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construct/ircd/gpt.cc

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22 KiB
C++

// Matrix Construct Is All You Need Is All You Need Is AllĊĊĊĊĊĊĊĊ
//
// Copyright (C) Matrix Construct Developers, Authors & Contributors
// Copyright (C) 2016-2021 Jason Volk <jason@zemos.net>
//
// Permission to use, copy, modify, and/or distribute this software for any
// purpose with or without fee is hereby granted, provided that the above
// copyright notice and this permission notice is present in all copies. The
// full license for this software is available in the LICENSE file.
decltype(ircd::gpt::log)
ircd::gpt::log
{
"gpt"
};
//
// debug
//
void
ircd::gpt::log_debug_prof(const opts &opts,
const ctrl &ctrl,
const pipe::prof &prof)
{
static char
buf[2][512];
const auto head
{
debug_head(buf[0], opts, ctrl)
};
for(uint i(0); i < prof.stages; ++i)
{
if(!std::get<1>(prof.info[i]))
continue;
log::logf
{
log, log::level::DEBUG,
"%s %2u: %s",
head,
i,
pipe::debug(buf[1], prof, i),
};
}
}
void
ircd::gpt::log_debug_topn(const opts &opts,
const ctrl &ctrl)
{
static char
buf[2][512];
const auto head
{
debug_head(buf[0], opts, ctrl)
};
for(uint i(0); i < opts.top_n; ++i)
log::logf
{
log, log::level::DEBUG,
"%s %s",
head,
debug_top(buf[1], opts, ctrl, i),
};
}
void
ircd::gpt::log_debug_labels(const opts &opts,
const ctrl &ctrl)
{
static char
buf[2][512];
const auto head
{
debug_head(buf[0], opts, ctrl)
};
for(uint i(0); i < opts.labels; ++i)
log::logf
{
log, log::level::DEBUG,
"%s %s",
head,
debug_label(buf[1], opts, ctrl, i, 1),
};
}
void
ircd::gpt::log_debug_attns_top(const opts &opts,
const ctrl &ctrl)
{
static char
buf[8][512];
const auto head
{
debug_head(buf[0], opts, ctrl)
};
std::map<uint, uint> tokm;
for(uint i(0); i < opts.layers; ++i)
for(uint j(0); j < opts.attn_rank; ++j)
tokm[ctrl.attn[i][j]]++;
std::vector<std::pair<uint, uint>> tok(begin(tokm), end(tokm));
std::sort(begin(tok), end(tok), [&tokm]
(const auto &a, const auto &b)
{
return b.second < a.second;
});
for(const auto &[idx, score] : tok)
{
const auto barsz
{
std::min(score, std::min(80U, uint(sizeof(buf[2]) - 1)))
};
memset(buf[2], '|', barsz);
buf[2][barsz] = '\0';
log::logf
{
log, log::level::DEBUG,
"%s %s [%3u] %s %-3u",
head,
vocab::debug(buf[1], ctrl.token[idx], 1),
idx,
buf[2],
score,
};
}
}
void
ircd::gpt::log_debug_attns(const opts &opts,
const ctrl &ctrl)
{
static char
buf[2][512];
const auto head
{
debug_head(buf[0], opts, ctrl)
};
for(uint i(0); i < ctrl.count; ++i)
log::logf
{
log, log::level::DEBUG,
"%s %s",
head,
debug_attn(buf[1], opts, ctrl, i),
};
}
void
ircd::gpt::log_debug_token(const opts &opts,
const ctrl &ctrl,
const uint i)
{
static char
buf[2][512];
log::logf
{
log, log::level::DEBUG,
"%s %s",
debug_head(buf[0], opts, ctrl),
debug_token_at(buf[1], opts, ctrl, i),
};
}
void
ircd::gpt::log_debug(const opts &opts,
const ctrl &ctrl)
{
static char
buf[2][512];
log::logf
{
log, log::level::DEBUG,
"%s %s",
debug_head(buf[0], opts, ctrl),
debug(buf[1], opts, ctrl),
};
}
///////////////////////////////////////////////////////////////////////////////
//
// gpt::task
//
void
ircd::gpt::reset(task &task)
