diff --git a/array_api_tests/_array_module.py b/array_api_tests/_array_module.py
index 899a2591..8a7c7887 100644
--- a/array_api_tests/_array_module.py
+++ b/array_api_tests/_array_module.py
@@ -63,7 +63,7 @@ def __repr__(self):
 _constants = ["e", "inf", "nan", "pi"]
 _funcs = [f.__name__ for funcs in stubs.category_to_funcs.values() for f in funcs]
 _funcs += ["take", "isdtype", "conj", "imag", "real"]  # TODO: bump spec and update array-api-tests to new spec layout
-_top_level_attrs = _dtypes + _constants + _funcs + stubs.EXTENSIONS
+_top_level_attrs = _dtypes + _constants + _funcs + stubs.EXTENSIONS + ["fft"]
 
 for attr in _top_level_attrs:
     try:
diff --git a/array_api_tests/hypothesis_helpers.py b/array_api_tests/hypothesis_helpers.py
index 31f1e153..c4235ba1 100644
--- a/array_api_tests/hypothesis_helpers.py
+++ b/array_api_tests/hypothesis_helpers.py
@@ -11,7 +11,7 @@
                                    integers, just, lists, none, one_of,
                                    sampled_from, shared)
 
-from . import _array_module as xp
+from . import _array_module as xp, api_version
 from . import dtype_helpers as dh
 from . import shape_helpers as sh
 from . import xps
@@ -141,6 +141,13 @@ def oneway_broadcastable_shapes(draw) -> SearchStrategy[OnewayBroadcastableShape
     return OnewayBroadcastableShapes(input_shape, result_shape)
 
 
+def all_floating_dtypes() -> SearchStrategy[DataType]:
+    strat = xps.floating_dtypes()
+    if api_version >= "2022.12":
+        strat |= xps.complex_dtypes()
+    return strat
+
+
 # shared() allows us to draw either the function or the function name and they
 # will both correspond to the same function.
 
diff --git a/array_api_tests/pytest_helpers.py b/array_api_tests/pytest_helpers.py
index c51b14a6..e6ede7b2 100644
--- a/array_api_tests/pytest_helpers.py
+++ b/array_api_tests/pytest_helpers.py
@@ -122,6 +122,7 @@ def assert_dtype(
         >>> assert_dtype('sum', in_dtype=x, out_dtype=out.dtype, expected=default_int)
 
     """
+    __tracebackhide__ = True
     in_dtypes = in_dtype if isinstance(in_dtype, Sequence) and not isinstance(in_dtype, str) else [in_dtype]
     f_in_dtypes = dh.fmt_types(tuple(in_dtypes))
     f_out_dtype = dh.dtype_to_name[out_dtype]
@@ -149,6 +150,7 @@ def assert_kw_dtype(
         >>> assert_kw_dtype('ones', kw_dtype=kw['dtype'], out_dtype=out.dtype)
 
     """
+    __tracebackhide__ = True
     f_kw_dtype = dh.dtype_to_name[kw_dtype]
     f_out_dtype = dh.dtype_to_name[out_dtype]
     msg = (
@@ -166,6 +168,7 @@ def assert_default_float(func_name: str, out_dtype: DataType):
         >>> assert_default_float('ones', out.dtype)
 
     """
+    __tracebackhide__ = True
     f_dtype = dh.dtype_to_name[out_dtype]
     f_default = dh.dtype_to_name[dh.default_float]
     msg = (
@@ -183,6 +186,7 @@ def assert_default_complex(func_name: str, out_dtype: DataType):
         >>> assert_default_complex('asarray', out.dtype)
 
     """
+    __tracebackhide__ = True
     f_dtype = dh.dtype_to_name[out_dtype]
     f_default = dh.dtype_to_name[dh.default_complex]
     msg = (
@@ -200,6 +204,7 @@ def assert_default_int(func_name: str, out_dtype: DataType):
         >>> assert_default_int('full', out.dtype)
 
     """
+    __tracebackhide__ = True
     f_dtype = dh.dtype_to_name[out_dtype]
     f_default = dh.dtype_to_name[dh.default_int]
     msg = (
@@ -217,6 +222,7 @@ def assert_default_index(func_name: str, out_dtype: DataType, repr_name="out.dty
         >>> assert_default_int('argmax', out.dtype)
 
