We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Fix Frontend Failing Test: torch - creation.paddle.eye
To-do List: https://github.com/unifyai/ivy/issues/27498

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `ivy/functional/frontends/paddle/creation.py`
Content:
```
1 # global
2 import ivy
3 from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
4 import ivy.functional.frontends.paddle as paddle_frontend
5 from ivy.functional.frontends.paddle.func_wrapper import (
6     to_ivy_arrays_and_back,
7 )
8 
9 
10 @with_unsupported_dtypes({"2.6.0 and below": ("float16", "bfloat16")}, "paddle")
11 @to_ivy_arrays_and_back
12 def arange(start, end=None, step=1, dtype=None, name=None):
13     return ivy.arange(start, end, step=step, dtype=dtype)
14 
15 
16 @with_supported_dtypes(
17     {"2.6.0 and below": ("float16", "float32", "float64", "int32", "int64", "bool")},
18     "paddle",
19 )
20 @to_ivy_arrays_and_back
21 def assign(x, output=None):
22     if len(ivy.shape(x)) == 0:
23         x = ivy.reshape(ivy.Array(x), (1,))
24         if ivy.exists(output):
25             output = ivy.reshape(ivy.Array(output), (1,))
26     else:
27         x = ivy.reshape(x, ivy.shape(x))
28     ret = ivy.copy_array(x, to_ivy_array=False, out=output)
29     return ret
30 
31 
32 @with_unsupported_dtypes(
33     {"2.6.0 and below": ("bfloat16", "uint16", "uint32", "uint64")}, "paddle"
34 )
35 @to_ivy_arrays_and_back
36 def clone(x):
37     return ivy.copy_array(x)
38 
39 
40 @with_supported_dtypes(
41     {"2.6.0 and below": ("float32", "float64")},
42     "paddle",
43 )
44 @to_ivy_arrays_and_back
45 def complex(real, imag, name=None):
46     assert real.dtype == imag.dtype, (
47         "(InvalidArgument) The type of data we are trying to retrieve does not match"
48         " the type of data currently contained in the container."
49     )
50     complex_dtype = "complex64" if real.dtype == "float32" else "complex128"
51     imag_cmplx = ivy.astype(imag, complex_dtype) * 1j
52     complex_array = real + imag_cmplx
53     return complex_array
54 
55 
56 @with_supported_dtypes(
57     {"2.6.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
58 )
59 @to_ivy_arrays_and_back
60 def diag(x, offset=0, padding_value=0, name=None):
61     if len(x.shape) == 1:
62         padding_value = ivy.astype(padding_value, ivy.dtype(x))
63         ret = ivy.diagflat(x, offset=offset, padding_value=padding_value)
64         if len(ret.shape) != 2:
65             ret = ivy.reshape(ret, (1, 1))
66     else:
67         ret = ivy.diag(x, k=offset)
68     return ret
69 
70 
71 @with_supported_dtypes(
72     {"2.6.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
73 )
74 @to_ivy_arrays_and_back
75 def diagflat(x, offset=0, name=None):
76     arr = ivy.diagflat(x, offset=offset)
77     return arr
78 
79 
80 @to_ivy_arrays_and_back
81 def empty(shape, dtype=None):
82     return ivy.empty(shape=shape, dtype=dtype)
83 
84 
85 @to_ivy_arrays_and_back
86 def empty_like(x, dtype=None, name=None):
87     return ivy.empty_like(x, dtype=dtype)
88 
89 
90 @to_ivy_arrays_and_back
91 def eye(num_rows, num_columns=None, dtype=None, name=None):
92     return ivy.eye(num_rows, num_columns, dtype=dtype)
93 
94 
95 @to_ivy_arrays_and_back
96 def full(shape, fill_value, /, *, dtype=None, name=None):
97     dtype = "float32" if dtype is None else dtype
98     return ivy.full(shape, fill_value, dtype=dtype)
99 
100 
101 @to_ivy_arrays_and_back
102 def full_like(x, fill_value, /, *, dtype=None, name=None):
103     dtype = x.dtype if dtype is None else dtype
104     return ivy.full_like(x, fill_value, dtype=dtype)
105 
106 
107 @with_supported_dtypes(
108     {"2.6.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
109 )
110 @to_ivy_arrays_and_back
111 def linspace(start, stop, num, dtype=None, name=None):
112     return ivy.linspace(start, stop, num=num, dtype=dtype)
113 
114 
115 @with_supported_dtypes(
116     {"2.6.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
117 )
118 @to_ivy_arrays_and_back
119 def logspace(start, stop, num, base=10.0, dtype=None, name=None):
120     return ivy.logspace(start, stop, num=num, base=base, dtype=dtype)
121 
122 
123 @with_supported_dtypes(
