cavis/libnd4j/include/ops/declarable/generic/nn/convo/im2col.cpp

/*******************************************************************************
 * Copyright (c) 2015-2018 Skymind, Inc.
 *
 * This program and the accompanying materials are made available under the
 * terms of the Apache License, Version 2.0 which is available at
 * https://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.
 *
 * SPDX-License-Identifier: Apache-2.0
 ******************************************************************************/

//
// Created by raver119 on 17.10.2017.
//

#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_im2col)

#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/convolutions.h>
#include <ops/declarable/helpers/im2col.h>
#include <ops/declarable/helpers/col2im.h>

namespace nd4j {
    namespace ops {
        CUSTOM_OP_IMPL(im2col, 1, 1, false, 0, 9) {
            auto x = INPUT_VARIABLE(0);
            auto z = OUTPUT_VARIABLE(0);


            REQUIRE_TRUE(x->rankOf() == 4, 0, "im2col input should be 4D, but got %i instead", x->rankOf());
            REQUIRE_TRUE(z->rankOf() == 6, 0, "im2col output should be 6D, but got %i instead", z->rankOf());

            int kernelHeight = INT_ARG(0);
            int kernelWidth = INT_ARG(1);
            int strideY = INT_ARG(2);
            int strideX = INT_ARG(3);
            int padHeight = INT_ARG(4);
            int padWidth = INT_ARG(5);
            int dY = INT_ARG(6);			//Dilation, height/y dimension
            int dX = INT_ARG(7);			//Dilation, width/x dimension
            bool isSameMode = INT_ARG(8) > 0;
            double zeroPadVal = 0.0;
            if (block.getTArguments()->size() > 0)
                zeroPadVal = T_ARG(0);

            // FIXME: zeropad value is void
            LaunchContext* ctx = block.launchContext();
            nd4j::ops::helpers::im2col(*ctx, *x, *z, kernelHeight, kernelWidth, strideY, strideX, padHeight, padWidth, dY, dX, NDArrayFactory::create(zeroPadVal, block.launchContext()));

            STORE_RESULT(*z);

            return Status::OK();
        }

        DECLARE_SHAPE_FN(im2col) {
            auto inShape = inputShape->at(0);

            int bS = shape::shapeOf(inShape)[0];
            int iD = shape::shapeOf(inShape)[1];
            int inY = shape::shapeOf(inShape)[2];
            int inX = shape::shapeOf(inShape)[3];

            int kY = INT_ARG(0);
            int kX = INT_ARG(1);
            int sY = INT_ARG(2);
            int sX = INT_ARG(3);
            int pY = INT_ARG(4);
            int pX = INT_ARG(5);
            int dY = INT_ARG(6);			//Dilation, height/y dimension
            int dX = INT_ARG(7);			//Dilation, width/x dimension
            bool isSameMode = INT_ARG(8) > 0;

            // output is always 6d for im2col
            Nd4jLong* zShape;
            ALLOCATE(zShape, block.getWorkspace(), shape::shapeInfoLength(6), Nd4jLong);

            int oY = 0;
            int oX = 0;

            ConvolutionUtils::calcOutSizePool2D(oY, oX, kY, kX, sY, sX, pY, pX, dY, dX, inY, inX, isSameMode);

            if (isSameMode)
                ConvolutionUtils::calcPadding2D(pY, pX, oY, oX, inY, inX, kY, kX, sY, sX, dY, dX);

            zShape[0] = 6;
            zShape[1] = bS;
            zShape[2] = iD;
            zShape[3] = kY;
            zShape[4] = kX;
            zShape[5] = oY;
            zShape[6] = oX;

            zShape[shape::shapeInfoLength(zShape) - 2] = 1;
            zShape[shape::shapeInfoLength(zShape) - 1] = 99;

            ShapeUtils::updateStridesAndType(zShape, inShape, 'c');            

            return SHAPELIST(CONSTANT(zShape));
        }

		CUSTOM_OP_IMPL(im2col_bp, 2, 1, false, 0, 9) {
            auto input = INPUT_VARIABLE(0);
			auto gradAtOutput = INPUT_VARIABLE(1);
            auto z = OUTPUT_VARIABLE(0);

            REQUIRE_TRUE(input->rankOf() == 4, 0, "im2col_bp input should be 4D, but got %i instead", input->rankOf());
			REQUIRE_TRUE(gradAtOutput->rankOf() == 6, 0, "im2col_bp gradient at output (input idx 1) should be 6D, but got %i instead", gradAtOutput->rankOf());
            REQUIRE_TRUE(z->rankOf() == 4, 0, "im2col_bp output (grad at input) should be 4D, but got %i instead", z->rankOf());

            int kernelHeight = INT_ARG(0);
            int kernelWidth = INT_ARG(1);
            int strideY = INT_ARG(2);
            int strideX = INT_ARG(3);
            int pH = INT_ARG(4);
            int pW = INT_ARG(5);
            int dY = INT_ARG(6);			//Dilation, height/y dimension
            int dX = INT_ARG(7);			//Dilation, width/x dimension
            bool isSameMode = INT_ARG(8) > 0;
            double zeroPadVal = 0.0;
            if (block.getTArguments()->size() > 0)
                zeroPadVal = T_ARG(0);

			//Assuming NCHW format here
			int imgH = input->sizeAt(2);
			int imgW = input->sizeAt(3);
			
            LaunchContext* ctx = block.launchContext();
            // FIXME:: all helpers should accept NDArray
			ops::helpers::col2im(*ctx, *gradAtOutput, *z, strideY, strideX, pH, pW, imgH, imgW, dY, dX);

            return Status::OK();
        }

        DECLARE_TYPES(im2col) {
            getOpDescriptor()
                    ->setAllowedInputTypes(0, DataType::ANY)
                    ->setAllowedOutputTypes(0, DataType::INHERIT)
                    ->setSameMode(true);
        }

        DECLARE_TYPES(im2col_bp) {
            getOpDescriptor()
                    ->setAllowedInputTypes(0, DataType::ANY)
                    ->setAllowedOutputTypes(0, DataType::INHERIT)
                    ->setSameMode(true);
        }
		
		DECLARE_SHAPE_FN(im2col_bp) {
            Nd4jLong *inShape;
            COPY_SHAPE(inputShape->at(0), inShape);

			return SHAPELIST(CONSTANT(inShape));
		}
    }
}

#endif