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mtmd : add qwen2vl and qwen2.5vl (#13141)

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* llava : add clip_n_output_tokens, deprecate clip_n_patches

* mtmd : add qwen2vl and qwen2.5vl

* decode_embd_batch::set_position_...

* working version

* deprecate llama-qwen2vl-cli

* correct order W, H of clip_embd_nbytes_by_img

* edit existing line in hot topics
This commit is contained in:
Xuan-Son Nguyen
2025-04-29 11:47:04 +02:00
committed by GitHub
parent e98b3692be
commit 00e3e5a194
10 changed files with 196 additions and 79 deletions
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146
examples/llava/mtmd.cpp
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@ -40,11 +40,14 @@ struct mtmd_context {
llama_token tok_sli_img_end = LLAMA_TOKEN_NULL; // single slice
llama_token tok_row_end = LLAMA_TOKEN_NULL; // end of row
bool use_mrope = false; // for Qwen2VL, we need to use M-RoPE
// TODO @ngxson : add timings
mtmd_context(const char * mmproj_fname,
const llama_model * text_model,
const mtmd_context_params & ctx_params) :
text_model (text_model),
print_timings(ctx_params.print_timings),
n_threads (ctx_params.n_threads),
image_marker (ctx_params.image_marker)
@ -56,9 +59,8 @@ struct mtmd_context {
if (!ctx_clip) {
throw std::runtime_error(string_format("Failed to load CLIP model from %s\n", mmproj_fname));
}
this->text_model = text_model;
GGML_ASSERT(!clip_is_qwen2vl(ctx_clip) && "Qwen2VL model is not supported yet, use llama-qwen2vl-cli instead");
use_mrope = clip_is_qwen2vl(ctx_clip);
int minicpmv_version = clip_is_minicpmv(ctx_clip);
if (minicpmv_version == 2) {
@ -126,6 +128,7 @@ struct mtmd_image_tokens_data {
struct mtmd_image_tokens {
uint32_t nx; // number of tokens in x direction
uint32_t ny; // number of tokens in y direction
bool use_mrope_pos = false; // use M-RoPE position counting (the whole image is 1 temporal position)
uint32_t n_tokens() const { return nx * ny; }
clip_image_f32_batch batch_f32; // preprocessed image patches
std::string id; // optional user-defined ID, useful for KV cache tracking
@ -202,6 +205,13 @@ int32_t mtmd_tokenize(mtmd_context * ctx,
string_replace_all(prompt_modified, ctx->image_marker, marker_modified);
}
else if (proj_type == PROJECTOR_TYPE_QWEN2VL || proj_type == PROJECTOR_TYPE_QWEN25VL) {
// <|vision_start|> ... (image embeddings) ... <|vision_end|>
marker_modified = "<|vision_start|>" + ctx->image_marker + "<|vision_end|>";
string_replace_all(prompt_modified, ctx->image_marker, marker_modified);
}
// llava-1.5, llava-1.6, Yi-VL, Yi-34B, granite: don't need to add prefix and suffix
std::vector<std::string> parts = string_split_str(prompt_modified, ctx->image_marker);
@ -226,7 +236,7 @@ int32_t mtmd_tokenize(mtmd_context * ctx,
for (auto & entry : batch_f32.entries) {
mtmd_image_tokens_ptr image_tokens(new mtmd_image_tokens);
image_tokens->nx = clip_n_patches_by_img(ctx->ctx_clip, entry.get());
image_tokens->nx = clip_n_output_tokens(ctx->ctx_clip, entry.get());
image_tokens->ny = 1;
image_tokens->batch_f32.entries.push_back(std::move(entry));
image_tokens->id = id;
@ -322,12 +332,20 @@ int32_t mtmd_tokenize(mtmd_context * ctx,
} else {
size_t n_tokens = 0;
for (const auto & entry : batch_f32.entries) {
n_tokens += clip_n_patches_by_img(ctx->ctx_clip, entry.get());
n_tokens += clip_n_output_tokens(ctx->ctx_clip, entry.get());
}
mtmd_image_tokens_ptr image_tokens(new mtmd_image_tokens);
image_tokens->nx = n_tokens;
image_tokens->ny = 1; // TODO
if (ctx->use_mrope) {
// for Qwen2VL, we need this information for M-RoPE decoding positions
image_tokens->nx = clip_n_output_tokens_x(ctx->ctx_clip, batch_f32.entries[0].get());
