mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2026-06-30 00:00:23 +00:00
b7828
629 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Johannes Gäßler
|
4e5b83b226 | GGUF: check that tensor size is representable (#19072) | ||
|
Xuan-Son Nguyen
|
51fa458a92 |
server : support preserving reasoning_content in assistant message (#18994)
* support reasoning_content input * report template caps to webui * add docs * rm commented code |
||
|
Georgi Gerganov
|
a5eaa1d6a3 |
mla : make the V tensor a view of K (#18986)
* mla : pass V as a view of K to the FA op * cuda : adjust mla logic to new layout * kv-cache : fix rope shift * tests : remove comment * cuda : fix reusable_cutoff Co-authored-by: Johannes Gäßler <johannesg@5d6.de> --------- Co-authored-by: Johannes Gäßler <johannesg@5d6.de> |
||
|
Piotr Wilkin (ilintar)
|
c301172f66 |
jinja: support none|string (#18995)
* jinja: support none|string * Update common/jinja/value.cpp Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Update tests/test-jinja.cpp Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Add as_string() --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> |
||
|
Jeff Bolz
|
33f890e579 | vulkan: support flash attention GQA/split_k with small batches (#18938) | ||
|
Xuan-Son Nguyen
|
2c1f199653 |
cli : fix reasoning responses in CLI (#18961)
* cli : fix reasoning responses in CLI * fix build * fix build (2) |
||
|
Sigbjørn Skjæret
|
959ecf7f23 |
jinja : fix undefined keys and attributes and int/float as bool (#18924)
* fix undefined keys and attributes * add falsy tests * as_bool for integers and floats * more falsy/truthy tests * --typo |
||
|
Sigbjørn Skjæret
|
4037093c66 | ci : run test-jinja -py on high perf [no ci] (#18916) | ||
|
Xuan-Son Nguyen
|
fe44d35574 |
tests : add test-jinja -py option for cross-checking (#18906)
* tests : add test-jinja -py option or cross-checking * Update tests/test-jinja.cpp Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * fix + add source * SandboxedEnvironment * fix array.map case --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> |
||
|
Sigbjørn Skjæret
|
d03c45c9c5 |
jinja : attribute support for join, map and sort (#18883)
* support negative array index and default value * attribute support (int and str) for join, map and sort * add tests * update CODEOWNERS * improve fixme sorting comment |
||
|
Sigbjørn Skjæret
|
10c98cbdf6 |
jinja : add missing tojson filter for bool (#18900)
* add missing tojson for bool * add more literal tests |
||
|
Sigbjørn Skjæret
|
420960ab92 |
jinja : fix lexing of float literals with sign (#18901)
* fix lexing of float literals with sign * add test * consume_numeric |
||
|
Xuan-Son Nguyen
|
f55b033ae6 | jinja: correct member access rule (#18905) | ||
|
Thore Koritzius
|
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> |
||
|
Xuan-Son Nguyen
|
c15395f73c |
common : implement new jinja template engine (#18462)
* jinja vm * lexer * add vm types * demo * clean up * parser ok * binary_expression::execute * shadow naming * bin ops works! * fix map object * add string builtins * add more builtins * wip * use mk_val * eval with is_user_input * render gemma tmpl ok * track input string even after transformations * support binded functions * keyword arguments and slicing array * use shared_ptr for values * add mk_stmt * allow print source on exception * fix negate test * testing more templates * mostly works * add filter_statement * allow func to access ctx * add jinja-value.cpp * impl global_from_json * a lot of fixes * more tests * more fix, more tests * more fixes * rm workarounds * demo: type inferrence * add placeholder for tojson * improve function args handling * rm type inference * no more std::regex * trailing spaces * make testing more flexible * make output a bit cleaner * (wip) redirect minja calls * test: add --output * fix crash on macro kwargs * add minimal caps system * add some workarounds * rm caps_apply_workarounds * get rid of preprocessing * more fixes * fix test-chat-template * move test-chat-jinja into test-chat-template * rm test-chat-jinja from cmake * test-chat-template: use common * fix build * fix build (2) * rename vm --> interpreter * improve error reporting * correct lstrip behavior * add tojson * more fixes * disable tests for COMMON_CHAT_FORMAT_GENERIC * make sure tojson output correct order * add object.length * fully functional selectattr / rejectattr * improve error reporting * more builtins added, more fixes * create