Implement unstack using multiple outputs (#575)

cubed/__init__.py

@@ -286,6 +286,7 @@
     roll,
     squeeze,
     stack,
+    unstack,
 )
 
 __all__ += [
@@ -300,6 +301,7 @@
     "roll",
     "squeeze",
     "stack",
+    "unstack",
 ]
 
 from .array_api.searching_functions import argmax, argmin, where

cubed/array_api/__init__.py

@@ -228,6 +228,7 @@
     roll,
     squeeze,
     stack,
+    unstack,
 )
 
 __all__ += [
@@ -242,6 +243,7 @@
     "roll",
     "squeeze",
     "stack",
+    "unstack",
 ]
 
 from .searching_functions import argmax, argmin, where

cubed/array_api/manipulation_functions.py

@@ -412,3 +412,43 @@ def key_function(out_key):
 
 def _read_stack_chunk(array, axis=None):
     return nxp.expand_dims(array, axis=axis)
+
+
+def unstack(x, /, *, axis=0):
+    axis = validate_axis(axis, x.ndim)
+
+    n_arrays = x.shape[axis]
+
+    if n_arrays == 1:
+        return (x,)
+
+    shape = x.shape[:axis] + x.shape[axis + 1 :]
+    dtype = x.dtype
+    chunks = x.chunks[:axis] + x.chunks[axis + 1 :]
+
+    def key_function(out_key):
+        out_coords = out_key[1:]
+        all_in_coords = tuple(
+            out_coords[:axis] + (i,) + out_coords[axis:]
+            for i in range(x.numblocks[axis])
+        )
+        return tuple((x.name,) + in_coords for in_coords in all_in_coords)
+
+    return general_blockwise(
+        _unstack_chunk,
+        key_function,
+        x,
+        shapes=[shape] * n_arrays,
+        dtypes=[dtype] * n_arrays,
+        chunkss=[chunks] * n_arrays,
+        target_stores=[None] * n_arrays,  # filled in by general_blockwise
+        axis=axis,
+    )
+
+
+def _unstack_chunk(*arrs, axis=0):
+    # unstack each array in arrs and yield all in turn
+    for arr in arrs:
+        # TODO: replace with nxp.unstack(arr, axis=axis) when array-api-compat has unstack
+        for a in tuple(nxp.moveaxis(arr, axis, 0)):
+            yield a

cubed/tests/test_array_api.py

@@ -627,6 +627,28 @@ def test_stack(spec, executor):
     )
 
 
+@pytest.mark.parametrize("chunks", [(1, 2, 3), (2, 2, 3), (3, 2, 3)])
+def test_unstack(spec, executor, chunks):
+    a = xp.full((4, 6), 1, chunks=(2, 3), spec=spec)
+    b = xp.full((4, 6), 2, chunks=(2, 3), spec=spec)
+    c = xp.full((4, 6), 3, chunks=(2, 3), spec=spec)
+    d = xp.stack([a, b, c], axis=0)
+
+    d = d.rechunk(chunks)
+
+    au, bu, cu = cubed.compute(*xp.unstack(d), executor=executor, optimize_graph=False)
+
+    assert_array_equal(au, np.full((4, 6), 1))
+    assert_array_equal(bu, np.full((4, 6), 2))
+    assert_array_equal(cu, np.full((4, 6), 3))
+
+
+def test_unstack_noop(spec):
+    a = xp.full((1, 4, 6), 1, chunks=(1, 2, 3), spec=spec)
+    (b,) = xp.unstack(a)
+    assert a is b
+
+
 # Searching functions
 
 

cubed/tests/test_mem_utilization.py

@@ -279,6 +279,15 @@ def test_stack(tmp_path, spec, executor):
     run_operation(tmp_path, executor, "stack", c)
 
 
+@pytest.mark.slow
+def test_unstack(tmp_path, spec, executor):
+    a = cubed.random.random(
+        (2, 10000, 10000), chunks=(2, 5000, 5000), spec=spec
+    )  # 400MB chunks
+    b, c = xp.unstack(a)
+    run_operation(tmp_path, executor, "unstack", b, c)
+
+
 # Searching Functions