cavis/libnd4j/include/ops/declarable/impl/PlatformHelper.cpp
raver119 7783012f39
cuDNN integration (#150)
* initial commit

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* one file

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* few more includes

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* m?

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* const

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* cudnn linkage in tests

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* culibos

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* static reminder

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* platform engine tag

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* HAVE_CUDNN moved to config.h.in

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* include

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* include

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* skip cudnn handle creation if there's not cudnn

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* meh

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* target device in context

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* platform engines

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* platform engines

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* allow multiple -h args

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* allow multiple -h args

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* move mkldnn out of CPU block

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* link to mkldnn on cuda

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* less prints

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* minor tweaks

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* next step

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* conv2d NCHW draft

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* conv2d biasAdd

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* test for MKL/CUDNN combined use

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* - provide additional code for conv2d ff based on cudnn api, not tested yet

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* - further work on conv2d helper based on using cudnn api

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* - fixing several cuda bugs which appeared after cudnn lib had been started to use

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* - implementation of conv2d backprop op based on cudnn api

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* - implementaion of conv3d and conv3d_bp ops based on cudnn api

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* - bugs fixing in conv3d/conv3d_bp ops (cudnn in use)

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* - implementation of depthwiseConv2d (ff/bp) op based on cudnn api

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* - implementation of batchnorm ff op based on cudnn api

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* - disable cudnn batchnorm temporary

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* - add minor change in cmake

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* engine for depthwise mkldnn

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* couple of includes

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* - provide permutation to cudnn batchnorm ff when format is NHWC

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* lgamma fix

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* - eliminate memory leak in two tests

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Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2020-01-20 21:32:46 +03:00

91 lines
3.5 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 "../PlatformHelper.h"
#include <graph/Variable.h>
namespace nd4j {
namespace ops {
namespace platforms {
PlatformHelper::PlatformHelper(const char *name, samediff::Engine engine) {
// we just store name/hash of target operation
_name = std::string(name);
_hash = HashHelper::getInstance()->getLongHash(_name);
_engine = engine;
}
nd4j::NDArray *PlatformHelper::getZ(graph::Context &ctx, int inputId) {
NDArray *z = nullptr;
if (ctx.isFastPath()) {
if (ctx.fastpath_out().size() <= inputId) {
if (ctx.isInplace()) {
z = ctx.fastpath_in()[inputId];
} else
throw std::runtime_error("fastpath_out: unresolved output array");
} else {
z = ctx.fastpath_out()[inputId];
}
} else {
std::pair<int, int> pair(ctx.nodeId(), inputId);
if (ctx.isInplace()) {
z = ctx.variable(inputId)->getNDArray();
// hypothetically it's possible to have no variable. chances are low, but who knows. let's just create it for now
if (!ctx.getVariableSpace()->hasVariable(pair)) {
auto var = new graph::Variable();
ctx.getVariableSpace()->putVariable(pair, var);
}
// now we're saving input array as output array
auto var = ctx.getVariableSpace()->getVariable(pair);
var->markRemovable(false);
var->setNDArray(z);
} else if (!ctx.isInplace()) {
auto var = ctx.variable(pair);
if (var->getNDArray() != nullptr && var->getNDArray()->nonNull()) {
z = var->getNDArray();
} else {
nd4j_printf("Can't get Z variable for node_%i!\n", ctx.nodeId());
}
} else {
nd4j_printf("BOOM!\n", "");
throw std::runtime_error("Boom!");
}
}
return z;
}
samediff::Engine PlatformHelper::engine() {
return _engine;
}
std::string PlatformHelper::name() {
return _name;
}
Nd4jLong PlatformHelper::hash() {
return _hash;
}
}
}
}