jinja rendering tests * fix testing.h path * adjust whitespace rules * more fixes * temporary disable test for ibm-granite * r/lstrip behavior matched with hf.js * minimax, glm4.5 ok * add append and pop * kimi-k2 ok * test-chat passed * fix lstrip_block * add more jinja tests * cast to unsigned char * allow dict key to be numeric * nemotron: rm windows newline * tests ok * fix test * rename interpreter --> runtime * fix build * add more checks * bring back generic format support * fix Apertus * [json.exception.out_of_range.403] key 'content' not found * rm generic test * refactor input marking * add docs * fix windows build * clarify error message * improved tests * split/rsplit with maxsplit * non-inverse maxsplit forgot to change after simplifying * implement separators for tojson and fix indent * i like to move it move it * rename null -- > none * token::eof * some nits + comments * add exception classes for lexer and parser * null -> none * rename global -> env * rm minja * update docs * docs: add input marking caveats * imlement missing jinja-tests functions * oops * support trim filter with args, remove bogus to_json reference * numerous argument fixes * updated tests * implement optional strip chars parameter * use new chars parameter * float filter also has default * always leave at least one decimal in float string * jinja : static analysis + header cleanup + minor fixes * add fuzz test * add string.cpp * fix chat_template_kwargs * nits * fix build * revert * unrevert sorry :) * add fuzz func_args, refactor to be safer * fix array.map() * loosen ensure_vals max count condition, add not impl for map(int) * hopefully fix windows * check if empty first * normalize newlines --------- Co-authored-by: Alde Rojas <hello@alde.dev> Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> |
||
|
Adrien Gallouët
|
ec997b4f2b |
tests : download models only when running ctest (#18843)
Signed-off-by: Adrien Gallouët <angt@huggingface.co> |
||
|
Oliver Simons
|
36f0132464 |
CUDA: Factor out and re-use block_reduce function (#18785)
* CUDA: Refactor and expose two_stage_warp_reduce_* function * Use `two_stage_warp_reduce` also in softmax kernel, move smem out of it Moving smem out of `__device__` function to `__global__` function allows for explicit smem reuse, as either compiler or cuda rt seem to not free it afterwards (`cudaFuncSetAttribute` fails when not accounting for it once for each call to two_stage_warp_reduce) * Update ggml/src/ggml-cuda/common.cuh Co-authored-by: Aman Gupta <amangupta052@gmail.com> * Use two_stage_warp_reduce in group_norm_f32 * Use two_stage_warp_reduce in rms_norm_f32 * Fix smem calculation which expects bytes * Make `two_stage_warp_reduce` accept all values warp_reduce accepts Also integrate it into norm_f32 function * Use two_stage_warp_reduce in l2_norm_f32 * Use type traits for block reduction for better legibility Also adresss other requests by @am17an such as variable renaming * Make norm tests cover all cuda paths * Mark columns % WARP_SIZE !=0 as supported for RMS_NORM_BACK Unit-tests passed locally, let's see if they pass in the CI as well * Use `enum class` for `block_reduce_method` This is more type-safe than plain enum * Rename variables as suggested in code review by @am17an * Rename two_stage_warp_reduce -> block_reduce * Fix trailing whitespace in common.cuh * Make condition of static_assert type-dependent This delays evaluation until the template is actually instantiated. Otherwise, some compilers may evaluate the assert when parsing the template, resulting in build errors as observed here: https://github.com/ggml-org/llama.cpp/actions/runs/20960323123/job/60235530068?pr=18785 * Inline definitions --------- Co-authored-by: Aman Gupta <amangupta052@gmail.com> |
||
|
Adrien Gallouët
|
f709c7a33f |
ci, tests : use cmake to download models and remove libcurl dependency (#18791)
* ci, tests : use cmake to download models and remove libcurl dependency * llama_dl_model -> llama_download_model * use EXPECTED_HASH for robust model downloading * Move llama_download_model to cmake/common.cmake Signed-off-by: Adrien Gallouët <angt@huggingface.co> |
||
|
Jeff Bolz
|
2bbe4c2cf8 |
vulkan: Use VK_EXT_shader_64bit_indexing to handle large mat_mul(_id) (#18678)
