113 lines
6.2 KiB
C++
113 lines
6.2 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author Yurii Shyrma, created on 20.03.2018
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//
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#include <ops/declarable/CustomOperations.h>
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#include <ops/declarable/helpers/convolutions.h>
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namespace nd4j {
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namespace ops {
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CUSTOM_OP_IMPL(pointwise_conv2d, 2, 1, false, 0, 0) {
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auto input = INPUT_VARIABLE(0); // [bS, iH, iW, iC] (NHWC) or [bS, iC, iH, iW] (NCHW)
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auto weights = INPUT_VARIABLE(1); // [1, 1, iC, oC] always
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auto bias = block.width() > 2 ? INPUT_VARIABLE(2) : nullptr; // [oC]
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auto output = OUTPUT_VARIABLE(0); // [bS, iH, iW, oC] (NHWC) or [bS, oC, iH, iW] (NCHW)
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REQUIRE_TRUE(input->rankOf() == 4, 0, "CUSTOM POINTWISECONV2D OP: rank of input array must be equal to 4, but got %i instead !", input->rankOf());
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REQUIRE_TRUE(weights->rankOf() == 4, 0, "CUSTOM POINTWISECONV2D OP: rank of weights array must be equal to 4, but got %i instead !", weights->rankOf());
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if(bias)
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REQUIRE_TRUE(bias->rankOf() <= 2, 0, "CUSTOM POINTWISECONV2D OP: rank of biases array must be equal <= 2, but got %i instead !", bias->rankOf());
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int kH = 1; // filter(kernel) height
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int kW = 1; // filter(kernel) width
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int sH = 1; // strides height
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int sW = 1; // strides width
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int pH = 0; // paddings height
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int pW = 0; // paddings width
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int dH = 1; // dilations height
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int dW = 1; // dilations width
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int isNCHW = block.getIArguments()->size() > 0 ? !INT_ARG(0) : 1; // INT_ARG(0): 0-NCHW, 1-NHWC
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int bS, iC, iH, iW, oC, oH, oW; // batch size, input channels, input height/width, output channels, output height/width;
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int indIOioC, indIiH, indWoC, indWiC, indWkH, indOoH; // corresponding indexes
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ConvolutionUtils::getSizesAndIndexesConv2d(isNCHW, *input, *output, bS, iC, iH, iW, oC, oH, oW, indIOioC, indIiH, indWiC, indWoC, indWkH, indOoH);
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std::string expectedWeightsShape = ShapeUtils::shapeAsString({1, 1, iC, oC});
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REQUIRE_TRUE(expectedWeightsShape == ShapeUtils::shapeAsString(weights), 0, "CUSTOM POINTWISECONV2D OP: wrong shape of weights array, expected is %s, but got %s instead !", expectedWeightsShape.c_str(), ShapeUtils::shapeAsString(weights).c_str());
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if (bias)
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REQUIRE_TRUE(bias->rankOf() <= 2 && oC == bias->lengthOf(), 0, "CUSTOM POINTWISECONV2D OP: wrong shape of array with biases, expected rank, length: <=2, %i, but got %i, %i instead !", oC, bias->rankOf(), bias->lengthOf());
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ConvolutionUtils::conv2d(block, input, weights, bias, output, kH,kW, sH,sW, pH,pW, dH,dW, 1/*isSameMode*/, isNCHW);
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return Status::OK();
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}
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DECLARE_TYPES(pointwise_conv2d) {
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getOpDescriptor()
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->setAllowedInputTypes(nd4j::DataType::ANY)
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->setAllowedOutputTypes({ALL_FLOATS});
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}
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DECLARE_SHAPE_FN(pointwise_conv2d) {
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Nd4jLong* inputShapeInfo = inputShape->at(0); // [bS, iH, iW, iC] (NHWC) or [bS, iC, iH, iW] (NCHW)
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Nd4jLong* weightsShapeInfo = inputShape->at(1); // [1, 1, iC, oC] always
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Nd4jLong* biasShapeInfo = block.width() > 2 ? inputShape->at(2) : nullptr; // [oC]
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const int rank = 4;
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REQUIRE_TRUE(inputShapeInfo[0] == rank, 0, "CUSTOM POINTWISECONV2D OP: rank of input array must be equal to %i, but got %i instead !", rank, inputShapeInfo[0]);
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REQUIRE_TRUE(weightsShapeInfo[0] == rank, 0, "CUSTOM POINTWISECONV2D OP: rank of weights array must be equal to %i, but got %i instead !", rank, weightsShapeInfo[0]);
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int isNCHW = block.getIArguments()->size() > 0 ? !INT_ARG(0) : 1; // INT_ARG(0): 0-NCHW, 1-NHWC
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int indIOioC, indWoC(3);
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if(!isNCHW)
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indIOioC = 3;
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else
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indIOioC = 1;
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const int bS = inputShapeInfo[1]; // batch size
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const int iC = inputShapeInfo[indIOioC+1]; // input channels
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const int oC = weightsShapeInfo[indWoC+1]; // output channels
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std::string expectedWeightsShape = ShapeUtils::shapeAsString({1, 1, iC, oC});
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REQUIRE_TRUE(expectedWeightsShape == ShapeUtils::shapeAsString(weightsShapeInfo), 0, "POINTWISECONV2D OP: wrong shape of weights array, expected is %s, but got %s instead !", expectedWeightsShape.c_str(), ShapeUtils::shapeAsString(weightsShapeInfo).c_str());
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if (biasShapeInfo)
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REQUIRE_TRUE(biasShapeInfo[0] <= 2 && oC == shape::length(biasShapeInfo), 0, "POINTWISECONV2D OP: wrong shape of array with biases, expected rank, length: <=2, %i, but got %i, %i instead !", oC, biasShapeInfo[0], shape::length(biasShapeInfo));
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auto outputShapeInfo = ShapeBuilders::copyShapeInfoAndType(inputShapeInfo, weightsShapeInfo, true, block.getWorkspace());
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// do not forget to put oC instead of iC in outputShapeInfo
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outputShapeInfo[indIOioC + 1] = oC;
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shape::updateStrides(outputShapeInfo, shape::order(inputShapeInfo));
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return SHAPELIST(CONSTANT(outputShapeInfo));
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}
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}
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}
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