cavis/libnd4j/include/ops/declarable/generic/blas/axpy.cpp

61 lines
2.1 KiB
C++

/*******************************************************************************
* 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 raver119@gmail.com
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_axpy)
#include <ops/declarable/CustomOperations.h>
namespace nd4j {
namespace ops {
CONFIGURABLE_OP_IMPL(axpy, 2, 1, false, -2, 0) {
auto x = INPUT_VARIABLE(0);
auto y = INPUT_VARIABLE(1);
auto z = OUTPUT_VARIABLE(0);
REQUIRE_TRUE(x->isSameShape(y),0, "Axpy: both arguments should have the same shape");
REQUIRE_TRUE(x->dataType() == y->dataType() && x->dataType() == z->dataType(), 0, "Axpy: all arguments must have the same data type");
double a = 1.0;
if (block.width() > 2) {
auto alpha = INPUT_VARIABLE(2);
REQUIRE_TRUE(alpha->isScalar(), 0, "Axpy: alpha argument should be scalar or TArg");
} else if (block.getTArguments()->size() > 0) {
a = T_ARG(0);
}
ExtraArguments arguments({a});
y->applyPairwiseTransform(pairwise::Axpy, *x, *z, &arguments);
return ND4J_STATUS_OK;
}
DECLARE_TYPES(axpy) {
getOpDescriptor()
->setAllowedInputTypes(0, {ALL_FLOATS})
->setAllowedInputTypes(1, {ALL_FLOATS})
->setAllowedOutputTypes(0, {ALL_FLOATS});
}
}
}
#endif