27 #ifndef LBANN_LIBRARY_HPP 28 #define LBANN_LIBRARY_HPP 49 std::vector<int> input_dims,
50 std::vector<int> output_dims);
58 template <
typename DataT,
61 El::DistWrap DistView,
63 El::Matrix<int, El::Device::CPU>
65 El::DistMatrix<DataT, CDist, RDist, DistView, Device>
const& samples,
69 return inf_alg.infer(model, samples, mbs);
77 lbann_data::Trainer* pb_trainer,
78 lbann_data::LbannPB& pb);
86 const lbann_data::Trainer* pb_trainer,
87 lbann_data::LbannPB& pb,
90 std::vector<std::shared_ptr<callback_base>>& shared_callbacks);
93 int io_threads_per_process,
94 int io_threads_offset);
98 #endif // LBANN_LIBRARY_HPP
std::unique_ptr< model > load_inference_model(lbann_comm *lc, std::string cp_dir, int mbs, std::vector< int > input_dims, std::vector< int > output_dims)
Loads a trained model from checkpoint for inference only.
constexpr El::Device Device
El::Matrix< int, El::Device::CPU > infer(observer_ptr< model > model, El::DistMatrix< DataT, CDist, RDist, DistView, Device > const &samples, size_t mbs)
Creates execution algorithm and infers on samples using a model.
const int lbann_default_random_seed
Abstract base class for neural network models.
std::unique_ptr< model > build_model_from_prototext(int argc, char **argv, const lbann_data::Trainer *pb_trainer, lbann_data::LbannPB &pb, lbann_comm *comm, thread_pool &io_thread_pool, std::vector< std::shared_ptr< callback_base >> &shared_callbacks)
typename std::add_pointer< T >::type observer_ptr
Creating an observer_ptr to complement the unique_ptr and shared_ptr.
Class for LBANN batch inference algorithms.
User-facing class that represents a set of compute resources.
std::unique_ptr< thread_pool > construct_io_thread_pool(lbann_comm *comm, bool serialized_io)
void print_lbann_configuration(lbann_comm *comm, int io_threads_per_process, int io_threads_offset)
trainer & construct_trainer(lbann_comm *comm, lbann_data::Trainer *pb_trainer, lbann_data::LbannPB &pb)
::distconv::tensor::Distribution Dist
int allocate_trainer_resources(lbann_comm *comm)