124     {"2.6.0 and below": ("float32", "float64", "int32", "int64")}, "paddle"
125 )
126 @to_ivy_arrays_and_back
127 def meshgrid(*args, **kwargs):
128     return ivy.meshgrid(*args, indexing="ij")
129 
130 
131 @with_unsupported_dtypes({"2.6.0 and below": "int8"}, "paddle")
132 @to_ivy_arrays_and_back
133 def ones(shape, /, *, dtype=None, name=None):
134     dtype = "float32" if dtype is None else dtype
135     return ivy.ones(shape, dtype=dtype)
136 
137 
138 @with_unsupported_dtypes(
139     {"2.6.0 and below": ("uint8", "int8", "complex64", "complex128")}, "paddle"
140 )
141 @to_ivy_arrays_and_back
142 def ones_like(x, /, *, dtype=None, name=None):
143     dtype = x.dtype if dtype is None else dtype
144     return ivy.ones_like(x, dtype=dtype)
145 
146 
147 @to_ivy_arrays_and_back
148 def to_tensor(data, /, *, dtype=None, place=None, stop_gradient=True):
149     array = ivy.array(data, dtype=dtype, device=place)
150     return paddle_frontend.Tensor(array, dtype=dtype, place=place)
151 
152 
153 @with_unsupported_dtypes(
154     {
155         "2.6.0 and below": (
156             "uint8",
157             "int8",
158             "int16",
159             "float16",
160             "complex64",
161             "complex128",
162             "bool",
163         )
164     },
165     "paddle",
166 )
167 @to_ivy_arrays_and_back
168 def tril(x, diagonal=0, name=None):
169     return ivy.tril(x, k=diagonal)
170 
171 
172 @with_supported_dtypes({"2.6.0 and below": ("int32", "int64")}, "paddle")
173 @to_ivy_arrays_and_back
174 def tril_indices(row, col, offset=0, dtype="int64"):
175     arr = ivy.tril_indices(row, col, offset)
176     arr = ivy.astype(arr, dtype)
177     return arr
178 
179 
180 @with_unsupported_dtypes(
181     {
182         "2.6.0 and below": (
183             "uint8",
184             "int8",
185             "int16",
186             "float16",
187             "complex64",
188             "complex128",
189             "bool",
190         )
191     },
192     "paddle",
193 )
194 @to_ivy_arrays_and_back
195 def triu(x, diagonal=0, name=None):
196     return ivy.triu(x, k=diagonal)
197 
198 
199 @with_supported_dtypes({"2.6.0 and below": ("int32", "int64")}, "paddle")
200 @to_ivy_arrays_and_back
201 def triu_indices(row, col=None, offset=0, dtype="int64"):
202     arr = ivy.triu_indices(row, col, offset)
203     if not ivy.to_scalar(ivy.shape(arr[0], as_array=True)):
204         return arr
205     arr = ivy.astype(arr, dtype)
206     return arr
207 
208 
209 @with_unsupported_dtypes({"2.6.0 and below": "int8"}, "paddle")
210 @to_ivy_arrays_and_back
211 def zeros(shape, /, *, dtype=None, name=None):
212     dtype = "float32" if dtype is None else dtype
213     return ivy.zeros(shape, dtype=dtype)
214 
215 
216 @with_unsupported_dtypes(
217     {"2.6.0 and below": ("uint8", "int8", "complex64", "complex128")}, "paddle"
218 )
219 @to_ivy_arrays_and_back
220 def zeros_like(x, /, *, dtype=None, name=None):
221     dtype = x.dtype if dtype is None else dtype
222     return ivy.zeros_like(x, dtype=dtype)
223
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/ivy/functional/frontends/paddle/creation.py b/ivy/functional/frontends/paddle/creation.py
--- a/ivy/functional/frontends/paddle/creation.py
+++ b/ivy/functional/frontends/paddle/creation.py
@@ -87,6 +87,9 @@
     return ivy.empty_like(x, dtype=dtype)
 
 
+@with_supported_dtypes(
+    {"2.6.0 and below": ("float16", "float32", "float64", "int32", "int64")}, "paddle"
+)
 @to_ivy_arrays_and_back
 def eye(num_rows, num_columns=None, dtype=None, name=None):
     return ivy.eye(num_rows, num_columns, dtype=dtype)

