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

Issue:
 Fix Frontend Failing Test: paddle - math.paddle.pow
To-do List: https://github.com/unifyai/ivy/issues/27500


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
@@ -514,7 +514,9 @@ def outer(x, y, name=None):
     return ivy.outer(x, y)
 
 
-@with_unsupported_dtypes({"2.6.0 and below": ("float16", "bfloat16")}, "paddle")
+@with_supported_dtypes(
+    {"2.6.0 and below": ("float16", "float32", "float64", "int32", "int64")}, "paddle"
+)
 @to_ivy_arrays_and_back
 def pow(x, y, name=None):
     return ivy.pow(x, y)


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: paddle - raw_ops.tensorflow.raw_ops.Equal
To-do List: https://github.com/unifyai/ivy/issues/27500




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
@@ -120,6 +120,9 @@ def isinf(
     return paddle.zeros(shape=x.shape, dtype=bool)
 
 
+@with_supported_dtypes(
+    {"2.6.0 and below": ("float32", "float64", "int32", "int64")}, backend_version
+)
 def equal(
     x1: Union[float, paddle.Tensor],
     x2: Union[float, paddle.Tensor],


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: paddle - attribute.paddle.real
To-do List: https://github.com/unifyai/ivy/issues/27500


Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/attribute.py b/ivy/functional/frontends/paddle/attribute.py
--- a/ivy/functional/frontends/paddle/attribute.py
+++ b/ivy/functional/frontends/paddle/attribute.py
@@ -1,5 +1,6 @@
 # global
 import ivy
+from ivy.func_wrapper import with_supported_dtypes
 from ivy.functional.frontends.paddle.func_wrapper import (
     to_ivy_arrays_and_back,
 )
@@ -30,6 +31,15 @@ def rank(input):
     return ivy.get_num_dims(input)
 
 
+@with_supported_dtypes(
+    {
+        "2.6.0 and below": (
+            "complex64",
+            "complex128",
+        )
+    },
+    "paddle",
+)
 @to_ivy_arrays_and_back
 def real(x):
     return ivy.real(x)


Test patch:
Repository: ivy-llc/ivy

Issue:
 Fix Frontend Failing Test: torch - linalg.torch.linalg.norm
Example of failed tests:

==================================================================================== 20.0% of 5 passed ====================================================================================================================================================================== short test summary info ==================================================================================
FAILED ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py::test_torch_norm[cpu-jax-False-False] - ivy.utils.exceptions.IvyValueError: jax: matrix_norm: Invalid axis values ((0, 1, 2)) for jnp.linalg.norm.
FAILED ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py::test_torch_norm[cpu-tensorflow-False-False] - ivy.utils.exceptions.IvyValueError: tensorflow: matrix_norm: 'axis' must be None, an integer, or a tuple of 2 unique integers, got (0, 1, 2)
FAILED ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py::test_torch_norm[cpu-torch-False-False] - ivy.utils.exceptions.IvyBackendException: torch: matrix_norm: linalg.matrix_norm: dim must be a 2-tuple. Got 0 1 2
FAILED ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py::test_torch_norm[cpu-paddle-False-False] - RuntimeError: linalg.norm: If dim is specified, it must be of length 1 or 2. Got [0, 1, 2]


Issue: torch.linalg.norm can take axis of length 1 or 2 (in addition to None). Test allows for axis of length upto 5.