noexcept
{
clear(task);
seed(task);
}
void
ircd::gpt::clear(task &task)
noexcept
{
assert(task.ctrl);
memset(task.ctrl, 0x0, sizeof(gpt::ctrl));
}
void
ircd::gpt::seed(task &task)
noexcept
{
assert(task.opts);
seed(task, task.opts->seed);
}
void
ircd::gpt::seed(task &task,
const uint64_t &val)
noexcept
{
assert(task.ctrl);
task.ctrl->rand[0] = val;
task.ctrl->rand[1] = val;
task.ctrl->rand[2] = 65537;
task.ctrl->rand[3] = -1UL;
}
//
// gpt::task::task
//
ircd::gpt::task::task(const gpt::opts *const opts,
gpt::ctrl *const ctrl)
try
:opts
{
opts
}
,ctrl
{
ctrl
}
,code
{
std::make_unique<pipe::code>()
}
,model
{
std::make_unique<pipe::model>
(
*const_cast<const gpt::model::decoder *>(gpt::model::default_model)
)
}
,desc
{
this->opts,
this->ctrl,
*this->model,
*this->code,
}
{
assert(aligned(opts, size_t(cl::data::gart_page_size)));
assert(aligned(ctrl, size_t(cl::data::gart_page_size)));
seed(*this, this->opts->seed);
}
catch(const std::exception &e)
{
log::error
{
log, "Task ctor :%s", e.what()
};
throw;
}
ircd::gpt::task::~task()
noexcept
{
}
ircd::string_view
ircd::gpt::task::operator()(const mutable_buffer &out,
const string_view &in)
{
u16 input_buf[1024];
const auto input_tokens
{
gpt::vocab::tokenize(input_buf, in)
};
u16 output_buf[1024];
const auto output_tokens
{
operator()(output_buf, input_tokens)
};
const auto output
{
gpt::vocab::detokenize(out, output_tokens)
};
return output;
}
ircd::vector_view<ircd::u16>
ircd::gpt::task::operator()(const vector_view<u16> &out,
const vector_view<const u16> &in)
{
assert(this->opts);
const auto &opts{*this->opts};
assert(this->ctrl);
auto &ctrl{*this->ctrl};
size_t in_i(0);
for(; in_i < in.size() && ctrl.count < opts.buffer_tokens; in_i++)
if(in[in_i] == 628)
{
ctrl.token[ctrl.count++] = 198;
ctrl.token[ctrl.count++] = 198;
}
else ctrl.token[ctrl.count++] = in[in_i];
gpt::epoch epoch
{
*this,
};
gpt::step step
{
epoch
};
gpt::samp samp
{
step
};
bool halt {false}; do
{
halt = samp();
}
while(!halt);
size_t out_i(0);
for(; out_i < out.size() && in_i + out_i < ctrl.count; out_i++)
out[out_i] = ctrl.token[in_i + out_i];
return vector_view<u16>
{
out, out_i
};
}
bool
ircd::gpt::task::operator()()
{
gpt::epoch epoch
{
*this
};
while(!epoch())
ctx::interruption_point();
return done();
}
bool
ircd::gpt::task::done()
const noexcept
{
return false;
}
///////////////////////////////////////////////////////////////////////////////
//
// epoch
//
namespace ircd::gpt
{
static thread_local u16 marker alignas(64) [1024];
}
//
// epoch::epoch
//
ircd::gpt::epoch::epoch(gpt::task &task)
:task
{
task
}
,desc
{
task.desc
}
,opts
{
*task.opts
}
,ctrl
{
*task.ctrl
}
,id
{
ctrl.clk.epoch
}
,start
{
0
}
,stop
{
std::min(start + uint(opts.batch_size), gpt::model::default_data.size())
}
,moment
{
gpt::model::default_moment[0],
gpt::model::default_moment[1],
}
{
assert(task.opts);
assert(task.ctrl);
ctrl.clk.step = 0;
}
ircd::gpt::epoch::~epoch()
noexcept
{
if(opts.debug & 0x80000000U)
log_debug_prof(opts, ctrl, this->profile);
}
bool
ircd::gpt::epoch::operator()()
{
gpt::step step
{
*this
};
while(!step())
ctx::interruption_point();
if(!step.backpropagate())
throw error
{
"Failed to backprop."
