#pragma once

#include "ggml.h" // ggml_op

#include <string>

//

// gguf constants (sync with gguf.py)

//

enum llm_arch {

    LLM_ARCH_CLIP,

    LLM_ARCH_LLAMA,

    LLM_ARCH_LLAMA4,

    LLM_ARCH_DECI,

    LLM_ARCH_FALCON,

    LLM_ARCH_BAICHUAN,

    LLM_ARCH_GROK,

    LLM_ARCH_GPT2,

    LLM_ARCH_GPTJ,

    LLM_ARCH_GPTNEOX,

    LLM_ARCH_MPT,

    LLM_ARCH_STARCODER,

    LLM_ARCH_REFACT,

    LLM_ARCH_BERT,

    LLM_ARCH_NOMIC_BERT,

    LLM_ARCH_NOMIC_BERT_MOE,

    LLM_ARCH_NEO_BERT,

    LLM_ARCH_JINA_BERT_V2,

    LLM_ARCH_JINA_BERT_V3,

    LLM_ARCH_BLOOM,

    LLM_ARCH_STABLELM,

    LLM_ARCH_QWEN,

    LLM_ARCH_QWEN2,

    LLM_ARCH_QWEN2MOE,

    LLM_ARCH_QWEN2VL,

    LLM_ARCH_QWEN3,

    LLM_ARCH_QWEN3MOE,

    LLM_ARCH_QWEN3VL,

    LLM_ARCH_QWEN3VLMOE,

    LLM_ARCH_PHI2,

    LLM_ARCH_PHI3,

    LLM_ARCH_PHIMOE,

    LLM_ARCH_PLAMO,

    LLM_ARCH_PLAMO2,

    LLM_ARCH_CODESHELL,

    LLM_ARCH_ORION,

    LLM_ARCH_INTERNLM2,

    LLM_ARCH_MINICPM,

    LLM_ARCH_MINICPM3,

    LLM_ARCH_GEMMA,

    LLM_ARCH_GEMMA2,

    LLM_ARCH_GEMMA3,

    LLM_ARCH_GEMMA3N,

    LLM_ARCH_GEMMA_EMBEDDING,

    LLM_ARCH_STARCODER2,

    LLM_ARCH_MAMBA,

    LLM_ARCH_MAMBA2,

    LLM_ARCH_JAMBA,

    LLM_ARCH_FALCON_H1,

    LLM_ARCH_XVERSE,

    LLM_ARCH_COMMAND_R,

    LLM_ARCH_COHERE2,

    LLM_ARCH_DBRX,

    LLM_ARCH_OLMO,

    LLM_ARCH_OLMO2,

    LLM_ARCH_OLMOE,

    LLM_ARCH_OPENELM,

    LLM_ARCH_ARCTIC,

    LLM_ARCH_DEEPSEEK,

    LLM_ARCH_DEEPSEEK2,

    LLM_ARCH_CHATGLM,

    LLM_ARCH_GLM4,

    LLM_ARCH_GLM4_MOE,

    LLM_ARCH_BITNET,

    LLM_ARCH_T5,

    LLM_ARCH_T5ENCODER,

    LLM_ARCH_JAIS,

    LLM_ARCH_NEMOTRON,

    LLM_ARCH_NEMOTRON_H,

    LLM_ARCH_EXAONE,

    LLM_ARCH_EXAONE4,

    LLM_ARCH_RWKV6,

    LLM_ARCH_RWKV6QWEN2,

    LLM_ARCH_RWKV7,

    LLM_ARCH_ARWKV7,

    LLM_ARCH_GRANITE,

    LLM_ARCH_GRANITE_MOE,

    LLM_ARCH_GRANITE_HYBRID,

    LLM_ARCH_CHAMELEON,

    LLM_ARCH_WAVTOKENIZER_DEC,

    LLM_ARCH_PLM,

    LLM_ARCH_BAILINGMOE,

    LLM_ARCH_BAILINGMOE2,

    LLM_ARCH_DOTS1,

    LLM_ARCH_ARCEE,

    LLM_ARCH_AFMOE,

    LLM_ARCH_ERNIE4_5,

    LLM_ARCH_ERNIE4_5_MOE,

    LLM_ARCH_HUNYUAN_MOE,

    LLM_ARCH_HUNYUAN_DENSE,

    LLM_ARCH_SMOLLM3,

    LLM_ARCH_OPENAI_MOE,

    LLM_ARCH_LFM2,

    LLM_ARCH_LFM2MOE,

    LLM_ARCH_DREAM,

    LLM_ARCH_SMALLTHINKER,

    LLM_ARCH_LLADA,

    LLM_ARCH_LLADA_MOE,

    LLM_ARCH_SEED_OSS,

    LLM_ARCH_GROVEMOE,

    LLM_ARCH_APERTUS,

    LLM_ARCH_MINIMAX_M2,

    LLM_ARCH_COGVLM,

    LLM_ARCH_PANGU_EMBED,

    LLM_ARCH_UNKNOWN,

};

