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Valeriy Fedyunin
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Add CDataLayer (#428)
* Add CDataLayer Signed-off-by: Valeriy Fedyunin <[email protected]> * Add Data layer to the neoml module initialization Signed-off-by: Valeriy Fedyunin <[email protected]> * Fix python build Signed-off-by: Valeriy Fedyunin <[email protected]> * Remove test code Signed-off-by: Valeriy Fedyunin <[email protected]>
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‎NeoML/Python/CMakeLists.txt

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@@ -52,6 +52,7 @@ pybind11_add_module(PythonWrapper
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src/PyCrfLayer.cpp
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src/PyCtcLayer.cpp
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src/PyCustomLossLayer.cpp
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src/PyDataLayer.cpp
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src/PyDifferentialEvolution.cpp
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src/PyDotProductLayer.cpp
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src/PyDropoutLayer.cpp

‎NeoML/Python/neoml/Dnn/Data.py

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""" Copyright (c) 2017-2020 ABBYY Production LLC
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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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,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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--------------------------------------------------------------------------------------------------------------
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"""
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import neoml.PythonWrapper as PythonWrapper
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from .Dnn import Layer
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import neoml.Blob as Blob
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class Data(Layer):
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"""The data layer that serves to pass a fixed data blob into the network.
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:param dnn: The neural network.
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:type dnn: object
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:param name: The layer name.
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:type name: str, default=None
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.. rubric:: Layer inputs:
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The layer has no inputs.
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.. rubric:: Layer outputs:
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The layer has one output that contains the data blob
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passed into the last call of set_blob.
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"""
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def __init__(self, dnn, name=None):
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if type(dnn) is PythonWrapper.Data:
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super().__init__(dnn)
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return
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internal = PythonWrapper.Data(dnn, str(name))
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super().__init__(internal)
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def set_blob(self, blob):
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"""Sets the blob with data.
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"""
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self._internal.set_blob(blob._internal)
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def get_blob(self):
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"""Gets the blob with data.
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"""
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return Blob(self._internal.get_blob())

‎NeoML/Python/neoml/Dnn/Source.py

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class Source(Layer):
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"""The source layer that serves to pass a data blob into the network.
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"""The source layer that serves to pass a user data blob into the network.
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:param dnn: The neural network.
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:type dnn: object

‎NeoML/Python/neoml/Dnn/__init__.py

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from .Conv import Conv, Conv3D, TransposedConv3D, TransposedConv, ChannelwiseConv, TimeConv
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from .Crf import Crf, CrfLoss, BestSequence
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from .Ctc import CtcLoss, CtcDecoding
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from .Data import Data
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from .DotProduct import DotProduct
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from .Dropout import Dropout
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from .Eltwise import EltwiseSum, EltwiseSub, EltwiseMul, EltwiseDiv, EltwiseNegMul, EltwiseMax

‎NeoML/Python/src/PyDataLayer.cpp

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/* Copyright © 2017-2021 ABBYY Production LLC
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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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,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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--------------------------------------------------------------------------------------------------------------*/
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#include <common.h>
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#pragma hdrstop
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#include "PyDataLayer.h"
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#include "PyDnnBlob.h"
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#include "PyDnn.h"
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#include "PyMathEngine.h"
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class CPyDataLayer : public CPyLayer {
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public:
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CPyDataLayer( CDataLayer* layer, CPyMathEngineOwner& mathEngineOwner ) : CPyLayer( *layer, mathEngineOwner ) {}
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void SetBlob( const CPyBlob& blob )
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{
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Layer<CDataLayer>()->SetBlob( blob.Blob() );
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}
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CPyBlob GetBlob() const
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{
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return CPyBlob( MathEngineOwner(), Layer<CDataLayer>()->GetBlob() );
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}
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py::object CreatePythonObject() const
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{
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py::object pyModule = py::module::import( "neoml.Dnn" );
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py::object pyConstructor = pyModule.attr( "Data" );
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return pyConstructor( py::cast(this) );
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}
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};
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void InitializeDataLayer( py::module& m )
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{
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py::class_<CPyDataLayer, CPyLayer>(m, "Data")
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.def( py::init([]( const CPyLayer& layer )
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{
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return new CPyDataLayer( layer.Layer<CDataLayer>(), layer.MathEngineOwner() );
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}))
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.def( py::init([]( const CPyDnn& dnn, const std::string& name )
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{
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py::gil_scoped_release release;
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CPtr<CDataLayer> dataLayer( new CDataLayer( dnn.MathEngine() ) );
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dataLayer->SetName( FindFreeLayerName( dnn.Dnn(), "Data", name ).c_str() );
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dnn.Dnn().AddLayer( *dataLayer );
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return new CPyDataLayer( dataLayer, dnn.MathEngineOwner() );
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}))
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.def( "set_blob", &CPyDataLayer::SetBlob, py::return_value_policy::reference )
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.def( "get_blob", &CPyDataLayer::GetBlob, py::return_value_policy::reference )
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;
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}

