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minmax_ops.h
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minmax_ops.h
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#ifndef CAFFE2_OPERATORS_MINMAX_OPS_H_
#define CAFFE2_OPERATORS_MINMAX_OPS_H_
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/types.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T, class Context>
class MaxOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
USE_SIMPLE_CTOR_DTOR(MaxOp)
bool RunOnDevice() override {
const auto& X0 = Input(0);
auto* Y = Output(0);
Y->ResizeLike(X0);
const T* X0_data = X0.template data<T>();
T* Y_data = Y->template mutable_data<T>();
const int N = X0.numel();
if (InputSize() == 1) {
if (Y != &X0) {
context_.template CopySameDevice<T>(N, X0_data, Y_data);
}
return true;
}
const auto& X1 = Input(1);
CAFFE_ENFORCE_EQ(
X0.sizes(),
Y->sizes(),
"Description: Input #1, input dimension:",
X1.sizes(),
" should match output dimension: ",
Y->sizes());
const T* X1_data = X1.template data<T>();
math::Max<T, Context>(N, X0_data, X1_data, Y_data, &context_);
for (int i = 2; i < InputSize(); ++i) {
const auto& Xi = Input(i);
CAFFE_ENFORCE_EQ(
Xi.sizes(),
Y->sizes(),
"Description: Input #",
i,
", input dimension:",
Input(i).sizes(),
" should match output dimension: ",
Y->sizes());
const T* Xi_data = Xi.template data<T>();
math::Max<T, Context>(N, Y_data, Xi_data, Y_data, &context_);
}
return true;
}
};
template <typename T, class Context>
class MinOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
USE_SIMPLE_CTOR_DTOR(MinOp)
bool RunOnDevice() override {
const auto& X0 = Input(0);
auto* Y = Output(0);
Y->ResizeLike(X0);
const T* X0_data = X0.template data<T>();
T* Y_data = Y->template mutable_data<T>();
const int N = X0.numel();
if (InputSize() == 1) {
if (Y != &X0) {
context_.template CopySameDevice<T>(N, X0_data, Y_data);
}
return true;
}
const auto& X1 = Input(1);
CAFFE_ENFORCE_EQ(
X0.sizes(),
Y->sizes(),
"Description: Input #1, input dimension:",
X1.sizes(),
" should match output dimension: ",
Y->sizes());
const T* X1_data = X1.template data<T>();
math::Min<T, Context>(N, X0_data, X1_data, Y_data, &context_);
for (int i = 2; i < InputSize(); ++i) {
const auto& Xi = Input(i);
CAFFE_ENFORCE_EQ(
Xi.sizes(),
Y->sizes(),
"Description: Input #",
i,
", input dimension:",
Input(i).sizes(),
" should match output dimension: ",
Y->sizes());
const T* Xi_data = Xi.template data<T>();
math::Min<T, Context>(N, Y_data, Xi_data, Y_data, &context_);
}
return true;
}
};
template <typename T, class Context>
class SelectGradientOpBase : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
USE_SIMPLE_CTOR_DTOR(SelectGradientOpBase)
bool RunOnDevice() override;
};
template <typename T, class Context>
class MaxGradientOp final : public SelectGradientOpBase<T, Context> {
public:
template <class... Args>
explicit MaxGradientOp(Args&&... args)
: SelectGradientOpBase<T, Context>(std::forward<Args>(args)...) {}
~MaxGradientOp() = default;
};
template <typename T, class Context>
class MinGradientOp final : public SelectGradientOpBase<T, Context> {
public:
template <class... Args>
explicit MinGradientOp(Args&&... args)
: SelectGradientOpBase<T, Context>(std::forward<Args>(args)...) {}
~MinGradientOp() = default;
};
} // namespace caffe2
#endif // CAFFE2_OPERATORS_MINMAX_OPS_H_