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

Issue:
Fix Frontend Failing Test: torch - linalg.tensorflow.linalg.matrix_rank



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/linalg.py b/ivy/functional/frontends/torch/linalg.py
--- a/ivy/functional/frontends/torch/linalg.py
+++ b/ivy/functional/frontends/torch/linalg.py
@@ -190,8 +190,8 @@ def matrix_power(A, n, *, out=None):
 @with_supported_dtypes(
     {"2.2 and below": ("float32", "float64", "complex32", "complex64")}, "torch"
 )
-def matrix_rank(A, *, atol=None, rtol=None, hermitian=False, out=None):
-    return ivy.matrix_rank(A, atol=atol, rtol=rtol, hermitian=hermitian, out=out)
+def matrix_rank(input, *, atol=None, rtol=None, hermitian=False, out=None):
+    return ivy.matrix_rank(input, atol=atol, rtol=rtol, hermitian=hermitian, out=out)
 
 
 @to_ivy_arrays_and_back


Test patch:
diff --git a/ivy_tests/test_ivy/helpers/function_testing.py b/ivy_tests/test_ivy/helpers/function_testing.py
--- a/ivy_tests/test_ivy/helpers/function_testing.py
+++ b/ivy_tests/test_ivy/helpers/function_testing.py
@@ -806,6 +806,8 @@ def test_frontend_function(
         if True, test for the correctness of the resulting values.
     all_as_kwargs_np
         input arguments to the function as keyword arguments.
+        If an input argument has the same name as any other parameter
+        of this function, add "arg_" before the argument name.
 
     Returns
     -------
@@ -825,6 +827,10 @@ def test_frontend_function(
         test_flags.with_out = False
         test_flags.inplace = False
 
+    all_as_kwargs_np = {
+        k[4:] if k.startswith("arg_") else k: v for k, v in all_as_kwargs_np.items()
+    }
+
     # split the arguments into their positional and keyword components
     args_np, kwargs_np = kwargs_to_args_n_kwargs(
         num_positional_args=test_flags.num_positional_args, kwargs=all_as_kwargs_np
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -1002,9 +1002,11 @@ def test_torch_matrix_rank(
         test_flags=test_flags,
         fn_tree=fn_tree,
         on_device=on_device,
+        rtol=0,
+        atol=0,
         input=x,
-        rtol=rtol,
-        atol=atol,
+        arg_rtol=rtol,
+        arg_atol=atol,
         hermitian=hermitian,
     )
 
diff --git a/ivy_tests/test_ivy/test_functional/test_core/test_linalg.py b/ivy_tests/test_ivy/test_functional/test_core/test_linalg.py
--- a/ivy_tests/test_ivy/test_functional/test_core/test_linalg.py
+++ b/ivy_tests/test_ivy/test_functional/test_core/test_linalg.py
@@ -279,6 +279,9 @@ def _matrix_rank_helper(draw):
     )
     atol = draw(tol_strategy)
     rtol = draw(tol_strategy)
+    if not (atol is None or rtol is None):
+        assume(type(atol) is type(rtol))
+
     return dtype, x[0], hermitian, atol, rtol
Repository: ivy-llc/ivy

Issue:
Fix Ivy Failing Test: paddle - statistical.cummin



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/experimental/statistical.py b/ivy/functional/backends/paddle/experimental/statistical.py
--- a/ivy/functional/backends/paddle/experimental/statistical.py
+++ b/ivy/functional/backends/paddle/experimental/statistical.py
@@ -680,8 +680,17 @@ def __get_index(lst, indices=None, prefix=None):
     return indices
 
 
-@with_unsupported_device_and_dtypes(
-    {"2.6.0 and below": {"cpu": ("uint8", "int8", "int16")}},
+@with_supported_dtypes(
+    {
+        "2.6.0 and below": (
+            "complex",
+            "int32",
+            "int64",
+            "bfloat16",
+            "float32",
+            "float64",
+        )
+    },
     backend_version,
 )
 def cummin(
diff --git a/ivy/functional/backends/tensorflow/experimental/statistical.py b/ivy/functional/backends/tensorflow/experimental/statistical.py
--- a/ivy/functional/backends/tensorflow/experimental/statistical.py
+++ b/ivy/functional/backends/tensorflow/experimental/statistical.py
@@ -564,7 +564,7 @@ def __get_index(lst, indices=None, prefix=None):
 
