Cherry 1220 #6
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Cherry 1220 #6
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arthw
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Dec 20, 2024
arthw
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* Vulkan: Fix device info output format specifiers * Vulkan: Use zu printf specifier for size_t instead of ld
Flake lock file updates:
• Updated input 'nixpkgs':
'github:NixOS/nixpkgs/4aa36568d413aca0ea84a1684d2d46f55dbabad7?narHash=sha256-Zwl8YgTVJTEum%2BL%2B0zVAWvXAGbWAuXHax3KzuejaDyo%3D' (2024-11-05)
→ 'github:NixOS/nixpkgs/5e4fbfb6b3de1aa2872b76d49fafc942626e2add?narHash=sha256-OZiZ3m8SCMfh3B6bfGC/Bm4x3qc1m2SVEAlkV6iY7Yg%3D' (2024-11-15)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Seems like this isn't working for vulkan-over-metal when the array is sized by a spec constant. Maybe a spirv-cross limitation?
* vulkan: Optimize soft_max Large soft_max could already saturate memory, but small/medium sizes were pretty slow. The bulk of the gains for them comes from using a smaller workgroup size, and making the workgroup size match the subgroup size also makes the barriers much cheaper. Cache some values in locals to avoid refetching/recomputing. And stamp out a few "template instantiations" so smaller cases will fully unroll. Add a missing early return for OOB rows. This happens when there are more than 512 rows and the dispatch is 512 x H. * vulkan: Further soft_max optimizations Restore the workgroup size of 512 case, use it for >1024. Use unrollable loops for more iteration counts.
…anov#10266) * Add option to set the SYCL architecture for all targets * Convert GGML_SYCL_HIP_TARGET to the more generic GGML_SYCL_ARCH option * Document that setting GGML_SYCL_ARCH can improve the performance
* Add OLMo November 2024 constants * Add OLMo November 2024 converter * Add loading of OLMo November 2024 tensors and hyper parameters * Add building of OLMo November 2024 model
-- While running StableDiffusion.cpp locally with Metal some offsets overflow and results in incorrect calculations
Co-authored-by: arthw <14088817+arthw@users.noreply.github.com>
) * vulkan: Use pipeline_robustness to disable robustness in mul_mat_vec. Add some early returns for nonexistent rows in mul_mat_vec shaders. These can only be hit when dispatching a 2D grid of workgroups. Fix the logic for the 2D grid of workgroups to round up. Enable the pipeline robustness extension if it's available, and use it to disable robustness for these pipelines. The instructions to do the bounds checking contend for the same ALU resources as the bit twiddling dequant instructions. * vulkan: Add GLSL structure aliases for quant types to allow larger loads In Vulkan it's not possible to cast pointer types, so instead you have to declare an aliased binding for the memory with a different type. This commit adds aliases for the quant formats using 16b ints, and in a few places where the struct size is a multiple of 4 also using 32b ints. Currently only q4_k's aliases are used, but others will be used in subsequent commits. * vulkan: use larger loads in q5_k and q6_k shaders. Similar to the optimization I did in q4_k recently, this vectorizes some loads and reduces the number of bit twiddling instructions. * vulkan: use larger K step per iteration in mul_mat_vec. Add vec4 dequantization functions, and use them to do K=8 per iteration in mul_mat_vec. This uses 16b loads for the quant values and 128b loads for B which helps reduce the load on the memory system. The K_PER_ITER==2 logic is still there, just for F16/F32, and really only because they support unaligned sizes. Tweak the num_iters/unrolling logic to be simpler and catch a couple missed unrolling opportunities.
* cmake pkg: find accelerate, openmp, memkind libs * cmake pkg: find BLAS libs * try BLAS_LIBRARIES instead * Add BLAS link opts * Add more link deps. and set GGML_ vars
* cuda : optimize argmax * remove unused parameter ggml-ci * fixup : use full warps ggml-ci * Apply suggestions from code review Co-authored-by: Johannes Gäßler <johannesg@5d6.de> * fix ub * ggml : check ne00 <= INT32_MAX in argmax and argsort --------- Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
…0216) * CANN Support Ascend310P to accelerate F32 and F16 Model * Add compile option soc type macro ASCEND_310P to ggml-cann lib * Remove unused code * Remove the ascend soc_type hard code compile option in CMakelist.txt
* server: avoid overwriting Authorization header If no API key is set, leave the Authorization header as is. It may be used by another part of the Web stack, such as an authenticating proxy. Fixes ggerganov#10854 * rebuild --------- Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* server : add "tokens" output ggml-ci * server : output embeddings for all tokens when pooling = none ggml-ci * server : be explicit about the pooling type in the tests ggml-ci * server : do not normalize embeddings when there is no pooling ggml-ci * llama : add OuteTTS support (wip) * wip * extract features * first conv * group norm * resnet conv * resnet * attn * pos net * layer norm * convnext * head * hann window * fix n_embd + remove llama.cpp hacks * compute hann window * fft * spectrum processing * clean-up * tts : receive input text and generate codes * clip : fix new conv name * tts : minor fix * tts : add header + minor fixes ggml-ci * tts : add matchematical constant ggml-ci * tts : fix sampling + cut initial noise * tts : fixes * tts : update default samplers ggml-ci * tts : text pre-processing * tts : outetts-voc -> wavtokenizer-dec * tts : remove hardcoded constants ggml-ci * tts : fix tensor shapes * llama : refactor wavtokenizer tensors ggml-ci * cont ggml-ci * cont [no ci] * llama : update WavTokenizer to non-causal attn * llama : handle no-vocab detokenization * tts : add Python example for OuteTTS (wip) * tts : extend python example to generate spectrogram ggml-ci * server : fix rebase artifacts * tts : enable "return_tokens" in Python example ggml-ci * tts : minor fixes * common : support HF download for vocoder
* ggml: GGML_NATIVE uses -mcpu=native on ARM Signed-off-by: Adrien Gallouët <angt@huggingface.co> * ggml: Show detected features with GGML_NATIVE Signed-off-by: Adrien Gallouët <angt@huggingface.co> * remove msvc support, add GGML_CPU_ARM_ARCH option * disable llamafile in android example * march -> mcpu, skip adding feature macros ggml-ci --------- Signed-off-by: Adrien Gallouët <angt@huggingface.co> Co-authored-by: Adrien Gallouët <angt@huggingface.co>
Set default width to whatever the terminal is. Also fixed a small bug around default n_gpu_layers value. Signed-off-by: Eric Curtin <ecurtin@redhat.com>
* convert : use GPT2 vocab for Phi-4 model * convert : use null value of sliding_window to distinguish Phi-4 from other PHI3-based models * llama : do not use sliding window attention mask for Phi-4 model --------- Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
* fix: Use gpt2 tokenizer for roberta and add eos/bos tokens Branch: RobertaTokenizer Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fixes to position embeddings Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * map roberta-bpe to gpt-2 Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * fix linting Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> --------- Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> Co-authored-by: Gabe Goodhart <ghart@us.ibm.com>
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* server : fix logprobs, make it openai-compatible * update docs * add std::log * return pre-sampling p * sort before apply softmax * add comment * fix test * set p for sampled token * update docs * add --multi-token-probs * update docs * add `post_sampling_probs` option * update docs [no ci] * remove --multi-token-probs * "top_probs" with "post_sampling_probs" * resolve review comments * rename struct token_prob to prob_info * correct comment placement * fix setting prob for sampled token
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