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#pragma once
#include <cmath>
#include <limits>
#include "caffe2/core/operator.h"
namespace caffe2 {
template <class Context>
class HistogramOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit HistogramOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...),
bin_edges_(this->template GetRepeatedArgument<float>("bin_edges")) {
CAFFE_ENFORCE_GE(
bin_edges_.size(),
2,
"Number of bin edges must be greater than or equal to 2.");
for (int i = 1; i < bin_edges_.size(); i++) {
CAFFE_ENFORCE_GT(
bin_edges_[i],
bin_edges_[i - 1],
"bin_edges must be a strictly increasing sequence of values.");
}
}
bool RunOnDevice() override {
return DispatchHelper<TensorTypes<float, double>>::call(this, Input(0));
}
template <typename T>
bool DoRunWithType() {
CheckInputs();
const auto* histogram = Output(HISTOGRAM);
histogram->Resize(bin_edges_.size() - 1);
auto* histogram_data = histogram->template mutable_data<int64_t>();
math::Set<int64_t, Context>(
bin_edges_.size() - 1, 0, histogram_data, &context_);
for (int input_idx = 0; input_idx < InputSize(); input_idx++) {
const auto& x = Input(input_idx);
const int64_t N = x.numel();
const auto* x_data = x.template data<T>();
for (int64_t data_idx = 0; data_idx < N; data_idx++) {
const auto bisection_it = std::upper_bound(
bin_edges_.begin(), bin_edges_.end(), x_data[data_idx]);
const int bisection_idx = bisection_it - bin_edges_.begin();
if (bisection_idx > 0 && bisection_idx < bin_edges_.size()) {
histogram_data[bisection_idx - 1]++;
}
}
}
return true;
}
protected:
OUTPUT_TAGS(HISTOGRAM);
private:
vector<float> bin_edges_;
void CheckInputs() {
const auto& input_zero = Input(0);
for (int i = 1; i < InputSize(); i++) {
CAFFE_ENFORCE_EQ(
Input(i).dtype(),
input_zero.dtype(),
"All inputs must have the same type; expected ",
input_zero.dtype().name(),
" but got ",
Input(i).dtype().name(),
" for input ",
i);
}
}
};
} // namespace caffe2
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