Add `standard_t` function to numpy frontend #21549

MichalisPanayides · 2023-08-09T15:52:52Z

github-actions · 2023-08-09T15:53:07Z

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ivy-leaves · 2023-08-09T16:00:03Z

If you are working on an open task, please edit the PR description to link to the issue you've created.

For more information, please check ToDo List Issues Guide.

Thank you 🤗

MichalisPanayides · 2023-08-09T16:25:44Z

ivy/functional/frontends/numpy/random/functions.py

+    denominator = ivy.gamma(df / 2, 1.0, shape=size, dtype="float64")
+    return ivy.sqrt(df / 2) * ivy.divide(numerator, ivy.sqrt(denominator))


Should I be using the division function implemented in ivy here (ivy.divide)? I tried to do that but the gamma function fails because it expects to have integers or floats as inputs rather than ivy.arrays.

Gamma accepts both Array and NativeArray so this shouldn't be an issue

Suggested change

denominator = ivy.gamma(df / 2, 1.0, shape=size, dtype="float64")

return ivy.sqrt(df / 2) * ivy.divide(numerator, ivy.sqrt(denominator))

denominator = ivy.gamma(ivy.divide(df, 2), 1.0, shape=size, dtype="float64")

return ivy.sqrt(ivy.divide(df, 2)) * ivy.divide(numerator, ivy.sqrt(denominator))

When I run the tests locally with ivy.divide I get an error saying:

ivy.utils.exceptions.IvyBackendException: numpy: gamma: low and high bounds must be numerics when shape is specified

Error on the CI seems to be somewhat different anbd suggest input issues. Please check the same and request a review once done
https://github.com/unifyai/ivy/actions/runs/5811559595/job/15755368193?pr=21549#step:3:543

MichalisPanayides · 2023-08-09T16:28:09Z

The mathematical formula that was implemented was found from numpy's source code

aparajith21 · 2023-08-11T04:45:47Z

ivy_tests/test_ivy/test_frontends/test_numpy/test_random/test_functions.py

@@ -410,6 +410,40 @@ def test_numpy_standard_gamma(
    )


+@handle_frontend_test(
+    fn_tree="numpy.random.standard_t",
+    df=st.floats(min_value=0, max_value=20, exclude_min=True),


Please get integers here instead of floats for df

I had it as integers initially, but the documentation of numpy.random.standard_t says that df is a float. Do you still want me to change that to integers?

This is okay then, unless its causing failures elsewhere

aparajith21 · 2023-08-11T04:47:10Z

Thanks for contributing, could you please comment add_frontend_checklist and check the items there!

MichalisPanayides · 2023-08-11T07:52:04Z

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 📑:

- ✅: The function/method definition is not missing any of the original arguments.
- ✅: 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.
- ✅: The naming of the function/method and its arguments exactly matches the original.
- ✅: No defined argument is being ignored in the function/method's implementation.
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  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.
- ❌: 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.
- ✅: 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.
- ✅: 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.
- ❌: The PR is not introducing any test failures.
  1. - ✅: The lint checks are passing.
  2. - ❌: The implemented test is passing for all backends.
- ✅: The PR closes a Sub Task issue linked to one of the open frontend ToDo lists.
- ✅: The function/method and its test have been added to the correct .py files corresponding to the addressed ToDo list.
- ✅: The PR only contains changes relevant to the addressed subtask.

MichalisPanayides · 2023-08-22T11:52:25Z

ivy_tests/test_ivy/test_frontends/test_numpy/test_random/test_functions.py

@@ -410,6 +410,40 @@ def test_numpy_standard_gamma(
    )


+@handle_frontend_test(
+    fn_tree="numpy.random.standard_t",
+    df=st.floats(min_value=1, max_value=20),


@aparajith21 The tests failed when df was so small that it was practically 0 even though the exclude_min argument was set to True. I changed the min_value of floats from 0 to 1 and I believe everything passes now 👍

Alright, thanks for the contribution! LGTM now then. Sorry for the late review, really busy personally.

Please request review again once you resolve merge conflicts, and will then merge it

@aparajith21 No problem at all. Have resolved the merge conflict but now some tests fail on the jax backend 🤷‍♂️

No issues, sorry for the late review, believe it's not directly related to your PR, will go ahead and merge, thanks!

Add failing test for standard_t function

717ac8c

ivy-leaves added the NumPy Frontend Developing the NumPy Frontend, checklist triggered by commenting add_frontend_checklist label Aug 9, 2023

ivy-seed assigned aparajith21 Aug 9, 2023

MichalisPanayides added 2 commits August 9, 2023 17:18

Implement standard_t function

4528b4c

Add test for standard_t function

9c6e534

MichalisPanayides commented Aug 9, 2023

View reviewed changes

aparajith21 reviewed Aug 11, 2023

View reviewed changes

MichalisPanayides requested a review from aparajith21 August 17, 2023 08:10

MichalisPanayides added 2 commits August 22, 2023 13:53

Change min value of df from 0 to 1 in test

4bd46e0

Remove temporary import to reproduce failed test

0b0989a

MichalisPanayides commented Aug 22, 2023

View reviewed changes

MichalisPanayides added 6 commits August 29, 2023 11:46

Merge branch 'main' into implement-standard-t-function

1cbb8f6

Remove duplicate functions

bc6942c

Order functions alphabetically

ae58f52

Merge branch 'main' into implement-standard-t-function

3e0c5c2

Comment "standard_t" before the test

5b53f80

Order tests alphabetically

1689679

aparajith21 merged commit 1ef0125 into ivy-llc:main Sep 3, 2023

druvdub pushed a commit to druvdub/ivy that referenced this pull request Oct 14, 2023

Add standard_t function to numpy frontend (ivy-llc#21549)

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Add `standard_t` function to numpy frontend #21549

Add `standard_t` function to numpy frontend #21549

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		denominator = ivy.gamma(df / 2, 1.0, shape=size, dtype="float64")
		return ivy.sqrt(df / 2) * ivy.divide(numerator, ivy.sqrt(denominator))

Add standard_t function to numpy frontend #21549

Add standard_t function to numpy frontend #21549

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Frontend Task Checklist

IMPORTANT NOTICE 🚨:

LEGEND 🗺:

CHECKS 📑:

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Add `standard_t` function to numpy frontend #21549

Add `standard_t` function to numpy frontend #21549

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