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

Issue:
trace



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
@@ -714,6 +714,14 @@ def std(self, axis=None, unbiased=True, keepdim=False, name=None):
     def trunc(self, name=None):
         return paddle_frontend.Tensor(ivy.trunc(self._ivy_array))
 
+    @with_supported_dtypes(
+        {"2.5.1 and below": ("int32", "int64", "float32", "float64")}, "paddle"
+    )
+    def trace(self, offset=0, axis1=0, axis2=1, name=None):
+        return paddle_frontend.Tensor(
+            ivy.trace(self._ivy_array, offset=offset, axis1=axis1, axis2=axis2)
+        )
+
     @with_supported_dtypes(
         {"2.5.1 and below": ("float32", "float64", "int16", "int32", "int64", "uint8")},
         "paddle",


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
@@ -3300,6 +3300,56 @@ def test_paddle_tensor_tanh(
     )
 
 
+# trace
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="trace",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        num_arrays=1,
+        min_num_dims=2,
+        min_value=-1e04,
+        max_value=1e04,
+        allow_inf=False,
+    ),
+    offset=st.integers(min_value=-1e04, max_value=1e04),
+    axis1=st.integers(min_value=0, max_value=0),
+    axis2=st.integers(min_value=1, max_value=1),
+)
+def test_paddle_tensor_trace(
+    dtype_and_x,
+    offset,
+    axis1,
+    axis2,
+    frontend,
+    backend_fw,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={
+            "value": x[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "offset": offset,
+            "axis1": axis1,
+            "axis2": axis2,
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        on_device=on_device,
+    )
+
+
 @handle_frontend_method(
     class_tree=CLASS_TREE,
     init_tree="paddle.to_tensor",
Repository: ivy-llc/ivy

Issue:
pow



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
@@ -694,6 +694,12 @@ def tolist(self):
     def min(self, axis=None, keepdim=False, name=None):
         return ivy.min(self._ivy_array, axis=axis, keepdims=keepdim)
 
+    @with_supported_dtypes(
+        {"2.5.1 and below": ("int32", "int64", "float32", "float64")}, "paddle"
+    )
+    def pow(self, y, name=None):
+        return paddle_frontend.Tensor(ivy.pow(self._ivy_array, _to_ivy_array(y)))
+
     @with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
     def atan(self, name=None):
         return ivy.atan(self._ivy_array)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
@@ -2629,6 +2629,42 @@ def test_paddle_tensor_numel(
     )
 
 
+# pow
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="pow",
+    dtypes_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        num_arrays=2,
+        allow_inf=False,
+        shared_dtype=True,
+    ),
+)
+def test_paddle_tensor_pow(
+    dtypes_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtypes_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,
+    )
+
+
 # rad2deg
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
argmax



Discussion:

Resolving patch:
diff --git a/ivy/functional/ivy/searching.py b/ivy/functional/ivy/searching.py
--- a/ivy/functional/ivy/searching.py
+++ b/ivy/functional/ivy/searching.py
@@ -50,7 +50,7 @@ def argmax(
         input array. Should have a numeric data type.
     axis
         axis along which to search. If None, the function must return the index of the
-        maximum value of the flattened array. Deafult: ``None``.
+        maximum value of the flattened array. Default = None.
     keepdims
         If this is set to True, the axes which are reduced are left in the result as
         dimensions with size one. With this option, the result will broadcast correctly
@@ -117,6 +117,16 @@ def argmax(
     >>> y = ivy.argmax(x, axis=1, keepdims=True, out=z)
     >>> print(z)
     ivy.array([[0],[2],[2]])
+
+    With :class:`ivy.Container` input:
+
+    >>> x = ivy.Container(a=ivy.array([0., -1., 2.]), b=ivy.array([3., 4., 5.]))
+    >>> y = ivy.argmax(x)
+    >>> print(y)
+    {
+        a: ivy.array(2),
+        b: ivy.array(2)
+    }
     """
     return current_backend(x).argmax(
         x,
@@ -164,7 +174,10 @@ def argmin(
         input array (see Broadcasting). Otherwise, if False, the reduced axes
         (dimensions) must not be included in the result. Default = False.
     dtype
-            An optional output_dtype from: int32, int64. Defaults to int64.
+        An optional output_dtype from: int32, int64. Defaults to int64.
+    select_last_index
+        If this is set to True, the index corresponding to the
+        last occurrence of the maximum value will be returned.
     out
         if axis is None, a zero-dimensional array containing the index of the first
         occurrence of the minimum value; otherwise, a non-zero-dimensional array


