vbatts/llama.cpp
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llm : add Falcon support (#2717)

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* llama : refactor GGUF constants into static maps

* llama : check if model architecture is known

* llama : refactor llama_model_load_internal()

* gguf : add KV constant maps

* llm : read arch-specific KVs

* convert : add dummy scores + types

* falcon : load tensor data (CPU only)

* llama : fix loading progress bar

* llama : add arch member to llama_model

* falcon : CPU inference working

* falcon : support non-40B models

* falcon : minor

* llama : minor updates

ggml-ci

* convert-falcon-hf-to-gguf.py : fix special token mapping

* llama.cpp : llama default UNK token = id 0

* llama.cpp : fix bpe tokenizer

* llama.cpp : fix the fix of bpe tokenizer

* ggml : pass eps to ggml_norm

* metal : implement RoPE (mode = 2) + avoid ggml_repeat

* ggml : ggml_repeat always creates new tensor

* falcon : copy-paste self-attention from LLaMA

* metal : print extra compute pipeline info

* falcon : minor changes (still chasing the Metal problem)

* llama.cpp : fix linefeed token

* metal : fix GELU kernel numerical stability by using precise::tanh

* metal : temporary workaround for the concurrency optimization bug

* falcon : add CUDA offloading (#2739)

* llama : better model naming and size reporting

* llama : prep new tokenizer support

* llama : advanced BPE tokenizer based on ggllm.cpp imlpementation

* llama : remove oboslete comment

ggml-ci

* common : remove obsolete BPE API + disable test-tokenizer-1

* llama : revert BPE special-case in llama_byte_to_token()

* cuda : add TODOs for RoPE NeoX implementation

* llama : default special tokens based on vocab type

* perplexity : add log for start of tokenization

---------

Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
Co-authored-by: slaren <slarengh@gmail.com>
This commit is contained in:
Georgi Gerganov 2023-08-23 23:08:04 +03:00 • committed by GitHub
parent a192860cfe
commit cf658adc83
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18 changed files with 1596 additions and 668 deletions
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29
ggml-cuda.cu
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@ -3907,6 +3907,29 @@ static __global__ void rope_f32(const float * x, float * dst, const int ncols, c
dst[i + 1] = x0*sin_theta + x1*cos_theta;
}
// TODO: this implementation is wrong!
//static __global__ void rope_neox_f32(const float * x, float * dst, const int ncols, const float p0,
// const float p_delta, const int p_delta_rows, const float theta_scale) {
// const int col = 2*(blockDim.y*blockIdx.y + threadIdx.y);
//
// if (col >= ncols) {
// return;
// }
//
// const int row = blockDim.x*blockIdx.x + threadIdx.x;
// const int i = row*ncols + col/2;
//
// const float theta = (p0 + p_delta * (row/p_delta_rows))*powf(theta_scale, col/2);
// const float sin_theta = sinf(theta);
// const float cos_theta = cosf(theta);
//
// const float x0 = x[i + 0];
// const float x1 = x[i + ncols/2];
//
// dst[i + 0] = x0*cos_theta - x1*sin_theta;
// dst[i + ncols/2] = x0*sin_theta + x1*cos_theta;
//}
static __global__ void rope_glm_f32(const float * x, float * dst, const int ncols, const float p, const float block_p, const float theta_scale) {
const int col = blockDim.x*blockIdx.x + threadIdx.x;
const int half_n_dims = ncols/4;
@ -5515,7 +5538,8 @@ inline void ggml_cuda_op_rope(
const float theta_scale = powf(freq_base, -2.0f/n_dims);
const bool is_glm = mode & 4;
const bool is_neox = mode & 2;
const bool is_glm = mode & 4;
// compute
if (is_glm) {
@ -5523,6 +5547,9 @@ inline void ggml_cuda_op_rope(
const float id_p = min(p, n_ctx - 2.f);
const float block_p = max(p - (n_ctx - 2.f), 0.f);
rope_glm_f32_cuda(src0_ddf_i, dst_ddf_i, ne00, i01_diff, id_p, block_p, theta_scale, cudaStream_main);
} else if (is_neox) {
GGML_ASSERT(false && "RoPE NeoX not implemented yet");
#pragma message("TODO: implement RoPE NeoX for CUDA")
} else {
const float p0 = (((mode & 1) == 0 ? n_past : 0)) * freq_scale;
rope_f32_cuda(src0_ddf_i, dst_ddf_i, ne00, i01_diff, p0, freq_scale, ne01, theta_scale, cudaStream_main);