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nanquantile #20888
nanquantile #20888
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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 🤗 |
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Requested 2 changes, can you get the tests to pass for this function.
Also its weird that there was no test for nanquantile
in the experimental API, Thanks for adding that too 😄
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1 change requested
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nanquantile.unsupported_dtypes = { | ||
"torch": ("float16", "bfloat16"), |
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Actually can you add this as a decorator on the function.
@with_unsupported_dtypes(
{"2.0.1 and below": ("float16", "bfloat16")}, "torch"
)
Sorry for making you change this the 2nd time 😅
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Requested 1 change.
Can you get the test passing if they fail after that.
Feel free to ask me anything if you get stuck. 😄
Thanks
test_gradients=st.just(False), | ||
) | ||
def test_nanquantile( | ||
*, dtype_and_x, keep_dims, test_flags, backend_fw, fn_name, on_device |
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dtype_and_x
should be dtype_x_axis
because that's how its defined above
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Pointed out 1 thing.
You can check the intelligent tests run in this PR and see if the tests are failing and you can see the failure. You'll get a good understanding of why is it failing form that.
Thanks
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Hi,
So one thing I realized, there is no backend implementation of ivy.nanquantile
😅, its just a hollow function with no implementation, This is a mistake on our end, I'll create a task for this and someone from the engineering team can look into it.
I'll merge your PR since you've written tests and torch frontend function is just supposed to call ivy.nanquantile
.
I've requested 1 change, I'll merge it after you've made that change
Thanks
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