Revert "fold_function"

This reverts commit 524d93b.

ivy/functional/frontends/paddle/nn/functional/common.py

@@ -114,3 +114,7 @@ def linear(x, weight, bias=None, name=None):
 @with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
 def alpha_dropout( x, p=0.5, training=True, name=None ):
     return ivy.alpha_dropout(x, p=p, training=training)
+@to_ivy_arrays_and_back
+@with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
+def fold( x, output_sizes, kernel_sizes, strides=1, paddings=0, dilations=1, name=None ):
+    return ivy.fold(x, output_sizes, kernel_sizes, strides, paddings, dilations)

ivy_tests/test_ivy/test_frontends/test_paddle/test_nn/test_functional/test_common.py

@@ -464,3 +464,51 @@ def test_paddle_alpha_dropout(
         axis=axis,
         mode=mode,
     )
+
+#fold
+@handle_frontend_test(
+    fn_tree="paddle.nn.functional.common.fold",
+    d_type_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        num_arrays=1,
+        shared_dtype=True,
+        min_value=2,
+        max_value=5,
+        min_num_dims=1,
+        max_num_dims=1,
+        min_dim_size=2,
+    ),
+    p=st.floats(min_value=0.0, max_value=1.0),
+    axis=st.integers(min_value=0, max_value=1),
+    training=st.booleans(),
+    mode=st.one_of(
+        *[st.just(seq) for seq in ["upscale_in_train", "downscale_in_infer"]]
+    ),
+)
+def test_paddle_fold(
+    *,
+    d_type_and_x,
+    p,
+    on_device,
+    fn_tree,
+    backend_fw,
+    frontend,
+    test_flags,
+    training,
+    axis,
+    mode,
+):
+    dtype, x = d_type_and_x
+    helpers.test_frontend_function(
+        input_dtypes=dtype,
+        p=p,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        fn_tree=fn_tree,
+        test_flags=test_flags,
+        on_device=on_device,
+        x=x[0],
+        training=training,
+        axis=axis,
+        mode=mode,
+    )