LogspaceBatchTensor.cxx

// Copyright 2023, UChicago Argonne, LLC
// All Rights Reserved
// Software Name: NEML2 -- the New Engineering material Model Library, version 2
// By: Argonne National Laboratory
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#include "neml2/tensors/user_tensors/LogspaceBatchTensor.h"
#include "neml2/base/CrossRef.h"
 
namespace neml2
{
register_NEML2_object(LogspaceBatchTensor);
 
OptionSet
LogspaceBatchTensor::expected_options()
{
  OptionSet options = UserTensor::expected_options();
  options.doc() = "Construct a BatchTensor with exponents linearly spaced on the batch dimensions. "
                  "See neml2::BatchTensorBase::logspace for a detailed explanation.";
 
  options.set<CrossRef<BatchTensor>>("start");
  options.set("start").doc() = "The starting tensor";
 
  options.set<CrossRef<BatchTensor>>("end");
  options.set("end").doc() = "The ending tensor";
 
  options.set<TorchSize>("nstep");
  options.set("nstep").doc() = "The number of steps with even spacing along the new dimension";
 
  options.set<TorchSize>("dim") = 0;
  options.set("dim").doc() = "Where to insert the new dimension";
 
  options.set<TorchSize>("batch_dim") = -1;
  options.set("batch_dim").doc() = "Batch dimension of the output";
 
  options.set<Real>("base") = 10;
  options.set("base").doc() = "Exponent base";
 
  return options;
}
 
LogspaceBatchTensor::LogspaceBatchTensor(const OptionSet & options)
  : BatchTensor(BatchTensor::logspace(options.get<CrossRef<BatchTensor>>("start"),
                                      options.get<CrossRef<BatchTensor>>("end"),
                                      options.get<TorchSize>("nstep"),
                                      options.get<TorchSize>("dim"),
                                      options.get<TorchSize>("batch_dim"),
                                      options.get<Real>("base"))),
    UserTensor(options)
{
}
} // namespace neml2