0.99 rebase #4
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0.99 rebase #4
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* embedding: assign `n_ubatch` value, print error on `n_batch` overflow * Update examples/embedding/embedding.cpp Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> * use %ld instead of %lld * Revert "use %ld instead of %lld" This reverts commit ea753ed. --------- Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* quantize: be able to override metadata by key * minor : spacing --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* iq1_m: basics * iq1_m: basics-2 * iq1_m: CUDA dequantize works Very 1st shot I get PPL = 9.76 for LLaMA-v2-7B. * iq1_m: separate shifts for each group of 8 in a block We get PPL(LLaMA-v2-7B ) = 9.2810 PPL(LLaMA-v2-13B) = 6.8105 Not bad, but slightly higher than sqrt(PPL(IQ1_S) * PPL(IQ2_XXS)) which is the expected outcome given that IQ1_M is halfway between IQ1_S and IQ2_XXS in terms of bpw. From this, we would expect PPL = 9.14 for LLaMA-v2-7B PPL = 6.63 for LLaMA-v2-13B * iq1_m: go to 3-bit scales There is slight increase in PPL, but the 0.0625 bpw reduction in size is totally worth it. We now have PPL(LLaMA-v2-7B ) = 9.4469 at 1.96 bpw PPL(LLaMA-v2-13B) = 6.8717 at 1.93 bpw PPL(LLaMA-v2-70B) = 4.8568 at 1.85 bpw * iq1_m: scalar dot product * iq1_m: AVX2 dot product * iq1_m: very slightly faster AVX2 dot product * iq1_m: ARM_NEON dot product Works, but very slow (10.5 t/s) * iq1_m: Metal - dequantize works, dot product does not * iq1_m: Metal now works About the same performance as iq1_s. * iq1_m: minor * iq1_m: checking pure iq1_m quantization It is pretty bad: PPL(LLaMA-v2-7B) = 34 if we quantize output.weight with Q4_K. * iiq1_m: slightly faster ARM_NEON dot product 10.5 t/s -> 11.65 t/s * iq1_m: faster ARM_NEON dot product 11.65 t/s -> 14.9 t/s * iq1_m: another minor ARM_NEON dot product improvement 14.9 -> 15.0 t/s * iq1_m: small PPL improvement via super-block scale adjustment After quantizing block scales redo the super-block scale fit. PPL(LLaMA-v2-7B ) = 9.3346 PPL(LLaMA-v2-13B) = 6.8419 PPL(LLaMA-v2-70B) = 4.8294 PPL(Mistral-7B ) = 8.1624 * iq1_m: adapt to CUDA refactoring * iq1_m: remove unused variable We have progressed to warnings being errors. * iq1_m: add to backend-ops tests * iq1_m: fix Windows ARM * iq1_m: use common definition of iq1m_scale_t * cuda: assert -> NO_DEVICE_CODE * iq1_M: PR comments --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
* llama : greatly reduce logits memory usage * llama : more compact state saving and reloading * llama : fix lctx.n_outputs not being set before building graph * perplexity : adapt to the logits API changes * perplexity : fix Winogrande, use correct logits for second choice start The first logits used to evaluate the second choice were not from the end of the common prefix; instead, they were the logits from the end of the first choice. This has been corrected. The previous implementation sometimes had outliers in the scores of choices for some tasks, and the logic to skip choices words in the log-likelihood evaluation probably was an attempt to reduce those, but it was complex and didn't quite seem to be the right thing. This is simpler now, and the outlier scores aren't there anymore. * perplexity : normalize spaces and punctuation in Winogrande sentences * llama : fix embedding conditions * llama : fix llama_get_embeddings_ith when the resulting id is 0 * llama : fix wrong n_outputs in llama_set_inputs A mismatch happened when using a smaller n_ubatch than n_batch and then using llama_batch_get_one(). The decision of what n_outputs should be now almost fully depends on how lctx.n_outputs is set in llama_decode_internal. The conditions are simpler this way. * llama : when saving the state, recalculate n_outputs This ensures the correct number of outputs for the entire previous batch is stored in the session file, even when n_ubatch is smaller than n_batch. * llama : fix not-skipping outputs of non-causal models * llama : fix running a batch with n_outputs == 0 It previously worked because lctx.inp_out_ids was not initialized, so it pointed to some garbage address which was somehow still valid when I ran my tests. * llama : keep same graph topology even when n_outputs == 0 * ggml : saner ggml_can_repeat with empty tensors * ggml : future-proof ggml_is_empty by using GGML_MAX_DIMS - 1 * ggml : do not multi-thread ops returning empty tensors * ggml : make ggml_is_empty public and work with views * llama : use a vector for ctx->output_ids * llama : rework reallocation logic for llama_output_reserve Now comparing the actual size with the new total size of the output buffer to allow more efficient enabling and disabling of the embeddings and/or logits output in the future. * ggml : skip empty tensors in all backends * llama : fix llama_output_reserve nullptr deref when new_size is 0 * perplexity : make Winogrande work as it does on master The problems with the Winogrande implementation will need to be fixed in a separate PR to ease review. * llama : clearer error messages for invalid logits or embeddings ids * llama : assert all models that can have inp_out_ids Since the graph topology is now constant, this presence check can be done even when there are no outputs. * llama : assert logits and embd buffers exist before writing to them * llama : handle errors from llama_output_reserve at call sites * perplexity : make hellaswag and multiple-choice outputs identical to master Due to how the KV cache is updated, the logprobs for tokens in a batch are very slightly affected by the other tokens present in the batch, so to make hellaswag and multiple-choice return exactly the same results as on master, the last token of each sequence needs to be evaluated even though its output is not used at all. This will probably be changed back in the future to make these benchmarks a tiny bit faster. * perplexity : fix division by zero when using less than 100 multiple-choice tasks * llama : allow loading state saved with a different ctx size When loading a session file, the context size is now only required to be at least enough to load the KV cells contained in that session file, instead of requiring to use exactly the same context size as when saving. Doing this enables the use-case of extending or shrinking the context size of a saved session. This breaks existing session files because the meaning of kv_buf_size is slightly changed (previously it was the size of the whole KV cache, now it's only the size of the saved part of it). This allows for finer-grained sanity checks when loading in an effort to keep kv_buf_size useful even when the kv_size is changed. * llama : minor ggml-ci * readme : update recent API changes, and warn about Vulkan --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Also use C locale for ispunct/isspace, and split unicode-data.cpp from unicode.cpp.
server: public: support custom `api_url`, default to relative base path
* add php bindings to readme * readme : add link to PR --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Change --no-penalize-nl to --penalize-nl * Update documentation too
* iq1_m: make it work for QK_K = 64 (WIP) * iq1_m: make it work for QK_K = 64 (scalar and AVX2) * iq1_m: QK_K = 64 seems to work on Metal and ARM_NEON --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
* Fix batched impl * Maintain previous behaviour for igpu * retrigger CI --------- Co-authored-by: Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
* embedding : show full embedding for single prompt To support the use case of creating an embedding for a given prompt, the entire embedding and not just the first part needed to be printed. Also, show cosine similarity matrix only if there is more than one prompt, as the cosine similarity matrix for a single prompt is always `1.00`. * Update examples/embedding/embedding.cpp --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Until ggml-org#6346 is resolved
* server: bench: init * server: bench: reduce list of GPU nodes * server: bench: fix graph, fix output artifact * ci: bench: add mermaid in case of image cannot be uploaded * ci: bench: more resilient, more metrics * ci: bench: trigger build * ci: bench: fix duration * ci: bench: fix typo * ci: bench: fix mermaid values, markdown generated * typo on the step name Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> * ci: bench: trailing spaces * ci: bench: move images in a details section * ci: bench: reduce bullet point size --------- Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
initial nix build for windows using zig mingwW64 build removes nix zig windows build removes nix zig windows build removed unnessesary glibc.static removed unnessesary import of pkgs in nix fixed missing trailing newline on non-windows nix builds overriding stdenv when building for crosscompiling to windows in nix better variables when crosscompiling windows in nix cross compile windows on macos removed trailing whitespace remove unnessesary overwrite of "CMAKE_SYSTEM_NAME" in nix windows build nix: keep file extension when copying result files during cross compile for windows nix: better checking for file extensions when using MinGW nix: using hostPlatform instead of targetPlatform when cross compiling for Windows using hostPlatform.extensions.executable to extract executable format
- The generic /usr/bin/env shebangs are good enough - Python deps are provisioned in the devShells - We need to be able to leave python out at least on windows (currently breaks eval)
Take all dependencies from the cross stage, rather tha only stdenv
* doc: fix outdated default value of batch size * doc: add doc for ubatch-size
…at the end of the loop.
…igned reads across a 64 byte boundary.
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