Skip to content

Commit

Permalink
Mass use of the few/some/more/many bits bump logic
Browse files Browse the repository at this point in the history 
Add few bits logic and rework the 4 settings for 25/37.5/50/75% quant bump when used.
  • Loading branch information
@Nexesenex
Nexesenex committed Aug 18, 2024
1 parent 4ba5618 commit b02eaf6
Showing 1 changed file with 50 additions and 26 deletions.
76 changes: 50 additions & 26 deletions src/llama.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -15847,9 +15847,23 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
const llm_arch arch = qs.model.arch;
const auto tn = LLM_TN(arch);

auto use_few_bits = [](int i_layer, int n_layers) -> bool {
return i_layer <= n_layers/8 || i_layer > 7*n_layers/8;
};
//few_bits has a broad 25% bump to the upper quant.
auto use_some_bits = [](int i_layer, int n_layers) -> bool {
return i_layer <= n_layers/8 || i_layer > 7*n_layers/8 || (i_layer >= 2*n_layers/8 && i_layer < 3*n_layers/8);
};
// return i_layer < n_layers/8 || i_layer >= 7*n_layers/8 || (i_layer - n_layers/8)%3 == 2;
// The intervals of 3 are replaced by a broad bump in the central layers. some_bits has a broad 37.5% bump to the upper quant.
auto use_more_bits = [](int i_layer, int n_layers) -> bool {
return i_layer < n_layers/8 || i_layer >= 7*n_layers/8 || (i_layer - n_layers/8)%3 == 2;
return i_layer <= n_layers/8 || i_layer > 6*n_layers/8 || (i_layer >= 2*n_layers/8 && i_layer < 3*n_layers/8);
};
//more_bits has a broad 50% bump to the upper quant.
auto use_many_bits = [](int i_layer, int n_layers) -> bool {
return i_layer <= n_layers/8 || i_layer > 5*n_layers/8 || (i_layer >= 2*n_layers/8 && i_layer < 4*n_layers/8);
};
//many_bits has a broad 75% bump to the upper quant.
const int n_expert = std::max(1, (int)qs.model.hparams.n_expert);
auto layer_info = [n_expert] (int i_layer, int n_layer, const char * name) {
if (n_expert > 1) {
Expand Down Expand Up @@ -15917,10 +15931,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
if (qs.model.hparams.n_vocab >= 127999) new_type = GGML_TYPE_IQ3_XXS;
else new_type = GGML_TYPE_IQ3_S;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL) {
if (qs.model.hparams.n_vocab >= 127999) new_type = GGML_TYPE_IQ3_S;
else new_type = GGML_TYPE_IQ4_XS;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL) new_type = GGML_TYPE_IQ4_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M) new_type = GGML_TYPE_IQ3_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XL) new_type = GGML_TYPE_IQ3_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS) new_type = GGML_TYPE_IQ3_S;
Expand Down Expand Up @@ -15969,7 +15980,8 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_S) new_type = GGML_TYPE_Q4_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_M || ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL) {
new_type = (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2) ? GGML_TYPE_Q5_K : GGML_TYPE_Q4_K;
if (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2) new_type = GGML_TYPE_Q5_K;
else new_type = GGML_TYPE_IQ4_XS;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M) {
new_type = qs.i_attention_wv < 2 ? GGML_TYPE_Q5_K : GGML_TYPE_Q4_K;
Expand All @@ -15988,7 +16000,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ4_XSR) {
if (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2) {
new_type = qs.i_attention_wv < qs.n_attention_wv/8 ? GGML_TYPE_Q5_K :
use_more_bits(qs.i_attention_wv, qs.n_attention_wv) ? GGML_TYPE_Q6_K : GGML_TYPE_Q5_K;
use_more_bits(qs.i_attention_wv, qs.n_attention_wv) ? GGML_TYPE_Q5_K : GGML_TYPE_Q5_K;
}
}
++qs.i_attention_wv;
Expand Down Expand Up @@ -16027,9 +16039,15 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XS && qs.model.hparams.n_gqa() < 2 && qs.model.hparams.n_expert < 2) {
new_type = GGML_TYPE_IQ3_XXS;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_M || ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL) {
if (qs.model.hparams.n_gqa() >= 4 || qs.model.hparams.n_expert >= 2) new_type = GGML_TYPE_Q5_K;
else if (qs.model.hparams.n_gqa() >= 2) new_type = GGML_TYPE_IQ4_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_M) {
if (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2)
new_type = use_some_bits(qs.i_attention_wk, qs.n_attention_wk) ? GGML_TYPE_Q5_K : GGML_TYPE_IQ4_XS;
else new_type = use_some_bits(qs.i_attention_wk, qs.n_attention_wk) ? GGML_TYPE_IQ4_XS : GGML_TYPE_IQ3_S;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL) {
if (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2)
new_type = use_many_bits(qs.i_attention_wk, qs.n_attention_wk) ? GGML_TYPE_Q5_K : GGML_TYPE_IQ4_XS;
else new_type = use_many_bits(qs.i_attention_wk, qs.n_attention_wk) ? GGML_TYPE_IQ4_XS : GGML_TYPE_IQ3_S;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L && (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2)) {
new_type = GGML_TYPE_Q4_K;
