Add Linear Algebra operations to PyTorch frontend

[AnnaTz]

Add Linear Algebra operations to PyTorch frontend:

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Please keep in mind that the proper way to link an issue to this list is to comment "- [ ] #issue_number" while the issue's title only includes the name of the function you've chosen.
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• torch.norm #14816
  vector_norm #8886
  matrix_norm #7534
  diagonal #22531
  det
  slogdet
  cond #14591
  matrix_rank
  cholesky #7595
  qr #7604
  lu #18377
  lu_factor
  eig #8391
  eigvals #10848
  eigh #22636
  eigvalsh #7571
  svd #7665
  svdvals #23145
  solve #9152
  solve_triangular #21197
  lu_solve #22754
  lstsq #22395
  inv
  pinv #7550
  matrix_exp
  matrix_power
  cross #7597
  matmul #10204
  vecdot
  multi_dot #11952
  householder_product #24132
  householder_product
  tensorinv #7786
  tensorsolve #9889
  vander #12988
  cholesky_ex #16661
  inv_ex #7920
  solve_ex #16488
  lu_factor_ex #21504
  ldl_factor #26396
  #23720_ex
  ldl_solve #22402
  Note: If the Linear Algebra function to be implemented has identical behavior to another PyTorch function, you should simply keep an alias in the linalg.py file rather than creating a duplicate implementation.
  For example:
  torch.linalg.diagonal is defined as an alias of torch.diagonal in the official docs, and so it is defined as shown below
  https://github.com/unifyai/ivy/blob/34f0eebc25c5d8b1af5299912f64ce531efc3e38/ivy/functional/frontends/torch/linalg.py#L7

The main file paths where these functions are likely to be added are:

ivy/functional/frontends/torch/linalg.py
ivy\_tests/test\_ivy/test\_frontends/test\_torch/test\_linalg.py

[dettmerramon]

• det #22617

[dettmerramon]

Hi @AnnaTz, just wanted to point out that inv has already been implemented, see https://github.com/unifyai/ivy/blob/570e1a93d319b308ed9ce4cb72103045cdc6ae11/ivy/functional/frontends/torch/linalg.py#L107-L108

[jordonah]

• matrix_rank #22432

[tiwariaayushi]

#22943

[jordonah]

• matrix_rank #23531

[odunola499]

• householder_product #23935

[Tinny-Robot]

@ivy-branch The task involves implementing the "householder_product" function #23515 on the frontend. However, upon inspecting the frontend codebase, I couldn't locate any existing implementation for this function on the backend.

[AnaamSayeda]

• vecdot #26035

[mehak1598]

Hi I noticed that det has already been implemented in the linalg.py files of both torch and tensorflow in frontend and backend folders. Is there anything else that needs to be done for det or can I pick another task ?