enum llm_kv {

    LLM_KV_GENERAL_TYPE,

    LLM_KV_GENERAL_ARCHITECTURE,

    LLM_KV_GENERAL_QUANTIZATION_VERSION,

    LLM_KV_GENERAL_ALIGNMENT,

    LLM_KV_GENERAL_FILE_TYPE,

    LLM_KV_GENERAL_NAME,

    LLM_KV_GENERAL_AUTHOR,

    LLM_KV_GENERAL_VERSION,

    LLM_KV_GENERAL_URL,

    LLM_KV_GENERAL_DESCRIPTION,

    LLM_KV_GENERAL_LICENSE,

    LLM_KV_GENERAL_SOURCE_URL,

    LLM_KV_GENERAL_SOURCE_HF_REPO,

    LLM_KV_VOCAB_SIZE,

    LLM_KV_CONTEXT_LENGTH,

    LLM_KV_EMBEDDING_LENGTH,

    LLM_KV_FEATURES_LENGTH,

    LLM_KV_BLOCK_COUNT,

    LLM_KV_LEADING_DENSE_BLOCK_COUNT,

    LLM_KV_FEED_FORWARD_LENGTH,

    LLM_KV_EXPERT_FEED_FORWARD_LENGTH,

    LLM_KV_EXPERT_SHARED_FEED_FORWARD_LENGTH,

    LLM_KV_EXPERT_CHUNK_FEED_FORWARD_LENGTH,

    LLM_KV_USE_PARALLEL_RESIDUAL,

    LLM_KV_TENSOR_DATA_LAYOUT,

    LLM_KV_EXPERT_COUNT,

    LLM_KV_EXPERT_USED_COUNT,

    LLM_KV_EXPERT_SHARED_COUNT,

    LLM_KV_EXPERT_GROUP_COUNT,

    LLM_KV_EXPERT_GROUP_USED_COUNT,

    LLM_KV_EXPERT_WEIGHTS_SCALE,

    LLM_KV_EXPERT_WEIGHTS_NORM,

    LLM_KV_EXPERT_GATING_FUNC,

    LLM_KV_EXPERT_GROUP_SCALE,

    LLM_KV_EXPERTS_PER_GROUP,

    LLM_KV_MOE_EVERY_N_LAYERS,

    LLM_KV_NEXTN_PREDICT_LAYERS,

    LLM_KV_NUM_DEEPSTACK_LAYERS,

    LLM_KV_POOLING_TYPE,

    LLM_KV_LOGIT_SCALE,

    LLM_KV_DECODER_START_TOKEN_ID,

    LLM_KV_DECODER_BLOCK_COUNT,

    LLM_KV_ATTN_LOGIT_SOFTCAPPING,

    LLM_KV_ROUTER_LOGIT_SOFTCAPPING,

    LLM_KV_FINAL_LOGIT_SOFTCAPPING,

    LLM_KV_SWIN_NORM,

    LLM_KV_RESCALE_EVERY_N_LAYERS,

    LLM_KV_TIME_MIX_EXTRA_DIM,

    LLM_KV_TIME_DECAY_EXTRA_DIM,

    LLM_KV_RESIDUAL_SCALE,

    LLM_KV_EMBEDDING_SCALE,

    LLM_KV_TOKEN_SHIFT_COUNT,

    LLM_KV_INTERLEAVE_MOE_LAYER_STEP,

    LLM_KV_ATTENTION_HEAD_COUNT,

    LLM_KV_ATTENTION_HEAD_COUNT_KV,

    LLM_KV_ATTENTION_MAX_ALIBI_BIAS,

    LLM_KV_ATTENTION_CLAMP_KQV,

    LLM_KV_ATTENTION_KEY_LENGTH,

    LLM_KV_ATTENTION_VALUE_LENGTH,

    LLM_KV_ATTENTION_LAYERNORM_EPS,

    LLM_KV_ATTENTION_LAYERNORM_RMS_EPS,

    LLM_KV_ATTENTION_GROUPNORM_EPS,

    LLM_KV_ATTENTION_GROUPNORM_GROUPS,

    LLM_KV_ATTENTION_CAUSAL,

    LLM_KV_ATTENTION_Q_LORA_RANK,

    LLM_KV_ATTENTION_KV_LORA_RANK,

    LLM_KV_ATTENTION_DECAY_LORA_RANK,

    LLM_KV_ATTENTION_ICLR_LORA_RANK,

    LLM_KV_ATTENTION_VALUE_RESIDUAL_MIX_LORA_RANK,

    LLM_KV_ATTENTION_GATE_LORA_RANK,

    LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT,

    LLM_KV_ATTENTION_SLIDING_WINDOW,

    LLM_KV_ATTENTION_SCALE,

    LLM_KV_ATTENTION_OUTPUT_SCALE,

    LLM_KV_ATTENTION_TEMPERATURE_LENGTH,

    LLM_KV_ATTENTION_KEY_LENGTH_MLA,

    LLM_KV_ATTENTION_VALUE_LENGTH_MLA,

    LLM_KV_ROPE_DIMENSION_COUNT,

    LLM_KV_ROPE_DIMENSION_SECTIONS,

    LLM_KV_ROPE_FREQ_BASE,

    LLM_KV_ROPE_SCALE_LINEAR,

    LLM_KV_ROPE_SCALING_TYPE,

    LLM_KV_ROPE_SCALING_FACTOR,

    LLM_KV_ROPE_SCALING_ATTN_FACTOR,

    LLM_KV_ROPE_SCALING_ORIG_CTX_LEN,

    LLM_KV_ROPE_SCALING_FINETUNED,

    LLM_KV_ROPE_SCALING_YARN_LOG_MUL,

    LLM_KV_ROPE_SCALING_YARN_EXT_FACTOR,

    LLM_KV_ROPE_SCALING_YARN_ATTN_FACTOR,

    LLM_KV_ROPE_SCALING_YARN_BETA_FAST,

    LLM_KV_ROPE_SCALING_YARN_BETA_SLOW,

    LLM_KV_SPLIT_NO,

    LLM_KV_SPLIT_COUNT,

    LLM_KV_SPLIT_TENSORS_COUNT,

    LLM_KV_SSM_INNER_SIZE,

    LLM_KV_SSM_CONV_KERNEL,

    LLM_KV_SSM_STATE_SIZE,

    LLM_KV_SSM_TIME_STEP_RANK,

    LLM_KV_SSM_GROUP_COUNT,

    LLM_KV_SSM_DT_B_C_RMS,

    LLM_KV_WKV_HEAD_SIZE,

    LLM_KV_TOKENIZER_MODEL,

    LLM_KV_TOKENIZER_PRE,

    LLM_KV_TOKENIZER_LIST,

    LLM_KV_TOKENIZER_TOKEN_TYPE,

    LLM_KV_TOKENIZER_TOKEN_TYPE_COUNT,

    LLM_KV_TOKENIZER_SCORES,

    LLM_KV_TOKENIZER_MERGES,

    LLM_KV_TOKENIZER_BOS_ID,

    LLM_KV_TOKENIZER_EOS_ID,

    LLM_KV_TOKENIZER_EOT_ID,

    LLM_KV_TOKENIZER_EOM_ID,

    LLM_KV_TOKENIZER_UNK_ID,

    LLM_KV_TOKENIZER_SEP_ID,

    LLM_KV_TOKENIZER_PAD_ID,

    LLM_KV_TOKENIZER_CLS_ID,

    LLM_KV_TOKENIZER_MASK_ID,

    LLM_KV_TOKENIZER_ADD_BOS,

    LLM_KV_TOKENIZER_ADD_EOS,

    LLM_KV_TOKENIZER_ADD_SEP,

    LLM_KV_TOKENIZER_ADD_PREFIX,

    LLM_KV_TOKENIZER_REMOVE_EXTRA_WS,

    LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP,

    LLM_KV_TOKENIZER_HF_JSON,

    LLM_KV_TOKENIZER_RWKV,

    LLM_KV_TOKENIZER_CHAT_TEMPLATE,

    LLM_KV_TOKENIZER_FIM_PRE_ID,

    LLM_KV_TOKENIZER_FIM_SUF_ID,

    LLM_KV_TOKENIZER_FIM_MID_ID,

    LLM_KV_TOKENIZER_FIM_PAD_ID,

    LLM_KV_TOKENIZER_FIM_REP_ID,

    LLM_KV_TOKENIZER_FIM_SEP_ID,

    LLM_KV_ADAPTER_TYPE,

    LLM_KV_ADAPTER_LORA_ALPHA,

    LLM_KV_ADAPTER_LORA_TASK_NAME,

    LLM_KV_ADAPTER_LORA_PROMPT_PREFIX,

    LLM_KV_ADAPTER_ALORA_INVOCATION_TOKENS,

    LLM_KV_POSNET_EMBEDDING_LENGTH,

    LLM_KV_POSNET_BLOCK_COUNT,

    LLM_KV_CONVNEXT_EMBEDDING_LENGTH,

    LLM_KV_CONVNEXT_BLOCK_COUNT,

    LLM_KV_CLASSIFIER_OUTPUT_LABELS,

    LLM_KV_SHORTCONV_L_CACHE,

    LLM_KV_XIELU_ALPHA_N,

    LLM_KV_XIELU_ALPHA_P,

    LLM_KV_XIELU_BETA,

    LLM_KV_XIELU_EPS,

    // deprecated:

    LLM_KV_TOKENIZER_PREFIX_ID,

    LLM_KV_TOKENIZER_SUFFIX_ID,

    LLM_KV_TOKENIZER_MIDDLE_ID,

    // sentence-transformers dense layers in and out features

    LLM_KV_DENSE_2_FEAT_IN,

    LLM_KV_DENSE_2_FEAT_OUT,

    LLM_KV_DENSE_3_FEAT_IN,

    LLM_KV_DENSE_3_FEAT_OUT,

};

enum llm_tensor {

    LLM_TENSOR_TOKEN_EMBD,

    LLM_TENSOR_TOKEN_EMBD_NORM,

    LLM_TENSOR_TOKEN_TYPES,

    LLM_TENSOR_POS_EMBD,

    LLM_TENSOR_DENSE_2_OUT,

    LLM_TENSOR_DENSE_3_OUT,

    LLM_TENSOR_OUTPUT,

    LLM_TENSOR_OUTPUT_NORM,

    LLM_TENSOR_ROPE_FREQS,

    LLM_TENSOR_ROPE_FACTORS_LONG,

    LLM_TENSOR_ROPE_FACTORS_SHORT,

    LLM_TENSOR_ATTN_Q,

    LLM_TENSOR_ATTN_K,

    LLM_TENSOR_ATTN_V,

    LLM_TENSOR_ATTN_QKV,

    LLM_TENSOR_ATTN_OUT,

    LLM_TENSOR_ATTN_NORM,

    LLM_TENSOR_ATTN_NORM_2,

    LLM_TENSOR_ATTN_OUT_NORM,

    LLM_TENSOR_ATTN_POST_NORM,

    LLM_TENSOR_ATTN_ROT_EMBD,

    LLM_TENSOR_ATTN_SINKS,

    LLM_TENSOR_ATTN_GATE,

    LLM_TENSOR_FFN_GATE_INP,

    LLM_TENSOR_FFN_GATE_INP_SHEXP,

    LLM_TENSOR_FFN_NORM,

    LLM_TENSOR_FFN_POST_NORM,

    LLM_TENSOR_FFN_GATE,

    LLM_TENSOR_FFN_DOWN,

    LLM_TENSOR_FFN_UP,

    LLM_TENSOR_FFN_ACT,

    LLM_TENSOR_FFN_DOWN_EXP,  // split experts for backward compatibility

    LLM_TENSOR_FFN_GATE_EXP,

    LLM_TENSOR_FFN_UP_EXP,

    LLM_TENSOR_FFN_NORM_EXPS,

    LLM_TENSOR_FFN_DOWN_EXPS, // merged experts

    LLM_TENSOR_FFN_GATE_EXPS,

    LLM_TENSOR_FFN_UP_EXPS,

    LLM_TENSOR_FFN_DOWN_SHEXP,

    LLM_TENSOR_FFN_GATE_SHEXP,

    LLM_TENSOR_FFN_UP_SHEXP,

    LLM_TENSOR_FFN_DOWN_CHEXPS,

    LLM_TENSOR_FFN_GATE_CHEXPS,

    LLM_TENSOR_FFN_UP_CHEXPS,

    LLM_TENSOR_FFN_EXP_PROBS_B,

    LLM_TENSOR_ATTN_Q_NORM,

    LLM_TENSOR_ATTN_K_NORM,

    LLM_TENSOR_LAYER_OUT_NORM,

    LLM_TENSOR_POST_ATTN_NORM,

    LLM_TENSOR_POST_MLP_NORM,

    LLM_TENSOR_PER_LAYER_TOKEN_EMBD, // gemma3n

    LLM_TENSOR_PER_LAYER_MODEL_PROJ, // gemma3n

    LLM_TENSOR_PER_LAYER_INP_GATE,   // gemma3n

    LLM_TENSOR_PER_LAYER_PROJ,       // gemma3n

    LLM_TENSOR_PER_LAYER_PROJ_NORM,  // gemma3n

    LLM_TENSOR_PER_LAYER_POST_NORM,  // gemma3n

    LLM_TENSOR_ALTUP_PROJ,           // gemma3n

    LLM_TENSOR_ALTUP_UNEMBD_PROJ,    // gemma3n

    LLM_TENSOR_ALTUP_CORRECT_COEF,   // gemma3n

    LLM_TENSOR_ALTUP_CORRECT_SCALE,  // gemma3n

    LLM_TENSOR_ALTUP_PREDICT_COEF,   // gemma3n

    LLM_TENSOR_ALTUP_ROUTER,         // gemma3n

    LLM_TENSOR_ALTUP_ROUTER_NORM,    // gemma3n

    LLM_TENSOR_LAUREL_L,             // gemma3n

    LLM_TENSOR_LAUREL_R,             // gemma3n

    LLM_TENSOR_LAUREL_POST_NORM,     // gemma3n

    LLM_TENSOR_SSM_IN,

    LLM_TENSOR_SSM_CONV1D,

    LLM_TENSOR_SSM_X,

    LLM_TENSOR_SSM_DT,

    LLM_TENSOR_SSM_DT_NORM,

    LLM_TENSOR_SSM_A,

    LLM_TENSOR_SSM_B_NORM,

    LLM_TENSOR_SSM_C_NORM,

    LLM_TENSOR_SSM_D,

    LLM_TENSOR_SSM_NORM,

    LLM_TENSOR_SSM_OUT,

    LLM_TENSOR_TIME_MIX_W0,

    LLM_TENSOR_TIME_MIX_W1,

    LLM_TENSOR_TIME_MIX_W2,

    LLM_TENSOR_TIME_MIX_A0,

    LLM_TENSOR_TIME_MIX_A1,

    LLM_TENSOR_TIME_MIX_A2,

    LLM_TENSOR_TIME_MIX_V0,

    LLM_TENSOR_TIME_MIX_V1,

    LLM_TENSOR_TIME_MIX_V2,

    LLM_TENSOR_TIME_MIX_G1,

    LLM_TENSOR_TIME_MIX_G2,

    LLM_TENSOR_TIME_MIX_K_K,

    LLM_TENSOR_TIME_MIX_K_A,

    LLM_TENSOR_TIME_MIX_R_K,

    LLM_TENSOR_TIME_MIX_LERP_X,

    LLM_TENSOR_TIME_MIX_LERP_W,

    LLM_TENSOR_TIME_MIX_LERP_K,

    LLM_TENSOR_TIME_MIX_LERP_V,

    LLM_TENSOR_TIME_MIX_LERP_R,

    LLM_TENSOR_TIME_MIX_LERP_G,

    LLM_TENSOR_TIME_MIX_LERP_FUSED,

    LLM_TENSOR_TIME_MIX_FIRST,

    LLM_TENSOR_TIME_MIX_DECAY,

    LLM_TENSOR_TIME_MIX_DECAY_W1,

    LLM_TENSOR_TIME_MIX_DECAY_W2,

    LLM_TENSOR_TIME_MIX_KEY,

    LLM_TENSOR_TIME_MIX_VALUE,

    LLM_TENSOR_TIME_MIX_RECEPTANCE,

    LLM_TENSOR_TIME_MIX_GATE,

    LLM_TENSOR_TIME_MIX_LN,

    LLM_TENSOR_TIME_MIX_OUTPUT,

    LLM_TENSOR_CHANNEL_MIX_LERP_K,

    LLM_TENSOR_CHANNEL_MIX_LERP_R,

    LLM_TENSOR_CHANNEL_MIX_KEY,

    LLM_TENSOR_CHANNEL_MIX_RECEPTANCE,

    LLM_TENSOR_CHANNEL_MIX_VALUE,

    LLM_TENSOR_ATTN_Q_A,

    LLM_TENSOR_ATTN_Q_B,

    LLM_TENSOR_ATTN_KV_A_MQA,

    LLM_TENSOR_ATTN_KV_B,

    LLM_TENSOR_ATTN_K_B,

    LLM_TENSOR_ATTN_V_B,

    LLM_TENSOR_ATTN_Q_A_NORM,

    LLM_TENSOR_ATTN_KV_A_NORM,

    LLM_TENSOR_ATTN_SUB_NORM,

    LLM_TENSOR_FFN_SUB_NORM,

    LLM_TENSOR_DEC_ATTN_NORM,

    LLM_TENSOR_DEC_ATTN_Q,

    LLM_TENSOR_DEC_ATTN_K,

    LLM_TENSOR_DEC_ATTN_V,

    LLM_TENSOR_DEC_ATTN_OUT,

    LLM_TENSOR_DEC_ATTN_REL_B,

    LLM_TENSOR_DEC_CROSS_ATTN_NORM,

    LLM_TENSOR_DEC_CROSS_ATTN_Q,

    LLM_TENSOR_DEC_CROSS_ATTN_K,

    LLM_TENSOR_DEC_CROSS_ATTN_V,

    LLM_TENSOR_DEC_CROSS_ATTN_OUT,

    LLM_TENSOR_DEC_CROSS_ATTN_REL_B,

    LLM_TENSOR_DEC_FFN_NORM,

    LLM_TENSOR_DEC_FFN_GATE,

    LLM_TENSOR_DEC_FFN_DOWN,

    LLM_TENSOR_DEC_FFN_UP,

    LLM_TENSOR_DEC_OUTPUT_NORM,

    LLM_TENSOR_ENC_ATTN_NORM,

    LLM_TENSOR_ENC_ATTN_Q,

    LLM_TENSOR_ENC_ATTN_K,

    LLM_TENSOR_ENC_ATTN_V,

    LLM_TENSOR_ENC_ATTN_OUT,

    LLM_TENSOR_ENC_ATTN_REL_B,

    LLM_TENSOR_ENC_FFN_NORM,

    LLM_TENSOR_ENC_FFN_GATE,

    LLM_TENSOR_ENC_FFN_DOWN,

    LLM_TENSOR_ENC_FFN_UP,

    LLM_TENSOR_ENC_OUTPUT_NORM,

    LLM_TENSOR_CLS,

    LLM_TENSOR_CLS_OUT,

    LLM_TENSOR_CONV1D,

    LLM_TENSOR_CONVNEXT_DW,

    LLM_TENSOR_CONVNEXT_NORM,

    LLM_TENSOR_CONVNEXT_PW1,

    LLM_TENSOR_CONVNEXT_PW2,

    LLM_TENSOR_CONVNEXT_GAMMA,

    LLM_TENSOR_POS_NET_CONV1,

    LLM_TENSOR_POS_NET_CONV2,

    LLM_TENSOR_POS_NET_NORM,