};
return done();
}
bool
ircd::gpt::epoch::done()
const noexcept
{
return ctrl.clk.epoch != id;
}
void
ircd::gpt::epoch::profile_accumulate(const pipe::prof &profile)
{
for(size_t i(0); i < profile.ts.size(); ++i)
for(size_t j(0); j < profile.phases; ++j)
this->profile.ts[i][j] += profile.ts[i][j];
}
///////////////////////////////////////////////////////////////////////////////
//
// step::step
//
ircd::gpt::step::step(gpt::epoch &epoch)
:epoch
{
epoch
}
,desc
{
epoch.desc
}
,opts
{
epoch.opts
}
,ctrl
{
epoch.ctrl
}
,id
{
ctrl.clk.step
}
,start
{
ctrl.clk.step * opts.batch_size
}
{
assert(opts.batch_size > 0);
ctrl.clk.samp = 0;
ctrl.hit = 0;
ctrl.miss = 0;
ctrl.target.ppl = {{0}};
ctrl.target.loss = {{0}};
ctrl.select.ppl = {{0}};
ctrl.select.loss = {{0}};
for(uint i(0); i < opts.labels; ++i)
{
ctrl.label[i].ppl = {{0}};
ctrl.label[i].loss = {{0}};
}
}
ircd::gpt::step::~step()
noexcept
{
if(opts.debug & 0x40000000U)
log_debug_prof(opts, ctrl, this->profile);
}
bool
ircd::gpt::step::backpropagate()
{
const auto hit
{
ctrl.target.logit.token == ctrl.select.logit.token
};
const auto select_loss_mean
{
ctrl.select.loss.mean
};
const auto target_loss_mean
{
ctrl.target.loss.mean
};
const auto loss_mean
{
(target_loss_mean + select_loss_mean) / 2.0f
};
static float mean_best { 10000.0f }, target_mean_best { 10000.0f };
static ulong hit_best;
static bool tack, last_tack;
last_tack = tack;
const auto loss
{
loss_mean
};
const bool improve_global
{
target_loss_mean < target_mean_best
};
const bool improve
{
improve_global
};
if(improve)
mean_best = loss,
target_mean_best = target_loss_mean,
hit_best = ctrl.hit;
else
tack = !tack;
const auto grad
{
!tack? loss : -loss
};
const auto steps
{
(opts.training_steps + opts.validation_steps + opts.testing_steps) / opts.batch_size
};
const auto step
{
this->epoch.id * steps + this->id
};
log::logf
{
log, improve? log::level::INFO: log::level::ERROR,
"epoch:%u step:%u completed range[%u -> %zu] dsid:%u target:%-10.7f select:%-10.7f loss:%-10.7f [ %10.7f ] hit:%u miss:%u",
this->epoch.id,
step,
this->start,
this->start + opts.batch_size,
this->id * opts.batch_size + ctrl.clk.samp,
target_loss_mean,
select_loss_mean,
loss,
grad * opts.alpha,
ctrl.hit,
ctrl.miss,
};
if(!opts.alpha)
return true;
if(!improve)
return false;
cl::exec
{
desc.model->decode->master[0], std::memory_order_acq_rel
};
auto &model
{
*mutable_cast(desc.model->decode_const)
};
const mutable_buffer model_buffer
{
reinterpret_cast<char *>(&model),
sizeof(gpt::model::decoder) * 3
};
const mutable_buffer checkpoint_buffer
{
reinterpret_cast<char *>(&model) + sizeof(gpt::model::decoder) * 3,
sizeof(gpt::model::decoder) * 3
};
if(improve)
copy(checkpoint_buffer, model_buffer);
else
