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llama.cpp
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llama.cpp
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b8849
src/llama-arch.cpp
906 строк
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Johannes Gäßler
ggml: backend-agnostic tensor parallelism (experimental) (#19378)
09 апр 2026, 17:42
Не верифицирован
09 апр 2026, 17:42
d6f3030
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#include "llama-arch.h" #include "llama-impl.h" #include <map> #include <set> #include <vector> static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = { { LLM_ARCH_CLIP, "clip" }, // dummy, only used by llama-quantize { LLM_ARCH_LLAMA, "llama" }, { LLM_ARCH_LLAMA4, "llama4" }, { LLM_ARCH_DECI, "deci" }, { LLM_ARCH_FALCON, "falcon" }, { LLM_ARCH_GROK, "grok" }, { LLM_ARCH_GPT2, "gpt2" }, { LLM_ARCH_GPTJ, "gptj" }, { LLM_ARCH_GPTNEOX, "gptneox" }, { LLM_ARCH_MPT, "mpt" }, { LLM_ARCH_BAICHUAN, "baichuan" }, { LLM_ARCH_STARCODER, "starcoder" }, { LLM_ARCH_REFACT, "refact" }, { LLM_ARCH_BERT, "bert" }, { LLM_ARCH_MODERN_BERT, "modern-bert" }, { LLM_ARCH_NOMIC_BERT, "nomic-bert" }, { LLM_ARCH_NOMIC_BERT_MOE, "nomic-bert-moe" }, { LLM_ARCH_NEO_BERT, "neo-bert" }, { LLM_ARCH_JINA_BERT_V2, "jina-bert-v2" }, { LLM_ARCH_JINA_BERT_V3, "jina-bert-v3" }, { LLM_ARCH_EUROBERT, "eurobert" }, { LLM_ARCH_BLOOM, "bloom" }, { LLM_ARCH_STABLELM, "stablelm" }, { LLM_ARCH_QWEN, "qwen" }, { LLM_ARCH_QWEN2, "qwen2" }, { LLM_ARCH_QWEN2MOE, "qwen2moe" }, { LLM_ARCH_QWEN2VL, "qwen2vl" }, { LLM_ARCH_QWEN3, "qwen3" }, { LLM_ARCH_QWEN3MOE, "qwen3moe" }, { LLM_ARCH_QWEN3NEXT, "qwen3next" }, { LLM_ARCH_QWEN3VL, "qwen3vl" }, { LLM_ARCH_QWEN3VLMOE, "qwen3vlmoe" }, { LLM_ARCH_QWEN35, "qwen35" }, { LLM_ARCH_QWEN35MOE, "qwen35moe" }, { LLM_ARCH_PHI2, "phi2" }, { LLM_ARCH_PHI3, "phi3" }, { LLM_ARCH_PHIMOE, "phimoe" }, { LLM_ARCH_PLAMO, "plamo" }, { LLM_ARCH_PLAMO2, "plamo2" }, { LLM_ARCH_PLAMO3, "plamo3" }, { LLM_ARCH_CODESHELL, "codeshell" }, { LLM_ARCH_ORION, "orion" }, { LLM_ARCH_INTERNLM2, "internlm2" }, { LLM_ARCH_MINICPM, "minicpm" }, { LLM_ARCH_MINICPM3, "minicpm3" }, { LLM_ARCH_GEMMA, "gemma" }, { LLM_ARCH_GEMMA2, "gemma2" }, { LLM_ARCH_GEMMA3, "gemma3" }, { LLM_ARCH_GEMMA3N, "gemma3n" }, { LLM_ARCH_GEMMA4, "gemma4" }, { LLM_ARCH_GEMMA_EMBEDDING, "gemma-embedding" }, { LLM_ARCH_STARCODER2, "starcoder2" }, { LLM_ARCH_MAMBA, "mamba" }, { LLM_ARCH_MAMBA2, "mamba2" }, { LLM_ARCH_JAMBA, "jamba" }, { LLM_ARCH_FALCON_H1, "falcon-h1" }, { LLM_ARCH_XVERSE, "xverse" }, { LLM_ARCH_COMMAND_R, "command-r" }, { LLM_ARCH_COHERE2, "cohere2" }, { LLM_ARCH_DBRX, "dbrx" }, { LLM_ARCH_OLMO, "olmo" }, { LLM_ARCH_OLMO2, "olmo2" }, { LLM_ARCH_OLMOE, "olmoe" }, { LLM_ARCH_OPENELM, "openelm" }, { LLM_ARCH_ARCTIC, "arctic" }, { LLM_ARCH_DEEPSEEK, "deepseek" }, { LLM_ARCH_DEEPSEEK2, "deepseek2" }, { LLM_ARCH_DEEPSEEK2OCR, "deepseek2-ocr" }, { LLM_ARCH_CHATGLM, "chatglm" }, { LLM_ARCH_GLM4, "glm4" }, { LLM_ARCH_GLM4_MOE, "glm4moe" }, { LLM_ARCH_GLM_DSA, "glm-dsa" }, { LLM_ARCH_BITNET, "bitnet" }, { LLM_ARCH_T5, "t5" }, { LLM_ARCH_T5ENCODER, "t5encoder" }, { LLM_ARCH_JAIS, "jais" }, { LLM_ARCH_JAIS2, "jais2" }, { LLM_ARCH_NEMOTRON, "nemotron" }, { LLM_ARCH_NEMOTRON_H, "nemotron_h" }, { LLM_ARCH_NEMOTRON_H_MOE, "nemotron_h_moe" }, { LLM_ARCH_EXAONE, "exaone" }, { LLM_ARCH_EXAONE4, "exaone4" }, { LLM_ARCH_EXAONE_MOE, "exaone-moe" }, { LLM_ARCH_RWKV6, "rwkv6" }, { LLM_ARCH_RWKV6QWEN2, "rwkv6qwen2" }, { LLM_ARCH_RWKV7, "rwkv7" }, { LLM_ARCH_ARWKV7, "arwkv7" }, { LLM_ARCH_GRANITE, "granite" }, { LLM_ARCH_GRANITE_MOE, "granitemoe" }, { LLM_ARCH_GRANITE_HYBRID, "granitehybrid" }, { LLM_ARCH_CHAMELEON, "chameleon" }, { LLM_ARCH_WAVTOKENIZER_DEC, "wavtokenizer-dec" }, { LLM_ARCH_PLM, "plm" }, { LLM_ARCH_BAILINGMOE, "bailingmoe" }, { LLM_ARCH_BAILINGMOE2, "bailingmoe2" }, { LLM_ARCH_DOTS1, "dots1" }, { LLM_ARCH_ARCEE, "arcee" }, { LLM_ARCH_AFMOE, "afmoe" }, { LLM_ARCH_ERNIE4_5, "ernie4_5" }, { LLM_ARCH_ERNIE4_5_MOE, "ernie4_5-moe" }, { LLM_ARCH_HUNYUAN_MOE, "hunyuan-moe" }, { LLM_ARCH_HUNYUAN_DENSE, "hunyuan-dense" }, { LLM_ARCH_SMOLLM3, "smollm3" }, { LLM_ARCH_OPENAI_MOE, "gpt-oss" }, { LLM_ARCH_LFM2, "lfm2" }, { LLM_ARCH_LFM2MOE, "lfm2moe" }, { LLM_ARCH_DREAM, "dream" }, { LLM_ARCH_SMALLTHINKER, "smallthinker" }, { LLM_ARCH_LLADA, "llada" }, { LLM_ARCH_LLADA_MOE, "llada-moe" }, { LLM_ARCH_SEED_OSS, "seed_oss" }, { LLM_ARCH_GROVEMOE, "grovemoe" }, { LLM_ARCH_APERTUS, "apertus" }, { LLM_ARCH_MINIMAX_M2, "minimax-m2" }, { LLM_ARCH_COGVLM, "cogvlm" }, { LLM_ARCH_RND1, "rnd1" }, { LLM_ARCH_PANGU_EMBED, "pangu-embedded" }, { LLM_ARCH_MISTRAL3, "mistral3" }, { LLM_ARCH_MISTRAL4, "mistral4" }, { LLM_ARCH_PADDLEOCR, "paddleocr" }, { LLM_ARCH_MIMO2, "mimo2" }, { LLM_ARCH_STEP35, "step35" }, { LLM_ARCH_LLAMA_EMBED, "llama-embed" }, { LLM_ARCH_MAINCODER, "maincoder" }, { LLM_ARCH_KIMI_LINEAR, "kimi-linear" }, { LLM_ARCH_UNKNOWN, "(unknown)" }, }; static const std::map<llm_kv, const char *> LLM_KV_NAMES = { { LLM_KV_GENERAL_TYPE, "general.type" }, { LLM_KV_GENERAL_ARCHITECTURE, "general.architecture" }, { LLM_KV_GENERAL_QUANTIZATION_VERSION, "general.quantization_version" }, { LLM_KV_GENERAL_ALIGNMENT, "general.alignment" }, { LLM_KV_GENERAL_FILE_TYPE, "general.file_type" }, { LLM_KV_GENERAL_SAMPLING_SEQUENCE, "general.sampling.sequence" }, { LLM_KV_GENERAL_SAMPLING_TOP_K, "general.sampling.top_k" }, { LLM_KV_GENERAL_SAMPLING_TOP_P, "general.sampling.top_p" }, { LLM_KV_GENERAL_SAMPLING_MIN_P, "general.sampling.min_p" }, { LLM_KV_GENERAL_SAMPLING_XTC_PROBABILITY, "general.sampling.xtc_probability" }, { LLM_KV_GENERAL_SAMPLING_XTC_THRESHOLD, "general.sampling.xtc_threshold" }, { LLM_KV_GENERAL_SAMPLING_TEMP, "general.sampling.temp" }, { LLM_KV_GENERAL_SAMPLING_PENALTY_LAST_N, "general.sampling.penalty_last_n" }, { LLM_KV_GENERAL_SAMPLING_PENALTY_REPEAT, "general.sampling.penalty_repeat" }, { LLM_KV_GENERAL_SAMPLING_MIROSTAT, "general.sampling.mirostat" }, { LLM_KV_GENERAL_SAMPLING_MIROSTAT_TAU, "general.sampling.mirostat_tau" }, { LLM_KV_GENERAL_SAMPLING_MIROSTAT_ETA, "general.sampling.mirostat_eta" }, { LLM_KV_GENERAL_NAME, "general.name" }, { LLM_KV_GENERAL_AUTHOR, "general.author" }, { LLM_KV_GENERAL_VERSION, "general.version" }, { LLM_KV_GENERAL_URL, "general.url" }, { LLM_KV_GENERAL_DESCRIPTION, "general.description" }, { LLM_KV_GENERAL_LICENSE, "general.license" }, { LLM_KV_GENERAL_SOURCE_URL, "general.source.url" }, { LLM_KV_GENERAL_SOURCE_HF_REPO, "general.source.huggingface.repository" }, { LLM_KV_VOCAB_SIZE, "%s.vocab_size" }, { LLM_KV_CONTEXT_LENGTH, "%s.context_length" }, { LLM_KV_EMBEDDING_LENGTH, "%s.embedding_length" }, { LLM_KV_EMBEDDING_LENGTH_OUT, "%s.embedding_length_out" }, { LLM_KV_EMBEDDING_LENGTH_PER_LAYER, "%s.embedding_length_per_layer_input" }, { LLM_KV_FEATURES_LENGTH, "%s.features_length" }, { LLM_KV_BLOCK_COUNT, "%s.block_count" }, { LLM_KV_LEADING_DENSE_BLOCK_COUNT, "%s.leading_dense_block_count" }, { LLM_KV_FEED_FORWARD_LENGTH, "%s.feed_forward_length" }, { LLM_KV_EXPERT_FEED_FORWARD_LENGTH, "%s.expert_feed_forward_length" }, { LLM_KV_EXPERT_SHARED_FEED_FORWARD_LENGTH, "%s.expert_shared_feed_forward_length" }, { LLM_KV_EXPERT_CHUNK_FEED_FORWARD_LENGTH, "%s.expert_chunk_feed_forward_length" }, { LLM_KV_SWIGLU_CLAMP_EXP, "%s.swiglu_clamp_exp" }, { LLM_KV_SWIGLU_CLAMP_SHEXP, "%s.swiglu_clamp_shexp" }, { LLM_KV_USE_PARALLEL_RESIDUAL, "%s.use_parallel_residual" }, { LLM_KV_TENSOR_DATA_LAYOUT, "%s.tensor_data_layout" }, { LLM_KV_EXPERT_COUNT, "%s.expert_count" }, { LLM_KV_EXPERT_USED_COUNT, "%s.expert_used_count" }, { LLM_KV_EXPERT_SHARED_COUNT, "%s.expert_shared_count" }, { LLM_KV_EXPERT_GROUP_COUNT, "%s.expert_group_count" }, { LLM_KV_EXPERT_GROUP_USED_COUNT, "%s.expert_group_used_count" }, { LLM_KV_EXPERT_WEIGHTS_SCALE, "%s.expert_weights_scale" }, { LLM_KV_EXPERT_WEIGHTS_NORM, "%s.expert_weights_norm" }, { LLM_KV_EXPERT_GATING_FUNC, "%s.expert_gating_func" }, { LLM_KV_EXPERT_GROUP_SCALE, "%s.expert_group_scale" }, { LLM_KV_EXPERTS_PER_GROUP, "%s.experts_per_group" }, { LLM_KV_MOE_EVERY_N_LAYERS, "%s.moe_every_n_layers" }, { LLM_KV_MOE_LATENT_SIZE, "%s.moe_latent_size" }, { LLM_KV_NEXTN_PREDICT_LAYERS, "%s.nextn_predict_layers" }, { LLM_KV_NUM_DEEPSTACK_LAYERS, "%s.n_deepstack_layers" }, { LLM_KV_POOLING_TYPE, "%s.pooling_type" }, { LLM_KV_LOGIT_SCALE, "%s.logit_scale" }, { LLM_KV_DECODER_START_TOKEN_ID, "%s.decoder_start_token_id" }, { LLM_KV_DECODER_BLOCK_COUNT, "%s.decoder_block_count" }, { LLM_KV_ATTN_LOGIT_SOFTCAPPING, "%s.attn_logit_softcapping" }, { LLM_KV_ROUTER_LOGIT_SOFTCAPPING, "%s.router_logit_softcapping" }, { LLM_KV_FINAL_LOGIT_SOFTCAPPING, "%s.final_logit_softcapping" }, { LLM_KV_SWIN_NORM, "%s.swin_norm" }, { LLM_KV_RESCALE_EVERY_N_LAYERS, "%s.rescale_every_n_layers" }, { LLM_KV_TIME_MIX_EXTRA_DIM, "%s.time_mix_extra_dim" }, { LLM_KV_TIME_DECAY_EXTRA_DIM, "%s.time_decay_extra_dim" }, { LLM_KV_RESIDUAL_SCALE, "%s.residual_scale" }, { LLM_KV_EMBEDDING_SCALE, "%s.embedding_scale" }, { LLM_KV_TOKEN_SHIFT_COUNT, "%s.token_shift_count" }, { LLM_KV_INTERLEAVE_MOE_LAYER_STEP, "%s.interleave_moe_layer_step" }, { LLM_KV_FULL_ATTENTION_INTERVAL, "%s.full_attention_interval" }, { LLM_KV_ATTENTION_HEAD_COUNT, "%s.attention.head_count" }, { LLM_KV_ATTENTION_HEAD_COUNT_KV, "%s.attention.head_count_kv" }, { LLM_KV_ATTENTION_MAX_ALIBI_BIAS, "%s.attention.max_alibi_bias" }, { LLM_KV_ATTENTION_CLAMP_KQV, "%s.attention.clamp_kqv" }, { LLM_KV_ATTENTION_KEY_LENGTH, "%s.attention.key_length" }, { LLM_KV_ATTENTION_VALUE_LENGTH, "%s.attention.value_length" }, { LLM_KV_ATTENTION_LAYERNORM_EPS, "%s.attention.layer_norm_epsilon" }, { LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, "%s.attention.layer_norm_rms_epsilon" }, { LLM_KV_ATTENTION_GROUPNORM_EPS, "%s.attention.group_norm_epsilon" }, { LLM_KV_ATTENTION_GROUPNORM_GROUPS, "%s.attention.group_norm_groups" }, { LLM_KV_ATTENTION_CAUSAL, "%s.attention.causal" }, { LLM_KV_ATTENTION_Q_LORA_RANK, "%s.attention.q_lora_rank" }, { LLM_KV_ATTENTION_KV_LORA_RANK, "%s.attention.kv_lora_rank" }, { LLM_KV_ATTENTION_DECAY_LORA_RANK, "%s.attention.decay_lora_rank" }, { LLM_KV_ATTENTION_ICLR_LORA_RANK, "%s.attention.iclr_lora_rank" }, { LLM_KV_ATTENTION_VALUE_RESIDUAL_MIX_LORA_RANK, "%s.attention.value_residual_mix_lora_rank" }, { LLM_KV_ATTENTION_GATE_LORA_RANK, "%s.attention.gate_lora_rank" }, { LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT, "%s.attention.relative_buckets_count" }, { LLM_KV_ATTENTION_SLIDING_WINDOW, "%s.attention.sliding_window" }, { LLM_KV_ATTENTION_SLIDING_WINDOW_PATTERN, "%s.attention.sliding_window_pattern" }, { LLM_KV_ATTENTION_SCALE, "%s.attention.scale" }, { LLM_KV_ATTENTION_OUTPUT_SCALE, "%s.attention.output_scale" }, { LLM_KV_ATTENTION_TEMPERATURE_LENGTH, "%s.attention.temperature_length" }, { LLM_KV_ATTENTION_TEMPERATURE_SCALE, "%s.attention.temperature_scale" }, { LLM_KV_ATTENTION_KEY_LENGTH_MLA, "%s.attention.key_length_mla" }, { LLM_KV_ATTENTION_VALUE_LENGTH_MLA, "%s.attention.value_length_mla" }, { LLM_KV_ATTENTION_KEY_LENGTH_SWA, "%s.attention.key_length_swa" }, { LLM_KV_ATTENTION_VALUE_LENGTH_SWA, "%s.attention.value_length_swa" }, { LLM_KV_ATTENTION_INDEXER_HEAD_COUNT, "%s.attention.indexer.head_count" }, { LLM_KV_ATTENTION_INDEXER_KEY_LENGTH, "%s.attention.indexer.key_length" }, { LLM_KV_ATTENTION_INDEXER_TOP_K, "%s.attention.indexer.top_k" }, { LLM_KV_ATTENTION_SHARED_KV_LAYERS, "%s.attention.shared_kv_layers" }, { LLM_KV_ROPE_DIMENSION_COUNT, "%s.rope.dimension_count" }, { LLM_KV_ROPE_DIMENSION_COUNT_SWA, "%s.rope.dimension_count_swa" }, { LLM_KV_ROPE_DIMENSION_SECTIONS, "%s.rope.dimension_sections" }, { LLM_KV_ROPE_FREQ_BASE, "%s.rope.freq_base" }, { LLM_KV_ROPE_FREQ_BASE_SWA, "%s.rope.freq_base_swa" }, { LLM_KV_ROPE_SCALE_LINEAR, "%s.rope.scale_linear" }, { LLM_KV_ROPE_SCALING_TYPE, "%s.rope.scaling.type" }, { LLM_KV_ROPE_SCALING_FACTOR, "%s.rope.scaling.factor" }, { LLM_KV_ROPE_SCALING_ATTN_FACTOR, "%s.rope.scaling.attn_factor" }, { LLM_KV_ROPE_SCALING_ORIG_CTX_LEN, "%s.rope.scaling.original_context_length" }, { LLM_KV_ROPE_SCALING_FINETUNED, "%s.rope.scaling.finetuned" }, { LLM_KV_ROPE_SCALING_YARN_LOG_MUL, "%s.rope.scaling.yarn_log_multiplier" }, { LLM_KV_ROPE_SCALING_YARN_EXT_FACTOR, "%s.rope.scaling.yarn_ext_factor" }, { LLM_KV_ROPE_SCALING_YARN_ATTN_FACTOR, "%s.rope.scaling.yarn_attn_factor" }, { LLM_KV_ROPE_SCALING_YARN_BETA_FAST, "%s.rope.scaling.yarn_beta_fast" }, { LLM_KV_ROPE_SCALING_YARN_BETA_SLOW, "%s.rope.scaling.yarn_beta_slow" }, { LLM_KV_SPLIT_NO, "split.no" }, { LLM_KV_SPLIT_COUNT, "split.count" }, { LLM_KV_SPLIT_TENSORS_COUNT, "split.tensors.count" }, { LLM_KV_SSM_CONV_KERNEL, "%s.ssm.conv_kernel" }, { LLM_KV_SSM_INNER_SIZE, "%s.ssm.inner_size" }, { LLM_KV_SSM_STATE_SIZE, "%s.ssm.state_size" }, { LLM_KV_SSM_TIME_STEP_RANK, "%s.ssm.time_step_rank" }, { LLM_KV_SSM_GROUP_COUNT, "%s.ssm.group_count" }, { LLM_KV_SSM_DT_B_C_RMS, "%s.ssm.dt_b_c_rms" }, { LLM_KV_KDA_HEAD_DIM, "%s.kda.head_dim" }, { LLM_KV_WKV_HEAD_SIZE, "%s.wkv.head_size" }, { LLM_KV_POSNET_EMBEDDING_LENGTH, "%s.posnet.embedding_length" }, { LLM_KV_POSNET_BLOCK_COUNT, "%s.posnet.block_count" }, { LLM_KV_CONVNEXT_EMBEDDING_LENGTH, "%s.convnext.embedding_length" }, { LLM_KV_CONVNEXT_BLOCK_COUNT, "%s.convnext.block_count" }, { LLM_KV_CLASSIFIER_OUTPUT_LABELS, "%s.classifier.output_labels" }, { LLM_KV_SHORTCONV_L_CACHE, "%s.shortconv.l_cache" }, // sentence-transformers dense modules feature dims { LLM_KV_DENSE_2_FEAT_IN, "%s.dense_2_feat_in" }, { LLM_KV_DENSE_2_FEAT_OUT, "%s.dense_2_feat_out" }, { LLM_KV_DENSE_3_FEAT_IN, "%s.dense_3_feat_in" }, { LLM_KV_DENSE_3_FEAT_OUT, "%s.dense_3_feat_out" }, { LLM_KV_TOKENIZER_MODEL, "tokenizer.ggml.model" }, { LLM_KV_TOKENIZER_PRE, "tokenizer.ggml.pre" }, { LLM_KV_TOKENIZER_LIST, "tokenizer.ggml.tokens" }, { LLM_KV_TOKENIZER_TOKEN_TYPE, "tokenizer.ggml.token_type" }, { LLM_KV_TOKENIZER_TOKEN_TYPE_COUNT, "tokenizer.ggml.token_type_count" }, { LLM_KV_TOKENIZER_SCORES, "tokenizer.ggml.scores" }, { LLM_KV_TOKENIZER_MERGES, "tokenizer.ggml.merges" }, { LLM_KV_TOKENIZER_BOS_ID, "tokenizer.ggml.bos_token_id" }, { LLM_KV_TOKENIZER_EOS_ID, "tokenizer.ggml.eos_token_id" }, { LLM_KV_TOKENIZER_EOT_ID, "tokenizer.ggml.eot_token_id" }, { LLM_KV_TOKENIZER_EOM_ID, "tokenizer.ggml.eom_token_id" }, { LLM_KV_TOKENIZER_UNK_ID, "tokenizer.ggml.unknown_token_id" }, { LLM_KV_TOKENIZER_SEP_ID, "tokenizer.ggml.seperator_token_id" }, { LLM_KV_TOKENIZER_PAD_ID, "tokenizer.ggml.padding_token_id" }, { LLM_KV_TOKENIZER_CLS_ID, "tokenizer.ggml.cls_token_id" }, { LLM_KV_TOKENIZER_MASK_ID, "tokenizer.ggml.mask_token_id" }, { LLM_KV_TOKENIZER_ADD_BOS, "tokenizer.ggml.add_bos_token" }, { LLM_KV_TOKENIZER_ADD_EOS, "tokenizer.ggml.add_eos_token" }, { LLM_KV_TOKENIZER_ADD_SEP, "tokenizer.ggml.add_sep_token" }, { LLM_KV_TOKENIZER_ADD_PREFIX, "tokenizer.ggml.add_space_prefix" }, { LLM_KV_TOKENIZER_REMOVE_EXTRA_WS, "tokenizer.ggml.remove_extra_whitespaces" }, { LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP, "tokenizer.ggml.precompiled_charsmap" }, { LLM_KV_TOKENIZER_HF_JSON, "tokenizer.huggingface.json" }, { LLM_KV_TOKENIZER_RWKV, "tokenizer.rwkv.world" }, { LLM_KV_TOKENIZER_CHAT_TEMPLATE, "tokenizer.chat_template" }, { LLM_KV_TOKENIZER_FIM_PRE_ID, "tokenizer.ggml.fim_pre_token_id" }, { LLM_KV_TOKENIZER_FIM_SUF_ID, "tokenizer.ggml.fim_suf_token_id" }, { LLM_KV_TOKENIZER_FIM_MID_ID, "tokenizer.ggml.fim_mid_token_id" }, { LLM_KV_TOKENIZER_FIM_PAD_ID, "tokenizer.ggml.fim_pad_token_id" }, { LLM_KV_TOKENIZER_FIM_REP_ID, "tokenizer.ggml.fim_rep_token_id" }, { LLM_KV_TOKENIZER_FIM_SEP_ID, "tokenizer.ggml.fim_sep_token_id" }, { LLM_KV_ADAPTER_TYPE, "adapter.type" }, { LLM_KV_ADAPTER_LORA_ALPHA, "adapter.lora.alpha" }, { LLM_KV_ADAPTER_LORA_TASK_NAME, "adapter.lora.task_name" }, { LLM_KV_ADAPTER_LORA_PROMPT_PREFIX, "adapter.lora.prompt_prefix" }, { LLM_KV_ADAPTER_ALORA_INVOCATION_TOKENS, "adapter.alora.invocation_tokens" }, { LLM_KV_XIELU_ALPHA_N, "xielu.alpha_n" }, { LLM_KV_XIELU_ALPHA_P, "xielu.alpha_p" }, { LLM_KV_XIELU_BETA, "xielu.beta" }, { LLM_KV_XIELU_EPS, "xielu.eps" }, // deprecated { LLM_KV_TOKENIZER_PREFIX_ID, "tokenizer.ggml.prefix_token_id" }, { LLM_KV_TOKENIZER_SUFFIX_ID, "tokenizer.ggml.suffix_token_id" }, { LLM_KV_TOKENIZER_MIDDLE_ID, "tokenizer.ggml.middle_token_id" }, }; static const std::map<llm_tensor, const char *> LLM_TENSOR_NAMES = { { LLM_TENSOR_TOKEN_EMBD, "token_embd" }, { LLM_TENSOR_OUTPUT_NORM, "output_norm" }, { LLM_TENSOR_OUTPUT_NORM_LFM2, "token_embd_norm" }, // fix for wrong tensor name { LLM_TENSOR_OUTPUT, "output" }, { LLM_TENSOR_ROPE_FREQS, "rope_freqs" }, { LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" }, { LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" }, { LLM_TENSOR_ATTN_K, "blk.%d.attn_k" }, { LLM_TENSOR_ATTN_V, "blk.