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deeplearning4j--deeplearning4j/libnd4j/include/ops/declarable/generic/parity_ops/expose.cpp
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2026-07-13 12:47:05 +08:00

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/* ******************************************************************************
*
*
* 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.
*
* See the NOTICE file distributed with this work for additional
* information regarding copyright ownership.
* 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 raver119 on 12/11/17.
//
#include <ops/declarable/CustomOperations.h>
#if NOT_EXCLUDED(OP_expose)
namespace sd {
namespace ops {
CUSTOM_OP_IMPL(expose, -2, -2, true, 0, 0) {
for (size_t e = 0; e < block.width(); e++) {
//omit for eager computation, normally array size should be equal to block size
if(block.getVariableSpace() == nullptr || block.getVariableSpace()->getVariables().size() != block.width()) {
auto in = INPUT_VARIABLE(e);
auto out = OUTPUT_VARIABLE(e);
out->assign(in);
} else {
auto inVar = block.variable(e);
if (inVar->variableType() == NDARRAY) {
auto in = INPUT_VARIABLE(e);
auto out = OUTPUT_VARIABLE(e);
out->assign(in);
} else if (inVar->variableType() == ARRAY_LIST) {
auto var = block.ensureVariable(e);
if (!var->hasNDArrayList()) {
auto list = inVar->getNDArrayList();
block.pushNDArrayListToVariableSpace(block.nodeId(), e, list, false);
}
}
}
}
return Status::OK;
}
DECLARE_SYN(Enter, expose);
DECLARE_SYN(enter, expose);
DECLARE_TYPES(expose) { getOpDescriptor()->setAllowedInputTypes(ANY)->setSameMode(true); }
DECLARE_SHAPE_FN(expose) {
auto shapeList = SHAPELIST();
for (size_t e = 0; e < block.width(); e++) {
auto var = block.getVariable(e);
if (var->variableType() == NDARRAY) {
auto inShape = inputShape->at(e);
shapeList->push_back(ConstantShapeHelper::getInstance().bufferForShapeInfo(inShape)->primary());
}
}
return shapeList;
}
} // namespace ops
} // namespace sd
#endif