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alpha_dropout #21564

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alpha_dropout #21564

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teckno
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@teckno teckno commented Aug 9, 2023 •
edited by fnhirwa
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closes #22124

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github-actions bot commented Aug 9, 2023

Thanks for contributing to Ivy! 😊👏
Here are some of the important points from our Contributing Guidelines 📝:
1. Feel free to ignore the run_tests (1), run_tests (2), … jobs, and only look at the display_test_results job. 👀 It contains the following two sections:
- Combined Test Results: This shows the results of all the ivy tests that ran on the PR. ✔️
- New Failures Introduced: This lists the tests that are passing on master, but fail on the PR Fork. Please try to make sure that there are no such tests. 💪
2. The lint / Check formatting / check-formatting tests check for the formatting of your code. 📜 If it fails, please check the exact error message in the logs and fix the same. ⚠️🔧
3. Finally, the test-docstrings / run-docstring-tests check for the changes made in docstrings of the functions. This may be skipped, as well. 📚
Happy coding! 🎉👨‍💻

@teckno teckno mentioned this pull request Aug 9, 2023
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@ivy-leaves ivy-leaves added the Paddle Frontend Developing the Paddle Frontend, checklist triggered by commenting add_frontend_checklist label Aug 9, 2023
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@teckno teckno mentioned this pull request Aug 18, 2023
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fnhirwa
fnhirwa suggested changes Aug 29, 2023
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Hey @teckno

Check the comments below but mainly it would be good if you check for ivy implementation of the function that you're going to use in the frontend this will make the review process easy🙂
Thanks

ivy_tests/test_ivy/test_frontends/test_paddle/test_nn/test_functional/test_common.py Outdated
p=st.floats(min_value=0.0, max_value=1.0),
axis=st.integers(min_value=0, max_value=1),
training=st.booleans(),
mode=st.one_of(
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We can sample from a list of these modes no need to nest different strategies🙂

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Okay thanks will follow up

ivy/functional/frontends/paddle/nn/functional/common.py Outdated
@to_ivy_arrays_and_back
@with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
def alpha_dropout( x, p=0.5, training=True, name=None ):
return ivy.alpha_dropout(x, p=p, training=training)
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There is no alpha_dropout in Ivy API you will need a compositional implementation here 🙂

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Thanks i try and follow up

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github-actions bot reviewed Sep 30, 2023
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PR Compliance Checks

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@teckno teckno closed this Nov 18, 2023
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alpha_dropout
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@teckno @ivy-leaves @fnhirwa