1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
|
#include "stdafx.h"
#include "HybridLoader.h"
using namespace CpuCompute;
using namespace ComLight;
static void populateDecodeTensorsMap( CAtlMap<CStringA, Tensor*>& map, int layersDec, DecoderTensors& dec )
{
dec.layers.resize( layersDec );
map[ "decoder.positional_embedding" ] = &dec.positionalEmbedding;
map[ "decoder.token_embedding.weight" ] = &dec.tokenEmbedding;
map[ "decoder.ln.weight" ] = &dec.ln.w;
map[ "decoder.ln.bias" ] = &dec.ln.b;
CStringA tempString;
auto add = [ & ]( const char* name, int i, Tensor& t )
{
tempString.Format( "decoder.blocks.%i.%s", i, name );
map[ tempString ] = &t;
};
auto add2 = [ & ]( const char* name, int i, TensorPair& tensors )
{
tempString.Format( "decoder.blocks.%i.%s.weight", i, name );
map[ tempString ] = &tensors.w;
tempString.Format( "decoder.blocks.%i.%s.bias", i, name );
map[ tempString ] = &tensors.b;
};
for( int i = 0; i < layersDec; i++ )
{
auto& gpu = dec.layers[ i ];
add2( "mlp_ln", i, gpu.mlpLn );
add2( "mlp.0", i, gpu.mlp0 );
add2( "mlp.2", i, gpu.mlp1 );
add2( "attn_ln", i, gpu.attnLn0 );
add2( "attn.query", i, gpu.attnQuery );
add( "attn.key.weight", i, gpu.attnKey );
add2( "attn.value", i, gpu.attnValue );
add2( "attn.out", i, gpu.attnLn1 );
add2( "cross_attn_ln", i, gpu.crossAttnLn0 );
add2( "cross_attn.query", i, gpu.crossAttnQuery );
// These 3 tensors are used by the encode() method, to compute cross-attention buffers
// Need them in VRAM even for the hybrid model
// add( "cross_attn.key.weight", i, gpu.cross_attn_k_w );
// add2( "cross_attn.value", i, gpu.cross_attn_v_w, gpu.cross_attn_v_b );
add2( "cross_attn.out", i, gpu.crossAttnLn1 );
}
}
HybridLoader::HybridLoader( DecoderTensors& m, int countLayers ) :
destination( m )
{
populateDecodeTensorsMap( map, countLayers, destination );
pending.reserve( map.GetCount() );
}
HRESULT HybridLoader::setupTensor( const CStringA& name, int n_dims, int ftype, const std::array<int, 4>& ne, ComLight::iReadStream* stream, int64_t& postponedBytes )
{
auto p = map.Lookup( name );
if( nullptr == p )
return S_FALSE;
Tensor& rdi = *p->m_value;
PendingTensor& pt = pending.emplace_back();
__m128i vec = load16( ne.data() );
vec = _mm_insert_epi32( vec, 1, 3 );
store16( &rdi.ne, vec );
rdi.setDenseStrides();
pt.destPointer = p->m_value;
CHECK( stream->getPosition( pt.streamOffset ) );
pt.bufferOffset = bufferBytes;
size_t cbElement;
if( ftype == 0 )
{
rdi.setType( eDataType::FP32 );
cbElement = 4;
}
else
{
rdi.setType( eDataType::FP16 );
cbElement = 2;
}
const size_t totalElts = (size_t)(uint32_t)ne[ 0 ] * (uint32_t)ne[ 1 ] * (uint32_t)ne[ 2 ];
if( totalElts * cbElement > UINT_MAX )
return DISP_E_OVERFLOW;
size_t payloadBytes = cbElement * totalElts;
pt.payloadBytes = payloadBytes;
CHECK( stream->seek( payloadBytes, eSeekOrigin::Current ) );
postponedBytes += (int64_t)payloadBytes;
payloadBytes = ( payloadBytes + 31 ) & ( ~( (size_t)31 ) );
bufferBytes += payloadBytes;
return S_OK;
}
HRESULT HybridLoader::completeLoad( ComLight::iReadStream* stream, iLoaderProgressSink& progressSink )
{
if( pending.size() != map.GetCount() )
{
logError( u8"Not all tensors loaded from model file - expected %zu, got %zu", map.GetCount(), pending.size() );
return E_INVALIDARG;
}
LargeBuffer buffer;
CHECK( buffer.allocate( bufferBytes ) );
uint8_t* rdi = buffer.pointer();
for( const auto& pt : pending )
{
if( pt.payloadBytes > INT_MAX )
return DISP_E_OVERFLOW;
CHECK( stream->seek( pt.streamOffset, eSeekOrigin::Begin ) );
int written = 0;
CHECK( stream->read( rdi, (int)pt.payloadBytes, written ) );
CHECK( progressSink.gotBytes( (int64_t)pt.payloadBytes ) );
pt.destPointer->setDataPointer( rdi );
const size_t cb = ( pt.payloadBytes + 31 ) & ( ~( (size_t)31 ) );
rdi += cb;
}
CHECK( buffer.setReadOnly( bufferBytes ) );
destination.setMemoryBuffer( std::move( buffer ) );
constexpr double mulMb = 1.0 / ( 1 << 20 );
logDebug( u8"Loaded %zu decoder tensors, %g MB RAM", pending.size(), mulMb * (double)(int64_t)bufferBytes );
return S_OK;
}
|
