text: #ifndef CAFFE_BLOB_HPP_
  #define CAFFE_BLOB_HPP_
  
  #include <algorithm>
  #include <string>
  #include <vector>
  
  #include "caffe/common.hpp"
  #include "caffe/proto/caffe.pb.h"
  #include "caffe/syncedmem.hpp"
  
  const int kMaxBlobAxes = 32;
  
  namespace caffe {
  
  /**
   * @brief A wrapper around SyncedMemory holders serving as the basic
   *        computational unit through which Layer%s, Net%s, and Solver%s
   *        interact.
   *
   * TODO(dox): more thorough description.
   */
  template <typename Dtype>
  class Blob {
   public:
    Blob()
         : data_(), diff_(), count_(0), capacity_(0) {}
  
    /// @brief Deprecated; use <code>Blob(const vector<int>& shape)</code>.
    explicit Blob(const int num, const int channels, const int height,
        const int width);
    explicit Blob(const vector<int>& shape);
  
    /// @brief Deprecated; use <code>Reshape(const vector<int>& shape)</code>.
    void Reshape(const int num, const int channels, const int height,
        const int width);
    /**
     * @brief Change the dimensions of the blob, allocating new memory if
     *        necessary.
     *
     * This function can be called both to create an initial allocation
     * of memory, and to adjust the dimensions of a top blob during Layer::Reshape
     * or Layer::Forward. When changing the size of blob, memory will only be
     * reallocated if sufficient memory does not already exist, and excess memory
     * will never be freed.
     *
     * Note that reshaping an input blob and immediately calling Net::Backward is
     * an error; either Net::Forward or Net::Reshape need to be called to
     * propagate the new input shape to higher layers.
     */
    void Reshape(const vector<int>& shape);
    void Reshape(const BlobShape& shape);
    void ReshapeLike(const Blob& other);
    inline string shape_string() const {
      ostringstream stream;
      for (int i = 0; i < shape_.size(); ++i) {
        stream << shape_[i] << " ";
      }
      stream << "(" << count_ << ")";
      return stream.str();
    }
    inline const vector<int>& shape() const { return shape_; }
    /**
     * @brief Returns the dimension of the index-th axis (or the negative index-th
     *        axis from the end, if index is negative).
     *
     * @param index the axis index, which may be negative as it will be
     *        "canonicalized" using CanonicalAxisIndex.
     *        Dies on out of range index.
     */
    inline int shape(int index) const {
      return shape_[CanonicalAxisIndex(index)];
    }
    inline int num_axes() const { return shape_.size(); }
    inline int count() const { return count_; }
  
    /**
     * @brief Compute the volume of a slice; i.e., the product of dimensions
     *        among a range of axes.
     *
     * @param start_axis The first axis to include in the slice.
     *
     * @param end_axis The first axis to exclude from the slice.
     */
    inline int count(int start_axis, int end_axis) const {
      CHECK_LE(start_axis, end_axis);
      CHECK_GE(start_axis, 0);
      CHECK_GE(end_axis, 0);
      CHECK_LE(start_axis, num_axes());
      CHECK_LE(end_axis, num_axes());
      int count = 1;
      for (int i = start_axis; i < end_axis; ++i) {
        count *= shape(i);
      }
      return count;
    }
    /**
     * @brief Compute the volume of a slice spanning from a particular first
     *        axis to the final axis.
     *
     * @param start_axis The first axis to include in the slice.
     */
    inline int count(int start_axis) const {
      return count(start_axis, num_axes());
    }
  
    /**
     * @brief Returns the 'canonical' version of a (usually) user-specified axis,
     *        allowing for negative indexing (e.g., -1 for the last axis).
     *
     * @param axis_index the axis index.
     *        If 0 <= index < num_axes(), return index.
     *        If -num_axes <= index <= -1, return (num_axes() - (-index)),
     *        e.g., the last axis index (num_axes() - 1) if index == -1,
     *        the second to last if index == -2, etc.
     *        Dies on out of range index.
     */
    inline int CanonicalAxisIndex(int axis_index) const {
      CHECK_GE(axis_index, -num_axes())
          << "axis " << axis_index << " out of range for " << num_axes()
          << "-D Blob with shape " << shape_string();
      CHECK_LT(axis_index, num_axes())
          << "axis " << axis_index << " out of range for " << num_axes()
          << "-D Blob with shape " << shape_string();
      if (axis_index < 0) {
        return axis_index + num_axes();
      }
      return axis_index;
    }
  
    /// @brief Deprecated legacy shape accessor num: use shape(0) instead.
    inline int num() const { return LegacyShape(0); }
    /// @brief Deprecated legacy shape accessor channels: use shape(1) instead.
    inline int channels() const { return LegacyShape(1); }
    /// @brief Deprecated legacy shape accessor height: use shape(2) instead.
    inline int height() const { return LegacyShape(2); }
    /// @brief Deprecated legacy shape accessor width: use shape(3) instead.
    inline int width() const { return LegacyShape(3); }
    inline int LegacyShape(int index) const {
      CHECK_LE(num_axes(), 4)
          << "Cannot use legacy accessors on Blobs with > 4 axes.";
      CHECK_LT(index, 4);
      CHECK_GE(index, -4);
      if (index >= num_axes() || index < -num_axes()) {
        // Axis is out of range, but still in [0, 3] (or [-4, -1] for reverse
        // indexing) -- this special case simulates the one-padding used to fill
        // extraneous axes of legacy blobs.
        return 1;
      }
      return shape(index);
    }
  
