bug fixed logs print copy

zhangmeng

2020-01-17 f7c4a3cfd07adede3308f8d9d3d7315427d90a7c

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
#ifndef CAFFE2_OPERATORS_LOCALLY_CONNECTED_OP_H_
#define CAFFE2_OPERATORS_LOCALLY_CONNECTED_OP_H_
 
#include <vector>
 
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/operators/conv_op_shared.h"
#include "caffe2/operators/conv_pool_op_base.h"
#include "caffe2/operators/locally_connected_op_util.h"
 
namespace caffe2 {
 
template <typename T, class Context>
class LocallyConnectedOp final : public ConvPoolOpBase<Context> {
 public:
  USE_CONV_POOL_BASE_FUNCTIONS(Context);
 
  template <class... Args>
  explicit LocallyConnectedOp(Args&&... args)
      : ConvPoolOpBase<Context>(std::forward<Args>(args)...) {
    // Since this is the default locally connected implementation, we will
    // use CAFFE_ENFORCE instead of OPERATOR_NEEDS_FEATURE.
    CAFFE_ENFORCE(
        group_ == 1 || order_ == StorageOrder::NCHW,
        "Group locally connected only supports NCHW order right now.");
  }
 
  ~LocallyConnectedOp() = default;
 
  bool RunOnDeviceWithOrderNCHW() override;
  bool RunOnDeviceWithOrderNHWC() override;
 
 private:
  void RunOnDeviceWithOrderNCHWImpl(
      const lc_op_util::ShapeParams& shape,
      const T* X_data,
      const T* filter_data,
      const T* bias_data,
      T* Y_data,
      Tensor* column_buffer,
      Tensor* column_transposed_buffer,
      Tensor* output_buffer);
 
  void RunOnDeviceWithOrderNHWCImpl(
      const lc_op_util::ShapeParams& shape,
      const T* X_data,
      const T* filter_data,
      const T* bias_data,
      T* Y_data,
      Tensor* column_buffer,
      Tensor* column_transposed_buffer,
      Tensor* Y_transposed_buffer);
 
  Tensor bias_multiplier_{Context::GetDeviceType()};
 
  // Buffer.
  Tensor column_buffer_{Context::GetDeviceType()};
  Tensor column_transposed_buffer_{Context::GetDeviceType()};
  Tensor Y_transposed_buffer_{Context::GetDeviceType()};
 
  // Input: X, W, b
  // Output: Y
  INPUT_TAGS(INPUT, FILTER, BIAS);
};
 
template <typename T, class Context>
class LocallyConnectedGradientOp final : public ConvPoolOpBase<Context> {
 public:
  USE_CONV_POOL_BASE_FUNCTIONS(Context);
 
  template <class... Args>
  explicit LocallyConnectedGradientOp(Args&&... args)
      : ConvPoolOpBase<Context>(std::forward<Args>(args)...),
        OP_SINGLE_ARG(bool, "no_bias", no_bias_, false) {
    CAFFE_ENFORCE(
        !(no_bias_ && OutputSize() == 3),
        "If bias is not present, you should not have 3 grad output.");
    CAFFE_ENFORCE(
        group_ == 1 || order_ == StorageOrder::NCHW,
        "Group locally connected only supports NCHW order right now.");
  }
 
  ~LocallyConnectedGradientOp() = default;
 
  bool RunOnDeviceWithOrderNCHW() override;
  bool RunOnDeviceWithOrderNHWC() override;
 
 private:
  void RunOnDeviceWithOrderNCHWImpl(
      const lc_op_util::ShapeParams& shape,
      const T* X_data,
      const T* filter_data,
      const T* dY_data,
      T* dfilter_data,
      T* dX_data,
      T* dbias_data,
      Tensor* column_buffer,
      Tensor* column_transposed_buffer,
      Tensor* dY_transposed_buffer);
 
  void RunOnDeviceWithOrderNHWCImpl(
      const lc_op_util::ShapeParams& shape,
      const T* X_data,
      const T* filter_data,
      const T* dY_data,
      T* dfilter_data,
      T* dX_data,
      T* dbias_data,
      Tensor* column_buffer,
      Tensor* column_transposed_buffer,
      Tensor* dY_transposed_buffer);
 
  const bool no_bias_;
 
  Tensor bias_multiplier_{Context::GetDeviceType()};
 
  // Buffer.
  Tensor column_buffer_{Context::GetDeviceType()};
  Tensor column_transposed_buffer_{Context::GetDeviceType()};
  Tensor dY_transposed_buffer_{Context::GetDeviceType()};
 
  // input: X, W, dY
  // output: dW, db, and optionally dX
  INPUT_TAGS(INPUT, FILTER, OUTPUT_GRAD);
  OUTPUT_TAGS(FILTER_GRAD, BIAS_OR_INPUT_GRAD, INPUT_GRAD);
};
 
} // namespace caffe2
 
#endif // CAFFE2_OPERATORS_LOCALLY_CONNECTED_OP_H_