‎NeoML/Python/src/PyDataLayer.h

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/* Copyright © 2017-2021 ABBYY Production LLC
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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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,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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--------------------------------------------------------------------------------------------------------------*/
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#pragma once
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#include "PyLayer.h"
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void InitializeDataLayer( py::module& m );

‎NeoML/Python/src/PyDnn.cpp

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@@ -170,6 +170,7 @@ REGISTER_NEOML_PYLAYER( "IndRnn", "NeoMLDnnIndRnnLayer" )
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REGISTER_NEOML_PYLAYER( "Qrnn", "NeoMLDnnQrnnLayer" )
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REGISTER_NEOML_PYLAYER( "Lrn", "NeoMLDnnLrnLayer" )
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REGISTER_NEOML_PYLAYER( "Cast", "NeoMLDnnCastLayer" )
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REGISTER_NEOML_PYLAYER( "Data", "NeoMLDnnDataLayer" )
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}
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‎NeoML/Python/src/PyWrapper.cpp

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#include "PyCrfLayer.h"
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#include "PyCtcLayer.h"
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#include "PyCustomLossLayer.h"
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#include "PyDataLayer.h"
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#include "PyDotProductLayer.h"
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#include "PyDropoutLayer.h"
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#include "PyFullyConnectedLayer.h"
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InitializeConcatLayer( m );
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InitializeCrfLayer( m );
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InitializeCtcLayer( m );
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InitializeDataLayer( m );
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InitializeEltwiseLayer( m );
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InitializeDotProductLayer( m );
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InitializeDropoutLayer( m );

‎NeoML/docs/en/API/NN/IOLayers/DataLayer.md

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# CDataLayer Class
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<!-- TOC -->
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- [CDataLayer Class](#cdatalayer-class)
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- [Settings](#settings)
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- [Trainable parameters](#trainable-parameters)
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- [Inputs](#inputs)
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- [Outputs](#outputs)
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<!-- /TOC -->
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This class implements a layer that serves to input a blob of fixed data into the neural network.
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## Settings
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```c++
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void SetBlob( CDnnBlob* blob );
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```
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Sets the blob with source data. It may be of arbitrary size and contain any kind of data.
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## Trainable parameters
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There are no trainable parameters for this layer.
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## Inputs
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The layer has no inputs.
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## Outputs
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The single output contains the data blob that was passed into the last call of `SetBlob()`.

‎NeoML/docs/en/API/NN/IOLayers/SourceLayer.md

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<!-- /TOC -->
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This class implements a layer that serves to input a blob of data into the neural network.
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This class implements a layer that serves to input a blob of user data into the neural network.
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## Settings
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‎NeoML/docs/en/API/NN/README.md

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- [CBaseLayer](BaseLayer.md) is the base class for common layer functionality
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- The layers used to pass the data to and from the network:
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- [CSourceLayer](IOLayers/SourceLayer.md) transmits a blob of data into the network
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- [CSourceLayer](IOLayers/SourceLayer.md) transmits a blob of user data into the network
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- [CSinkLayer](IOLayers/SinkLayer.md) is used to retrieve a blob of data with the network response
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- [CProblemSourceLayer](IOLayers/ProblemSourceLayer.md) transmits the data from [`IProblem`](../ClassificationAndRegression/Problems.md) into the network
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- [CFullyConnectedSourceLayer](IOLayers/FullyConnectedSourceLayer.md) transmits the data from `IProblem` into the network, multiplying the vectors by a trainable weights matrix
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- [CDataLayer](IOLayers/DataLayer.md) transmits a blob of fixed data into the network
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- [CFullyConnectedLayer](FullyConnectedLayer.md) is the fully-connected layer
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- [Activation functions](ActivationLayers/README.md):
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- [CLinearLayer](ActivationLayers/LinearLayer.md) - a linear activation function `ax + b`

‎NeoML/docs/ru/API/NN/IOLayers/DataLayer.md

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# Класс CDataLayer
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<!-- TOC -->
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- [Класс CDataLayer](#класс-cdatalayer)
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- [Настройки](#настройки)
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- [Обучаемые параметры](#обучаемые-параметры)
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- [Входы](#входы)
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- [Выходы](#выходы)
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<!-- /TOC -->
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Класс реализует слой, передающий блоб с фиксированными данными в сеть.
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## Настройки
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```c++
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void SetBlob( CDnnBlob* blob );
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```
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Установка блоба с данными, который будет передан в сеть. Блоб может иметь любые размеры и содержать данные любого типа.
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## Обучаемые параметры
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Слой не имеет обучаемых параметров.
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## Входы
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Слой не имеет входов.
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## Выходы
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Единственный выход содержит блоб, который был передан при последнем вызове `SetBlob()`.

