feat: implement rfftn to Paddle Frontend (#23484)

ivy/functional/frontends/paddle/fft.py

@@ -131,3 +131,29 @@ def rfftfreq(n, d=1.0, dtype=None, name=None):
     pos_max = n // 2 + 1
     indices = ivy.arange(0, pos_max, dtype=dtype)
     return indices * val
+
+
+@with_supported_dtypes(
+    {"2.5.1 and below": ("complex64", "complex128")},
+    "paddle",
+)
+@to_ivy_arrays_and_back
+def rfftn(x, s=None, axes=None, norm="backward", name=None):
+    """Compute the N-dimensional discrete Fourier Transform over any number of axes in
+    an M-dimensional real array by means of the Fast Fourier Transform (FFT)."""
+    if s is None:
+        s = x.shape
+
+    # Apply rfft along the last axis
+    rfft_result = ivy.rfftn(x, s=s, axes=axes, norm=norm, name=name)
+
+    if axes is None:
+        # If axes is not specified, transform all axes except the last one.
+        axes = tuple(range(x.ndim - 1))
+
+    # Apply fft on the specified axes for N-dimensional FFT
+    fftn_result = rfft_result
+    for axis in axes:
+        fftn_result = ivy.fft(fftn_result, axis=axis, norm=norm)
+
+    return fftn_result

ivy_tests/test_ivy/test_frontends/test_paddle/test_fft.py

@@ -242,3 +242,52 @@ def test_paddle_rfftfreq(
         n=n,
         d=d,
     )
+
+
+@handle_frontend_test(
+    fn_tree="paddle.fft.rfftn",
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_value=-10,
+        max_value=10,
+        min_num_dims=1,
+        valid_axis=True,
+        force_int_axis=True,
+    ),
+    s=st.one_of(
+        st.tuples(
+            st.integers(min_value=2, max_value=10),
+            st.integers(min_value=2, max_value=10),
+        ),
+        st.just(None),
+    ),
+    axes=st.one_of(
+        st.lists(
+            st.integers(min_value=0, max_value=2), min_size=1, max_size=3, unique=True
+        ),
+        st.just(None),
+    ),
+    norm=st.sampled_from(["backward", "ortho", "forward"]),
+)
+def test_paddle_rfftn(
+    dtype_x_axis,
+    s,
+    axes,
+    norm,
+    frontend,
+    backend_fw,
+    test_flags,
+    fn_tree,
+):
+    input_dtypes, x, axis = dtype_x_axis
+    helpers.test_frontend_function(
+        input_dtypes=input_dtypes,
+        backend_to_test=backend_fw,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        x=x[0],
+        s=s,
+        axes=axes,
+        norm=norm,
+    )