%d.attn_v" }, { LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" }, { LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" }, { LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" }, { LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" }, { LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" }, { LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" }, { LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" }, { LLM_TENSOR_FFN_GATE_EXP, "blk.%d.ffn_gate.%d" }, { LLM_TENSOR_FFN_DOWN_EXP, "blk.%d.ffn_down.%d" }, { LLM_TENSOR_FFN_UP_EXP, "blk.%d.ffn_up.%d" }, { LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" }, { LLM_TENSOR_FFN_GATE_UP_EXPS, "blk.%d.ffn_gate_up_exps" }, { LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" }, { LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" }, { LLM_TENSOR_ATTN_POST_NORM, "blk.%d.post_attention_norm" }, { LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" }, { LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" }, { LLM_TENSOR_ATTN_GATE, "blk.%d.attn_gate" }, { LLM_TENSOR_FFN_POST_NORM, "blk.%d.post_ffw_norm" }, { LLM_TENSOR_FFN_POST_NORM_1, "blk.%d.post_ffw_norm_1" }, { LLM_TENSOR_FFN_POST_NORM_2, "blk.%d.post_ffw_norm_2" }, { LLM_TENSOR_FFN_PRE_NORM_2, "blk.%d.pre_ffw_norm_2" }, { LLM_TENSOR_FFN_GATE_SHEXP, "blk.%d.ffn_gate_shexp" }, { LLM_TENSOR_FFN_UP_SHEXP, "blk.%d.ffn_up_shexp" }, { LLM_TENSOR_FFN_DOWN_SHEXP, "blk.%d.ffn_down_shexp" }, { LLM_TENSOR_FFN_EXP_PROBS_B, "blk.%d.exp_probs_b" }, { LLM_TENSOR_FFN_LATENT_DOWN, "blk.%d.ffn_latent_down" }, { LLM_TENSOR_FFN_LATENT_UP, "blk.%d.ffn_latent_up" }, { LLM_TENSOR_ATTN_NORM_2, "blk.%d.attn_norm_2" }, { LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" }, { LLM_TENSOR_LAYER_OUT_NORM, "blk.%d.layer_output_norm" }, { LLM_TENSOR_LAYER_OUT_SCALE, "blk.%d.layer_output_scale" }, { LLM_TENSOR_ATTN_OUT_NORM, "blk.%d.attn_output_norm" }, { LLM_TENSOR_POS_EMBD, "position_embd" }, { LLM_TENSOR_FFN_ACT, "blk.%d.ffn.act" }, { LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" }, { LLM_TENSOR_TOKEN_TYPES, "token_types" }, { LLM_TENSOR_CLS, "cls" }, { LLM_TENSOR_CLS_OUT, "cls.output" }, { LLM_TENSOR_CLS_NORM, "cls.norm" }, { LLM_TENSOR_ENC_OUTPUT_NORM, "enc.output_norm" }, { LLM_TENSOR_FFN_GATE_INP_SHEXP, "blk.%d.ffn_gate_inp_shexp" }, { LLM_TENSOR_SSM_A_NOSCAN, "blk.%d.ssm_a" }, { LLM_TENSOR_SSM_CONV1D, "blk.%d.ssm_conv1d" }, { LLM_TENSOR_SSM_DT, "blk.%d.ssm_dt" }, { LLM_TENSOR_SSM_BETA_ALPHA, "blk.%d.ssm_ba" }, { LLM_TENSOR_SSM_ALPHA, "blk.%d.ssm_alpha" }, { LLM_TENSOR_SSM_IN, "blk.%d.ssm_in" }, { LLM_TENSOR_SSM_NORM, "blk.%d.ssm_norm" }, { LLM_TENSOR_SSM_OUT, "blk.%d.ssm_out" }, { LLM_TENSOR_ROPE_FACTORS_LONG, "rope_factors_long" }, { LLM_TENSOR_ROPE_FACTORS_SHORT, "rope_factors_short" }, { LLM_TENSOR_SSM_X, "blk.%d.ssm_x" }, { LLM_TENSOR_SSM_A, "blk.%d.ssm_a" }, { LLM_TENSOR_SSM_D, "blk.%d.ssm_d" }, { LLM_TENSOR_SSM_DT_NORM, "blk.%d.ssm_dt_norm" }, { LLM_TENSOR_SSM_B_NORM, "blk.%d.ssm_b_norm" }, { LLM_TENSOR_SSM_C_NORM, "blk.%d.ssm_c_norm" }, { LLM_TENSOR_SSM_CONV1D_Q, "blk.%d.ssm_conv1d_q" }, { LLM_TENSOR_SSM_CONV1D_K, "blk.%d.ssm_conv1d_k" }, { LLM_TENSOR_SSM_CONV1D_V, "blk.%d.ssm_conv1d_v" }, { LLM_TENSOR_SSM_F_A, "blk.%d.ssm_f_a" }, { LLM_TENSOR_SSM_F_B, "blk.%d.ssm_f_b" }, { LLM_TENSOR_SSM_BETA, "blk.%d.ssm_beta" }, { LLM_TENSOR_SSM_G_A, "blk.%d.ssm_g_a" }, { LLM_TENSOR_SSM_G_B, "blk.%d.ssm_g_b" }, { LLM_TENSOR_SSM_NORM, "blk.%d.ssm_norm" }, { LLM_TENSOR_ATTN_Q_A_NORM, "blk.%d.attn_q_a_norm" }, { LLM_TENSOR_ATTN_KV_A_NORM, "blk.%d.attn_kv_a_norm" }, { LLM_TENSOR_ATTN_Q_A, "blk.%d.attn_q_a" }, { LLM_TENSOR_ATTN_Q_B, "blk.%d.attn_q_b" }, { LLM_TENSOR_ATTN_KV_A_MQA, "blk.%d.attn_kv_a_mqa" }, { LLM_TENSOR_ATTN_KV_B, "blk.%d.attn_kv_b" }, { LLM_TENSOR_PER_LAYER_TOKEN_EMBD, "per_layer_token_embd" }, { LLM_TENSOR_PER_LAYER_MODEL_PROJ, "per_layer_model_proj" }, { LLM_TENSOR_PER_LAYER_PROJ_NORM, "per_layer_proj_norm" }, { LLM_TENSOR_ALTUP_UNEMBD_PROJ, "altup_unembd_proj" }, { LLM_TENSOR_ALTUP_PROJ, "altup_proj" }, { LLM_TENSOR_PER_LAYER_INP_GATE, "blk.%d.inp_gate" }, { LLM_TENSOR_PER_LAYER_PROJ, "blk.%d.proj" }, { LLM_TENSOR_PER_LAYER_POST_NORM, "blk.%d.post_norm" }, { LLM_TENSOR_ALTUP_CORRECT_COEF, "blk.%d.altup_correct_coef" }, { LLM_TENSOR_ALTUP_CORRECT_SCALE, "blk.%d.altup_correct_scale" }, { LLM_TENSOR_ALTUP_PREDICT_COEF, "blk.%d.altup_predict_coef" }, { LLM_TENSOR_ALTUP_ROUTER, "blk.%d.altup_router" }, { LLM_TENSOR_ALTUP_ROUTER_NORM, "blk.%d.altup_router_norm" }, { LLM_TENSOR_LAUREL_L, "blk.%d.laurel_l" }, { LLM_TENSOR_LAUREL_R, "blk.%d.laurel_r" }, { LLM_TENSOR_LAUREL_POST_NORM, "blk.%d.laurel_post_norm" }, { LLM_TENSOR_DENSE_2_OUT, "dense_2" }, { LLM_TENSOR_DENSE_3_OUT, "dense_3" }, { LLM_TENSOR_FFN_NORM_EXPS, "blk.%d.ffn_norm_exps" }, { LLM_TENSOR_ATTN_K_B, "blk.%d.attn_k_b" }, { LLM_TENSOR_ATTN_V_B, "blk.%d.attn_v_b" }, { LLM_TENSOR_NEXTN_EH_PROJ, "blk.%d.nextn.eh_proj" }, { LLM_TENSOR_NEXTN_EMBED_TOKENS, "blk.%d.nextn.embed_tokens" }, { LLM_TENSOR_NEXTN_ENORM, "blk.%d.nextn.enorm" }, { LLM_TENSOR_NEXTN_HNORM, "blk.%d.nextn.hnorm" }, { LLM_TENSOR_NEXTN_SHARED_HEAD_HEAD, "blk.%d.nextn.shared_head_head" }, { LLM_TENSOR_NEXTN_SHARED_HEAD_NORM, "blk.%d.nextn.shared_head_norm" }, { LLM_TENSOR_ATTN_SUB_NORM, "blk.%d.attn_sub_norm" }, { LLM_TENSOR_FFN_SUB_NORM, "blk.%d.ffn_sub_norm" }, { LLM_TENSOR_DEC_OUTPUT_NORM, "dec.output_norm" }, { LLM_TENSOR_DEC_ATTN_NORM, "dec.blk.%d.attn_norm" }, { LLM_TENSOR_DEC_ATTN_Q, "dec.blk.%d.attn_q" }, { LLM_TENSOR_DEC_ATTN_K, "dec.blk.%d.attn_k" }, { LLM_TENSOR_DEC_ATTN_V, "dec.blk.%d.attn_v" }, { LLM_TENSOR_DEC_ATTN_OUT, "dec.blk.%d.attn_o" }, { LLM_TENSOR_DEC_ATTN_REL_B, "dec.blk.%d.attn_rel_b" }, { LLM_TENSOR_DEC_CROSS_ATTN_NORM, "dec.blk.%d.cross_attn_norm" }, { LLM_TENSOR_DEC_CROSS_ATTN_Q, "dec.blk.