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0b9d537056
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38514 this diff introduces the `Histogram` caffe2 op, which computes a histogram tensor for a list of input tensors. the bin edges of the histogram are defined by arg `bin_edges`. Test Plan: tests Reviewed By: chocjy Differential Revision: D21553956 fbshipit-source-id: fc98c8db691d66d2dad57b6ad14867109913cb6f
83 lines
2.3 KiB
C++
83 lines
2.3 KiB
C++
#pragma once
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#include <cmath>
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#include <limits>
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#include "caffe2/core/operator.h"
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namespace caffe2 {
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template <class Context>
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class HistogramOp final : public Operator<Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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template <class... Args>
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explicit HistogramOp(Args&&... args)
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: Operator<Context>(std::forward<Args>(args)...),
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bin_edges_(this->template GetRepeatedArgument<float>("bin_edges")) {
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CAFFE_ENFORCE_GE(
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bin_edges_.size(),
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2,
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"Number of bin edges must be greater than or equal to 2.");
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for (int i = 1; i < bin_edges_.size(); i++) {
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CAFFE_ENFORCE_GT(
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bin_edges_[i],
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bin_edges_[i - 1],
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"bin_edges must be a strictly increasing sequence of values.");
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}
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}
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bool RunOnDevice() override {
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return DispatchHelper<TensorTypes<float, double>>::call(this, Input(0));
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}
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template <typename T>
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bool DoRunWithType() {
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CheckInputs();
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const auto* histogram = Output(HISTOGRAM);
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histogram->Resize(bin_edges_.size() - 1);
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auto* histogram_data = histogram->template mutable_data<int64_t>();
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math::Set<int64_t, Context>(
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bin_edges_.size() - 1, 0, histogram_data, &context_);
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for (int input_idx = 0; input_idx < InputSize(); input_idx++) {
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const auto& x = Input(input_idx);
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const int64_t N = x.numel();
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const auto* x_data = x.template data<T>();
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for (int64_t data_idx = 0; data_idx < N; data_idx++) {
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const auto bisection_it = std::upper_bound(
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bin_edges_.begin(), bin_edges_.end(), x_data[data_idx]);
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const int bisection_idx = bisection_it - bin_edges_.begin();
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if (bisection_idx > 0 && bisection_idx < bin_edges_.size()) {
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histogram_data[bisection_idx - 1]++;
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}
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}
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}
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return true;
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}
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protected:
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OUTPUT_TAGS(HISTOGRAM);
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private:
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vector<float> bin_edges_;
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void CheckInputs() {
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const auto& input_zero = Input(0);
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for (int i = 1; i < InputSize(); i++) {
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CAFFE_ENFORCE_EQ(
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Input(i).dtype(),
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input_zero.dtype(),
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"All inputs must have the same type; expected ",
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input_zero.dtype().name(),
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" but got ",
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Input(i).dtype().name(),
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" for input ",
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i);
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}
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}
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};
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} // namespace caffe2
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