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	* Create llava-survery-v2.py * Update convert-image-encoder-to-gguf.py * Update convert-image-encoder-to-gguf.py * Rename llava-survery-v2.py to llava-surgery-v2.py * Update convert-image-encoder-to-gguf.py will now search for projector * Update convert-image-encoder-to-gguf.py whoops * Update llava-surgery-v2.py * Clip: Bugfix for normalization (it did not loat the 3 std and mean values) Clip: bicubic resize function Clip: added save-to-bmp/pil for debugging and conversion from/to 32/8 images Clip: added normalization with FP16 precision simulation (image tensors match HF implementation, can be switched off, only used for llava-1.6) Clip: added newline tensor, mergetype kv, image-grid kv, new resize-pad function with resolution from gridpoints Clip: clip_image_preprocess now returns a float * vector instead of float, this way llava 1.5 and 1.6 is supported llava: added ggml cpu graph for embedding patching, added spatial_unpad preliminary support, added a lot of comments that need to be cleaned when all is final convert-image-encoder: fixed image-grid flattening * whitespace corrections * ws * Tensors are now properly permuted. Before the embeddings were inserted 1:1, now they are split into the 24x24 patches as in reference. * ws * added verbose_prompt support into cli added stopwords for llava-1.6 into cli * moved llava functions to llava.cpp, made clip.h C compatible API, replaced vector style functions with pointers, added a debug define to remove functions from compilation while not needed * ws * convert : skip unknown tensors (need for LLaVA) * llava : update readme * llava : fix compile warnings * llava : style * convert : add --skip-unknown CLI arg * server : remove clip structs * bugfix for non llava-1.6 It should now work with llava-1.5 as well * clip : minor code rearrange * llava : update readme a bit --------- Co-authored-by: John <cmt-nct@users.noreply.github.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
		
			
				
	
	
		
			84 lines
		
	
	
		
			2.7 KiB
		
	
	
	
		
			C
		
	
	
	
	
	
			
		
		
	
	
			84 lines
		
	
	
		
			2.7 KiB
		
	
	
	
		
			C
		
	
	
	
	
	
#ifndef CLIP_H
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#define CLIP_H
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#include <stddef.h>
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#include <stdint.h>
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#ifdef LLAMA_SHARED
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#    if defined(_WIN32) && !defined(__MINGW32__)
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#        ifdef LLAMA_BUILD
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#            define CLIP_API __declspec(dllexport)
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#        else
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#            define CLIP_API __declspec(dllimport)
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#        endif
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#    else
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#        define CLIP_API __attribute__ ((visibility ("default")))
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#    endif
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#else
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#    define CLIP_API
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#endif
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struct clip_ctx;
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#ifdef __cplusplus
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extern "C" {
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#endif
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struct clip_ctx;
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struct clip_image_u8_batch {
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    struct clip_image_u8 * data;
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    size_t size;
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};
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struct clip_image_f32_batch {
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    struct clip_image_f32 * data;
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    size_t size;
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};
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CLIP_API struct clip_ctx * clip_model_load    (const char * fname, int verbosity);
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CLIP_API struct clip_ctx * clip_model_load_cpu(const char * fname, int verbosity);
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CLIP_API void clip_free(struct clip_ctx * ctx);
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CLIP_API size_t clip_embd_nbytes(const struct clip_ctx * ctx);
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CLIP_API int32_t clip_image_size (const struct clip_ctx * ctx);
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CLIP_API int32_t clip_patch_size (const struct clip_ctx * ctx);
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CLIP_API int32_t clip_hidden_size(const struct clip_ctx * ctx);
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// TODO: should be enum, not string
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CLIP_API const char * clip_patch_merge_type(const struct clip_ctx * ctx);
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CLIP_API const int32_t * clip_image_grid(const struct clip_ctx * ctx);
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CLIP_API int clip_n_patches    (const struct clip_ctx * ctx);
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CLIP_API int clip_n_mmproj_embd(const struct clip_ctx * ctx);
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CLIP_API struct clip_image_u8  * clip_image_u8_init ();
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CLIP_API struct clip_image_f32 * clip_image_f32_init();
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CLIP_API void clip_image_u8_free (struct clip_image_u8  * img);
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CLIP_API void clip_image_f32_free(struct clip_image_f32 * img);
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CLIP_API bool clip_image_load_from_file(const char * fname, struct clip_image_u8 * img);
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/** interpret bytes as an image file with length bytes_length, and use the result to populate img */
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CLIP_API bool clip_image_load_from_bytes(const unsigned char * bytes, size_t bytes_length, struct clip_image_u8 * img);
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/** preprocess img and store the result in res_imgs, pad_to_square may be overriden to false depending on model configuration */
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CLIP_API bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, clip_image_f32_batch & res_imgs );
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CLIP_API struct ggml_tensor * clip_get_newline_tensor(const struct clip_ctx * ctx);
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CLIP_API bool clip_image_encode      (struct clip_ctx * ctx, int n_threads, struct clip_image_f32 * img, float * vec);
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CLIP_API bool clip_image_batch_encode(struct clip_ctx * ctx, int n_threads, const struct clip_image_f32_batch * imgs, float * vec);
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CLIP_API bool clip_model_quantize(const char * fname_inp, const char * fname_out, int itype);
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#ifdef __cplusplus
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}
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#endif
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#endif // CLIP_H
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