    inline int offset(const int n, const int c = 0, const int h = 0,
        const int w = 0) const {
      CHECK_GE(n, 0);
      CHECK_LE(n, num());
      CHECK_GE(channels(), 0);
      CHECK_LE(c, channels());
      CHECK_GE(height(), 0);
      CHECK_LE(h, height());
      CHECK_GE(width(), 0);
      CHECK_LE(w, width());
      return ((n * channels() + c) * height() + h) * width() + w;
    }
  
    inline int offset(const vector<int>& indices) const {
      CHECK_LE(indices.size(), num_axes());
      int offset = 0;
      for (int i = 0; i < num_axes(); ++i) {
        offset *= shape(i);
        if (indices.size() > i) {
          CHECK_GE(indices[i], 0);
          CHECK_LT(indices[i], shape(i));
          offset += indices[i];
        }
      }
      return offset;
    }
    /**
     * @brief Copy from a source Blob.
     *
     * @param source the Blob to copy from
     * @param copy_diff if false, copy the data; if true, copy the diff
     * @param reshape if false, require this Blob to be pre-shaped to the shape
     *        of other (and die otherwise); if true, Reshape this Blob to other's
     *        shape if necessary
     */
    void CopyFrom(const Blob<Dtype>& source, bool copy_diff = false,
        bool reshape = false);
  
    inline Dtype data_at(const int n, const int c, const int h,
        const int w) const {
      return cpu_data()[offset(n, c, h, w)];
    }
  
    inline Dtype diff_at(const int n, const int c, const int h,
        const int w) const {
      return cpu_diff()[offset(n, c, h, w)];
    }
  
    inline Dtype data_at(const vector<int>& index) const {
      return cpu_data()[offset(index)];
    }
  
    inline Dtype diff_at(const vector<int>& index) const {
      return cpu_diff()[offset(index)];
    }
  
    inline const shared_ptr<SyncedMemory>& data() const {
      CHECK(data_);
      return data_;
    }
  
    inline const shared_ptr<SyncedMemory>& diff() const {
      CHECK(diff_);
      return diff_;
    }
  
    const Dtype* cpu_data() const;
    void set_cpu_data(Dtype* data);
    const int* gpu_shape() const;
    const Dtype* gpu_data() const;
    const Dtype* cpu_diff() const;
    const Dtype* gpu_diff() const;
    Dtype* mutable_cpu_data();
    Dtype* mutable_gpu_data();
    Dtype* mutable_cpu_diff();
    Dtype* mutable_gpu_diff();
  
    // jay add
    const Dtype* cpu_data_at(const int n = 0, const int c = 0,
  			   const int h = 0, const int w = 0) const;
    const Dtype* gpu_data_at(const int n = 0, const int c = 0,
  			   const int h = 0, const int w = 0) const;
    const Dtype* cpu_diff_at(const int n = 0, const int c = 0,
  			   const int h = 0, const int w = 0) const;
    const Dtype* gpu_diff_at(const int n = 0, const int c = 0,
  			   const int h = 0, const int w = 0) const;
    Dtype* mutable_cpu_data_at(const int n = 0, const int c = 0,
  			     const int h = 0, const int w = 0);
    Dtype* mutable_gpu_data_at(const int n = 0, const int c = 0,
  			     const int h = 0, const int w = 0);
    Dtype* mutable_cpu_diff_at(const int n = 0, const int c = 0,
  			     const int h = 0, const int w = 0);
    Dtype* mutable_gpu_diff_at(const int n = 0, const int c = 0,
  			     const int h = 0, const int w = 0);
    // end jay add
  
    void Update();
    void FromProto(const BlobProto& proto, bool reshape = true);
    void ToProto(BlobProto* proto, bool write_diff = false) const;
  
    /// @brief Compute the sum of absolute values (L1 norm) of the data.
    Dtype asum_data() const;
    /// @brief Compute the sum of absolute values (L1 norm) of the diff.
    Dtype asum_diff() const;
    /// @brief Compute the sum of squares (L2 norm squared) of the data.
    Dtype sumsq_data() const;
    /// @brief Compute the sum of squares (L2 norm squared) of the diff.
    Dtype sumsq_diff() const;
  
    /// @brief Scale the blob data by a constant factor.
    void scale_data(Dtype scale_factor);
    /// @brief Scale the blob diff by a constant factor.
    void scale_diff(Dtype scale_factor);
  
    /**
     * @brief Set the data_ shared_ptr to point to the SyncedMemory holding the
     *        data_ of Blob other -- useful in Layer%s which simply perform a copy
     *        in their Forward pass.
     *
     * This deallocates the SyncedMemory holding this Blob's data_, as
     * shared_ptr calls its destructor when reset with the "=" operator.
     */
    void ShareData(const Blob& other);
    /**
     * @brief Set the diff_ shared_ptr to point to the SyncedMemory holding the
     *        diff_ of Blob other -- useful in Layer%s which simply perform a copy
     *        in their Forward pass.
     *
     * This deallocates the SyncedMemory holding this Blob's diff_, as
     * shared_ptr calls its destructor when reset with the "=" operator.
     */
    void ShareDiff(const Blob& other);
  
    bool ShapeEquals(const BlobProto& other);
  
   protected:
    shared_ptr<SyncedMemory> data_;
    shared_ptr<SyncedMemory> diff_;
    shared_ptr<SyncedMemory> shape_data_;
    vector<int> shape_;
    int count_;
    int capacity_;
  
    DISABLE_COPY_AND_ASSIGN(Blob);
  };  // class Blob
  
  }  // namespace caffe
  
  #endif  // CAFFE_BLOB_HPP_
  