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

Issue:
diagflat
Working on (#15024 -> )


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
@@ -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 .tensor import Tensor
 from ivy.functional.frontends.paddle.func_wrapper import (
     to_ivy_arrays_and_back,
@@ -114,3 +114,12 @@ def tril(x, diagonal=0, name=None):
 @to_ivy_arrays_and_back
 def triu(x, diagonal=0, name=None):
     return ivy.triu(x, k=diagonal)
+
+
+@with_supported_dtypes(
+    {"2.5.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
+)
+@to_ivy_arrays_and_back
+def diagflat(x, offset=0, name=None):
+    arr = ivy.diagflat(x, offset=offset)
+    return arr


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
@@ -420,3 +420,37 @@ def test_paddle_triu(
         x=values[0],
         diagonal=diagonal,
     )
+
+
+# diagflat
+@handle_frontend_test(
+    fn_tree="paddle.diagflat",
+    dtype_and_values=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_num_dims=1,
+        max_num_dims=5,
+        min_dim_size=1,
+        max_dim_size=5,
+    ),
+    offset=st.integers(min_value=-4, max_value=4),
+    test_with_out=st.just(False),
+)
+def test_paddle_diagflat(
+    dtype_and_values,
+    offset,
+    test_flags,
+    frontend,
+    fn_tree,
+    on_device,
+):
+    input_dtype, x = dtype_and_values
+    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],
+        offset=offset,
+    )
Repository: ivy-llc/ivy

Issue:
cumsum



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
@@ -280,3 +280,7 @@ def rsqrt(self, name=None):
     @with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
     def cumprod(self, dim=None, dtype=None, name=None):
         return ivy.cumprod(self._ivy_array, axis=dim, dtype=dtype)
+
+    @with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
+    def cumsum(self, axis=None, dtype=None, name=None):
+        return ivy.cumsum(self._ivy_array, axis=axis, 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
@@ -1485,3 +1485,40 @@ def test_paddle_cumprod(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="cumsum",
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=helpers.get_dtypes("float"),
+        valid_axis=True,
+        force_int_axis=True,
+        min_num_dims=1,
+        min_value=-5,
+        max_value=5,
+    ),
+)
+def test_paddle_cumsum(
+    dtype_x_axis,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+):
+    input_dtype, x, axis = dtype_x_axis
+    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={"axis": axis},
+        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:
matrix_exp



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/linalg.py b/ivy/functional/frontends/torch/linalg.py
--- a/ivy/functional/frontends/torch/linalg.py
+++ b/ivy/functional/frontends/torch/linalg.py
@@ -98,6 +98,12 @@ def matrix_power(A, n, *, out=None):
     return ivy.matrix_power(A, n, out=out)
 
 
+@with_unsupported_dtypes({"2.0.1 and below": ("bfloat16", "float16")}, "torch")
+@to_ivy_arrays_and_back
+def matrix_exp(A):
+    return ivy.matrix_exp(A)
+
+
 @with_supported_dtypes(
     {"2.0.1 and below": ("float32", "float64", "complex64", "complex128")}, "torch"
 )


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -497,6 +497,31 @@ def test_torch_matrix_power(
     )
 
 
+# matrix_exp
+@handle_frontend_test(
+    fn_tree="torch.linalg.matrix_exp",
+    dtype_and_x=_get_dtype_and_square_matrix(),
+)
+def test_torch_matrix_exp(
+    *,
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    dtype, x = dtype_and_x
+    test_flags.num_positional_args = len(x)
+    helpers.test_frontend_function(
+        input_dtypes=dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        A=x,
+    )
+
+
 # matrix_norm
 @handle_frontend_test(
     fn_tree="torch.linalg.matrix_norm",
Repository: ivy-llc/ivy

Issue:
angle



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
@@ -284,3 +284,10 @@ def cumprod(self, dim=None, dtype=None, name=None):
     @with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
     def cumsum(self, axis=None, dtype=None, name=None):
         return ivy.cumsum(self._ivy_array, axis=axis, dtype=dtype)
+
+    @with_supported_dtypes(
+        {"2.5.0 and below": ("complex64", "complex128", "float32", "float64")},
+        "paddle",
+    )
+    def angle(self, name=None):
+        return ivy.angle(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
@@ -1522,3 +1522,35 @@ def test_paddle_cumsum(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="angle",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=["float64", "complex64", "complex128"],
+    ),
+)
+def test_paddle_angle(
+    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:
standard_cauchy



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/numpy/random/functions.py b/ivy/functional/frontends/numpy/random/functions.py
--- a/ivy/functional/frontends/numpy/random/functions.py
+++ b/ivy/functional/frontends/numpy/random/functions.py
@@ -150,3 +150,10 @@ def negative_binomial(n, p, size=None):
         size = (size,)
     lambda_ = ivy.gamma(n, scale, shape=size)
     return ivy.poisson(lam=lambda_, shape=size)
+
+
+@to_ivy_arrays_and_back
+@from_zero_dim_arrays_to_scalar
+def standard_cauchy(size=None):
+    u = ivy.random_uniform(low=0.0, high=1.0, shape=size, dtype="float64")
+    return ivy.tan(ivy.pi * (u - 0.5))


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_random/test_functions.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_random/test_functions.py
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_random/test_functions.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_random/test_functions.py
@@ -567,3 +567,29 @@ def test_numpy_negative_binomial(
         p=p,
         size=size,
     )
+
+
+# standard_cauchy
+@handle_frontend_test(
+    fn_tree="numpy.random.standard_cauchy",
+    input_dtypes=helpers.get_dtypes("integer", full=False),
+    size=helpers.get_shape(allow_none=True),
+    test_with_out=st.just(False),
+)
+def test_numpy_standard_cauchy(
+    input_dtypes,
+    size,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+):
+    helpers.test_frontend_function(
+        input_dtypes=input_dtypes,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        test_values=False,
+        size=size,
+    )
Repository: ivy-llc/ivy

Issue:
Fix tensor.test_torch_instance_heaviside
|   |   |
|---|---|
|tensorflow|<a href="https://github.com/unifyai/ivy/actions/runs/5366528325/jobs/9735999286"><img src=https://img.shields.io/badge/-failure-red></a>
|jax|<a href="https://github.com/unifyai/ivy/actions/runs/5366528325/jobs/9735999286"><img src=https://img.shields.io/badge/-success-success></a>
|numpy|<a href="https://github.com/unifyai/ivy/actions/runs/5366528325/jobs/9735999286"><img src=https://img.shields.io/badge/-success-success></a>
|torch|<a href="https://github.com/unifyai/ivy/actions/runs/5366528325/jobs/9735999286"><img src=https://img.shields.io/badge/-success-success></a>
|paddle|<a href="https://github.com/unifyai/ivy/actions/runs/5366528325/jobs/9735999286"><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
@@ -605,6 +605,9 @@ def dsplit(
     def dim(self):
         return self.ivy_array.ndim
 
+    @with_supported_dtypes(
+        {"2.5.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
+    )
     def heaviside(self, values, *, out=None):
         return torch_frontend.heaviside(self, values, out=out)
 


Test patch:
Repository: ivy-llc/ivy

Issue:
logit



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
@@ -239,9 +239,14 @@ def reciprocal(x, name=None):
 def gcd(x, y, name=None):
     return ivy.gcd(x, y)
 
-  
+
 @with_unsupported_dtypes({"2.5.0 and below": "bfloat16"}, "paddle")
 @to_ivy_arrays_and_back
 def fmin(x, y, name=None):
     return ivy.fmin(x, y)
 
+
+@with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
+@to_ivy_arrays_and_back
+def logit(x, eps=None, name=None):
+    return ivy.logit(x, eps=eps)


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
@@ -974,7 +974,6 @@ def test_paddle_cumprod(
     )
 
 
-
 # gcd
 @handle_frontend_test(
     fn_tree="paddle.gcd",
@@ -982,7 +981,7 @@ def test_paddle_cumprod(
         available_dtypes=helpers.get_dtypes("valid"),
         num_arrays=2,
         min_num_dims=1,
-        shared_dtype=True
+        shared_dtype=True,
     ),
 )
 def test_paddle_gcd(
@@ -1029,3 +1028,30 @@ def test_paddle_fmin(
         x=x[0],
         y=x[1],
     )
+
+
+# logit
+@handle_frontend_test(
+    fn_tree="paddle.logit",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_paddle_logit(
+    *,
+    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],
+        eps=1e-2,
+    )
Repository: ivy-llc/ivy

