Merge pull request #293 from IntelPython/return-input-array-on-empty-axes

Return input array unchanged when axes=() (ignore out parameter)

Author: antonwolfy

mkl_fft/_fft_utils.py

@@ -519,16 +519,13 @@ def _c2c_fftnd_impl(
     else:
         x = np.asarray(x)
 
-        # Fast path: FFT over no axes is complete identity (preserve dtype)
+        # Fast path: FFT over no axes is a complete identity operation.
+        # Returns the input unchanged (same object, no copy), preserving
+        # dtype and avoiding any FFT computation. The out parameter is
+        # ignored to match NumPy behavior.
         _, xa = _cook_nd_args(x, s, axes)
         if len(xa) == 0:
-            if out is None:
-                out = x.copy()
-            else:
-                _validate_out_array(out, x, x.dtype)
-                np.copyto(out, x)
-            # No scaling applied - identity transform has no normalization
-            return out
+            return x
 
         if _complementary and x.dtype in valid_dtypes:
             if out is None:

mkl_fft/tests/test_fftnd.py

@@ -353,12 +353,33 @@ def test_empty_axes_with_out(dtype, func):
     else:
         x = rnd.random((3, 4)).astype(dtype)
 
-    # For axes=(), output dtype should match input dtype (identity transform)
+    # NumPy ignores out parameter when axes=() and returns input
     out = np.empty_like(x, dtype=dtype)
     result = getattr(mkl_fft, func)(x, axes=(), out=out)
-    expected = getattr(np.fft, func)(x, axes=())
+    expected = getattr(np.fft, func)(x, axes=(), out=out)
 
-    # Result should be written to out
-    assert result is out
-    rtol, atol = _get_rtol_atol(result)
-    assert_allclose(result, expected, rtol=rtol, atol=atol, strict=True)
+    # Result should be the input array (out parameter ignored)
+    assert result is x, f"{func} with axes=() should return input (ignore out)"
+    assert expected is x, "NumPy should also return input"
+    assert result is expected
+
+
+@pytest.mark.parametrize(
+    "dtype", [np.float32, np.float64, np.complex64, np.complex128]
+)
+@pytest.mark.parametrize("func", ["fftn", "ifftn", "fft2", "ifft2"])
+def test_empty_axes_returns_same_object(dtype, func):
+    if np.issubdtype(dtype, np.complexfloating):
+        x = rnd.random((3, 4)).astype(dtype) + 1j * rnd.random((3, 4)).astype(
+            dtype
+        )
+    else:
+        x = rnd.random((3, 4)).astype(dtype)
+
+    # Without out parameter, should return the same object
+    result = getattr(mkl_fft, func)(x, axes=())
+
+    # Verify it's the exact same object (identity check)
+    assert (
+        result is x
+    ), f"{func} with axes=() should return the same object, not a copy"