 
 @with_unsupported_dtypes(
-    {"2.15.0 and below": ("bfloat16", "complex")},
+    {"2.15.0 and below": ("bfloat16", "bool", "complex")},
     backend_version,
 )
 def cummin(
diff --git a/ivy/functional/backends/torch/experimental/statistical.py b/ivy/functional/backends/torch/experimental/statistical.py
--- a/ivy/functional/backends/torch/experimental/statistical.py
+++ b/ivy/functional/backends/torch/experimental/statistical.py
@@ -630,7 +630,7 @@ def cummax(
 
 @with_unsupported_dtypes(
     {
-        "2.2 and below": ("uint8", "float16", "bfloat16"),
+        "2.2 and below": ("bool", "float16"),
         "1.12.1 and above": ("uint8", "float16"),
     },
     backend_version,


Test patch:
diff --git a/ivy_tests/test_ivy/test_functional/test_experimental/test_core/test_statistical.py b/ivy_tests/test_ivy/test_functional/test_experimental/test_core/test_statistical.py
--- a/ivy_tests/test_ivy/test_functional/test_experimental/test_core/test_statistical.py
+++ b/ivy_tests/test_ivy/test_functional/test_experimental/test_core/test_statistical.py
@@ -463,6 +463,7 @@ def test_cummax(
     dtype_x_axis_castable=_get_castable_dtype(),
     exclusive=st.booleans(),
     reverse=st.booleans(),
+    test_gradients=st.just(False),
 )
 def test_cummin(
     *,
Repository: ivy-llc/ivy

Issue:
 Fix Ivy Failing Test: paddle - searching.where
To-Do list #27501


Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/searching.py b/ivy/functional/backends/paddle/searching.py
--- a/ivy/functional/backends/paddle/searching.py
+++ b/ivy/functional/backends/paddle/searching.py
@@ -119,6 +119,7 @@ def nonzero(
     return res.T
 
 
+@with_unsupported_dtypes({"2.6.0 and below": ("bfloat16", "float16")}, backend_version)
 def where(
     condition: paddle.Tensor,
     x1: Union[float, int, paddle.Tensor],


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: torch - math.paddle.floor
To-do List: https://github.com/unifyai/ivy/issues/27498


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
@@ -257,9 +257,7 @@ def expm1(x, name=None):
     return ivy.expm1(x)
 
 
-@with_supported_dtypes(
-    {"2.6.0 and below": ("bfloat16", "float32", "float64")}, "paddle"
-)
+@with_supported_dtypes({"2.6.0 and below": ("float32", "float64")}, "paddle")
 @to_ivy_arrays_and_back
 def floor(x, name=None):
     return ivy.floor(x)


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Ivy Failing Test: jax - sorting.argsort
To-do List: https://github.com/unifyai/ivy/issues/27501


Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/jax/sorting.py b/ivy/functional/backends/jax/sorting.py
--- a/ivy/functional/backends/jax/sorting.py
+++ b/ivy/functional/backends/jax/sorting.py
@@ -20,7 +20,7 @@ def argsort(
 ) -> JaxArray:
     kind = "stable" if stable else "quicksort"
     return (
-        jnp.argsort(-x, axis=axis, kind=kind)
+        jnp.argsort(x, axis=axis, kind=kind, descending=descending)
         if descending
         else jnp.argsort(x, axis=axis, kind=kind)
     )


Test patch:
Repository: ivy-llc/ivy

Issue:
clip_vector_norm
To-Do List: https://github.com/unifyai/ivy/issues/791


Discussion:

Resolving patch:
diff --git a/ivy/functional/ivy/general.py b/ivy/functional/ivy/general.py
--- a/ivy/functional/ivy/general.py
+++ b/ivy/functional/ivy/general.py
@@ -1004,31 +1004,32 @@ def clip_vector_norm(
     >>> x = ivy.array([0., 1., 2.])
     >>> y = ivy.clip_vector_norm(x, 2.0)
     >>> print(y)
-    ivy.array([0.   , 0.894, 1.79 ])
+    ivy.array([0.        , 0.89442718, 1.78885436])
 