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
@@ -215,10 +215,14 @@ def norm(input, ord=None, dim=None, keepdim=False, *, dtype=None, out=None):
     elif dim is None and ord is None:
         input = ivy.flatten(input)
         ret = ivy.vector_norm(input, axis=0, keepdims=keepdim, ord=2)
-    if isinstance(dim, int):
+    elif isinstance(dim, int):
         ret = ivy.vector_norm(input, axis=dim, keepdims=keepdim, ord=ord)
-    elif isinstance(dim, tuple):
+    elif isinstance(dim, tuple) and len(dim) <= 2:
         ret = ivy.matrix_norm(input, axis=dim, keepdims=keepdim, ord=ord)
+    elif isinstance(dim, tuple) and len(dim) > 2:
+        raise RuntimeError(
+            f"linalg.norm: If dim is specified, it must be of length 1 or 2. Got {dim}"
+        )
     return ret
 
 


Test patch:
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
@@ -68,7 +68,7 @@ def _get_axis_and_p(draw):
         min_axes_size = 2
     else:
         min_axes_size = 1
-        max_axes_size = 5
+        max_axes_size = 2
     x_dtype, values, axis = draw(
         helpers.dtype_values_axis(
             available_dtypes=helpers.get_dtypes("valid"),
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: paddle - comparison.numpy.less_equal
To-do List: https://github.com/unifyai/ivy/issues/27500


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
@@ -155,8 +155,8 @@ def less_equal(
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
     x1, x2, ret_dtype = _elementwise_helper(x1, x2)
-    if paddle.is_complex(x1):
-        if paddle.is_complex(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)
@@ -335,10 +335,11 @@ def less(
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
     x1, x2, ret_dtype = _elementwise_helper(x1, x2)
-    if paddle.is_complex(x1):
-        real = paddle.less_than(x1.real(), x2.real())
-        imag = paddle.less_than(x1.imag(), x2.imag())
-        return logical_and(real, imag)
+    if isinstance(x1, paddle.Tensor) and isinstance(x2, paddle.Tensor):
+        if paddle.is_complex(x1) and paddle.is_complex(x2):
+            real = paddle.less_than(x1.real(), x2.real())
+            imag = paddle.less_than(x1.imag(), x2.imag())
+            return logical_and(real, imag)
 
     return paddle.less_than(x1, x2)
 


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: paddle - comparison.numpy.greater
To-do List: https://github.com/unifyai/ivy/issues/27500


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
@@ -457,8 +457,8 @@ def greater(
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
     x1, x2, ret_dtype = _elementwise_helper(x1, x2)
-    if paddle.is_complex(x1):
-        if paddle.is_complex(x1):
+    if isinstance(x1, paddle.Tensor) and isinstance(x2, paddle.Tensor):
+        if paddle.is_complex(x1) and paddle.is_complex(x2):
             real = paddle.greater_than(x1.real(), x2.real())
             imag = paddle.greater_than(x1.imag(), x2.imag())
             return paddle.logical_and(real, imag)
@@ -487,8 +487,8 @@ def greater_equal(
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
     x1, x2, ret_dtype = _elementwise_helper(x1, x2)
-    if paddle.is_complex(x1):
-        if paddle.is_complex(x1):
+    if isinstance(x1, paddle.Tensor) and isinstance(x2, paddle.Tensor):
+        if paddle.is_complex(x1) and paddle.is_complex(x2):
             real = paddle.greater_equal(x1.real(), x2.real())
             imag = paddle.greater_equal(x1.imag(), x2.imag())
             return paddle.logical_and(real, imag)


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: tensorflow - pointwise_ops.torch.real
To-do List: https://github.com/unifyai/ivy/issues/27499


Discussion:

Resolving patch:
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
@@ -486,7 +486,7 @@ def logaddexp(
     return tf.experimental.numpy.logaddexp(x1, x2)
 
 
-@with_unsupported_dtypes({"2.15.0 and below": ("float16",)}, backend_version)
+@with_unsupported_dtypes({"2.15.0 and below": ("bool",)}, backend_version)
 def real(
     x: Union[tf.Tensor, tf.Variable],
     /,


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Ivy Failing Test: paddle - elementwise.fmod



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
@@ -1182,6 +1182,10 @@ def isreal(
         return paddle.ones_like(x, dtype="bool")
 
 
+@with_supported_dtypes(
+    {"2.6.0 and below": ("float32", "float64", "int32", "int64", "complex")},
+    backend_version,
+)
 def fmod(
     x1: paddle.Tensor,
     x2: paddle.Tensor,


