Close #18063 (permuted in numpy frontend)

[PerfectionistAF]

Close #18063

[PerfectionistAF]

permuted test

commit from closed test PR

(path: ivy_tests/test_ivy/test_frontends/test_numpy/test_random/test_functions)

@handle_frontend_test(
    fn_tree="ivy.functional.frontends.numpy.random.functions.permuted",
    dtype_value=helpers.dtype_and_values(
        available_dtypes=helpers.get_dtypes("valid", full=True),
        shape=st.shared(helpers.get_shape(min_num_dims=1), key="value_shape")
    ),
)

def test_permuted(
    *,
    dtype_value,
    permutation,
    x,
    out,
    copy,
    test_flags,
    fn_name,
):

    dtype, value = dtype_value
    shape = dtype_value.shape
    dims = [x for x in range(len(shape))]
    permutation = shape(st.permutations(dims))
    helpers.test_frontend_function(
        input_dtypes=dtype,
        test_flags=test_flags,
        fn_name=fn_name,
        x=value[0],
        axes=permutation,
        out=dtype,
        copy=None
    )

[PerfectionistAF]

Ookamice commented last week
@PerfectionistAF
Thank you for your contributions, may I ask if you could link the relevant issue this PR is associated with? That way I can provide more structured help.

Also, please could you also comment "add_frontend_checklist" (no quotation marks). A bot should automatically edit your message to include the relevant checklist that you can also edit! 😄

[PerfectionistAF]

Frontend Task Checklist

IMPORTANT NOTICE 🚨:

The Ivy Docs represent the ground truth for the task descriptions and this checklist should only be used as a supplementary item to aid with the review process.

Please note that the contributor is not expected to understand everything in the checklist. It's mainly here for the reviewer to make sure everything has been done correctly 🙂

LEGEND 🗺:

• ❌ : Check item is not completed.
• ✅ : Check item is ready for review.
• 🆘 : Stuck/Doubting implementation (PR author should add comments explaining why).
• ⏩ : Check is not applicable to function (skip).
• 🆗 : Check item is implemented and does not require any edits.

CHECKS 📑:

1. • ❌: The function/method definition is not missing any of the original arguments.
2. • ❌: In case the function/method to be implemented is an alias of an existing function/method:
     1. • ❌: It is being declared as such by setting fun1 = fun2, rather than being re-implemented from scratch.
     2. • ❌: The alias is added to the existing function/method's test in the aliases parameter of handle_frontend_test/handle_frontend_method.
3. • ❌: The naming of the function/method and its arguments exactly matches the original.
4. • ❌: No defined argument is being ignored in the function/method's implementation.
5. • ❌: In special cases where an argument's implementation should be pending due to an incomplete superset of an ivy function:
     1. • ❌: A descriptive comment has been left under the Implement superset behavior ToDo list in Implement superset behavior #6406.
     2. • ❌: A ToDo comment has been added prompting to pass the frontend argument to the ivy function whose behavior is to be extended.
6. • ❌: In case a frontend function is being added:
     1. • ❌: It is a composition of ivy functions.
     2. • ❌: In case the needed composition is long (using numerous ivy functions), a Missing Function Suggestion issue has been opened to suggest a new ivy function should be added to shorten the frontend implementation.
     3. • ❌: @to_ivy_arrays_and_back has been added to the function.
7. • ❌: In case a frontend method is being added:
     1. • ❌: It is composed of existing frontend functions or methods.
     2. • ❌: If a required frontend function has not yet been added, the method may be implemented as a composition of ivy functions, making sure that:
          • ❌: @to_ivy_arrays_and_back has been added to the method.
          • ❌: A ToDo comment has been made prompting to remove the decorator and update the implementation as soon as the missing function has been added.
8. • ❌: The function/method's test has been added (except in the alias case mentioned in <2>):
     1. • ❌: All supported arguments are being generated in handle_frontend_test/handle_frontend_method and passed to test_frontend_function/test_frontend_method.
     2. • ❌: The argument generation covers all possible supported values. Array sizes, dimensions, and axes adhere to the full supported set of the original function/method.
     3. • ❌: The available_dtypes parameter passed to the helper generating the function/method's input array is set to helpers.get_dtypes("valid"). If there are unsupported dtypes that cause the test to fail, they should be handled by adding @with_supported_dtypes/@with_unsupported_dtype to the function/method.
9. • ❌: The PR is not introducing any test failures.
     1. • ❌: The lint checks are passing.
     2. • ❌: The implemented test is passing for all backends.
10. • ❌: The PR closes a Sub Task issue linked to one of the open frontend ToDo lists.
11. • ❌: The function/method and its test have been added to the correct .py files corresponding to the addressed ToDo list.
12. • ❌: The PR only contains changes relevant to the addressed subtask.

[PerfectionistAF]

Ookamice commented 3 hours ago
@PerfectionistAF
Hiya, just dug through the issue you linked and it appears you've opened two PRs: one for the frontend function, and one for the tests. Ideally this should be in one PR as it would be difficult to run tests and keep track otherwise. I would believe the easiest solution would be closing one of the PRs and copy-pasting its content into the remaining one!

Let me know if you have any questions regarding this 😄

[zhumakhan]

Hi, could you please add tests for it?

[PerfectionistAF]

The test is pasted above as a comment since some issues occurred with me while committing twice to the same PR

permuted test

commit from closed test PR

(path: ivy_tests/test_ivy/test_frontends/test_numpy/test_random/test_functions)

@handle_frontend_test(
    fn_tree="ivy.functional.frontends.numpy.random.functions.permuted",
    dtype_value=helpers.dtype_and_values(
        available_dtypes=helpers.get_dtypes("valid", full=True),
        shape=st.shared(helpers.get_shape(min_num_dims=1), key="value_shape")
    ),
)

def test_permuted(
    *,
    dtype_value,
    permutation,
    x,
    out,
    copy,
    test_flags,
    fn_name,
):

    dtype, value = dtype_value
    shape = dtype_value.shape
    dims = [x for x in range(len(shape))]
    permutation = shape(st.permutations(dims))
    helpers.test_frontend_function(
        input_dtypes=dtype,
        test_flags=test_flags,
        fn_name=fn_name,
        x=value[0],
        axes=permutation,
        out=dtype,
        copy=None
    )

[zhumakhan]

It seems this function is not implemented properly. Could you please fix it?

[ivy-seed]

This PR has been labelled as stale because it has been inactive for more than 7 days. If you would like to continue working on this PR, then please add another comment or this PR will be closed in 7 days.

[ivy-seed]

This PR has been closed because it has been marked as stale for more than 7 days with no activity.