Move first-party hypothesis test to its own file

Author: honno

torch_np/tests/__init__.py

@@ -4,16 +4,12 @@
 
 # import numpy as np
 import torch
-from hypothesis import given
-from hypothesis import strategies as st
 from pytest import raises as assert_raises
 
 import torch_np as np
 from torch_np._ndarray import ndarray
 from torch_np.testing import assert_equal
 
-from . import xps
-
 
 class TestIndexing:
     def test_indexing_simple(self):
@@ -30,30 +26,6 @@ def test_setitem(self):
         assert_equal(a, [[8, 2, 3], [4, 5, 6]])
 
 
-def integer_array_indices(shape, result_shape) -> st.SearchStrategy[tuple]:
-    # See hypothesis.extra.numpy.integer_array_indices()
-    # n.b. result_shape only accepts a shape, as opposed to only accepting a strategy
-    def array_for(index_shape, size):
-        return xps.arrays(
-            dtype=xps.integer_dtypes(),
-            shape=index_shape,
-            elements=st.integers(-size, size - 1),
-        )
-
-    return st.tuples(*(array_for(result_shape, size) for size in shape))
-
-
-@given(
-    x=xps.arrays(dtype=xps.integer_dtypes(), shape=xps.array_shapes()),
-    data=st.data(),
-)
-def test_integer_indexing(x, data):
-    result_shape = data.draw(xps.array_shapes(), label="result_shape")
-    idx = data.draw(integer_array_indices(x.shape, result_shape), label="idx")
-    result = x[idx]
-    assert result.shape == result_shape
-
-
 class TestReshape:
     def test_reshape_function(self):
         arr = [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]

torch_np/tests/test_ndarray_methods.py

@@ -0,0 +1,42 @@
+import warnings
+
+import pytest
+
+pytest.importorskip("hypothesis")
+
+from hypothesis import given
+from hypothesis import strategies as st
+from hypothesis.errors import HypothesisWarning
+from hypothesis.extra.array_api import make_strategies_namespace
+
+import torch_np
+
+__all__ = ["xps"]
+
+with warnings.catch_warnings():
+    warnings.filterwarnings("ignore", category=HypothesisWarning)
+    xps = make_strategies_namespace(torch_np, api_version="2021.12")
+
+
+def integer_array_indices(shape, result_shape) -> st.SearchStrategy[tuple]:
+    # See hypothesis.extra.numpy.integer_array_indices()
+    # n.b. result_shape only accepts a shape, as opposed to only accepting a strategy
+    def array_for(index_shape, size):
+        return xps.arrays(
+            dtype=xps.integer_dtypes(),
+            shape=index_shape,
+            elements=st.integers(-size, size - 1),
+        )
+
+    return st.tuples(*(array_for(result_shape, size) for size in shape))
+
+
+@given(
+    x=xps.arrays(dtype=xps.integer_dtypes(), shape=xps.array_shapes()),
+    data=st.data(),
+)
+def test_integer_indexing(x, data):
+    result_shape = data.draw(xps.array_shapes(), label="result_shape")
+    idx = data.draw(integer_array_indices(x.shape, result_shape), label="idx")
+    result = x[idx]
+    assert result.shape == result_shape