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

Issue:
 torch.Tensor.movedim



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
@@ -1323,6 +1323,9 @@ def gather(self, dim, index):
     def take_along_dim(self, indices, dim):
         return torch_frontend.take_along_dim(self, indices=indices, dim=dim)
 
+    def movedim(self, source, destination):
+        return torch_frontend.movedim(self, source=source, destination=destination)
+
 
 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
@@ -9354,3 +9354,79 @@ def test_torch_instance_take_along_dim(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="movedim",
+    dtype_and_input=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        min_value=-100,
+        max_value=100,
+        shape=st.shared(
+            helpers.get_shape(
+                min_num_dims=1,
+                max_num_dims=3,
+                min_dim_size=1,
+                max_dim_size=3,
+            ),
+            key="a_s_d",
+        ),
+    ),
+    source=helpers.get_axis(
+        allow_none=False,
+        unique=True,
+        shape=st.shared(
+            helpers.get_shape(
+                min_num_dims=1,
+                max_num_dims=3,
+                min_dim_size=1,
+                max_dim_size=3,
+            ),
+            key="a_s_d",
+        ),
+        min_size=1,
+        force_int=True,
+    ),
+    destination=helpers.get_axis(
+        allow_none=False,
+        unique=True,
+        shape=st.shared(
+            helpers.get_shape(
+                min_num_dims=1,
+                max_num_dims=3,
+                min_dim_size=1,
+                max_dim_size=3,
+            ),
+            key="a_s_d",
+        ),
+        min_size=1,
+        force_int=True,
+    ),
+)
+def test_torch_instance_movedim(
+    dtype_and_input,
+    source,
+    destination,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, value = dtype_and_input
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={"data": value[0]},
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "source": source,
+            "destination": destination,
+        },
+        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.addcdiv_



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
@@ -1326,6 +1326,13 @@ def take_along_dim(self, indices, dim):
     def movedim(self, source, destination):
         return torch_frontend.movedim(self, source=source, destination=destination)
 
+    @with_unsupported_dtypes({"2.0.1 and below": ("float16",)}, "torch")
+    def addcdiv_(self, tensor1, tensor2, *, value=1):
+        self.ivy_array = self.addcdiv(
+            tensor1=tensor1, tensor2=tensor2, value=value
+        ).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
@@ -9430,3 +9430,47 @@ def test_torch_instance_movedim(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="addcdiv_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        num_arrays=3,
+        large_abs_safety_factor=2.5,
+        small_abs_safety_factor=2.5,
+        safety_factor_scale="log",
+        shared_dtype=True,
+    ),
+    value=st.floats(min_value=-100, max_value=100),
+)
+def test_torch_instance_addcdiv_(
+    dtype_and_x,
+    value,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    assume(not np.any(np.isclose(x[2], 0)))
+
+    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={
+            "tensor1": x[1],
+            "tensor2": x[2],
+            "value": value,
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+        atol_=1e-03,
+    )
Repository: ivy-llc/ivy

Issue:
nanquantile



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/stat.py b/ivy/functional/frontends/paddle/tensor/stat.py
--- a/ivy/functional/frontends/paddle/tensor/stat.py
+++ b/ivy/functional/frontends/paddle/tensor/stat.py
@@ -23,3 +23,10 @@ def numel(x, name=None):
     except (ValueError, TypeError):
         length = 1  # if 0 dimensional tensor with 1 element
     return ivy.array([prod if prod > 0 else ivy.array(length, dtype=ivy.int64)])
+
+@with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
+@to_ivy_arrays_and_back
+def nanquantile(a, q, axis=None, keepdims=False, interpolation='linear', out=None):
+   return ivy.nanquantile(a, q, axis=axis, keepdims=keepdims, interpolation=interpolation, out=out)
+
+
diff --git a/ivy/functional/ivy/experimental/statistical.py b/ivy/functional/ivy/experimental/statistical.py
--- a/ivy/functional/ivy/experimental/statistical.py
+++ b/ivy/functional/ivy/experimental/statistical.py
@@ -490,3 +490,21 @@ def igamma(
         ivy.array([0.3614, 0.2085])
     """
     return ivy.current_backend().igamma(a, x=x, out=out)
+
+@handle_exceptions
+@handle_nestable
+@handle_out_argument
+@to_native_arrays_and_back
+def nanquantile(a: ivy.Array,
+   q: Union[ivy.Array, float],
+   /,
+   *,
+   axis: Optional[Union[Sequence[int], int]] = None,
+   keepdims: bool = False,
+   interpolation: str = "linear",
+   out: Optional[ivy.Array] = None,
+) -> ivy.Array:
+
+    return ivy.current_backend(a).nanquantile(
+       a, q, axis=axis, keepdims=keepdims, interpolation=interpolation, out=out)
+


