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llama_kv_cache_seq_shift does not work with cache type q4_0

Open ngxson opened this issue 5 months ago • 2 comments

The llama_kv_cache_seq_shift or llama_kv_cache_seq_rm (or all two of them) is broken with cache type q4_0 for K.

In the main.cpp, these functions are used for "context swapping", meaning we can remove old tokens from sequence to make place for new tokens.

My command: ./main -m ../dolphin-2.0-mistral-7b.Q4_K_M.gguf -p "test" -n 50 --cache-type-k q4_0 -c 10

(It does work normal without the --cache-type-k q4_0)

See the log below for more details:

stdout / stderr
Log start
main: build = 2232 (7fe4678b)
main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
main: seed  = 1708557165
llama_model_loader: loaded meta data with 20 key-value pairs and 291 tensors from ../dolphin-2.0-mistral-7b.Q4_K_M.gguf (version GGUF V2)
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              = ehartford_dolphin-2.0-mistral-7b
llama_model_loader: - kv   2:                       llama.context_length u32              = 32768
llama_model_loader: - kv   3:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   4:                          llama.block_count u32              = 32
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv   7:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   8:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                       llama.rope.freq_base f32              = 10000.000000
llama_model_loader: - kv  11:                          general.file_type u32              = 15
llama_model_loader: - kv  12:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr[str,32000]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv  14:                      tokenizer.ggml.scores arr[f32,32000]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  15:                  tokenizer.ggml.token_type arr[i32,32000]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv  16:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  17:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  18:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  19:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_K:  193 tensors
llama_model_loader: - type q6_K:   33 tensors
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format           = GGUF V2
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: n_ctx_train      = 32768
llm_load_print_meta: n_embd           = 4096
llm_load_print_meta: n_head           = 32
llm_load_print_meta: n_head_kv        = 8
llm_load_print_meta: n_layer          = 32
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 4
llm_load_print_meta: n_embd_k_gqa     = 1024
llm_load_print_meta: n_embd_v_gqa     = 1024
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
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: n_ff             = 14336
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 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_yarn_orig_ctx  = 32768
llm_load_print_meta: rope_finetuned   = unknown
llm_load_print_meta: model type       = 7B
llm_load_print_meta: model ftype      = Q4_K - Medium
llm_load_print_meta: model params     = 7.24 B
llm_load_print_meta: model size       = 4.07 GiB (4.83 BPW) 
llm_load_print_meta: general.name     = ehartford_dolphin-2.0-mistral-7b
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: LF token         = 13 '<0x0A>'
llm_load_tensors: ggml ctx size =    0.11 MiB
llm_load_tensors:        CPU buffer size =  4165.37 MiB
...............................................................................................
llama_new_context_with_model: n_ctx      = 10
llama_new_context_with_model: freq_base  = 10000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init:        CPU KV buffer size =     0.80 MiB
llama_new_context_with_model: KV self size  =    0.80 MiB, K (q4_0):    0.18 MiB, V (f16):    0.62 MiB
llama_new_context_with_model:        CPU input buffer size   =     9.03 MiB
llama_new_context_with_model:        CPU compute buffer size =     1.41 MiB
llama_new_context_with_model: graph splits (measure): 1

system_info: n_threads = 8 / 16 | AVX = 1 | AVX_VNNI = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | 
sampling: 
        repeat_last_n = 64, repeat_penalty = 1.100, frequency_penalty = 0.000, presence_penalty = 0.000
        top_k = 40, tfs_z = 1.000, top_p = 0.950, min_p = 0.050, typical_p = 1.000, temp = 0.800
        mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
sampling order: 
CFG -> Penalties -> top_k -> tfs_z -> typical_p -> top_p -> min_p -> temperature 
generate: n_ctx = 10, n_batch = 512, n_predict = 50, n_keep = 1


