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

Issue:
torch.Tensor.as_strided



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
@@ -1289,6 +1289,11 @@ def var(self, dim=None, *, correction=1, keepdim=False):
     def narrow(self, dim, start, length):
         return torch_frontend.narrow(self, dim=dim, start=start, length=length)
 
+    def as_strided(self, size, stride, storage_offset=None):
+        return torch_frontend.as_strided(
+            self, size=size, stride=stride, storage_offset=storage_offset
+        )
+
 
 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
@@ -6,6 +6,9 @@
 from ivy_tests.test_ivy.test_frontends.test_torch.test_comparison_ops import (
     _topk_helper,
 )
+from ivy_tests.test_ivy.test_frontends.test_torch.test_creation_ops import (
+    _as_strided_helper,
+)
 from ivy_tests.test_ivy.test_frontends.test_torch.test_indexing_slicing_joining_mutating_ops import (  # noqa: E501
     _dtype_input_dim_start_length,
 )
@@ -9095,3 +9098,35 @@ def test_torch_instance_narrow(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="as_strided",
+    dtype_x_and_other=_as_strided_helper(),
+)
+def test_torch_instance_as_strided(
+    dtype_x_and_other,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x, size, stride, offset = dtype_x_and_other
+    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={
+            "size": size,
+            "stride": stride,
+            "storage_offset": offset,
+        },
+        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.var



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
@@ -1272,6 +1272,9 @@ def greater_(self, other):
     def eq_(self, other):
         return torch_frontend.eq(self, other)
 
+    def var(self, dim=None, *, correction=1, keepdim=False):
+        return torch_frontend.var(self, dim=dim, unbiased=correction, keepdim=keepdim)
+
 
 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
@@ -8986,3 +8986,41 @@ def test_torch_special_eq_(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="var",
+    dtype_and_x=_statistical_dtype_values(
+        function="var",
+        min_value=-1e04,
+        max_value=1e04,
+    ),
+    keepdim=st.booleans(),
+)
+def test_torch_instance_var(
+    dtype_and_x,
+    keepdim,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x, axis, correction = 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={
+            "dim": axis,
+            "correction": int(correction),
+            "keepdim": keepdim,
+        },
+        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.narrow



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
@@ -1286,6 +1286,9 @@ def eq_(self, other):
     def var(self, dim=None, *, correction=1, keepdim=False):
         return torch_frontend.var(self, dim=dim, unbiased=correction, keepdim=keepdim)
 
+    def narrow(self, dim, start, length):
+        return torch_frontend.narrow(self, dim=dim, start=start, length=length)
+
 
 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
@@ -6,6 +6,9 @@
 from ivy_tests.test_ivy.test_frontends.test_torch.test_comparison_ops import (
     _topk_helper,
 )
+from ivy_tests.test_ivy.test_frontends.test_torch.test_indexing_slicing_joining_mutating_ops import (  # noqa: E501
+    _dtype_input_dim_start_length,
+)
 from ivy_tests.test_ivy.test_frontends.test_torch.test_reduction_ops import (
     _get_axis_and_p,
 )
@@ -9060,3 +9063,35 @@ def test_torch_instance_var(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="narrow",
+    dtype_input_dim_start_length=_dtype_input_dim_start_length(),
+)
+def test_torch_instance_narrow(
+    dtype_input_dim_start_length,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    (input_dtype, x, dim, start, length) = dtype_input_dim_start_length
+    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={
+            "dim": dim,
+            "start": start,
+            "length": length,
+        },
+        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:
conj



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
@@ -128,7 +128,13 @@ def pow(x, y, name=None):
     return ivy.pow(x, y)
 
 
-@with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
+@with_unsupported_dtypes({"2.4.2 and below": ("int16", "float16")}, "paddle")
+@to_ivy_arrays_and_back
+def conj(x, name=None):
+    return ivy.conj(x)
+
+
+@with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
 @to_ivy_arrays_and_back
 def floor(x, name=None):
     return ivy.floor(x)


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
@@ -560,6 +560,32 @@ def test_paddle_abs(
     )
 
 
+# conj
+@handle_frontend_test(
+    fn_tree="paddle.tensor.math.conj",
+    dtype_and_input=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric"),
+    ),
+)
+def test_paddle_conj(
+    *,
+    dtype_and_input,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+):
+    input_dtype, x = dtype_and_input
+    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],
+    )
+
+
 # floor
 @handle_frontend_test(
     fn_tree="paddle.tensor.math.floor",
Repository: ivy-llc/ivy

