Add array and axis testing to repeat()

Still need to add values testing.

Author: asmeurer

array_api_tests/test_manipulation_functions.py

@@ -287,6 +287,45 @@ def test_permute_dims(x, axes):
                          out_indices=permuted_indices)
 
 
+@pytest.mark.min_version("2023.12")
+@given(
+    x=hh.arrays(dtype=hh.all_dtypes, shape=shared_shapes(min_dims=1)),
+    kw=hh.kwargs(
+        axis=st.none() | shared_shapes(min_dims=1).flatmap(
+            lambda s: st.integers(-len(s), len(s) - 1)
+        )
+    ),
+    data=st.data(),
+)
+def test_repeat(x, kw, data):
+    shape = x.shape
+    axis = kw.get("axis", None)
+    dim = math.prod(shape) if axis is None else shape[axis]
+    repeat_strat = st.integers(1, 4)
+    repeats = data.draw(repeat_strat
+                        | hh.arrays(dtype=hh.int_dtypes, elements=repeat_strat,
+                                    shape=st.sampled_from([(1,), (dim,)])),
+        label="repeats")
+    if isinstance(repeats, int):
+        n_repitions = dim*repeats
+    else:
+        if repeats.shape == (1,):
+            n_repitions = dim*repeats[0]
+        else:
+            n_repitions = int(xp.sum(repeats))
+
+    out = xp.repeat(x, repeats, **kw)
+    ph.assert_dtype("repeat", in_dtype=x.dtype, out_dtype=out.dtype)
+    if axis is None:
+        expected_shape = (n_repitions,)
+    else:
+        expected_shape = list(shape)
+        expected_shape[axis] = n_repitions
+        expected_shape = tuple(expected_shape)
+    ph.assert_shape("repeat", out_shape=out.shape, expected=expected_shape)
+    # TODO: values testing
+
+
 @st.composite
 def reshape_shapes(draw, shape):
     size = 1 if len(shape) == 0 else math.prod(shape)
@@ -298,20 +337,6 @@ def reshape_shapes(draw, shape):
     return tuple(rshape)
 
 
-@pytest.mark.min_version("2023.12")
-@given(
-    x=hh.arrays(dtype=hh.all_dtypes, shape=hh.shapes(min_dims=1)),
-    repeats=st.integers(1, 4),
-)
-def test_repeat(x, repeats):
-    # TODO: test array repeats and non-None axis, adjust shape and value testing accordingly
-    out = xp.repeat(x, repeats)
-    ph.assert_dtype("repeat", in_dtype=x.dtype, out_dtype=out.dtype)
-    expected_shape = (math.prod(x.shape) * repeats,)
-    ph.assert_shape("repeat", out_shape=out.shape, expected=expected_shape)
-    # TODO: values testing
-
-
 @pytest.mark.unvectorized
 @pytest.mark.skip("flaky")  # TODO: fix!
 @given(