Deep learning software for Windows C# programmers.
1using System;
2using System.Collections.Generic;
3using System.Linq;
4using System.Text;
5using System.Threading;
6using System.IO;
7using MyCaffe.basecode;
8using MyCaffe.db.image;
9using MyCaffe.common;
10using MyCaffe.param;
21 public class AdaDeltaSolver<T> : SGDSolver<T>
22 {
39 public AdaDeltaSolver(CudaDnn<T> cuda, Log log, SolverParameter p, CancelEvent evtCancel, AutoResetEvent evtForceSnapshot, AutoResetEvent evtForceTest, IXDatabaseBase db, IXPersist<T> persist, int nSolverCount = 1, int nSolverRank = 0, Net<T> shareNet = null, onGetWorkspace getws = null, onSetWorkspace setws = null)
40 : base(cuda, log, p, evtCancel, evtForceSnapshot, evtForceTest, db, persist, nSolverCount, nSolverRank, shareNet, getws, setws)
41 {
43 }
48 public void AdaDeltaPreSolve()
49 {
50 // Add the extra history entries for AdaDelta after those from
51 // SGDSolver::PreSolve
52 BlobCollection<T> colNetParams = m_net.learnable_parameters;
54 for (int i = 0; i < colNetParams.Count; i++)
55 {
56 List<int> rgShape = colNetParams[i].shape();
57 Blob<T> blob = new Blob<T>(m_cuda, m_log, rgShape);
58 m_colHistory.Add(blob);
59 }
60 }
68 public override void ComputeUpdateValue(int param_id, double dfRate, int nIterationOverride = -1)
69 {
70 BlobCollection<T> colNetParams = m_net.learnable_parameters;
72 if (!colNetParams[param_id].DiffExists)
73 return;
75 List<double?> net_params_lr = m_net.params_lr;
76 T fDelta = Utility.ConvertVal<T>(;
77 T fMomentum = Utility.ConvertVal<T>(m_param.momentum);
78 T fLocalRate = Utility.ConvertVal<T>(dfRate * net_params_lr[param_id].GetValueOrDefault(0));
79 int nUpdateHistoryOffset = colNetParams.Count;
81 // Compute the update to history, then copy it to the parameter diff.
82 m_cuda.adadelta_update(colNetParams[param_id].count(),
83 colNetParams[param_id].mutable_gpu_diff,
84 m_colHistory[param_id].mutable_gpu_data,
85 m_colHistory[nUpdateHistoryOffset + param_id].mutable_gpu_data,
86 fMomentum,
87 fDelta,
88 fLocalRate);
89 }
90 }
The CancelEvent provides an extension to the manual cancel event that allows for overriding the manua...
Definition: CancelEvent.cs:17
The Log class provides general output in text form.
Definition: Log.cs:13
The Utility class provides general utility funtions.
Definition: Utility.cs:35
The BlobCollection contains a list of Blobs.
int Count
Returns the number of items in the collection.
The Blob is the main holder of data that moves through the Layers of the Net.
Definition: Blob.cs:25
The CudaDnn object is the main interface to the Low-Level Cuda C++ DLL.
Definition: CudaDnn.cs:969
Connects Layer's together into a direct acrylic graph (DAG) specified by a NetParameter
Definition: Net.cs:23
The SolverParameter is a parameter for the solver, specifying the train and test networks.
double delta
Numerical stability for RMSProp, AdaGrad, AdaDelta, Adam and AdamW solvers (default = 1e-08).
double momentum
Specifies the momentum value - used by all solvers EXCEPT the 'AdaGrad' and 'RMSProp' solvers....
Use AdaDelta Solver which has gradient based optimization like SGD.
void AdaDeltaPreSolve()
Runs the AdaDleta pre-solve which parpares the Solver to start Solving.
AdaDeltaSolver(CudaDnn< T > cuda, Log log, SolverParameter p, CancelEvent evtCancel, AutoResetEvent evtForceSnapshot, AutoResetEvent evtForceTest, IXDatabaseBase db, IXPersist< T > persist, int nSolverCount=1, int nSolverRank=0, Net< T > shareNet=null, onGetWorkspace getws=null, onSetWorkspace setws=null)
The SGDSolver constructor.
override void ComputeUpdateValue(int param_id, double dfRate, int nIterationOverride=-1)
Compute the AdaDelta update value that will be applied to a learnable blobs in the training Net.
Stochastic Gradient Descent solver with momentum updates weights by a linear combination of the negat...
Definition: SGDSolver.cs:22
BlobCollection< T > m_colHistory
History maintains the historical momentum data.
Definition: SGDSolver.cs:26
SolverParameter m_param
Specifies the SolverParameter that defines how the Solver operates.
Definition: Solver.cs:40
CudaDnn< T > m_cuda
Specifies the instance of CudaDnn used by the Solver that provides a connection to Cuda.
Definition: Solver.cs:32
Net< T > m_net
Specifies the training Net.
Definition: Solver.cs:44
Log m_log
Specifies the Log for output.
Definition: Solver.cs:36
The IXDatabaseBase interface defines the general interface to the in-memory database.
Definition: Interfaces.cs:444
The IXPersist interface is used by the CaffeControl to load and save weights.
Definition: Interfaces.cs:187
The MyCaffe.basecode contains all generic types used throughout MyCaffe.
Definition: Annotation.cs:12
The MyCaffe.common namespace contains common MyCaffe classes.
Definition: BatchInput.cs:8
The MyCaffe.db.image namespace contains all image database related classes.
Definition: Database.cs:18
The MyCaffe.param namespace contains parameters used to create models.
The MyCaffe.solvers namespace contains all solver classes, including the base Solver.
The MyCaffe namespace contains the main body of MyCaffe code that closesly tracks the C++ Caffe open-...
Definition: Annotation.cs:12