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
|
/*
* Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef __NNKIT_SUPPORT_CAFFE_TENSOR_CONTEXT_H__
#define __NNKIT_SUPPORT_CAFFE_TENSOR_CONTEXT_H__
#include "nnkit/support/caffe/BlobContext.h"
#include <nnkit/TensorContext.h>
#include <nncc/core/ADT/tensor/LexicalLayout.h>
#include <nncc/core/ADT/tensor/Overlay.h>
#include <type_traits>
#include <stdexcept>
namespace nnkit
{
namespace support
{
namespace caffe
{
template <typename DType> class TensorContext final : public nnkit::TensorContext
{
public:
TensorContext(BlobContext<DType> &blobs) : _blobs(blobs)
{
// DO NOTHING
}
private:
static nncc::core::ADT::tensor::Shape shapeOf(const ::caffe::Blob<DType> &blob)
{
nncc::core::ADT::tensor::Shape shape;
const uint32_t rank = blob.shape().size();
shape.resize(rank);
for (uint32_t axis = 0; axis < rank; ++axis)
{
shape.dim(axis) = blob.shape(axis);
}
return shape;
}
public:
uint32_t size(void) const override { return _blobs.size(); }
std::string name(uint32_t n) const override { return _blobs.name(n); }
nncc::core::ADT::tensor::Shape shape(uint32_t n) const override
{
return shapeOf(*_blobs.blob(n));
}
// Float (fp32) tensor support
bool isFloatTensor(uint32_t n) const override { return std::is_same<DType, float>::value; }
void getMutableFloatTensor(uint32_t n, const TensorContext::TypedAccessor<float> &f) override
{
if (!std::is_same<DType, float>::value)
{
throw std::runtime_error{"type mismatch"};
}
using nncc::core::ADT::tensor::LexicalLayout;
using nncc::core::ADT::tensor::make_overlay;
auto base = _blobs.region(n);
auto view = make_overlay<float, LexicalLayout>(shape(n), base);
f(*this, n, view);
}
void getConstFloatTensor(uint32_t n, const TensorContext::TypedReader<float> &f) const override
{
if (!std::is_same<DType, float>::value)
{
throw std::runtime_error{"type mismatch"};
}
using nncc::core::ADT::tensor::LexicalLayout;
using nncc::core::ADT::tensor::make_overlay;
auto base = _blobs.region(n);
auto view = make_overlay<float, LexicalLayout>(shape(n), base);
f(*this, n, view);
}
private:
BlobContext<DType> &_blobs;
};
} // namespace caffe
} // namespace support
} // namespace nnkit
#endif // __NNKIT_SUPPORT_CAFFE_TENSOR_CONTEXT_H__
|
