model : Apertus model implementation (#15852)
* First attempt * No permute during convert (fixes qk tensors), proper norm application. * RoPE = NeoX * Coherence! * Migrate xielu params from tensors to hyperparameters * Simple CUDA kernel * Revert stupid LLM refactorings * Chat template support * configchecker / flake8 errors * Reorder unary.cu * I do conclude that LLMs are, in fact, stupid. * Fix after merge * Final newline * Make xIELU an UNARY_OP * Final newline * Correctly account for parameter shift * Argh. * Update ggml/src/ggml-cpu/unary-ops.cpp Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Refactor: remove unused methods, inline and factorize softplus, add const modifiers * Revert CUDA changes, implement xIELU as a separate OP * Pesky newline * Add float2half / half2float for F16 inputs/outputs * CUDA variants, attempt 2 * Actually, attempt 3 * Update ggml/src/ggml-cuda/unary.cu Co-authored-by: Johannes Gäßler <johannesg@5d6.de> * Missing convert header * Proper formula and reference for xIELU in the comments. * Modify unary-ops.cpp to add the functor-based logic besides the template system to retain optimizations * Apply suggestions from code review Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Add tensor mappings for Apertus to global list instead * Fix lazy on scalars * Update ggml/src/ggml-cuda/unary.cu Co-authored-by: Johannes Gäßler <johannesg@5d6.de> * Add comment about the constraints on positive/negative alpha * Change `softplus` to `ggml_softplus` --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Johannes Gäßler <johannesg@5d6.de> Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
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@@ -99,6 +99,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
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{ LLM_ARCH_LLADA_MOE, "llada-moe" },
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{ LLM_ARCH_SEED_OSS, "seed_oss" },
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{ LLM_ARCH_GROVEMOE, "grovemoe" },
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{ LLM_ARCH_APERTUS, "apertus" },
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{ LLM_ARCH_UNKNOWN, "(unknown)" },
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};
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@@ -256,6 +257,11 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
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{ LLM_KV_ADAPTER_LORA_PROMPT_PREFIX, "adapter.lora.prompt_prefix" },
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{ LLM_KV_ADAPTER_ALORA_INVOCATION_TOKENS, "adapter.alora.invocation_tokens" },
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{ LLM_KV_XIELU_ALPHA_N, "xielu.alpha_n" },
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{ LLM_KV_XIELU_ALPHA_P, "xielu.alpha_p" },
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{ LLM_KV_XIELU_BETA, "xielu.beta" },
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{ LLM_KV_XIELU_EPS, "xielu.eps" },
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// deprecated
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{ LLM_KV_TOKENIZER_PREFIX_ID, "tokenizer.ggml.prefix_token_id" },
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{ LLM_KV_TOKENIZER_SUFFIX_ID, "tokenizer.ggml.suffix_token_id" },
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@@ -2119,6 +2125,25 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
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{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" }
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},
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},
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{
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LLM_ARCH_APERTUS,
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{
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{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },
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{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },
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{ LLM_TENSOR_OUTPUT, "output" },
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{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },
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{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },
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{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },
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{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },
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{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },
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{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },
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{ LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" },
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{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" },
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{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },
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{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },
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{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },
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},
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},
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{
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LLM_ARCH_DREAM,
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{
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