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

Issue:
allclose



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/logic.py b/ivy/functional/frontends/paddle/tensor/logic.py
--- a/ivy/functional/frontends/paddle/tensor/logic.py
+++ b/ivy/functional/frontends/paddle/tensor/logic.py
@@ -196,3 +196,25 @@ def bitwise_and(x, y, /, *, name=None, out=None):
 @handle_out_argument
 def bitwise_xor(x, y, /, *, name=None, out=None):
     return ivy.bitwise_xor(x, y, out=out)
+
+
+@with_supported_dtypes(
+    {
+        "2.4.2 and below": (
+            "float32",
+            "float64",
+            "bool",
+            "uint8",
+            "int8",
+            "int16",
+            "int32",
+            "int64",
+        )
+    },
+    "paddle",
+)
+@to_ivy_arrays_and_back
+@handle_out_argument
+def allclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
+    ret = ivy.allclose(x, y, rtol=rtol, atol=atol, equal_nan=equal_nan)
+    return paddle.to_tensor([ret])


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py
@@ -380,3 +380,35 @@ def test_paddle_bitwise_xor(
         x=x[0],
         y=x[1],
     )
+
+
+# allclose
+@handle_frontend_test(
+    fn_tree="paddle.allclose",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+    equal_nan=st.booleans(),
+)
+def test_paddle_allclose(
+    *,
+    dtype_and_x,
+    equal_nan,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        x=x[0],
+        y=x[1],
+        equal_nan=equal_nan,
+    )
Repository: ivy-llc/ivy

Issue:
isclose



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/logic.py b/ivy/functional/frontends/paddle/tensor/logic.py
--- a/ivy/functional/frontends/paddle/tensor/logic.py
+++ b/ivy/functional/frontends/paddle/tensor/logic.py
@@ -223,3 +223,17 @@ def allclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
 @to_ivy_arrays_and_back
 def is_tensor(x):
     return ivy.is_array(x)
+
+
+@with_supported_dtypes(
+    {
+        "2.4.2 and below": (
+            "float32",
+            "float64",
+        )
+    },
+    "paddle",
+)
+@to_ivy_arrays_and_back
+def isclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
+    return ivy.isclose(x, y, rtol=rtol, atol=atol, equal_nan=equal_nan)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py
@@ -436,3 +436,35 @@ def test_paddle_is_tensor(
         fn_tree=fn_tree,
         x=x[0],
     )
+
+
+# isclose
+@handle_frontend_test(
+    fn_tree="paddle.isclose",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+    equal_nan=st.booleans(),
+)
+def test_paddle_isclose(
+    *,
+    dtype_and_x,
+    equal_nan,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        x=x[0],
+        y=x[1],
+        equal_nan=equal_nan,
+    )
Repository: ivy-llc/ivy

Issue:
is_tensor



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/logic.py b/ivy/functional/frontends/paddle/tensor/logic.py
--- a/ivy/functional/frontends/paddle/tensor/logic.py
+++ b/ivy/functional/frontends/paddle/tensor/logic.py
@@ -218,3 +218,8 @@ def bitwise_xor(x, y, /, *, name=None, out=None):
 def allclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
     ret = ivy.allclose(x, y, rtol=rtol, atol=atol, equal_nan=equal_nan)
     return paddle.to_tensor([ret])
+
+
+@to_ivy_arrays_and_back
+def is_tensor(x):
+    return ivy.is_array(x)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_logic.py
@@ -412,3 +412,27 @@ def test_paddle_allclose(
         y=x[1],
         equal_nan=equal_nan,
     )
+
+
+# is_tensor
+@handle_frontend_test(
+    fn_tree="paddle.is_tensor",
+    dtype_and_x=helpers.dtype_and_values(available_dtypes=helpers.get_dtypes("valid")),
+)
+def test_paddle_is_tensor(
+    *,
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        on_device=on_device,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        x=x[0],
+    )
Repository: ivy-llc/ivy

Issue:
deg2rad



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/math.py b/ivy/functional/frontends/paddle/tensor/math.py
--- a/ivy/functional/frontends/paddle/tensor/math.py
+++ b/ivy/functional/frontends/paddle/tensor/math.py
@@ -158,6 +158,12 @@ def rad2deg(x, name=None):
     return ivy.rad2deg(x)
 
