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backend: factor out common elements in model code (#1089)

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* backend: factor out common structs in model code

prepping to hack on these by hopefully making there be fewer places to fix the same bug

rename

* use common buffer wrapper instead of manual malloc

* fix replit compile warnings
This commit is contained in:
Aaron Miller 2023-06-28 17:35:07 -07:00 committed by GitHub
parent 285aa50b60
commit 8d19ef3909
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GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 81 additions and 202 deletions
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8
gpt4all-backend/CMakeLists.txt
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@ -98,7 +98,7 @@ foreach(BUILD_VARIANT IN LISTS BUILD_VARIANTS)
prepare_target(llamamodel-mainline llama-mainline)
add_library(replit-mainline-${BUILD_VARIANT} SHARED
replit.cpp utils.h utils.cpp llmodel_shared.cpp)
replit.cpp utils.h utils.cpp llmodel_shared.cpp llmodel_shared.h)
prepare_target(replit-mainline llama-mainline)
if (NOT LLAMA_METAL)
@ -114,15 +114,15 @@ foreach(BUILD_VARIANT IN LISTS BUILD_VARIANTS)
prepare_target(llamamodel-230511 llama-230511)
add_library(gptj-${BUILD_VARIANT} SHARED
gptj.cpp utils.h utils.cpp llmodel_shared.cpp)
gptj.cpp utils.h utils.cpp llmodel_shared.cpp llmodel_shared.h)
prepare_target(gptj ggml-230511)
add_library(falcon-${BUILD_VARIANT} SHARED
falcon.cpp utils.h utils.cpp llmodel_shared.cpp)
falcon.cpp utils.h utils.cpp llmodel_shared.cpp llmodel_shared.h)
prepare_target(falcon llama-mainline)
add_library(mpt-${BUILD_VARIANT} SHARED
mpt.cpp utils.h utils.cpp llmodel_shared.cpp)
mpt.cpp utils.h utils.cpp llmodel_shared.cpp llmodel_shared.h)
prepare_target(mpt ggml-230511)
endif()
endforeach()

74
gpt4all-backend/falcon.cpp
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@ -3,6 +3,7 @@
#include "llama.h"
#include "llama-util.h"
#include "utils.h"
#include "llmodel_shared.h"
#include <cassert>
#include <cinttypes>
@ -46,38 +47,6 @@ struct falcon_layer {
struct ggml_tensor* ffn_down;
};
struct falcon_buffer {
uint8_t * addr = NULL;
size_t size = 0;
void resize(size_t size) {
delete[] addr;
addr = new uint8_t[size];
this->size = size;
}
~falcon_buffer() {
delete[] addr;
}
};
struct falcon_kv_cache {
struct ggml_tensor * k;
struct ggml_tensor * v;
struct ggml_context * ctx = NULL;
falcon_buffer buf;
int n; // number of tokens currently in the cache
~falcon_kv_cache() {
if (ctx) {
ggml_free(ctx);
}
}
};
struct falcon_model {
falcon_hparams hparams;
@ -89,22 +58,19 @@ struct falcon_model {
std::vector<falcon_layer> layers;
// key + value memory
falcon_kv_cache kv_self;
llm_kv_cache kv_self;
struct ggml_context* ctx;
std::map<std::string, struct ggml_tensor*> tensors;
void * eval_buf;
size_t eval_buf_size;
void * scr0_buf;
size_t scr0_buf_size;
void * scr1_buf;
size_t scr1_buf_size;
llm_buffer eval_buf;
llm_buffer scr0_buf;
llm_buffer scr1_buf;
};
static bool kv_cache_init(
const struct falcon_hparams & hparams,
struct falcon_kv_cache & cache,
struct llm_kv_cache & cache,
ggml_type wtype,
int n_ctx) {
const int n_embd = hparams.n_embd;
@ -464,12 +430,9 @@ bool falcon_model_load(const std::string & fname, falcon_model & model, gpt_voca
fin.close();
model.eval_buf_size = 256u * 1024 * 1024;
model.eval_buf = malloc(model.eval_buf_size);
model.scr0_buf_size = 256u * 1024 * 1024;
model.scr0_buf = malloc(model.scr0_buf_size);
model.scr1_buf_size = 256u * 1024 * 1024;
model.scr1_buf = malloc(model.scr1_buf_size);
model.eval_buf.resize(256u * 1024 * 1024);
model.scr0_buf.resize(256u * 1024 * 1024);
model.scr1_buf.resize(256u * 1024 * 1024);
return true;
}
@ -503,8 +466,8 @@ bool falcon_eval(
const size_t head_dim = n_embd / n_head;
struct ggml_init_params eval_ctx_params = {
.mem_size = model.eval_buf_size,
.mem_buffer = model.eval_buf,
.mem_size = model.eval_buf.size,
.mem_buffer = model.eval_buf.addr,
.no_alloc = false,
};
@ -526,7 +489,7 @@ bool falcon_eval(
struct ggml_tensor * cur;
struct ggml_tensor * layernorm_output;
ggml_set_scratch(ctx0, {0, model.scr0_buf_size, model.scr0_buf, });
ggml_set_scratch(ctx0, {0, model.scr0_buf.size, model.scr0_buf.addr, });
// self-attention
{
@ -667,7 +630,7 @@ bool falcon_eval(
}
}
ggml_set_scratch(ctx0, {0, model.scr1_buf_size, model.scr1_buf, });
ggml_set_scratch(ctx0, {0, model.scr1_buf.size, model.scr1_buf.addr, });
struct ggml_tensor* inpFF = layernorm_output;
struct ggml_tensor* attn_out = ggml_cpy(
@ -685,7 +648,7 @@ bool falcon_eval(
inpL = cur;
}
ggml_set_scratch(ctx0, {0, model.scr0_buf_size, model.scr0_buf, });
ggml_set_scratch(ctx0, {0, model.scr0_buf.size, model.scr0_buf.addr, });
// norm
{
@ -864,15 +827,6 @@ Falcon::~Falcon() {
ggml_free(d_ptr->model->ctx);
d_ptr->model->ctx = nullptr;
}
if(d_ptr->model->eval_buf) {
free(d_ptr->model->eval_buf);
}
if(d_ptr->model->scr0_buf) {
free(d_ptr->model->scr0_buf);
}
if(d_ptr->model->scr1_buf) {
free(d_ptr->model->scr1_buf);
}
delete d_ptr->model;
}