copy(model_buffer, checkpoint_buffer);
ircd::timer stopwatch;
backprop(opts, step, grad, model, epoch.moment);
allocator::sync(model_buffer);
char pbuf[1][32];
log::logf
{
log, improve? log::level::DEBUG: log::level::ERROR,
"backpropagation step:%u lr:%-8.6f mean:%-10.7f$L hits:%-5u Tbest:%-10.7f$L Mbest:%-10.7f$L Hbest:%-5lu grad:{ %10.7f$L } %s",
step,
opts.alpha,
loss_mean,
ctrl.hit,
target_mean_best,
mean_best,
hit_best,
grad,
pretty(pbuf[0], stopwatch.at<milliseconds>(), 1),
};
return true;
}
bool
ircd::gpt::step::operator()()
{
gpt::samp samp
{
*this
};
while(!samp())
ctx::interruption_point();
return done();
}
bool
ircd::gpt::step::done()
const noexcept
{
return ctrl.clk.step != id;
}
void
ircd::gpt::step::profile_accumulate(const pipe::prof &profile)
{
for(size_t i(0); i < profile.ts.size(); ++i)
for(size_t j(0); j < profile.phases; ++j)
this->profile.ts[i][j] += profile.ts[i][j];
epoch.profile_accumulate(profile);
}
///////////////////////////////////////////////////////////////////////////////
//
// samp::samp
//
ircd::gpt::samp::samp(gpt::step &step)
:step
{
step
}
,desc
{
step.desc
}
,opts
{
step.opts
}
,ctrl
{
step.ctrl
}
,id
{
ctrl.clk.samp
}
,accept
{
-1
}
,dispatch
{
1
}
,cycle
{
0
}
,tokens
{
ctrl.count?:
tokenize()
}
,count
{
opts.limit > 0?
tokens - opts.limit:
opts.limit < 0?
std::abs(opts.limit):
!ctrl.count?
tokens:
1
}
{
desc.cached = 0;
ctrl.clk.cycle = cycle;
ctrl.dispatch = dispatch;
ctrl.accept = accept;
ctrl.count = count;
ctrl.tokens = tokens;
ctrl.magic = 0xDEADBEEF;
for(uint i(0); i < opts.labels; ++i)
{
ctrl.label[i].ppl = {{0}};
ctrl.label[i].loss = {{0}};
}
assert(ctrl.count > 0);
assert(ctrl.count < opts.context_tokens);
assert(ctrl.count <= ctrl.tokens);
if(opts.debug & 0x01)
for(uint j(0); j < ctrl.count; ++j)
log_debug_token(opts, ctrl, j);
}
ircd::gpt::samp::~samp()
noexcept
{
if(run::level != run::level::RUN)
return;
cl::exec
{
desc.ctrl, std::memory_order_acq_rel
};
if(opts.debug & 0x04)
log_debug(opts, ctrl);
if(opts.debug & 0x40)
log_debug_labels(opts, ctrl);
if(opts.debug & 0x20000000U)
log_debug_prof(opts, ctrl, this->profile);
}
bool
ircd::gpt::samp::operator()()
{
if(dispatch > 0)
{
ctx::interruption_point();
queue.emplace_back(*this);
desc.cached = tokens;
tokens += count >= tokens;
++cycle;
++count;
--dispatch;
return false;
}
while(!queue.empty())
{
const unwind pop{[this]
{
queue.pop_front();
}};
if(evaluate(queue.front()))
break;
}
return done();
}
bool
ircd::gpt::samp::done()
const noexcept
{
return accept >= 0;
}
uint
ircd::gpt::samp::tokenize()
{
const auto idx
{
step.start + ctrl.clk.samp
};
const gpt::model::text text
{
gpt::model::default_data.at(idx)
};
const json::string input
{
json::get<"text"_>(text)
};
thread_local char str_buf[16_KiB];
