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

Issue:
diff
adding .diff method to torch frontend


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
@@ -1698,6 +1698,21 @@ def floor_(self):
         self.ivy_array = self.floor().ivy_array
         return self
 
+    @with_unsupported_dtypes(
+        {
+            "2.0.1 and below": (
+                "bfloat16",
+                "complex",
+                "float64",
+                "int8",
+                "int64",
+            )
+        },
+        "torch",
+    )
+    def diff(self, n=1, dim=-1, prepend=None, append=None):
+        return torch_frontend.diff(self, n=n, dim=dim, prepend=prepend, append=append)
+
     def diag(self, diagonal=0):
         return torch_frontend.diag(self, diagonal=diagonal)
 


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
@@ -5863,6 +5863,67 @@ def test_torch_tensor_diagonal(
     )
 
 
+# diff
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="diff",
+    dtype_n_x_n_axis=helpers.dtype_values_axis(
+        available_dtypes=st.shared(helpers.get_dtypes("valid"), key="dtype"),
+        min_num_dims=1,
+        min_value=-1e09,
+        max_value=1e09,
+        valid_axis=True,
+        force_int_axis=True,
+    ),
+    n=st.integers(min_value=0, max_value=5),
+    dtype_prepend=helpers.dtype_and_values(
+        available_dtypes=st.shared(helpers.get_dtypes("numeric"), key="dtype"),
+        min_num_dims=1,
+        max_num_dims=1,
+    ),
+    dtype_append=helpers.dtype_and_values(
+        available_dtypes=st.shared(helpers.get_dtypes("numeric"), key="dtype"),
+        min_num_dims=1,
+        max_num_dims=1,
+    ),
+)
+def test_torch_tensor_diff(
+    dtype_n_x_n_axis,
+    n,
+    dtype_prepend,
+    dtype_append,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x, axis = dtype_n_x_n_axis
+    _, prepend = dtype_prepend
+    _, append = dtype_append
+    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={
+            "n": n,
+            "dim": axis,
+            "prepend": prepend[0],
+            "append": append[0],
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # dim
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
tril_indices_from



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/numpy/indexing_routines/generating_index_arrays.py b/ivy/functional/frontends/numpy/indexing_routines/generating_index_arrays.py
--- a/ivy/functional/frontends/numpy/indexing_routines/generating_index_arrays.py
+++ b/ivy/functional/frontends/numpy/indexing_routines/generating_index_arrays.py
@@ -22,6 +22,11 @@ def tril_indices(n, k=0, m=None):
     return ivy.tril_indices(n, m, k)
 
 
+@to_ivy_arrays_and_back
+def tril_indices_from(arr, k=0):
+    return ivy.tril_indices(arr.shape[0], arr.shape[1], k)
+
+
 # unravel_index
 @to_ivy_arrays_and_back
 def unravel_index(indices, shape, order="C"):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_indexing_routines/test_generating_index_arrays.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_indexing_routines/test_generating_index_arrays.py
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_indexing_routines/test_generating_index_arrays.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_indexing_routines/test_generating_index_arrays.py
@@ -123,6 +123,44 @@ def test_numpy_tril_indices(
     )
 
 
+@handle_frontend_test(
+    fn_tree="numpy.tril_indices_from",
+    dtype_and_values=helpers.dtype_and_values(
+        dtype=["float32"],
+        min_dim_size=3,
+        max_dim_size=3,
+        min_num_dims=2,
+        max_num_dims=2,
+        array_api_dtypes=True,
+    ),
+    k=st.integers(min_value=-10, max_value=10),
+    dtype=helpers.get_dtypes("valid", full=False),
+    test_with_out=st.just(False),
+)
+def test_numpy_tril_indices_from(
+    *,
+    dtype_and_values,
+    k,
+    dtype,
+    test_flags,
+    frontend,
+    backend_fw,
+    fn_tree,
+    on_device,
+):
+    dtype, values = dtype_and_values
+    helpers.test_frontend_function(
+        input_dtypes=dtype,
+        test_flags=test_flags,
+        backend_to_test=backend_fw,
+        frontend=frontend,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        arr=values[0],
+        k=k,
+    )
+
+
 @handle_frontend_test(
     fn_tree="numpy.unravel_index",
     dtype_x_shape=max_value_as_shape_prod(),
Repository: ivy-llc/ivy

Issue:
fftfreq



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/jax/numpy/fft.py b/ivy/functional/frontends/jax/numpy/fft.py
--- a/ivy/functional/frontends/jax/numpy/fft.py
+++ b/ivy/functional/frontends/jax/numpy/fft.py
@@ -18,6 +18,26 @@ def fft2(a, s=None, axes=(-2, -1), norm=None):
     return ivy.array(ivy.fft2(a, s=s, dim=axes, norm=norm), dtype=ivy.dtype(a))
 