40
gpt4all-backend/gptj.cpp
View File

@ -2,6 +2,7 @@
#include "gptj_impl.h"
#include "utils.h"
#include "llmodel_shared.h"
#include <cassert>
#include <cmath>
@ -63,39 +64,6 @@ struct gptj_layer {
struct ggml_tensor * c_mlp_proj_b;
};
struct gptj_buffer {
uint8_t * addr = NULL;
size_t size = 0;
void resize(size_t size) {
delete[] addr;
addr = new uint8_t[size];
this->size = size;
}
~gptj_buffer() {
fflush(stdout);
delete[] addr;
}
};
struct gptj_kv_cache {
struct ggml_tensor * k;
struct ggml_tensor * v;
struct ggml_context * ctx = NULL;
gptj_buffer buf;
int n; // number of tokens currently in the cache
~gptj_kv_cache() {
if (ctx) {
ggml_free(ctx);
}
}
};
struct gptj_model {
gptj_hparams hparams;
@ -111,13 +79,13 @@ struct gptj_model {
std::vector<gptj_layer> layers;
// key + value memory
struct gptj_kv_cache kv_self;
struct llm_kv_cache kv_self;
//
struct ggml_context * ctx;
std::map<std::string, struct ggml_tensor *> tensors;
gptj_buffer buf;
llm_buffer buf;
~gptj_model() {
if (ctx) {
@ -128,7 +96,7 @@ struct gptj_model {
static bool kv_cache_init(
const struct gptj_hparams & hparams,
struct gptj_kv_cache & cache,
struct llm_kv_cache & cache,
ggml_type wtype,
int n_ctx) {
const int n_embd = hparams.n_embd;

36
gpt4all-backend/llmodel_shared.h Normal file
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@ -0,0 +1,36 @@
#pragma once
#include <cstdint>
#include <cstddef>
#include <ggml.h>
struct llm_buffer {
uint8_t * addr = NULL;
size_t size = 0;
void resize(size_t size) {
delete[] addr;
addr = new uint8_t[size];
this->size = size;
}
~llm_buffer() {
delete[] addr;
}
};
struct llm_kv_cache {
struct ggml_tensor * k;
struct ggml_tensor * v;
struct ggml_context * ctx = NULL;
llm_buffer buf;
int n; // number of tokens currently in the cache
~llm_kv_cache() {
if (ctx) {
ggml_free(ctx);
}
}
};

