internlm/SWE-Fixer-Train-110K huggingface dataset:
Repository: ivy-llc/ivy

Issue:
unbind



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/tensor.py b/ivy/functional/frontends/paddle/tensor/tensor.py
--- a/ivy/functional/frontends/paddle/tensor/tensor.py
+++ b/ivy/functional/frontends/paddle/tensor/tensor.py
@@ -798,3 +798,19 @@ def real(self, name=None):
     )
     def cast(self, dtype):
         return paddle_frontend.cast(self, dtype)
+
+    @with_supported_dtypes(
+        {
+            "2.5.1 and below": (
+                "bool",
+                "int32",
+                "int64",
+                "float16",
+                "float32",
+                "float64",
+            )
+        },
+        "paddle",
+    )
+    def unbind(self, axis=0):
+        return paddle_frontend.unbind(self._ivy_array, axis=axis)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
@@ -4160,6 +4160,49 @@ def test_paddle_tensor_trunc(
     )
 
 
+# unbind
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="unbind",
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_num_dims=2,
+        max_num_dims=2,
+        max_dim_size=1,
+        force_int_axis=True,
+        min_axis=-1,
+        max_axis=0,
+    ),
+)
+def test_paddle_tensor_unbind(
+    dtype_x_axis,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtypes, x, axis = dtype_x_axis
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtypes,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=input_dtypes,
+        method_all_as_kwargs_np={
+            "axis": axis,
+        },
+        frontend=frontend,
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        on_device=on_device,
+    )
+
+
 # unsqueeze
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
minimum



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -2046,6 +2046,10 @@ def unique(self, sorted=True, return_inverse=False, return_counts=False, dim=Non
     def xlogy(self, *, other, out=None):
         return torch_frontend.xlogy(self, other, out=out)
 
+    @with_unsupported_dtypes({"2.0.1 and below": "complex"}, "torch")
+    def minimum(self, other, *, out=None):
+        return torch_frontend.minimum(self, other=other, out=out)
+
     # Method aliases
     absolute, absolute_ = abs, abs_
     clip, clip_ = clamp, clamp_


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -9378,6 +9378,44 @@ def test_torch_tensor_min(
     )
 
 
+# minimum
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="minimum",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        num_arrays=2,
+    ),
+)
+def test_torch_tensor_minimum(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "other": x[1],
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # mm
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
is_floating_point



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -1094,6 +1094,10 @@ def isinf(self):
     def is_complex(self):
         return torch_frontend.is_complex(self._ivy_array)
 
+    @with_unsupported_dtypes({"2.0.1 and below": ("uint16", "bfloat16")}, "torch")
+    def is_floating_point(self):
+        return torch_frontend.is_floating_point(self._ivy_array)
+
     @with_unsupported_dtypes({"2.0.1 and below": ("bfloat16",)}, "torch")
     def isreal(self):
         return torch_frontend.isreal(self._ivy_array)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -8133,6 +8133,39 @@ def test_torch_tensor_is_cuda(
     ivy.previous_backend()
 
 
+# is_floating_point
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="is_floating_point",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+    ),
+)
+def test_torch_tensor_is_floating_point(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={"data": x[0]},
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 @given(
     requires_grad=st.booleans(),
 )
Repository: ivy-llc/ivy

Issue:
frac



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/tensor.py b/ivy/functional/frontends/paddle/tensor/tensor.py
--- a/ivy/functional/frontends/paddle/tensor/tensor.py
+++ b/ivy/functional/frontends/paddle/tensor/tensor.py
@@ -863,3 +863,9 @@ def unbind(self, axis=0):
     def cpu(self):
         self.ivy_array = ivy.to_device(self.ivy_array, ivy.as_ivy_dev("cpu"))
         return self
+
+    @with_supported_dtypes(
+        {"2.5.1 and below": ("float32", "float64", "int32", "int64")}, "paddle"
+    )
+    def frac(self, name=None):
+        return paddle_frontend.frac(self._ivy_array)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
@@ -2339,6 +2339,44 @@ def test_paddle_tensor_fmin(
     )
 
