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Multi-dimensional arrays support #17

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1fc81ee
test ndarrays in special cases
honno Aug 16, 2021
007175d
proof of concept `test_full_like`
honno Aug 16, 2021
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25 changes: 20 additions & 5 deletions array_api_tests/hypothesis_helpers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
shared, tuples as hypotheses_tuples,
floats, just, composite, one_of, none,
booleans)
from hypothesis.extra.numpy import mutually_broadcastable_shapes
from hypothesis_array import mutually_broadcastable_shapes, get_strategies_namespace
from hypothesis import assume

from .pytest_helpers import nargs
Expand All @@ -16,10 +16,14 @@
integer_or_boolean_dtype_objects, dtype_objects)
from ._array_module import (ones, full, float32, float64, bool as bool_dtype, _UndefinedStub)
from . import _array_module
from ._array_module import mod as xp

from .function_stubs import elementwise_functions


xps = get_strategies_namespace(xp)


# Set this to True to not fail tests just because a dtype isn't implemented.
# If no compatible dtype is implemented for a given test, the test will fail
# with a hypothesis health check error. Note that this functionality will not
Expand Down Expand Up @@ -89,11 +93,11 @@ def tuples(elements, *, min_size=0, max_size=None, unique_by=None, unique=False)
return lists(elements, min_size=min_size, max_size=max_size,
unique_by=unique_by, unique=unique).map(tuple)

shapes = tuples(integers(0, 10)).filter(lambda shape: prod(shape) < MAX_ARRAY_SIZE)
shapes = xps.array_shapes(min_side=0).filter(lambda shape: prod(shape) < MAX_ARRAY_SIZE)

# Use this to avoid memory errors with NumPy.
# See https://github.com/numpy/numpy/issues/15753
shapes = tuples(integers(0, 10)).filter(
shapes = xps.array_shapes(min_side=0).filter(
lambda shape: prod([i for i in shape if i]) < MAX_ARRAY_SIZE)

two_mutually_broadcastable_shapes = mutually_broadcastable_shapes(num_shapes=2)\
Expand Down Expand Up @@ -121,8 +125,17 @@ def two_broadcastable_shapes(draw, shapes=shapes):

nonbroadcastable_ones_array_two_args = hypotheses_tuples(ones_arrays, ones_arrays)

# TODO: Generate general arrays here, rather than just scalars.
numeric_arrays = builds(full, just((1,)), floats())
floating_arrays = xps.arrays(dtype=xps.floating_dtypes(), shape=xps.array_shapes())

@composite
def broadcastable_floating_array_pairs(draw):
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I think we instead want a function broadcastable_array_pairs (or mutually_broadcastable_array_pairs), which takes a dtype strategy as input. This will be similar to the array_scalars function in this file, which I expect this strategy will replace most instances of. The specific dtype combinations can then be set as floating_arrays = broadcastable_array_pairs(floating_dtypes) and so on. See the stuff at the top of test_elementwise.py (which should probably be moved to this file).

dtype = draw(xps.floating_dtypes())
broadcastable_shapes = draw(xps.mutually_broadcastable_shapes(2, min_dims=1))
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Why min_dims=1? We definitely want to make sure dimension 0 arrays are tested.

Actually, can't you use two_mutually_broadcastable_shapes defined above here?

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No idea why I did this heh.

shape1, shape2 = broadcastable_shapes.input_shapes
assume(len(shape1) >= len(shape2))
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Why is this restriction here?

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Ahh this goes back to the issue I was having with the special case tests generating indices which (mostly) worked only when the first array had ndims >= the second array. This would be resolved if both arrays in the special case tests shared the same shape, as you suggested.

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I see. Yeah, there's no need to test broadcasting in the special cases tests (it's already tested separately in test_broadcasting.py), and it just makes building a mask more complicated, so we should just generate arrays of the same shape.

array1 = draw(xps.arrays(dtype=dtype, shape=shape1))
array2 = draw(xps.arrays(dtype=dtype, shape=shape2))
return array1, array2

@composite
def scalars(draw, dtypes, finite=False):
Expand Down Expand Up @@ -227,3 +240,5 @@ def multiaxis_indices(draw, shapes):
extra = draw(lists(one_of(integer_indices(sizes), slices(sizes)), min_size=0, max_size=3))
res += extra
return tuple(res)