40
gpt4all-backend/mpt.cpp
View File

@ -2,6 +2,7 @@
#include "mpt_impl.h"
#include "utils.h"
#include "llmodel_shared.h"
#include <cassert>
#include <cmath>
@ -62,39 +63,6 @@ struct mpt_layer {
struct ggml_tensor * ffn_down_proj_w;
};
struct mpt_buffer {
uint8_t * addr = NULL;
size_t size = 0;
void resize(size_t size) {
delete[] addr;
addr = new uint8_t[size];
this->size = size;
}
~mpt_buffer() {
fflush(stdout);
delete[] addr;
}
};
struct mpt_kv_cache {
struct ggml_tensor * k;
struct ggml_tensor * v;
struct ggml_context * ctx = NULL;
mpt_buffer buf;
int n; // number of tokens currently in the cache
~mpt_kv_cache() {
if (ctx) {
ggml_free(ctx);
}
}
};
struct mpt_model {
mpt_hparams hparams;
@ -107,12 +75,12 @@ struct mpt_model {
std::vector<mpt_layer> layers;
struct mpt_kv_cache kv_self;
struct llm_kv_cache kv_self;
struct ggml_context * ctx;
std::map<std::string, struct ggml_tensor *> tensors;
mpt_buffer buf;
llm_buffer buf;
~mpt_model() {
if (ctx) {
@ -123,7 +91,7 @@ struct mpt_model {
static bool kv_cache_init(
const struct mpt_hparams & hparams,
struct mpt_kv_cache & cache,
struct llm_kv_cache & cache,
ggml_type wtype,
int n_ctx) {
const int n_embd = hparams.n_embd;

