27 #ifndef LBANN_LAYERS_MISC_MINI_BATCH_INDEX_HPP_INCLUDED 28 #define LBANN_LAYERS_MISC_MINI_BATCH_INDEX_HPP_INCLUDED 40 template <
typename TensorDataType,
53 template <
typename ArchiveT>
58 std::string
get_type()
const override;
75 #ifndef LBANN_MINI_BATCH_INDEX_LAYER_INSTANTIATE 76 #define PROTO_DEVICE(T, Device) \ 77 extern template class mini_batch_index_layer<T, \ 78 data_layout::DATA_PARALLEL, \ 80 extern template class mini_batch_index_layer<T, \ 81 data_layout::MODEL_PARALLEL, \ 86 #endif // LBANN_MINI_BATCH_INDEX_LAYER_INSTANTIATE 90 #endif // LBANN_LAYERS_MISC_MINI_BATCH_INDEX_HPP_INCLUDED
std::string get_type() const override
Get the layer type's name.
constexpr El::Device Device
void fp_compute() override
Apply layer operation. Called by the 'forward_prop' function. Given the input tensors, the output tensors are populated with computed values.
void setup_dims() override
Setup tensor dimensions Called by the 'setup' function. If there are any input tensors, the base method sets all uninitialized output tensor dimensions equal to the first input tensor dimensions.
int get_backprop_requirements() const override
Returns the necessary tensors for computing backpropagation.
void serialize(ArchiveT &ar)
void write_specific_proto(lbann_data::Layer &proto) const final
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...
data_layout
Data layout that is optimized for different modes of parallelism.
El::Device get_device_allocation() const override
Get the device allocation for the data tensors. We assume that the decice allocation of the previous ...
friend class cereal::access
mini_batch_index_layer * copy() const override
Copy function. This function dynamically allocates memory for a layer instance and instantiates a cop...