cuh,
  quantize.cu/cuh, mma.cuh, ggml-cuda.cu, fattn-tile.cuh
- ggml-metal: ggml-metal.metal, ggml-metal-device.cpp, ggml-metal-impl.h,
  ggml-metal-ops.cpp
- ggml-vulkan: ggml-vulkan.cpp, all vulkan-shaders/*
- ggml-cpu arch: arm/quants.c, x86/quants.c, powerpc/quants.c, s390/quants.c

Core NVFP4 support (type definition, CPU fallback dot product,
quantization, dequantization, conversion) is retained.

* Fix arch-fallback.h: add NVFP4 generic fallback for all platforms

After shelving backend-specific SIMD implementations, the generic
CPU dot product needs to be aliased on ARM, x86, PowerPC, and s390
platforms that previously relied on arch-specific versions.

* quantize: add NVFP4 as a quantization type option

* Fix ggml_fp32_to_ue4m3: handle subnormal values

Previously, values with ue4m3_exp <= 0 were clamped to 0, causing
all small scales to underflow. This made NVFP4 quantization via
llama-quantize produce garbage (PPL = 5.8M) since typical transformer
weights have amax/6.0 in the range 0.001-0.01, which falls in the
UE4M3 subnormal range.

Now subnormals are properly encoded as man * 2^-9 (exp=0, man=1..7),
matching the decode path in ggml_ue4m3_to_fp32.

Result: NVFP4 requantization now produces PPL = 15.25 (vs F16 = 14.33),
comparable to Q4_1 (PPL = 15.81) at slightly lower BPW (4.70 vs 5.15).

* Restore ARM NEON NVFP4 dot product implementation

Restores the optimized ggml_vec_dot_nvfp4_q8_0 for ARM NEON using
vqtbl1q_s8 lookup and ggml_vdotq_s32 dot products.

tg128 performance: 4.37 t/s (generic) -> 13.66 t/s (NEON) = 3.1x speedup

* Optimize ARM NEON NVFP4 dot product: LUT + vpaddq + vfmaq

- Add ue4m3_scale_lut[128] to ggml-common.h replacing branch-heavy
  ggml_ue4m3_to_fp32() in the hot loop
- Use vpaddq_s32 for pairwise int32 reduction instead of vaddvq_s32
- Accumulate with vfmaq_f32 into float32x4_t vector accumulators

tg128: 8.1 -> 31.0 t/s (3.8x speedup, 77% of Q4_1 speed)

* ARM NEON NVFP4: rearrange q8 to match nibble layout

Alternative approach: rearrange q8 data to match the NVFP4 lo/hi
nibble layout instead of rearranging the looked-up NVFP4 values.
Eliminates vcombine_s8(vget_low, vget_low) shuffles.

Performance is equivalent (~18.5 t/s) - the bottleneck is the 2x
block overhead from QK=16 vs QK=32, not the shuffle instructions.

* CPU only backend 64 super-block layout

* cleanup

* Remove unused LUT

* int

* exclude NVFP4 from unsupported ops in metal build

* remove quantization for now

* store scales as native UE4M3, preserve original model bits when possible

* Update convert_hf_to_gguf.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* correct comment

* format

* reduce duplication and cleanup

* Address comments

* move detection to prepare_tensors

* Use math instead of const

* Move

* fix comment

* Shelf quantize tests

* Rebase and move check

* cleanup

* lint

* Update gguf-py/gguf/scripts/gguf_convert_endian.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Use fallback quant config

* Simplify

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* organize

* Refactor

* Update convert_hf_to_gguf.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Update convert_hf_to_gguf.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Update convert_hf_to_gguf.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* add quantize_nvfp4 (required for test_quants.py)

* add quantize_nvfp4 (required for test_quants.py)

* add quantize_nvfp4 (required for test_quants.py)

* fix return type

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
2026-03-11 21:02:54 +01:00
Aman GuptaandGeorgi Gerganov c5a778891b ggml: add GATED_DELTA_NET op (#19504)
* ggml: add GATED_DELTA_NET op