Issue:
mish



Discussion:
- [ ] #16249

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/nn/functional/activation.py b/ivy/functional/frontends/paddle/nn/functional/activation.py
--- a/ivy/functional/frontends/paddle/nn/functional/activation.py
+++ b/ivy/functional/frontends/paddle/nn/functional/activation.py
@@ -191,3 +191,9 @@ def relu_(x, name=None):
     ret = ivy.relu(x)
     ivy.inplace_update(x, ret)
     return x
+
+
+@with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
+@to_ivy_arrays_and_back
+def mish(x, name=None):
+    return ivy.mish(x)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_nn/test_functional/test_paddle_activation.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_nn/test_functional/test_paddle_activation.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_nn/test_functional/test_paddle_activation.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_nn/test_functional/test_paddle_activation.py
@@ -457,3 +457,31 @@ def test_paddle_relu_(
         fn_tree=fn_tree,
         x=x[0],
     )
+
+
+# mish
+@handle_frontend_test(
+    fn_tree="paddle.nn.functional.mish",
+    dtype_and_input=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        safety_factor_scale="log",
+        small_abs_safety_factor=20,
+    ),
+)
+def test_paddle_mish(
+    *,
+    dtype_and_input,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    input_dtype, x = dtype_and_input
+    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],
+    )
Repository: ivy-llc/ivy

Issue:
max_pool1d



Discussion:

Resolving patch:
diff --git a/ivy/stateful/layers.py b/ivy/stateful/layers.py
--- a/ivy/stateful/layers.py
+++ b/ivy/stateful/layers.py
@@ -1593,3 +1593,58 @@ def _forward(self, inputs):
             self._padding,
             data_format=self._data_format,
         )
+
+
+class MaxPool1D(Module):
+    def __init__(
+        self,
+        kernel_size,
+        stride,
+        padding,
+        /,
+        *,
+        data_format="NWC",
+        device=None,
+        v=None,
+        dtype=None,
+    ):
+        """
+        Class for applying Max Pooling over a mini-batch of inputs.
+
+        Parameters
+        ----------
+        kernel_size
+            The size of the window to take a max over.
+        stride
+            The stride of the window. Default value: 1
+        padding
+            Implicit zero padding to be added on both sides.
+        device
+            device on which to create the layer's variables 'cuda:0', 'cuda:1', 'cpu'
+        """
+        self._kernel_size = kernel_size
+        self._stride = stride
+        self._padding = padding
+        self._data_format = data_format
+        Module.__init__(self, device=device, dtype=dtype)
+
+    def _forward(self, inputs):
+        """
+        Forward pass of the layer.
+
+        Parameters
+        ----------
+        x
+            The input to the layer.
+
+        Returns
+        -------
+        The output of the layer.
+        """
+        return ivy.max_pool1d(
+            inputs,
+            self._kernel_size,
+            self._stride,
+            self._padding,
+            data_format=self._data_format,
+        )


Test patch:
diff --git a/ivy_tests/test_ivy/test_stateful/test_layers.py b/ivy_tests/test_ivy/test_stateful/test_layers.py
--- a/ivy_tests/test_ivy/test_stateful/test_layers.py
+++ b/ivy_tests/test_ivy/test_stateful/test_layers.py
@@ -1165,3 +1165,40 @@ def test_avgpool2d_layer(
 
 
 # ToDo : Add gradient testing once random number generation is unified
+
+
+# MaxPool1D
+@handle_method(
+    method_tree="MaxPool1D.__call__",
+    x_k_s_p=helpers.arrays_for_pooling(min_dims=3, max_dims=3, min_side=1, max_side=4),
+)
+def test_maxpool1d_layer(
+    *,
+    x_k_s_p,
+    test_gradients,
+    on_device,
+    class_name,
+    method_name,
+    ground_truth_backend,
+    init_flags,
+    method_flags,
+):
+    input_dtype, x, kernel_size, stride, padding = x_k_s_p
+    helpers.test_method(
+        ground_truth_backend=ground_truth_backend,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        init_all_as_kwargs_np={
+            "kernel_size": kernel_size,
+            "stride": stride,
+            "padding": padding,
+            "device": on_device,
+            "dtype": input_dtype[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={"inputs": x[0]},
+        class_name=class_name,
+        method_name=method_name,
+        test_gradients=test_gradients,
+        on_device=on_device,
+    )
Repository: ivy-llc/ivy

Issue:
add asfarray implementation and test
Close #16302


Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/numpy/manipulation_routines/changing_array_shape.py b/ivy/functional/frontends/numpy/manipulation_routines/changing_array_shape.py
--- a/ivy/functional/frontends/numpy/manipulation_routines/changing_array_shape.py
+++ b/ivy/functional/frontends/numpy/manipulation_routines/changing_array_shape.py
@@ -42,6 +42,11 @@ def moveaxis(a, source, destination):
     return ivy.moveaxis(a, source, destination)
 
 
+@to_ivy_arrays_and_back
+def asfarray(a, dtype=ivy.float64):
+    return ivy.asarray(a, dtype=ivy.float64)
+
+
 @to_ivy_arrays_and_back
 def asarray_chkfinite(a, dtype=None, order=None):
     a = ivy.asarray(a, dtype=dtype)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_manipulation_routines/test_changing_array_shape.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_manipulation_routines/test_changing_array_shape.py
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_manipulation_routines/test_changing_array_shape.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_manipulation_routines/test_changing_array_shape.py
@@ -235,6 +235,30 @@ def test_numpy_resize(
     )
 
