wangwei created SINGA-341:
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Summary: Add stride field to Tensor class
Key: SINGA-341
URL: https://issues.apache.org/jira/browse/SINGA-341
Project: Singa
Issue Type: Improvement
Reporter: wangwei
The current Tensor class stores data in a contiguous chunk of memory. It is a
very simple implementation. However, it is difficult to support some
operations. For example,
{code}
Tensor a = b.transpose()
Tensor d = a + c
{code}
Like other tensor implementation (e.g. numpy), Tensor a and b shares memory.
The addition operation has to do real transpose, which incurs some overhead.
With stride, we can avoid the transpose operation. Instead, we enumerate each
element of a and c using the index, shape and stride information.
https://stackoverflow.com/questions/32034237/how-does-numpys-transpose-method-permute-the-axes-of-an-array
More over, stride is necessary for broadcasting operations.
[https://stackoverflow.com/questions/39626233/how-did-numpy-implement-multi-dimensional-broadcasting.]
Code in src/core/tensor.cc tensor_math_cpp.h tensor_math_cuda.h needs
modification when stride is added as a field/member of Tensor.
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