conjugate method in DNDarray

[mtar]

Description

Adds conj to DNDarray to match the NumPy/PyTorch API

Changes proposed:

• DNDarray method conj

Type of change

• Enhancement/feature

Memory requirements

N/A 😃

Performance

N/A 😃

Due Diligence

• All split configurations tested
• Multiple dtypes tested in relevant functions
• Documentation updated (if needed)
• Updated changelog.md under the title "Pending Additions"

Does this change modify the behaviour of other functions? If so, which?

no

[codecov]

Codecov Report

Merging #885 (fe05e9e) into master (ef32ccf) will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master     #885   +/-   ##
=======================================
  Coverage   95.47%   95.47%           
=======================================
  Files          64       64           
  Lines        9533     9535    +2     
=======================================
+ Hits         9102     9104    +2     
  Misses        431      431           

Flag	Coverage Δ
gpu	94.61% <100.00%> (+<0.01%)	⬆️
unit	91.04% <100.00%> (+<0.01%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
heat/core/complex_math.py	100.00% <100.00%> (ø)

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[coquelin77]

well that was easy! 😁