     >>> x = ivy.array([0.5, -0.7, 2.4])
     >>> y = ivy.clip_vector_norm(x, 3.0, p=1.0)
     >>> print(y)
-    ivy.array([ 0.417, -0.583,  2.   ])
+    ivy.array([ 0.41666666, -0.58333331,  2.        ])
 
     >>> x = ivy.array([[[0., 0.], [1., 3.], [2., 6.]],
     ...                [[3., 9.], [4., 12.], [5., 15.]]])
     >>> y = ivy.zeros(((2, 3, 2)))
     >>> ivy.clip_vector_norm(x, 4.0, p=1.0, out=y)
     >>> print(y)
-    ivy.array([[[0.    , 0.    ],
-                [0.0667, 0.2   ],
-                [0.133 , 0.4   ]],
-               [[0.2   , 0.6   ],
-                [0.267 , 0.8   ],
-                [0.333 , 1.    ]]])
+    ivy.array([[[0.        , 0.        ],
+        [0.06666667, 0.20000002],
+        [0.13333334, 0.40000004]],
+
+       [[0.20000002, 0.60000002],
+        [0.26666668, 0.80000007],
+        [0.33333334, 1.        ]]]))
 
     >>> x = ivy.array([[1.1, 2.2, 3.3],
     ...                [-4.4, -5.5, -6.6]])
     >>> ivy.clip_vector_norm(x, 1.0, p=3.0, out=x)
     >>> print(x)
-    ivy.array([[ 0.131,  0.263,  0.394],
-               [-0.526, -0.657, -0.788]])
+    ivy.array([[ 0.13137734,  0.26275468,  0.39413199],
+       [-0.52550936, -0.6568867 , -0.78826398]])
 
     With :class:`ivy.Container` input:
 
@@ -1037,8 +1038,8 @@ def clip_vector_norm(
     >>> y = ivy.clip_vector_norm(x, 2.0)
     >>> print(y)
     {
-        a: ivy.array([0., 0.894, 1.79]),
-        b: ivy.array([0.849, 1.13, 1.41])
+        a: ivy.array([0., 0.89442718, 1.78885436]),
+        b: ivy.array([0.84852815, 1.1313709, 1.41421366])
     }
 
     With multiple :class:`ivy.Container` inputs:
@@ -1049,7 +1050,7 @@ def clip_vector_norm(
     >>> y = ivy.clip_vector_norm(x, max_norm)
     >>> print(y)
     {
-        a: ivy.array([0., 0.894, 1.79]),
+        a: ivy.array([0., 0.89442718, 1.78885436]),
         b: ivy.array([1.27279221, 1.69705628, 2.12132034])
     }
     """


Test patch:
Repository: ivy-llc/ivy

Issue:
Fixed `ivy.equal` unsupported dtype at `paddle backend`



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/elementwise.py b/ivy/functional/backends/paddle/elementwise.py
--- a/ivy/functional/backends/paddle/elementwise.py
+++ b/ivy/functional/backends/paddle/elementwise.py
@@ -121,10 +121,6 @@ def isinf(
     return paddle.zeros(shape=x.shape, dtype=bool)
 
 
-@with_unsupported_device_and_dtypes(
-    {"2.6.0 and below": {"cpu": ("bfloat16", "complex128", "float64", "float32")}},
-    backend_version,
-)
 def equal(
     x1: Union[float, paddle.Tensor],
     x2: Union[float, paddle.Tensor],


Test patch:
diff --git a/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py b/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py
--- a/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py
+++ b/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py
@@ -694,7 +694,11 @@ def test_divide(*, dtype_and_x, test_flags, backend_fw, fn_name, on_device):
 @handle_test(
     fn_tree="functional.ivy.equal",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("valid", full=False), num_arrays=2
+        available_dtypes=helpers.get_dtypes("valid", full=False),
+        num_arrays=2,
+        large_abs_safety_factor=6,
+        small_abs_safety_factor=6,
+        safety_factor_scale="log",
     ),
     test_gradients=st.just(False),
 )
@@ -708,8 +712,8 @@ def test_equal(*, dtype_and_x, test_flags, backend_fw, fn_name, on_device):
         on_device=on_device,
         x1=x[0],
         x2=x[1],
-        atol_=1e-03,
-        rtol_=1e-03,
+        atol_=1e-02,
+        rtol_=1e-02,
     )
Repository: ivy-llc/ivy

