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tolist #21303

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tolist #21303

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done
Sanchay-T Aug 4, 2023
41a7ef3
remove idea and ivy_dev
Sanchay-T Aug 5, 2023
1285149
Update .gitignore
Sanchay-T Aug 7, 2023
d42fb59
Delete .idea directory
Sanchay-T Aug 7, 2023
810b28c
1.1
Sanchay-T Aug 9, 2023
9bcaf4d
Merge remote-tracking branch 'origin/tolist' into tolist
Sanchay-T Aug 9, 2023
dd97263
1.1
Sanchay-T Aug 15, 2023
79ce782
Merge branch 'main' into tolist
Sanchay-T Aug 15, 2023
76fbf1a
remove changes from .idea and gitignore
vaithak Aug 17, 2023
9bb5c6d
Update test_manipulation.py
Sanchay-T Aug 22, 2023
daa8ccb
Update manipulation.py
Sanchay-T Aug 22, 2023
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3 changes: 2 additions & 1 deletion .gitignore
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Expand Up @@ -42,4 +42,5 @@ env.bak/
venv.bak/
ivy_dev/
*venv/
venv*
venv*
ivy_dev
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6 changes: 4 additions & 2 deletions .idea/ivy.iml
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2 changes: 1 addition & 1 deletion .idea/misc.xml
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3 changes: 1 addition & 2 deletions .idea/runConfigurations/_template__of_py_test.xml
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14 changes: 14 additions & 0 deletions ivy/functional/frontends/paddle/tensor/manipulation.py
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Expand Up @@ -61,6 +61,15 @@ def split(x, num_or_sections, axis=0, name=None):
return ivy.split(x, num_or_size_splits=num_or_sections, axis=axis)


@with_unsupported_dtypes(
{"2.5.1 and below": ("int16", "complex64", "complex128")},
"paddle",
)
@to_ivy_arrays_and_back
def tolist(x):
return ivy.tolist(x)
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Also, ivy.tolist has no implementation in the functional layer so this won't work. Have you tested this locally?

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No , I had trouble checking it locally , as when I imported the file on top and ran , it kept on looks at the ivy package that was installed through req I guess

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Should I just delete this all and start again?

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How will starting over again help? You need to implement the corresponding function in ivy's functional layer and maybe in the backend too. Please read through ivy's documentation to get an understanding on this.

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I will go through the documentation once again , but I understood the paddle implementation. I cannot seem to find the implementation of tolist in ivy. Maybe I am wrong and sorry for troubling you. But I know that my function will take the tensor as an input and the output should be the list. But is there something inbuilt?
This is the paddle paddle documentation:
image

And this is what I found in the source code on github of Paddle paddle :
image

I still dont understand the tolist() declaration. It would help me a lot if you can somewhat guide me?
Thankyou

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I will say the same thing again, go through ivy's documentation to understand what you are missing.

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Yes went thorough the entire documentation , understood what I was doing wrong. Thankyou. After I push the corrected code here , is the octernship task complete. I didnt understand where to exactly create a pr , in the webinar on youtube they said , there is another repo that will be created by the ivy team for me , and there I have to push

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Also is the issue still allocated to me how do I check , because in the documentation it was mentioned 7 days



@with_unsupported_dtypes(
{"2.5.1 and below": ("float16", "bfloat16", "int8", "int16")},
"paddle",
Expand Down Expand Up @@ -132,3 +141,8 @@ def gather(params, indices, axis=-1, batch_dims=0, name=None):
@to_ivy_arrays_and_back
def roll(x, shifts, axis=None, name=None):
return ivy.roll(x, shifts, axis=axis)


@to_ivy_arrays_and_back
def to_list(x):
return x.tolist()
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why do we need this extra function?

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It was pasted again at the end by mistake , I corrected it.

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I pushed again. @vaithak

30 changes: 30 additions & 0 deletions ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_manipulation.py
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Expand Up @@ -601,3 +601,33 @@ def test_paddle_roll(
shifts=shift,
axis=axis,
)


# tolist
@handle_frontend_test(
fn_tree="paddle.tensor.manipulation.tolist",
dtype_and_x=helpers.dtype_and_values(
available_dtypes=helpers.get_dtypes("valid"),
min_num_dims=1,
max_num_dims=6,
),
)
def test_tolist(
*,
dtype_and_x,
on_device,
fn_tree,
frontend,
test_flags,
backend_fw,
):
input_dtype, x = dtype_and_x
helpers.test_frontend_function(
input_dtypes=input_dtype,
backend_to_test=backend_fw,
frontend=frontend,
test_flags=test_flags,
fn_tree=fn_tree,
on_device=on_device,
x=x[0],
)