Test patch:
Repository: ivy-llc/ivy

Issue:
Missing @to_ivy_arrays_and_back in topk frontend function
### Bug Explanation

The bug was @to_ivy_arrays_and_back was not present while defining the frontend function for paddle.topk in ivy/functional/frontends/paddle/tensor/search.py. Due to which all the test cases were failing. 

### Steps to Reproduce Bug

The bug is present in ivy/functional/frontends/paddle/tensor/search.py

### Environment

Windows 11, Docker & Vs Code

### Ivy Version

latest

### Backend

- [X] NumPy
- [X] TensorFlow
- [X] PyTorch
- [X] JAX

### Device

_No response_


Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/search.py b/ivy/functional/frontends/paddle/tensor/search.py
--- a/ivy/functional/frontends/paddle/tensor/search.py
+++ b/ivy/functional/frontends/paddle/tensor/search.py
@@ -83,6 +83,7 @@ def sort(x, /, *, axis=-1, descending=False, name=None):
     {"2.5.1 and below": ("float32", "float64", "int32", "int64")},
     "paddle",
 )
+@to_ivy_arrays_and_back
 def topk(x, k, axis=None, largest=True, sorted=True, name=None):
     return ivy.top_k(x, k, axis=axis, largest=largest, sorted=sorted)
 


Test patch:
Repository: ivy-llc/ivy

Issue:
stop_gradient



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/tensorflow/general_functions.py b/ivy/functional/frontends/tensorflow/general_functions.py
--- a/ivy/functional/frontends/tensorflow/general_functions.py
+++ b/ivy/functional/frontends/tensorflow/general_functions.py
@@ -429,6 +429,11 @@ def stack(values, axis=0, name="stack"):
     return ivy.stack(values, axis=axis)
 
 
+@to_ivy_arrays_and_back
+def stop_gradient(input, name=None):
+    return ivy.stop_gradient(input)
+
+
 # ToDo: find a way around for negative indexing, which torch does not support
 @to_ivy_arrays_and_back
 def strided_slice(


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_general_functions.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_general_functions.py
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_general_functions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_general_functions.py
@@ -1865,6 +1865,28 @@ def test_tensorflow_stack(
     )
 
 
+# stop_gradient
+@handle_frontend_test(
+    fn_tree="tensorflow.stop_gradient",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric")
+    ),
+)
+def test_tensorflow_stop_gradient(
+    *, dtype_and_x, test_flags, backend_fw, fn_tree, frontend, on_device
+):
+    dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=dtype,
+        test_flags=test_flags,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        input=x[0],
+    )
+
+
 # strided_slice
 @handle_frontend_test(
     fn_tree="tensorflow.strided_slice",
Repository: ivy-llc/ivy

Issue:
eigvals



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/numpy/linalg/matrix_eigenvalues.py b/ivy/functional/frontends/numpy/linalg/matrix_eigenvalues.py
--- a/ivy/functional/frontends/numpy/linalg/matrix_eigenvalues.py
+++ b/ivy/functional/frontends/numpy/linalg/matrix_eigenvalues.py
@@ -17,6 +17,11 @@ def eigh(a, /, UPLO="L"):
     return ivy.eigh(a, UPLO=UPLO)
 
 
+@to_ivy_arrays_and_back
+def eigvals(a):
+    return ivy.eig(a)[0]
+
+
 @to_ivy_arrays_and_back
 @from_zero_dim_arrays_to_scalar
 def eigvalsh(a, /, UPLO="L"):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_matrix_eigenvalues.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_matrix_eigenvalues.py
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_matrix_eigenvalues.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_matrix_eigenvalues.py
@@ -130,6 +130,55 @@ def test_numpy_eigh(
         )
 
 
+@handle_frontend_test(
+    fn_tree="numpy.linalg.eigvals",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        min_value=0,
+        max_value=10,
+        shape=helpers.ints(min_value=2, max_value=4).map(lambda x: tuple([x, x])),
+    ).filter(
+        lambda x: "float16" not in x[0]
+        and "bfloat16" not in x[0]
+        and np.linalg.cond(x[1][0]) < 1 / sys.float_info.epsilon
+        and np.linalg.det(np.asarray(x[1][0])) != 0
+    ),
+    test_with_out=st.just(False),
+)
+def test_numpy_eigvals(
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+    backend_fw,
+):
+    dtype, x = dtype_and_x
+    ret, frontend_ret = helpers.test_frontend_function(
+        input_dtypes=dtype,
+        backend_to_test=backend_fw,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        test_values=False,
+        a=x,
+    )
+    with BackendHandler.update_backend(backend_fw) as ivy_backend:
+        ret = np.sort(
+            np.array([ivy_backend.to_numpy(x).astype(np.float128) for x in ret])
+        )
+        frontend_ret = np.sort(np.array([x.astype(np.float128) for x in frontend_ret]))
+        assert_all_close(
+            ret_np=ret,
+            ret_from_gt_np=frontend_ret,
+            backend=backend_fw,
+            ground_truth_backend=frontend,
+            atol=1e-2,
+            rtol=1e-2,
+        )
+
+
 # eigvalsh
 @handle_frontend_test(
     fn_tree="numpy.linalg.eigvalsh",
Repository: ivy-llc/ivy

Issue:
stanh



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
@@ -714,6 +714,10 @@ def std(self, axis=None, unbiased=True, keepdim=False, name=None):
     def trunc(self, name=None):
         return paddle_frontend.Tensor(ivy.trunc(self._ivy_array))
 
+    @with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
+    def stanh(self, scale_a=0.67, scale_b=1.7159, name=None):
+        return paddle_frontend.stanh(self, scale_a=scale_a, scale_b=scale_b)
+
     @with_supported_dtypes(
         {"2.5.1 and below": ("float32", "float64", "int16", "int32", "int64", "uint8")},
         "paddle",


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
@@ -3155,6 +3155,49 @@ def test_paddle_tensor_square(
     )
 
 
+
+# stanh
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="stanh",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+    ),
+    scale_a=st.floats(1e-5, 1e5),
+    scale_b=st.floats(1e-5, 1e5),
+)
+def test_paddle_tensor_stanh(
+    dtype_and_x,
+    frontend_method_data,
+    scale_a,
+    scale_b,
+    init_flags,
+    method_flags,
+    frontend,
+    backend_fw,
+    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,
+        backend_to_test=backend_fw,
+        method_all_as_kwargs_np={
+            "scale_a": scale_a,
+            "scale_b": scale_b,
+          },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+          
+      
 # squeeze_
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
 topk



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
@@ -741,6 +741,13 @@ def argmin(self, axis=None, keepdim=False, dtype=None, name=None):
             self._ivy_array, axis=axis, keepdim=keepdim, dtype=dtype
         )
 
+    @with_supported_dtypes(
+        {"2.5.1 and below": ("float32", "float64", "int32", "int64")},
+        "paddle",
+    )
+    def topk(self, k, axis=None, largest=True, sorted=True, name=None):
+        return ivy.top_k(self._ivy_array, k, axis=axis, largest=largest, sorted=sorted)
+
     @with_unsupported_dtypes({"2.5.1 and below": ("float16", "bfloat16")}, "paddle")
     def remainder(self, y, name=None):
         return ivy.remainder(self._ivy_array, y)


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
@@ -3378,6 +3378,57 @@ def test_paddle_tensor_tanh(
     )
 
 
+# topk
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="topk",
+    dtype_x_and_axis=helpers.dtype_values_axis(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_num_dims=1,
+        valid_axis=True,
+        force_int_axis=True,
+    ),
+    k=st.data(),
+    sorted=st.booleans(),
+    largest=st.booleans(),
+)
+def test_paddle_tensor_topk(
+    dtype_x_and_axis,
+    k,
+    sorted,
+    largest,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x, axis = dtype_x_and_axis
+    k = k.draw(st.integers(min_value=1, max_value=x[0].shape[axis]))
+    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={
+            "k": k,
+            "axis": axis,
+            "largest": largest,
+            "sorted": sorted,
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+        test_values=False,
+    )
+
+
 # trace
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
asscalar



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/numpy/manipulation_routines/changing_kind_of_array.py b/ivy/functional/frontends/numpy/manipulation_routines/changing_kind_of_array.py
--- a/ivy/functional/frontends/numpy/manipulation_routines/changing_kind_of_array.py
+++ b/ivy/functional/frontends/numpy/manipulation_routines/changing_kind_of_array.py
@@ -5,3 +5,7 @@
 
 def asmatrix(data, dtype=None):
     return np_frontend.matrix(ivy.array(data), dtype=dtype, copy=False)
+
+
+def asscalar(a):
+    return a.item()


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_manipulation_routines/test_changing_kind_of_array.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_manipulation_routines/test_changing_kind_of_array.py
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_manipulation_routines/test_changing_kind_of_array.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_manipulation_routines/test_changing_kind_of_array.py
@@ -18,3 +18,13 @@ def test_numpy_asmatrix(arr, backend_fw):
         ret_gt = np.asmatrix(x[0])
         assert ret.shape == ret_gt.shape
         assert ivy_backend.all(ivy_backend.flatten(ret._data) == np.ravel(ret_gt))
+
+
+@handle_frontend_test(
+    fn_tree="numpy.asscalar",
+    arr=helpers.array_values(dtype=helpers.get_dtypes("numeric"), shape=1),
+)
+def test_numpy_asscalar(arr: np.ndarray):
+    ret_1 = arr.item()
+    ret_2 = np_frontend.asscalar(arr)
+    assert ret_1 == ret_2
Repository: ivy-llc/ivy

Issue:
digamma



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
@@ -166,6 +166,13 @@ def diff(x, n=1, axis=-1, prepend=None, append=None, name=None):
     return ivy.diff(x, n=n, axis=axis, prepend=prepend, append=append)
 
 
+@with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
+@to_ivy_arrays_and_back
+def digamma(x, name=None):
+    digamma_fun = ivy.digamma
+    return ivy.array(digamma_fun(x), dtype=x.dtype)
+
+
 @with_unsupported_dtypes({"2.5.1 and below": ("float16", "bfloat16")}, "paddle")
 @to_ivy_arrays_and_back
 def divide(x, y, name=None):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_math.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_math.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_math.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_math.py
@@ -699,6 +699,36 @@ def test_paddle_diff(
     )
 
 
+# digamma
+@handle_frontend_test(
+    fn_tree="paddle.tensor.math.digamma",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        safety_factor_scale="log",
+    ),
+)
+def test_paddle_digamma(
+    *,
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    backend_fw,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        atol=1e-4,
+        x=x[0],
+    )
+
+
 # divide
 @handle_frontend_test(
     fn_tree="paddle.divide",
Repository: ivy-llc/ivy

Issue:
sqrt_



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
@@ -463,6 +463,12 @@ def sqrt(x, name=None):
     return ivy.sqrt(x)
 
 
+@with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
+@to_ivy_arrays_and_back
+def sqrt_(x, name=None):
+    return ivy.inplace_update(x, sqrt(x))
+
+
 @with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
 @to_ivy_arrays_and_back
 def square(x, name=None):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_math.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_math.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_math.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_math.py
@@ -2038,6 +2038,34 @@ def test_paddle_sqrt(
     )
 
 
+# sqrt_
+@handle_frontend_test(
+    fn_tree="paddle.tensor.math.sqrt_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+    ),
+)
+def test_paddle_sqrt_(
+    *,
+    dtype_and_x,
+    fn_tree,
+    frontend,
+    test_flags,
+    backend_fw,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        x=x[0],
+    )
+
+
 # square
 @handle_frontend_test(
     fn_tree="paddle.tensor.math.square",