#include "llama-arch.h"

#include "llama-impl.h"

#include <map>

#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_GEMMA4_ASSISTANT, "gemma4-assistant" },

{ 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_COHERE2MOE, "cohere2moe" },

{ 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_DEEPSEEK32, "deepseek32" },

{ LLM_ARCH_DEEPSEEK4, "deepseek4" },

{ 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_HUNYUAN_VL, "hunyuan_vl" },

{ LLM_ARCH_HY_V3, "hy_v3" },

{ 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_EAGLE3, "eagle3" },

{ LLM_ARCH_DFLASH, "dflash" },

{ 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_TALKIE, "talkie" },

{ LLM_ARCH_MELLUM, "mellum" },

{ 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_DEEPSTACK_MAPPING, "%s.deepstack_mapping" },

{ LLM_KV_HIDDEN_ACT, "%s.hidden_activation" },

{ 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_VALUE_SCALE, "%s.attention.value_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_OUTPUT_GROUP_COUNT, "%s.attention.output_group_count" },

{ LLM_KV_ATTENTION_OUTPUT_LORA_RANK, "%s.attention.output_lora_rank" },

{ LLM_KV_ATTENTION_COMPRESS_ROPE_FREQ_BASE, "%s.attention.compress_rope_freq_base" },

{ LLM_KV_ATTENTION_COMPRESS_RATIOS, "%s.attention.compress_ratios" },

{ LLM_KV_ATTENTION_SHARED_KV_LAYERS, "%s.attention.shared_kv_layers" },

{ LLM_KV_ATTENTION_RECURRENT_LAYERS, "%s.attention.recurrent_layers" },

{ LLM_KV_HYPER_CONNECTION_COUNT, "%s.hyper_connection.count" },

{ LLM_KV_HYPER_CONNECTION_SINKHORN_ITERATIONS, "%s.hyper_connection.sinkhorn_iterations" },

{ LLM_KV_HYPER_CONNECTION_EPSILON, "%s.hyper_connection.epsilon" },

{ LLM_KV_HASH_LAYER_COUNT, "%s.hash_layer_count" },

{ 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_ALPHA, "%s.rope.scaling.alpha" },

{ 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_TARGET_LAYERS, "%s.target_layers" },

{ LLM_KV_TARGET_HIDDEN_SIZE, "%s.target_hidden_size" },

{ LLM_KV_NORM_BEFORE_RESIDUAL, "%s.norm_before_residual" },

{ 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_NORMALIZER_LOWERCASE, "tokenizer.ggml.normalizer.lowercase" },

{ LLM_KV_TOKENIZER_NORMALIZER_STRIP_ACCENTS, "tokenizer.ggml.normalizer.strip_accents" },

{ 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_TOKENIZER_SUPPRESS_TOKENS, "tokenizer.ggml.suppress_tokens" },

{ 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_ATTN_KV, "blk.%d.attn_kv" },

{ LLM_TENSOR_ATTN_KV_NORM, "blk.%d.attn_kv_a_norm" },

{ LLM_TENSOR_ATTN_OUT_A, "blk.%d.attn_output_a" },

{ LLM_TENSOR_ATTN_OUT_B, "blk.%d.attn_output_b" },

{ LLM_TENSOR_HC_HEAD_FN, "output_hc_fn" },

{ LLM_TENSOR_HC_HEAD_BASE, "output_hc_base" },

{ LLM_TENSOR_HC_HEAD_SCALE, "output_hc_scale" },

{ LLM_TENSOR_HC_ATTN_FN, "blk.%d.hc_attn_fn" },

{ LLM_TENSOR_HC_ATTN_BASE, "blk.%d.hc_attn_base" },

{ LLM_TENSOR_HC_ATTN_SCALE, "blk.%d.hc_attn_scale" },

{ LLM_TENSOR_HC_FFN_FN, "blk.%d.hc_ffn_fn" },

{ LLM_TENSOR_HC_FFN_BASE, "blk.%d.hc_ffn_base" },

{ LLM_TENSOR_HC_FFN_SCALE, "blk.%d.hc_ffn_scale" },

{ LLM_TENSOR_ATTN_COMPRESSOR_WKV, "blk.%d.attn_compressor_kv" },

{ LLM_TENSOR_ATTN_COMPRESSOR_WGATE, "blk.%d.attn_compressor_gate" },

{ LLM_TENSOR_ATTN_COMPRESSOR_APE, "blk.%d.attn_compressor_ape" },

{ LLM_TENSOR_ATTN_COMPRESSOR_NORM, "blk.%d.attn_compressor_norm" },

{ 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_PROJ_PRE, "nextn.pre_projection" },

