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ba7d31240e
expand backend loading error handling to catch more problems and log them instead of panicing
80 lines
4.6 KiB
Diff
80 lines
4.6 KiB
Diff
From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
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From: jmorganca <jmorganca@gmail.com>
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Date: Thu, 27 Feb 2025 15:12:26 -0800
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Subject: [PATCH] add phi4 support
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---
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include/llama.h | 1 +
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src/llama-model.cpp | 10 +++++++---
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src/llama-vocab.cpp | 11 +++++++++++
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3 files changed, 19 insertions(+), 3 deletions(-)
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diff --git a/include/llama.h b/include/llama.h
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index cc948005..16774711 100644
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--- a/include/llama.h
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+++ b/include/llama.h
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@@ -105,6 +105,7 @@ extern "C" {
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LLAMA_VOCAB_PRE_TYPE_CHAMELEON = 26,
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LLAMA_VOCAB_PRE_TYPE_MINERVA = 27,
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LLAMA_VOCAB_PRE_TYPE_DEEPSEEK3_LLM = 28,
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+ LLAMA_VOCAB_PRE_TYPE_GPT4O = 29,
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};
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enum llama_rope_type {
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diff --git a/src/llama-model.cpp b/src/llama-model.cpp
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index 21819080..ab1a07d1 100644
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--- a/src/llama-model.cpp
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+++ b/src/llama-model.cpp
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@@ -2283,7 +2283,11 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
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// output
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output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), { n_embd }, 0);
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- output = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), { n_embd, n_vocab }, 0);
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+ output = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);
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+ // if output is NULL, init from the input tok embed
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+ if (output == NULL) {
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+ output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);
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+ }
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for (int i = 0; i < n_layer; ++i) {
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auto & layer = layers[i];
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@@ -2298,8 +2302,8 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
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layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd }, 0);
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layer.ffn_up = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), { n_embd, 2 * n_ff }, 0);
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- layer.rope_long = create_tensor(tn(LLM_TENSOR_ROPE_FACTORS_LONG, "weight", i), { n_embd_head/2 }, TENSOR_NOT_REQUIRED | (i != 0 ? TENSOR_DUPLICATED : 0));
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- layer.rope_short = create_tensor(tn(LLM_TENSOR_ROPE_FACTORS_SHORT, "weight", i), { n_embd_head/2 }, TENSOR_NOT_REQUIRED | (i != 0 ? TENSOR_DUPLICATED : 0));
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+ layer.rope_long = create_tensor(tn(LLM_TENSOR_ROPE_FACTORS_LONG, "weight", i), { n_rot/2 }, TENSOR_NOT_REQUIRED | (i != 0 ? TENSOR_DUPLICATED : 0));
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+ layer.rope_short = create_tensor(tn(LLM_TENSOR_ROPE_FACTORS_SHORT, "weight", i), { n_rot/2 }, TENSOR_NOT_REQUIRED | (i != 0 ? TENSOR_DUPLICATED : 0));
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}
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} break;
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case LLM_ARCH_PHIMOE:
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diff --git a/src/llama-vocab.cpp b/src/llama-vocab.cpp
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index 1ca827eb..c7ff28be 100644
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--- a/src/llama-vocab.cpp
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+++ b/src/llama-vocab.cpp
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@@ -392,6 +392,13 @@ struct llm_tokenizer_bpe : llm_tokenizer {
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"'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
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};
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break;
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+ case LLAMA_VOCAB_PRE_TYPE_GPT4O:
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+ // original regex from tokenizer.json
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+ // [^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]*[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]+(?i:'s|'t|'re|'ve|'m|'ll|'d)?|[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]+[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]*(?i:'s|'t|'re|'ve|'m|'ll|'d)?|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+
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+ regex_exprs = {
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+ "[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))*((?=[\\p{L}])([^A-Z]))+(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])?|[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))+((?=[\\p{L}])([^A-Z]))*(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])?|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+"
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+ };
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+ break;
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default:
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// default regex for BPE tokenization pre-processing
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regex_exprs = {
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@@ -1583,6 +1590,10 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
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} else if (
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tokenizer_pre == "megrez") {
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pre_type = LLAMA_VOCAB_PRE_TYPE_QWEN2;
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+ } else if (
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+ tokenizer_pre == "gpt-4o") {
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+ pre_type = LLAMA_VOCAB_PRE_TYPE_GPT4O;
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+ clean_spaces = false;
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} else {
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LLAMA_LOG_WARN("%s: missing or unrecognized pre-tokenizer type, using: 'default'\n", __func__);
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pre_type = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
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