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Ivy Failing Test: paddle - elementwise.rad2deg



Discussion:

Resolving patch:
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
@@ -872,6 +872,7 @@ def deg2rad(
     return radians
 
 
+@with_supported_dtypes({"2.15.0 and below": ("float",)}, backend_version)
 def rad2deg(
     x: Union[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
@@ -1636,9 +1636,7 @@ def test_pow(*, dtype_and_x, test_flags, backend_fw, fn_name, on_device):
 
 @handle_test(
     fn_tree="functional.ivy.rad2deg",
-    dtype_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("numeric")
-    ),
+    dtype_and_x=helpers.dtype_and_values(available_dtypes=helpers.get_dtypes("valid")),
 )
 def test_rad2deg(*, dtype_and_x, test_flags, backend_fw, fn_name, on_device):
     input_dtype, x = dtype_and_x
@@ -1646,6 +1644,8 @@ def test_rad2deg(*, dtype_and_x, test_flags, backend_fw, fn_name, on_device):
         input_dtypes=input_dtype,
         test_flags=test_flags,
         backend_to_test=backend_fw,
+        rtol_=1e-2,
+        atol_=1e-2,
         fn_name=fn_name,
         on_device=on_device,
         x=x[0],
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: paddle - mathematical_functions.jax.numpy.fmin



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
@@ -291,7 +291,9 @@ def fmax(x, y, name=None):
     return ivy.fmax(x, y)
 
 
-@with_unsupported_dtypes({"2.6.0 and below": "bfloat16"}, "paddle")
+@with_supported_dtypes(
+    {"2.6.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
+)
 @to_ivy_arrays_and_back
 def fmin(x, y, name=None):
     return ivy.fmin(x, y)


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
@@ -1165,7 +1165,7 @@ def test_paddle_fmax(
 @handle_frontend_test(
     fn_tree="paddle.fmin",
     dtypes_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float"), num_arrays=2, shared_dtype=True
+        available_dtypes=helpers.get_dtypes("valid"), num_arrays=2, shared_dtype=True
     ),
 )
 def test_paddle_fmin(
Repository: ivy-llc/ivy

Issue:
 Fix Frontend Failing Test: paddle - mathematical_functions.jax.numpy.fmax



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
@@ -285,7 +285,9 @@ def floor_mod(x, y, name=None):
     return ivy.remainder(x, y)
 
 
-@with_unsupported_dtypes({"2.6.0 and below": "bfloat16"}, "paddle")
+@with_supported_dtypes(
+    {"2.6.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
+)
 @to_ivy_arrays_and_back
 def fmax(x, y, name=None):
     return ivy.fmax(x, y)


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
@@ -1137,7 +1137,7 @@ def test_paddle_floor_mod(
 @handle_frontend_test(
     fn_tree="paddle.fmax",
     dtypes_and_x=helpers.dtype_and_values(
-        available_dtypes=helpers.get_dtypes("float"), num_arrays=2, shared_dtype=True
+        available_dtypes=helpers.get_dtypes("valid"), num_arrays=2, shared_dtype=True
     ),
 )
 def test_paddle_fmax(
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: paddle - pointwise_ops.torch.copysign
To-do List: https://github.com/unifyai/ivy/issues/27500


Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/experimental/elementwise.py b/ivy/functional/backends/paddle/experimental/elementwise.py
--- a/ivy/functional/backends/paddle/experimental/elementwise.py
+++ b/ivy/functional/backends/paddle/experimental/elementwise.py
@@ -137,6 +137,9 @@ def ldexp(
         return ivy.astype(ret, out_dtype, copy=False)
 
 
+@with_unsupported_device_and_dtypes(
+    {"2.6.0 and below": {"cpu": ("float16", "bfloat16")}}, backend_version
+)
 def copysign(
     x1: Union[paddle.Tensor, Number],
     x2: Union[paddle.Tensor, Number],