 
+@with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
+@to_ivy_arrays_and_back
+def deg2rad(x, name=None):
+    return ivy.deg2rad(x)
+
+
 @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
 @to_ivy_arrays_and_back
 def tan(x, name=None):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_math.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_math.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_math.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_math.py
@@ -697,6 +697,32 @@ def test_paddle_rad2deg(
     )
 
 
+# deg2rad
+@handle_frontend_test(
+    fn_tree="paddle.deg2rad",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_paddle_deg2rad(
+    *,
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        x=x[0],
+    )
+
+
 # tan
 @handle_frontend_test(
     fn_tree="paddle.tensor.math.tan",
Repository: ivy-llc/ivy

Issue:
 torch.Tensor.log1p



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
@@ -1294,6 +1294,10 @@ def as_strided(self, size, stride, storage_offset=None):
             self, size=size, stride=stride, storage_offset=storage_offset
         )
 
+    @with_unsupported_dtypes({"2.0.1 and below": ("float16",)}, "torch")
+    def log1p(self):
+        return torch_frontend.log1p(self)
+
 
 class Size(tuple):
     def __new__(cls, iterable=()):


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
@@ -9130,3 +9130,33 @@ def test_torch_instance_as_strided(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="log1p",
+    dtype_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric"),
+    ),
+)
+def test_torch_instance_log1p(
+    dtype_x,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x = dtype_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={"data": x[0]},
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={},
+        frontend=frontend,
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        on_device=on_device,
+    )
Repository: ivy-llc/ivy

Issue:
torch.Tensor.floor_



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
@@ -1309,6 +1309,11 @@ def baddbmm(self, batch1, batch2, *, beta=1, alpha=1):
             self, batch1=batch1, batch2=batch2, beta=beta, alpha=alpha
         )
 
+    @with_unsupported_dtypes({"2.0.1 and below": ("float16",)}, "torch")
+    def floor_(self, *, out=None):
+        self.ivy_array = self.floor().ivy_array
+        return self
+
 
 class Size(tuple):
     def __new__(cls, iterable=()):


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
@@ -9209,3 +9209,35 @@ def test_torch_instance_baddbmm(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="floor_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_torch_instance_floor_(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        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,
+    )
Repository: ivy-llc/ivy

Issue:
torch.Tensor.baddbmm



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
@@ -1298,6 +1298,11 @@ def as_strided(self, size, stride, storage_offset=None):
     def log1p(self):
         return torch_frontend.log1p(self)
 
+    def baddbmm(self, batch1, batch2, *, beta=1, alpha=1):
+        return torch_frontend.baddbmm(
+            self, batch1=batch1, batch2=batch2, beta=beta, alpha=alpha
+        )
+
 
 class Size(tuple):
     def __new__(cls, iterable=()):


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
@@ -9160,3 +9160,52 @@ def test_torch_instance_log1p(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="baddbmm",
+    dtype_and_matrices=_get_dtype_and_3dbatch_matrices(with_input=True, input_3d=True),
+    beta=st.floats(
+        min_value=-5,
+        max_value=5,
+        allow_nan=False,
+        allow_subnormal=False,
+        allow_infinity=False,
+    ),
+    alpha=st.floats(
+        min_value=-5,
+        max_value=5,
+        allow_nan=False,
+        allow_subnormal=False,
+        allow_infinity=False,
+    ),
+)
+def test_torch_instance_baddbmm(
+    dtype_and_matrices,
+    beta,
+    alpha,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x, batch1, batch2 = dtype_and_matrices
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={"data": x[0]},
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "batch1": batch1,
+            "batch2": batch2,
+            "beta": beta,
+            "alpha": alpha,
+        },
+        frontend=frontend,
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        on_device=on_device,
+    )
Repository: ivy-llc/ivy

Issue:
round



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/jax/devicearray.py b/ivy/functional/frontends/jax/devicearray.py
--- a/ivy/functional/frontends/jax/devicearray.py
+++ b/ivy/functional/frontends/jax/devicearray.py
@@ -237,3 +237,6 @@ def __iter__(self):
             raise TypeError("iteration over a 0-d devicearray not supported")
         for i in range(self.shape[0]):
             yield self[i]
+
+    def round(self, decimals=0):
+        return jax_frontend.numpy.round(self, decimals)
diff --git a/ivy/functional/frontends/jax/numpy/mathematical_functions.py b/ivy/functional/frontends/jax/numpy/mathematical_functions.py
--- a/ivy/functional/frontends/jax/numpy/mathematical_functions.py
+++ b/ivy/functional/frontends/jax/numpy/mathematical_functions.py
@@ -704,7 +704,7 @@ def product(
 
