mtmd : Expose helper_decode_image_chunk (#13366)
* mtmd: Expose helper_decode_image, output_embd_copy, image_tokens_copy/free * Slim down * Cleanups
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Matt Clayton
GitHub
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ee01d71e58
commit
f05a6d71a0
2 changed files with 90 additions and 51 deletions
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@ -580,6 +580,79 @@ struct decode_embd_batch {
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}
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};
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// Helper function for decoding an image whose embeddings have already been calculated
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int32_t mtmd_helper_decode_image_chunk(
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mtmd_context * ctx,
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struct llama_context * lctx,
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const mtmd_input_chunk * chunk,
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float * encoded_embd,
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llama_pos n_past,
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llama_seq_id seq_id,
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int32_t n_batch,
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llama_pos * new_n_past) {
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if (mtmd_input_chunk_get_type(chunk) != MTMD_INPUT_CHUNK_TYPE_IMAGE) {
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LOG_ERR("failed to decode image chunk: input chunk not of image type\n");
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return -1;
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}
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const auto image_tokens = mtmd_input_chunk_get_tokens_image(chunk);
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if (!image_tokens) {
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LOG_ERR("failed to decode image chunk: image tokens are null\n");
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return -1;
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}
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int n_mmproj_embd = clip_n_mmproj_embd(ctx->ctx_clip);
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int n_pos_per_embd = mtmd_decode_use_mrope(ctx) ? 4 : 1;
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int32_t n_tokens = mtmd_image_tokens_get_n_tokens(image_tokens);
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int32_t i_batch = 0;
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int32_t n_img_batches = GGML_PAD(n_tokens, n_batch) / n_batch;
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decode_embd_batch batch_embd(encoded_embd, n_tokens, n_pos_per_embd, n_mmproj_embd);
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const int nx = mtmd_image_tokens_get_nx(image_tokens);
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const int ny = mtmd_image_tokens_get_ny(image_tokens);
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if (mtmd_decode_use_mrope(ctx)) {
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batch_embd.set_position_mrope(n_past, nx, ny, seq_id);
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} else {
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batch_embd.set_position_normal(n_past, seq_id);
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}
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if (mtmd_decode_use_non_causal(ctx)) {
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llama_set_causal_attn(lctx, false);
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// TODO @ngxson : need to make sure only one image is processed at a time, and n_ubatch must be enough to hold the image
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}
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while (i_batch < n_img_batches) { // split into batches
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int pos_offset = i_batch*n_batch;
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int n_tokens_batch = std::min(n_batch, n_tokens - pos_offset);
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llama_batch batch_embd_view = batch_embd.get_view(pos_offset, n_tokens_batch);
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LOG_INF("decoding image batch %d/%d, n_tokens_batch = %d\n", i_batch+1, n_img_batches, n_tokens_batch);
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int64_t t1 = ggml_time_ms();
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int32_t ret = llama_decode(lctx, batch_embd_view);
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if (ret != 0) {
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LOG_ERR("failed to decode image\n");
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llama_set_causal_attn(lctx, true); // restore causal attn
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return ret;
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}
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if (ctx->print_timings) {
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LOG_INF("image decoded (batch %d/%d) in %" PRId64 " ms\n", i_batch+1, n_img_batches, ggml_time_ms() - t1);
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}
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i_batch++;
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}
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n_past += mtmd_image_tokens_get_n_pos(image_tokens);
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*new_n_past = n_past;
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if (mtmd_decode_use_non_causal(ctx)) {
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llama_set_causal_attn(lctx, true);
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}
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return 0;
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}
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int32_t mtmd_helper_eval_chunk_single(mtmd_context * ctx,
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struct llama_context * lctx,
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const mtmd_input_chunk * chunk,
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@ -591,8 +664,6 @@ int32_t mtmd_helper_eval_chunk_single(mtmd_context * ctx,
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int32_t ret;
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llama_batch text_batch = llama_batch_init(n_batch, 0, 1);
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auto chunk_type = mtmd_input_chunk_get_type(chunk);