 test "Authentication page is displayed" do
 GGML_ASSERT: ggml.c:12646: false
GGML_ASSERT: ggml.c:12646: false
GGML_ASSERT: ggml.c:12646: false
GGML_ASSERT: ggml.c:12646: false
GGML_ASSERT: ggml.c:12646: false
GGML_ASSERT: ggml.c:12646: false
GGML_ASSERT: ggml.c:12646: false
GGML_ASSERT: ggml.c:12646: false
[1]    2211794 IOT instruction (core dumped)
main.log
[1708557165] Log start
[1708557165] Cmd: ./main -m ../dolphin-2.0-mistral-7b.Q4_K_M.gguf -p test -n 50 --cache-type-k q4_0 -c 10
[1708557165] main: build = 2232 (7fe4678b)
[1708557165] main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
[1708557165] main: seed  = 1708557165
[1708557165] main: llama backend init
[1708557165] main: load the model and apply lora adapter, if any
[1708557165] llama_model_loader: loaded meta data with 20 key-value pairs and 291 tensors from ../dolphin-2.0-mistral-7b.Q4_K_M.gguf (version GGUF V2)
[1708557165] llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
[1708557165] llama_model_loader: - kv   0:                       general.architecture str              = llama
[1708557165] llama_model_loader: - kv   1:                               general.name str              = ehartford_dolphin-2.0-mistral-7b
[1708557165] llama_model_loader: - kv   2:                       llama.context_length u32              = 32768
[1708557165] llama_model_loader: - kv   3:                     llama.embedding_length u32              = 4096
[1708557165] llama_model_loader: - kv   4:                          llama.block_count u32              = 32
[1708557165] llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
[1708557165] llama_model_loader: - kv   6:                 llama.rope.dimension_count u32              = 128
[1708557165] llama_model_loader: - kv   7:                 llama.attention.head_count u32              = 32
[1708557165] llama_model_loader: - kv   8:              llama.attention.head_count_kv u32              = 8
[1708557165] llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
[1708557165] llama_model_loader: - kv  10:                       llama.rope.freq_base f32              = 10000.000000
[1708557165] llama_model_loader: - kv  11:                          general.file_type u32              = 15
[1708557165] llama_model_loader: - kv  12:                       tokenizer.ggml.model str              = llama
[1708557165] llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr[str,32000]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
[1708557165] llama_model_loader: - kv  14:                      tokenizer.ggml.scores arr[f32,32000]   = [0.000000, 0.000000, 0.000000, 0.0000...
[1708557165] llama_model_loader: - kv  15:                  tokenizer.ggml.token_type arr[i32,32000]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
[1708557165] llama_model_loader: - kv  16:                tokenizer.ggml.bos_token_id u32              = 1
[1708557165] llama_model_loader: - kv  17:                tokenizer.ggml.eos_token_id u32              = 2
[1708557165] llama_model_loader: - kv  18:            tokenizer.ggml.unknown_token_id u32              = 0
[1708557165] llama_model_loader: - kv  19:               general.quantization_version u32              = 2
[1708557165] llama_model_loader: - type  f32:   65 tensors
[1708557165] llama_model_loader: - type q4_K:  193 tensors
[1708557165] llama_model_loader: - type q6_K:   33 tensors
[1708557165] llm_load_vocab: special tokens definition check successful ( 259/32000 ).
[1708557165] llm_load_print_meta: format           = GGUF V2
[1708557165] llm_load_print_meta: arch             = llama
[1708557165] llm_load_print_meta: vocab type       = SPM
[1708557165] llm_load_print_meta: n_vocab          = 32000
[1708557165] llm_load_print_meta: n_merges         = 0
[1708557165] llm_load_print_meta: n_ctx_train      = 32768
[1708557165] llm_load_print_meta: n_embd           = 4096
[1708557165] llm_load_print_meta: n_head           = 32
[1708557165] llm_load_print_meta: n_head_kv        = 8
[1708557165] llm_load_print_meta: n_layer          = 32