 
+@to_ivy_arrays_and_back
+@with_unsupported_dtypes({"2.5.1 and below": ("float16", "bfloat16")}, "paddle")
+def fftfreq(n, d=1.0, *, dtype=None):
+    if not isinstance(
+        n, (int, type(ivy.int8), type(ivy.int16), type(ivy.int32), type(ivy.int64))
+    ):
+        raise ValueError("n should be an integer")
+
+    dtype = ivy.float64 if dtype is None else ivy.as_ivy_dtype(dtype)
+
+    N = (n - 1) // 2 + 1
+    val = 1.0 / (n * d)
+
+    results = ivy.zeros(tuple([n]), dtype=dtype)
+    results[:N] = ivy.arange(0, N, dtype=dtype)
+    results[N:] = ivy.arange(-(n // 2), 0, dtype=dtype)
+
+    return results * val
+
+
 @to_ivy_arrays_and_back
 @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
 def fftshift(x, axes=None, name=None):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_fft.py b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_fft.py
--- a/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_fft.py
+++ b/ivy_tests/test_ivy/test_frontends/test_jax/test_numpy/test_fft.py
@@ -99,6 +99,32 @@ def test_jax_numpy_fft2(
     )
 
 
+# fftfreq
+@handle_frontend_test(
+    fn_tree="jax.numpy.fft.fftfreq",
+    n=st.integers(min_value=10, max_value=100),
+    sample_rate=st.integers(min_value=1, max_value=10),
+    dtype=st.one_of(helpers.get_dtypes("float", full=False), st.none()),
+)
+def test_jax_numpy_fftfreq(
+    n, sample_rate, dtype, backend_fw, frontend, test_flags, fn_tree, on_device
+):
+    d = 1 / sample_rate
+    dtype = dtype[0] if dtype is not None else None
+    helpers.test_frontend_function(
+        input_dtypes=[int],
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        test_values=True,
+        n=n,
+        d=d,
+        dtype=dtype,
+    )
+
+
 # fftshift
 @handle_frontend_test(
     fn_tree="jax.numpy.fft.fftshift",
Repository: ivy-llc/ivy

Issue:
[Enhancement] Add  `real_if_close` to numpy frontends
The [ivy.real_if_close](https://github.com/unifyai/ivy/blob/main/ivy/functional/frontends/numpy/mathematical_functions/miscellaneous.py#L361) function at Ivy's NumPy frontend currently acts as a placeholder, directly returning the input through `ivy.array(a)`. This was due to the previous limitations in the ivy library where it did not support complex numbers.

With the recent update in ivy supporting complex numbers, it's time to fully implement the` real_if_close` function.

## Steps for Implementation

- Update the `real_if_close` function to handle complex numbers.
 - Add necessary tests to ensure the function behaves as expected w.r.t. [numpy.real_if_close](https://numpy.org/doc/stable/reference/generated/numpy.real_if_close.html#numpy-real-if-close).


Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/numpy/mathematical_functions/miscellaneous.py b/ivy/functional/frontends/numpy/mathematical_functions/miscellaneous.py
--- a/ivy/functional/frontends/numpy/mathematical_functions/miscellaneous.py
+++ b/ivy/functional/frontends/numpy/mathematical_functions/miscellaneous.py
@@ -359,4 +359,17 @@ def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None):
 
 @to_ivy_arrays_and_back
 def real_if_close(a, tol=100):
-    return ivy.array(a)  # ivy doesn't yet support complex numbers
+    a = ivy.array(a, dtype=a.dtype)
+    dtype_ = a.dtype
+
+    if not ivy.is_complex_dtype(dtype_):
+        return a
+
+    if tol > 1:
+        f = ivy.finfo(dtype_)
+        tol = f.eps * tol
+
+    if ivy.all(ivy.abs(ivy.imag(a)) < tol):
+        a = ivy.real(a)
+
+    return a


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_numpy/test_mathematical_functions/test_miscellaneous.py b/ivy_tests/test_ivy/test_frontends/test_numpy/test_mathematical_functions/test_miscellaneous.py
--- a/ivy_tests/test_ivy/test_frontends/test_numpy/test_mathematical_functions/test_miscellaneous.py
+++ b/ivy_tests/test_ivy/test_frontends/test_numpy/test_mathematical_functions/test_miscellaneous.py
@@ -585,11 +585,17 @@ def test_numpy_nan_to_num(
 # real_if_close
 @handle_frontend_test(
     fn_tree="numpy.real_if_close",
-    dtype_and_x=helpers.dtype_and_values(available_dtypes=helpers.get_dtypes("float")),
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float_and_complex"),
+        min_dim_size=1,
+        min_num_dims=1,
+    ).filter(lambda x: "bfloat16" not in x[0]),
+    tol=st.integers(min_value=1, max_value=1000),
     test_with_out=st.just(False),
 )
 def test_numpy_real_if_close(
     dtype_and_x,
+    tol,
     frontend,
     test_flags,
     fn_tree,
@@ -605,6 +611,7 @@ def test_numpy_real_if_close(
         fn_tree=fn_tree,
         on_device=on_device,
         a=x[0],
+        tol=tol,
     )
Repository: ivy-llc/ivy