image_tokens->ny = clip_n_output_tokens_y(ctx->ctx_clip, batch_f32.entries[0].get());
image_tokens->use_mrope_pos = true;
} else {
// other models, we only need the total number of tokens
image_tokens->nx = n_tokens;
image_tokens->ny = 1;
}
image_tokens->batch_f32 = std::move(batch_f32);
image_tokens->id = bitmaps[i_img].id; // optional
@ -372,6 +390,13 @@ std::string mtmd_image_tokens_get_id(const mtmd_image_tokens * image_tokens) {
return image_tokens->id;
}
llama_pos mtmd_image_tokens_get_n_pos(const mtmd_image_tokens * image_tokens) {
if (image_tokens->use_mrope_pos) {
return 1; // for M-RoPE, the whole image is 1 in temporal dimension
}
return image_tokens->n_tokens();
}
int32_t mtmd_encode(mtmd_context * ctx, const mtmd_image_tokens * image_tokens) {
int n_mmproj_embd = clip_n_mmproj_embd(ctx->ctx_clip);
ctx->image_embd_v.resize(image_tokens->n_tokens() * n_mmproj_embd);
@ -389,7 +414,7 @@ int32_t mtmd_encode(mtmd_context * ctx, const mtmd_image_tokens * image_tokens)
// TODO @ngxson : llava does not support batched encoding ; this should be fixed inside clip_image_batch_encode()
const auto & entries = image_tokens->batch_f32.entries;
for (size_t i = 0; i < entries.size(); i++) {
int n_tokens_per_image = clip_n_patches_by_img(ctx->ctx_clip, entries[i].get());
int n_tokens_per_image = clip_n_output_tokens(ctx->ctx_clip, entries[i].get());
ok = clip_image_encode(
ctx->ctx_clip,
ctx->n_threads,
@ -417,7 +442,7 @@ size_t mtmd_helper_get_n_tokens(mtmd_input_chunks & chunks) {
if (chunk.type == MTMD_INPUT_CHUNK_TYPE_TEXT) {
n_tokens += chunk.tokens_text.size();
} else if (chunk.type == MTMD_INPUT_CHUNK_TYPE_IMAGE) {
n_tokens += chunk.tokens_image->n_tokens();
n_tokens += mtmd_image_tokens_get_n_tokens(chunk.tokens_image.get());
} else {
GGML_ASSERT(false && "chunk type not supported");
}
@ -425,22 +450,38 @@ size_t mtmd_helper_get_n_tokens(mtmd_input_chunks & chunks) {
return n_tokens;
}
llama_pos mtmd_helper_get_n_pos(mtmd_input_chunks & chunks) {
llama_pos n_pos = 0;
for (auto & chunk : chunks) {
if (chunk.type == MTMD_INPUT_CHUNK_TYPE_TEXT) {
n_pos += chunk.tokens_text.size();
} else if (chunk.type == MTMD_INPUT_CHUNK_TYPE_IMAGE) {
n_pos += mtmd_image_tokens_get_n_pos(chunk.tokens_image.get());
} else {
GGML_ASSERT(false && "chunk type not supported");
}
}
return n_pos;
}
// helper struct to make working with embd batch easier
// note: this will be removed after llama_batch_ext refactoring
struct decode_embd_batch {
int n_pos_per_embd;
int n_mmproj_embd;
std::vector<llama_pos> pos;
std::vector<llama_pos> pos_view; // used by mrope
std::vector<int32_t> n_seq_id;
std::vector<llama_seq_id> seq_id_0;
std::vector<llama_seq_id *> seq_ids;
std::vector<int8_t> logits;
llama_batch batch;
decode_embd_batch(float * embd, int32_t n_tokens, llama_pos pos_0, llama_seq_id seq_id) {
pos .resize(n_tokens);
decode_embd_batch(float * embd, int32_t n_tokens, int n_pos_per_embd, int n_mmproj_embd) : n_pos_per_embd(n_pos_per_embd), n_mmproj_embd(n_mmproj_embd) {
pos .resize(n_tokens * n_pos_per_embd);
n_seq_id.resize(n_tokens);
seq_ids .resize(n_tokens + 1);
logits .resize(n_tokens);
seq_id_0.resize(1);
seq_id_0[0] = seq_id;
seq_ids [n_tokens] = nullptr;
batch = {
/*n_tokens =*/ n_tokens,
@ -451,13 +492,64 @@ struct decode_embd_batch {
/*seq_id =*/ seq_ids.data(),
/*logits =*/ logits.data(),
};
for (int i = 0; i < n_tokens; i++) {
}
void set_position_normal(llama_pos pos_0, llama_seq_id seq_id) {
seq_id_0[0] = seq_id;
for (int i = 0; i < batch.n_tokens; i++) {
batch.pos [i] = pos_0 + i;
batch.n_seq_id[i] = 1;
batch.seq_id [i] = seq_id_0.data();
batch.logits [i] = false;
}
}
void set_position_mrope(llama_pos pos_0, int nx, int ny, llama_seq_id seq_id) {