[1708557165] llm_load_print_meta: n_rot            = 128
[1708557165] llm_load_print_meta: n_embd_head_k    = 128
[1708557165] llm_load_print_meta: n_embd_head_v    = 128
[1708557165] llm_load_print_meta: n_gqa            = 4
[1708557165] llm_load_print_meta: n_embd_k_gqa     = 1024
[1708557165] llm_load_print_meta: n_embd_v_gqa     = 1024
[1708557165] llm_load_print_meta: f_norm_eps       = 0.0e+00
[1708557165] llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
[1708557165] llm_load_print_meta: f_clamp_kqv      = 0.0e+00
[1708557165] llm_load_print_meta: f_max_alibi_bias = 0.0e+00
[1708557165] llm_load_print_meta: n_ff             = 14336
[1708557165] llm_load_print_meta: n_expert         = 0
[1708557165] llm_load_print_meta: n_expert_used    = 0
[1708557165] llm_load_print_meta: rope scaling     = linear
[1708557165] llm_load_print_meta: freq_base_train  = 10000.0
[1708557165] llm_load_print_meta: freq_scale_train = 1
[1708557165] llm_load_print_meta: n_yarn_orig_ctx  = 32768
[1708557165] llm_load_print_meta: rope_finetuned   = unknown
[1708557165] llm_load_print_meta: model type       = 7B
[1708557165] llm_load_print_meta: model ftype      = Q4_K - Medium
[1708557165] llm_load_print_meta: model params     = 7.24 B
[1708557165] llm_load_print_meta: model size       = 4.07 GiB (4.83 BPW) 
[1708557165] llm_load_print_meta: general.name     = ehartford_dolphin-2.0-mistral-7b
[1708557165] llm_load_print_meta: BOS token        = 1 '<s>'
[1708557165] llm_load_print_meta: EOS token        = 2 '</s>'
[1708557165] llm_load_print_meta: UNK token        = 0 '<unk>'
[1708557165] llm_load_print_meta: LF token         = 13 '<0x0A>'
[1708557165] llm_load_tensors: ggml ctx size =    0.11 MiB
[1708557166] llm_load_tensors:        CPU buffer size =  4165.37 MiB
[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] .[1708557166] 
[1708557166] llama_new_context_with_model: n_ctx      = 10
[1708557166] llama_new_context_with_model: freq_base  = 10000.0
[1708557166] llama_new_context_with_model: freq_scale = 1
[1708557166] llama_kv_cache_init:        CPU KV buffer size =     0.80 MiB
[1708557166] llama_new_context_with_model: KV self size  =    0.80 MiB, K (q4_0):    0.18 MiB, V (f16):    0.62 MiB
[1708557166] llama_new_context_with_model:        CPU input buffer size   =     9.03 MiB
[1708557166] llama_new_context_with_model:        CPU compute buffer size =     1.41 MiB
[1708557166] llama_new_context_with_model: graph splits (measure): 1
[1708557166] warming up the model with an empty run
[1708557166] n_ctx: 10
[1708557166] 
[1708557166] system_info: n_threads = 8 / 16 | AVX = 1 | AVX_VNNI = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | 
[1708557166] add_bos: 1
[1708557166] tokenize the prompt
[1708557166] prompt: "test"
[1708557166] tokens: [ '':1, ' test':1369 ]
[1708557166] recalculate the cached logits (check): embd_inp.empty() false, n_matching_session_tokens 0, embd_inp.size() 2, session_tokens.size() 0, embd_inp.size() 2
[1708557166] inp_pfx: [ '':1, ' ':28705, '':13, '':13, '###':27332, ' Inst':3133, 'ruction':3112, ':':28747, '':13, '':13 ]
[1708557166] inp_sfx: [ ' ':28705, '':13, '':13, '###':27332, ' Response':12107, ':':28747, '':13, '':13 ]
[1708557166] cml_pfx: [ '':1, ' ':28705, '':13, '<':28789, '|':28766, 'im':321, '_':28730, 'start':2521, '|':28766, '>':28767, 'user':1838, '':13 ]
[1708557166] cml_sfx: [ ' <':523, '|':28766, 'im':321, '_':28730, 'end':416, '|':28766, '>':28767, '':13, '<':28789, '|':28766, 'im':321, '_':28730, 'start':2521, '|':28766, '>':28767, 'ass':489, 'istant':11143, '':13 ]
[1708557166] sampling: 
	repeat_last_n = 64, repeat_penalty = 1.100, frequency_penalty = 0.000, presence_penalty = 0.000
	top_k = 40, tfs_z = 1.000, top_p = 0.950, min_p = 0.050, typical_p = 1.000, temp = 0.800
	mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
[1708557166] sampling order: 
CFG -> Penalties -> top_k -> tfs_z -> typical_p -> top_p -> min_p -> temperature 
[1708557166] generate: n_ctx = 10, n_batch = 512, n_predict = 50, n_keep = 1
[1708557166] 