Issue:
mod



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
@@ -636,6 +636,10 @@ def floor_divide(self, y, name=None):
             ivy.floor_divide(self._ivy_array, _to_ivy_array(y))
         )
 
+    @with_supported_dtypes({"2.5.1 and below": ("int32", "int64")}, "paddle")
+    def mod(self, y, name=None):
+        return paddle_frontend.Tensor(ivy.fmod(self._ivy_array, _to_ivy_array(y)))
+
     # cond
     @with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
     def cond(self, p=None, name=None):


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
@@ -2563,6 +2563,42 @@ def test_paddle_tensor_minimum(
     )
 
 
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="mod",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        num_arrays=2,
+        shared_dtype=True,
+        min_value=0,
+        exclude_min=True,
+    ),
+)
+def test_paddle_tensor_mod(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_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,
+    )
+
+
 @handle_frontend_method(
     class_tree=CLASS_TREE,
     init_tree="paddle.to_tensor",
Repository: ivy-llc/ivy

Issue:
is_int_dtype



Discussion:

Resolving patch:
diff --git a/ivy/functional/ivy/data_type.py b/ivy/functional/ivy/data_type.py
--- a/ivy/functional/ivy/data_type.py
+++ b/ivy/functional/ivy/data_type.py
@@ -1915,18 +1915,14 @@ def is_int_dtype(
             else False
         )
     elif isinstance(dtype_in, (list, tuple, dict)):
-        return (
-            True
-            if ivy.nested_argwhere(
-                dtype_in,
-                lambda x: (
-                    isinstance(x, (int, np.integer))
-                    or (ivy.is_array(x) and "int" in ivy.dtype(x))
-                )
-                and x is not bool,
-            )
-            else False
-        )
+
+        def nested_fun(x):
+            return (
+                isinstance(x, (int, np.integer))
+                or (ivy.is_array(x) and "int" in ivy.dtype(x))
+            ) and x is not bool
+
+        return True if ivy.nested_argwhere(dtype_in, nested_fun) else False
     return "int" in ivy.as_ivy_dtype(dtype_in)
 
 


Test patch:
Repository: ivy-llc/ivy

Issue:
nonzero



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
@@ -758,3 +758,7 @@ def remainder(self, y, name=None):
 
     def is_floating_point(self):
         return paddle_frontend.is_floating_point(self._ivy_array)
+
+    @with_unsupported_dtypes({"2.5.1 and below": ("float16", "bfloat16")}, "paddle")
+    def nonzero(self):
+        return paddle_frontend.nonzero(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
@@ -2652,6 +2652,43 @@ def test_paddle_tensor_neg(
     )
 
 
+# nonzero
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="nonzero",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes(kind="float"),
+        min_num_dims=1,
+        allow_inf=True,
+    ),
+)
+def test_paddle_tensor_nonzero(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_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={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 @handle_frontend_method(
     class_tree=CLASS_TREE,
     init_tree="paddle.to_tensor",
Repository: ivy-llc/ivy

Issue:
negative_



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
@@ -914,6 +914,11 @@ def neg_(self):
     def negative(self):
         return torch_frontend.negative(self)
 
+    @with_unsupported_dtypes({"2.0.1 and below": ("bool", "bfloat16")}, "torch")
+    def negative_(self):
+        self.ivy_array = torch_frontend.negative(self).ivy_array
+        return self
+
     def int(self, memory_format=None):
         self.ivy_array = ivy.astype(self.ivy_array, ivy.int32, copy=False)
         return self


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
@@ -9480,6 +9480,44 @@ def test_torch_tensor_negative(
     )
 
 
+# negative_
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="negative_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_value=-1e04,
+        max_value=1e04,
+        allow_inf=False,
+    ),
+)
+def test_torch_tensor_negative_(
+    dtype_and_x,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_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={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # new_empty (not actually intuitive for testing)
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
corrcoef

corrcoef

corrcoef



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/paddle/experimental/statistical.py b/ivy/functional/backends/paddle/experimental/statistical.py
--- a/ivy/functional/backends/paddle/experimental/statistical.py
+++ b/ivy/functional/backends/paddle/experimental/statistical.py
@@ -7,7 +7,6 @@
 