{ LLM_TENSOR_NEXTN_PROJ_POST, "nextn.post_projection" },

{ 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" },

{ LLM_TENSOR_INDEXER_COMPRESSOR_WKV, "blk.%d.indexer_compressor_kv" },

{ LLM_TENSOR_INDEXER_COMPRESSOR_WGATE, "blk.%d.indexer_compressor_gate" },

{ LLM_TENSOR_INDEXER_COMPRESSOR_APE, "blk.%d.indexer_compressor_ape" },

{ LLM_TENSOR_INDEXER_COMPRESSOR_NORM, "blk.%d.indexer_compressor_norm" },

{ LLM_TENSOR_FFN_GATE_TID2EID, "blk.%d.ffn_gate_tid2eid" },

{ LLM_TENSOR_MASKED_EMBD_CENTROIDS, "masked_embd_centroids" },

{ LLM_TENSOR_MASKED_EMBD_ORDERING, "masked_embd_ordering" },

{ LLM_TENSOR_FC, "fc" },

{ LLM_TENSOR_D2T, "d2t" },

};

// 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_KV, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_ATTN_KV_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},

{LLM_TENSOR_ATTN_OUT_A, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_ATTN_OUT_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_HC_HEAD_FN, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}},

{LLM_TENSOR_HC_HEAD_BASE, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_ADD}},

{LLM_TENSOR_HC_HEAD_SCALE, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL}},

{LLM_TENSOR_HC_ATTN_FN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_HC_ATTN_BASE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},

{LLM_TENSOR_HC_ATTN_SCALE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},

{LLM_TENSOR_HC_FFN_FN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_HC_FFN_BASE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},

{LLM_TENSOR_HC_FFN_SCALE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},

{LLM_TENSOR_ATTN_COMPRESSOR_WKV, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_ATTN_COMPRESSOR_WGATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_ATTN_COMPRESSOR_APE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},

{LLM_TENSOR_ATTN_COMPRESSOR_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},

{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}},

{LLM_TENSOR_INDEXER_COMPRESSOR_WKV, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_INDEXER_COMPRESSOR_WGATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_INDEXER_COMPRESSOR_APE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},

{LLM_TENSOR_INDEXER_COMPRESSOR_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},

{LLM_TENSOR_FFN_GATE_TID2EID, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_GET_ROWS}},

{LLM_TENSOR_NEXTN_PROJ_PRE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_NEXTN_PROJ_POST, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}},

// NextN/MTP tensors are stored per-block (blk.%d.nextn.*) even though only the

// last nextn_predict_layers blocks carry them. Classify as LAYER_REPEATING so

// the model loader doesn't fault on the block index.

{LLM_TENSOR_NEXTN_EH_PROJ, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_NEXTN_EMBED_TOKENS, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_GET_ROWS}},

{LLM_TENSOR_NEXTN_ENORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},

{LLM_TENSOR_NEXTN_HNORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},

{LLM_TENSOR_NEXTN_SHARED_HEAD_HEAD, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_NEXTN_SHARED_HEAD_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},

// Nemotron 3 Super

// latent projections feed ggml_mul_mat, the buft probe must use MUL_MAT to keep them on GPU

{LLM_TENSOR_FFN_LATENT_DOWN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_FFN_LATENT_UP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},

{LLM_TENSOR_MASKED_EMBD_CENTROIDS, {LLM_TENSOR_LAYER_INPUT, GGML_OP_NONE}},

{LLM_TENSOR_MASKED_EMBD_ORDERING, {LLM_TENSOR_LAYER_INPUT, GGML_OP_NONE}},

// eagle3

{LLM_TENSOR_FC, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}},

{LLM_TENSOR_D2T, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_GET_ROWS}},

};

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_rs_rollback(const llm_arch & arch) {

switch (arch) {

case LLM_ARCH_QWEN35:

case LLM_ARCH_QWEN35MOE:

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_DEEPSEEK32:

case LLM_ARCH_DEEPSEEK4:

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: