diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py index c0ab0f955..8fc4c4f56 100755 --- a/convert_hf_to_gguf.py +++ b/convert_hf_to_gguf.py @@ -2032,9 +2032,9 @@ class Qwen2VLModel(Model): yield name, data -@Model.register("OuteTTSVocoder") -class OuteTTSVocoderModel(Model): - model_arch = gguf.MODEL_ARCH.OUTETTS_VOC +@Model.register("WavTokenizerDec") +class WavTokenizerDecModel(Model): + model_arch = gguf.MODEL_ARCH.WAVTOKENIZER_DEC def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: del bid # unused diff --git a/examples/tts/convert_pt_to_hf.py b/examples/tts/convert_pt_to_hf.py index 62dcc05ef..8d68290e2 100644 --- a/examples/tts/convert_pt_to_hf.py +++ b/examples/tts/convert_pt_to_hf.py @@ -1,5 +1,5 @@ # convert the https://huggingface.co/novateur/WavTokenizer-large-speech-75token to HF format -# the goal is to be able to reuse the convert_hf_to_gguf.py after that to create a GGUF file with the OuteTTSS vocoder +# the goal is to be able to reuse the convert_hf_to_gguf.py after that to create a GGUF file with the WavTokenizer decoder # # TODO: this script is LLM-generated and probably very inefficient and should be rewritten @@ -144,7 +144,7 @@ print(f"Metadata has been saved to {index_path}") config = { "architectures": [ - "OuteTTSVocoder" + "WavTokenizerDec" ], "hidden_size": 1282, "vocab_size": 4096, diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index f1f44c7d2..af2a4f4f4 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -209,59 +209,59 @@ class GGUFType: class MODEL_ARCH(IntEnum): - LLAMA = auto() - FALCON = auto() - BAICHUAN = auto() - GROK = auto() - GPT2 = auto() - GPTJ = auto() - GPTNEOX = auto() - MPT = auto() - STARCODER = auto() - REFACT = auto() - BERT = auto() - NOMIC_BERT = auto() - JINA_BERT_V2 = auto() - BLOOM = auto() - STABLELM = auto() - QWEN = auto() - QWEN2 = auto() - QWEN2MOE = auto() - QWEN2VL = auto() - PHI2 = auto() - PHI3 = auto() - PLAMO = auto() - CODESHELL = auto() - ORION = auto() - INTERNLM2 = auto() - MINICPM = auto() - MINICPM3 = auto() - GEMMA = auto() - GEMMA2 = auto() - STARCODER2 = auto() - RWKV6 = auto() - MAMBA = auto() - XVERSE = auto() - COMMAND_R = auto() - DBRX = auto() - OLMO = auto() - OLMO2 = auto() - OLMOE = auto() - OPENELM = auto() - ARCTIC = auto() - DEEPSEEK = auto() - DEEPSEEK2 = auto() - CHATGLM = auto() - BITNET = auto() - T5 = auto() - T5ENCODER = auto() - JAIS = auto() - NEMOTRON = auto() - EXAONE = auto() - GRANITE = auto() - GRANITE_MOE = auto() - CHAMELEON = auto() - OUTETTS_VOC = auto() + LLAMA = auto() + FALCON = auto() + BAICHUAN = auto() + GROK = auto() + GPT2 = auto() + GPTJ = auto() + GPTNEOX = auto() + MPT = auto() + STARCODER = auto() + REFACT = auto() + BERT = auto() + NOMIC_BERT = auto() + JINA_BERT_V2 = auto() + BLOOM = auto() + STABLELM = auto() + QWEN = auto() + QWEN2 = auto() + QWEN2MOE = auto() + QWEN2VL = auto() + PHI2 = auto() + PHI3 = auto() + PLAMO = auto() + CODESHELL = auto() + ORION = auto() + INTERNLM2 = auto() + MINICPM = auto() + MINICPM3 = auto() + GEMMA = auto() + GEMMA2 = auto() + STARCODER2 = auto() + RWKV6 = auto() + MAMBA = auto() + XVERSE = auto() + COMMAND_R = auto() + DBRX = auto() + OLMO = auto() + OLMO2 = auto() + OLMOE = auto() + OPENELM = auto() + ARCTIC = auto() + DEEPSEEK = auto() + DEEPSEEK2 = auto() + CHATGLM = auto() + BITNET = auto() + T5 = auto() + T5ENCODER = auto() + JAIS = auto() + NEMOTRON = auto() + EXAONE = auto() + GRANITE = auto() + GRANITE_MOE = auto() + CHAMELEON = auto() + WAVTOKENIZER_DEC = auto() class MODEL_TENSOR(IntEnum): @@ -390,59 +390,59 @@ class MODEL_TENSOR(IntEnum): MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = { - MODEL_ARCH.LLAMA: "llama", - MODEL_ARCH.FALCON: "falcon", - MODEL_ARCH.BAICHUAN: "baichuan", - MODEL_ARCH.GROK: "grok", - MODEL_ARCH.GPT2: "gpt2", - MODEL_ARCH.GPTJ: "gptj", - MODEL_ARCH.GPTNEOX: "gptneox", - MODEL_ARCH.MPT: "mpt", - MODEL_ARCH.STARCODER: "starcoder", - MODEL_ARCH.REFACT: "refact", - MODEL_ARCH.BERT: "bert", - MODEL_ARCH.NOMIC_BERT: "nomic-bert", - MODEL_ARCH.JINA_BERT_V2: "jina-bert-v2", - MODEL_ARCH.BLOOM: "bloom", - MODEL_ARCH.STABLELM: "stablelm", - MODEL_ARCH.QWEN: "qwen", - MODEL_ARCH.QWEN2: "qwen2", - MODEL_ARCH.QWEN2MOE: "qwen2moe", - MODEL_ARCH.QWEN2VL: "qwen2vl", - MODEL_ARCH.PHI2: "phi2", - MODEL_ARCH.PHI3: "phi3", - MODEL_ARCH.PLAMO: "plamo", - MODEL_ARCH.CODESHELL: "codeshell", - MODEL_ARCH.ORION: "orion", - MODEL_ARCH.INTERNLM2: "internlm2", - MODEL_ARCH.MINICPM: "minicpm", - MODEL_ARCH.MINICPM3: "minicpm3", - MODEL_ARCH.GEMMA: "gemma", - MODEL_ARCH.GEMMA2: "gemma2", - MODEL_ARCH.STARCODER2: "starcoder2", - MODEL_ARCH.RWKV6: "rwkv6", - MODEL_ARCH.MAMBA: "mamba", - MODEL_ARCH.XVERSE: "xverse", - MODEL_ARCH.COMMAND_R: "command-r", - MODEL_ARCH.DBRX: "dbrx", - MODEL_ARCH.OLMO: "olmo", - MODEL_ARCH.OLMO2: "olmo2", - MODEL_ARCH.OLMOE: "olmoe", - MODEL_ARCH.OPENELM: "openelm", - MODEL_ARCH.ARCTIC: "arctic", - MODEL_ARCH.DEEPSEEK: "deepseek", - MODEL_ARCH.DEEPSEEK2: "deepseek2", - MODEL_ARCH.CHATGLM: "chatglm", - MODEL_ARCH.BITNET: "bitnet", - MODEL_ARCH.T5: "t5", - MODEL_ARCH.T5ENCODER: "t5encoder", - MODEL_ARCH.JAIS: "jais", - MODEL_ARCH.NEMOTRON: "nemotron", - MODEL_ARCH.EXAONE: "exaone", - MODEL_ARCH.GRANITE: "granite", - MODEL_ARCH.GRANITE_MOE: "granitemoe", - MODEL_ARCH.CHAMELEON: "chameleon", - MODEL_ARCH.OUTETTS_VOC: "outetts-voc", + MODEL_ARCH.LLAMA: "llama", + MODEL_ARCH.FALCON: "falcon", + MODEL_ARCH.BAICHUAN: "baichuan", + MODEL_ARCH.GROK: "grok", + MODEL_ARCH.GPT2: "gpt2", + MODEL_ARCH.GPTJ: "gptj", + MODEL_ARCH.GPTNEOX: "gptneox", + MODEL_ARCH.MPT: "mpt", + MODEL_ARCH.STARCODER: "starcoder", + MODEL_ARCH.REFACT: "refact", + MODEL_ARCH.BERT: "bert", + MODEL_ARCH.NOMIC_BERT: "nomic-bert", + MODEL_ARCH.JINA_BERT_V2: "jina-bert-v2", + MODEL_ARCH.BLOOM: "bloom", + MODEL_ARCH.STABLELM: "stablelm", + MODEL_ARCH.QWEN: "qwen", + MODEL_ARCH.QWEN2: "qwen2", + MODEL_ARCH.QWEN2MOE: "qwen2moe", + MODEL_ARCH.QWEN2VL: "qwen2vl", + MODEL_ARCH.PHI2: "phi2", + MODEL_ARCH.PHI3: "phi3", + MODEL_ARCH.PLAMO: "plamo", + MODEL_ARCH.CODESHELL: "codeshell", + MODEL_ARCH.ORION: "orion", + MODEL_ARCH.INTERNLM2: "internlm2", + MODEL_ARCH.MINICPM: "minicpm", + MODEL_ARCH.MINICPM3: "minicpm3", + MODEL_ARCH.GEMMA: "gemma", + MODEL_ARCH.GEMMA2: "gemma2", + MODEL_ARCH.STARCODER2: "starcoder2", + MODEL_ARCH.RWKV6: "rwkv6", + MODEL_ARCH.MAMBA: "mamba", + MODEL_ARCH.XVERSE: "xverse", + MODEL_ARCH.COMMAND_R: "command-r", + MODEL_ARCH.DBRX: "dbrx", + MODEL_ARCH.OLMO: "olmo", + MODEL_ARCH.OLMO2: "olmo2", + MODEL_ARCH.OLMOE: "olmoe", + MODEL_ARCH.OPENELM: "openelm", + MODEL_ARCH.ARCTIC: "arctic", + MODEL_ARCH.DEEPSEEK: "deepseek", + MODEL_ARCH.DEEPSEEK2: "deepseek2", + MODEL_ARCH.CHATGLM: "chatglm", + MODEL_ARCH.BITNET: "bitnet", + MODEL_ARCH.T5: "t5", + MODEL_ARCH.T5ENCODER: "t5encoder", + MODEL_ARCH.JAIS: "jais", + MODEL_ARCH.NEMOTRON: "nemotron", + MODEL_ARCH.EXAONE: "exaone", + MODEL_ARCH.GRANITE: "granite", + MODEL_ARCH.GRANITE_MOE: "granitemoe", + MODEL_ARCH.CHAMELEON: "chameleon", + MODEL_ARCH.WAVTOKENIZER_DEC: "wavtokenizer-dec", } TENSOR_NAMES: dict[MODEL_TENSOR, str] = { @@ -1406,7 +1406,7 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = { MODEL_TENSOR.FFN_DOWN, MODEL_TENSOR.FFN_UP, ], - MODEL_ARCH.OUTETTS_VOC: [ + MODEL_ARCH.WAVTOKENIZER_DEC: [ MODEL_TENSOR.TOKEN_EMBD, MODEL_TENSOR.TOKEN_EMBD_NORM, MODEL_TENSOR.CONV1D, diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py index 5bf1f514a..296f1ca05 100644 --- a/gguf-py/gguf/tensor_mapping.py +++ b/gguf-py/gguf/tensor_mapping.py @@ -42,7 +42,7 @@ class TensorNameMap: "emb_ln", # nomic-bert "transformer.norm", # openelm "rwkv.blocks.0.pre_ln", # rwkv - "backbone.norm", # outetts + "backbone.norm", # wavtokenizer ), # Position embeddings @@ -61,7 +61,7 @@ class TensorNameMap: "lm_head.linear", # phi2 "output_layer", # chatglm "head", # rwkv - "head.out", # outetts + "head.out", # wavtokenizer ), # Output norm @@ -82,7 +82,7 @@ class TensorNameMap: "transformer.norm", # openelm "model.norm", # nemotron "rwkv.ln_out", # rwkv - "backbone.final_layer_norm", # outetts + "backbone.final_layer_norm", # wavtokenizer ), # Rope frequencies @@ -705,63 +705,63 @@ class TensorNameMap: ############################################################################# MODEL_TENSOR.CONV_NEXT_DW: ( - "backbone.convnext.{bid}.dwconv", # outetts + "backbone.convnext.{bid}.dwconv", # wavtokenizer ), MODEL_TENSOR.CONV_NEXT_NORM: ( - "backbone.convnext.{bid}.norm", # outetts + "backbone.convnext.{bid}.norm", # wavtokenizer ), MODEL_TENSOR.CONV_NEXT_PW1: ( - "backbone.convnext.{bid}.pwconv1", # outetts + "backbone.convnext.{bid}.pwconv1", # wavtokenizer ), MODEL_TENSOR.CONV_NEXT_PW2: ( - "backbone.convnext.{bid}.pwconv2", # outetts + "backbone.convnext.{bid}.pwconv2", # wavtokenizer ), MODEL_TENSOR.CONV_NEXT_GAMMA: ( - "backbone.convnext.{bid}.gamma", # outetts + "backbone.convnext.{bid}.gamma", # wavtokenizer ), MODEL_TENSOR.POS_NET_CONV1: ( - "backbone.pos_net.{bid}.conv1", # outetts + "backbone.pos_net.{bid}.conv1", # wavtokenizer ), MODEL_TENSOR.POS_NET_CONV2: ( - "backbone.pos_net.{bid}.conv2", # outetts + "backbone.pos_net.{bid}.conv2", # wavtokenizer ), MODEL_TENSOR.POS_NET_NORM: ( - "backbone.pos_net.{bid}.norm", # outetts + "backbone.pos_net.{bid}.norm", # wavtokenizer ), MODEL_TENSOR.POS_NET_NORM1: ( - "backbone.pos_net.{bid}.norm1", # outetts + "backbone.pos_net.{bid}.norm1", # wavtokenizer ), MODEL_TENSOR.POS_NET_NORM2: ( - "backbone.pos_net.{bid}.norm2", # outetts + "backbone.pos_net.{bid}.norm2", # wavtokenizer ), MODEL_TENSOR.POS_NET_ATTN_NORM: ( - "backbone.pos_net.{bid}.norm", # outetts + "backbone.pos_net.{bid}.norm", # wavtokenizer ), MODEL_TENSOR.POS_NET_ATTN_Q: ( - "backbone.pos_net.{bid}.q", # outetts + "backbone.pos_net.{bid}.q", # wavtokenizer ), MODEL_TENSOR.POS_NET_ATTN_K: ( - "backbone.pos_net.{bid}.k", # outetts + "backbone.pos_net.{bid}.k", # wavtokenizer ), MODEL_TENSOR.POS_NET_ATTN_V: ( - "backbone.pos_net.{bid}.v", # outetts + "backbone.pos_net.{bid}.v", # wavtokenizer ), MODEL_TENSOR.POS_NET_ATTN_OUT: ( - "backbone.pos_net.{bid}.proj_out", # outetts + "backbone.pos_net.{bid}.proj_out", # wavtokenizer ), } diff --git a/src/llama.cpp b/src/llama.cpp index 79c6e800b..ff042b856 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -197,65 +197,65 @@ enum llm_arch { LLM_ARCH_GRANITE, LLM_ARCH_GRANITE_MOE, LLM_ARCH_CHAMELEON, - LLM_ARCH_OUTETTS_VOC, + LLM_ARCH_WAVTOKENIZER_DEC, LLM_ARCH_UNKNOWN, }; static const std::map LLM_ARCH_NAMES = { - { LLM_ARCH_LLAMA, "llama" }, - { 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_NOMIC_BERT, "nomic-bert" }, - { LLM_ARCH_JINA_BERT_V2, "jina-bert-v2" }, - { 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_PHI2, "phi2" }, - { LLM_ARCH_PHI3, "phi3" }, - { LLM_ARCH_PLAMO, "plamo" }, - { 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_STARCODER2, "starcoder2" }, - { LLM_ARCH_MAMBA, "mamba" }, - { LLM_ARCH_XVERSE, "xverse" }, - { LLM_ARCH_COMMAND_R, "command-r" }, - { 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_CHATGLM, "chatglm" }, - { LLM_ARCH_BITNET, "bitnet" }, - { LLM_ARCH_T5, "t5" }, - { LLM_ARCH_T5ENCODER, "t5encoder" }, - { LLM_ARCH_JAIS, "jais" }, - { LLM_ARCH_NEMOTRON, "nemotron" }, - { LLM_ARCH_EXAONE, "exaone" }, - { LLM_ARCH_RWKV6, "rwkv6" }, - { LLM_ARCH_GRANITE, "granite" }, - { LLM_ARCH_GRANITE_MOE, "granitemoe" }, - { LLM_ARCH_CHAMELEON, "chameleon" }, - { LLM_ARCH_OUTETTS_VOC, "outetts-voc" }, - { LLM_ARCH_UNKNOWN, "(unknown)" }, + { LLM_ARCH_LLAMA, "llama" }, + { 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_NOMIC_BERT, "nomic-bert" }, + { LLM_ARCH_JINA_BERT_V2, "jina-bert-v2" }, + { 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_PHI2, "phi2" }, + { LLM_ARCH_PHI3, "phi3" }, + { LLM_ARCH_PLAMO, "plamo" }, + { 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_STARCODER2, "starcoder2" }, + { LLM_ARCH_MAMBA, "mamba" }, + { LLM_ARCH_XVERSE, "xverse" }, + { LLM_ARCH_COMMAND_R, "command-r" }, + { 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_CHATGLM, "chatglm" }, + { LLM_ARCH_BITNET, "bitnet" }, + { LLM_ARCH_T5, "t5" }, + { LLM_ARCH_T5ENCODER, "t5encoder" }, + { LLM_ARCH_JAIS, "jais" }, + { LLM_ARCH_NEMOTRON, "nemotron" }, + { LLM_ARCH_EXAONE, "exaone" }, + { LLM_ARCH_RWKV6, "rwkv6" }, + { LLM_ARCH_GRANITE, "granite" }, + { LLM_ARCH_GRANITE_MOE, "granitemoe" }, + { LLM_ARCH_CHAMELEON, "chameleon" }, + { LLM_ARCH_WAVTOKENIZER_DEC, "wavtokenizer-dec" }, + { LLM_ARCH_UNKNOWN, "(unknown)" }, }; enum llm_kv { @@ -1612,7 +1612,7 @@ static const std::map> LLM_TENSOR_N }, }, { - LLM_ARCH_OUTETTS_VOC, + LLM_ARCH_WAVTOKENIZER_DEC, { { LLM_TENSOR_TOKEN_EMBD, "token_embd" }, { LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" }, @@ -3063,7 +3063,7 @@ struct llama_model { struct ggml_tensor * cls_out = nullptr; struct ggml_tensor * cls_out_b = nullptr; - // outetts vocoder + // wavtokenizer decoder // TODO: dedup struct ggml_tensor * conv_1d = nullptr; struct ggml_tensor * conv_1d_b = nullptr; @@ -6443,7 +6443,7 @@ static void llm_load_hparams( default: model.type = e_model::MODEL_UNKNOWN; } } break; - case LLM_ARCH_OUTETTS_VOC: + case LLM_ARCH_WAVTOKENIZER_DEC: { ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps); } break; @@ -9545,7 +9545,7 @@ static bool llm_load_tensors( layer.ffn_up = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff}, 0); } } break; - case LLM_ARCH_OUTETTS_VOC: + case LLM_ARCH_WAVTOKENIZER_DEC: { model.tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {512, n_vocab}, 0); @@ -16142,7 +16142,7 @@ struct llm_build_context { return gf; } - struct ggml_cgraph * build_t5_encoder() { + struct ggml_cgraph * build_t5_enc() { struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, llama_model_max_nodes(model), false); // mutable variable, needed during the last layer of the computation to skip unused tokens @@ -16274,7 +16274,7 @@ struct llm_build_context { return gf; } - struct ggml_cgraph * build_t5_decoder() { + struct ggml_cgraph * build_t5_dec() { struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, llama_model_max_nodes(model), false); // mutable variable, needed during the last layer of the computation to skip unused tokens @@ -17224,7 +17224,7 @@ struct llm_build_context { return gf; } - struct ggml_cgraph * build_outetts_voc() { + struct ggml_cgraph * build_wavtokenizer_dec() { struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, llama_model_max_nodes(model), false); struct ggml_tensor * cur; @@ -17692,14 +17692,14 @@ static struct ggml_cgraph * llama_build_graph( case LLM_ARCH_T5: { if (lctx.is_encoding) { - result = llm.build_t5_encoder(); + result = llm.build_t5_enc(); } else { - result = llm.build_t5_decoder(); + result = llm.build_t5_dec(); } } break; case LLM_ARCH_T5ENCODER: { - result = llm.build_t5_encoder(); + result = llm.build_t5_enc(); } break; case LLM_ARCH_JAIS: { @@ -17721,9 +17721,9 @@ static struct ggml_cgraph * llama_build_graph( { result = llm.build_chameleon(); } break; - case LLM_ARCH_OUTETTS_VOC: + case LLM_ARCH_WAVTOKENIZER_DEC: { - result = llm.build_outetts_voc(); + result = llm.build_wavtokenizer_dec(); } break; default: GGML_ABORT("fatal error"); @@ -20904,7 +20904,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) { case LLM_ARCH_T5ENCODER: case LLM_ARCH_JAIS: case LLM_ARCH_RWKV6: - case LLM_ARCH_OUTETTS_VOC: + case LLM_ARCH_WAVTOKENIZER_DEC: return LLAMA_ROPE_TYPE_NONE; // use what we call a normal RoPE, operating on pairs of consecutive head values