85
gpt4all-backend/replit.cpp
View File

@ -2,8 +2,10 @@
#include "replit_impl.h"
#include "utils.h"
#include "llmodel_shared.h"
#include <cassert>
#include <cinttypes>
#include <cmath>
#include <cstddef>
#include <cstdio>
@ -181,40 +183,6 @@ struct replit_layer {
struct ggml_tensor * c_mlp_mlp_down_weight;
};
struct replit_buffer {
uint8_t * addr = NULL;
size_t size = 0;
void resize(size_t size) {
delete[] addr;
addr = new uint8_t[size];
this->size = size;
}
~replit_buffer() {
fflush(stdout);
delete[] addr;
}
};
struct replit_kv_cache {
struct ggml_tensor * k;
struct ggml_tensor * v;
struct ggml_context * ctx = NULL;
replit_buffer buf;
int n; // number of tokens currently in the cache
~replit_kv_cache() {
if (ctx) {
ggml_free(ctx);
}
}
};
struct replit_model {
mpt_hparams hparams;
@ -224,15 +192,12 @@ struct replit_model {
std::vector<replit_layer> layers;
// key + value memory
struct replit_kv_cache kv_self;
struct llm_kv_cache kv_self;
struct ggml_context * ctx;
void * eval_buf;
size_t eval_buf_size;
void * scr0_buf;
size_t scr0_buf_size;
void * scr1_buf;
size_t scr1_buf_size;
llm_buffer eval_buf;
llm_buffer scr0_buf;
llm_buffer scr1_buf;
#ifdef GGML_USE_METAL
struct ggml_metal_context * ctx_metal;
#endif
@ -241,7 +206,7 @@ struct replit_model {
static bool kv_cache_init(
const struct mpt_hparams & hparams,
struct replit_kv_cache & cache,
struct llm_kv_cache & cache,
ggml_type wtype,
int n_ctx) {
const int n_embd = hparams.n_embd;
@ -438,7 +403,7 @@ bool replit_model_load(const std::string & fname, std::istream &fin, replit_mode
const size_t memory_size = ggml_nbytes(model.kv_self.k) + ggml_nbytes(model.kv_self.v);
printf("%s: memory_size = %8.2f MB, n_mem = %ld\n", __func__, memory_size / 1024.0 / 1024.0, n_mem);
printf("%s: memory_size = %8.2f MB, n_mem = %" PRId64 "\n", __func__, memory_size / 1024.0 / 1024.0, n_mem);
}
// load weights
@ -520,12 +485,9 @@ bool replit_model_load(const std::string & fname, std::istream &fin, replit_mode
printf("%s: model size = %8.2f MB / num tensors = %d\n", __func__, total_size / 1024.0 / 1024.0, n_tensors);
}
model.eval_buf_size = 256u * 1024 * 1024;
model.eval_buf = malloc(model.eval_buf_size);
model.scr0_buf_size = 256u * 1024 * 1024;
model.scr0_buf = malloc(model.scr0_buf_size);
model.scr1_buf_size = 256u * 1024 * 1024;
model.scr1_buf = malloc(model.scr1_buf_size);
model.eval_buf.resize(256u * 1024 * 1024);
model.scr0_buf.resize(256u * 1024 * 1024);
model.scr1_buf.resize(256u * 1024 * 1024);
#ifdef GGML_USE_METAL
model.ctx_metal = ggml_metal_init();
@ -542,9 +504,9 @@ bool replit_model_load(const std::string & fname, std::istream &fin, replit_mode
GGML_CHECK_BUF(ggml_metal_add_buffer(model.ctx_metal, "data", data_ptr, data_size, max_size));
GGML_CHECK_BUF(ggml_metal_add_buffer(model.ctx_metal, "kv", ggml_get_mem_buffer(model.kv_self.ctx),
ggml_get_mem_size(model.kv_self.ctx), 0));
GGML_CHECK_BUF(ggml_metal_add_buffer(model.ctx_metal, "eval", model.eval_buf, model.eval_buf_size, 0));
GGML_CHECK_BUF(ggml_metal_add_buffer(model.ctx_metal, "scr0", model.scr0_buf, model.scr0_buf_size, 0));
GGML_CHECK_BUF(ggml_metal_add_buffer(model.ctx_metal, "scr1", model.scr1_buf, model.scr1_buf_size, 0));
GGML_CHECK_BUF(ggml_metal_add_buffer(model.ctx_metal, "eval", model.eval_buf.addr, model.eval_buf.size, 0));
GGML_CHECK_BUF(ggml_metal_add_buffer(model.ctx_metal, "scr0", model.scr0_buf.addr, model.scr0_buf.size, 0));
GGML_CHECK_BUF(ggml_metal_add_buffer(model.ctx_metal, "scr1", model.scr1_buf.addr, model.scr1_buf.size, 0));
#endif
return true;
@ -585,8 +547,8 @@ bool replit_eval(const replit_model & model, const int n_threads, const int n_pa
const int n_vocab = hparams.n_vocab;
struct ggml_init_params eval_ctx_params = {
.mem_size = model.eval_buf_size,
.mem_buffer = model.eval_buf,
.mem_size = model.eval_buf.size,
.mem_buffer = model.eval_buf.addr,
.no_alloc = false,
};
struct ggml_context * ctx0 = ggml_init(eval_ctx_params);
@ -598,7 +560,7 @@ bool replit_eval(const replit_model & model, const int n_threads, const int n_pa
struct ggml_tensor * inpL = ggml_get_rows(ctx0, model.wte_weight, embd);
for (int il = 0; il < n_layer; ++il) {
ggml_set_scratch(ctx0, {0, model.scr0_buf_size, model.scr0_buf, });
ggml_set_scratch(ctx0, {0, model.scr0_buf.size, model.scr0_buf.addr, });
struct ggml_tensor * cur;
// a = self.ln_1(x)
@ -689,7 +651,7 @@ bool replit_eval(const replit_model & model, const int n_threads, const int n_pa
// projection
{ cur = ggml_mul_mat(ctx0, model.layers[il].c_attn_out_proj_weight, cur); }
}
ggml_set_scratch(ctx0, {0, model.scr1_buf_size, model.scr1_buf, });
ggml_set_scratch(ctx0, {0, model.scr1_buf.size, model.scr1_buf.addr, });
inpL = ggml_add(ctx0, inpL, cur);
@ -716,7 +678,7 @@ bool replit_eval(const replit_model & model, const int n_threads, const int n_pa
// x = x + n
inpL = ggml_add(ctx0, inpL, cur);
}
ggml_set_scratch(ctx0, {0, model.scr0_buf_size, model.scr0_buf, });
ggml_set_scratch(ctx0, {0, model.scr0_buf.size, model.scr0_buf.addr, });
// norm
{
inpL = ggml_norm(ctx0, inpL);
@ -946,15 +908,6 @@ Replit::~Replit()
ggml_free(d_ptr->model->ctx);
d_ptr->model->ctx = nullptr;
}
if(d_ptr->model->eval_buf) {
free(d_ptr->model->eval_buf);
}
if(d_ptr->model->scr0_buf) {
free(d_ptr->model->scr0_buf);
}
if(d_ptr->model->scr1_buf) {
free(d_ptr->model->scr1_buf);
}
delete d_ptr->model;
}