    LLM_TENSOR_POS_NET_NORM1,

    LLM_TENSOR_POS_NET_NORM2,

    LLM_TENSOR_POS_NET_ATTN_NORM,

    LLM_TENSOR_POS_NET_ATTN_Q,

    LLM_TENSOR_POS_NET_ATTN_K,

    LLM_TENSOR_POS_NET_ATTN_V,

    LLM_TENSOR_POS_NET_ATTN_OUT,

    LLM_TENSOR_SHORTCONV_CONV,

    LLM_TENSOR_SHORTCONV_INPROJ,

    LLM_TENSOR_SHORTCONV_OUTPROJ,

    LLM_TENSOR_VISEXP_ATTN_QKV,

    LLM_TENSOR_VISEXP_ATTN_OUT,

    LLM_TENSOR_VISEXP_FFN_GATE,

    LLM_TENSOR_VISEXP_FFN_DOWN,

    LLM_TENSOR_VISEXP_FFN_UP,

    LLM_TENSOR_NEXTN_EH_PROJ,

    LLM_TENSOR_NEXTN_EMBED_TOKENS,

    LLM_TENSOR_NEXTN_ENORM,

    LLM_TENSOR_NEXTN_HNORM,

    LLM_TENSOR_NEXTN_SHARED_HEAD_HEAD,

    LLM_TENSOR_NEXTN_SHARED_HEAD_NORM,

};

enum llm_tensor_layer {

    LLM_TENSOR_LAYER_INPUT,

    LLM_TENSOR_LAYER_REPEATING,

    LLM_TENSOR_LAYER_OUTPUT,

};

struct LLM_KV {

    LLM_KV(llm_arch arch, const char * suffix = nullptr);

    llm_arch arch;

    const char * suffix;

    std::string operator()(llm_kv kv) const;

};

// helper to handle gguf constants

// usage:

//

//   const auto tn = LLM_TN(LLM_ARCH_LLAMA);

//

//   std::string name = tn(LLM_TENSOR_OUTPUT);                     -> "output"

//   std::string name = tn(LLM_TENSOR_TOKEN_EMBD, "bias");         -> "token_embd.bias"

//   std::string name = tn(LLM_TENSOR_ATTN_NORM, "weight", 3);     -> "blk.3.attn_norm.weight"

//

struct LLM_TN_IMPL {

    const llm_arch arch;

    const llm_tensor tensor;

    const char * const suffix;

    const int bid;

    const int xid;

    std::string str() const;

    operator std::string() const {

        return str();

    }

    friend bool operator==(const std::string & str, const LLM_TN_IMPL & tn) {

        return str == tn.str();

    }

    friend bool operator!=(const std::string & str, const LLM_TN_IMPL & tn) {

        return str != tn.str();

    }

};

struct LLM_TN {

    LLM_TN(llm_arch arch) : arch(arch) {}

    llm_arch arch;

    LLM_TN_IMPL operator()(llm_tensor tensor, const char * suffix, int bid = -1, int xid = -1) const {

        return { arch, tensor, suffix, bid, xid };

    }

    LLM_TN_IMPL operator()(llm_tensor tensor, int bid = -1, int xid = -1) const {

        return { arch, tensor, nullptr, bid, xid };

    }

};

struct llm_tensor_info {

    llm_tensor_layer layer;

    ggml_op op;

};

const char * llm_arch_name(llm_arch arch);

llm_arch llm_arch_from_string(const std::string & name);

const llm_tensor_info & llm_tensor_info_for(llm_tensor tensor);

bool llm_arch_is_recurrent(const llm_arch & arch);

bool llm_arch_is_hybrid   (const llm_arch & arch);

bool llm_arch_is_diffusion(const llm_arch & arch);