LBANN  0.103.0
LivermoreBigArtificialNeuralNetworkToolkit
categorical_accuracy_impl.hpp
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1 // Copyright (c) 2014-2023, Lawrence Livermore National Security, LLC.
3 // Produced at the Lawrence Livermore National Laboratory.
4 // Written by the LBANN Research Team (B. Van Essen, et al.) listed in
5 // the CONTRIBUTORS file. <lbann-dev@llnl.gov>
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7 // LLNL-CODE-697807.
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11 // Toolkit. For details, see http://software.llnl.gov/LBANN or
12 // https://github.com/LLNL/LBANN.
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26 
27 #ifndef LBANN_LAYERS_LOSS_CATEGORICAL_ACCURACY_IMPL_HPP_INCLUDED
28 #define LBANN_LAYERS_LOSS_CATEGORICAL_ACCURACY_IMPL_HPP_INCLUDED
29 
32 
33 namespace lbann {
34 
35 template <typename TensorDataType, data_layout T_layout, El::Device Dev>
37 {
39  this->set_output_dims({1});
40 
41  // Check that input dimensions match
42  if (this->get_input_dims(0) != this->get_input_dims(1)) {
43  const auto& parents = this->get_parent_layers();
44  std::stringstream err;
45  err << get_type() << " layer \"" << this->get_name() << "\" "
46  << "has input tensors with different dimensions (";
47  for (int i = 0; i < this->get_num_parents(); ++i) {
48  const auto& dims = this->get_input_dims(i);
49  err << (i > 0 ? ", " : "") << "layer \"" << parents[i]->get_name()
50  << "\" outputs ";
51  for (size_t j = 0; j < dims.size(); ++j) {
52  err << (j > 0 ? " x " : "") << dims[j];
53  }
54  }
55  err << ")";
56  LBANN_ERROR(err.str());
57  }
58 }
59 
60 } // namespace lbann
61 
62 #endif // LBANN_LAYERS_LOSS_CATEGORICAL_ACCURACY_IMPL_HPP_INCLUDED
virtual void setup_dims()
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.
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.
#define LBANN_ERROR(...)
Definition: exception.hpp:37