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int n_mmproj_embd = clip_n_mmproj_embd(ctx->ctx_clip);
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int n_pos_per_embd = mtmd_decode_use_mrope(ctx) ? 4 : 1;
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if (chunk_type == MTMD_INPUT_CHUNK_TYPE_TEXT) {
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size_t n_tokens;
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@ -637,57 +708,13 @@ int32_t mtmd_helper_eval_chunk_single(mtmd_context * ctx,
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if (ctx->print_timings) {
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LOG_INF("image/slice encoded in %" PRId64 " ms\n", ggml_time_ms() - t0);
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}
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int32_t n_tokens = mtmd_image_tokens_get_n_tokens(image_tokens);
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int32_t i_batch = 0;
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int32_t n_img_batches = GGML_PAD(n_tokens, n_batch) / n_batch;
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float * embd = mtmd_get_output_embd(ctx);
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decode_embd_batch batch_embd(embd, n_tokens, n_pos_per_embd, n_mmproj_embd);
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const int nx = mtmd_image_tokens_get_nx(image_tokens);
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const int ny = mtmd_image_tokens_get_ny(image_tokens);
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if (mtmd_decode_use_mrope(ctx)) {
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batch_embd.set_position_mrope(n_past, nx, ny, seq_id);
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} else {
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batch_embd.set_position_normal(n_past, seq_id);
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ret = mtmd_helper_decode_image_chunk(ctx, lctx, chunk, embd, n_past, seq_id, n_batch, new_n_past);
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if (ret != 0) {
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LOG_ERR("failed to decode image\n");
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llama_batch_free(text_batch);
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return ret;
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}
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if (mtmd_decode_use_non_causal(ctx)) {
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llama_set_causal_attn(lctx, false);
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// TODO @ngxson : need to make sure only one image is processed at a time, and n_ubatch must be enough to hold the image
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}
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while (i_batch < n_img_batches) { // split into batches
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int pos_offset = i_batch*n_batch;
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int n_tokens_batch = std::min(n_batch, n_tokens - pos_offset);
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llama_batch batch_embd_view = batch_embd.get_view(pos_offset, n_tokens_batch);
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LOG_INF("decoding image batch %d/%d, n_tokens_batch = %d\n", i_batch+1, n_img_batches, n_tokens_batch);
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int64_t t1 = ggml_time_ms();
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ret = llama_decode(lctx, batch_embd_view);
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if (ret != 0) {
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LOG_ERR("failed to decode image\n");
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llama_set_causal_attn(lctx, true); // restore causal attn
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llama_batch_free(text_batch);
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return ret;
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}
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if (ctx->print_timings) {
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LOG_INF("image decoded (batch %d/%d) in %" PRId64 " ms\n", i_batch+1, n_img_batches, ggml_time_ms() - t1);
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}
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i_batch++;
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}
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n_past += mtmd_image_tokens_get_n_pos(image_tokens);
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*new_n_past = n_past;
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if (mtmd_decode_use_non_causal(ctx)) {
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llama_set_causal_attn(lctx, true);
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}
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} else {
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GGML_ABORT("chunk type not supported");
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}
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@ -231,6 +231,18 @@ MTMD_API int32_t mtmd_helper_eval_chunk_single(mtmd_context * ctx,
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bool logits_last,
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llama_pos * new_n_past);
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// helper function to decode an image whose embeddings have already been calculated
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// this helper will handle batching and pre/post decoding setup (for ex. gemma 3 requires non-causal attention)
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// ret 0 on success, -1 on chunk not being a valid image chunk, 1 on decode failure
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MTMD_API int32_t mtmd_helper_decode_image_chunk(mtmd_context * ctx,
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struct llama_context * lctx,
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const mtmd_input_chunk * chunk,
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float * encoded_embd,
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llama_pos n_past,
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llama_seq_id seq_id,
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int32_t n_batch,
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llama_pos * new_n_past);
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/////////////////////////////////////////
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// test function, to be used in test-mtmd-c-api.c
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