llama.cpp/src/llama-hparams.cpp
Molly Sophia ee7136c6d1
llama: add support for QRWKV6 model architecture (#11001)
llama: add support for QRWKV6 model architecture (#11001)

* WIP: Add support for RWKV6Qwen2

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* RWKV: Some graph simplification

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Add support for RWKV6Qwen2 with cpu and cuda GLA

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* RWKV6[QWEN2]: Concat lerp weights together to reduce cpu overhead

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Fix some typos

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* code format changes

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Fix wkv test & add gla test

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Fix cuda warning

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Update README.md

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Update ggml/src/ggml-cuda/gla.cu

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Fix fused lerp weights loading with RWKV6

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* better sanity check skipping for QRWKV6 in llama-quant

thanks @compilade

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>
Co-authored-by: compilade <git@compilade.net>

---------

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: compilade <git@compilade.net>
2025-01-10 09:58:08 +08:00

72 lines
1.6 KiB
C++

#include "llama-hparams.h"
#include "ggml.h"
uint32_t llama_hparams::n_head(uint32_t il) const {
if (il < n_layer) {
return n_head_arr[il];
}
GGML_ABORT("fatal error");
}
uint32_t llama_hparams::n_head_kv(uint32_t il) const {
if (il < n_layer) {
return n_head_kv_arr[il];
}
GGML_ABORT("fatal error");
}
uint32_t llama_hparams::n_ff(uint32_t il) const {
if (il < n_layer) {
return n_ff_arr[il];
}
GGML_ABORT("fatal error");
}
uint32_t llama_hparams::n_gqa(uint32_t il) const {
const uint32_t n_head = this->n_head(il);
const uint32_t n_head_kv = this->n_head_kv(il);
if (n_head_kv == 0) {
return 0;
}
return n_head/n_head_kv;
}
uint32_t llama_hparams::n_embd_k_gqa(uint32_t il) const {
const uint32_t n_head_kv = this->n_head_kv(il);
return n_embd_head_k * n_head_kv;
}
uint32_t llama_hparams::n_embd_v_gqa(uint32_t il) const {
const uint32_t n_head_kv = this->n_head_kv(il);
return n_embd_head_v * n_head_kv;
}
uint32_t llama_hparams::n_embd_k_s() const {
if (wkv_head_size != 0) {
// for RWKV models
return token_shift_count * n_embd;
}
// TODO: maybe support other convolution strides than 1
// NOTE: since the first column of the conv_state is shifted out each time, it's not actually needed
return (ssm_d_conv > 0 ? ssm_d_conv - 1 : 0) * ssm_d_inner;
}
uint32_t llama_hparams::n_embd_v_s() const {
if (wkv_head_size != 0) {
// corresponds to RWKV's wkv_states size
return n_embd * wkv_head_size;
}
// corresponds to Mamba's ssm_states size
return ssm_d_state * ssm_d_inner;
}