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llava : support for Yi-VL and fix for mobileVLM (#5093)

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* Support for Yi-VL, templating fix for mobileVLM

* ws

* Update examples/llava/clip.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update llava-cli.cpp

* Update clip.cpp

bugfix for new conversions

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
John 2024-01-27 16:09:18 +01:00 • committed by GitHub
parent 753eafed0e
commit 6db2b41a76
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2 changed files with 92 additions and 10 deletions
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70
examples/llava/clip.cpp
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@ -98,6 +98,7 @@ static std::string format(const char * fmt, ...) {
enum projector_type {
PROJECTOR_TYPE_MLP,
PROJECTOR_TYPE_MLP_NORM,
PROJECTOR_TYPE_LDP,
PROJECTOR_TYPE_UNKNOWN,
};
@ -304,10 +305,18 @@ struct clip_vision_model {
struct ggml_tensor * projection;
// LLaVA projection
struct ggml_tensor * mm_0_w;
struct ggml_tensor * mm_0_b;
struct ggml_tensor * mm_2_w;
struct ggml_tensor * mm_2_b;
struct ggml_tensor * mm_0_w = NULL;
struct ggml_tensor * mm_0_b = NULL;
struct ggml_tensor * mm_2_w = NULL;
struct ggml_tensor * mm_2_b = NULL;
// Yi type models with mlp+normalization projection
struct ggml_tensor * mm_1_w = NULL; // Yi type models have 0, 1, 3, 4
struct ggml_tensor * mm_1_b = NULL;
struct ggml_tensor * mm_3_w = NULL;
struct ggml_tensor * mm_3_b = NULL;
struct ggml_tensor * mm_4_w = NULL;
struct ggml_tensor * mm_4_b = NULL;
// MobileVLM projection
struct ggml_tensor * mm_model_mlp_1_w;
@ -460,6 +469,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32
// pre-layernorm
{
embeddings = ggml_norm(ctx0, embeddings, eps);
ggml_set_name(embeddings, "pre_ln");
embeddings = ggml_add(ctx0, ggml_mul(ctx0, embeddings, model.pre_ln_w), model.pre_ln_b);
}
@ -575,6 +585,27 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32
embeddings = ggml_mul_mat(ctx0, model.mm_2_w, embeddings);
embeddings = ggml_add(ctx0, embeddings, model.mm_2_b);
} else if (ctx->proj_type == PROJECTOR_TYPE_MLP_NORM) {
embeddings = ggml_mul_mat(ctx0, model.mm_0_w, embeddings);
embeddings = ggml_add(ctx0, embeddings, model.mm_0_b);
// ggml_tensor_printf(embeddings, "mm_0_w",0,true,false);
// First LayerNorm
embeddings = ggml_norm(ctx0, embeddings, eps);
embeddings = ggml_add(ctx0, ggml_mul(ctx0, embeddings, model.mm_1_w),
model.mm_1_b);
// GELU activation
embeddings = ggml_gelu(ctx0, embeddings);
// Second linear layer
embeddings = ggml_mul_mat(ctx0, model.mm_3_w, embeddings);
embeddings = ggml_add(ctx0, embeddings, model.mm_3_b);
// Second LayerNorm
embeddings = ggml_norm(ctx0, embeddings, eps);
embeddings = ggml_add(ctx0, ggml_mul(ctx0, embeddings, model.mm_4_w),
model.mm_4_b);
}
else if (ctx->proj_type == PROJECTOR_TYPE_LDP) {
// MobileVLM projector
@ -808,6 +839,11 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
else {
new_clip->proj_type = PROJECTOR_TYPE_MLP;
}
if (new_clip->proj_type == PROJECTOR_TYPE_MLP) {
if (gguf_find_tensor(ctx, format(TN_LLAVA_PROJ, 3, "weight").c_str()) != -1) {
new_clip->proj_type = PROJECTOR_TYPE_MLP_NORM;
}
}
}
#ifdef GGML_USE_CUBLAS
@ -956,11 +992,29 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
vision_model.pre_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "bias"));
// LLaVA projection
if (new_clip->proj_type == PROJECTOR_TYPE_MLP) {
if (new_clip->proj_type == PROJECTOR_TYPE_MLP || new_clip->proj_type == PROJECTOR_TYPE_MLP_NORM) {
vision_model.mm_0_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 0, "weight"));
vision_model.mm_0_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 0, "bias"));
vision_model.mm_2_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "weight"));
vision_model.mm_2_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "bias"));
try {
// Yi-type llava
vision_model.mm_1_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 1, "weight"));
vision_model.mm_1_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 1, "bias"));
} catch (std::runtime_error & e) { }
try {
// missing in Yi-type llava
vision_model.mm_2_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "weight"));
vision_model.mm_2_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "bias"));
} catch (std::runtime_error & e) { }
try {
// Yi-type llava
vision_model.mm_3_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 3, "weight"));
vision_model.mm_3_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 3, "bias"));
} catch (std::runtime_error & e) { }
try {
// Yi-type llava
vision_model.mm_4_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 4, "weight"));
vision_model.mm_4_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 4, "bias"));
} catch (std::runtime_error & e) { }
}
else if (new_clip->proj_type == PROJECTOR_TYPE_LDP) {
// MobileVLM projection
@ -1432,6 +1486,8 @@ int clip_n_mmproj_embd(const struct clip_ctx * ctx) {
}
else if (ctx->proj_type == PROJECTOR_TYPE_MLP) {
return ctx->vision_model.mm_2_b->ne[0];
} else if (ctx->proj_type == PROJECTOR_TYPE_MLP_NORM) {
return ctx->vision_model.mm_3_b->ne[0];
}
else {
std::string proj_type = PROJECTOR_TYPE_NAMES[ctx->proj_type];