Expand Down Expand Up @@ -16059,8 +16077,8 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ4_XSR) {
if (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2) {
new_type = qs.i_attention_wq < qs.n_attention_wq/8 ? GGML_TYPE_IQ4_XS :
use_more_bits(qs.i_attention_wq, qs.n_attention_wq) ? GGML_TYPE_IQ4_XS : GGML_TYPE_IQ4_XS;
new_type = qs.i_attention_wq < qs.n_attention_wq/8 ? GGML_TYPE_IQ3_S :
use_more_bits(qs.i_attention_wq, qs.n_attention_wq) ? GGML_TYPE_IQ3_S : GGML_TYPE_IQ3_S;
}
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ4_XSR) new_type = GGML_TYPE_IQ3_S;
Expand Down Expand Up @@ -16091,11 +16109,13 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
: arch != LLM_ARCH_FALCON || use_more_bits(i_layer, n_layer) ? GGML_TYPE_Q4_K
: GGML_TYPE_Q3_K;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_M && (i_layer < n_layer/8 ||
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_M && (use_some_bits(i_layer, n_layer) ||
(qs.model.hparams.n_expert >= 4 && use_more_bits(i_layer, n_layer)))) {
new_type = GGML_TYPE_Q4_K;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ4_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL) {
new_type = use_many_bits(i_layer, n_layer) ? GGML_TYPE_IQ4_XS : GGML_TYPE_IQ3_S;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L) {
new_type = arch == LLM_ARCH_FALCON ? GGML_TYPE_Q4_K : GGML_TYPE_Q5_K;
}
Expand Down Expand Up @@ -16193,30 +16213,34 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
auto info = layer_info(qs.i_ffn_gate, qs.n_ffn_gate, name.c_str());
int i_layer = info.first, n_layer = info.second;
if (ftype == LLAMA_FTYPE_MOSTLY_Q2_K_L && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_Q3_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_S && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_M && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_XS && (use_few_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ1_M;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_S && (use_some_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_M && (use_some_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_XL && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ2_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ2_S;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_M && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ3_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS && (use_some_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS && (use_few_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_S;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_M && (use_some_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ3_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XL && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ3_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XS && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ3_S;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ4_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL && (use_many_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ4_XS;
++qs.i_ffn_gate;
}
else if (name.find("ffn_up") != std::string::npos) {
auto info = layer_info(qs.i_ffn_up, qs.n_ffn_up, name.c_str());
int i_layer = info.first, n_layer = info.second;
if (ftype == LLAMA_FTYPE_MOSTLY_Q2_K_L && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_Q3_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_S && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_M && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_XS && (use_few_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ1_M;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_S && (use_some_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_M && (use_some_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_XL && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ2_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ2_S;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_M && (i_layer < n_layer/8)) new_type = GGML_TYPE_IQ3_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS && (use_some_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS && (use_few_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ2_S;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_M && (use_some_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ3_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XL && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ3_XXS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XS && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ3_S;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL && (use_more_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ4_XS;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL && (use_many_bits(i_layer, n_layer))) new_type = GGML_TYPE_IQ4_XS;
++qs.i_ffn_up;
}

Expand Down

0 comments on commit b02eaf6

Please sign in to comment.