This fixes incoherent output in Llama-4-Maverick-17B-128E-PAB-Q8_0, which has a mul_mat_id with an A matrix that's Q8_0 8192 x 5120 x 128. This should work when the number of blocks in the A matrix is less than 2^32 (for mul_mat_vec or mul_mm_cm2), or for mul_mm I think the limit is like 2^32*LOAD_VEC_A elements. - Divide batch_stride by QUANT_K earlier, so the block index calculation works in 32b. - Each vk_pipeline_struct has a linked list of pipelines that will allow it to handle variants. So far this change just adds a single use case for this, compiling with the e64BitIndexingEXT flag. - Use the 64b indexing variant when the A matrix is larger than maxStorageBufferRange. 64-bit indexing has some cost - around 3-5% in MoE models, so it's worth the effort to avoid enabling it unconditionally. |
||
|
Georgi Gerganov
|
84ae04f163 |
tests : refactor test-backend-sampler (#18753)
* tests : use "auto", use std::string * tests : refactor test-backend-sampler.cpp * cmake : remove redundant declarations * ci : use smaller model * tests : add struct test_params * tests : reduce logit bias 100.0f -> 10.0f |
||
|
Aman Gupta
|
b137718878 | test-backend-ops: fix mxfp4 tests on blackwell (#18736) | ||
|
Adrien Gallouët
|
55abc39355 |
vendor : update cpp-httplib to 0.30.0 (#18660)
* vendor : update cpp-httplib to 0.30.0 * common : allow custom headers when downloading |
||
|
Xuan-Son Nguyen
|
07fbe19f1f |
arg: use CSV escape style for multiple-value args (#18643)
* arg: use CSV escape style for multiple-value args * add test |
||
|
Jeff Bolz
|
f1768d8f03 | vulkan: fix topk_moe_sigmoid_norm_bias failures in GLM-4.6 (#18582) | ||
|
Jeff Bolz
|
b37124d2d2 |
vulkan: handle quantize_q8_1 overflowing the max workgroup count (#18515)
* vulkan: handle quantize_q8_1 overflowing the max workgroup count * vulkan: Fix small tile size matmul on lavapipe * fix mul_mat_id failures |
||
|
Chenguang Li
|
67e3f6f601 |
CANN: add operator fusion support for ADD + RMS_NORM (#17512)
This commit implements operator fusion for ADD + RMS_NORM operations in the CANN backend to reduce memory access overhead and improve performance. The fusion is controlled by the GGML_CANN_OPERATOR_FUSION environment variable (default: false). Changes: - Implement ggml_cann_op_add_rms_norm_fused() using ACLNN AddRmsNorm - Add ggml_cann_can_fuse() to check fusion eligibility - Integrate fusion logic into computation graph evaluation - Add test cases for ADD + RMS_NORM fusion - Update documentation with new environment variable The fusion combines ADD and RMS_NORM into a single kernel call, which is more efficient than executing them separately. |
||
|
Daniel Bevenius
|
d3dce4e0a5 |
sampling : add support for backend sampling (#17004)
* sampling : add support for backend sampling This commit adds support for performing sampling operations on the backend (e.g. GPU) as part of the model computation graph. The motivation for this feature is to enable sampling to be performed directly on the backend as part of the computation graph being executed, allowing for some or all of the sampling to be done on the backend. For example, the backend sampler chain might select/sample a token directly in which case only the sampled token needs to be transferred from device memory to host memory. It is also possible for the backend samplers to perform filtering of the logits, or compute and filter the probability distribution, in which case only the filtered logits or probabilites need to be transferred back to system memory for further processing by CPU samplers. Currently the backend sampling works in a similar manner to how pooling works, it is a function that is called by build_graph and the sampler operations become part of the models computation graph. * llama-cli : add backend sampler configuration * server : add backend sampling options/configuration * webui : add backend sampling options * ggml : add initial cumsum implementation for CUDA * sampling : enable all backend sampler tests This commit enables all exisiting backend sampler tests in the test-backend-sampler. Previously, some tests were disabled because there were missing ggml operation implementations. * graph : do not include llama-model.h * sampling : always expose sampled_ids This commit precomputes and caches the full-vocab token id list in llama_context's constructor, so llama_get_backend_sampled_token_ids_ith always returns a valid pointer. The motivation for this is that this enables both common/sampling.cpp and src/llama-sampling.cpp can simplify their logic. Not all backends samplers that process logits need to set the sampled_tokens_id as they may not change the order of the logits, for example the