 
+# asfarray
+@handle_frontend_test(
+    fn_tree="numpy.asfarray",
+    dtype_and_a=helpers.dtype_and_values(available_dtypes=helpers.get_dtypes("float")),
+)
+def test_numpy_asfarray(
+    *,
+    dtype_and_a,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    dtype, a = dtype_and_a
+    helpers.test_frontend_function(
+        input_dtypes=dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        a=a[0],
+    )
+
+
 # asarray_chkfinite
 @handle_frontend_test(
     fn_tree="numpy.asarray_chkfinite",
Repository: ivy-llc/ivy

Issue:
truncatemod



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
@@ -558,3 +558,11 @@ def while_loop(
 @to_ivy_arrays_and_back
 def truncatediv(x, y, name=None):
     return x.trunc_divide(y)
+
+
+@with_unsupported_dtypes({"2.12.0 and below": ("int16", "int8","uint8"," uint16")}, "tensorflow")
+@to_ivy_arrays_and_back
+def truncatemod(x, y):
+    x = ivy.broadcast_to(x, ivy.shape(y))
+    y = ivy.broadcast_to(y, ivy.shape(x))
+    return ivy.trunc(x / y) * y + (x % y)


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
@@ -2056,3 +2056,35 @@ def test_tensorflow_truncatediv(
         x=x[0],
         y=x[1],
     )
+    
+    
+# Truncatemod
+@handle_frontend_test(
+    fn_tree="tensorflow.truncatemod",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric"),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+    test_with_out=st.just(False),
+)
+def test_tensorflow_truncatemod(
+    *,
+    dtype_and_x,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    assume(not np.any(np.isclose(x[0], 0)))
+    assume(not np.any(np.isclose(x[1], 0)))
+    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],
+    )
Repository: ivy-llc/ivy

Issue:
greater_
greater_


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
@@ -1255,6 +1255,11 @@ def copysign(self, other, *, out=None):
     def greater(self, other, *, out=None):
         return torch_frontend.greater(self, other, out=out)
 
+    @with_unsupported_dtypes({"2.0.1 and below": ("bfloat16",)}, "torch")
+    def greater_(self, other):
+        self.ivy_array = ivy.astype(self.greater(other).ivy_array, self.dtype)
+        return self
+      
     @with_unsupported_dtypes({"2.0.1 and below": ("bfloat16",)}, "torch")
     def eq_(self, other):
         return torch_frontend.eq(self, other)


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
@@ -8808,6 +8808,45 @@ def test_torch_greater(
     )
 
 
+# greater_
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="greater_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric"),
+        num_arrays=2,
+        min_value=-1e04,
+        max_value=1e04,
+        allow_inf=False,
+    ),
+)
+def test_torch_greater_(
+    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={
+            "other": x[1],
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # addr_
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
__rshift__



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/numpy/ndarray/ndarray.py b/ivy/functional/frontends/numpy/ndarray/ndarray.py
--- a/ivy/functional/frontends/numpy/ndarray/ndarray.py
+++ b/ivy/functional/frontends/numpy/ndarray/ndarray.py
@@ -523,3 +523,6 @@ def ptp(self, *, axis=None, out=None, keepdims=False):
         xmax = self.max(axis=axis, out=out, keepdims=keepdims)
         xmin = self.min(axis=axis, out=out, keepdims=keepdims)
         return np_frontend.subtract(xmax, xmin)
+
+    def __rshift__(self, value, /):
+        return ivy.bitwise_right_shift(self.ivy_array, value)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_ndarray/test_ndarray.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_ndarray/test_ndarray.py
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_ndarray/test_ndarray.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_ndarray/test_ndarray.py
@@ -3056,3 +3056,38 @@ def test_numpy_instance_ptp(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="numpy.array",
+    method_name="__rshift__",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("integer"),
+        num_arrays=2,
+    ),
+)
+def test_numpy_instance_rshift__(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+):
+    input_dtypes, x = dtype_and_x
+    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={
+            "value": x[1],
+        },
+        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:
sinh



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
@@ -114,6 +114,10 @@ def log(self, name=None):
     def sin(self, name=None):
         return ivy.sin(self._ivy_array)
 
+    @with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
+    def sinh(self, name=None):
+        return ivy.sinh(self._ivy_array)
+
     @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
     def argmax(self, axis=None, keepdim=False, dtype=None, name=None):
         return ivy.argmax(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
@@ -311,6 +311,39 @@ def test_paddle_sin(
     )
 
 
+# sinh
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="sinh",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_paddle_sinh(
+    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,
+    )
+
+
 # asin
 @handle_frontend_method(
     class_tree=CLASS_TREE,