* remove the transpose

* add KDA

* add qwen35 dense

* llama : check for fused gated delta net backend support

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2026-03-07 15:41:10 +08:00
Johannes Gäßler 7f5ee54968 ggml: fix ggml_is_contiguous_n for ne == 1 (#20092) 2026-03-04 12:04:31 +01:00
Georgi GerganovandSigbjørn Skjæret 418dea39ce ggml/gguf : prevent integer overflows (#19856)
* gguf : prevent integer overflow for ggml_context mem size

* ggml : fix int overflows in ggml_new_object()

* gguf : prevent string exhaustion

* gguf : prevent array elements exhaustion

* ggml : fix negative tensor type oob

* py : assert that alignment is non-zero power of 2

* ggml : check int overflow in ggml_new_tensor_impl and ggml_new_object

* gguf-py : error on duplicate keys when reading

* py : restore tensor_fields

* enforce proper alignment in add_custom_alignment

* gguf : better name

* gguf : fix ctx size for no_alloc == true

* gguf : minor print fix

* ggml : print values when overflow

* ggml : remove deprecated ggml_type_sizef()

* ggml : relax ggml_type asserts to debug-only

* gguf : add mem_size overflow test

* gguf : add file size check for arrays

* ggml : relax asseerts for ggml_get_type_traits()

* flake8 fix

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
2026-02-24 20:17:11 +02:00
Judd d23a55997d ggml : make ggml_is_view as API (#19539)
* make `ggml_is_view` as API

* introduce `ggml_aux_is_view` as inline version for internal use.

* change `ggml_aux_is_view` to  `ggml_impl_is_view`
2026-02-16 17:43:34 +02:00
Georgi Gerganov 914dde72ba ggml : unary ops support non-cont src0 + metal F16 unary ops (#19511)
* ggml : unary ops support non-cont src0

* metal : support F16 unary ops + fix ELU
2026-02-11 18:58:43 +02:00
George e9a859db3c ggml: added cleanups in ggml_quantize_free (#19278)
Add missing cleanup calls for IQ2_S, IQ1_M quantization types and IQ3XS with 512 blocks during quantization cleanup.
2026-02-03 08:43:39 +02:00
Christian Kastner 7a4ca3cbd9 docs : Minor cleanups (#19252)
* Update old URLs to github.com/ggml-org/

* Bump copyrights
2026-02-02 08:38:55 +02:00
Georgi Gerganov 365a3e8c31 ggml : add ggml_build_forward_select (#18550)
* ggml : add ggml_build_forward_select

* cuda : adapt CUDA graph compat to new feature

* vulkan : update logic to handle command buffer closing

* ggml : check compute for fusion

* ggml : add comment
2026-01-19 20:03:19 +02:00
Thore KoritziusandGeorgi Gerganov 388ce82241 ggml : extend ggml_pool_1d + metal (#16429)
* chore: resolve conflicts

* feat: ggml metal impl

* fix: ggml_metal_kargs_pool_1d struct

* fix: require contiguous input

* chore: test pool_1d

* chore: limit pool1d test cases to p0=0 and s0=k0 to conform with asserts

* chore: add p0 and s0 to testing

* fix: allow padding for cpu and metal

* Update ggml/src/ggml-metal/ggml-metal.metal

* fix: correct single-threaded loop

* ggml : cleanup

* tests : add ne[1] != 1 tests

* fix: ne[1] handling in np

* cont : fixes

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2026-01-16 16:59:56 +02:00
Adrien Gallouët e75ee11024 ggml : fix avx512bf16 build (#18623)
- include `immintrin.h` when required
- remove unused m512bh