temperature sampler only scales the logits but does not change their order. Simliar the logit bias sampler only adds bias to specific token ids but does not change the order of the logits. In these cases there will not be a device to host copy of the sampled token ids, and this is the use case where having this precomputed list is useful. * sampling : ensure at most one output token per seq This commit adds a check in the batch allocator to ensure that when backend sampling is enabled, at most one output token is specified per sequence. * CUDA: Optimize argsort for gpu-based token sampling Argsort is used for top-k currently. WE optimize argsort by 2 things: 1. Use `DeviceRadixSort` for single-row/sequence to parallelize it across our SMs 2. Use `DeviceSegmentedSort` for multi-row/sequence as this is the correct entrypoint (the function chooses different execution paths, it contains `DeviceSegmentedRadixSort` as one of the paths and will choose the best one according to heuristics. https://nvidia.github.io/cccl/cub/api/structcub_1_1DeviceSegmentedSort.html#overview Some perf numbers for a RTX PRO 6000: On the kernel level, tested with `GGML_CUDA_DISABLE_GRAPHS=1 ./test-backend-ops -o ARGSORT perf` Before: ``` ARGSORT(type=f32,ne=[65000,16,1,1],order=0): 4130 runs - 359.24 us/run ARGSORT(type=f32,ne=[200000,1,1,1],order=0): 8192 runs - 861.34 us/run ARGSORT(type=f32,ne=[200000,16,1,1],order=0): 1343 runs - 1020.01 us/run ``` After: ``` ARGSORT(type=f32,ne=[65000,16,1,1],order=0): 4130 runs - 312.41 us/run ARGSORT(type=f32,ne=[200000,1,1,1],order=0): 16384 runs - 63.48 us/run ARGSORT(type=f32,ne=[200000,16,1,1],order=0): 1343 runs - 874.36 us/run ``` --- On the model level, tested with `llama-cli -m gpt-oss-20b-mxfp4.gguf -n 200 -p "What is the Capital of Sweden?" -no-cnv -fa 1 --backend-sampling` Before: ``` llama_perf_sampler_print: sampling time = 0.25 ms / 207 runs ( 0.00 ms per token, 824701.20 tokens per second) llama_perf_context_print: load time = 18215.58 ms llama_perf_context_print: prompt eval time = 28.20 ms / 7 tokens ( 4.03 ms per token, 248.19 tokens per second) llama_perf_context_print: eval time = 714.79 ms / 199 runs ( 3.59 ms per token, 278.40 tokens per second) llama_perf_context_print: total time = 857.62 ms / 206 tokens ``` After ``` llama_perf_sampler_print: sampling time = 0.25 ms / 207 runs ( 0.00 ms per token, 828000.00 tokens per second) llama_perf_context_print: load time = 18366.92 ms llama_perf_context_print: prompt eval time = 35.92 ms / 7 tokens ( 5.13 ms per token, 194.87 tokens per second) llama_perf_context_print: eval time = 532.79 ms / 199 runs ( 2.68 ms per token, 373.50 tokens per second) llama_perf_context_print: total time = 683.65 ms / 206 tokens ``` * sampling : remove version from sampler chain This commit removes the version field from the sampler chain and instead used the sampler pointer itself for change detection. * sampling : always populate logits for sampled probs This commit updates common/sampler.cpp set_logits and src/llama-sampling.cpp llama_sampler_sample to always populate the logits field when backend sampled probabilities are available. The motivation for this is that this ensure that CPU sampler always have access to the logits values even when probabilites have been produced by backend samplers. * sampling : simplify backend sampling logic decode This commit tries to simplify the backend sampling logic in llama_context::decode. * squash! sampling : simplify backend sampling logic decode Fix condition to check if backend actually sampled tokens, not just that backend samplers are available. * common : fix regression caused by extra memory allocations during sampling * squash! sampling : simplify backend sampling logic decode The commit fixes a variable shadowing issue in the `llama_context::decode` function which was introduced in a previous refactoring. * squash! common : fix regression caused by extra memory allocations during sampling Apply the same changes to llama-sampling.cpp, llama_sampler_sample as were applied in commit |
||
|
Aldehir Rojas
|
cef1d23c5a |
common/grammar : replace problematic backtracking regex [\s\S]* (#18342)
* grammar : add support for std::regex_search() with trigger patterns * common : update hermes2 pro trigger to search instead of match * common : use regex_search with anchoring for partial matching * common : adjust regex partial tests to use new pattern * grammar : check pattern directly instead of adding a type * common : adjust existing patterns to match new semantics |