 @to_ivy_arrays_and_back
 def round(x, decimals=0, /):
-    return ivy.round(x, decimals)
+    return ivy.round(x, decimals=decimals)
 
 
 @to_ivy_arrays_and_back


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_jax_devicearray.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_jax_devicearray.py
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_jax_devicearray.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_jax_devicearray.py
@@ -1727,3 +1727,40 @@ def test_jax_special_getitem(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="jax.numpy.array",
+    method_name="round",
+    dtype_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        allow_inf=False,
+    ),
+    decimals=st.one_of(
+        st.integers(min_value=-10, max_value=10),
+    ),
+)
+def test_jax_devicearray_round(
+    dtype_x,
+    decimals,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x = dtype_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={
+            "object": x[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={"decimals": decimals},
+        frontend=frontend,
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        on_device=on_device,
+    )
Repository: ivy-llc/ivy

Issue:
all



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
@@ -167,3 +167,7 @@ def square(self, name=None):
     @with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
     def cholesky(self, upper=False, name=None):
         return ivy.cholesky(self._ivy_array, upper=upper)
+    
+    @with_supported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
+    def all(self, axis=None, keepdim=False, dtype=None, name=None):
+        return ivy.all(self.ivy_array, axis=axis, keepdims=keepdim, dtype=dtype)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_tensor.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_tensor.py
@@ -843,3 +843,44 @@ def test_paddle_cholesky(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+# all
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="all",
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=st.one_of(helpers.get_dtypes("float")),
+        min_axis=-1,
+        max_axis=0,
+        min_num_dims=1,
+        force_int_axis=True,
+    ),
+    keep_dims=st.booleans(),
+)
+def test_paddle_all(
+    dtype_x_axis,
+    keep_dims,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+):
+    input_dtypes, x, axis = dtype_x_axis
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtypes,
+        init_all_as_kwargs_np={
+            "object": x[0],
+        },
+        method_input_dtypes=input_dtypes,
+        method_all_as_kwargs_np={
+            "axis": axis,
+            "keepdim": keep_dims,
+        },
+        frontend=frontend,
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        on_device=on_device,
+    )
Repository: ivy-llc/ivy

Issue:
 torch.Tensor.gather



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
@@ -1317,6 +1317,9 @@ def floor_(self):
     def diag(self, diagonal=0):
         return torch_frontend.diag(self, diagonal=diagonal)
 
+    def gather(self, dim, index):
+        return torch_frontend.gather(self, dim=dim, index=index)
+
 
 class Size(tuple):
     def __new__(cls, iterable=()):


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
@@ -9278,3 +9278,38 @@ def test_torch_instance_diag(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="gather",
+    params_indices_others=helpers.array_indices_axis(
+        array_dtypes=helpers.get_dtypes("valid"),
+        indices_dtypes=["int64"],
+        indices_same_dims=True,
+    ),
+)
+def test_torch_instance_gather(
+    params_indices_others,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtypes, x, indices, axis, batch_dims = params_indices_others
+    helpers.test_frontend_method(
+        init_input_dtypes=[input_dtypes[0]],
+        init_all_as_kwargs_np={"data": x},
+        method_input_dtypes=[input_dtypes[1]],
+        method_all_as_kwargs_np={
+            "dim": axis,
+            "index": indices,
+        },
+        frontend=frontend,
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        on_device=on_device,
+    )
Repository: ivy-llc/ivy

Issue:
neg



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/math.py b/ivy/functional/frontends/paddle/tensor/math.py
--- a/ivy/functional/frontends/paddle/tensor/math.py
+++ b/ivy/functional/frontends/paddle/tensor/math.py
@@ -170,6 +170,12 @@ def tan(x, name=None):
     return ivy.tan(x)
 
 
+@with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
+@to_ivy_arrays_and_back
+def neg(x, name=None):
+    return ivy.negative(x)
+
+
 @with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
 @to_ivy_arrays_and_back
 def exp(x, name=None):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_math.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_math.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_math.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_math.py
@@ -750,6 +750,32 @@ def test_paddle_tan(
     )
 
 
+# neg
+@handle_frontend_test(
+    fn_tree="paddle.neg",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+    ),
+)
+def test_paddle_neg(
+    *,
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        x=x[0],
+    )
+
+
 # exp
 @handle_frontend_test(
     fn_tree="paddle.exp",