From cccccbf6cca94a3eaf813b4468453160e91c332b Mon Sep 17 00:00:00 2001
From: Joe Zhao <ztuowen@gmail.com>
Date: Mon, 14 Apr 2014 08:14:45 +0800
Subject: First commit

---
 src/CuTNetLib/cuCache.h | 94 +++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 src/CuTNetLib/cuCache.h

(limited to 'src/CuTNetLib/cuCache.h')

diff --git a/src/CuTNetLib/cuCache.h b/src/CuTNetLib/cuCache.h
new file mode 100644
index 0000000..42d9b4d
--- /dev/null
+++ b/src/CuTNetLib/cuCache.h
@@ -0,0 +1,94 @@
+#ifndef _CUCACHE_H_
+#define _CUCACHE_H_
+
+#include "cumatrix.h"
+
+namespace TNet {
+
+
+  /**
+   * \brief The feature-target pair cache
+   *
+   * \ingroup CuNNComp
+   * Preloads mCachesize features and labels to GRAM
+   * 
+   * During every iterations read mBunchsize data to networks.
+   *
+   * When Cache is to be filled with more data that it can hold 
+   * extras are stored in LeftOver, and when data is filled again
+   * LeftOvers are moved to the Cache.
+   *
+   * Note:
+   *  - Cache Size must be divisible by Bunch Size to ensure proper functionality
+   *  - Once extracted data. Cache must be depleted to begin filling or every time extraction start at location Zero. 
+   *  - Cache must be filled to begin extraction of Data or we can't start filling and harder to avoid discarding data.
+   *  - @todo Why not implement CuCache as a Stack instead of a Queue?
+   *  .
+   */
+  class CuCache {
+    typedef enum { EMPTY, INTAKE, FULL, EXHAUST } State;
+    public:
+      CuCache();
+      ~CuCache();
+     
+      /// Initialize the cache
+      void Init(size_t cachesize, size_t bunchsize);
+
+      /// Add data to cache, returns number of added vectors
+      /// \param[in] rFeatures CuNN Input features data
+      /// \param[in] rDesired CuNN features data label
+      void AddData(const CuMatrix<BaseFloat>& rFeatures, const CuMatrix<BaseFloat>& rDesired);
+      /// Randomizes the cache
+      void Randomize();
+      /// Get the bunch of training data
+      /// \param[out] rFeatures Bunchsize of CuNN Input features data
+      /// \param[out] rDesired  Bunchsize of CuNN features data label
+      void GetBunch(CuMatrix<BaseFloat>& rFeatures, CuMatrix<BaseFloat>& rDesired);
+
+
+      /// Returns true if the cache was completely filled
+      bool Full()
+      { return (mState == FULL); }
+      
+      /// Returns true if the cache is empty
+      bool Empty()
+      { return (mState == EMPTY || mIntakePos < mBunchsize); }
+      
+      /// Number of discarded frames
+      int Discarded() 
+      { return mDiscarded; }
+      
+      /// Set the trace message level
+      void Trace(int trace)
+      { mTrace = trace; }
+
+    private:
+    
+      static long int GenerateRandom(int max)
+      { return lrand48() % max; }
+      
+      State mState; ///< Current state of the cache
+
+      size_t mIntakePos; ///< Number of intaken vectors by AddData
+      size_t mExhaustPos; ///< Number of exhausted vectors by GetBunch
+      
+      size_t mCachesize; ///< Size of cache
+      size_t mBunchsize; ///< Size of bunch
+      int mDiscarded; ///< Number of discarded frames
+
+      CuMatrix<BaseFloat> mFeatures; ///< Feature cache
+      CuMatrix<BaseFloat> mFeaturesRandom; ///< Feature cache
+      CuMatrix<BaseFloat> mFeaturesLeftover; ///< Feature cache
+      
+      CuMatrix<BaseFloat> mDesired;  ///< Desired vector cache
+      CuMatrix<BaseFloat> mDesiredRandom;  ///< Desired vector cache
+      CuMatrix<BaseFloat> mDesiredLeftover;  ///< Desired vector cache
+
+      bool mRandomized;
+
+      int mTrace;
+  }; 
+
+}
+
+#endif
-- 
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