tensor_adapter.h

// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#pragma once

#include <algorithm>
#include <vector>

namespace aby3 {

template <typename T>
class TensorAdapter {
public:

    TensorAdapter() = default;

    virtual ~TensorAdapter() = default;

    virtual T* data() = 0;

    virtual const T* data() const = 0;

    virtual std::vector<size_t> shape() const = 0;

    virtual void reshape(const std::vector<size_t>& shape) = 0;

    virtual size_t numel() const = 0;

    virtual void copy(TensorAdapter* ret) const {
        // TODO: check shape equals
        std::copy(data(), data() + numel(), ret->data());
    }

    // element wise op, need operands' dim are same
    virtual void add(const TensorAdapter* rhs, TensorAdapter* ret) const = 0;

    // element wise op, need operands' dim are same
    virtual void sub(const TensorAdapter* rhs, TensorAdapter* ret) const = 0;

    virtual void negative(TensorAdapter* ret) const = 0;

    // element wise op, need operands' dim are same
    virtual void mul(const TensorAdapter* rhs, TensorAdapter* ret) const = 0;

    // element wise op, need operands' dim are same
    virtual void div(const TensorAdapter* rhs, TensorAdapter* ret) const = 0;

    // 2d matrix muliply,  need operands' rank are 2
    virtual void mat_mul(const TensorAdapter* rhs, TensorAdapter* ret) const = 0;

    // element wise op, need operands' dim are same
    virtual void bitwise_xor(const TensorAdapter* rhs, TensorAdapter* ret) const = 0;

    // element wise op, need operands' dim are same
    virtual void bitwise_and(const TensorAdapter* rhs, TensorAdapter* ret) const = 0;

    // element wise op, need operands' dim are same
    virtual void bitwise_or(const TensorAdapter* rhs, TensorAdapter* ret) const = 0;

    // element wise op, need operands' dim are same
    virtual void bitwise_not(TensorAdapter* ret) const = 0;

    virtual void lshift(size_t rhs, TensorAdapter* ret) const = 0;

    virtual void rshift(size_t rhs, TensorAdapter* ret) const = 0;

    virtual void logical_rshift(size_t rhs, TensorAdapter* ret) const = 0;

    // when using an integer type T as fixed-point number
    // value of T val is interpreted as val / 2 ^ scaling_factor()
    virtual size_t scaling_factor() const = 0;

    virtual size_t& scaling_factor() = 0;

    // slice by shape[0]
    // e.g. x.shape = [ 2, 3, 4]
    //      x.slice(1, 2, y)
    //      y.shape = [ 1, 3, 4]
    virtual void slice(size_t begin_idx, size_t end_idx, TensorAdapter* out) const = 0;
};

template<typename T>
inline void assign_to_tensor(TensorAdapter<T>* input, T assign_num) {
    std::transform(input->data(), input->data() + input->numel(),
                   input->data(), [assign_num](T) { return assign_num; });
}

} // namespace aby3