Signed-off-by: Adrien Gallouët <angt@huggingface.co>
2026-01-06 08:54:10 +02:00
Johannes Gäßler b1f3a6e5db llama: automatically set parameters not set by the user in such a way that maximizes GPU utilization (#16653)
* llama: automatically fit args to free memory

llama-fit-params tool

* fix CI

* hints for bug reports, ensure no reallocation

* fix segfault with Vulkan

* add llama-fit-params to CI

* fix CI

* fix CI

* fix CI

* minor adjustments

* fix assignment of 1 dense layer

* fix logger not being reset on model load failure

* remove --n-gpu-layer hint on model load failure

* fix llama-fit-params verbosity

* fix edge case

* fix typo [no ci]
2025-12-15 09:24:59 +01:00
Georgi Gerganov 4dff236a52 ggml : remove GGML_KQ_MASK_PAD constant (#17910)
* ggml : remove GGML_KQ_MASK_PAD constant

* cont : remove comment
2025-12-10 20:53:16 +02:00
Gabe Goodhart 02e409a5be ggml : Provide macos-specific backtrace printing to avoid terminal death (#17869)
* fix: Provide macos-specific backtrace printing to avoid terminal death

Branch: MacOSSafeBacktrace

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Add GGML_BACKTRACE_LLDB env var to enable using lldb for backtrace

Branch: MacOSSafeBacktrace

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
2025-12-09 18:29:07 +02:00
09c7c50e64 ggml : add circular tiling support to pad, for Vulkan, CUDA, and CPU (used for making seamless textures) (#16985)
* Feat: Added vulkan circular tiling support

* Feat: Added cpu circular

* Feat: Added cuda kernels

* Added tests

* Added tests

* Removed non-pad operations

* Removed unneded changes

* removed backend non pad tests

* Update test-backend-ops.cpp

* Fixed comment on pad test

* removed trailing whitespace

* Removed unneded test in test-backend-ops

* Removed removed test from calls

* Update ggml/src/ggml-vulkan/vulkan-shaders/pad.comp

Co-authored-by: Ruben Ortlam <picard12@live.de>

* Fixed alignment

* Formatting

Co-authored-by: Aman Gupta <amangupta052@gmail.com>

* Format pad

* Format

* Clang format

* format

* format

* don't change so much stuff

* clang format and update to bool

* fix duplicates

* don't need to fix the padding

* make circular bool

* duplicate again

* rename vulkan to wrap around

* Don't need indent

* moved to const expr

* removed unneded extra line break

* More readable method calls

* Minor wording changes

* Added final newline

* Update ggml/include/ggml.h

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml/include/ggml.h

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Added circular pad ext tests

* Gate non circular pad devices

* Cleaned gating of non-circular pad devices

---------

Co-authored-by: Phylliida <phylliidadev@gmail.com>
Co-authored-by: Ruben Ortlam <picard12@live.de>
Co-authored-by: Aman Gupta <amangupta052@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2025-12-06 15:07:02 +01:00
Tarek Dakhran 2ba719519d model: LFM2-VL fixes (#17577)
* Adjust to pytorch

* Add antialiasing upscale

* Increase number of patches to 1024

* Handle default marker insertion for LFM2

* Switch to flag

* Reformat

* Cuda implementation of antialias kernel

* Change placement in ops.cpp

* consistent float literals

* Pad only for LFM2

* Address PR feedback

* Rollback default marker placement changes

* Fallback to CPU implementation for antialias implementation of upscale
2025-11-30 21:57:31 +01:00
Georgi Gerganov 583cb83416 ggml : add ggml_top_k (#17365)
* ggml : add ggml_top_k

* cont : add ggml_argsort_top_k

* metal : add top_k support

* ggml : cleanup

* tests : add virtual err() function for test_case

* ggml : add comments
2025-11-25 15:31:43 +02:00
389ac78b26 ggml : add ops SOFTPLUS, EXPM1, TRI, SOLVE_TRI, CUMSUM (#17063)
* Add ops needed for new hybrid models: SOFTPLUS, EXPM1, TRI, SOLVE_TRI, CUMSUM

* Update ggml/include/ggml.h

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update tests/test-backend-ops.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Code review

* Whitespace

* Update tests/test-backend-ops.cpp

Co-authored-by: Diego Devesa <slarengh@gmail.com>

* This is actually sigmoid, duh.

