feat: irfft2 function and test implemented. (ivy-llc#23353)

Co-authored-by: nathzi1505 <41519676+nathzi1505@users.noreply.github.com>

ivy/functional/frontends/paddle/fft.py

@@ -51,19 +51,19 @@ def fftshift(x, axes=None, name=None):
     "paddle",
 )
 @to_ivy_arrays_and_back
-def hfft(x, n=None, axis=-1, norm="backward", name=None):
+def hfft(x, n=None, axes=-1, norm="backward", name=None):
     """Compute the FFT of a signal that has Hermitian symmetry, resulting in a real
     spectrum."""
     # Determine the input shape and axis length
     input_shape = x.shape
-    input_len = input_shape[axis]
+    input_len = input_shape[axes]
 
     # Calculate n if not provided
     if n is None:
         n = 2 * (input_len - 1)
 
     # Perform the FFT along the specified axis
-    result = ivy.fft(x, axis, n=n, norm=norm)
+    result = ivy.fft(x, axes, n=n, norm=norm)
 
     return ivy.real(result)
 
@@ -146,7 +146,48 @@ def irfft(x, n=None, axis=-1.0, norm="backward", name=None):
 
 
 @with_supported_dtypes(
-    {"2.5.1 and below": ("complex64", "complex128")},
+    {
+        "2.5.1 and below": (
+            "int32",
+            "int64",
+            "float16",
+            "float32",
+            "float64",
+            "complex64",
+            "complex128",
+        )
+    },
+    "paddle",
+)
+@to_ivy_arrays_and_back
+def irfft2(x, s=None, axes=(-2, -1), norm="backward"):
+    # Handle values if None
+    if s is None:
+        s = x.shape
+    if axes is None:
+        axes = (-2, -1)
+
+    # Calculate the normalization factor 'n' based on the shape 's'
+    n = ivy.prod(ivy.array(s))
+
+    result = ivy.ifftn(x, dim=axes[0], norm=norm)
+
+    # Normalize the result based on the 'norm' parameter
+    if norm == "backward":
+        result /= n
+    elif norm == "forward":
+        result *= n
+    elif norm == "ortho":
+        result /= ivy.sqrt(n)
+    return result
+
+@with_supported_dtypes(
+    {
+        "2.5.1 and below": (
+            "complex64",
+            "complex128"
+        )
+    },
     "paddle",
 )
 @to_ivy_arrays_and_back

ivy_tests/test_ivy/test_frontends/test_paddle/test_fft.py

@@ -6,6 +6,11 @@
 from ivy_tests.test_ivy.helpers import handle_frontend_test
 
 
+# Custom Hypothesis strategy for generating sequences of 2 integers
+def sequence_of_two_integers():
+    return st.lists(st.integers(), min_size=2, max_size=2)
+
+
 @handle_frontend_test(
     fn_tree="paddle.fft.fft",
     dtype_x_axis=helpers.dtype_values_axis(
@@ -260,9 +265,60 @@ def test_paddle_irfft(
         n=n,
         axis=axis,
         norm=norm,
+    )
+
+
+@handle_frontend_test(
+    fn_tree="paddle.fft.irfft2",
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_value=-10,
+        max_value=10,
+        min_num_dims=2,
         valid_axis=True,
         force_int_axis=True,
-    )
+    ),
+)
+@given(st.data())
+def test_paddle_irfft2(
+    data,
+    dtype_x_axis,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x, axes = dtype_x_axis
+    for norm in ["backward", "forward", "ortho"]:
+        s_values = data.draw(s_strategy)
+        axes_values = data.draw(axes_strategy)
+
+        # Ensure s and axes are sequences of 2 integers
+        assert len(s_values) == 2
+        assert len(axes_values) == 2
+
+        # Convert s and axes to tuples as needed
+        s = tuple(s_values)
+        axes = tuple(axes_values)
+
+        helpers.test_frontend_function(
+            input_dtypes=input_dtype,
+            frontend=frontend,
+            backend_to_test=backend_fw,
+            test_flags=test_flags,
+            fn_tree=fn_tree,
+            on_device=on_device,
+            test_values=True,
+            x=x[0],
+            s=s,
+            axes=axes,
+            norm=norm,
+        )
+
+# Use the custom strategy for s and axes
+axes_strategy = sequence_of_two_integers()
+s_strategy = sequence_of_two_integers()
 
 
 @handle_frontend_test(