feat: Added hfftn

[ptdatta]

PR Description

Added hfftn to paddle frontend

Related Issue

Close #23457

Checklist

• Did you add a function?
• Did you add the tests?
• Did you follow the steps we provided?

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[ptdatta]

@djl11 @vedpatwardhan @Ishticode kindly review this PR. Thank you.

[vedpatwardhan]

Given that @Ishticode is assigned to the PR, he'll take a look soon, sorry for the delay @ptdatta 😄

[Ishticode]

Hi @ptdatta
Thanks for the PR. Currently the PR calls upon ivy.hfftn where ivy does not yet implement hfftn for the backends. This is why test_paddle_hfftn seems to fail as a new failure as seen in the logs. Please either compose the function using existing ivy functions or make a proposal for hfftn to be added as a function in all backends as a ToDo as seen here #3856.

Let me know if unsure. Thanks 🙂️

[ptdatta]

@Ishticode But I have added the backend for this function at ivy/functional/backends/paddle/experimental/layers.py

@with_supported_dtypes(
    {
        "2.5.1 and below": (
            "complex64",
            "complex128",
        )
    },
    backend_version,
)
def hfftn(
    x: paddle.Tensor,
    s: Optional[Union[int, Tuple[int]]] = None,
    axes: Optional[Union[int, Tuple[int]]] = None,
    *,
    norm: Optional[str] = "backward",
    out: Optional[paddle.Tensor] = None,
) -> paddle.Tensor:
    result = paddle.fft.hfftn(x, s, axes, norm)
    return result

Am I missing something?

[ptdatta]

@Ishticode But I have added the backend for this function at ivy/functional/backends/paddle/experimental/layers.py

@with_supported_dtypes(
    {
        "2.5.1 and below": (
            "complex64",
            "complex128",
        )
    },
    backend_version,
)
def hfftn(
    x: paddle.Tensor,
    s: Optional[Union[int, Tuple[int]]] = None,
    axes: Optional[Union[int, Tuple[int]]] = None,
    *,
    norm: Optional[str] = "backward",
    out: Optional[paddle.Tensor] = None,
) -> paddle.Tensor:
    result = paddle.fft.hfftn(x, s, axes, norm)
    return result

Am I missing something?

@vedpatwardhan @Ishticode please reply??

[Ishticode]

Hi @ptdatta
As already pointed out the majority of backends are missing the implementation. You do have implementation for paddle backend which is good but other backends don't have it. This leads to recursion error where you call current_backend.hfftn it keeps going back onto itself.

When a frontend function is implemented, we expect the ivy... calls to be able to run with any of our supported backends including tf, torch jax and paddle.

Please check our contributing guidelines if these things don't make sense. Thank you very much.

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