#ifndef CAFFE2_OPERATORS_ROW_MUL_H_
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#define CAFFE2_OPERATORS_ROW_MUL_H_
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#include "caffe2/core/context.h"
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#include "caffe2/core/logging.h"
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#include "caffe2/core/operator.h"
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#include "caffe2/utils/math.h"
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namespace caffe2 {
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// A hacky version of Mul with broadcast
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// RowMul([mat, w], [output])
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template <typename T, class Context>
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class RowMulOp : public Operator<Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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USE_SIMPLE_CTOR_DTOR(RowMulOp);
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bool RunOnDevice() override {
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auto& mat = Input(0);
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auto& w = Input(1);
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auto* output = Output(0, mat.sizes(), at::dtype<T>());
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T* output_data = output->template mutable_data<T>();
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const T* mat_data = mat.template data<T>();
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const T* w_data = w.template data<T>();
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// Dimension checking
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CAFFE_ENFORCE_EQ(
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w.numel(),
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mat.dim32(0),
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"Length of w should be equal to the first dim of mat");
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auto block_size = mat.size_from_dim(1);
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for (int i = 0; i < w.numel(); i++) {
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size_t offset = i * block_size;
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for (int j = 0; j < block_size; j++) {
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output_data[offset + j] = mat_data[offset + j] * w_data[i];
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}
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}
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return true;
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}
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};
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// A hacky version
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template <typename T, class Context>
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class ReduceTailSumOp : public Operator<Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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USE_SIMPLE_CTOR_DTOR(ReduceTailSumOp);
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bool RunOnDevice() override {
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auto& mat = Input(0);
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int N = mat.dim32(0);
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int block_size = mat.size_from_dim(1);
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auto* output = Output(0, {N}, at::dtype<T>());
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T* output_data = output->template mutable_data<T>();
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const T* mat_data = mat.template data<T>();
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for (int i = 0; i < N; i++) {
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output_data[i] = 0;
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size_t offset = i * block_size;
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for (int j = 0; j < block_size; j++) {
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output_data[i] += mat_data[offset + j];
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}
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}
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return true;
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}
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};
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} // namespace caffe2
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#endif // CAFFE2_OPERATORS_ROW_MUL_H_
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