// Copyright 2004-present Facebook. All Rights Reserved.
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#pragma once
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#include <unordered_map>
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#include <unordered_set>
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#include "caffe2/core/context.h"
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#include "caffe2/core/operator.h"
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#include "caffe2/utils/eigen_utils.h"
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namespace caffe2 {
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template <class Context>
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class CopyRowsToTensorOp : public Operator<Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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CopyRowsToTensorOp(const OperatorDef& operator_def, Workspace* ws)
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: Operator<Context>(operator_def, ws) {}
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bool RunOnDevice() override {
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return DispatchHelper<
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TensorTypes<at::Half, float, double, int32_t, int64_t>>::
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call(this, Input(INPUT_TENSOR));
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}
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template <typename T>
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bool DoRunWithType() {
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auto& input_tensor = Input(INPUT_TENSOR);
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auto& indices = Input(INDICES);
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auto& row = Input(ROW);
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auto tensor_width = input_tensor.size(1);
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CAFFE_ENFORCE_EQ(input_tensor.dim(), 2, "INPUT_TENSOR should be 2-d");
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CAFFE_ENFORCE_EQ(indices.dim(), 1, "INDICES should be 1-d");
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CAFFE_ENFORCE_EQ(row.dim(), 1, "ROW should be 1-d");
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CAFFE_ENFORCE_EQ(
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tensor_width,
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row.size(0),
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"width of input tensor should match lengths of row");
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const auto* indices_data = indices.template data<int64_t>();
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const auto* row_data = row.template data<T>();
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auto* output = Output(0);
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auto* output_data = output->template mutable_data<T>();
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CAFFE_ENFORCE(
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IsInputOutputAlias(0, 0), "Input 0 and Output 0 should be alias.");
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for (size_t i = 0; i < indices.sizes()[0]; ++i) {
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std::memcpy(
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output_data + indices_data[i] * tensor_width,
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row_data,
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tensor_width * sizeof(T));
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}
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return true;
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}
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protected:
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INPUT_TAGS(INPUT_TENSOR, INDICES, ROW);
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};
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template <class Context>
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class CopyRowsToTensorGradientOp : public Operator<Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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CopyRowsToTensorGradientOp(const OperatorDef& operator_def, Workspace* ws)
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: Operator<Context>(operator_def, ws) {}
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bool RunOnDevice() override {
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return DispatchHelper<
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TensorTypes<at::Half, float, double, int32_t, int64_t>>::
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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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auto* output = Output(0);
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output->ResizeLike(Input(0));
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auto* output_data = output->template mutable_data<T>();
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auto& input = Input(0);
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const auto* input_data = input.template data<T>();
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std::memcpy(output_data, input_data, input.size(0) * sizeof(T));
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return true;
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}
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};
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} // namespace caffe2
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