{"golden_diff": "diff --git a/ivy/functional/frontends/paddle/creation.py b/ivy/functional/frontends/paddle/creation.py\n--- a/ivy/functional/frontends/paddle/creation.py\n+++ b/ivy/functional/frontends/paddle/creation.py\n@@ -87,6 +87,9 @@\n     return ivy.empty_like(x, dtype=dtype)\n \n \n+@with_supported_dtypes(\n+    {\"2.6.0 and below\": (\"float16\", \"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n+)\n @to_ivy_arrays_and_back\n def eye(num_rows, num_columns=None, dtype=None, name=None):\n     return ivy.eye(num_rows, num_columns, dtype=dtype)\n", "issue": "Fix Frontend Failing Test: torch - creation.paddle.eye\nTo-do List: https://github.com/unifyai/ivy/issues/27498\n", "before_files": [{"content": "# global\nimport ivy\nfrom ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes\nimport ivy.functional.frontends.paddle as paddle_frontend\nfrom ivy.functional.frontends.paddle.func_wrapper import (\n    to_ivy_arrays_and_back,\n)\n\n\n@with_unsupported_dtypes({\"2.6.0 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef arange(start, end=None, step=1, dtype=None, name=None):\n    return ivy.arange(start, end, step=step, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float16\", \"float32\", \"float64\", \"int32\", \"int64\", \"bool\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef assign(x, output=None):\n    if len(ivy.shape(x)) == 0:\n        x = ivy.reshape(ivy.Array(x), (1,))\n        if ivy.exists(output):\n            output = ivy.reshape(ivy.Array(output), (1,))\n    else:\n        x = ivy.reshape(x, ivy.shape(x))\n    ret = ivy.copy_array(x, to_ivy_array=False, out=output)\n    return ret\n\n\n@with_unsupported_dtypes(\n    {\"2.6.0 and below\": (\"bfloat16\", \"uint16\", \"uint32\", \"uint64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef clone(x):\n    return ivy.copy_array(x)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef complex(real, imag, name=None):\n    assert real.dtype == imag.dtype, (\n        \"(InvalidArgument) The type of data we are trying to retrieve does not match\"\n        \" the type of data currently contained in the container.\"\n    )\n    complex_dtype = \"complex64\" if real.dtype == \"float32\" else \"complex128\"\n    imag_cmplx = ivy.astype(imag, complex_dtype) * 1j\n    complex_array = real + imag_cmplx\n    return complex_array\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef diag(x, offset=0, padding_value=0, name=None):\n    if len(x.shape) == 1:\n        padding_value = ivy.astype(padding_value, ivy.dtype(x))\n        ret = ivy.diagflat(x, offset=offset, padding_value=padding_value)\n        if len(ret.shape) != 2:\n            ret = ivy.reshape(ret, (1, 1))\n    else:\n        ret = ivy.diag(x, k=offset)\n    return ret\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef diagflat(x, offset=0, name=None):\n    arr = ivy.diagflat(x, offset=offset)\n    return arr\n\n\n@to_ivy_arrays_and_back\ndef empty(shape, dtype=None):\n    return ivy.empty(shape=shape, dtype=dtype)\n\n\n@to_ivy_arrays_and_back\ndef empty_like(x, dtype=None, name=None):\n    return ivy.empty_like(x, dtype=dtype)\n\n\n@to_ivy_arrays_and_back\ndef eye(num_rows, num_columns=None, dtype=None, name=None):\n    return ivy.eye(num_rows, num_columns, dtype=dtype)\n\n\n@to_ivy_arrays_and_back\ndef full(shape, fill_value, /, *, dtype=None, name=None):\n    dtype = \"float32\" if dtype is None else dtype\n    return ivy.full(shape, fill_value, dtype=dtype)\n\n\n@to_ivy_arrays_and_back\ndef full_like(x, fill_value, /, *, dtype=None, name=None):\n    dtype = x.dtype if dtype is None else dtype\n    return ivy.full_like(x, fill_value, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef linspace(start, stop, num, dtype=None, name=None):\n    return ivy.linspace(start, stop, num=num, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef logspace(start, stop, num, base=10.0, dtype=None, name=None):\n    return ivy.logspace(start, stop, num=num, base=base, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef meshgrid(*args, **kwargs):\n    return ivy.meshgrid(*args, indexing=\"ij\")\n\n\n@with_unsupported_dtypes({\"2.6.0 and below\": \"int8\"}, \"paddle\")\n@to_ivy_arrays_and_back\ndef ones(shape, /, *, dtype=None, name=None):\n    dtype = \"float32\" if dtype is None else dtype\n    return ivy.ones(shape, dtype=dtype)\n\n\n@with_unsupported_dtypes(\n    {\"2.6.0 and below\": (\"uint8\", \"int8\", \"complex64\", \"complex128\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef ones_like(x, /, *, dtype=None, name=None):\n    dtype = x.dtype if dtype is None else dtype\n    return ivy.ones_like(x, dtype=dtype)\n\n\n@to_ivy_arrays_and_back\ndef to_tensor(data, /, *, dtype=None, place=None, stop_gradient=True):\n    array = ivy.array(data, dtype=dtype, device=place)\n    return paddle_frontend.Tensor(array, dtype=dtype, place=place)\n\n\n@with_unsupported_dtypes(\n    {\n        \"2.6.0 and below\": (\n            \"uint8\",\n            \"int8\",\n            \"int16\",\n            \"float16\",\n            \"complex64\",\n            \"complex128\",\n            \"bool\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef tril(x, diagonal=0, name=None):\n    return ivy.tril(x, k=diagonal)\n\n\n@with_supported_dtypes({\"2.6.0 and below\": (\"int32\", \"int64\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef tril_indices(row, col, offset=0, dtype=\"int64\"):\n    arr = ivy.tril_indices(row, col, offset)\n    arr = ivy.astype(arr, dtype)\n    return arr\n\n\n@with_unsupported_dtypes(\n    {\n        \"2.6.0 and below\": (\n            \"uint8\",\n            \"int8\",\n            \"int16\",\n            \"float16\",\n            \"complex64\",\n            \"complex128\",\n            \"bool\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef triu(x, diagonal=0, name=None):\n    return ivy.triu(x, k=diagonal)\n\n\n@with_supported_dtypes({\"2.6.0 and below\": (\"int32\", \"int64\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef triu_indices(row, col=None, offset=0, dtype=\"int64\"):\n    arr = ivy.triu_indices(row, col, offset)\n    if not ivy.to_scalar(ivy.shape(arr[0], as_array=True)):\n        return arr\n    arr = ivy.astype(arr, dtype)\n    return arr\n\n\n@with_unsupported_dtypes({\"2.6.0 and below\": \"int8\"}, \"paddle\")\n@to_ivy_arrays_and_back\ndef zeros(shape, /, *, dtype=None, name=None):\n    dtype = \"float32\" if dtype is None else dtype\n    return ivy.zeros(shape, dtype=dtype)\n\n\n@with_unsupported_dtypes(\n    {\"2.6.0 and below\": (\"uint8\", \"int8\", \"complex64\", \"complex128\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef zeros_like(x, /, *, dtype=None, name=None):\n    dtype = x.dtype if dtype is None else dtype\n    return ivy.zeros_like(x, dtype=dtype)\n", "path": "ivy/functional/frontends/paddle/creation.py"}], "after_files": [{"content": "# global\nimport ivy\nfrom ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes\nimport ivy.functional.frontends.paddle as paddle_frontend\nfrom ivy.functional.frontends.paddle.func_wrapper import (\n    to_ivy_arrays_and_back,\n)\n\n\n@with_unsupported_dtypes({\"2.6.0 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef arange(start, end=None, step=1, dtype=None, name=None):\n    return ivy.arange(start, end, step=step, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float16\", \"float32\", \"float64\", \"int32\", \"int64\", \"bool\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef assign(x, output=None):\n    if len(ivy.shape(x)) == 0:\n        x = ivy.reshape(ivy.Array(x), (1,))\n        if ivy.exists(output):\n            output = ivy.reshape(ivy.Array(output), (1,))\n    else:\n        x = ivy.reshape(x, ivy.shape(x))\n    ret = ivy.copy_array(x, to_ivy_array=False, out=output)\n    return ret\n\n\n@with_unsupported_dtypes(\n    {\"2.6.0 and below\": (\"bfloat16\", \"uint16\", \"uint32\", \"uint64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef clone(x):\n    return ivy.copy_array(x)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef complex(real, imag, name=None):\n    assert real.dtype == imag.dtype, (\n        \"(InvalidArgument) The type of data we are trying to retrieve does not match\"\n        \" the type of data currently contained in the container.\"\n    )\n    complex_dtype = \"complex64\" if real.dtype == \"float32\" else \"complex128\"\n    imag_cmplx = ivy.astype(imag, complex_dtype) * 1j\n    complex_array = real + imag_cmplx\n    return complex_array\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef diag(x, offset=0, padding_value=0, name=None):\n    if len(x.shape) == 1:\n        padding_value = ivy.astype(padding_value, ivy.dtype(x))\n        ret = ivy.diagflat(x, offset=offset, padding_value=padding_value)\n        if len(ret.shape) != 2:\n            ret = ivy.reshape(ret, (1, 1))\n    else:\n        ret = ivy.diag(x, k=offset)\n    return ret\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef diagflat(x, offset=0, name=None):\n    arr = ivy.diagflat(x, offset=offset)\n    return arr\n\n\n@to_ivy_arrays_and_back\ndef empty(shape, dtype=None):\n    return ivy.empty(shape=shape, dtype=dtype)\n\n\n@to_ivy_arrays_and_back\ndef empty_like(x, dtype=None, name=None):\n    return ivy.empty_like(x, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float16\", \"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef eye(num_rows, num_columns=None, dtype=None, name=None):\n    return ivy.eye(num_rows, num_columns, dtype=dtype)\n\n\n@to_ivy_arrays_and_back\ndef full(shape, fill_value, /, *, dtype=None, name=None):\n    dtype = \"float32\" if dtype is None else dtype\n    return ivy.full(shape, fill_value, dtype=dtype)\n\n\n@to_ivy_arrays_and_back\ndef full_like(x, fill_value, /, *, dtype=None, name=None):\n    dtype = x.dtype if dtype is None else dtype\n    return ivy.full_like(x, fill_value, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef linspace(start, stop, num, dtype=None, name=None):\n    return ivy.linspace(start, stop, num=num, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef logspace(start, stop, num, base=10.0, dtype=None, name=None):\n    return ivy.logspace(start, stop, num=num, base=base, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.6.0 and below\": (\"float32\", \"float64\", \"int32\", \"int64\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef meshgrid(*args, **kwargs):\n    return ivy.meshgrid(*args, indexing=\"ij\")\n\n\n@with_unsupported_dtypes({\"2.6.0 and below\": \"int8\"}, \"paddle\")\n@to_ivy_arrays_and_back\ndef ones(shape, /, *, dtype=None, name=None):\n    dtype = \"float32\" if dtype is None else dtype\n    return ivy.ones(shape, dtype=dtype)\n\n\n@with_unsupported_dtypes(\n    {\"2.6.0 and below\": (\"uint8\", \"int8\", \"complex64\", \"complex128\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef ones_like(x, /, *, dtype=None, name=None):\n    dtype = x.dtype if dtype is None else dtype\n    return ivy.ones_like(x, dtype=dtype)\n\n\n@to_ivy_arrays_and_back\ndef to_tensor(data, /, *, dtype=None, place=None, stop_gradient=True):\n    array = ivy.array(data, dtype=dtype, device=place)\n    return paddle_frontend.Tensor(array, dtype=dtype, place=place)\n\n\n@with_unsupported_dtypes(\n    {\n        \"2.6.0 and below\": (\n            \"uint8\",\n            \"int8\",\n            \"int16\",\n            \"float16\",\n            \"complex64\",\n            \"complex128\",\n            \"bool\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef tril(x, diagonal=0, name=None):\n    return ivy.tril(x, k=diagonal)\n\n\n@with_supported_dtypes({\"2.6.0 and below\": (\"int32\", \"int64\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef tril_indices(row, col, offset=0, dtype=\"int64\"):\n    arr = ivy.tril_indices(row, col, offset)\n    arr = ivy.astype(arr, dtype)\n    return arr\n\n\n@with_unsupported_dtypes(\n    {\n        \"2.6.0 and below\": (\n            \"uint8\",\n            \"int8\",\n            \"int16\",\n            \"float16\",\n            \"complex64\",\n            \"complex128\",\n            \"bool\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef triu(x, diagonal=0, name=None):\n    return ivy.triu(x, k=diagonal)\n\n\n@with_supported_dtypes({\"2.6.0 and below\": (\"int32\", \"int64\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef triu_indices(row, col=None, offset=0, dtype=\"int64\"):\n    arr = ivy.triu_indices(row, col, offset)\n    if not ivy.to_scalar(ivy.shape(arr[0], as_array=True)):\n        return arr\n    arr = ivy.astype(arr, dtype)\n    return arr\n\n\n@with_unsupported_dtypes({\"2.6.0 and below\": \"int8\"}, \"paddle\")\n@to_ivy_arrays_and_back\ndef zeros(shape, /, *, dtype=None, name=None):\n    dtype = \"float32\" if dtype is None else dtype\n    return ivy.zeros(shape, dtype=dtype)\n\n\n@with_unsupported_dtypes(\n    {\"2.6.0 and below\": (\"uint8\", \"int8\", \"complex64\", \"complex128\")}, \"paddle\"\n)\n@to_ivy_arrays_and_back\ndef zeros_like(x, /, *, dtype=None, name=None):\n    dtype = x.dtype if dtype is None else dtype\n    return ivy.zeros_like(x, dtype=dtype)\n", "path": "ivy/functional/frontends/paddle/creation.py"}]}