[1708557166] embd_inp.size(): 2, n_consumed: 0
[1708557166] eval: [ '':1, ' test':1369 ]
[1708557166] n_past = 2
[1708557166] sampled token:   345: ' "'
[1708557166] last: [ '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':1, ' test':1369, ' "':345 ]
[1708557166] n_remain: 49
[1708557166] eval: [ ' "':345 ]
[1708557166] n_past = 3
[1708557166] sampled token: 19504: 'Authentication'
[1708557166] last: [ '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':1, ' test':1369, ' "':345, 'Authentication':19504 ]
[1708557166] n_remain: 48
[1708557166] eval: [ 'Authentication':19504 ]
[1708557166] n_past = 4
[1708557166] sampled token:  2884: ' page'
[1708557166] last: [ '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':1, ' test':1369, ' "':345, 'Authentication':19504, ' page':2884 ]
[1708557166] n_remain: 47
[1708557166] eval: [ ' page':2884 ]
[1708557167] n_past = 5
[1708557167] sampled token:   349: ' is'
[1708557167] last: [ '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':1, ' test':1369, ' "':345, 'Authentication':19504, ' page':2884, ' is':349 ]
[1708557167] n_remain: 46
[1708557167] eval: [ ' is':349 ]
[1708557167] n_past = 6
[1708557167] sampled token: 13992: ' displayed'
[1708557167] last: [ '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':1, ' test':1369, ' "':345, 'Authentication':19504, ' page':2884, ' is':349, ' displayed':13992 ]
[1708557167] n_remain: 45
[1708557167] eval: [ ' displayed':13992 ]
[1708557167] n_past = 7
[1708557167] sampled token: 28739: '"'
[1708557167] last: [ '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':1, ' test':1369, ' "':345, 'Authentication':19504, ' page':2884, ' is':349, ' displayed':13992, '"':28739 ]
[1708557167] n_remain: 44
[1708557167] eval: [ '"':28739 ]
[1708557167] n_past = 8
[1708557167] sampled token:   511: ' do'
[1708557167] last: [ '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':1, ' test':1369, ' "':345, 'Authentication':19504, ' page':2884, ' is':349, ' displayed':13992, '"':28739, ' do':511 ]
[1708557167] n_remain: 43
[1708557167] eval: [ ' do':511 ]
[1708557167] n_past = 9
[1708557167] sampled token:    13: '
'
[1708557167] last: [ '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':1, ' test':1369, ' "':345, 'Authentication':19504, ' page':2884, ' is':349, ' displayed':13992, '"':28739, ' do':511, '':13 ]
[1708557167] n_remain: 42
[1708557167] eval: [ '':13 ]
[1708557167] n_past = 10
[1708557167] sampled token: 28705: ' '
[1708557167] last: [ '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':0, '':1, ' test':1369, ' "':345, 'Authentication':19504, ' page':2884, ' is':349, ' displayed':13992, '"':28739, ' do':511, '':13, ' ':28705 ]
[1708557167] n_remain: 41
[1708557167] context full, swapping: n_past = 10, n_left = 9, n_ctx = 10, n_keep = 1, n_discard = 4
[1708557167] after swap: n_past = 6, n_past_guidance = 0
[1708557167] embd: [ ' ':28705 ]
[1708557167] clear session path
[1708557167] eval: [ ' ':28705 ]

ngxson avatar Feb 21 '24 23:02 ngxson