||
|
Jeff Bolz
|
be47fb9285 |
vulkan: extend topk_moe to handle sigmoid w/exp_probs_b for nemotron (#18295)
* vulkan: extend topk_moe to handle sigmoid w/exp_probs_b for nemotron Also handle GGML_OP_SCALE at the end (nemotron, deepseek2). Fewer pipeline variants and spec constants, just use push constants. In test_topk_moe, change exp_probs_b to be 1D, matching real networks. Update test-backend-ops and ggml-backend to allow verifying multiple outputs in a fusion test (topk_moe has two outputs). Previously only the final node was verified. * change test_topk_moe to allow results in arbitrary order * disable sigmoid fusion for moltenvk |
||
|
Anri Lombard
|
4cd162a123 |
chat: make tool description and parameters optional per OpenAI spec (#18478)
* chat: make tool description and parameters optional per OpenAI spec Per the OpenAI API specification, both 'description' and 'parameters' fields in tool function definitions are optional. Previously, the parser would throw an exception if these fields were missing. Attempts to fix #17667 * refactor: use value() for cleaner optional field access |
||
|
Aldehir Rojas
|
0f89d2ecf1 |
common : default content to an empty string (#18485)
* common : default content to an empty string * common : fix tests that break when content != null |
||
|
Jeff Bolz
|
b96b82fc85 | vulkan: Support UPSCALE w/antialias (#18327) | ||
|
Jeff Bolz
|
10dc500bdb | vulkan: handle rope with large number of rows (#18306) | ||
|
Jeff Bolz
|
e3b35ddf1c |
vulkan: Extend rope fusions to allow mrope (#18264)
Extend the test-backend-ops tests as well. |
||
|
Johannes Gäßler
|
147a521636 | tool/ex/tests: consistently free ctx, then model (#18168) | ||
|
Jeff Bolz
|
fd05c51cec | vulkan: fix im2col overflowing maxworkgroupcount (#18180) | ||
|
Jeff Bolz
|
b365c3ff01 |
vulkan/cuda: fix topk_moe with exp_probs_b (#18071)
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. |
||
|
Jeff Bolz
|
52ab19df63 |
tests: Avoid floating point precision false positives in SUM (#17471)
* tests: Avoid floating point precision false positives in SUM * also apply to test_mean |
||
|
Jeff Bolz
|
5182dd64cd | test-backend-ops: improve msvc build time (#18209) | ||
|
Xuan-Son Nguyen
|
9e39a1e6a9 |
server: support load model on startup, support preset-only options (#18206)
* server: support autoload model, support preset-only options * add docs * load-on-startup * fix * Update common/arg.cpp Co-authored-by: Pascal <admin@serveurperso.com> --------- Co-authored-by: Pascal <admin@serveurperso.com> |
||
|
Pascal
|
14931a826e |
arg: fix order to use short form before long form (#18196)
* 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 |
||
|
Xuan-Son Nguyen
|
8ea958d4d9 |
model : add ASR support for LFM2-Audio-1.5B (conformer) (#18106)
* ASR with LFM2-Audio-1.5B * Set rope_theta * Fix comment * Remove rope_theta setting * Address PR feedback * rename functions to conformer * remove some redundant ggml_cont * fix missing tensor * add prefix "a." for conv tensors * remove redundant reshape * clean up * add test model --------- Co-authored-by: Tarek Dakhran <tarek@liquid.ai> |
||
|
Aldehir Rojas
|
c05aa69f32 |
common : add nemotron 3 parsing (#18077)
* 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 |
||
|
ssweens
|
4529c660c8 |
kv-cache: Fix state restore fragmented cache (#17982)
* 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> |
||
|
Xuan-Son Nguyen
|
4d5ae24c0a | arg: fix common_params_parse not accepting negated arg (#17991) | ||
|
Jeff Bolz
|
303f8615e9 |
vulkan: Multi-pass softmax for large number of cols (#17892)
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 |
||
|
Jeff Bolz
|
07a10c1090 | vulkan: Allow non-pow2 n_experts in topk_moe (#17872) | ||
|
Xuan-Son Nguyen
|
380b4c984e |
common: support negated args (#17919)
* args: support negated args * update docs * fix typo * add more neg options * Apply suggestions from code review Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * rm duplicated arg * fix LLAMA_ARG_NO_HOST * add test --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> |
||
|
Piotr Wilkin (ilintar)
|
53ecd4fdb9 |
SOLVE_TRI extension to more dimensions (#17793)
* 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> |
||
|
Max Krasnyansky
|
e1f4921980 |
Fix race conditions in threadpool when dealing with dynamic/frequent n_threads changes (#17748)
* 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 |