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: paddle - pointwise_ops.torch.signbit
To-do List: https://github.com/unifyai/ivy/issues/27500


Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/experimental/elementwise.py b/ivy/functional/backends/paddle/experimental/elementwise.py
--- a/ivy/functional/backends/paddle/experimental/elementwise.py
+++ b/ivy/functional/backends/paddle/experimental/elementwise.py
@@ -214,6 +214,9 @@ def _tensor(val):
     )
 
 
+@with_unsupported_device_and_dtypes(
+    {"2.6.0 and below": {"cpu": ("float16",)}}, backend_version
+)
 def signbit(
     x: Union[paddle.Tensor, float, int, list, tuple],
     /,


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix Frontend Failing Test: paddle - pointwise_ops.torch.i0
To-do List: https://github.com/unifyai/ivy/issues/27500


Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/experimental/manipulation.py b/ivy/functional/backends/paddle/experimental/manipulation.py
--- a/ivy/functional/backends/paddle/experimental/manipulation.py
+++ b/ivy/functional/backends/paddle/experimental/manipulation.py
@@ -311,6 +311,10 @@ def fliplr(
     return paddle.flip(m, axis=1)
 
 
+@with_unsupported_dtypes(
+    {"2.6.0 and below": ("bfloat16", "float16")},
+    backend_version,
+)
 def i0(
     x: paddle.Tensor,
     /,


Test patch:
Repository: ivy-llc/ivy

Issue:
 Fix Ivy Failing Test: paddle - creation.ones_like



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/creation.py b/ivy/functional/backends/paddle/creation.py
--- a/ivy/functional/backends/paddle/creation.py
+++ b/ivy/functional/backends/paddle/creation.py
@@ -11,6 +11,7 @@
 import ivy
 from ivy.func_wrapper import (
     with_unsupported_device_and_dtypes,
+    with_supported_device_and_dtypes,
 )
 from ivy.functional.ivy.creation import (
     _asarray_to_native_arrays_and_back,
@@ -471,6 +472,22 @@ def ones(
     return paddle.ones(shape=shape).cast(dtype)
 
 
+@with_supported_device_and_dtypes(
+    {
+        "2.6.0 and below": {
+            "cpu": (
+                "int32",
+                "int64",
+                "float64",
+                "float32",
+                "complex128",
+                "complex64",
+                "bool",
+            )
+        }
+    },
+    backend_version,
+)
 def ones_like(
     x: paddle.Tensor,
     /,


Test patch:
Repository: ivy-llc/ivy

Issue:
set_default_device
To-do List: https://github.com/unifyai/ivy/issues/814


Discussion:

Resolving patch:
diff --git a/ivy/functional/ivy/device.py b/ivy/functional/ivy/device.py
--- a/ivy/functional/ivy/device.py
+++ b/ivy/functional/ivy/device.py
@@ -826,30 +826,47 @@ def default_device(
 
 @handle_exceptions
 def set_default_device(device: Union[ivy.Device, ivy.NativeDevice], /) -> None:
-    """Set the default device to given device instance.
+    """Sets the default device to the argument provided in the function.
 
     Parameters
     ----------
     device
-        The device to set as the default device
+        The device to be set as the default device.
+
+    Returns
+    -------
+    ret
+        The new default device.
 
     Examples
     --------
-    >>> ivy.set_default_device("cpu")
     >>> ivy.default_device()
     'cpu'
 
-    >>> ivy.set_backend("torch")
-    >>> ivy.set_default_device("gpu:0")
-    >>> ivy.default_device(as_native=True)
-    device(type='cuda', index=0)
+    >>> ivy.set_backend('jax')
+    >>> ivy.set_default_device('gpu:0')
+    >>> ivy.default_device()
+    'gpu:0'
 