GGML_ASSERT(n_pos_per_embd == 4);
seq_id_0[0] = seq_id;
for (int y = 0; y < ny; y++) {
for (int x = 0; x < nx; x++) {
int i = y * nx + x;
pos[i ] = pos_0;
pos[i + batch.n_tokens ] = pos_0 + y;
pos[i + batch.n_tokens * 2] = pos_0 + x;
pos[i + batch.n_tokens * 3] = 0; // last pos dim is unused
}
}
for (int i = 0; i < batch.n_tokens; i++) {
batch.n_seq_id[i] = 1;
batch.seq_id [i] = seq_id_0.data();
batch.logits [i] = false;
}
}
llama_batch get_view(int offset, int n_tokens) {
llama_pos * pos_ptr;
pos_view.clear();
pos_view.resize(n_tokens * n_pos_per_embd);
if (n_pos_per_embd > 1) {
// mrope
// for example, with layout of src: 1234...1234...1234...1234...
// offset 2 will give us dst: 34...34...34...34...
for (int i = 0; i < n_pos_per_embd; i++) {
auto src = pos.begin() + i * batch.n_tokens + offset;
pos_view.insert(pos_view.end(), src, src + n_tokens);
}
pos_ptr = pos_view.data();
} else {
// normal
pos_ptr = pos.data() + offset;
}
return {
/*n_tokens =*/ n_tokens,
/*tokens =*/ nullptr,
/*embd =*/ batch.embd + offset * n_mmproj_embd,
/*pos =*/ pos_ptr,
/*n_seq_id =*/ batch.n_seq_id + offset,
/*seq_id =*/ batch.seq_id + offset,
/*logits =*/ batch.logits + offset,
};
}
};
int32_t mtmd_helper_eval(mtmd_context * ctx,
@ -470,6 +562,7 @@ int32_t mtmd_helper_eval(mtmd_context * ctx,
llama_pos n_past = pos0;
llama_batch text_batch = llama_batch_init(n_batch, 0, 1);
int n_mmproj_embd = clip_n_mmproj_embd(ctx->ctx_clip);
int n_pos_per_embd = mtmd_decode_use_mrope(ctx) ? 4 : 1;
for (auto & chunk : chunks) {
bool is_last = &chunk == &chunks.back();
@ -517,6 +610,16 @@ int32_t mtmd_helper_eval(mtmd_context * ctx,
int32_t i_batch = 0;
int32_t n_img_batches = GGML_PAD(n_tokens, n_batch) / n_batch;
float * embd = mtmd_get_output_embd(ctx);
decode_embd_batch batch_embd(embd, n_tokens, n_pos_per_embd, n_mmproj_embd);
const int nx = mtmd_image_tokens_get_nx(chunk.tokens_image.get());
const int ny = mtmd_image_tokens_get_ny(chunk.tokens_image.get());
if (mtmd_decode_use_mrope(ctx)) {
batch_embd.set_position_mrope(n_past, nx, ny, seq_id);
} else {
batch_embd.set_position_normal(n_past, seq_id);
}
if (mtmd_decode_use_non_causal(ctx)) {
llama_set_causal_attn(lctx, false);
@ -524,15 +627,14 @@ int32_t mtmd_helper_eval(mtmd_context * ctx,
}
while (i_batch < n_img_batches) { // split into batches
int32_t pos_offset = i_batch*n_batch;
int32_t n_tokens_batch = std::min(n_batch, n_tokens - pos_offset);
float * embd_batch = embd + pos_offset*n_mmproj_embd;
decode_embd_batch batch_img(embd_batch, n_tokens_batch, n_past, 0);
int pos_offset = i_batch*n_batch;
int n_tokens_batch = std::min(n_batch, n_tokens - pos_offset);
llama_batch batch_embd_view = batch_embd.get_view(pos_offset, n_tokens_batch);
printf("decoding image batch %d/%d, n_tokens_batch = %d\n", i_batch+1, n_img_batches, n_tokens_batch);
LOG_INF("decoding image batch %d/%d, n_tokens_batch = %d\n", i_batch+1, n_img_batches, n_tokens_batch);
int64_t t1 = ggml_time_ms();
ret = llama_decode(lctx, batch_img.batch);
ret = llama_decode(lctx, batch_embd_view);
if (ret != 0) {
LOG_ERR("failed to decode image\n");
llama_set_causal_attn(lctx, true); // restore causal attn
@ -545,9 +647,11 @@ int32_t mtmd_helper_eval(mtmd_context * ctx,
}
i_batch++;
n_past += n_tokens_batch;
}
// for mrope, one image is one single **temporal** position
n_past += mtmd_decode_use_mrope(ctx) ? 1 : n_tokens;
if (mtmd_decode_use_non_causal(ctx)) {
llama_set_causal_attn(lctx, true);
}
@ -595,6 +699,10 @@ bool mtmd_decode_use_non_causal(mtmd_context * ctx) {
return false;
}
bool mtmd_decode_use_mrope(mtmd_context * ctx) {
return ctx->use_mrope;
}
void mtmd_image_tokens_deleter::operator()(mtmd_image_tokens * val) {
mtmd_image_tokens_free(val);
}