8 changes: 4 additions & 4 deletions array_api_tests/special_cases/test_abs.py
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Expand Up @@ -8,13 +8,13 @@
"""

from ..array_helpers import NaN, assert_exactly_equal, exactly_equal, infinity, zero
from ..hypothesis_helpers import numeric_arrays
from ..hypothesis_helpers import floating_arrays, broadcastable_floating_array_pairs
from .._array_module import abs

from hypothesis import given


@given(numeric_arrays)
@given(floating_arrays)
def test_abs_special_cases_one_arg_equal_1(arg1):
"""
Special case test for `abs(x, /)`:
Expand All @@ -27,7 +27,7 @@ def test_abs_special_cases_one_arg_equal_1(arg1):
assert_exactly_equal(res[mask], (NaN(arg1.shape, arg1.dtype))[mask])


@given(numeric_arrays)
@given(floating_arrays)
def test_abs_special_cases_one_arg_equal_2(arg1):
"""
Special case test for `abs(x, /)`:
Expand All @@ -40,7 +40,7 @@ def test_abs_special_cases_one_arg_equal_2(arg1):
assert_exactly_equal(res[mask], (zero(arg1.shape, arg1.dtype))[mask])


@given(numeric_arrays)
@given(floating_arrays)
def test_abs_special_cases_one_arg_equal_3(arg1):
"""
Special case test for `abs(x, /)`:
Expand Down
10 changes: 5 additions & 5 deletions array_api_tests/special_cases/test_acos.py
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Expand Up @@ -8,13 +8,13 @@
"""

from ..array_helpers import NaN, assert_exactly_equal, exactly_equal, greater, less, one, zero
from ..hypothesis_helpers import numeric_arrays
from ..hypothesis_helpers import floating_arrays, broadcastable_floating_array_pairs
from .._array_module import acos

from hypothesis import given


@given(numeric_arrays)
@given(floating_arrays)
def test_acos_special_cases_one_arg_equal_1(arg1):
"""
Special case test for `acos(x, /)`:
Expand All @@ -27,7 +27,7 @@ def test_acos_special_cases_one_arg_equal_1(arg1):
assert_exactly_equal(res[mask], (NaN(arg1.shape, arg1.dtype))[mask])


@given(numeric_arrays)
@given(floating_arrays)
def test_acos_special_cases_one_arg_equal_2(arg1):
"""
Special case test for `acos(x, /)`:
Expand All @@ -40,7 +40,7 @@ def test_acos_special_cases_one_arg_equal_2(arg1):
assert_exactly_equal(res[mask], (zero(arg1.shape, arg1.dtype))[mask])


@given(numeric_arrays)
@given(floating_arrays)
def test_acos_special_cases_one_arg_greater(arg1):
"""
Special case test for `acos(x, /)`:
Expand All @@ -53,7 +53,7 @@ def test_acos_special_cases_one_arg_greater(arg1):
assert_exactly_equal(res[mask], (NaN(arg1.shape, arg1.dtype))[mask])


@given(numeric_arrays)
@given(floating_arrays)
def test_acos_special_cases_one_arg_less(arg1):
"""
Special case test for `acos(x, /)`:
Expand Down
10 changes: 5 additions & 5 deletions array_api_tests/special_cases/test_acosh.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,13 +8,13 @@
"""

from ..array_helpers import NaN, assert_exactly_equal, exactly_equal, infinity, less, one, zero
from ..hypothesis_helpers import numeric_arrays
from ..hypothesis_helpers import floating_arrays, broadcastable_floating_array_pairs
from .._array_module import acosh

from hypothesis import given


@given(numeric_arrays)
@given(floating_arrays)
def test_acosh_special_cases_one_arg_equal_1(arg1):
"""
Special case test for `acosh(x, /)`:
Expand All @@ -27,7 +27,7 @@ def test_acosh_special_cases_one_arg_equal_1(arg1):
assert_exactly_equal(res[mask], (NaN(arg1.shape, arg1.dtype))[mask])


@given(numeric_arrays)
@given(floating_arrays)
def test_acosh_special_cases_one_arg_equal_2(arg1):
"""
Special case test for `acosh(x, /)`:
Expand All @@ -40,7 +40,7 @@ def test_acosh_special_cases_one_arg_equal_2(arg1):
assert_exactly_equal(res[mask], (zero(arg1.shape, arg1.dtype))[mask])


@given(numeric_arrays)
@given(floating_arrays)
def test_acosh_special_cases_one_arg_equal_3(arg1):
"""
Special case test for `acosh(x, /)`:
Expand All @@ -53,7 +53,7 @@ def test_acosh_special_cases_one_arg_equal_3(arg1):
assert_exactly_equal(res[mask], (infinity(arg1.shape, arg1.dtype))[mask])


@given(numeric_arrays)
@given(floating_arrays)
def test_acosh_special_cases_one_arg_less(arg1):
"""
Special case test for `acosh(x, /)`:
Expand Down
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