MegEngine/dnn/src/common/images2neibs.cpp

/**
 * \file dnn/src/common/images2neibs.cpp
 * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
 *
 * Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or
 * implied.
 */
#include "megdnn/oprs.h"

#include "src/common/utils.h"

namespace megdnn {

void Images2NeibsBase::deduce_layout_fwd(const TensorLayout& src, TensorLayout& dst) {
    auto errmsg = [&]() {
        return megdnn_layout_msg(src) + ", " +
               "pad_h=" + std::to_string(param().pad_h) + ", " +
               "pad_w=" + std::to_string(param().pad_w) + ", " +
               "stride_h=" + std::to_string(param().stride_h) + ", " +
               "stride_w=" + std::to_string(param().stride_w) + ", " +
               "dilate_h=" + std::to_string(param().dilate_h) + ", " +
               "dilate_w=" + std::to_string(param().dilate_w) + ", " +
               "window_h=" + std::to_string(param().window_h) + ", " +
               "window_w=" + std::to_string(param().window_w);
    };
    MEGDNN_MARK_USED_VAR(errmsg);
    megdnn_assert_contiguous(src);
    megdnn_assert(src.ndim == 4_z || src.ndim == 5_z, "%s", errmsg().c_str());

    if (src.ndim == 4_z) {
        size_t n = src[0], ic = src[1], ih = src[2], iw = src[3];
        size_t ph = this->param().pad_h;
        size_t pw = this->param().pad_w;
        size_t sh = this->param().stride_h;
        size_t sw = this->param().stride_w;
        size_t dh = this->param().dilate_h;
        size_t dw = this->param().dilate_w;
        size_t wh = this->param().window_h;
        size_t ww = this->param().window_w;
        size_t oh, ow;
        infer_conv_shape2d(
                ih, iw, wh + (wh - 1) * (dh - 1), ww + (ww - 1) * (dw - 1), sh, sw, ph,
                pw, oh, ow);
        dst = TensorLayout(TensorShape({n, ic, oh, ow, wh, ww}), src.dtype, src.format);
    } else if (src.ndim == 5_z) {
        size_t n = src[0], ih = src[1], iw = src[3], ic = src[2];
        size_t ph = this->param().pad_h;
        size_t pw = this->param().pad_w;
        size_t sh = this->param().stride_h;
        size_t sw = this->param().stride_w;
        size_t dh = this->param().dilate_h;
        size_t dw = this->param().dilate_w;
        size_t wh = this->param().window_h;
        size_t ww = this->param().window_w;
        size_t oh, ow;
        infer_conv_shape2d(
                ih, iw, wh + (wh - 1) * (dh - 1), ww + (ww - 1) * (dw - 1), sh, sw, ph,
                pw, oh, ow);
        dst = TensorLayout(
                TensorShape({n, oh, ic, ow, wh, ww, 4}), src.dtype, src.format);
    }
}

void Images2NeibsBase::check_layout_fwd(
        const TensorLayout& src, const TensorLayout& dst) {
    TensorLayout dst_expected;
    deduce_layout_fwd(src, dst_expected);
    megdnn_assert_eq_layout(dst_expected, dst);
}

void Images2NeibsForward::deduce_layout(const TensorLayout& src, TensorLayout& dst) {
    deduce_layout_fwd(src, dst);
}

void Images2NeibsForward::check_exec(
        const TensorLayout& src, const TensorLayout& dst, size_t workspace_in_bytes) {
    check_layout_fwd(src, dst);
    auto required_workspace_in_bytes = get_workspace_in_bytes(src, dst);
    megdnn_assert(workspace_in_bytes >= required_workspace_in_bytes);
}

void Images2NeibsBackward::check_exec(
        const TensorLayout& diff, const TensorLayout& grad, size_t workspace_in_bytes) {
    check_layout_fwd(grad, diff);
    auto required_workspace_in_bytes = get_workspace_in_bytes(grad, diff);
    megdnn_assert(workspace_in_bytes >= required_workspace_in_bytes);
}

}  // namespace megdnn

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