feat: add one_hot function of paddle frontend(#24153)

ivy/functional/frontends/paddle/manipulation.py

@@ -117,6 +117,16 @@ def index_add(x, index, axis, value, *, name=None):
     return ret
 
 
+@with_supported_dtypes({"2.5.1 and below": ("int32", "int64")}, "paddle")
+@to_ivy_arrays_and_back
+def one_hot(x, num_classes, name=None):
+    if not isinstance(num_classes, int) or num_classes <= 0:
+        raise ValueError("num_classes must be a positive integer.")
+
+    one_hot_tensor = ivy.one_hot(x, num_classes)
+    return one_hot_tensor.astype(ivy.float32)
+
+
 @to_ivy_arrays_and_back
 def put_along_axis(arr, indices, values, axis, reduce="assign"):
     result = ivy.put_along_axis(arr, indices, values, axis)

ivy_tests/test_ivy/test_frontends/test_paddle/test_manipulation.py

@@ -297,6 +297,39 @@ def dtypes_x_reshape(draw):
 # ------------ #
 
 
+@handle_frontend_test(
+    fn_tree="paddle.one_hot",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=["int64"],
+        min_value=0,
+        min_num_dims=1,
+        max_num_dims=5,
+    ),
+    num_classes=helpers.ints(min_value=1),
+)
+def test_one_hot(
+    *,
+    dtype_and_x,
+    num_classes,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+    backend_fw,
+):
+    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],
+        num_classes=num_classes,
+        backend_to_test=backend_fw,
+    )
+
+
 # abs
 @handle_frontend_test(
     fn_tree="paddle.abs",