Issue:
fix `ivy.less_equal` to support `complex` dtype and all dtype at `paddle backend`



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/elementwise.py b/ivy/functional/backends/paddle/elementwise.py
--- a/ivy/functional/backends/paddle/elementwise.py
+++ b/ivy/functional/backends/paddle/elementwise.py
@@ -140,8 +140,8 @@ def equal(
     return paddle.equal(x1, x2)
 
 
-@with_supported_dtypes(
-    {"2.6.0 and below": ("bool", "float32", "float64", "int32", "int64", "complex")},
+@with_unsupported_dtypes(
+    {"2.6.0 and below": ("bool",)},
     backend_version,
 )
 def less_equal(
@@ -154,9 +154,11 @@ def less_equal(
     x1, x2, ret_dtype = _elementwise_helper(x1, x2)
     if isinstance(x1, paddle.Tensor) and isinstance(x2, paddle.Tensor):
         if paddle.is_complex(x1) and paddle.is_complex(x2):
-            real = paddle.less_equal(x1.real(), x2.real())
-            imag = paddle.less_equal(x1.imag(), x2.imag())
-            return paddle_backend.logical_and(real, imag)
+            real_comparison = paddle.real(x1) < paddle.real(x2)
+            imag_comparison = paddle_backend.logical_and(
+                paddle.real(x1) == paddle.real(x2), paddle.imag(x1) < paddle.imag(x2)
+            )
+            return paddle_backend.logical_or(real_comparison, imag_comparison)
 
     return paddle.less_equal(x1, x2)
 
diff --git a/ivy/functional/backends/tensorflow/elementwise.py b/ivy/functional/backends/tensorflow/elementwise.py
--- a/ivy/functional/backends/tensorflow/elementwise.py
+++ b/ivy/functional/backends/tensorflow/elementwise.py
@@ -423,7 +423,7 @@ def less(
     return tf.math.less(x1, x2)
 
 
-@with_unsupported_dtypes({"2.15.0 and below": ("complex",)}, backend_version)
+@with_unsupported_dtypes({"2.15.0 and below": ("complex", "bool")}, backend_version)
 def less_equal(
     x1: Union[float, tf.Tensor, tf.Variable],
     x2: Union[float, tf.Tensor, tf.Variable],


Test patch:
diff --git a/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py b/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py
--- a/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py
+++ b/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py
@@ -1183,7 +1183,11 @@ def test_less(*, dtype_and_x, test_flags, backend_fw, fn_name, on_device):
 @handle_test(
     fn_tree="functional.ivy.less_equal",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("numeric"), num_arrays=2
+        available_dtypes=helpers.get_dtypes("numeric"),
+        num_arrays=2,
+        large_abs_safety_factor=6,
+        small_abs_safety_factor=6,
+        safety_factor_scale="log",
     ),
     test_gradients=st.just(False),
     ground_truth_backend="jax",
Repository: ivy-llc/ivy

Issue:
fix the `ivy.not_equal` to support the float dtype and  numeric dtype 



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/elementwise.py b/ivy/functional/backends/paddle/elementwise.py
--- a/ivy/functional/backends/paddle/elementwise.py
+++ b/ivy/functional/backends/paddle/elementwise.py
@@ -613,10 +613,6 @@ def negative(
     return paddle.neg(x)
 
 
-@with_unsupported_device_and_dtypes(
-    {"2.6.0 and below": {"cpu": ("bfloat16", "complex128", "float64", "float32")}},
-    backend_version,
-)
 def not_equal(
     x1: Union[float, paddle.Tensor],
     x2: Union[float, paddle.Tensor],