 # local
 from ivy.func_wrapper import with_unsupported_device_and_dtypes, with_supported_dtypes
-from ivy.utils.exceptions import IvyNotImplementedException
 from . import backend_version
 
 
@@ -331,9 +330,14 @@ def corrcoef(
     *,
     y: Optional[paddle.Tensor] = None,
     rowvar: Optional[bool] = True,
+    name: Optional[str] = None,
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
-    raise IvyNotImplementedException()
+    return paddle.linalg.corrcoef(
+        x=x,
+        rowvar=rowvar,
+        name=name,
+    )
 
 
 def histogram(


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix paddle_stat.test_paddle_numel
|   |   |
|---|---|
|paddle|<a href="https://github.com/unifyai/ivy/actions/runs/5634798880"><img src=https://img.shields.io/badge/-failure-red></a>
|numpy|<a href="https://github.com/unifyai/ivy/actions/runs/5634798880"><img src=https://img.shields.io/badge/-failure-red></a>
|tensorflow|<a href="https://github.com/unifyai/ivy/actions/runs/5634798880"><img src=https://img.shields.io/badge/-failure-red></a>
|jax|<a href="https://github.com/unifyai/ivy/actions/runs/5634798880"><img src=https://img.shields.io/badge/-failure-red></a>
|torch|<a href="https://github.com/unifyai/ivy/actions/runs/5634798880"><img src=https://img.shields.io/badge/-failure-red></a>



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/stat.py b/ivy/functional/frontends/paddle/stat.py
--- a/ivy/functional/frontends/paddle/stat.py
+++ b/ivy/functional/frontends/paddle/stat.py
@@ -41,7 +41,10 @@ def nanmedian(x, axis=None, keepdim=True, name=None):
     return ivy.median(x, axis=axis, keepdims=keepdim)
 
 
-@with_unsupported_dtypes({"2.5.1 and below": ("complex", "int8")}, "paddle")
+@with_supported_dtypes(
+    {"2.5.1 and below": ("bool", "float16", "float32", "float64", "int32", "int64")},
+    "paddle",
+)
 @to_ivy_arrays_and_back
 def numel(x, name=None):
     prod = ivy.prod(x.size, dtype=ivy.int64)


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix logic.test_paddle_less_than
|   |   |
|---|---|
|numpy|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-failure-red></a>
|jax|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-failure-red></a>
|tensorflow|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-success-success></a>
|torch|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-success-success></a>
|paddle|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-failure-red></a>



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/paddle/logic.py b/ivy/functional/frontends/paddle/logic.py
--- a/ivy/functional/frontends/paddle/logic.py
+++ b/ivy/functional/frontends/paddle/logic.py
@@ -189,13 +189,13 @@ def less_equal(x, y, /, *, name=None):
     return ivy.less_equal(x, y)
 
 
-@with_unsupported_dtypes(
-    {"2.5.1 and below": ("bool", "uint8", "int8", "int16", "complex64", "complex128")},
+@with_supported_dtypes(
+    {"2.5.1 and below": ("bool", "float16", "float32", "float64", "int32", "int64")},
     "paddle",
 )
 @to_ivy_arrays_and_back
 def less_than(x, y, /, *, name=None):
-    return ivy.less(x, y)
+    return ivy.astype(ivy.less(x, y), ivy.bool)
 
 
 @with_supported_dtypes(


Test patch:
Repository: ivy-llc/ivy

Issue:
Fix logic.test_paddle_less_than
|   |   |
|---|---|
|numpy|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-failure-red></a>
|jax|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-failure-red></a>
|tensorflow|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-success-success></a>
|torch|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-success-success></a>
|paddle|<a href="https://github.com/unifyai/ivy/actions/runs/6243648593/job/16949368135"><img src=https://img.shields.io/badge/-failure-red></a>



Discussion:

Resolving patch:
diff --git a/ivy/functional/backends/tensorflow/elementwise.py b/ivy/functional/backends/tensorflow/elementwise.py
--- a/ivy/functional/backends/tensorflow/elementwise.py
+++ b/ivy/functional/backends/tensorflow/elementwise.py
@@ -399,7 +399,15 @@ def lcm(
     return tf.experimental.numpy.lcm(x1, x2)
 
 
-@with_unsupported_dtypes({"2.13.0 and below": ("complex",)}, backend_version)
+@with_unsupported_dtypes(
+    {
+        "2.13.0 and below": (
+            "bool",
+            "complex",
+        )
+    },
+    backend_version,
+)
 def less(
     x1: Union[float, tf.Tensor, tf.Variable],
     x2: Union[float, tf.Tensor, tf.Variable],


Test patch: