clip_model_load: CLIP using CPU backend

encode_image_with_clip: image encoded in  2887.00 ms by CLIP (   20.05 ms per image patch)

This image captures a delightful scene featuring a tan Labrador Retriever puppy. The puppy, with its yellow fur and black nose, is seen panting with its tongue sticking out, a common sign of excitement and happiness. The puppy is wearing a blue collar around its neck, adding a pop of color to the scene. The backdrop of the image is a tree-lined street, providing a serene and peaceful setting for this adorable pet. The puppy's position and the surrounding environment create a sense of harmony between the viewer and the natural world. The image is a beautiful representation of the joy and innocence that can be found in simple moments in our lives.
llama_perf_context_print:        load time =    5034.15 ms
llama_perf_context_print: prompt eval time =    1544.06 ms /   189 tokens (    8.17 ms per token,   122.40 tokens per second)
llama_perf_context_print:        eval time =    7537.75 ms /   255 runs   (   29.56 ms per token,    33.83 tokens per second)
llama_perf_context_print:       total time =   12628.64 ms /   444 tokens

clip_model_load: CLIP using Vulkan backend
clip_model_load: text_encoder:   0
clip_model_load: vision_encoder: 1
clip_model_load: llava_projector:  1
clip_model_load: minicpmv_projector:  0
clip_model_load: model size:     567.51 MB
clip_model_load: metadata size:  0.13 MB
clip_model_load: params backend buffer size =  567.51 MB (379 tensors)
key clip.vision.image_grid_pinpoints not found in file
key clip.vision.mm_patch_merge_type not found in file
key clip.vision.image_crop_resolution not found in file
clip_model_load: compute allocated memory: 32.89 MB
llama_new_context_with_model: n_ctx      = 2048
llama_new_context_with_model: n_batch    = 2048
llama_new_context_with_model: n_ubatch   = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base  = 10000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: Intel(R) Iris(R) Xe Graphics KV buffer size =   320.00 MiB
llama_kv_cache_init: Vulkan_Host KV buffer size =    64.00 MiB
llama_new_context_with_model: KV self size  =  384.00 MiB, K (f16):  192.00 MiB, V (f16):  192.00 MiB
llama_new_context_with_model: Vulkan_Host  output buffer size =     0.12 MiB
llama_new_context_with_model: Intel(R) Iris(R) Xe Graphics compute buffer size =   117.77 MiB
llama_new_context_with_model: Vulkan_Host compute buffer size =    12.01 MiB
llama_new_context_with_model: graph nodes  = 774
llama_new_context_with_model: graph splits = 48
ggml_vulkan: Error: Missing op: POOL_2D
C:\work\llm\cyzero\llama.cpp\ggml\src\ggml-vulkan.cpp:5735: fatal error

clip_model_load: CLIP using Vulkan backend

encode_image_with_clip: image encoded in   782.45 ms by CLIP (    5.43 ms per image patch)

 The image captures a moment of joy and tranquility in nature, featuring a golden Labrador Retriever. The dog, adorned with a blue collar and a red ribbon around its neck, is sitting on a sidewalk, gazing directly into the camera, exuding a sense of calm and contentment. Its large, expressive eyes are wide open, and its tongue is playfully sticking out, adding a touch of whimsy to the scene. The background is filled with lush green trees, providing a natural backdrop to the adorable canine. The overall image paints a picture of a serene day in the life of this golden retriever.
llama_perf_context_print:        load time =    6255.86 ms
llama_perf_context_print: prompt eval time =    2343.40 ms /   189 tokens (   12.40 ms per token,    80.65 tokens per second)
llama_perf_context_print:        eval time =    5164.95 ms /   145 runs   (   35.62 ms per token,    28.07 tokens per second)
llama_perf_context_print:       total time =   11472.51 ms /   334 tokens

PS C:\work\llm\cyzero\llama.cpp.latest> .\build\bin\Release\test-backend-ops.exe -o POOL2D
ggml_vulkan: Found 1 Vulkan devices:
Vulkan0: Intel(R) Iris(R) Xe Graphics (Intel Corporation) | uma: 1 | fp16: 1 | warp size: 32
Testing 2 backends

Backend 1/2 (CPU)
  Skipping CPU backend
Backend 2/2 (Vulkan0)
  Backend name: Vulkan0
  1605/1605 tests passed
  Backend Vulkan0: OK

