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# This file is part of Hypothesis, which may be found at
# https://github.com/HypothesisWorks/hypothesis/
#
# Copyright the Hypothesis Authors.
# Individual contributors are listed in AUTHORS.rst and the git log.
#
# This Source Code Form is subject to the terms of the Mozilla Public License,
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at https://mozilla.org/MPL/2.0/.
import sys
from copy import copy
from types import SimpleNamespace
from typing import Tuple
import pytest
from hypothesis import given, strategies as st
from hypothesis.errors import HypothesisWarning, InvalidArgument
from hypothesis.extra.array_api import (
COMPLEX_NAMES,
DTYPE_NAMES,
FLOAT_NAMES,
INT_NAMES,
UINT_NAMES,
make_strategies_namespace,
mock_xp,
)
MOCK_WARN_MSG = f"determine.*{mock_xp.__name__}.*Array API"
def make_mock_xp(*, exclude: Tuple[str, ...] = ()) -> SimpleNamespace:
xp = copy(mock_xp)
assert isinstance(exclude, tuple) # sanity check
for attr in exclude:
delattr(xp, attr)
return xp
def test_warning_on_noncompliant_xp():
"""Using non-compliant array modules raises helpful warning"""
xp = make_mock_xp()
with pytest.warns(HypothesisWarning, match=MOCK_WARN_MSG):
make_strategies_namespace(xp, api_version="draft")
@pytest.mark.filterwarnings(f"ignore:.*{MOCK_WARN_MSG}.*")
@pytest.mark.parametrize(
"stratname, args, attr",
[("from_dtype", ["int8"], "iinfo"), ("arrays", ["int8", 5], "full")],
)
def test_error_on_missing_attr(stratname, args, attr):
"""Strategies raise helpful error when using array modules that lack
required attributes."""
xp = make_mock_xp(exclude=(attr,))
xps = make_strategies_namespace(xp, api_version="draft")
func = getattr(xps, stratname)
with pytest.raises(InvalidArgument, match=f"{mock_xp.__name__}.*required.*{attr}"):
func(*args).example()
dtypeless_xp = make_mock_xp(exclude=tuple(DTYPE_NAMES))
with pytest.warns(HypothesisWarning):
dtypeless_xps = make_strategies_namespace(dtypeless_xp, api_version="draft")
@pytest.mark.parametrize(
"stratname",
[
"scalar_dtypes",
"boolean_dtypes",
"numeric_dtypes",
"integer_dtypes",
"unsigned_integer_dtypes",
"floating_dtypes",
"real_dtypes",
"complex_dtypes",
],
)
def test_error_on_missing_dtypes(stratname):
"""Strategies raise helpful error when using array modules that lack
required dtypes."""
func = getattr(dtypeless_xps, stratname)
with pytest.raises(InvalidArgument, match=f"{mock_xp.__name__}.*dtype.*namespace"):
func().example()
@pytest.mark.filterwarnings(f"ignore:.*{MOCK_WARN_MSG}.*")
@pytest.mark.parametrize(
"stratname, keep_anys",
[
("scalar_dtypes", [INT_NAMES, UINT_NAMES, FLOAT_NAMES]),
("numeric_dtypes", [INT_NAMES, UINT_NAMES, FLOAT_NAMES, COMPLEX_NAMES]),
("integer_dtypes", [INT_NAMES]),
("unsigned_integer_dtypes", [UINT_NAMES]),
("floating_dtypes", [FLOAT_NAMES]),
("real_dtypes", [INT_NAMES, UINT_NAMES, FLOAT_NAMES]),
("complex_dtypes", [COMPLEX_NAMES]),
],
)
@given(st.data())
def test_warning_on_partial_dtypes(stratname, keep_anys, data):
"""Strategies using array modules with at least one of a dtype in the
necessary category/categories execute with a warning."""
exclude = []
for keep_any in keep_anys:
exclude.extend(
data.draw(
st.lists(
st.sampled_from(keep_any),
min_size=1,
max_size=len(keep_any) - 1,
unique=True,
)
)
)
xp = make_mock_xp(exclude=tuple(exclude))
xps = make_strategies_namespace(xp, api_version="draft")
func = getattr(xps, stratname)
with pytest.warns(HypothesisWarning, match=f"{mock_xp.__name__}.*dtype.*namespace"):
data.draw(func())
def test_raises_on_inferring_with_no_dunder_version():
"""When xp has no __array_api_version__, inferring api_version raises
helpful error."""
xp = make_mock_xp(exclude=("__array_api_version__",))
with pytest.raises(InvalidArgument, match="has no attribute"):
make_strategies_namespace(xp)
def test_raises_on_invalid_dunder_version():
"""When xp has invalid __array_api_version__, inferring api_version raises
helpful error."""
xp = make_mock_xp()
xp.__array_api_version__ = None
with pytest.raises(InvalidArgument):
make_strategies_namespace(xp)
@pytest.mark.filterwarnings(f"ignore:.*{MOCK_WARN_MSG}.*")
def test_patch_torch_full(monkeypatch):
"""When xp is torch, full() is patched so xps.arrays() can work.
See https://github.com/HypothesisWorks/hypothesis/pull/3542
"""
xp = make_mock_xp()
old_full = copy(xp.full)
def bad_full(shape, *a, **kw):
bad_full.__counter += 1
if isinstance(shape, int):
raise AttributeError("xp.full() has not been patched correctly")
return old_full(shape, *a, **kw)
bad_full.__counter = 0
xp.full = bad_full
with monkeypatch.context() as m:
m.setitem(sys.modules, "torch", xp)
xps = make_strategies_namespace(xp)
xps.arrays(xp.int8, 5).example()
assert bad_full.__counter > 0 # sanity check
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