%d.cross_attn_q" }, { LLM_TENSOR_DEC_CROSS_ATTN_K, "dec.blk.%d.cross_attn_k" }, { LLM_TENSOR_DEC_CROSS_ATTN_V, "dec.blk.%d.cross_attn_v" }, { LLM_TENSOR_DEC_CROSS_ATTN_OUT, "dec.blk.%d.cross_attn_o" }, { LLM_TENSOR_DEC_CROSS_ATTN_REL_B, "dec.blk.%d.cross_attn_rel_b" }, { LLM_TENSOR_DEC_FFN_NORM, "dec.blk.%d.ffn_norm" }, { LLM_TENSOR_DEC_FFN_GATE, "dec.blk.%d.ffn_gate" }, { LLM_TENSOR_DEC_FFN_DOWN, "dec.blk.%d.ffn_down" }, { LLM_TENSOR_DEC_FFN_UP, "dec.blk.%d.ffn_up" }, { LLM_TENSOR_ENC_ATTN_NORM, "enc.blk.%d.attn_norm" }, { LLM_TENSOR_ENC_ATTN_Q, "enc.blk.%d.attn_q" }, { LLM_TENSOR_ENC_ATTN_K, "enc.blk.%d.attn_k" }, { LLM_TENSOR_ENC_ATTN_V, "enc.blk.%d.attn_v" }, { LLM_TENSOR_ENC_ATTN_OUT, "enc.blk.%d.attn_o" }, { LLM_TENSOR_ENC_ATTN_REL_B, "enc.blk.%d.attn_rel_b" }, { LLM_TENSOR_ENC_FFN_NORM, "enc.blk.%d.ffn_norm" }, { LLM_TENSOR_ENC_FFN_GATE, "enc.blk.%d.ffn_gate" }, { LLM_TENSOR_ENC_FFN_DOWN, "enc.blk.%d.ffn_down" }, { LLM_TENSOR_ENC_FFN_UP, "enc.blk.%d.ffn_up" }, { LLM_TENSOR_TIME_MIX_W1, "blk.%d.time_mix_w1" }, { LLM_TENSOR_TIME_MIX_W2, "blk.%d.time_mix_w2" }, { LLM_TENSOR_TIME_MIX_LERP_X, "blk.%d.time_mix_lerp_x" }, { LLM_TENSOR_TIME_MIX_LERP_W, "blk.%d.time_mix_lerp_w" }, { LLM_TENSOR_TIME_MIX_LERP_K, "blk.%d.time_mix_lerp_k" }, { LLM_TENSOR_TIME_MIX_LERP_V, "blk.%d.time_mix_lerp_v" }, { LLM_TENSOR_TIME_MIX_LERP_R, "blk.%d.time_mix_lerp_r" }, { LLM_TENSOR_TIME_MIX_LERP_G, "blk.%d.time_mix_lerp_g" }, { LLM_TENSOR_TIME_MIX_LERP_FUSED, "blk.%d.time_mix_lerp_fused" }, { LLM_TENSOR_TIME_MIX_FIRST, "blk.%d.time_mix_first" }, { LLM_TENSOR_TIME_MIX_DECAY, "blk.%d.time_mix_decay" }, { LLM_TENSOR_TIME_MIX_DECAY_W1, "blk.%d.time_mix_decay_w1" }, { LLM_TENSOR_TIME_MIX_DECAY_W2, "blk.%d.time_mix_decay_w2" }, { LLM_TENSOR_TIME_MIX_KEY, "blk.%d.time_mix_key" }, { LLM_TENSOR_TIME_MIX_VALUE, "blk.%d.time_mix_value" }, { LLM_TENSOR_TIME_MIX_RECEPTANCE, "blk.%d.time_mix_receptance" }, { LLM_TENSOR_TIME_MIX_GATE, "blk.%d.time_mix_gate" }, { LLM_TENSOR_TIME_MIX_LN, "blk.%d.time_mix_ln" }, { LLM_TENSOR_TIME_MIX_OUTPUT, "blk.%d.time_mix_output" }, { LLM_TENSOR_CHANNEL_MIX_LERP_K, "blk.%d.channel_mix_lerp_k" }, { LLM_TENSOR_CHANNEL_MIX_LERP_R, "blk.%d.channel_mix_lerp_r" }, { LLM_TENSOR_CHANNEL_MIX_KEY, "blk.%d.channel_mix_key" }, { LLM_TENSOR_CHANNEL_MIX_VALUE, "blk.%d.channel_mix_value" }, { LLM_TENSOR_CHANNEL_MIX_RECEPTANCE, "blk.%d.channel_mix_receptance" }, { LLM_TENSOR_TIME_MIX_W0, "blk.%d.time_mix_w0" }, { LLM_TENSOR_TIME_MIX_A0, "blk.%d.time_mix_a0" }, { LLM_TENSOR_TIME_MIX_A1, "blk.%d.time_mix_a1" }, { LLM_TENSOR_TIME_MIX_A2, "blk.%d.time_mix_a2" }, { LLM_TENSOR_TIME_MIX_V0, "blk.%d.time_mix_v0" }, { LLM_TENSOR_TIME_MIX_V1, "blk.%d.time_mix_v1" }, { LLM_TENSOR_TIME_MIX_V2, "blk.%d.time_mix_v2" }, { LLM_TENSOR_TIME_MIX_G1, "blk.%d.time_mix_g1" }, { LLM_TENSOR_TIME_MIX_G2, "blk.%d.time_mix_g2" }, { LLM_TENSOR_TIME_MIX_K_K, "blk.%d.time_mix_k_k" }, { LLM_TENSOR_TIME_MIX_K_A, "blk.%d.time_mix_k_a" }, { LLM_TENSOR_TIME_MIX_R_K, "blk.%d.time_mix_r_k" }, { LLM_TENSOR_CONV1D, "conv1d" }, { LLM_TENSOR_CONVNEXT_DW, "convnext.%d.dw" }, { LLM_TENSOR_CONVNEXT_NORM, "convnext.%d.norm" }, { LLM_TENSOR_CONVNEXT_PW1, "convnext.%d.pw1" }, { LLM_TENSOR_CONVNEXT_PW2, "convnext.%d.pw2" }, { LLM_TENSOR_CONVNEXT_GAMMA, "convnext.%d.gamma" }, { LLM_TENSOR_POS_NET_CONV1, "posnet.%d.conv1" }, { LLM_TENSOR_POS_NET_CONV2, "posnet.%d.conv2" }, { LLM_TENSOR_POS_NET_NORM, "posnet.%d.norm" }, { LLM_TENSOR_POS_NET_NORM1, "posnet.%d.norm1" }, { LLM_TENSOR_POS_NET_NORM2, "posnet.%d.norm2" }, { LLM_TENSOR_POS_NET_ATTN_NORM, "posnet.%d.attn_norm" }, { LLM_TENSOR_POS_NET_ATTN_Q, "posnet.%d.attn_q" }, { LLM_TENSOR_POS_NET_ATTN_K, "posnet.%d.attn_k" }, { LLM_TENSOR_POS_NET_ATTN_V, "posnet.%d.attn_v" }, { LLM_TENSOR_POS_NET_ATTN_OUT, "posnet.%d.attn_output" }, { LLM_TENSOR_ATTN_SINKS, "blk.%d.attn_sinks" }, { LLM_TENSOR_SHORTCONV_CONV, "blk.%d.shortconv.conv" }, { LLM_TENSOR_SHORTCONV_INPROJ, "blk.%d.shortconv.in_proj" }, { LLM_TENSOR_SHORTCONV_OUTPROJ, "blk.%d.shortconv.out_proj" }, { LLM_TENSOR_FFN_GATE_CHEXPS, "blk.%d.ffn_gate_chexps" }, { LLM_TENSOR_FFN_DOWN_CHEXPS, "blk.%d.ffn_down_chexps" }, { LLM_TENSOR_FFN_UP_CHEXPS, "blk.%d.ffn_up_chexps" }, { LLM_TENSOR_VISEXP_ATTN_QKV, "blk.%d.vis_attn_qkv" }, { LLM_TENSOR_VISEXP_ATTN_OUT, "blk.%d.vis_attn_output" }, { LLM_TENSOR_VISEXP_FFN_GATE, "blk.%d.vis_gate" }, { LLM_TENSOR_VISEXP_FFN_DOWN, "blk.%d.vis_down" }, { LLM_TENSOR_VISEXP_FFN_UP, "blk.%d.vis_up" }, { LLM_TENSOR_INDEXER_K_NORM, "blk.%d.indexer.k_norm" }, { LLM_TENSOR_INDEXER_PROJ, "blk.%d.indexer.proj" }, { LLM_TENSOR_INDEXER_ATTN_K, "blk.%d.indexer.attn_k" }, { LLM_TENSOR_INDEXER_ATTN_Q_B, "blk.%d.indexer.attn_q_b" }, }; // declare information about the model weight tensors: // - the layer in which the tensor is going to be used. this is needed in order to assign the correct buffer type for the weight // - the operator which is going to use the weight. this is needed to determine if the respective backend supports the operator // // for example, input layers are usually assigned to CPU/host buffer types // // a mismatch between the declared information and the actual layer/op in which the tensor is used can lead to sub-optimal // assignment of the buffer types and extra overhead during computation // example: https://github.com/ggml-org/llama.cpp/pull/17548 // static const std::map<llm_tensor, llm_tensor_info> LLM_TENSOR_INFOS = { {LLM_TENSOR_TOKEN_EMBD, {LLM_TENSOR_LAYER_INPUT, GGML_OP_GET_ROWS}}, {LLM_TENSOR_POS_EMBD, {LLM_TENSOR_LAYER_INPUT, GGML_OP_GET_ROWS}}, {LLM_TENSOR_TOKEN_TYPES, {LLM_TENSOR_LAYER_INPUT, GGML_OP_GET_ROWS}}, {LLM_TENSOR_TOKEN_EMBD_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, // do