implement bincount function #18199

druvdub · 2023-07-02T20:02:29Z

druvdub · 2023-07-02T20:20:23Z

could someone clarify if the implementation is correct or not?
as I am a bit confused as there is sub-task to implement bincount in tensor.linalg as well and was wondering if this one should reference that one via paddle_frontend

ivy-leaves · 2023-07-03T16:06:05Z

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 🤗

xoiga123 · 2023-07-03T22:47:17Z

Hi @druvdub! Thank you for contributing to Ivy 🤗 The implementation looks okay to me at first glance, but could you link to the issue that you've created (if you've been following the Frontend API Guide) so that I know what you're working on precisely? Also, please comment

add_frontend_checklist

to create a checklist so that I know where you're stuck on. Thank ya ⭐

druvdub · 2023-07-03T22:51:01Z

add_frontend_checklist

druvdub · 2023-07-03T22:58:43Z

Hi @xoiga123 I have added the reference to the issue and the checklist comment.

xoiga123 · 2023-07-04T00:04:24Z

Hey thank you for linking to the issue, but please re-comment add_frontend_checklist as editing a comment doesn't work 😢

ivy/functional/frontends/paddle/tensor/tensor.py

ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_tensor.py

druvdub · 2023-07-04T19:36:37Z

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druvdub · 2023-07-09T19:37:11Z

@xoiga123 hello, I made some changes to the test, but I still am not able to run it. Is it possible to test the function separately somewhere manually to test?

[UPDATE],
hi, I just realised, that bincount in the backend has

@with_unsupported_device_and_dtypes(
    {
        "2.5.0 and below": {
            "cpu": (
                "int8",
                "int16",
                "uint8",
                "float16",
                "float32",
                "float64",
                "complex64",
                "complex128",
                "bool",
            )
        }
    },```
    
should I update my function to be this? including the device as well?

druvdub · 2023-07-14T19:21:49Z

@xoiga123 I have updated the method and the test now, should hopefully work correctly.

xoiga123

Sorry for the late review 😓

xoiga123 · 2023-07-20T11:18:35Z

ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py

+        min_value=1,
+        max_value=2,


Why did you limit it to only [1, 2]? From their example,

x = paddle.to_tensor([1, 2, 1, 4, 5]) result1 = paddle.bincount(x) print(result1) # [0, 2, 1, 0, 1, 1]

xoiga123 · 2023-07-20T11:19:29Z

ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py

+        min_dim_size=1,
+        max_dim_size=2,


Why is the dimension only in [1, 2]? Same example as above.

Hi, sorry was busy last week, I couldn't figure why the tests are not running so I tried duplicating the test from paddle.linalg.bincount

xoiga123 · 2023-07-20T11:20:03Z

ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py

+def test_paddle_instance_bincount(
+    dtypes_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+):


Please also test for all the arguments, i.e. weights and minlength

ivy-seed · 2023-08-06T05:53:24Z

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.

druvdub · 2023-08-06T15:34:39Z

hi @xoiga123 sorry have been busy for a while so didn't do any changes till now but, I wrote the test with only two values since I was trying to follow the similar format to

@handle_frontend_test(
    fn_tree="paddle.bincount",
    dtype_and_x=helpers.dtype_and_values(
        available_dtypes=helpers.get_dtypes("integer"),
        min_value=1,
        max_value=2,
        shape=st.shared(
            helpers.get_shape(
                min_num_dims=1,
                max_num_dims=1,
            ),
            key="a_s_d",
        ),
    ),
    test_with_out=st.just(False),
)
def test_paddle_bincount(
    *,
    dtype_and_x,
    on_device,
    fn_tree,
    backend_fw,
    frontend,
    test_flags,
):
    input_dtype, x = dtype_and_x
    helpers.test_frontend_function(
        input_dtypes=input_dtype,
        frontend=frontend,
        test_flags=test_flags,
        backend_to_test=backend_fw,
        fn_tree=fn_tree,
        on_device=on_device,
        x=x[0],
        weights=None,
        minlength=0,
    )

to this test which is in linalg.py

xoiga123 · 2023-08-11T05:20:26Z

@druvdub that test seems to be misimplemented as well, it is also missing tests for weights and minlength and also too narrow parameter generation. It would be nice if you could fix this PR first, then maybe go on and fix test_paddle_bincount if you want to 😄

druvdub · 2023-08-13T23:47:57Z

will update and push soon

aparajith21 · 2023-09-20T11:45:32Z

will update and push soon

Hi, thanks for contributing, please let me know if this is still being worked on or in progress?

druvdub · 2023-09-20T13:09:44Z

will update and push soon

Hi, thanks for contributing, please let me know if this is still being worked on or in progress?

