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021389f7bb
The clip.cpp tensor-read loop was the fattest hook in the patch — it duplicated the host-vs-device buffer dispatch around a call into the compat layer. Move that dispatch into our code (maybe_load_tensor), so the upstream patch is a single conditional call. Net: upstream patch drops from 48 lines across 6 files to 34 lines. Every remaining edit is either a 1-line include, a 1-line function call, or the gguf_rename_tensor shim (which accesses gguf_context internals and has to live in gguf.cpp). Verified end-to-end: text + vision both still correct after rebuild.
83 lines
3.6 KiB
C++
Vendored
83 lines
3.6 KiB
C++
Vendored
#pragma once
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// Ollama-format GGUF compatibility shim.
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//
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// Older Ollama builds ship GGUFs that differ from upstream in a handful of
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// ways per-architecture. This shim detects those files during load and
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// translates them in-memory so the rest of llama.cpp can load them
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// unmodified. Single entry point per hook; all logic is data-driven from
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// per-architecture rules.
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//
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// Two hooks:
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// 1. translate_metadata() — runs after gguf_init_from_file, mutates KVs
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// and (optionally) tensor names on the gguf_context / ggml_context.
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// 2. apply_tensor_transforms() — runs after load_all_data, rewrites
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// tensor data that differs numerically (e.g. gemma3 RMSNorm +1).
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#include <cstdint>
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#include <string>
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#include <vector>
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#include "ggml-backend.h" // for ggml_backend_buffer_type_t
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struct gguf_context;
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struct ggml_context;
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struct ggml_tensor;
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struct llama_model_loader;
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namespace llama_ollama_compat {
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// Inspect and mutate the just-loaded gguf_context. May update arch_name if
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// the file uses an Ollama-specific architecture name. Safe to call for any
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// model — no-op when no Ollama markers are present.
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//
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// If compat was applied, registers any tensor transforms against `ml` for
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// apply_tensor_transforms() to consume later.
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void translate_metadata(const llama_model_loader * ml,
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gguf_context * meta,
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ggml_context * ctx,
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std::string & arch_name);
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// Returns true if the loader should skip this tensor entirely (not add to
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// weights_map, not count toward n_tensors). Used to drop embedded vision
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// tensors from the text model without physically removing them.
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bool should_skip_tensor(const llama_model_loader * ml, const char * tensor_name);
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// Called after load_all_data returns for a model context. Applies any
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// registered transforms (read tensor data from the backend buffer, modify,
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// write back) to tensors in `ctx`. Call once per model context.
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void apply_tensor_transforms(const llama_model_loader * ml, ggml_context * ctx);
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// Called from the clip loader (tools/mtmd/clip.cpp). If the file is an
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// Ollama-format monolithic GGUF (text + embedded vision), rewrites the
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// clip-facing view of the metadata so the clip loader sees it as a normal
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// mmproj file. Safe to call unconditionally — no-op when not an Ollama file.
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//
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// Operations:
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// - sets general.architecture = "clip"
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// - sets clip.has_vision_encoder, clip.projector_type, clip.use_gelu
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// - copies gemma3.vision.* KVs into clip.vision.*
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// - renames vision tensors (v.patch_embedding -> v.patch_embd, etc.)
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// - promotes specific F16 tensors to F32 in the ggml_context so clip
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// allocates the correct buffer size
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//
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// Non-vision text tensors remain in the gguf but are never looked up by
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// clip, so they cost nothing.
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void translate_clip_metadata(gguf_context * meta, ggml_context * ctx);
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// Called from clip.cpp's tensor-loading loop, before reading bytes from the
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// file. If this tensor was marked for type promotion by translate_clip_metadata
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// (e.g. F16→F32), reads the source bytes, converts them, and writes the
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// result directly into `cur` (choosing host copy vs. backend upload based
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// on `buft`). Returns true if the tensor was handled — caller should skip
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// its normal file-read path. Returns false otherwise; caller loads normally.
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//
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// `file_offset` is the absolute file offset of the original (pre-promotion)
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// tensor data in the source GGUF.
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bool maybe_load_tensor(ggml_tensor * cur,
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const char * source_file,
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size_t file_offset,
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ggml_backend_buffer_type_t buft);
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} // namespace llama_ollama_compat
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