LBANN  0.103.0
LivermoreBigArtificialNeuralNetworkToolkit
layers/image/cutout.hpp
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4 // Written by the LBANN Research Team (B. Van Essen, et al.) listed in
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7 // LLNL-CODE-697807.
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26 
27 #ifndef LBANN_LAYERS_IMAGE_CUTOUT_HPP_INCLUDED
28 #define LBANN_LAYERS_IMAGE_CUTOUT_HPP_INCLUDED
29 
31 
32 namespace lbann {
33 
39 template <typename TensorDataType, data_layout Layout, El::Device Device>
40 class cutout_layer : public data_type_layer<TensorDataType>
41 {
42  static_assert(Layout == data_layout::DATA_PARALLEL,
43  "cutout_layer only supports DATA_PARALLEL");
44  static_assert(Device == El::Device::CPU, "cutou_layer only supports CPU");
45 
46 public:
48 
51  using AbsDistMatrixType = El::AbstractDistMatrix<TensorDataType>;
52 
54 
55 public:
56  cutout_layer(lbann_comm* comm) : data_type_layer<TensorDataType>(comm)
57  {
59  }
60 
61  cutout_layer* copy() const override { return new cutout_layer(*this); }
62 
64 
66  template <typename ArchiveT>
67  void serialize(ArchiveT& ar);
68 
70 
71  std::string get_type() const override { return "cutout"; }
72  data_layout get_data_layout() const override { return Layout; }
73  El::Device get_device_allocation() const override { return Device; }
74  bool can_run_inplace() const override { return true; }
75  int get_backprop_requirements() const override { return ERROR_SIGNALS; }
76 
77  void fp_compute() override;
78 
79 protected:
80  friend class cereal::access;
81  cutout_layer() : cutout_layer(nullptr) {}
82 
83  void setup_dims() override;
84 
85  void write_specific_proto(lbann_data::Layer& proto) const final;
86 };
87 
88 #ifndef LBANN_CUTOUT_LAYER_INSTANTIATE
89 #define PROTO(T) \
90  extern template class cutout_layer<T, \
91  data_layout::DATA_PARALLEL, \
92  El::Device::CPU>
93 
95 #undef PROTO
96 #endif // LBANN_CUTOUT_LAYER_INSTANTIATE
97 
98 } // namespace lbann
99 
100 #endif // LBANN_LAYERS_IMAGE_CUTOUT_HPP_INCLUDED
data_layout get_data_layout() const override
Get data layout of the data tensors. We assume that the data layouts of the previous activations...
bool can_run_inplace() const override
If True, the computation can run in-place (feeding each input activations tensor as the corresponding...
El::AbstractDistMatrix< TensorDataType > AbsDistMatrixType
The tensor type expected in this object.
void serialize(ArchiveT &ar)
void fp_compute() override
Apply layer operation. Called by the &#39;forward_prop&#39; function. Given the input tensors, the output tensors are populated with computed values.
Cutout a square from an image.
constexpr El::Device Device
cutout_layer(lbann_comm *comm)
El::Device get_device_allocation() const override
Get the device allocation for the data tensors. We assume that the decice allocation of the previous ...
std::string get_type() const override
Get the layer type&#39;s name.
int get_backprop_requirements() const override
Returns the necessary tensors for computing backpropagation.
void write_specific_proto(lbann_data::Layer &proto) const final
Add layer specific data to prototext.
data_layout
Data layout that is optimized for different modes of parallelism.
Definition: base.hpp:218
void setup_dims() override
Setup tensor dimensions Called by the &#39;setup&#39; function. If there are any input tensors, the base method sets all uninitialized output tensor dimensions equal to the first input tensor dimensions.
int m_expected_num_parent_layers
Definition: layer.hpp:838
cutout_layer * copy() const override
Copy function. This function dynamically allocates memory for a layer instance and instantiates a cop...
friend class cereal::access