Implement test_outer()

Author: asmeurer

array_api_tests/hypothesis_helpers.py

@@ -110,6 +110,8 @@ def tuples(elements, *, min_size=0, max_size=None, unique_by=None, unique=False)
     lambda shape: prod(i for i in shape if i) < MAX_ARRAY_SIZE
 )
 
+one_d_shapes = xps.array_shapes(min_dims=1, max_dims=1, min_side=0, max_side=SQRT_MAX_ARRAY_SIZE)
+
 # Matrix shapes assume stacks of matrices
 matrix_shapes = xps.array_shapes(min_dims=2, min_side=1).filter(
     lambda shape: prod(i for i in shape if i) < MAX_ARRAY_SIZE

array_api_tests/test_linalg.py

@@ -14,15 +14,15 @@
 """
 
 from hypothesis import assume, given
-from hypothesis.strategies import booleans, composite, none, integers, shared
+from hypothesis.strategies import booleans, composite, none, tuples, integers, shared
 
 from .array_helpers import (assert_exactly_equal, ndindex, asarray,
                             numeric_dtype_objects, promote_dtypes)
 from .hypothesis_helpers import (xps, dtypes, shapes, kwargs, matrix_shapes,
                                  square_matrix_shapes, symmetric_matrices,
                                  positive_definite_matrices, MAX_ARRAY_SIZE,
                                  invertible_matrices, two_mutual_arrays,
-                                 mutually_promotable_dtypes)
+                                 mutually_promotable_dtypes, one_d_shapes)
 from .pytest_helpers import raises
 
 from .test_broadcasting import broadcast_shapes
@@ -339,12 +339,27 @@ def test_matrix_transpose(x):
     _test_stacks(linalg.matrix_transpose, x, res=res, true_val=true_val)
 
 @given(
-    x1=xps.arrays(dtype=xps.floating_dtypes(), shape=shapes),
-    x2=xps.arrays(dtype=xps.floating_dtypes(), shape=shapes),
+    *two_mutual_arrays(dtype_objects=numeric_dtype_objects,
+                       two_shapes=tuples(one_d_shapes, one_d_shapes))
 )
 def test_outer(x1, x2):
-    # res = linalg.outer(x1, x2)
-    pass
+    # outer does not work on stacks. See
+    # https://github.com/data-apis/array-api/issues/242.
+    res = linalg.outer(x1, x2)
+
+    shape = (x1.shape[0], x2.shape[0])
+    assert res.shape == shape, "outer() did not return the correct shape"
+    assert res.dtype == promote_dtypes(x1, x2), "outer() did not return the correct dtype"
+
+    if 0 in shape:
+        true_res = _array_module.empty(shape, dtype=res.dtype)
+    else:
+        true_res = _array_module.asarray([[x1[i]*x2[j]
+                                           for j in range(x2.shape[0])]
+                                          for i in range(x1.shape[0])],
+                                         dtype=res.dtype)
+
+    assert_exactly_equal(res, true_res)
 
 @given(
     x=xps.arrays(dtype=xps.floating_dtypes(), shape=shapes),