const string_view str
{
json::unescape(str_buf, input)
};
assert(!empty(str));
static const auto delim
{
"\n\n"_sv
};
const int phrases
(
ircd::token_count(str, delim)
);
uint count(0);
int p(phrases);
assert(p >= 0);
if(startswith(str, delim))
{
ctrl.token[count++] = 198;
ctrl.token[count++] = 198;
}
ircd::tokens(str, delim, [this, &count, &p, &phrases]
(const string_view &phrase) noexcept -> bool
{
assert(!empty(phrase));
const vector_view<u16> buf
{
ctrl.token + count, opts.buffer_tokens - count
};
const auto in
{
gpt::vocab::tokenize(buf, phrase)
};
if(count + size(in) + 2 > opts.context_tokens)
return false;
count += size(in);
ctrl.token[count++] = 198;
ctrl.token[count++] = 198;
assert(p > 0);
marker[--p] = count;
return true;
});
for(assert(p >= 0); p < phrases; ++p)
if(marker[p] <= opts.context_tokens)
break;
assert(p <= phrases);
count = marker[p];
for(uint i(count); i < opts.buffer_tokens; ++i)
ctrl.token[i] = 198;
if(!endswith(str, delim))
count -= 2;
assert(count > 0);
assert(count <= opts.context_tokens);
return count;
}
bool
ircd::gpt::samp::evaluate(pipe::cycle &cycle)
{
cl::exec
{
desc.frame[cycle.frame], std::memory_order_consume
};
const auto &frame
{
acquire(cycle)
};
if(!retire(cycle, frame))
return false;
memcpy(&ctrl, &frame, sizeof(gpt::ctrl));
const uint
batch_size = opts.batch_size,
samps = opts.training_steps + opts.validation_steps + opts.testing_steps,
steps = samps / batch_size;
const bool
accepting = accept >= 0,
cycling = !accepting,
sampling = accepting,
stepping = sampling && (frame.clk.samp + 1) >= batch_size,
epoching = stepping && (frame.clk.step + 1) >= steps;
//ctrl.token[ctrl.count] = ctrl.select.logit.token;
//ctrl.count++;
if(accepting)
{
ctrl.clk.cycle += cycling;
ctrl.clk.samp += sampling;
ctrl.clk.step += stepping;
ctrl.clk.epoch += epoching;
}
return true;
}
bool
ircd::gpt::samp::retire(pipe::cycle &cycle,
const gpt::ctrl &frame)
{
assert(accept < 0);
accept = frame.accept;
dispatch = frame.dispatch;
if(cl::profile_queue)
{
const pipe::prof profile
{
cycle
};
if(opts.debug & 0x10000000U)
log_debug_prof(opts, frame, profile);
profile_accumulate(profile);
}
if(opts.debug & 0x02)
log_debug(opts, frame);
if(opts.debug & 0x20)
log_debug_labels(opts, frame);
if(opts.debug & 0x10)
log_debug_topn(opts, frame);
if(opts.debug & 0x200)
log_debug_attns_top(opts, frame);
dispatch &= boolmask<uint>(ircd::run::level == run::level::RUN);
dispatch &= boolmask<uint>(!ctx::interruption_requested());
dispatch &= boolmask<uint>(accept < 0);
const bool finished
{
dispatch == 0
};
return finished;
}
void
ircd::gpt::samp::profile_accumulate(const pipe::prof &profile)
{
for(size_t i(0); i < profile.ts.size(); ++i)
for(size_t j(0); j < profile.phases; ++j)
