cavis/libnd4j/include/graph/execution/impl/LogicConditional.cpp

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2019-06-06 14:21:15 +02:00
/*******************************************************************************
* 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 raver119 on 20.10.2017.
//
#include <graph/execution/LogicConditional.h>
#include <GraphExecutioner.h>
#include <graph/execution/LogicReturn.h>
#include <Status.h>
namespace nd4j {
namespace graph {
Nd4jStatus LogicConditional::processNode(Graph *graph, Node *node) {
auto __variableSpace = graph->getVariableSpace();
auto size = node->input()->size();
// propagating inputs (optional)
for (int e = 0; e < size - 3; e++) {
std::pair<int, int> pair(node->id(), e);
if (!__variableSpace->hasVariable(pair)) {
__variableSpace->putVariable(pair, new Variable(nullptr, nullptr, node->id(), e));
}
auto va = node->input()->at(e);
auto inputVar = __variableSpace->getVariable(va);
auto innerVar = __variableSpace->getVariable(pair);
if (innerVar->hasNDArray()) {
// TODO: ???
} else {
// FIXME: in some cases it's possible to have no NDArray
if (inputVar->hasNDArray())
Shyrma temp (#131) * - specifying template instantiation for certain types in float16 and bloat16 Signed-off-by: Yurii <iuriish@yahoo.com> * - polishing bfloat16 and float16 member functions template specialization Signed-off-by: Yurii <iuriish@yahoo.com> * - rewrite and overload array +-*/ scalar and scalar +-*/ arr in NDAray class Signed-off-by: Yurii <iuriish@yahoo.com> * - make corrections which have to do with and rvalue lvalue conversions Signed-off-by: Yurii <iuriish@yahoo.com> * - provide move semantic in NDArray operators array +-/* array Signed-off-by: Yurii <iuriish@yahoo.com> * float16/bfloat16 tweaks Signed-off-by: raver119 <raver119@gmail.com> * one more tweak Signed-off-by: raver119 <raver119@gmail.com> * - make float16 and bfloat16 to compile successfully on cuda Signed-off-by: Yurii <iuriish@yahoo.com> * - do not use resources of view-like arrays when move semantics is applied Signed-off-by: Yurii <iuriish@yahoo.com> * - get rid of pointers in signatures NDArray methods 1 Signed-off-by: Yurii <iuriish@yahoo.com> * - correction of signature of NDArray::dup method Signed-off-by: Yurii <iuriish@yahoo.com> * - correction of signature of NDArray::reduceAlongDimension method Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::applyIndexReduce and applyTrueBroadcast methods Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::applyReduce3 and varianceAlongDimension methods Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::tensorsAlongDimension and diagonal methods Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::allTensorsAlongDimension Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::reduceAlongDimension 2 Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::applyTransform 2 Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::applyPairwiseTransform 2 Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::applyBroadcast 2 Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::applyTrueBroadcast 2 Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::applyScalar and applyScalarArr Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::lambda methods Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::reduce3 methods 2 Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of following NDArray methods: add/sub/mul/div row/column and fillAsTriangular Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::tileToShape methods Signed-off-by: Yurii <iuriish@yahoo.com> * - signature correction of NDArray::isShapeSameStrict method Signed-off-by: Yurii <iuriish@yahoo.com> * minor corrections in tests Signed-off-by: Yurii <iuriish@yahoo.com> * - replace reduce op in batchnorm mkldnn Signed-off-by: Yurii <iuriish@yahoo.com> * - add explicit templates instantiations for