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

Issue:
max



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
@@ -344,3 +344,9 @@ def fmin(self, y, name=None):
     def minimum(self, y, name=None):
         y_ivy = _to_ivy_array(y)
         return ivy.minimum(self._ivy_array, y_ivy)
+
+    @with_supported_dtypes(
+        {"2.5.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
+    )
+    def max(self, axis=None, keepdim=False, name=None):
+        return ivy.max(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
@@ -1741,3 +1741,45 @@ def test_paddle_less_than(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+# max
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="max",
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=st.one_of(helpers.get_dtypes("valid")),
+        min_axis=-1,
+        max_axis=0,
+        min_num_dims=1,
+        force_int_axis=False,
+    ),
+    keep_dims=st.booleans(),
+)
+def test_paddle_max(
+    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:
unravel_index



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
@@ -606,3 +606,8 @@ 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)
+
+
+@to_ivy_arrays_and_back
+def unravel_index(indices, dims, out=None, name=None):
+    return ivy.unravel_index(indices, dims, out=out)


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
@@ -2151,3 +2151,24 @@ def test_tensorflow_truncatemod(
         x=x[0],
         y=x[1],
     )
+
+
+@handle_frontend_test(
+    fn_tree="tensorflow.unravel_index",
+    indices=helpers.array_values(
+        dtype=helpers.get_dtypes("integer"), shape=(1, 2), min_value=0, max_value=49
+    ),
+    dims=helpers.array_values(
+        dtype=helpers.get_dtypes("integer"), shape=(1, 2), min_value=50
+    ),
+)
+def test_unravel_index(*, indices, dims, frontend, test_flags, fn_tree, on_device):
+    helpers.test_frontend_function(
+        input_dtypes=["int32"],
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        indices=indices[0],
+        dims=dims[0],
+    )
Repository: ivy-llc/ivy

Issue:
rad2deg



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
@@ -291,3 +291,7 @@ def cumsum(self, axis=None, dtype=None, name=None):
     )
     def angle(self, name=None):
         return ivy.angle(self._ivy_array)
+
+    @with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
+    def rad2deg(self, name=None):
+        return ivy.rad2deg(self._ivy_array)


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
@@ -1554,3 +1554,36 @@ def test_paddle_angle(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+# rad2deg
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="rad2deg",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_paddle_rad2deg(
+    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:
bitwise_and
implementing the bitwise and for paddle frontend 


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
@@ -208,6 +208,22 @@ 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_and(x, y, out=None, name=None):
+        return paddle_frontend.bitwise_and(x, y)
+
     @with_supported_dtypes(
         {
             "2.5.0 and below": (


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
@@ -1415,6 +1415,37 @@ def test_paddle_instance_ceil(
     )
 
 
+# bitwise_and
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="bitwise_and",
+    dtypes_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"), num_arrays=2, shared_dtype=True
+    ),
+)
+def test_paddle_bitwise_and(
+    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,
+    )
+
+
 # greater_than
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
rsqrt



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
@@ -257,3 +257,7 @@ def astype(self, dtype):
     )
     def logical_xor(self, y, out=None, name=None):
         return paddle_frontend.logical_xor(self, y, out=out)
+
+    @with_supported_dtypes({"2.5.0 and below": ("float32", "float64")}, "paddle")
+    def rsqrt(self, name=None):
+        return ivy.reciprocal(ivy.sqrt(self._ivy_array))


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
@@ -1347,3 +1347,36 @@ def test_paddle_logical_or(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+# rsqrt
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="rsqrt",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+    ),
+)
+def test_paddle_rsqrt(
+    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:
deg2rad



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
@@ -350,3 +350,7 @@ def minimum(self, y, name=None):
     )
     def max(self, axis=None, keepdim=False, name=None):
         return ivy.max(self._ivy_array, axis=axis, keepdims=keepdim)
+
+    @with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
+    def deg2rad(self, name=None):
+        return ivy.deg2rad(self._ivy_array)


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
@@ -1783,3 +1783,36 @@ def test_paddle_max(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+# deg2rad
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="deg2rad",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_paddle_deg2rad(
+    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:
gcd
from #15115


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
@@ -1,9 +1,7 @@
 # global
 import ivy
 from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
-from ivy.functional.frontends.paddle.func_wrapper import (
-    to_ivy_arrays_and_back,
-)
+from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back
 
 
 @with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
@@ -164,6 +162,12 @@ def deg2rad(x, name=None):
     return ivy.deg2rad(x)
 
 
+@with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
+@to_ivy_arrays_and_back
+def gcd(x, y, name=None):
+    return ivy.gcd(x, y)
+
+
 @with_unsupported_dtypes({"2.5.0 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
@@ -852,3 +852,32 @@ def test_paddle_reciprocal(
         on_device=on_device,
         x=x[0],
     )
+
+
+# gcd
+@handle_frontend_test(
+    fn_tree="paddle.gcd",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("int"),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+)
+def test_paddle_gcd(
+    *,
+    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],
+        y=x[1],
+    )
Repository: ivy-llc/ivy

Issue:
[Bug]: 'all' function bug in paddle frontend
### Bug Explanation

It's supposed to take tensor of bool but is taking float in the current implementation.

### Steps to Reproduce Bug

By comparing with paddle docs

### Environment

Windows 11 using Pycharm and Docker

### Ivy Version

Latest

### Backend

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

### Device

_No response_


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
@@ -195,9 +195,8 @@ def multiply(self, y, name=None):
     def isfinite(self, name=None):
         return ivy.isfinite(self._ivy_array)
 
-    @with_supported_dtypes({"2.5.0 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)
+    def all(self, axis=None, keepdim=False, name=None):
+        return ivy.all(self.ivy_array, axis=axis, keepdims=keepdim)
 
     @with_supported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
     def allclose(self, other, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):


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
@@ -921,7 +921,7 @@ def test_paddle_instance_multiply(
     init_tree="paddle.to_tensor",
     method_name="all",
     dtype_x_axis=helpers.dtype_values_axis(
-        available_dtypes=st.one_of(helpers.get_dtypes("float")),
+        available_dtypes=helpers.get_dtypes("bool"),
         min_axis=-1,
         max_axis=0,
         min_num_dims=1,
Repository: ivy-llc/ivy

Issue:
median



Discussion:
This issue has been labelled as stale. If you would like to continue working on this issue, then please add another comment or create a PR . If a PR has already been created which refers to this issue, then you should explicitly mention this issue in the relevant PR. For more information please refer to this page in our documentation: https://lets-unify.ai/ivy/contributing/1_the_basics.html#todo-list-issues

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
@@ -1,6 +1,6 @@
 # global
 import ivy
-from ivy.func_wrapper import with_unsupported_dtypes
+from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
 from ivy.functional.frontends.paddle.func_wrapper import (
     to_ivy_arrays_and_back,
 )
@@ -31,3 +31,17 @@ def nanquantile(a, q, axis=None, keepdims=False, interpolation="linear", out=Non
     return ivy.nanquantile(
         a, q, axis=axis, keepdims=keepdims, interpolation=interpolation, out=out
     )
+
+
+@with_supported_dtypes(
+    {"2.5.0 and below": ("bool", "float16", "float32", "float64", "int32", "int64")},
+    "paddle",
+)
+@to_ivy_arrays_and_back
+def median(x, axis=None, keepdim=False, name=None):
+    x = (
+        ivy.astype(x, ivy.float64)
+        if ivy.dtype(x) == "float64"
+        else ivy.astype(x, ivy.float32)
+    )
+    return ivy.median(x, axis=axis, keepdims=keepdim)


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
@@ -96,3 +96,35 @@ def test_paddle_nanquantile(
         interpolation=interpolation,
         keepdims=keepdims,
     )
+
+
+# median
+@handle_frontend_test(
+    fn_tree="paddle.median",
+    dtype_x_and_axis=helpers.dtype_values_axis(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_num_dims=1,
+        min_value=-1e10,
+        max_value=1e10,
+        valid_axis=True,
+        force_int_axis=True,
+    ),
+    keepdim=st.booleans(),
+)
+def test_paddle_median(
+    dtype_x_and_axis,
+    keepdim,
+    frontend,
+    test_flags,
+    fn_tree,
+):
+    input_dtypes, x, axis = dtype_x_and_axis
+    helpers.test_frontend_function(
+        input_dtypes=input_dtypes,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        x=x[0],
+        axis=axis,
+        keepdim=keepdim,
+    )
Repository: ivy-llc/ivy

Issue:
standard_normal



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/tensor/random.py b/ivy/functional/frontends/paddle/tensor/random.py
--- a/ivy/functional/frontends/paddle/tensor/random.py
+++ b/ivy/functional/frontends/paddle/tensor/random.py
@@ -47,3 +47,12 @@ def uniform_(x, min=-1.0, max=1.0, seed=0, name=None):
     return ivy.random_uniform(
         low=min, high=max, shape=x.shape, dtype=x.dtype, seed=seed
     )
+
+
+@with_supported_dtypes(
+    {"2.5.0 and below": ("float32", "float64")},
+    "paddle",
+)
+@to_ivy_arrays_and_back
+def standard_normal(shape, dtype=None, name=None):
+    return ivy.random_normal(mean=0, std=1, shape=shape, dtype=dtype)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_random.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_random.py
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_random.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_paddle_random.py
@@ -162,3 +162,31 @@ def test_paddle_uniform_(
         max=max,
         seed=seed,
     )
+
+
+@handle_frontend_test(
+    fn_tree="paddle.standard_normal",
+    input_dtypes=st.sampled_from([["int32"], ["int64"]]),
+    shape=helpers.get_shape(
+        min_num_dims=1,
+        min_dim_size=1,
+    ),
+    dtype=helpers.get_dtypes("valid", full=False),
+)
+def test_paddle_standard_normal(
+    input_dtypes,
+    shape,
+    dtype,
+    frontend,
+    test_flags,
+    fn_tree,
+):
+    helpers.test_frontend_function(
+        input_dtypes=input_dtypes,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        test_values=False,
+        shape=shape,
+        dtype=dtype[0],
+    )
Repository: ivy-llc/ivy

Issue:
min



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
@@ -567,3 +567,10 @@ def sgn(self, name=None):
 
     def tolist(self):
         return paddle_frontend.Tensor(ivy.to_list(self._ivy_array))
+
+    @with_supported_dtypes(
+        {"2.5.0 and below": ("float32", "float64", "int32", "int64")},
+        "paddle",
+    )
+    def min(self, axis=None, keepdim=False, name=None):
+        return ivy.min(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
@@ -2677,3 +2677,45 @@ def test_paddle_instance_tolist(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+# min
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="min",
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=st.one_of(helpers.get_dtypes("numeric")),
+        min_axis=-1,
+        max_axis=0,
+        min_num_dims=1,
+        force_int_axis=True,
+    ),
+    keep_dims=st.booleans(),
+)
+def test_paddle_instance_min(
+    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={
+            "data": 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,
+    )