this->profile.ts[i][j] += profile.ts[i][j];
step.profile_accumulate(profile);
}
///////////////////////////////////////////////////////////////////////////////
//
// ctrl
//
ircd::string_view
ircd::gpt::debug_top(const mutable_buffer &out,
const opts &opts,
const ctrl &ctrl,
const uint i)
{
thread_local char buf[2][256];
assert(opts.top_n > i);
const auto &top
{
ctrl.top[i]
};
return fmt::sprintf
{
out, "%s T%02d %s",
vocab::debug(buf[0], top.token, 1),
i,
debug(buf[1], opts, top),
};
}
ircd::string_view
ircd::gpt::debug_label(const mutable_buffer &out,
const opts &opts,
const ctrl &ctrl,
const uint i,
const uint fmt)
{
thread_local char buf[2][256];
assert(opts.labels > i);
const auto &label
{
ctrl.label[i]
};
return fmt::sprintf
{
out, "%s L%02d %s",
vocab::debug(buf[0], label.logit.token, 1),
i,
debug(buf[1], opts, label, fmt),
};
}
ircd::string_view
ircd::gpt::debug_attn(const mutable_buffer &out,
const opts &opts,
const ctrl &ctrl,
const uint ti)
{
thread_local char buf[4][256];
assert(ti < ctrl.count);
memset(buf[1], 0x0, sizeof(buf[1]));
for(uint i(0); i < opts.layers; ++i)
{
const auto f{[&](const auto &a) { return a == ti; }};
if(std::none_of(ctrl.attn[i], ctrl.attn[i] + opts.attn_rank, f))
continue;
strlcat{buf[1], fmt::sprintf
{
buf[2], " %1x[", uint(i)
}};
for(uint j(0); j < opts.attn_rank; ++j)
if(ctrl.attn[i][j] == ti)
strlcat{buf[1], fmt::sprintf
{
buf[2], "%1x", uint(j)
}};
strlcat{buf[1], "]"_sv};
}
return fmt::sprintf
{
out, "%s [%3u] <-%s",
vocab::debug(buf[0], ctrl.token[ti], 1),
ti,
string_view{buf[1]},
};
}
ircd::string_view
ircd::gpt::debug(const mutable_buffer &out,
const opts &opts,
const ctrl &ctrl)
{
thread_local char
buf[8][128],
tmbuf[4][32];
int top_idx {-1};
for(uint i(0); i < opts.top_n; ++i)
if(ctrl.top[i].token == ctrl.select.logit.token)
{
top_idx = i;
break;
}
return fmt::sprintf
{
out, "%s %s %c T%02d %4u %6.2f%% %10.7f$L %c %s %s",
vocab::debug(buf[0], ctrl.select.logit.token, 1),
debug(buf[1], opts, ctrl.select),
ctrl.target.logit.token == ctrl.top[0].token? '=' : ' ',
top_idx,
ctrl.hit,
(ctrl.hit / float(ctrl.hit + ctrl.miss)) * 100.0f,
ctrl.target.loss.mean - ctrl.select.loss.mean,
ctrl.target.logit.token == ctrl.select.logit.token? '=' : ' ',
debug(buf[2], opts, ctrl.target),
vocab::debug(buf[3], ctrl.target.logit.token, 1),
};
}
ircd::string_view
ircd::gpt::debug(const mutable_buffer &out,
const opts &opts,
const ctrl_label &label,
const uint fmt)
{
thread_local char buf[64], bar[128];
const auto diff
{
log2f(65536) - label.loss.mean
};
const auto pct
{
(diff / log2f(opts.logits)) * 100.0f
};
const auto barsz
{
std::min(uint(pct), std::min(66U, uint(sizeof(bar) - 1)))
};
memset(bar, '|', barsz);
bar[barsz] = '\0';
return fmt::sprintf
{
out,
fmt == 1?