the norms on the first layer (not the input layer) {LLM_TENSOR_OUTPUT, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}}, {LLM_TENSOR_CLS, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}}, {LLM_TENSOR_CLS_OUT, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}}, {LLM_TENSOR_CLS_NORM, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL}}, {LLM_TENSOR_DENSE_2_OUT, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}}, // Dense layer output {LLM_TENSOR_DENSE_3_OUT, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}}, // Dense layer output {LLM_TENSOR_OUTPUT_NORM, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL}}, {LLM_TENSOR_OUTPUT_NORM_LFM2, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL}}, {LLM_TENSOR_DEC_OUTPUT_NORM, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL}}, {LLM_TENSOR_ENC_OUTPUT_NORM, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL}}, {LLM_TENSOR_ROPE_FREQS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ROPE}}, {LLM_TENSOR_ROPE_FACTORS_LONG, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ROPE}}, {LLM_TENSOR_ROPE_FACTORS_SHORT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ROPE}}, {LLM_TENSOR_ATTN_Q, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_V, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_QKV, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_OUT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_GATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_FFN_GATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_FFN_DOWN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_FFN_UP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_FFN_DOWN_SHEXP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_FFN_GATE_SHEXP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_FFN_UP_SHEXP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_Q_A, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_Q_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_KV_A_MQA, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_KV_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_K_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_V_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ATTN_SINKS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_SCALE}}, {LLM_TENSOR_DEC_ATTN_Q, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_ATTN_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_ATTN_V, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_ATTN_OUT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_CROSS_ATTN_Q, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_CROSS_ATTN_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_CROSS_ATTN_V, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_CROSS_ATTN_OUT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_FFN_GATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_FFN_DOWN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_DEC_FFN_UP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ENC_ATTN_Q, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ENC_ATTN_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ENC_ATTN_V, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ENC_ATTN_OUT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ENC_FFN_GATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ENC_FFN_DOWN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ENC_FFN_UP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_FFN_GATE_INP_SHEXP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_FFN_GATE_INP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_IN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_X, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_DT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_OUT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_ALPHA, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_BETA_ALPHA, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_W1, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_W2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_A1, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_A2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_V1, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_V2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_G1, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_G2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_DECAY_W1, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_DECAY_W2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_KEY, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_VALUE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_RECEPTANCE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_GATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_OUTPUT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_CHANNEL_MIX_KEY, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_CHANNEL_MIX_RECEPTANCE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_CHANNEL_MIX_VALUE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_FFN_ACT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_DIV}}, {LLM_TENSOR_SSM_CONV1D, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_SSM_CONV}}, {LLM_TENSOR_SSM_A, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_SSM_SCAN}}, {LLM_TENSOR_SSM_A_NOSCAN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, // a version of SSM_A used for MUL instead of SSM_SCAN {LLM_TENSOR_SSM_DT_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_SSM_B_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_SSM_C_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_SSM_D, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_SSM_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, // Kimi