/******************************************************************************* * 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 ******************************************************************************/ // // @author Yurii Shyrma (iuriish@yahoo.com), created on 24.07.2018 // #include #if NOT_EXCLUDED(OP_prelu) #include #include #include namespace nd4j { namespace ops { //////////////////////////////////////////////////////////////////////// CONFIGURABLE_OP_IMPL(prelu, 2, 1, true, 0, 0) { auto input = INPUT_VARIABLE(0); auto alpha = INPUT_VARIABLE(1); auto output = OUTPUT_VARIABLE(0); std::vector sharedAxes = *block.getIArguments(); const int inputRank = input->rankOf(); const int alphaRank = alpha->rankOf(); const int numSharedAxes = sharedAxes.size(); // can be zero as well const Nd4jLong inputLen = input->lengthOf(); const Nd4jLong alphaLen = alpha->lengthOf(); const std::vector inputShape = input->getShapeAsVector(); const std::vector alphaShape = alpha->getShapeAsVector(); //***** input validation *****// std::vector expectedAlphaShape(&inputShape[1], &inputShape[inputRank]); REQUIRE_TRUE(inputRank > 1, 0, "PRELU OP: wrong rank of input array, expected rank should be > 1, but got %i instead !", inputRank); for(int i = 0; i < numSharedAxes; ++i) { if(sharedAxes[i] <= 0) sharedAxes[i] += inputRank - 1; REQUIRE_TRUE(1 <= sharedAxes[i] && sharedAxes[i] <= inputRank - 1, 0, "PRELU OP: wrong axis value %i in sharedAxes at position %i, axis value must be within range [1, input_rank-1] !", sharedAxes[i], i); expectedAlphaShape[sharedAxes[i] - 1] = 1; } Nd4jLong product = 1; for(const auto& item : expectedAlphaShape) product *= item; REQUIRE_TRUE(product == alphaLen, 0, "PRELU OP: wrong shape of alpha array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(expectedAlphaShape).c_str(), ShapeUtils::shapeAsString(alphaShape).c_str()); // ***** end of validation ***** // helpers::prelu(block.launchContext(), *input, alphaShape != expectedAlphaShape ? alpha->reshape(alpha->ordering(), expectedAlphaShape) : *alpha, *output); return Status::OK(); } DECLARE_TYPES(prelu) { getOpDescriptor() ->setAllowedInputTypes(0, DataType::ANY) ->setAllowedInputTypes(1, {ALL_FLOATS}) ->setAllowedOutputTypes(0, {ALL_FLOATS}); } //////////////////////////////////////////////////////////////////////// CONFIGURABLE_OP_IMPL(prelu_bp, 3, 2, true, 0, 0) { auto input = INPUT_VARIABLE(0); auto alpha = INPUT_VARIABLE(1); auto dLdO = INPUT_VARIABLE(2); auto dLdI = OUTPUT_VARIABLE(0); auto dLdA = OUTPUT_VARIABLE(1); std::vector sharedAxes = *block.getIArguments(); const int inputRank = input->rankOf(); const int alphaRank = alpha->rankOf(); const int numSharedAxes = sharedAxes.size(); // can be zero as well const Nd4jLong inputLen = input->lengthOf(); const Nd4jLong alphaLen = alpha->lengthOf(); const std::vector inputShape = input->getShapeAsVector(); const std::vector alphaShape = alpha->getShapeAsVector(); //***** input validation *****// // temporary limitation imposed by Yurii REQUIRE_TRUE(inputRank <= MAX_RANK/2, 0, "rank of input array should be <= MAX_RANK/2, but got %i instead!", inputRank); REQUIRE_TRUE(input->lengthOf() / alpha->lengthOf() <= MAX_RANK*2, 0, "the length of input array should be no more than MAX_RANK*2 times the alpha array length, but got %lld and %lld correspondingly!", input->lengthOf(), alpha->lengthOf()); std::vector expectedAlphaShape(&inputShape[1], &inputShape[inputRank]); REQUIRE_TRUE(inputRank > 1, 0, "PRELU_BP OP: wrong rank of input array, expected rank should be > 1, but got %i instead !", inputRank); for(int i = 0; i < numSharedAxes; ++i) { if(sharedAxes[i] <= 0) sharedAxes[i] += inputRank - 1; REQUIRE_TRUE(1 <= sharedAxes[i] && sharedAxes[i] <= inputRank - 1, 0, "PRELU_BP OP: wrong axis value %i in sharedAxes at position %i, axis value must be within range [1, input_rank-1] !", sharedAxes[i], i); expectedAlphaShape[sharedAxes[i] - 1] = 1; } Nd4jLong product = 1; for(const auto& item : expectedAlphaShape) product *= item; REQUIRE_TRUE(product == alphaLen, 0, "PRELU_BP OP: wrong shape of alpha array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(expectedAlphaShape).c_str(), ShapeUtils::shapeAsString(alphaShape).c_str()); // ***** end of validation ***** // if(alphaShape != expectedAlphaShape) { alpha = new NDArray(alpha->reshape(alpha->ordering(), expectedAlphaShape)); dLdA = new NDArray(dLdA->reshape(dLdA->ordering(), expectedAlphaShape)); } helpers::preluBP(block.launchContext(), *input, *alpha, *dLdO, *dLdI, *dLdA); if(alphaShape != expectedAlphaShape) { delete alpha; delete dLdA; } return Status::OK(); } DECLARE_TYPES(prelu_bp) { getOpDescriptor() ->setAllowedInputTypes(0, DataType::ANY) ->setAllowedInputTypes(1, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF}) ->setAllowedInputTypes(2, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF}) ->setAllowedOutputTypes(0, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF}) ->setAllowedOutputTypes(1, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF}); } } } #endif