mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
* Update elementwise ops to support numpy style boradcast Update elementwise ops to support numpy style boradcast * Fix sqrt_op * Fix compare ops * Fix gradient test * Fix optimizer legacy broadcast * Fix legacy broadcast for elementwise ops * Skip flaky test * Fix eigen simple binary op * Fix attention test * Fix rnn test * Fix LSTM test * Fix tan grad * Fix schema check
36 lines
772 B
C++
36 lines
772 B
C++
#ifndef CAFFE2_OPERATORS_SWISH_OP_H_
|
|
#define CAFFE2_OPERATORS_SWISH_OP_H_
|
|
|
|
#include "caffe2/operators/elementwise_ops.h"
|
|
#include "caffe2/utils/math.h"
|
|
|
|
namespace caffe2 {
|
|
|
|
template <class Context>
|
|
struct SwishFunctor {
|
|
template <typename T>
|
|
bool operator()(const int N, const T* X, T* Y, Context* context) const;
|
|
};
|
|
|
|
template <class Context>
|
|
class SwishGradientOp final : public Operator<Context> {
|
|
public:
|
|
USE_SIMPLE_CTOR_DTOR(SwishGradientOp)
|
|
USE_OPERATOR_CONTEXT_FUNCTIONS;
|
|
|
|
template <typename T>
|
|
bool DoRunWithType();
|
|
|
|
bool RunOnDevice() override {
|
|
return DispatchHelper<TensorTypes<float, double>>::call(this, Input(X));
|
|
}
|
|
|
|
protected:
|
|
INPUT_TAGS(X, Y, DY);
|
|
OUTPUT_TAGS(DX);
|
|
};
|
|
|
|
} // namespace caffe2
|
|
|
|
#endif // CAFFE2_OPERATORS_SWISH_OP_H_
|