Details
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Task
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Status: Open
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Major
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Resolution: Unresolved
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Description
This project is to implement and extend the transpose operation to work on matrices via a shape and transpose order argument.
The implementation should modify the matrices as if it has the tensor shape specified in the argument.
A simple example of this is the python numpy transpose operator for multi dimensional matrices such as
'X.transpose(2, 0, 1)' that change the order of the dimensions via a multi dimensional transpose.
A suggested interface to implement would be :
# read in matrix. # Shape is 2 by 12 X = read(X) # A shape of 2 by 3 by 4 treating the matrix as a tensor with one extra dimension shape = matrix("2 3 4", rows=1, cols=3) # The order of the dimensions wanted after transpose order = matrix("1 3 2", rows = 1, cols=3) Xt, newShape = t(target=X, shape=shape, order=order) # Xt should now have shape 2 by 12 still, but # new shape is 2 by 4 by 3 print(toString(newShape))