Test patch:
diff --git a/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py b/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py
--- a/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py
+++ b/ivy_tests/test_ivy/test_functional/test_core/test_elementwise.py
@@ -1587,7 +1587,11 @@ def test_negative(*, dtype_and_x, test_flags, backend_fw, fn_name, on_device):
 @handle_test(
     fn_tree="functional.ivy.not_equal",
     dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("valid", full=False), num_arrays=2
+        available_dtypes=helpers.get_dtypes("valid", full=False),
+        num_arrays=2,
+        large_abs_safety_factor=8,
+        small_abs_safety_factor=8,
+        safety_factor_scale="log",
     ),
     test_gradients=st.just(False),
 )
@@ -1602,8 +1606,8 @@ def test_not_equal(*, dtype_and_x, test_flags, backend_fw, fn_name, on_device):
         on_device=on_device,
         x1=x[0],
         x2=x[1],
-        atol_=1e-03,
-        rtol_=1e-03,
+        atol_=1e-02,
+        rtol_=1e-02,
     )
Repository: ivy-llc/ivy

Issue:
fix the `IvyValueError` at `sklearn frontend` 



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/sklearn/metrics/_classification.py b/ivy/functional/frontends/sklearn/metrics/_classification.py
--- a/ivy/functional/frontends/sklearn/metrics/_classification.py
+++ b/ivy/functional/frontends/sklearn/metrics/_classification.py
@@ -1,6 +1,7 @@
 import ivy
 from ivy.functional.frontends.numpy.func_wrapper import to_ivy_arrays_and_back
 from sklearn.utils.multiclass import type_of_target
+from ivy.utils.exceptions import IvyValueError
 
 
 @to_ivy_arrays_and_back


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix `ivy.logical_not` support for bfloat16 at `paddle backend`



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/elementwise.py b/ivy/functional/backends/paddle/elementwise.py
--- a/ivy/functional/backends/paddle/elementwise.py
+++ b/ivy/functional/backends/paddle/elementwise.py
@@ -377,14 +377,12 @@ def cos(x: paddle.Tensor, /, *, out: Optional[paddle.Tensor] = None) -> paddle.T
     return paddle.cos(x)
 
 
-@with_unsupported_dtypes({"2.6.0 and below": ("uint8", "float16")}, backend_version)
+@with_unsupported_dtypes(
+    {"2.6.0 and below": ("uint8", "float16", "bfloat16")}, backend_version
+)
 def logical_not(
     x: paddle.Tensor, /, *, out: Optional[paddle.Tensor] = None
 ) -> paddle.Tensor:
-    if paddle.is_complex(x):
-        return paddle.logical_and(
-            paddle.logical_not(x.real()), paddle.logical_not(x.imag())
-        )
     return paddle.logical_not(x)
 
 


Test patch:
Repository: ivy-llc/ivy

Issue:
 Fix Ivy Failing Test: paddle - sorting.msort
To-do List: https://github.com/unifyai/ivy/issues/27501


Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/sorting.py b/ivy/functional/backends/paddle/sorting.py
--- a/ivy/functional/backends/paddle/sorting.py
+++ b/ivy/functional/backends/paddle/sorting.py
@@ -74,7 +74,11 @@ def searchsorted(
 
 
 @with_unsupported_device_and_dtypes(
-    {"2.6.0 and below": {"cpu": ("int8", "uint8", "int16", "float16", "complex")}},
+    {
+        "2.6.0 and below": {
+            "cpu": ("int8", "uint8", "int16", "float16", "bfloat16", "complex")
+        }
+    },
     backend_version,
 )
 def msort(


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: jax - manipulation.paddle.tile



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/manipulation.py b/ivy/functional/frontends/paddle/manipulation.py
--- a/ivy/functional/frontends/paddle/manipulation.py
+++ b/ivy/functional/frontends/paddle/manipulation.py
@@ -208,7 +208,7 @@ def take_along_axis(arr, indices, axis):
 
 
 @with_unsupported_dtypes(
-    {"2.6.0 and below": ("int8", "uint8", "int16", "float16")},
+    {"2.6.0 and below": ("int8", "uint8", "int16", "float16", "bfloat16")},
     "paddle",
 )
 @to_ivy_arrays_and_back


