LBANN  0.103.0
LivermoreBigArtificialNeuralNetworkToolkit
batchwise_reduce_sum.hpp
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26 
27 #ifndef LBANN_LAYERS_TRANSFORM_BATCHWISE_REDUCE_SUM_HPP_INCLUDED
28 #define LBANN_LAYERS_TRANSFORM_BATCHWISE_REDUCE_SUM_HPP_INCLUDED
29 
31 
32 namespace lbann {
33 
38 template <typename TensorDataType,
40  El::Device Device = El::Device::CPU>
41 class batchwise_reduce_sum_layer : public data_type_layer<TensorDataType>
42 {
43 public:
47  operator=(const batchwise_reduce_sum_layer& other) = default;
48 
49  batchwise_reduce_sum_layer* copy() const override;
50 
52 
54  template <typename ArchiveT>
55  void serialize(ArchiveT& ar);
56 
58 
59  std::string get_type() const override;
60  data_layout get_data_layout() const override;
61  El::Device get_device_allocation() const override;
62  bool can_run_inplace() const override { return false; }
63  int get_backprop_requirements() const override { return ERROR_SIGNALS; }
64 
65 protected:
67  void write_specific_proto(lbann_data::Layer& proto) const final;
68 
69  void setup_dims() override;
70 
71  void fp_compute() override;
72  void bp_compute() override;
73 };
74 
75 #ifndef LBANN_BATCHWISE_REDUCE_SUM_LAYER_INSTANTIATE
76 #define PROTO_DEVICE(T, Device) \
77  extern template class batchwise_reduce_sum_layer<T, \
78  data_layout::DATA_PARALLEL, \
79  Device>; \
80  extern template class batchwise_reduce_sum_layer< \
81  T, \
82  data_layout::MODEL_PARALLEL, \
83  Device>;
85 #undef PROTO_DEVICE
86 #endif // LBANN_BATCHWISE_REDUCE_SUM_LAYER_INSTANTIATE
87 
88 } // namespace lbann
89 
90 #endif // LBANN_LAYERS_TRANSFORM_BATCHWISE_REDUCE_SUM_HPP_INCLUDED
void write_specific_proto(lbann_data::Layer &proto) const final
batchwise_reduce_sum_layer * copy() const override
Copy function. This function dynamically allocates memory for a layer instance and instantiates a cop...
data_layout get_data_layout() const override
Get data layout of the data tensors. We assume that the data layouts of the previous activations...
constexpr El::Device Device
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.
int get_backprop_requirements() const override
Returns the necessary tensors for computing backpropagation.
std::string get_type() const override
Get the layer type&#39;s name.
data_layout
Data layout that is optimized for different modes of parallelism.
Definition: base.hpp:218
El::Device get_device_allocation() const override
Get the device allocation for the data tensors. We assume that the decice allocation of the previous ...
Sum of tensor entries along batch dimension.
bool can_run_inplace() const override
If True, the computation can run in-place (feeding each input activations tensor as the corresponding...
void bp_compute() override
Compute objective funciton gradients. Called by the &#39;back_prop&#39; function. Given the input...
batchwise_reduce_sum_layer & operator=(const batchwise_reduce_sum_layer &other)=default
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.