67 lines
2.2 KiB
C++
67 lines
2.2 KiB
C++
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/*******************************************************************************
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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 raver119@gmail.com
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//
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#include <op_boilerplate.h>
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#if NOT_EXCLUDED(OP_axpy)
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#include <ops/declarable/CustomOperations.h>
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namespace nd4j {
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namespace ops {
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CONFIGURABLE_OP_IMPL(axpy, 2, 1, false, -2, 0) {
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auto x = INPUT_VARIABLE(0);
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auto y = INPUT_VARIABLE(1);
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auto z = OUTPUT_VARIABLE(0);
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REQUIRE_TRUE(x->isSameShape(y),0, "Axpy: both arguments should have the same shape")
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double a = (double) 1.0f;
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if (block.width() > 2) {
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auto alpha = INPUT_VARIABLE(2);
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REQUIRE_TRUE(alpha->isScalar(), 0, "Axpy: alpha argument should be scalar or TArg");
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} else if (block.getTArguments()->size() > 0) {
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a = T_ARG(0);
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}
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/*
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auto lambda = LAMBDA_TT(_y, _x, a) {
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return a * _x + _y;
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};
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y->applyPairwiseLambda(x, lambda, z);
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*/
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// FIXME: set proper extras here
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y->applyPairwiseTransform(pairwise::Axpy, x, z, nullptr);
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return ND4J_STATUS_OK;
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}
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DECLARE_TYPES(axpy) {
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getOpDescriptor()
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->setAllowedInputTypes(0, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF})
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->setAllowedInputTypes(1, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF})
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->setAllowedOutputTypes(0, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF});
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}
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}
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}
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#endif
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