‎NeoML/docs/ru/API/NN/IOLayers/SourceLayer.md

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<!-- /TOC -->
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Класс реализует слой, передающий блоб с данными в сеть.
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Класс реализует слой, передающий блоб с пользовательскими данными в сеть.
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## Настройки
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‎NeoML/docs/ru/API/NN/README.md

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- [CBaseLayer](BaseLayer.md) - базовый класс
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- Слои для обмена данными с сетью:
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- [CSourceLayer](IOLayers/SourceLayer.md) - передача блобов с данными в сеть
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- [CSourceLayer](IOLayers/SourceLayer.md) - передача блобов с пользовательскими данными в сеть
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- [CSinkLayer](IOLayers/SinkLayer.md) - получение блобов с данными из сети
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- [CProblemSourceLayer](IOLayers/ProblemSourceLayer.md) - передача данных из [`IProblem`](../ClassificationAndRegression/Problems.md) в сеть
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- [CFullyConnectedSourceLayer](IOLayers/FullyConnectedSourceLayer.md) - передача данных из `IProblem` в сеть и домножение их на матрицу
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- [CDataLayer](IOLayers/DataLayer.md) - передача блобов с фиксированными данными в сеть
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- [CFullyConnectedLayer](FullyConnectedLayer.md) - полносвязный слой
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- [Функции активации](ActivationLayers/README.md):
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- [CLinearLayer](ActivationLayers/LinearLayer.md) - функция активации вида `ax + b`

‎NeoML/include/NeoML/Dnn/Layers/DataLayer.h

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/* Copyright © 2017-2020 ABBYY Production LLC
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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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,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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--------------------------------------------------------------------------------------------------------------*/
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#pragma once
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#include <NeoML/NeoMLDefs.h>
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#include <NeoML/Dnn/Dnn.h>
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namespace NeoML {
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// The layer that pases data blob to the network
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// Unlike CSourceLayer this layer isn't interpreted as a user-provided data
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// The source layer that passes a data blob into the network. Can have exactly one output
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class NEOML_API CDataLayer : public CBaseLayer {
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NEOML_DNN_LAYER( CDataLayer )
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public:
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explicit CDataLayer( IMathEngine& mathEngine ) : CBaseLayer( mathEngine, "CDataLayer", false ) {}
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// Sets the input data blob
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void SetBlob( CDnnBlob* blob );
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// Gets the reference to the input blob
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const CPtr<CDnnBlob>& GetBlob() const { return blob; }
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void Serialize( CArchive& archive ) override;
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protected:
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CPtr<CDnnBlob> blob;
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// CBaseLayer class methods
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void Reshape() override;
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void RunOnce() override;
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void BackwardOnce() override;
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void AllocateOutputBlobs() override;
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};
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// Creates CDataLayer with the given name
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NEOML_API CDataLayer* Data( CDnn& network, const char* name );
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} // namespace NeoML

‎NeoML/include/NeoML/NeoML.h

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#include <NeoML/Dnn/Layers/SpaceToDepthLayer.h>
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#include <NeoML/Dnn/Layers/LrnLayer.h>
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#include <NeoML/Dnn/Layers/CastLayer.h>
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#include <NeoML/Dnn/Layers/DataLayer.h>
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#include <NeoML/ArchiveFile.h>
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#ifndef NO_NEOML_NAMESPACE

‎NeoML/src/CMakeLists.txt

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Dnn/Layers/CrfLayer.cpp
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Dnn/Layers/CrossEntropyLossLayer.cpp
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Dnn/Layers/CtcLayer.cpp
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Dnn/Layers/DataLayer.cpp
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Dnn/Layers/DepthToSpaceLayer.cpp
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Dnn/Layers/DotProductLayer.cpp
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Dnn/Layers/DropoutLayer.cpp
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../include/NeoML/Dnn/Layers/ConvLayer.h
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../include/NeoML/Dnn/Layers/CrfLayer.h
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../include/NeoML/Dnn/Layers/CtcLayer.h
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../include/NeoML/Dnn/Layers/DataLayer.h
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../include/NeoML/Dnn/Layers/DepthToSpaceLayer.h
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../include/NeoML/Dnn/Layers/DotProductLayer.h
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../include/NeoML/Dnn/Layers/DropoutLayer.h

‎NeoML/src/Dnn/Dnn.cpp

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#include <NeoML/Dnn/Layers/SpaceToDepthLayer.h>
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#include <NeoML/Dnn/Layers/LrnLayer.h>
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#include <NeoML/Dnn/Layers/CastLayer.h>
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#include <NeoML/Dnn/Layers/DataLayer.h>
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namespace NeoML {
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REGISTER_NEOML_LAYER( CSpaceToDepthLayer, "NeoMLDnnSpaceToDepthLayer" )
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REGISTER_NEOML_LAYER( CLrnLayer, "NeoMLDnnLrnLayer" )
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REGISTER_NEOML_LAYER( CCastLayer, "NeoMLDnnCastLayer" )
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REGISTER_NEOML_LAYER( CDataLayer, "NeoMLDnnDataLayer" )
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}
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