 
+# frac
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="frac",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes(kind="valid"),
+        num_arrays=1,
+        max_value=1e6,
+        min_value=-1e6,
+    ),
+)
+def test_paddle_tensor_frac(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # greater_than
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
t



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/tensor.py b/ivy/functional/frontends/paddle/tensor/tensor.py
--- a/ivy/functional/frontends/paddle/tensor/tensor.py
+++ b/ivy/functional/frontends/paddle/tensor/tensor.py
@@ -796,6 +796,11 @@ def less_equal(self, y, name=None):
     def real(self, name=None):
         return paddle_frontend.real(self._ivy_array)
 
+    @with_unsupported_dtypes({"2.5.1 and below": ("float16", "bfloat16")}, "paddle")
+    def t(self, name=None):
+        axes = list(range(len(self.ivy_array.shape)))[::-1]
+        return ivy.permute_dims(self.ivy_array, axes=axes)
+
     @with_supported_dtypes(
         {
             "2.5.1 and below": (


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
@@ -4006,6 +4006,42 @@ def test_paddle_tensor_subtract_(
     )
 
 
+# t
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="t",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        max_num_dims=2,
+    ),
+)
+def test_paddle_tensor_t(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        backend_to_test=backend_fw,
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # tanh
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
rad2deg



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -2050,6 +2050,9 @@ def xlogy(self, *, other, out=None):
     def minimum(self, other, *, out=None):
         return torch_frontend.minimum(self, other=other, out=out)
 
+    def rad2deg(self, *, out=None):
+        return torch_frontend.rad2deg(self, out=out)
+
     # Method aliases
     absolute, absolute_ = abs, abs_
     clip, clip_ = clamp, clamp_


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -10652,6 +10652,41 @@ def test_torch_tensor_quantile(
     )
 
 
+# rad2deg
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="rad2deg",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_torch_tensor_rad2deg(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # random_
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
mod



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/math.py b/ivy/functional/frontends/paddle/math.py
--- a/ivy/functional/frontends/paddle/math.py
+++ b/ivy/functional/frontends/paddle/math.py
@@ -271,8 +271,14 @@ def floor_divide(x, y, name=None):
     return ivy.floor_divide(x, y)
 
 
-@with_supported_dtypes(
-    {"2.5.2 and below": ("float32", "float64", "int32", "int64")}, "paddle"
+@with_supported_device_and_dtypes(
+    {
+        "2.5.2 and below": {
+            "cpu": ("float32", "float64", "int32", "int64"),
+            "gpu": ("float16", "float32", "float64", "int32", "int64"),
+        }
+    },
+    "paddle",
 )
 @to_ivy_arrays_and_back
 def floor_mod(x, y, name=None):
@@ -667,3 +673,6 @@ def trace(x, offset=0, axis1=0, axis2=1, name=None):
 @to_ivy_arrays_and_back
 def trunc(x, name=None):
     return ivy.trunc(x)
+
+
+mod = remainder


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_math.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_math.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_math.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_math.py
@@ -1,5 +1,5 @@
 # global
-from hypothesis import strategies as st
+from hypothesis import strategies as st, assume
 import hypothesis.extra.numpy as nph
 import numpy as np
 import sys
@@ -1876,6 +1876,43 @@ def test_paddle_mm(
     )
 
 
+# mod
+@handle_frontend_test(
+    fn_tree="paddle.mod",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        num_arrays=2,
+        allow_inf=False,
+        large_abs_safety_factor=2,
+        small_abs_safety_factor=2,
+        safety_factor_scale="log",
+        shared_dtype=True,
+    ),
+)
+def test_paddle_mod(
+    *,
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    backend_fw,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    assume(not np.any(np.isclose(x[0], 0)))
+    assume(not np.any(np.isclose(x[1], 0)))
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        x=x[0],
+        y=x[1],
+    )
+
+
 # multiply
 @handle_frontend_test(
     fn_tree="paddle.multiply",
Repository: ivy-llc/ivy

Issue:
A Potential string comparison mistake in `ivy/func_wrapper.py`
In the file [`ivy\func_wrapper.py`](https://github.com/unifyai/ivy/blob/main/ivy/func_wrapper.py)
In the following line I think the comparison is not exactly correct.
https://github.com/unifyai/ivy/blob/5fcdab2e1c6d9849559e31ce0eb3749c311b6576/ivy/func_wrapper.py#L396
I'm not sure but think it should be `"Array"` instead of `"rray"`.


