Constant slices are deduplicated too aggressively

[befeleme]

Bug report

Bug description:

I try to build numpy with Python 3.14.0a1 and encounter very strange test failures regarding array slicing. The offending tests source code can be found here and here.
I compiled both numpy 1.26.4 and 2.1.2 for Fedora Linux and installed it into an environment with Python 3.14. This happens for both versions of numpy. It doesn't happen with Python 3.13 and numpy 1.26.4.

In both tests, it's either TypeError expected and not raised (test_slicing_no_floats), or the other way around (test_valid_slicing). Let's take a look at test_slicing_no_floats. assert_raises is numpy's wrapper over unittest, but that's irrelevant for the problem - let's replace it with a minimal viable function and run the offending piece of code:

>>> def assert_raises(e, c):
...    try:
...        r = c()
...    except e:
...        pass
...    else:
...        raise AssertionError(f"function call: {c}, did not raise: {e}, return value: {r}")
...
>>> def test_slicing_no_floats():
...    a = np.array([[5]])
...    assert_raises(TypeError, lambda: a[0.0:])
...    assert_raises(TypeError, lambda: a[0:, 0.0:2])
...    assert_raises(TypeError, lambda: a[0.0::2, :0])
...    assert_raises(TypeError, lambda: a[0.0:1:2,:])
...    assert_raises(TypeError, lambda: a[:, 0.0:])
...    assert_raises(TypeError, lambda: a[:0.0])
...
>>> test_slicing_no_floats()
Traceback (most recent call last):
  File "<python-input-45>", line 1, in <module>
    test_slicing_no_floats()
    ~~~~~~~~~~~~~~~~~~~~~~^^
  File "<python-input-44>", line 8, in test_slicing_no_floats
    assert_raises(TypeError, lambda: a[:0.0])
    ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<python-input-34>", line 7, in assert_raises
    raise AssertionError(f"function call: {c}, did not raise: {e}, return code: {r}")
AssertionError: function call: <function test_slicing_no_floats.<locals>.<lambda> at 0x7f9a8a987c10>, did not raise: <class 'TypeError'>, return value: []

What if I switch the 1st and last line of the test? A completely different row stops raising TypeError:

>>> def test_slicing_no_floats():
...     a = np.array([[5]])
...     assert_raises(TypeError, lambda: a[:0.0])
...     assert_raises(TypeError, lambda: a[0:, 0.0:2])
...     assert_raises(TypeError, lambda: a[0.0::2, :0])
...     assert_raises(TypeError, lambda: a[0.0:1:2,:])
...     assert_raises(TypeError, lambda: a[:, 0.0:])
...     assert_raises(TypeError, lambda: a[0.0:])
...     
>>> test_slicing_no_floats()
Traceback (most recent call last):
  File "<python-input-49>", line 1, in <module>
    test_slicing_no_floats()
    ~~~~~~~~~~~~~~~~~~~~~~^^
  File "<python-input-48>", line 7, in test_slicing_no_floats
    assert_raises(TypeError, lambda: a[:, 0.0:])
    ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<python-input-34>", line 7, in assert_raises
    raise AssertionError(f"function call: {c}, did not raise: {e}, return code: {r}")
AssertionError: function call: <function test_slicing_no_floats.<locals>.<lambda> at 0x7f9a8a987740>, did not raise: <class 'TypeError'>, return value: [[5]]

When I arbitrarily remove the 3rd row from the function, suddenly TypeError is correctly raised:

>>> def test_slicing_no_floats():
...     a = np.array([[5]])
...     assert_raises(TypeError, lambda: a[0.0:])
...     assert_raises(TypeError, lambda: a[0:, 0.0:2])
...     assert_raises(TypeError, lambda: a[0.0:1:2,:])
...     assert_raises(TypeError, lambda: a[:, 0.0:])
...     assert_raises(TypeError, lambda: a[:0.0])
...     
>>> test_slicing_no_floats()
>>>

Other modifications are somewhat unpredictable:

>>> def test_slicing_no_floats():
...     a = np.array([[5]])
...     assert_raises(TypeError, lambda: a[:0.0])
...     assert_raises(TypeError, lambda: a[0:, 0.0:2])
...     assert_raises(TypeError, lambda: a[0.0:1:2,:])
...     assert_raises(TypeError, lambda: a[0.0:])
...     
>>> test_slicing_no_floats()
Traceback (most recent call last):
  File "<python-input-51>", line 1, in <module>
    test_slicing_no_floats()
    ~~~~~~~~~~~~~~~~~~~~~~^^
  File "<python-input-50>", line 6, in test_slicing_no_floats
    assert_raises(TypeError, lambda: a[0.0:])
    ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<python-input-34>", line 7, in assert_raises
    raise AssertionError(f"function call: {c}, did not raise: {e}, return code: {r}")
AssertionError: function call: <function test_slicing_no_floats.<locals>.<lambda> at 0x7f9a8a987950>, did not raise: <class 'TypeError'>, return value: [[5]]
>>> def test_slicing_no_floats():
...     a = np.array([[5]])
...     assert_raises(TypeError, lambda: a[:0.0])
...     assert_raises(TypeError, lambda: a[0.0:1:2,:])
...     assert_raises(TypeError, lambda: a[0.0:])
...     
>>> test_slicing_no_floats()  # no problem
>>> def test_slicing_no_floats():
...     a = np.array([[5]])
...     assert_raises(TypeError, lambda: a[:0.0])
...     assert_raises(TypeError, lambda: a[0.0:1:2,:])
...     
>>> test_slicing_no_floats() # no problem
>>> def test_slicing_no_floats():
...     a = np.array([[5]])
...     assert_raises(TypeError, lambda: a[:0.0])
...     
>>> test_slicing_no_floats() # no problem
>>>