* Add CONST, remove TRI_KEEP, other changes from review

* Update tests/test-backend-ops.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml/src/ggml.c

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml/src/ggml.c

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml/src/ggml-cuda/unary.cu

Co-authored-by: Aman Gupta <amangupta052@gmail.com>

* Remove extra script

* Update ggml/src/ggml.c

Co-authored-by: Diego Devesa <slarengh@gmail.com>

* Update tests/test-backend-ops.cpp

Co-authored-by: Diego Devesa <slarengh@gmail.com>

* moving changes from laptop [no ci]

* pre-rebase

* Update tests/test-backend-ops.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Update tests/test-backend-ops.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Refactor tests

* ggml : cleanup

* cont : fix ggml_fill srcs

* tests : add note

* ggml : add ggml_fill_inplace

* ggml : add asserts

* ggml : fix ggml_fill constant cast

* cont : ggml_tri minor

* Use TENSOR_LOCALS

* Fix regression from #14596, regenerate

* Don't make commits at night...

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Diego Devesa <slarengh@gmail.com>
Co-authored-by: Aman Gupta <amangupta052@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
2025-11-13 20:54:47 +02:00
Aman Gupta 4926419c4d ggml: add ggml_can_fuse_subgraph (#16662)
* ggml: add ggml_can_fuse_subgraph

* ggml-cuda: use ggml_can_fuse_subgraph for topk-moe

* format

* 1. remove inputs from signature as they are transient nodes
2. add check for views: view_src should be part of the subgraph

* - combine check into one loop
- check all view_src parents
- other minor review comments

* remove redudant if test

* - rename and other minor review comments

* add assert about count < 32
2025-10-21 16:43:14 +08:00
safranowith 466c1911ab cpu : add FLOOR, CEIL, ROUND and TRUNC unary operators (#16083)
* CPU: Add support for FLOOR,CEIL,ROUND and TRUNC unary operators

- Added the operators to unary op enum
- Implemented API functions
- Implemented forward and unary-op logic in CPU backend
- Updated ggml_get_n_tasks
- Updated operators names array and static_assert
- Updated docs and enabled automatic tests

* docs: add documentation for ggml_trunc and ggml_trunc_inplace in ggml.h

* chore: remove trailing whitespace from ggml.h

* Remove unresolved merge markers

* Apply review suggestions: cleanup formatting, enum order and leftover artifacts

* Regenerate ops.md using create_ops_docs.py
2025-10-15 21:24:51 +02:00
Reese LevineandGeorgi Gerganov ef07a40906 ggml webgpu: add support for soft_max, optimize rms_norm (#16357)
* Add inplace softmax

* Move rms_norm to split row approach

* Update debug for supports_op

* clean up debug statements

* Update tests/test-backend-ops.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2025-10-02 11:00:31 -07:00
34fcc5a4ac model : Apertus model implementation (#15852)
* First attempt

* No permute during convert (fixes qk tensors), proper norm application.

* RoPE = NeoX

* Coherence!

* Migrate xielu params from tensors to hyperparameters

* Simple CUDA kernel

* Revert stupid LLM refactorings

* Chat template support

* configchecker / flake8 errors

* Reorder unary.cu

* I do conclude that LLMs are, in fact, stupid.

* Fix after merge

* Final newline

* Make xIELU an UNARY_OP

* Final newline

* Correctly account for parameter shift

* Argh.

* Update ggml/src/ggml-cpu/unary-ops.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Refactor: remove unused methods, inline and factorize softplus, add const modifiers

* Revert CUDA changes, implement xIELU as a separate OP

* Pesky newline

* Add float2half / half2float for F16 inputs/outputs

* CUDA variants, attempt 2

* Actually, attempt 3

* Update ggml/src/ggml-cuda/unary.cu

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Missing convert header

* Proper formula and reference for xIELU in the comments.

* Modify unary-ops.cpp to add the functor-based logic besides the template system to retain optimizations

* Apply suggestions from code review

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Add tensor mappings for Apertus to global list instead

* Fix lazy on scalars

* Update ggml/src/ggml-cuda/unary.cu

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Add comment about the constraints on positive/negative alpha

* Change `softplus` to `ggml_softplus`

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
2025-10-02 20:43:22 +03:00
Georgi Gerganov a4a0aa5ea2 ggml : fix dependencies for ggml_set_rows (#16318) 2025-09-29 08:41:28 +03:00
624207e676 devops: add s390x & ppc64le CI (#15925)
* devops: move s390x and ppc64le ci build

we have access to ubuntu-24.04-s390x and ppc64le images now

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: disable ppc64le for now since they have compiler errors

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: stop warnings as errors

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: switch to non-macro flag

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: going the llama macro route

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: add big-endian gguf test models

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: disable ppc64le to test s390x, check test build

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: dup .gguf.inp files for big-endian tests

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: dup .gguf.out files for big-endian too

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: add python setup and endian byteswap

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: pooring thing does not have s390x python3

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: add missing rust compiler for s390x

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: try rust actions runner

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Revert "devops: try rust actions runner"

This reverts commit 3f8db04356033d6c1d7eccc75ca396bc5298250c.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: try a different path for rust

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: dump home directory and user info

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: install gguf-py only

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: missed relative path

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: remove big-endian files since local swapping is working

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: revert test-tokenizer-0 cmakelists

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Fix unicode flags conversion from and to uint16_t

Bitfields are allocated in different order on s390x

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Simplify byteswap command

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Add byteswapping and git-lfs for test-tokenizers-ggml-vocabs

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Fix endianness detection in vocab loader

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Disable test-thread-safety on s390x

In this test a model is downloaded,
then immediately loaded to check if more downloads are needed,
and then used for test.

There is no clean way to separate all those steps
 to add byteswapping between them, so just skip this test.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Fix q8_0 test in test-quantize-fns

vec_signed uses unexpected rounding mode.
Explicitly use different rounding function.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: add big-endian stories260K

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: add s390x test-eval-callback

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: fix test does not exist

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: fix model not found llama-eval-callback

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Fix q3_K dot product error in test-quantize-fns on s390x

Array q8bytes had only 4 elements allocated, but 8 elements accessed.
This lead to write out of bounds and later read of overwritten values out of bounds
and incorrect result.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: re-enable ppc64le for testing

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: activate test-thread-safety for s390x

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: disable ppc64le tests

for some reason it keeps failing test-thread-safety tests and I do not
    have a machine that is able to replicate the tests.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* devops: LLAMA_FATAL_WARNINGS=ON

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Correct repository URL for s390x for test-thread-safety model

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Fix fs_get_cache_directory

Ensure it works even if both XDG_CACHE_HOME and HOME are unset.
This might happen in containers.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Re-enable CI for ppc64le

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Fortify ggml_rope_impl

Only memcpy data from sections argument if it's non-NULL.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Add TODO in struct unicode_cpt_flags to reimplement it in endian-independent way

* Update URL for big-endian model

* Update .github/workflows/build.yml

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Update remaining mentions of BE models to ggml-org/models repo

---------

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
Co-authored-by: Aleksei Nikiforov <aleksei.nikiforov@linux.ibm.com>
Co-authored-by: Aleksei Nikiforov <103434461+AlekseiNikiforovIBM@users.noreply.github.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
2025-09-27 02:03:33 +08:00
3ecb2f671a ggml : implement set_rows with i32 index (#16159)
* implement set_rows with i32 index

* template fix

* test quantized path

warnings--

* Apply suggestions from code review

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* forgotten name change

* deduplicate cuda/sycl and test-fix

* indent++

* vulkan: support set_rows with i32 index type (#16162)

* disable i32 index for webgpu for now

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Jeff Bolz <jbolz@nvidia.com>
2025-09-22 19:13:00 +02:00