#ifndef CAFFE2_OPERATORS_FIND_OP_H_
#define CAFFE2_OPERATORS_FIND_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include <unordered_map>
namespace caffe2 {
template <class Context>
class FindOp final : public Operator<Context> {
public:
template <class... Args>
explicit FindOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...),
missing_value_(
this->template GetSingleArgument<int>("missing_value", -1)) {}
USE_OPERATOR_CONTEXT_FUNCTIONS;
USE_DISPATCH_HELPER;
bool RunOnDevice() {
return DispatchHelper<TensorTypes<int, long>>::call(this, Input(0));
}
protected:
template <typename T>
bool DoRunWithType() {
auto& idx = Input(0);
auto& needles = Input(1);
auto* res_indices = Output(0, needles.sizes(), at::dtype<T>());
const T* idx_data = idx.template data<T>();
const T* needles_data = needles.template data<T>();
T* res_data = res_indices->template mutable_data<T>();
auto idx_size = idx.numel();
// Use an arbitrary cut-off for when to use brute-force
// search. For larger needle sizes we first put the
// index into a map
if (needles.numel() < 16) {
// Brute force O(nm)
for (int i = 0; i < needles.numel(); i++) {
T x = needles_data[i];
T res = static_cast<T>(missing_value_);
for (int j = idx_size - 1; j >= 0; j--) {
if (idx_data[j] == x) {
res = j;
break;
}
}
res_data[i] = res;
}
} else {
// O(n + m)
std::unordered_map<T, int> idx_map;
for (int j = 0; j < idx_size; j++) {
idx_map[idx_data[j]] = j;
}
for (int i = 0; i < needles.numel(); i++) {
T x = needles_data[i];
auto it = idx_map.find(x);
res_data[i] = (it == idx_map.end() ? missing_value_ : it->second);
}
}
return true;
}
protected:
int missing_value_;
};
} // namespace caffe2
#endif // CAFFE2_OPERATORS_FIND_OP_H_