Discussion:

Resolving patch:
diff --git a/ivy/func_wrapper.py b/ivy/func_wrapper.py
--- a/ivy/func_wrapper.py
+++ b/ivy/func_wrapper.py
@@ -1316,7 +1316,7 @@ def _leaf_has_nans(x):
         return x.has_nans()
     elif ivy.is_array(x):
         return ivy.isnan(x).any()
-    elif x == float("nan"):
+    elif np.isnan(x):
         return True
     return False
 
diff --git a/ivy/functional/frontends/numpy/func_wrapper.py b/ivy/functional/frontends/numpy/func_wrapper.py
--- a/ivy/functional/frontends/numpy/func_wrapper.py
+++ b/ivy/functional/frontends/numpy/func_wrapper.py
@@ -243,10 +243,10 @@ def _from_zero_dim_arrays_to_scalar(*args, **kwargs):
                         ret_idx,
                         lambda x: np_frontend.numpy_dtype_to_scalar[ivy.dtype(x)](x),
                     )
-                except KeyError:
+                except KeyError as e:
                     raise ivy.utils.exceptions.IvyException(
                         "Casting to specified type is unsupported"
-                    )
+                    ) from e
                 return tuple(data)
             else:
                 # converting the scalar to float
@@ -254,10 +254,10 @@ def _from_zero_dim_arrays_to_scalar(*args, **kwargs):
                 if data.shape == ():
                     try:
                         return np_frontend.numpy_dtype_to_scalar[ivy.dtype(data)](data)
-                    except KeyError:
+                    except KeyError as e:
                         raise ivy.utils.exceptions.IvyException(
                             f"Casting to {ivy.dtype(data)} is unsupported"
-                        )
+                        ) from e
         return ret
 
     _from_zero_dim_arrays_to_scalar.from_zero_dim_arrays_to_scalar = True


Test patch:
Repository: ivy-llc/ivy

Issue:
Missing `logging` Import in `ivy\__init__.py`
In the file [`ivy\__init__.py`](https://github.com/unifyai/ivy/blob/main/ivy/__init__.py)
I noticed that the logging import is missing. This could potentially lead to issues with logging and debugging in the codebase.
For the following lines to work as intended I think the logging import should be added.
https://github.com/unifyai/ivy/blob/86afb43b97dab3ca2cd10f24bbe631a6cbfcdc6f/ivy/__init__.py#L1464
https://github.com/unifyai/ivy/blob/86afb43b97dab3ca2cd10f24bbe631a6cbfcdc6f/ivy/__init__.py#L1465
https://github.com/unifyai/ivy/blob/86afb43b97dab3ca2cd10f24bbe631a6cbfcdc6f/ivy/__init__.py#L1478
https://github.com/unifyai/ivy/blob/86afb43b97dab3ca2cd10f24bbe631a6cbfcdc6f/ivy/__init__.py#L1488


Discussion:

Resolving patch:
diff --git a/ivy/__init__.py b/ivy/__init__.py
--- a/ivy/__init__.py
+++ b/ivy/__init__.py
@@ -2,6 +2,7 @@
 import copy
 import re
 import warnings
+import logging
 import builtins
 import numpy as np
 import sys


Test patch:
Repository: ivy-llc/ivy

Issue:
tensor_scatter_nd_add



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/tensorflow/general_functions.py b/ivy/functional/frontends/tensorflow/general_functions.py
--- a/ivy/functional/frontends/tensorflow/general_functions.py
+++ b/ivy/functional/frontends/tensorflow/general_functions.py
@@ -586,6 +586,13 @@ def strided_slice(
     return ret
 
 
+@to_ivy_arrays_and_back
+def tensor_scatter_nd_add(tensor, indices, updates, name=None):
+    zero_tensor = ivy.zeros_like(tensor)
+    scatter_tensor = ivy.scatter_nd(indices, updates, zero_tensor.shape)
+    return ivy.add(tensor, scatter_tensor)
+
+
 @with_unsupported_dtypes({"2.14.0 and below": ("uint16",)}, "tensorflow")
 @to_ivy_arrays_and_back
 def tile(input, multiples, name=None):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_general_functions.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_general_functions.py
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_general_functions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_general_functions.py
@@ -2036,6 +2036,50 @@ def test_tensorflow_strided_slice(
         raise e
 
 
+# tensor_scatter_nd_add
+@handle_frontend_test(
+    fn_tree="tensorflow.tensor_scatter_nd_add",
+    all_arguments=_multiple_shape_helper(),
+    tensor=helpers.array_values(
+        dtype=helpers.get_dtypes("numeric"), shape=(8,), min_value=2, max_value=49
+    ),
+    indices=helpers.array_values(
+        dtype=helpers.get_dtypes("integer"), shape=(4, 1), min_value=0, max_value=7
+    ),
+    updates=helpers.array_values(
+        dtype=helpers.get_dtypes("integer"),
+        shape=(4,),
+        min_value=9,
+        max_value=12,
+    ),
+)
+def test_tensorflow_tensor_scatter_nd_add(
+    *,
+    all_arguments,
+    tensor,
+    indices,
+    updates,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+    backend_fw,
+):
+    input_dtype, input_matrix, dt_and_multiples = all_arguments
+    dt_mul, multiples = dt_and_multiples
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype + dt_mul,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        tensor=tensor[0],
+        indices=indices[0],
+        updates=updates[0],
+    )
+
+
 @handle_frontend_test(fn_tree="tensorflow.tile", all_arguments=_multiple_shape_helper())
 def test_tensorflow_tile(
     *,
Repository: ivy-llc/ivy

Issue:
Missing Parentheses after `super` calls at few places.
In the following places `super` is used without `parentheses`, which can lead to unexpected behavior in Python 3.
https://github.com/unifyai/ivy/blob/86afb43b97dab3ca2cd10f24bbe631a6cbfcdc6f/ivy/data_classes/container/base.py#L4008
https://github.com/unifyai/ivy/blob/86afb43b97dab3ca2cd10f24bbe631a6cbfcdc6f/ivy/data_classes/container/base.py#L4035
https://github.com/unifyai/ivy/blob/86afb43b97dab3ca2cd10f24bbe631a6cbfcdc6f/ivy_tests/test_ivy/helpers/globals.py#L66

`Parentheses` should be added after super to ensure correct behavior. I found these using [pylint](https://pylint.readthedocs.io/en/latest/user_guide/messages/warning/super-without-brackets.html).


Discussion:

Resolving patch:
diff --git a/ivy/data_classes/container/base.py b/ivy/data_classes/container/base.py
--- a/ivy/data_classes/container/base.py
+++ b/ivy/data_classes/container/base.py
@@ -3997,7 +3997,7 @@ def _add_newline(str_in):
         return new_dict
 
     def __dir__(self):
-        return list(super.__dir__(self)) + list(self.keys())
+        return list(super().__dir__()) + list(self.keys())
 
     # noinspection PyProtectedMember
     def __getattr__(self, item, *args, **kwargs):
@@ -4024,7 +4024,7 @@ def __setattr__(self, name, value):
         if name[0] != "_":
             self[name] = value
         else:
-            super.__setattr__(self, name, value)
+            super().__setattr__(name, value)
 
     def _get_queue_item(self, query):
         if isinstance(query, int):


Test patch:
diff --git a/ivy_tests/test_ivy/helpers/globals.py b/ivy_tests/test_ivy/helpers/globals.py
--- a/ivy_tests/test_ivy/helpers/globals.py
+++ b/ivy_tests/test_ivy/helpers/globals.py
@@ -62,7 +62,7 @@ class InterruptedTest(BaseException):
     """Indicate that a test tried to write global attributes while a test is running."""
 
     def __init__(self, test_interrupted):
-        super.__init__(f"{test_interrupted} was interrupted during execution.")
+        super().__init__(f"{test_interrupted} was interrupted during execution.")
 
 
 # Setup