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HiDream support

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#248
This commit is contained in:
City
2025-04-16 01:43:15 +02:00
parent 794fc28536
commit 2ef5a66a9f
3 changed files with 46 additions and 21 deletions
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tools/lcpp.patch
+32 -19
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@@ -39,10 +39,10 @@ index b16c462f..6d1568f1 100644
const int idx = gguf_find_tensor(ctx, name);
if (idx < 0) {
diff --git a/src/llama.cpp b/src/llama.cpp
index 24e1f1f0..d3ca4756 100644
index 24e1f1f0..6a0c0a0e 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -205,6 +205,14 @@ enum llm_arch {
@@ -205,6 +205,15 @@ enum llm_arch {
LLM_ARCH_GRANITE,
LLM_ARCH_GRANITE_MOE,
LLM_ARCH_CHAMELEON,
@@ -54,10 +54,11 @@ index 24e1f1f0..d3ca4756 100644
+ LLM_ARCH_LTXV,
+ LLM_ARCH_HYVID,
+ LLM_ARCH_WAN,
+ LLM_ARCH_HIDREAM,
LLM_ARCH_UNKNOWN,
};
@@ -258,6 +266,14 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
@@ -258,6 +267,15 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
{ LLM_ARCH_GRANITE, "granite" },
{ LLM_ARCH_GRANITE_MOE, "granitemoe" },
{ LLM_ARCH_CHAMELEON, "chameleon" },
@@ -69,25 +70,27 @@ index 24e1f1f0..d3ca4756 100644
+ { LLM_ARCH_LTXV, "ltxv" },
+ { LLM_ARCH_HYVID, "hyvid" },
+ { LLM_ARCH_WAN, "wan" },
+ { LLM_ARCH_HIDREAM, "hidream" },
{ LLM_ARCH_UNKNOWN, "(unknown)" },
};
@@ -1531,6 +1547,14 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
@@ -1531,6 +1549,15 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" },
},
},
+ { LLM_ARCH_FLUX, {}},
+ { LLM_ARCH_SD1, {}},
+ { LLM_ARCH_SDXL, {}},
+ { LLM_ARCH_SD3, {}},
+ { LLM_ARCH_AURA, {}},
+ { LLM_ARCH_LTXV, {}},
+ { LLM_ARCH_HYVID,{}},
+ { LLM_ARCH_WAN,{}},
+ { LLM_ARCH_FLUX, {}},
+ { LLM_ARCH_SD1, {}},
+ { LLM_ARCH_SDXL, {}},
+ { LLM_ARCH_SD3, {}},
+ { LLM_ARCH_AURA, {}},
+ { LLM_ARCH_LTXV, {}},
+ { LLM_ARCH_HYVID, {}},
+ { LLM_ARCH_WAN, {}},
+ { LLM_ARCH_HIDREAM, {}},
{
LLM_ARCH_UNKNOWN,
{
@@ -5403,6 +5427,22 @@ static void llm_load_hparams(
@@ -5403,6 +5430,23 @@ static void llm_load_hparams(
// get general kv
ml.get_key(LLM_KV_GENERAL_NAME, model.name, false);
@@ -101,6 +104,7 @@ index 24e1f1f0..d3ca4756 100644
+ case LLM_ARCH_LTXV:
+ case LLM_ARCH_HYVID:
+ case LLM_ARCH_WAN:
+ case LLM_ARCH_HIDREAM:
+ model.ftype = ml.ftype;
+ return;
+ default:
@@ -110,7 +114,7 @@ index 24e1f1f0..d3ca4756 100644
// get hparams kv
ml.get_key(LLM_KV_VOCAB_SIZE, hparams.n_vocab, false) || ml.get_arr_n(LLM_KV_TOKENIZER_LIST, hparams.n_vocab);
@@ -18016,6 +18056,128 @@ static void llama_tensor_dequantize_internal(
@@ -18016,6 +18060,128 @@ static void llama_tensor_dequantize_internal(
workers.clear();
}
@@ -239,7 +243,7 @@ index 24e1f1f0..d3ca4756 100644
static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type new_type, const ggml_tensor * tensor, llama_ftype ftype) {
const std::string name = ggml_get_name(tensor);
@@ -18513,7 +18675,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
@@ -18513,7 +18679,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
if (llama_model_has_encoder(&model)) {
n_attn_layer *= 3;
}
@@ -250,7 +254,7 @@ index 24e1f1f0..d3ca4756 100644
}
size_t total_size_org = 0;
@@ -18547,6 +18711,45 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
@@ -18547,6 +18715,45 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
ctx_outs[i_split] = gguf_init_empty();
}
gguf_add_tensor(ctx_outs[i_split], tensor);
@@ -296,7 +300,7 @@ index 24e1f1f0..d3ca4756 100644
}
// Set split info if needed
@@ -18647,6 +18850,83 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
@@ -18647,6 +18854,92 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
// do not quantize relative position bias (T5)
quantize &= name.find("attn_rel_b.weight") == std::string::npos;
@@ -372,6 +376,15 @@ index 24e1f1f0..d3ca4756 100644
+ quantize &= name.find("img_emb.") == std::string::npos;
+ quantize &= name.find("head.") == std::string::npos;
+ }
+ if (model.arch == LLM_ARCH_HIDREAM) {
+ image_model = true;
+ quantize &= name.find("p_embedder.") == std::string::npos;
+ quantize &= name.find("t_embedder.") == std::string::npos;
+ quantize &= name.find("x_embedder.") == std::string::npos;
+ quantize &= name.find("final_layer.") == std::string::npos;
+ quantize &= name.find(".ff_i.gate.weight") == std::string::npos;
+ quantize &= name.find("caption_projection.") == std::string::npos;
+ }
+ // ignore 3D/4D tensors for image models as the code was never meant to handle these
+ if (image_model) {
+ quantize &= ggml_n_dims(tensor) == 2;
@@ -380,7 +393,7 @@ index 24e1f1f0..d3ca4756 100644
enum ggml_type new_type;
void * new_data;
size_t new_size;
@@ -18655,6 +18935,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
@@ -18655,6 +18948,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
new_type = default_type;
// get more optimal quantization type based on the tensor shape, layer, etc.
@@ -390,7 +403,7 @@ index 24e1f1f0..d3ca4756 100644
if (!params->pure && ggml_is_quantized(default_type)) {
new_type = llama_tensor_get_type(qs, new_type, tensor, ftype);
}
@@ -18664,6 +18947,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
@@ -18664,6 +18960,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
if (params->output_tensor_type < GGML_TYPE_COUNT && strcmp(tensor->name, "output.weight") == 0) {
new_type = params->output_tensor_type;
}