Issue:
equal



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
@@ -297,7 +297,7 @@ def rsqrt(self, name=None):
     @with_supported_dtypes({"2.5.0 and below": ("float32", "float64")}, "paddle")
     def divide(self, y, name=None):
         return paddle_frontend.divide(self, y)
-      
+
     @with_unsupported_dtypes(
         {
             "2.5.0 and below": (
@@ -329,6 +329,21 @@ 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": (
+                "uint8",
+                "int8",
+                "int16",
+                "complex64",
+                "complex128",
+            )
+        },
+        "paddle",
+    )
+    def equal(self, y, name=None):
+        return paddle_frontend.equal(self, y)
+
     @with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
     def rad2deg(self, name=None):
         return ivy.rad2deg(self._ivy_array)
@@ -383,7 +398,7 @@ def isclose(self, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
         return paddle_frontend.isclose(
             self, y, rtol=rtol, atol=atol, equal_nan=equal_nan
         )
-    
+
     @with_supported_dtypes({"2.5.0 and below": ("int32", "int64")}, "paddle")
     def floor_divide(self, y, name=None):
         y_ivy = y._ivy_array if isinstance(y, Tensor) else _to_ivy_array(y)


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
@@ -1622,6 +1622,39 @@ def test_paddle_angle(
     )
 
 
+# equal
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="equal",
+    dtypes_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+)
+def test_paddle_equal(
+    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,
+    )
+
+
 # rad2deg
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
cholesky



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
@@ -1418,6 +1418,10 @@ def addcdiv_(self, tensor1, tensor2, *, value=1):
         ).ivy_array
         return self
 
+    @with_unsupported_dtypes({"2.0.1 and below": ("bfloat16", "float16")}, "torch")
+    def cholesky(self, upper=False):
+        return torch_frontend.cholesky(self, upper=upper)
+
 
 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
@@ -44,6 +44,7 @@
 )
 from ivy_tests.test_ivy.test_frontends.test_torch.test_linalg import (  # noqa
     _get_dtype_and_square_matrix,
+    _get_dtype_and_matrix,
 )
 from ivy_tests.test_ivy.test_functional.test_core.test_statistical import (
     _get_castable_dtype,
@@ -9810,6 +9811,45 @@ def test_torch_instance_addcdiv_(
     )
 
 
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="cholesky",
+    dtype_and_x=_get_dtype_and_matrix(),
+    upper=st.booleans(),
+)
+def test_torch_instance_cholesky(
+    dtype_and_x,
+    upper,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    x = x[0]
+    # make symmetric positive-definite
+    x = np.matmul(x.swapaxes(-1, -2), x) + np.identity(x.shape[-1]) * 1e-3
+
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={
+            "data": x,
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "upper": upper,
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+        rtol_=1e-2,
+    )
+
+
 @handle_frontend_method(
     class_tree=CLASS_TREE,
     init_tree="torch.tensor",
Repository: ivy-llc/ivy

Issue:
maximum



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
@@ -459,6 +459,10 @@ def equal_all(self, y, name=None):
             ivy.array_equal(self._ivy_array, _to_ivy_array(y))
         )
 
+    @with_supported_dtypes({"2.5.0 and below": ("float32", "float64")}, "paddle")
+    def maximum(self, other, name=None):
+        return ivy.maximum(self._ivy_array, other)
+
     @with_unsupported_dtypes({"2.5.0 and below": "bfloat16"}, "paddle")
     def fmax(self, y, name=None):
         return paddle_frontend.Tensor(ivy.fmax(self._ivy_array, _to_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
@@ -1,8 +1,6 @@
+# flake8: noqa
 # global
 import numpy as np
-from hypothesis import assume, given
-from hypothesis import strategies as st
-
 import ivy
 
 # local
@@ -2721,6 +2719,41 @@ def test_paddle_instance_min(
     )
 
 
+# maximum
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="maximum",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+)
+def test_paddle_instance_maximum(
+    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=frontend,
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        on_device=on_device,
+    )
+
+
 # std
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
fmax



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
@@ -311,3 +311,8 @@ def angle(self, name=None):
     @with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
     def rad2deg(self, name=None):
         return ivy.rad2deg(self._ivy_array)
+
+    @with_unsupported_dtypes({"2.5.0 and below": "bfloat16"}, "paddle")
+    def fmax(self, y, name=None):
+        y_ivy = _to_ivy_array(y)
+        return ivy.fmax(self._ivy_array, y_ivy)


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
@@ -1618,3 +1618,33 @@ def test_paddle_rad2deg(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="fmax",
+    dtypes_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"), num_arrays=2, shared_dtype=True
+    ),
+)
+def test_paddle_fmax(
+    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,
+    )