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From "wangwei (JIRA)" <>
Subject [jira] [Created] (SINGA-205) Enable slice and concatenate operations for Tensor objects
Date Thu, 23 Jun 2016 03:54:16 GMT
wangwei created SINGA-205:

             Summary: Enable slice and concatenate operations for Tensor objects
                 Key: SINGA-205
             Project: Singa
          Issue Type: New Feature
            Reporter: wangwei
            Assignee: wangwei

Slice and concatenate operations are typical array operations, and are necessary to support
some models, e.g., GoogleLeNet.
For this ticket, we are going to implement the two operations to support 1D and 2D tensors.
 The following functions would be implemented,
1. SliceRows(Tensor, start, end), the returned tensor shares the memory with the origin tensor.
2. CopyRows(Tensor, start, end), CopyColumns(Tensor, start, end) the returned tensor copies
values from the original tensor
3. ConcatenateRows(vector<Tensor>) and ConcatenateColumns(vector<Tensor>); the
returned tensor copies values from the origin tensors.

To support SliceRows, i.e., memory sharing between two tensors of different sizes, we need
to update the Block class as

class Block {
  Block(void* ptr, size_t size, size_t offset=0);
  void* mutable_data() const  { return data_+offset_;}
  const void* data() const  { return data_+offset_;}
    void *data_;
    size_t offset_ = 0;  // offset in terms of Bytes.
    shared_ptr<atomic<int>> ref_count_;
The sub-tensors (i.e., generated from SliceRows) would have a different Block instance as
the original tensor, but would share the internal `ref_count_` and `data_` fields.
`offset_` is 0 for the original tensors, but non-zero for sub-tensors . atomic makes the inc
and dec operations thread-safe. shared_ptr helps to free `ref_count_` safely.

SliceColumns is not supported as singa::Tensor uses row major storage which is difficult to
support SliceColumns SliceRows(). Users can use CopyColumns().

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