I tried also direct slicing, in all cases TypeError was correctly raised:

>>> a = np.array([[5]])
>>> a[:0.0]
Traceback (most recent call last):
  File "<python-input-18>", line 1, in <module>
    a[:0.0]
    ~^^^^^^
TypeError: slice indices must be integers or None or have an __index__ method

And calling lambdas with the same result:

>>> (lambda: a[0.0::2, :0])()
Traceback (most recent call last):
  File "<python-input-59>", line 1, in <module>
    (lambda: a[0.0::2, :0])()
    ~~~~~~~~~~~~~~~~~~~~~~~^^
  File "<python-input-59>", line 1, in <lambda>
    (lambda: a[0.0::2, :0])()
             ~^^^^^^^^^^^^
TypeError: slice indices must be integers or None or have an __index__ method

The original test failure from our build system

    def test_slicing_no_floats():
        a = np.array([[5]])
    
        # start as float.
        assert_raises(TypeError, lambda: a[0.0:])
        assert_raises(TypeError, lambda: a[0:, 0.0:2])
        assert_raises(TypeError, lambda: a[0.0::2, :0])
        assert_raises(TypeError, lambda: a[0.0:1:2,:])
        assert_raises(TypeError, lambda: a[:, 0.0:])
        # stop as float.
>       assert_raises(TypeError, lambda: a[:0.0])

a          = array([[5]])
self       = <numpy.core.tests.test_indexing.TestIndexing object at 0x7f7e1a3bfd90>

../../../BUILDROOT/usr/lib64/python3.14/site-packages/numpy/core/tests/test_indexing.py:54: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/usr/lib64/python3.14/unittest/case.py:804: in assertRaises
    return context.handle('assertRaises', args, kwargs)
        args       = (<function TestIndexing.test_slicing_no_floats.<locals>.<lambda> at 0x7f7e081dae50>,)
        context    = None
        expected_exception = <class 'TypeError'>
        kwargs     = {}
        self       = <numpy.testing._private.utils._Dummy testMethod=nop>
/usr/lib64/python3.14/unittest/case.py:237: in handle
    with self:
        args       = []
        callable_obj = <function TestIndexing.test_slicing_no_floats.<locals>.<lambda> at 0x7f7e081dae50>
        kwargs     = {}
        name       = 'assertRaises'
        self       = None
/usr/lib64/python3.14/unittest/case.py:260: in __exit__
    self._raiseFailure("{} not raised by {}".format(exc_name,
        exc_name   = 'TypeError'
        exc_type   = None
        exc_value  = None
        self       = <unittest.case._AssertRaisesContext object at 0x7f7e07ca8dd0>
        tb         = None
        
    # here no TypeError is expected, yet it is raised
    def test_valid_slicing(self):
        # These should raise no errors.
        a = np.array([[[5]]])
    
        a[::]
>       a[0:]
E       TypeError: slice indices must be integers or None or have an __index__ method

CPython versions tested on:

3.14

Operating systems tested on:

Linux

[JelleZijlstra]

What build options are you using (e.g. JIT, free-threading)? Wonder if this could be #126222.

[hroncok]

JIT is built but not enabled (--enable-experimental-jit=yes-off is used), GIL is enabled (--disable-gil is not used).

[Zheaoli]

What build options are you using (e.g. JIT, free-threading)? Wonder if this could be #126222.

I guess this is a different issue with #126222. Different behavior. I'm trying to reproduce it on my local branch

[brandtbucher]

No-NumPy reproducer:

class GetItemPrinter:
    def __getitem__(self, key):
        print(key) 

a = GetItemPrinter()
a[0.0:]
a[0:, 0.0:2]
a[0.0::2, :0]
a[0.0:1:2,:]
a[:, 0.0:]
a[:0.0]

Output:

slice(0.0, None, None)
(slice(0.0, None, None), slice(0.0, 2, None))
(slice(0.0, None, 2), slice(None, 0, None))
(slice(0.0, 1, 2), slice(None, None, None))
(slice(None, None, None), slice(0.0, None, None))
slice(None, 0, None)

I believe this is due to GH-125063 (CC @mdboom). In the bytecode compiler, we deduplicate constants. However, it's not enough to deduplicate them by equality; we also need to disambiguate based on type, signed zero, etc. so that 0, 0j, -0.0, 0.0, and False all become different constants. All of this happens recursively for containers like tuples and frozensets, so that (0,) and (False,) are distinct too. The logic is in _PyCode_ConstantKey.

It looks like slices are only being compared by equality, which means that slice(0, None, None) is being deduplicated with slice(0.0, None, None). We should probably do something similar to tuples here.