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_stat.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_stat.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_stat.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_stat.py
@@ -63,3 +63,34 @@ def test_paddle_numel(
         on_device=on_device,
         x=x[0],
     )
+
+@handle_frontend_test(
+   fn_tree="paddle.nanquantile",
+   dtype_and_x=_statistical_dtype_values(function="nanquantile"),
+   keepdims=st.booleans(),
+   q=st.floats(0.0, 1.0),
+   interpolation=st.sampled_from(['nearest', 'linear', 'lower', 'higher', 'midpoint'])
+)
+def test_paddle_nanquantile(
+   *,
+   q,
+   dtype_and_x,
+   keepdims,
+   interpolation,
+   on_device,
+   fn_tree,
+   frontend,
+   test_flags,
+):
+    input_dtype, x, axis = 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,
+       a=x[0],
+       q=q,
+       axis=axis,
+       interpolation=interpolation,
+       keepdims=keepdims)
Repository: ivy-llc/ivy

Issue:
Fix reduction_ops.test_torch_unique
|   |   |
|---|---|
|paddle|<a href="https://github.com/unifyai/ivy/actions/runs/6289534329/job/17076112252"><img src=https://img.shields.io/badge/-failure-red></a>
|numpy|<a href="https://github.com/unifyai/ivy/actions/runs/6289534329/job/17076112252"><img src=https://img.shields.io/badge/-failure-red></a>
|jax|<a href="https://github.com/unifyai/ivy/actions/runs/6289534329/job/17076112252"><img src=https://img.shields.io/badge/-failure-red></a>
|tensorflow|<a href="https://github.com/unifyai/ivy/actions/runs/6289534329/job/17076112252"><img src=https://img.shields.io/badge/-failure-red></a>
|torch|<a href="https://github.com/unifyai/ivy/actions/runs/6289534329/job/17076112252"><img src=https://img.shields.io/badge/-failure-red></a>



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
@@ -235,9 +235,11 @@ def logsumexp(input, dim, keepdim=False, *, out=None):
 
 @to_ivy_arrays_and_back
 def unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None):
-    results = ivy.unique_all(input, axis=dim)
+    if dim is not None:
+        sorted = True
+    results = ivy.unique_all(input, by_value=sorted, axis=dim)
 
-    fields = ["values"]
+    fields = ["output"]
     if return_inverse:
         fields.append("inverse_indices")
     if return_counts:
@@ -247,7 +249,12 @@ def unique(input, sorted=True, return_inverse=False, return_counts=False, dim=No
 
     values = [results.values]
     if return_inverse:
-        values.append(results.inverse_indices)
+        inverse_indices = results.inverse_indices
+
+        if dim is None:
+            inverse_indices = inverse_indices.reshape(input.shape)
+
+        values.append(inverse_indices)
     if return_counts:
         values.append(results.counts)
 


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_reduction_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_reduction_ops.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_reduction_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_reduction_ops.py
@@ -820,13 +820,14 @@ def test_torch_logsumexp(
     ),
     return_inverse=st.booleans(),
     return_counts=st.booleans(),
-    test_with_out=st.just(False),
+    sorted=st.booleans(),
 )
 def test_torch_unique(
     *,
     dtype_x_axis,
     return_inverse,
     return_counts,
+    sorted,
     on_device,
     fn_tree,
     frontend,
@@ -841,7 +842,7 @@ def test_torch_unique(
         fn_tree=fn_tree,
         on_device=on_device,
         input=x[0],
-        sorted=True,
+        sorted=sorted,
         return_inverse=return_inverse,
         return_counts=return_counts,
         dim=axis,
Repository: ivy-llc/ivy

Issue:
Fix tensor.test_torch_special_eq_
|   |   |
|---|---|
|tensorflow|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>
|jax|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>
|numpy|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>
|torch|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>
|paddle|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>



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
@@ -1296,7 +1296,10 @@ def greater_(self, other):
 
     @with_unsupported_dtypes({"2.0.1 and below": ("bfloat16",)}, "torch")
     def eq_(self, other):
-        return torch_frontend.eq(self, other)
+        self.ivy_array = ivy.astype(
+            torch_frontend.eq(self, other).ivy_array, self.dtype
+        )
+        return self
 
     def var(self, dim=None, *, correction=1, keepdim=False):
         return torch_frontend.var(self, dim=dim, unbiased=correction, keepdim=keepdim)


Test patch:
Repository: ivy-llc/ivy

Issue:
arccosh



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/numpy/mathematical_functions/trigonometric_functions.py b/ivy/functional/frontends/numpy/mathematical_functions/trigonometric_functions.py
--- a/ivy/functional/frontends/numpy/mathematical_functions/trigonometric_functions.py
+++ b/ivy/functional/frontends/numpy/mathematical_functions/trigonometric_functions.py
@@ -143,6 +143,28 @@ def _arctan(
     return ret
 
 
+@handle_numpy_out
+@handle_numpy_dtype
+@to_ivy_arrays_and_back
+@handle_numpy_casting
+@from_zero_dim_arrays_to_scalar
+def _arccosh(
+    x,
+    /,
+    out=None,
+    *,
+    where=True,
+    casting="same_kind",
+    order="K",
+    dtype=None,
+    subok=True,
+):
+    ret = ivy.acosh(x, out=out)
+    if ivy.is_array(where):
+        ret = ivy.where(where, ret, ivy.default(out, ivy.zeros_like(ret)), out=out)
+    return ret
+
+
 @handle_numpy_out
 @handle_numpy_dtype
 @to_ivy_arrays_and_back


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_mathematical_functions/test_trigonometric_functions.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_mathematical_functions/test_trigonometric_functions.py
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_mathematical_functions/test_trigonometric_functions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_mathematical_functions/test_trigonometric_functions.py
@@ -237,6 +237,52 @@ def test_numpy_arctan(
     )
 
 
+# arccosh
+@handle_frontend_test(
+    fn_tree="numpy.arccosh",
+    dtypes_values_casting=np_frontend_helpers.dtypes_values_casting_dtype(
+        arr_func=[
+            lambda: helpers.dtype_and_values(
+                available_dtypes=helpers.get_dtypes("float"),
+            )
+        ],
+    ),
+    where=np_frontend_helpers.where(),
+    number_positional_args=np_frontend_helpers.get_num_positional_args_ufunc(
+        fn_name="arccosh"
+    ),
+)
+def test_numpy_arccosh(
+    dtypes_values_casting,
+    where,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+):
+    input_dtypes, x, casting, dtype = dtypes_values_casting
+    where, input_dtypes, test_flags = np_frontend_helpers.handle_where_and_array_bools(
+        where=where,
+        input_dtype=input_dtypes,
+        test_flags=test_flags,
+    )
+    np_frontend_helpers.test_frontend_function(
+        input_dtypes=input_dtypes,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        atol=1e-3,
+        x=x[0],
+        out=None,
+        where=where,
+        casting=casting,
+        order="K",
+        dtype=dtype,
+        subok=True,
+    )
+
+
 # rad2deg
 @handle_frontend_test(
     fn_tree="numpy.rad2deg",
Repository: ivy-llc/ivy

Issue:
Fix tensor.test_torch_instance_logical_not_
|   |   |
|---|---|
|tensorflow|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>
|jax|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>
|numpy|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>
|torch|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>
|paddle|<a href="https://github.com/unifyai/ivy/actions/runs/5740357384"><img src=https://img.shields.io/badge/-failure-red></a>



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
@@ -355,11 +355,8 @@ def logical_and(self, other):
     def logical_not(self, *, out=None):
         return torch_frontend.logical_not(self, out=out)
 
-    def logical_not_(self, *, out=None):
-        ret = torch_frontend.logical_not(self, out=out)
-        self.ivy_array = ivy.inplace_update(
-            self.ivy_array, ivy.astype(ret.ivy_array, self.dtype)
-        )
+    def logical_not_(self):
+        self.ivy_array = ivy.astype(self.logical_not().ivy_array, self.dtype)
         return self
 
     @with_unsupported_dtypes({"2.0.1 and below": ("bfloat16",)}, "torch")


Test patch:
Repository: ivy-llc/ivy

Issue:
 bitwise_xor
Adding  bitwise_xor in paddle.tesnor.tesnor.Tesnor from this Todo list  #15115


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
@@ -209,6 +209,13 @@ def allclose(self, other, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
     def sort(self, axis=-1, descending=False, name=None):
         return ivy.sort(self._ivy_array, axis=axis, descending=descending)
 
+    @with_supported_dtypes(
+        {"2.4.2 and below": ("bool", "uint8", "int8", "int16", "int32", "int64")},
+        "paddle",
+    )
+    def bitwise_xor(self, y, out=None, name=None):
+        return paddle_frontend.bitwise_xor(self, y)
+
     @with_supported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
     def any(self, axis=None, keepdim=False, name=None):
         return ivy.any(self._ivy_array, axis=axis, keepdims=keepdim)


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
@@ -1254,3 +1254,34 @@ def test_paddle_subtract(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+# bitwise_xor
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="bitwise_xor",
+    dtypes_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"), num_arrays=2, shared_dtype=True
+    ),
+)
+def test_paddle_bitwise_xor(
+    dtypes_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+):
+    input_dtype, x = dtypes_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={"y": x[1]},
+        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:
pdist



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/nn/functional/distance_functions.py b/ivy/functional/frontends/torch/nn/functional/distance_functions.py
--- a/ivy/functional/frontends/torch/nn/functional/distance_functions.py
+++ b/ivy/functional/frontends/torch/nn/functional/distance_functions.py
@@ -40,3 +40,18 @@ def pairwise_distance(x1, x2, *, p=2.0, eps=1e-06, keepdim=False):
         output_dim = x2_dim
 
     return ivy.vector_norm(x1 - x2 + eps, ord=p, axis=output_dim - 1, keepdims=keepdim)
+
+
+@with_unsupported_dtypes({"2.0.1 and below": ("float16", "bfloat16")}, "torch")
+@to_ivy_arrays_and_back
+def pdist(input, *, p=2):
+    x = ivy.array(
+        [
+            abs(input[i] - input[j])
+            for i in range(len(input) - 1)
+            for j in range(i + 1, len(input))
+        ]
+    )
+    return ivy.vector_norm(x, ord=p, axis=1)
+
+


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_distance_functions.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_distance_functions.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_distance_functions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_distance_functions.py
@@ -1,5 +1,6 @@
 from hypothesis import strategies as st
 
+import ivy
 # local
 import ivy_tests.test_ivy.helpers as helpers
 from ivy_tests.test_ivy.helpers import handle_frontend_test
@@ -80,3 +81,38 @@ def test_torch_pairwise_distance(
         p=p,
         keepdim=keepdim,
     )
+
+# P-norm Distance
+@handle_frontend_test(
+    fn_tree="torch.nn.functional.pdist",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        min_num_dims=2,
+        max_num_dims=2,
+        min_dim_size=10,
+        max_dim_size=10,
+        min_value=1.0,
+        max_value=1.0e5,
+    ),
+    p=st.integers(min_value=0, max_value=1.0e5),
+)
+def test_torch_pdist(
+    *,
+    dtype_and_x,
+    p,
+    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,
+        input=x[0],
+        p=p,
+    )
Repository: ivy-llc/ivy

Issue:
empty_like



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/creation.py b/ivy/functional/frontends/paddle/tensor/creation.py
--- a/ivy/functional/frontends/paddle/tensor/creation.py
+++ b/ivy/functional/frontends/paddle/tensor/creation.py
@@ -71,3 +71,8 @@ def empty(shape, dtype=None):
 @to_ivy_arrays_and_back
 def eye(num_rows, num_columns=None, dtype=None, name=None):
     return ivy.eye(num_rows, num_columns, dtype=dtype)
+
+
+@to_ivy_arrays_and_back
+def empty_like(x, dtype=None, name=None):
+    return ivy.empty_like(x, dtype=dtype)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_creation.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_creation.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_creation.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_creation.py
@@ -332,3 +332,31 @@ def test_paddle_eye(
         num_columns=num_columns,
         dtype=dtypes[0],
     )
+
+
+# empty_like
+@handle_frontend_test(
+    fn_tree="paddle.empty_like",
+    dtype_and_x=helpers.dtype_and_values(available_dtypes=helpers.get_dtypes("valid")),
+    dtype=helpers.get_dtypes("valid", full=False),
+    test_with_out=st.just(False),
+)
+def test_paddle_empty_like(
+    dtype_and_x,
+    dtype,
+    test_flags,
+    frontend,
+    fn_tree,
+    on_device,
+):
+    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,
+        test_values=False,
+        x=x[0],
+        dtype=dtype[0],
+    )