I updated test_topk_moe to more closely match llm_graph_context::build_moe_ffn
and added coverage for exp_probs_b and some other missing combinations. This
exposed a bug in both CUDA and Vulkan backends where they were assuming the
input to argsort and the input to get_rows are the same. I'd like to optimize
this graph in another change, but for now just get it functional.
CUDA also had a bug where it got n_experts from the wrong place, leading to
GGML_ASSERT failures in some of the new tests.
* arg: fix order to use short form before long form
* arg: update doc
* arg: update test-arg-parser
* arg: address review feedback from ngxson
simplified to check first.length() <= last.length() only
fixed: --sampler-seq, --rerank, --draft ordering
note: middle positions in 3+ arg sets are not verified
* arg: update doc
* common : expose json-schema functionality to extract type info
* common : fix peg parser negation during needs_more_input
* common : add some defensive measures in constructed peg parser
* common : add nemotron nano 3 support
* common : add nemotron nano 3 tests
* remove debug line
* kv-cache : fix state restore with fragmented cache (#17527)
Change find_slot to allow non-contiguous allocation during state restore. Fixes 'failed to find available cells in kv cache' error when restoring state to fragmented cache.
* tests : update logic
* cleanup: tightened state_read_meta sig, added is_contiguous case
* fix: state_read_meta arg reorder loose ends
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
When the number of cols is large, split each row across multiple workgroups.
There are three phases that communicate partial results through temp buffers:
(1) compute max partials
(2) take max of partials, compute sum(exp(x-max)) partials
(3) sum partials, compute scaled result
* Extended TRI
* Fix whitespace
* chore: update webui build output
* Just use cuBLAS for everything...
* Merge both versions
* Remove incorrect imports causing failures for CI
* Still failing... remove all direct cublas imports and rely on common imports from "common.cuh"
* Defines for hipBlas
* Aaaand MUSA defines...
* I hate this job...
* Stupid typo...
* Update ggml/src/ggml-cuda/solve_tri.cu
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* tests: update barrier test to check for race condition in active threads
* cpu: combine n_graph and n_threads into a single atomic update
* tests: add multi-graph test for test_barrier
* feat: Add a batched version of ssm_conv
This was done using Claude Code. It found a number of optimizations around
how the threads were organized, resulting in a huge performance boost!
Branch: Mamba2SSD
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Optimized SSM_SCAN kernel for metal
This used Claude Code and resulted in a modest performance improvement
while maintaining correctness.
Branch: Mamba2SSD
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* test: Add test-backend-ops perf tests for SSM_CONV
Branch: SSMKernelImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* test: Real representitive tests for SSM_CONV
Branch: SSMKernelImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* refactor: Use function constant for ssm_conv batch size
Branch: SSMKernelImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* test: backend op tests for ssm_scan from granite4 1b-h
Branch: SSMKernelImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* style: remove commented out templates
Branch: SSMKernelImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: float4 version of ssm_conv_batched
Branch: SSMKernelImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Add missing ggml_metal_cv_free
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Old implementation parallelizes rows across SMs, which does not fit the
needs of backend-sampling (where we have ncols >> nrows and thus want to
parallelize ncols across SMs)
* Fix kimi-k2 parsing
* fix template & add more tests for kimi-k2
* Another fix for Kimi-K2 chat template.
* enable allow_toolcall_in_think for Kimi-K2
* Refine key-value separator and value end format
* Enable tool call in think for kimi-k2
* allow_toolcall_in_think is now tested with Kimi-K2
* Remove outdated TODO comment in XML tool call parser
Removed TODO comment about untested tool call feature.
* Rename function from "utf8_truncate_safe" to "utf8_truncate_safe_len"
Daniel Bevenius
Jeff Bolz
Georgi Gerganov
Johannes Gäßler
Xuan-Son Nguyen
Pascal
Aldehir Rojas
ssweens
Piotr Wilkin (ilintar)
Max Krasnyansky
Gabe Goodhart
Oliver Simons
hksdpc255