-    >>> import torch
-    >>> ivy.set_backend("torch")
-    >>> device = torch.device("cuda")
-    >>> ivy.set_default_device(device)
-    >>> ivy.default_device(as_native=True)
-    device(type='cuda')
+    >>> ivy.set_backend('torch')
+    >>> ivy.set_default_device('gpu:1')
+    >>> ivy.default_device()
+    'gpu:1
+
+    >>> ivy.set_backend('tensorflow')
+    >>> ivy.set_default_device('tpu:0)
+    >>> ivy.default_device()
+    'tpu:0
+
+    >>> ivy.set_backend('paddle')
+    >>> ivy.set_default_device('cpu)
+    >>> ivy.default_device()
+    'cpu'
+
+    >>> ivy.set_backend('mxnet')
+    >>> ivy.set_default_device('cpu')
+    >>> ivy.default_device()
+    'cpu'
     """
     global default_device_stack
     default_device_stack.append(device)


Test patch:
Repository: ivy-llc/ivy

Issue:
GatherNd



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/tensorflow/raw_ops.py b/ivy/functional/frontends/tensorflow/raw_ops.py
--- a/ivy/functional/frontends/tensorflow/raw_ops.py
+++ b/ivy/functional/frontends/tensorflow/raw_ops.py
@@ -619,6 +619,15 @@ def Gather(*, params, indices, validate_indices=None, name="Gather"):
     return ivy.gather(params, indices, axis=0, batch_dims=0)
 
 
+@with_supported_dtypes(
+    {"2.15.0 and below": ("int32", "int64", "float32", "float64")},
+    "tensorflow",
+)
+@to_ivy_arrays_and_back
+def GatherNd(*, params, indices, name=None):
+    return ivy.gather_nd(params, indices, batch_dims=0)
+
+
 @to_ivy_arrays_and_back
 def Greater(*, x, y, name="Greater"):
     x, y = check_tensorflow_casting(x, y)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
@@ -2132,6 +2132,44 @@ def test_tensorflow_Gather(  # NOQA
     )
 
 
+# GatherNd
+@handle_frontend_test(
+    fn_tree="tensorflow.raw_ops.GatherNd",
+    params_indices_axis_batch_dims=helpers.array_indices_axis(
+        array_dtypes=helpers.get_dtypes("valid"),
+        indices_dtypes=["int32", "int64"],
+        min_num_dims=3,
+        max_num_dims=3,
+        min_dim_size=3,
+        max_dim_size=3,
+        axis_zero=True,
+        disable_random_axis=True,
+        indices_same_dims=True,
+    ),
+    test_with_out=st.just(False),
+)
+def test_tensorflow_GatherNd(
+    *,
+    params_indices_axis_batch_dims,
+    frontend,
+    test_flags,
+    fn_tree,
+    backend_fw,
+    on_device,
+):
+    input_dtypes, params, indices = params_indices_axis_batch_dims
+    helpers.test_frontend_function(
+        input_dtypes=input_dtypes,
+        backend_to_test=backend_fw,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        params=params,
+        indices=indices,
+    )
+
+
 # Greater
 @handle_frontend_test(
     fn_tree="tensorflow.raw_ops.Greater",
Repository: ivy-llc/ivy

Issue:
__mod__



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
@@ -264,6 +264,10 @@ def __int__(self):
     def __long__(self):
         return int(self._ivy_array)
 
+    @with_supported_dtypes({"2.6.0 and below": ("int32", "int64")}, "paddle")
+    def __mod__(self, y, /, name=None):
+        return paddle_frontend.Tensor(ivy.fmod(self._ivy_array, _to_ivy_array(y)))
+
     # Instance Methods #
     # ---------------- #
 


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
@@ -918,6 +918,47 @@ def test_paddle___lt__(
     )
 
 
+# __mod__
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="__mod__",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        num_arrays=2,
+        shared_dtype=True,
+        min_value=0,
+        exclude_min=True,
+    ),
+)
+def test_paddle___mod__(
+    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={
+            "y": x[1],
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # __mul__
 @handle_frontend_method(
     class_tree=CLASS_TREE,