Hi, yea really sorry haven't made any progress on this due to some work issues. Will get around this week and push the tests.

…ld python 3.10 specific wheels (ivy-llc#26912)

Co-authored-by: hirwa-nshuti <[email protected]>

…vy-llc#26841)

…lc#26867) Co-authored-by: vedpatwardhan <[email protected]>

we were only testing with the `numpy` backend uptil now

…lc#26746) Co-authored-by: vedpatwardhan <[email protected]>

…ilation report to 5 instead of 1

Co-authored-by: Sam Armstrong <[email protected]>

Co-authored-by: ivy-branch <[email protected]>

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vandit98 · 2023-10-28T07:31:38Z

hi @aparajith21
can i work on this issue.

ivy-seed assigned xoiga123 Jul 2, 2023

ivy-leaves added the Paddle Frontend Developing the Paddle Frontend, checklist triggered by commenting add_frontend_checklist label Jul 2, 2023

druvdub marked this pull request as draft July 2, 2023 23:12

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Anik-et and others added 6 commits October 14, 2023 23:09

refactor: dev_util (ivy-llc#26075)

d1d59fc

feat : added paddle instance method not_equal with test (ivy-llc#25936)

0ce6b11

refactor: remove bfloat16 from decorators (ivy-llc#26238)

53bdd2c

fix: simplify paddle backend implementation of gradient

6726630

feat: Add diagonal function to paddle.tensor.math (ivy-llc#18799)

991b9d4

Update compiler.py

7001ce3

vedpatwardhan and others added 20 commits October 14, 2023 23:12

chore(ci): removed the statement, done testing

a5d3860

Update demos 🤖

b6ffdd9

chore: updated the demos submodule

ca4691c

fix: required changes for release regarding the python version to bui…

2b17d06

…ld python 3.10 specific wheels (ivy-llc#26912)

Update release.yml

8afee3d

Update release.yml

9b9c011

feat(tensorflow frontend): added max_pool3d (ivy-llc#26509)

9a2dfbc

Co-authored-by: hirwa-nshuti <[email protected]>

Chore: rename project.toml file

4422eca

🤖 Lint code

466b486

feat(activations): add scaled_tanh(stanh) to ivy experimental API. (i…

614bc43

…vy-llc#26841)

🤖 Lint code

b432bed

fix: Add missing job name for .github\workflows\binaries.yml (ivy-l…

43fbf6c

…lc#26867) Co-authored-by: vedpatwardhan <[email protected]>

feat: extended functional api of nanmin (ivy-llc#26412)

68ef510

🤖 Lint code

013589c

fix: Added backend handling to the module tests (ivy-llc#26988)

b2fb4c4

we were only testing with the `numpy` backend uptil now

fix: Replace use of default mutable arguments in a function. (ivy-l…

98ff0a6

…lc#26746) Co-authored-by: vedpatwardhan <[email protected]>

chore(ci): Changed the number of examples used to generate the transp…

4e8ac5a

…ilation report to 5 instead of 1

feat: add kaiser_window to pytorch frontend (ivy-llc#26788)

d3be4c8

Co-authored-by: Sam Armstrong <[email protected]>

feat(torch-frontend): Adds torch.lstm (ivy-llc#26543)

d1bcdd6

feat(docs): add example to clip_vector_norm doc (ivy-llc#26657)

bedfa8f

Co-authored-by: ivy-branch <[email protected]>

druvdub requested review from guillesanbri, Aarsh2001, KareemMAX, CatB1t and vedpatwardhan as code owners October 14, 2023 22:13

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druvdub deleted the bincount-implementation branch February 10, 2024 20:52

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implement bincount function #18199

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