/******************************************************************************* * 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 george@skymind.io on 2/21/2018. // #include #include namespace sd { namespace ops { CUSTOM_OP_IMPL(segment_min, 2, 1, false, 0, 0) { auto input = INPUT_VARIABLE(0); auto idxSegments = INPUT_VARIABLE(1); auto segmentedOutput = OUTPUT_VARIABLE(0); REQUIRE_TRUE(idxSegments->isVector(), 0, "segment_min: segment indexes array should be a vector, but it rank is %i.", idxSegments->rankOf()); REQUIRE_TRUE(idxSegments->lengthOf() == input->sizeAt(0), 0, "segment_min: segment indexes array length should be equal to the input first dimension, but %i != %i.", idxSegments->lengthOf(), input->sizeAt(0)); auto expected = NDArrayFactory::create(input->dataType(), 0.f, block.launchContext()); auto wrong = NDArrayFactory::create(input->dataType(), 0.f, block.launchContext()); REQUIRE_TRUE(helpers::segmentIndicesValidate(block.launchContext(), idxSegments, expected, wrong), 0, "segment_min: segment indices should be arranged, but %2.1f > %2.1f", expected.e(0), wrong.e(0)); segmentedOutput->nullify(); helpers::segmentMinFunctor(block.launchContext(), input, idxSegments, segmentedOutput); return Status::OK(); } DECLARE_SHAPE_FN(segment_min) { auto idxVector = INPUT_VARIABLE(1); auto in = inputShape->at(0); int outRank = shape::rank(in); Nd4jLong* outputShape = nullptr; int val = (*idxVector).e(idxVector->lengthOf() - 1); int numOfClasses = val + 1; ALLOCATE(outputShape, block.getWorkspace(), shape::shapeInfoLength(outRank), Nd4jLong); outputShape[0] = outRank; outputShape[1] = numOfClasses; for(int i = 1; i < outRank; ++i) outputShape[i + 1] = shape::sizeAt(in, i); ShapeUtils::updateStridesAndType(outputShape, in, shape::order(in)); return SHAPELIST(CONSTANT(outputShape)); } CUSTOM_OP_IMPL(segment_min_bp, 3, 2, false, 0, 0) { auto input = INPUT_VARIABLE(0); auto indices = INPUT_VARIABLE(1); auto gradOut = INPUT_VARIABLE(2); auto output = OUTPUT_NULLIFIED(0); auto outIndices = OUTPUT_NULLIFIED(1); outIndices->assign(indices); return helpers::segmentMinFunctorBP(block.launchContext(), input, indices, gradOut, output); } DECLARE_SHAPE_FN(segment_min_bp){ auto in = inputShape->at(0); auto inIdx = inputShape->at(1); Nd4jLong* outShape; Nd4jLong* outIndex; COPY_SHAPE(in, outShape); COPY_SHAPE(inIdx, outIndex); return SHAPELIST(CONSTANT(outShape), CONSTANT(outIndex)); // return SHAPELIST(in, inIdx); } DECLARE_TYPES(segment_min) { getOpDescriptor() ->setAllowedInputTypes(0, {ALL_FLOATS, ALL_INTS}) ->setAllowedInputTypes(1, {ALL_INTS}) ->setAllowedOutputTypes({ALL_FLOATS, ALL_INTS}) ->setSameMode(false); } DECLARE_TYPES(segment_min_bp) { getOpDescriptor() ->setAllowedInputTypes(sd::DataType::ANY) ->setAllowedOutputTypes(0, {ALL_FLOATS}) ->setAllowedOutputTypes(1, {ALL_INTS}) ->setSameMode(true); } } }