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: jax - reduction_ops.torch.mean



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/reduction_ops.py b/ivy/functional/frontends/torch/reduction_ops.py
--- a/ivy/functional/frontends/torch/reduction_ops.py
+++ b/ivy/functional/frontends/torch/reduction_ops.py
@@ -135,6 +135,19 @@ def max(*input, dim=None, keepdim=False, out=None):
 
 @numpy_to_torch_style_args
 @to_ivy_arrays_and_back
+@with_supported_dtypes(
+    {
+        "2.2.1 and below": (
+            "bfloat16",
+            "float16",
+            "float32",
+            "float64",
+            "complex64",
+            "complex128",
+        )
+    },
+    "torch",
+)
 def mean(input, dim=None, keepdim=False, *, dtype=None, out=None):
     if dtype is not None:
         input = input.astype(dtype)


Test patch:
diff --git a/ivy_tests/test_ivy/test_functional/test_core/test_statistical.py b/ivy_tests/test_ivy/test_functional/test_core/test_statistical.py
--- a/ivy_tests/test_ivy/test_functional/test_core/test_statistical.py
+++ b/ivy_tests/test_ivy/test_functional/test_core/test_statistical.py
@@ -63,10 +63,9 @@ def _statistical_dtype_values(draw, *, function, min_value=None, max_value=None)
     shape = values[0].shape
     size = values[0].size
     max_correction = np.min(shape)
-    if "complex" in dtype[0]:
-        # TODO skip complex median test until added ?
-        #  because it is not supported in tensorflow (ground truth backend)
-        dtype = ["float32"]
+    # TODO skip complex median test until added ?
+    #  because it is not supported in tensorflow (ground truth backend)
+    assume("complex" not in dtype[0])
     if any(ele in function for ele in ["std", "var"]):
         if size == 1:
             correction = 0
Repository: ivy-llc/ivy

Issue:
fix `greater_equal` at `tf frontend`



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/tensorflow/math.py b/ivy/functional/frontends/tensorflow/math.py
--- a/ivy/functional/frontends/tensorflow/math.py
+++ b/ivy/functional/frontends/tensorflow/math.py
@@ -464,6 +464,9 @@ def greater(x, y, name=None):
     return ivy.greater(x, y)
 
 
+@with_unsupported_dtypes(
+    {"2.15.0 and below": ("complex64", "complex128")}, "tensorflow"
+)
 @to_ivy_arrays_and_back
 def greater_equal(x, y, name=None):
     x, y = check_tensorflow_casting(x, y)


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: tensorflow - operators.jax.lax.real



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/elementwise.py b/ivy/functional/backends/paddle/elementwise.py
--- a/ivy/functional/backends/paddle/elementwise.py
+++ b/ivy/functional/backends/paddle/elementwise.py
@@ -886,22 +886,8 @@ def logaddexp2(
         return ivy.log2(ivy.exp2(x1) + ivy.exp2(x2))
 
 
-@with_unsupported_device_and_dtypes(
-    {
-        "2.6.0 and below": {
-            "cpu": (
-                "int8",
-                "int16",
-                "int32",
-                "int64",
-                "uint8",
-                "float16",
-                "float32",
-                "float64",
-                "bool",
-            )
-        }
-    },
+@with_supported_dtypes(
+    {"2.6.0 and below": ("complex",)},
     backend_version,
 )
 def real(x: paddle.Tensor, /, *, out: Optional[paddle.Tensor] = None) -> paddle.Tensor:


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: tensorflow - non_linear_activations.jax.nn.softplus



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/activations.py b/ivy/functional/backends/paddle/activations.py
--- a/ivy/functional/backends/paddle/activations.py
+++ b/ivy/functional/backends/paddle/activations.py
@@ -117,6 +117,9 @@ def softmax(
     return paddle.divide(exp_x, paddle.sum(exp_x, axis=axis, keepdim=True))
 
 
+@with_unsupported_device_and_dtypes(
+    {"2.6.0 and below": {"cpu": ("float16", "bfloat16")}}, backend_version
+)
 def softplus(
     x: paddle.Tensor,
     /,


Test patch: