Splits producing more than one ubatch per batch for recurrent models
were broken with ggml-org#14512.

This fixes it by moving the completeness check after the ubatch split loop.

* Init - first pass.

* Model -> ModelBase.

* fix errors in conversion.

* Update the graph.

* up.

* up.

* wip

* cgraph ok

* rm redundant code

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Co-authored-by: Vaibhavs10 <vaibhavs10@gmail.com>

Signed-off-by: stevenkuang <stevenkuang@tencent.com>

* vulkan: allow FA split_k with smaller KV values

* vulkan: spread split_k_reduce work across more threads

k_num can get rather large. Use the whole workgroup to reduce the M/L values.

Launch a thread for each element in the HSV dimension of the output. Helps a
lot for large HSV (like deepseek).

* v1

* push more fixes

* another fix

* fix

* more fixes

* minor fix

* more cleaning on python code

* python fixes

* changed precision for multipliers float 32->64

* fixes

* another fix

* fix

* pre-norm -> norm

* fix

* Revert "fix"

This reverts commit 243e4d1.

* fix

* small fix ffn_norm

* try

* mix instead of max

* fix vocab size

* conflict solve

* fixed multipliers

* falcon-h1 specefic vocab resolved

* read arch from gguf.MODEL_ARCH

* mamba_d_ssm added to d_inner find_hparam

* remove unused functions from gguf_writer.py

* override modify_tensors instead of get_tensors

* fix conversion and d_inner

* added some cb functions for debugging puposes

* inp_out_ids moved outside of layers loop

* mup_vec create as float64

* fix rope_theta

* injected mup

* clean ups

* rm extra space

* rm unused MAMBA_CHUNK_SIZE

* rm unused key

* add bos False

* changed ROPE_TYPE

* cleaning debugging stuff

* cleaning debug quant

* fix comment

* some cleanups

* some cleanups

* Update src/llama-model-loader.cpp

* more cleanups

* moe cleanuips

* d_ssm -> d_inner;

* cleaning unused hparams

* cleanup

* more cleanups

* more cleanups on python conversion;

* minor cleanups

* Apply suggestions from code review

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

* remove todo

* added falcon-h1

* tensor not required

* clean

* remove unneeded attributes

* more cleanups and fixed conversion

* remove final_norm

* flake8 fixes

* Update src/llama-model.cpp

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

* flake8 fixes

* Update src/llama-hparams.cpp

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

* Update src/llama-model.cpp

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

* Update src/llama-model.cpp

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

* Update src/llama-arch.cpp

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

* Update convert_hf_to_gguf.py

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

* added hashes

* Update src/llama-arch.cpp

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

* Update src/llama-vocab.cpp

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

* update the update file

* Revert "update the update file"

This reverts commit 082ab4a.

* fix: address suggestions

* fix: update convert_hf_to_gguf.py

* Update gguf-py/gguf/constants.py

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

* Update src/llama-model-loader.cpp

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

* d_inner fixed

* Update src/llama-model.cpp

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

* reshaping ssm_norm for 34B

* removing generate_mup

* remove duplicates metadata keys

* rm comment

* final comment

* fix unused args

* fix constants

* fix bad merge

* Update src/llama-model.cpp

Co-authored-by: compilade <git@compilade.net>

* falcon-h1: remove unused ssm_in_b and bad merge

* Update src/llama-model.cpp

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

* falcon-h1: fix last comment

* Update convert_hf_to_gguf.py

Co-authored-by: compilade <git@compilade.net>

* falcon-h1: revert add_add_bos(False)

* falcon-h1: fix tied weights

* falcon-h1: remove whitespace

* falcon-h1: fix wrong size param

* falcon-h1: fix whitespace issues

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Co-authored-by: younesbelkada <younes.belkada@tii.ae>
Co-authored-by: Younes B <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: compilade <git@compilade.net>

…-org#14595)

* ggml : add ggml_scale_bias

* ggml_vec_mad1_f32

* add more simd

* add CUDA

* sycl

* vulkan

* cann (placeholder)

* opencl

* will this fix cpu?

* fix cuda

* suggestions from coderabbit

* fix cann compile error

* vDSP_vsmsa

* rm __ARM_FEATURE_SVE

* use memcpy for op params

* make code looks more consistent

* use scalar for __ARM_FEATURE_SVE

* add x param to ggml_vec_mad1_f32

* wip: llama : separate recurrent states from the KV cache

This will be necessary to support Jamba
(and other recurrent models mixed with Attention).

Doesn't compile yet, and finding a slot isn't yet done correctly for recurrent states.

* llama : use std::find for seq_nodes in llama_rs_cache

* llama : state checkpoints for recurrent models

* llama : correctly handle more edge cases for the rs cache

* llama : rename many llama_kv_cache_* functions

* llama : remove useless return value for some llama_cache_* functions

* llama : rethink recurrent state cell counts

* llama : begin work on support for variable GQA

This will also be useful for Jamba if we consider the Mamba layers
to have 0 KV heads.

* llama : gracefully fail when not finding hybrid slot

* llama : support Jamba

* llama : fix BERT inference without KV cache

* convert-hf : check for unprocessed Jamba experts

* convert-hf : support Mini-Jamba conversion

* llama : fix Jamba quantization sanity checks

* llama : sequence-length-aware batch splitting

* llama : use equal-sequence-length sub-batches for recurrent models

* ggml : simplify SSM-related operators

* llama : make recurrent state slot allocation contiguous

* llama : adapt internal uses of batches to llama_ubatch

* llama : fix batch split output count for embeddings

* llama : minimize swaps when reordering logits

This reduces overhead when running hellaswag
on thousands of sequences with very small 100k params Mamba models.

* llama : fix edge case finding batch seq_id of split recurrent cell

This otherwise was a problem when running the HellaSwag benchmark
with small batch sizes, making it crash.

* llama : avoid copies for simple batch splits

* ggml : make ggml_ssm_scan not modify its source tensors

* llama : fix shared recurrent tail cell count for small ubatch sizes

Otherwise it was impossible to run the 'parallel' example with '-ub 1'
with a Mamba or Jamba model.

* llama : fix .base() compilation error on Windows

* llama : allow doing the equivalent of SSM_CONV with SUM_ROWS and MUL

* ggml : allow GGML_OP_CONCAT to work on non-contiguous tensors

The implementation already supported it,
and this makes Mamba's conv step slightly faster.

* mamba : fix non-contiguous usage of ggml_silu

* llama : session saving and reloading for hybrid models

* convert_hf : fix Jamba conversion

* llama : fix mixed signedness comparison

* llama : use unused n_embd_k_gqa in k_shift

This also slightly reduces the diff from the master branch

* llama : begin renaming llama_past back to llama_kv_cache

* llama : remove implicit recurrent state rollbacks

* llama : partially apply clang-format style

* convert : fix jamba conv1d shape squeezing

* graph : add back hybrid memory graph input

But this time it contains the sub-cache graph inputs.
This *should* make it easier to handle updating the inputs
when caching the graph (eventually).

* model : add Jamba to Mamba-specific hparams printing

* jamba : remove redundant nullptr initializations

* model : remove unnecessary prefix for tensor loading constants

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

* model : use ggml_swiglu_split for Mamba

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

* model : make falcon-h1 use shared mamba2 layer builder

* memory : avoid referring to KV in recurrent cache logs

* gguf-py : avoid adding duplicate tensor mappings for Jamba

Some of the tensor names are common with Llama4

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