2/2 backends passed
OK

PS C:\work\llm\cyzero\llama.cpp.latest\build\bin\Release> .\llama-llava-cli.exe -m 'C:\work\llm\MobileVLM_V2-1.7B-GGUF\ggml-model-q4_k.gguf' --mmproj C:\work\llm\MobileVLM_V2-1.7B-GGUF\mmproj-model-f16.gguf --image C:\work\llm\buddy.jpeg -ngl 20 -p "describe the image in detail."
build: 3838 (f4d2b884) with MSVC 19.35.32217.1 for x64
llama_model_loader: loaded meta data with 23 key-value pairs and 219 tensors from C:\work\llm\MobileVLM_V2-1.7B-GGUF\ggml-model-q4_k.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.name str              = Work
llama_model_loader: - kv   2:                           llama.vocab_size u32              = 32000
llama_model_loader: - kv   3:                       llama.context_length u32              = 2048
llama_model_loader: - kv   4:                     llama.embedding_length u32              = 2048
llama_model_loader: - kv   5:                          llama.block_count u32              = 24
llama_model_loader: - kv   6:                  llama.feed_forward_length u32              = 5632
llama_model_loader: - kv   7:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv   8:                 llama.attention.head_count u32              = 16
llama_model_loader: - kv   9:              llama.attention.head_count_kv u32              = 16
llama_model_loader: - kv  10:     llama.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  11:                       llama.rope.freq_base f32              = 10000.000000
llama_model_loader: - kv  12:                          general.file_type u32              = 14
llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  14:                      tokenizer.ggml.tokens arr[str,32000]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv  15:                      tokenizer.ggml.scores arr[f32,32000]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  16:                  tokenizer.ggml.token_type arr[i32,32000]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv  17:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  18:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  19:            tokenizer.ggml.padding_token_id u32              = 0
llama_model_loader: - kv  20:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  21:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  22:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   49 tensors
llama_model_loader: - type q4_K:  162 tensors
llama_model_loader: - type q5_K:    7 tensors
llama_model_loader: - type q6_K:    1 tensors
llm_load_vocab: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
llm_load_vocab: special tokens cache size = 3
llm_load_vocab: token to piece cache size = 0.1684 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = llama
llm_load_print_meta: vocab type       = SPM
llm_load_print_meta: n_vocab          = 32000
llm_load_print_meta: n_merges         = 0
llm_load_print_meta: vocab_only       = 0
llm_load_print_meta: n_ctx_train      = 2048
llm_load_print_meta: n_embd           = 2048
llm_load_print_meta: n_layer          = 24
llm_load_print_meta: n_head           = 16
llm_load_print_meta: n_head_kv        = 16
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_swa            = 0
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 1
llm_load_print_meta: n_embd_k_gqa     = 2048
llm_load_print_meta: n_embd_v_gqa     = 2048
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-06
llm_load_print_meta: f_clamp_kqv      = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale    = 0.0e+00
llm_load_print_meta: n_ff             = 5632
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 0
llm_load_print_meta: causal attn      = 1
llm_load_print_meta: pooling type     = 0
llm_load_print_meta: rope type        = 0
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn  = 2048
llm_load_print_meta: rope_finetuned   = unknown
llm_load_print_meta: ssm_d_conv       = 0
llm_load_print_meta: ssm_d_inner      = 0
llm_load_print_meta: ssm_d_state      = 0
llm_load_print_meta: ssm_dt_rank      = 0
llm_load_print_meta: ssm_dt_b_c_rms   = 0
llm_load_print_meta: model type       = ?B
llm_load_print_meta: model ftype      = Q4_K - Small
llm_load_print_meta: model params     = 1.36 B
llm_load_print_meta: model size       = 754.43 MiB (4.64 BPW)
llm_load_print_meta: general.name     = Work
llm_load_print_meta: BOS token        = 1 '<s>'
llm_load_print_meta: EOS token        = 2 '</s>'
llm_load_print_meta: UNK token        = 0 '<unk>'
llm_load_print_meta: PAD token        = 0 '<unk>'
llm_load_print_meta: LF token         = 13 '<0x0A>'
llm_load_print_meta: EOG token        = 2 '</s>'
llm_load_print_meta: max token length = 48
ggml_vulkan: Found 1 Vulkan devices:
Vulkan0: Intel(R) Iris(R) Xe Graphics (Intel Corporation) | uma: 1 | fp16: 1 | warp size: 32
llm_load_tensors: ggml ctx size =    0.20 MiB
llm_load_tensors: offloading 20 repeating layers to GPU
llm_load_tensors: offloaded 20/25 layers to GPU
llm_load_tensors: Intel(R) Iris(R) Xe Graphics buffer size =   551.56 MiB
llm_load_tensors:        CPU buffer size =   754.43 MiB
...........................................................................................
clip_model_load: model name:   openai/clip-vit-large-patch14-336
clip_model_load: description:  image encoder for LLaVA
clip_model_load: GGUF version: 3
clip_model_load: alignment:    32
clip_model_load: n_tensors:    379
clip_model_load: n_kv:         19
clip_model_load: ftype:        f16

