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#ifndef CAFFE2_OPERATORS_FIND_DUPLICATE_ELEMENTS_OP_H
#define CAFFE2_OPERATORS_FIND_DUPLICATE_ELEMENTS_OP_H
#include <unordered_map>
#include <vector>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor.h"
namespace caffe2 {
template <class Context>
class FindDuplicateElementsOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
USE_SIMPLE_CTOR_DTOR(FindDuplicateElementsOp);
USE_DISPATCH_HELPER;
bool RunOnDevice() override {
return DispatchHelper<TensorTypes<float, double, int, long, std::string>>::
call(this, Input(0));
}
template <typename T>
bool DoRunWithType() {
const auto& data = Input(0);
CAFFE_ENFORCE(data.dim() == 1, "data should be 1-D.");
const auto* data_ptr = data.template data<T>();
std::unordered_map<T, int64_t> dict;
std::vector<int64_t> dupIndices;
// i is the index of unique elements, j is the index of all elements
for (int64_t i = 0, j = 0; j < data.sizes()[0]; ++i, ++j) {
bool retVal = dict.insert({data_ptr[j], i}).second;
if (!retVal) {
--i;
dupIndices.push_back(j);
}
}
const auto dupSize = dupIndices.size();
auto* output =
Output(0, {static_cast<int64_t>(dupSize)}, at::dtype<int64_t>());
auto* out_ptr = output->template mutable_data<int64_t>();
for (size_t i = 0; i < dupSize; ++i) {
out_ptr[i] = dupIndices[i];
}
return true;
}
};
} // namespace caffe2
#endif // CAFFE2_OPERATORS_FIND_DUPLICATE_ELEMENTS_OP_H
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