Log1p

[MuhammadNizamani]

Adding log1p function paddle.tensor.tensor.Tensor from issue Closed #16519

[MuhammadNizamani]

@zaeemansari70 sir waiting for your review.

[zaeemansari70]

Hi @MuhammadNizamani,
Sorry for the delay in the review process. Thanks a lot for your patience. 🙂

I tested your changes locally they are failing for torch, with
AssertionError: the results from backend torch and ground truth framework paddle do not match E inf!=87.49822998046875
The array being passed has the value of 1.0000001e+38, maybe try looking into applying a small safety factor and see if it fixes it!

Let me know if you have any questions 🙂
Thanks!

[MuhammadNizamani]

@zaeemansari70 can you tell how can I test for torch.
and another question this paddle is tensor base then why you are runing it in torch.

[zaeemansari70]

Hi @MuhammadNizamani,
Just for the context, when we run a frontend function, our ground_truth is the actual frontend function from the original framework and is tested against every backend which we have in our Ivy for that specific function.
There can be an issue in the backends sometimes due to which the tests fail but this time it is particularly related to the frontends as the array which is being passed inside the function is of a huge number which can be fixed by a safety factor in your test function.

I've also added the falsifying example so you can test on it!

E           AssertionError:  the results from backend torch and ground truth framework paddle do not match
E            inf!=87.49822998046875 
E           
E           
E           Falsifying example: test_paddle_log1p(
E               frontend='paddle',
E               on_device='cpu',
E               dtype_and_x=(['float32'], [array(1.0000001e+38, dtype=float32)]),
E               frontend_method_data=FrontendMethodData(ivy_init_module=<module 'ivy.functional.frontends.paddle' from '/workspaces/ivy/ivy/functional/frontends/paddle/__init__.py'>, framework_init_module=<module 'paddle' from '/opt/fw/paddle/paddle/__init__.py'>, init_name='to_tensor', method_name='log1p'),
E               init_flags=FrontendMethodTestFlags(
E                   num_positional_args=1,
E                   as_variable=[False],
E                   native_arrays=[False],
E               ),
E               method_flags=FrontendMethodTestFlags(
E                   num_positional_args=0,
E                   as_variable=[False],
E                   native_arrays=[False],
E               ),
E           )
E           
E           You can reproduce this example by temporarily adding @reproduce_failure('6.78.3', b'AAEAAQAAAIfiztMwAAAAAAAAAAAAAAA=') as a decorator on your test case

Thanks! 🙂

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Thank you 🤗

[zaeemansari70]

The changes look good to me 👍
Kindly resolve the conflicts so I can merge the PR. 🙂

[MuhammadNizamani]

On it

[MuhammadNizamani]

@zaeemansari70 merge conflict are resolve

[zaeemansari70]

Hi @MuhammadNizamani ,

The conflicts are still being showed here 🤔

[MuhammadNizamani]

@zaeemansari70 sir I usually resolve the merge conflicts in this PR.

[zaeemansari70]

There was a small change which needed to be made, now your PR looks good to be merged, thanks! 🙂