clip_model_load: loaded meta data with 19 key-value pairs and 379 tensors from C:\work\llm\MobileVLM_V2-1.7B-GGUF\mmproj-model-f16.gguf
clip_model_load: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
clip_model_load: - kv   0:                       general.architecture str              = clip
clip_model_load: - kv   1:                      clip.has_text_encoder bool             = false
clip_model_load: - kv   2:                    clip.has_vision_encoder bool             = true
clip_model_load: - kv   3:                   clip.has_llava_projector bool             = true
clip_model_load: - kv   4:                          general.file_type u32              = 1
clip_model_load: - kv   5:                               general.name str              = openai/clip-vit-large-patch14-336
clip_model_load: - kv   6:                        general.description str              = image encoder for LLaVA
clip_model_load: - kv   7:                        clip.projector_type str              = ldpv2
clip_model_load: - kv   8:                     clip.vision.image_size u32              = 336
clip_model_load: - kv   9:                     clip.vision.patch_size u32              = 14
clip_model_load: - kv  10:               clip.vision.embedding_length u32              = 1024
clip_model_load: - kv  11:            clip.vision.feed_forward_length u32              = 4096
clip_model_load: - kv  12:                 clip.vision.projection_dim u32              = 768
clip_model_load: - kv  13:           clip.vision.attention.head_count u32              = 16
clip_model_load: - kv  14:   clip.vision.attention.layer_norm_epsilon f32              = 0.000010
clip_model_load: - kv  15:                    clip.vision.block_count u32              = 23
clip_model_load: - kv  16:                     clip.vision.image_mean arr[f32,3]       = [0.481455, 0.457828, 0.408211]
clip_model_load: - kv  17:                      clip.vision.image_std arr[f32,3]       = [0.268630, 0.261303, 0.275777]
clip_model_load: - kv  18:                              clip.use_gelu bool             = false
clip_model_load: - type  f32:  236 tensors
clip_model_load: - type  f16:  143 tensors
clip_model_load: CLIP using Vulkan backend
clip_model_load: text_encoder:   0
clip_model_load: vision_encoder: 1
clip_model_load: llava_projector:  1
clip_model_load: minicpmv_projector:  0
clip_model_load: model size:     567.51 MB
clip_model_load: metadata size:  0.13 MB
clip_model_load: params backend buffer size =  567.51 MB (379 tensors)
key clip.vision.image_grid_pinpoints not found in file
key clip.vision.mm_patch_merge_type not found in file
key clip.vision.image_crop_resolution not found in file
clip_model_load: compute allocated memory: 32.89 MB
llama_new_context_with_model: n_ctx      = 2048
llama_new_context_with_model: n_batch    = 2048
llama_new_context_with_model: n_ubatch   = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base  = 10000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: Intel(R) Iris(R) Xe Graphics KV buffer size =   320.00 MiB
llama_kv_cache_init: Vulkan_Host KV buffer size =    64.00 MiB
llama_new_context_with_model: KV self size  =  384.00 MiB, K (f16):  192.00 MiB, V (f16):  192.00 MiB
llama_new_context_with_model: Vulkan_Host  output buffer size =     0.12 MiB
llama_new_context_with_model: Intel(R) Iris(R) Xe Graphics compute buffer size =   117.77 MiB
llama_new_context_with_model: Vulkan_Host compute buffer size =    12.01 MiB
llama_new_context_with_model: graph nodes  = 774
llama_new_context_with_model: graph splits = 48
encode_image_with_clip: image embedding created: 144 tokens

encode_image_with_clip: image encoded in   782.45 ms by CLIP (    5.43 ms per image patch)

 The image captures a moment of joy and tranquility in nature, featuring a golden Labrador Retriever. The dog, adorned with a blue collar and a red ribbon around its neck, is sitting on a sidewalk, gazing directly into the camera, exuding a sense of calm and contentment. Its large, expressive eyes are wide open, and its tongue is playfully sticking out, adding a touch of whimsy to the scene. The background is filled with lush green trees, providing a natural backdrop to the adorable canine. The overall image paints a picture of a serene day in the life of this golden retriever.
llama_perf_context_print:        load time =    6255.86 ms
llama_perf_context_print: prompt eval time =    2343.40 ms /   189 tokens (   12.40 ms per token,    80.65 tokens per second)
llama_perf_context_print:        eval time =    5164.95 ms /   145 runs   (   35.62 ms per token,    28.07 tokens per second)
llama_perf_context_print:       total time =   11472.51 ms /   334 tokens