KDA - Conv tensors are 4D [d_conv, 1, d_inner, 1], reshaped to 2D at runtime {LLM_TENSOR_SSM_CONV1D_Q, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_SSM_CONV1D_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_SSM_CONV1D_V, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_SSM_F_A, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_F_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_BETA, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_G_A, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SSM_G_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_TIME_MIX_LERP_X, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_TIME_MIX_LN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_CHANNEL_MIX_LERP_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_CHANNEL_MIX_LERP_R, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_TIME_MIX_K_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_TIME_MIX_K_A, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_TIME_MIX_R_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_TIME_MIX_LERP_W, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_LERP_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_LERP_V, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_LERP_R, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_LERP_G, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_LERP_FUSED, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_DECAY, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_W0, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_A0, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_V0, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, {LLM_TENSOR_TIME_MIX_FIRST, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_RWKV_WKV6}}, {LLM_TENSOR_ATTN_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ATTN_NORM_2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ATTN_OUT_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ATTN_POST_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_FFN_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_FFN_PRE_NORM_2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_FFN_POST_NORM_1, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_FFN_POST_NORM_2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_FFN_POST_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_FFN_NORM_EXPS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ATTN_Q_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ATTN_K_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_LAYER_OUT_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_LAYER_OUT_SCALE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ATTN_Q_A_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ATTN_KV_A_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ATTN_SUB_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_FFN_SUB_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_DEC_ATTN_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_DEC_CROSS_ATTN_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_DEC_FFN_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ENC_ATTN_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ENC_FFN_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_DEC_ATTN_REL_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_GET_ROWS}}, {LLM_TENSOR_ENC_ATTN_REL_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_GET_ROWS}}, {LLM_TENSOR_FFN_DOWN_EXPS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT_ID}}, {LLM_TENSOR_FFN_GATE_EXPS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT_ID}}, {LLM_TENSOR_FFN_UP_EXPS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT_ID}}, {LLM_TENSOR_FFN_GATE_UP_EXPS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT_ID}}, {LLM_TENSOR_FFN_DOWN_CHEXPS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT_ID}}, {LLM_TENSOR_FFN_GATE_CHEXPS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT_ID}}, {LLM_TENSOR_FFN_UP_CHEXPS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT_ID}}, {LLM_TENSOR_FFN_EXP_PROBS_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}}, // altup / laurel (gemma 3n) {LLM_TENSOR_PER_LAYER_TOKEN_EMBD, {LLM_TENSOR_LAYER_INPUT, GGML_OP_GET_ROWS}}, {LLM_TENSOR_PER_LAYER_MODEL_PROJ, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_PER_LAYER_PROJ_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ALTUP_PROJ, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ALTUP_UNEMBD_PROJ, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}}, {LLM_TENSOR_PER_LAYER_INP_GATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_PER_LAYER_PROJ, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_PER_LAYER_POST_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ALTUP_CORRECT_COEF, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ALTUP_CORRECT_SCALE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_ALTUP_PREDICT_COEF, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ALTUP_ROUTER, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_ALTUP_ROUTER_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_LAUREL_L, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_LAUREL_R, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_LAUREL_POST_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, // this tensor is loaded for T5, but never used {LLM_TENSOR_DEC_CROSS_ATTN_REL_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_NONE}}, {LLM_TENSOR_CONV1D, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_IM2COL}}, {LLM_TENSOR_POS_NET_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_POS_NET_NORM1, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_POS_NET_NORM2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_POS_NET_CONV1, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_IM2COL}}, {LLM_TENSOR_POS_NET_CONV2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_IM2COL}}, {LLM_TENSOR_POS_NET_ATTN_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_POS_NET_ATTN_Q, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_POS_NET_ATTN_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_POS_NET_ATTN_V, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_POS_NET_ATTN_OUT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_CONVNEXT_DW, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_IM2COL}}, {LLM_TENSOR_CONVNEXT_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_CONVNEXT_PW1, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_CONVNEXT_PW2, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_CONVNEXT_GAMMA, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_SHORTCONV_CONV, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_SSM_CONV}}, {LLM_TENSOR_SHORTCONV_INPROJ, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_SHORTCONV_OUTPROJ, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_VISEXP_ATTN_QKV, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_VISEXP_ATTN_OUT, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_VISEXP_FFN_GATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_VISEXP_FFN_DOWN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_VISEXP_FFN_UP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_INDEXER_K_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_INDEXER_PROJ, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_INDEXER_ATTN_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, {LLM_TENSOR_INDEXER_ATTN_Q_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}}, // NextN/MTP tensors are currently ignored (reserved for future MTP support) // These tensors only exist in the last layer(s) and are treated as output tensors {LLM_TENSOR_NEXTN_EH_PROJ, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}}, {LLM_TENSOR_NEXTN_EMBED_TOKENS, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_GET_ROWS}}, {LLM_TENSOR_NEXTN_ENORM, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_GET_ROWS}}, {LLM_TENSOR_NEXTN_HNORM, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL}}, {LLM_TENSOR_NEXTN_SHARED_HEAD_HEAD, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}}, {LLM_TENSOR_NEXTN_SHARED_HEAD_NORM, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL}}, // Nemotron 3 Super {LLM_TENSOR_FFN_LATENT_DOWN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, {LLM_TENSOR_FFN_LATENT_UP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}}, }; LLM_KV::LLM_KV(llm_arch arch, const char * suffix) : arch(arch), suffix(suffix) {} std::string LLM_KV::operator()(llm_kv kv) const { std::string name = ::format(LLM_KV_NAMES.at(kv), LLM_ARCH_NAMES.at(arch)); if (suffix != nullptr) { name += "."; name += suffix; } return name; } LLM_TN_IMPL::LLM_TN_IMPL(llm_arch arch, llm_tensor tensor, const char * suffix, int bid, int xid) : arch(arch), tensor(tensor), suffix(suffix), bid(bid), xid(xid) {} std::string LLM_TN_IMPL::str() const { if (LLM_TENSOR_NAMES.find(tensor) == LLM_TENSOR_NAMES.end()) { GGML_ABORT("unknown tensor name for tensor id %d", static_cast<int>(tensor)); } std::string name = ::format(LLM_TENSOR_NAMES.at(tensor), bid, xid); if (suffix != nullptr) { name += "."; name += suffix; } return name; } std::vector<llm_arch> llm_arch_all() { std::vector<llm_arch> ret; ret.reserve(LLM_ARCH_NAMES.size()); for (const auto & [arch, _] : LLM_ARCH_NAMES) { ret.push_back(arch); } return ret; } const char * llm_arch_name(llm_arch arch) { auto it = LLM_ARCH_NAMES.find(arch); if (it == LLM_ARCH_NAMES.end()) { return "unknown"; } return it->second; } llm_arch llm_arch_from_string(const std::string & name) { for (const auto & kv : LLM_ARCH_NAMES) { // NOLINT if (kv.second == name) { return kv.first; } } return LLM_ARCH_UNKNOWN; } const llm_tensor_info & llm_tensor_info_for(llm_tensor tensor) { return LLM_TENSOR_INFOS.at(tensor); } bool llm_arch_is_recurrent(const llm_arch & arch) { switch (arch) { case LLM_ARCH_MAMBA: case LLM_ARCH_MAMBA2: case LLM_ARCH_RWKV6: case LLM_ARCH_RWKV6QWEN2: case LLM_ARCH_RWKV7: case LLM_ARCH_ARWKV7: return true; default: return false; } } bool llm_arch_is_hybrid(const llm_arch & arch) { switch (arch) { case LLM_ARCH_JAMBA: case LLM_ARCH_FALCON_H1: case LLM_ARCH_PLAMO2: case LLM_ARCH_GRANITE_HYBRID: case LLM_ARCH_LFM2: case LLM_ARCH_LFM2MOE: case LLM_ARCH_NEMOTRON_H: case LLM_ARCH_NEMOTRON_H_MOE: case LLM_ARCH_QWEN3NEXT: case LLM_ARCH_KIMI_LINEAR: case LLM_ARCH_QWEN35: case LLM_ARCH_QWEN35MOE: return true; default: return false; } } bool llm_arch_is_diffusion(const llm_arch & arch) { switch (arch) { case LLM_ARCH_DREAM: case LLM_ARCH_LLADA: case LLM_ARCH_LLADA_MOE: case LLM_ARCH_RND1: return true; default: return false; } } bool llm_arch_supports_sm_tensor(const llm_arch & arch) { switch (arch) { case LLM_ARCH_GROK: case LLM_ARCH_MPT: case LLM_ARCH_PLAMO2: case LLM_ARCH_MINICPM3: case LLM_ARCH_GEMMA3N: case LLM_ARCH_MAMBA: case LLM_ARCH_MAMBA2: case LLM_ARCH_JAMBA: case LLM_ARCH_FALCON_H1: case LLM_ARCH_OLMO2: case LLM_ARCH_OLMOE: case LLM_ARCH_DEEPSEEK2: case LLM_ARCH_GLM_DSA: case LLM_ARCH_BITNET: case LLM_ARCH_T5: case LLM_ARCH_NEMOTRON_H: case LLM_ARCH_NEMOTRON_H_MOE: case LLM_ARCH_GRANITE_HYBRID: case LLM_ARCH_LFM2: case LLM_ARCH_LFM2MOE: case LLM_ARCH_MINIMAX_M2: case LLM_ARCH_MISTRAL4: case LLM_ARCH_KIMI_LINEAR: return false; default: return true; } }