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
|
#ifndef CAFFE2_OPERATORS_AFFINE_CHANNEL_OP_H_
#define CAFFE2_OPERATORS_AFFINE_CHANNEL_OP_H_
#include <string>
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T, class Context>
class AffineChannelOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit AffineChannelOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...),
order_(StringToStorageOrder(
this->template GetSingleArgument<std::string>("order", "NCHW"))),
OP_SINGLE_ARG(bool, "is_learnable", is_learnable_, false) {
CAFFE_ENFORCE_NE(order_, StorageOrder::UNKNOWN);
}
bool RunOnDevice() override {
return order_ == StorageOrder::NCHW ? RunOnDeviceWithOrderNCHW()
: RunOnDeviceWithOrderNHWC();
}
bool RunOnDeviceWithOrderNCHW() {
const auto& X = Input(0);
const auto& scale = Input(1);
const auto& bias = Input(2);
if (is_learnable_) {
CAFFE_ENFORCE(
!IsInputOutputAlias(0, 0),
"In-place affine_channel_op is not supported when "
"is_learnable = true.");
}
const int N = X.dim32(0);
const int C = X.dim32(1);
const int HxW = X.numel() / (N * C);
auto* Y = Output(0, X.sizes(), at::dtype<T>());
math::AffineChannel<T, Context, StorageOrder::NCHW>(
N,
C,
HxW,
X.template data<T>(),
scale.template data<T>(),
bias.template data<T>(),
Y->template mutable_data<T>(),
&context_);
return true;
}
bool RunOnDeviceWithOrderNHWC() {
const auto& X = Input(0);
const auto& scale = Input(1);
const auto& bias = Input(2);
if (is_learnable_) {
CAFFE_ENFORCE(
!IsInputOutputAlias(0, 0),
"In-place affine_channel_op is not supported when "
"is_learnable = true.");
}
const int ndim = X.dim();
const int N = X.dim32(0);
const int C = X.dim32(ndim - 1);
const int HxW = X.numel() / (N * C);
auto* Y = Output(0, X.sizes(), at::dtype<T>());
math::AffineChannel<T, Context, StorageOrder::NHWC>(
N,
C,
HxW,
X.template data<T>(),
scale.template data<T>(),
bias.template data<T>(),
Y->template mutable_data<T>(),
&context_);
return true;
}
private:
const StorageOrder order_;
const bool is_learnable_;
};
template <typename T, class Context>
class AffineChannelGradientOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit AffineChannelGradientOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...),
order_(StringToStorageOrder(
this->template GetSingleArgument<std::string>("order", "NCHW"))),
OP_SINGLE_ARG(bool, "is_learnable", is_learnable_, false) {
CAFFE_ENFORCE_NE(order_, StorageOrder::UNKNOWN);
}
bool RunOnDevice() override {
return order_ == StorageOrder::NCHW ? RunOnDeviceWithOrderNCHW()
: RunOnDeviceWithOrderNHWC();
}
bool RunOnDeviceWithOrderNCHW();
bool RunOnDeviceWithOrderNHWC();
private:
const StorageOrder order_;
const bool is_learnable_;
};
} // namespace caffe2
#endif // CAFFE2_OPERATORS_AFFINE_CHANNEL_OP_H_
|