"%s %10.7f$La %6.2f%% %s":
"%s %10.7f$La",
debug(buf, opts, label.logit, fmt),
label.loss.mean,
pct,
string_view{bar},
};
}
ircd::string_view
ircd::gpt::debug(const mutable_buffer &out,
const opts &opts,
const ctrl_logit &logit,
const uint fmt)
{
return fmt::sprintf
{
out, "%6.2f%% %10.7f$L %5.1f$P",
logit.samax * 100.0f,
+0.0f - logf(logit.samax),
(1.0f - logit.samax) * log2f(opts.logits),
};
}
ircd::string_view
ircd::gpt::debug_head(const mutable_buffer &out,
const opts &opts,
const ctrl &ctrl)
{
thread_local char head[64];
return fmt::sprintf
{
out, "%s[%4u]-%1u",
debug_head(head, opts, ctrl.clk),
ctrl.count,
ctrl.dispatch,
};
}
ircd::string_view
ircd::gpt::debug_head(const mutable_buffer &out,
const opts &opts,
const ctrl_clk &clk)
{
return fmt::sprintf
{
out, "%02u:%06u|%04u|%04u|%04u",
clk.epoch,
clk.step * opts.batch_size + clk.samp,
clk.step,
clk.samp,
clk.cycle,
};
}
ircd::string_view
ircd::gpt::debug_token(const mutable_buffer &out,
const opts &opts,
const ctrl &ctrl,
const uint fmt)
{
assert(ctrl.count > 0);
const auto pos
{
ctrl.count - 1
};
return debug_token_at(out, opts, ctrl, pos, fmt);
}
ircd::string_view
ircd::gpt::debug_token_at(const mutable_buffer &out,
const opts &opts,
const ctrl &ctrl,
const uint i,
const uint fmt)
{
const auto &token
{
ctrl.token[i]
};
return vocab::debug(out, token, fmt);
}
///////////////////////////////////////////////////////////////////////////////
//
// opts
//
ircd_gpt_opts::ircd_gpt_opts()
noexcept
:seed
{
1234567890UL
}
,top_k
{
16
}
,top_p
{
0.90f
}
,top_n
{
0
}
,labels
{
0
}
,frames
{
8
}
,limit
{
-1
}
,debug
{
0x00
}
,accept
{
{ 198, 198, ushort(-1), },
{ 0, 0, 0, ushort(-1), },
{ ushort(-1), },
{ ushort(-1), },
}
,batch_size
{
32
}
,training_steps
{
250000
}
,validation_steps
{
5000
}
,testing_steps
{
5000
}
,alpha
{
0.00002
}
,beta
{
0.9f,
0.999f,
}
,epsilon
{
0.00001
}
,lambda
{
0.5
}
,logits
{
50256
}
,buffer_tokens
{
1024 - 16 // XXX
}
,context_tokens
{
512 // 1024
}
,layers
{
12
}
,lanes
{
4
}
,embed_elems
{
768
}
,embed_width
{
embed_elems / lanes
}
,attn_rank
{
12
}
,attn_mult
{
3
}
,attn_elems
{
embed_elems * attn_mult
}
,attn_fcon_width
{
attn_elems / lanes
}
,attn_fcon_height
{
embed_elems / lanes
}
,attn_proj_width
{
embed_elems / lanes
}
,attn_proj_height
{
embed_elems / lanes
}
,attn_self_elems
{
(uint(powl(context_tokens, 2)) / 2) * attn_rank
}
,ffnn_mult
{
4
}
,ffnn_elems
{
embed_elems * ffnn_mult
}
,ffnn_fcon_width
{
ffnn_elems / lanes
}
,ffnn_fcon_height
{
embed_elems / lanes
}
,ffnn_proj_width
{
embed_elems / lanes
}
,ffnn_proj_height
{
ffnn_elems / lanes
}
{
}