operator+(NDArray&&. const scalar) Signed-off-by: Yurii <iuriish@yahoo.com> * - corrections of casts in float16/bfloat16 Signed-off-by: Yurii <iuriish@yahoo.com> * - provide move semantics in following NDArray methods: transform, applyTrueBroadcast, transpose, reshape, permute Signed-off-by: Yurii <iuriish@yahoo.com> * - get rid of input array A duplicate in svd cuda op Signed-off-by: Yurii <iuriish@yahoo.com> * - avoid available bug in svd cuda API Signed-off-by: Yurii <iuriish@yahoo.com> * - add temporary global memory buffer in svd cuda when calcUV = false and m != n Signed-off-by: Yurii <iuriish@yahoo.com> * - remove test with blfoat16 type for betainC Signed-off-by: Yurii <iuriish@yahoo.com> * - resolve conflicts after master has been merged in Signed-off-by: Yurii <iuriish@yahoo.com> * - changed type of affected input array in fused_batch_norm Signed-off-by: Yurii <iuriish@yahoo.com> * - add several explicit type castings Signed-off-by: Yurii <iuriish@yahoo.com> * - add ND4J_EXPORT to operators Signed-off-by: Yurii <iuriish@yahoo.com> * - add explicit template types in instantiations of template arithm operators of NDArray class Signed-off-by: Yurii <iuriish@yahoo.com> * - one more test fix Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-by: raver119 <raver119@gmail.com>
2019-12-20 20:35:39 +01:00
innerVar->setNDArray(new NDArray(inputVar->getNDArray()->dup()));
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}
}
int scopeConditionIndex = node->input()->at(size - 3).first;
int scopeFalseIndex = node->input()->at(size - 2).first;
int scopeTrueIndex = node->input()->at(size - 1).first;
auto scopeCondition = graph->scopeById(scopeConditionIndex);
int lastNode = 0;
for (auto v: *scopeCondition->nodes()) {
GraphExecutioner::executeFlatNode(graph, v, __variableSpace);
lastNode = v->id();
}
// now we should take result of the Scope run, and evaluate it
//nd4j_debug("", "");
auto result = __variableSpace->getVariable(lastNode)->getNDArray();
//result->printBuffer("Result of the last node:");
bool isReturn = false;
// now we're executing one of the scopes, depending on condition evaluation
if (result->e<int>(0) == 0) {
auto scopeFalse = graph->scopeById(scopeFalseIndex);
lastNode = 0;
int nodes = scopeFalse->nodes()->size();
for (int e = 0; e < nodes - 1; e++) {
auto v = scopeFalse->nodes()->at(e);
GraphExecutioner::executeFlatNode(graph, v, __variableSpace);
lastNode = v->id();
}
// last node is either return or just last op
auto *node = scopeFalse->nodes()->at(nodes -1);
if (node->opType() == OpType_LOGIC && node->opNum() == 40) {
isReturn = true;
LogicReturn::processNode(graph, node);
} else {
GraphExecutioner::executeFlatNode(graph, node, __variableSpace);
lastNode = node->id();
}
} else {
auto scopeTrue = graph->scopeById(scopeTrueIndex);
lastNode = 0;
int nodes = scopeTrue->nodes()->size();
for (int e = 0; e < nodes - 1; e++) {
auto v = scopeTrue->nodes()->at(e);
GraphExecutioner::executeFlatNode(graph, v, __variableSpace);
lastNode = v->id();
}
// last node is either return or just last op
auto node = scopeTrue->nodes()->at(nodes -1);
if (node->opType() == OpType_LOGIC && node->opNum() == 40) {
isReturn = true;
LogicReturn::processNode(graph, node);
} else {
GraphExecutioner::executeFlatNode(graph, node, __variableSpace);
lastNode = node->id();
}
}
// now fetch and transfer variables to Conditional node
// but only if return wasn't called at the end of scope
if (!isReturn) {
for (int e = 0; e < DataTypeUtils::max<int>(); e++) {
std::pair<int, int> pair(lastNode, e);
std::pair<int, int> pairNew(node->id(), e);
if (__variableSpace->hasVariable(pair)) {
auto array = __variableSpace->getVariable(pair)->getNDArray();
auto newVar = new Variable(array);
newVar->setId(lastNode, e);
newVar->markRemovable(false);
__variableSpace->putVariable(pairNew, newVar);
} else
break;
}
}
return nd4j::Status::OK();
}
}
}