     """
+    __tracebackhide__ = True
     f_dtype = dh.dtype_to_name[out_dtype]
     msg = (
         f"{repr_name}={f_dtype}, should be the default index dtype, "
@@ -240,6 +246,7 @@ def assert_shape(
         >>> assert_shape('ones', out_shape=out.shape, expected=(3, 3, 3))
 
     """
+    __tracebackhide__ = True
     if isinstance(out_shape, int):
         out_shape = (out_shape,)
     if isinstance(expected, int):
@@ -273,6 +280,7 @@ def assert_result_shape(
         >>> assert out.shape == (3, 3)
 
     """
+    __tracebackhide__ = True
     if expected is None:
         expected = sh.broadcast_shapes(*in_shapes)
     f_in_shapes = " . ".join(str(s) for s in in_shapes)
@@ -307,6 +315,7 @@ def assert_keepdimable_shape(
         >>> assert out2.shape == (1, 1)
 
     """
+    __tracebackhide__ = True
     if keepdims:
         shape = tuple(1 if axis in axes else side for axis, side in enumerate(in_shape))
     else:
@@ -337,6 +346,7 @@ def assert_0d_equals(
         >>> assert res[0] == x[0]
 
     """
+    __tracebackhide__ = True
     msg = (
         f"{out_repr}={out_val}, but should be {x_repr}={x_val} "
         f"[{func_name}({fmt_kw(kw)})]"
@@ -369,6 +379,7 @@ def assert_scalar_equals(
         >>> assert int(out) == 5
 
     """
+    __tracebackhide__ = True
     repr_name = repr_name if idx == () else f"{repr_name}[{idx}]"
     f_func = f"{func_name}({fmt_kw(kw)})"
     if type_ in [bool, int]:
@@ -401,6 +412,7 @@ def assert_fill(
         >>> assert xp.all(out == 42)
 
     """
+    __tracebackhide__ = True
     msg = f"out not filled with {fill_value} [{func_name}({fmt_kw(kw)})]\n{out=}"
     if cmath.isnan(fill_value):
         assert xp.all(xp.isnan(out)), msg
@@ -443,6 +455,7 @@ def assert_array_elements(
         >>> assert xp.all(out == x)
 
     """
+    __tracebackhide__ = True
     dh.result_type(out.dtype, expected.dtype)  # sanity check
     assert_shape(func_name, out_shape=out.shape, expected=expected.shape, kw=kw)  # sanity check
     f_func = f"[{func_name}({fmt_kw(kw)})]"
diff --git a/array_api_tests/shape_helpers.py b/array_api_tests/shape_helpers.py
index ba7d994e..6a0bdfde 100644
--- a/array_api_tests/shape_helpers.py
+++ b/array_api_tests/shape_helpers.py
@@ -1,6 +1,6 @@
 import math
 from itertools import product
-from typing import Iterator, List, Optional, Tuple, Union
+from typing import Iterator, List, Optional, Sequence, Tuple, Union
 
 from ndindex import iter_indices as _iter_indices
 
@@ -66,10 +66,12 @@ def broadcast_shapes(*shapes: Shape):
 
 
 def normalise_axis(
-    axis: Optional[Union[int, Tuple[int, ...]]], ndim: int
+    axis: Optional[Union[int, Sequence[int]]], ndim: int
 ) -> Tuple[int, ...]:
     if axis is None:
         return tuple(range(ndim))
+    elif isinstance(axis, Sequence) and not isinstance(axis, tuple):
+        axis = tuple(axis)
     axes = axis if isinstance(axis, tuple) else (axis,)
     axes = tuple(axis if axis >= 0 else ndim + axis for axis in axes)
     return axes
diff --git a/array_api_tests/stubs.py b/array_api_tests/stubs.py
index 69ec886d..0134765b 100644
--- a/array_api_tests/stubs.py
+++ b/array_api_tests/stubs.py
@@ -52,7 +52,7 @@
     all_funcs.extend(funcs)
 name_to_func: Dict[str, FunctionType] = {f.__name__: f for f in all_funcs}
 
-EXTENSIONS: str = ["linalg"]
+EXTENSIONS: List[str] = ["linalg"]  # TODO: add "fft" once stubs available
 extension_to_funcs: Dict[str, List[FunctionType]] = {}
 for ext in EXTENSIONS:
     mod = name_to_mod[ext]
diff --git a/array_api_tests/test_fft.py b/array_api_tests/test_fft.py
new file mode 100644
index 00000000..7dc70d56
--- /dev/null
+++ b/array_api_tests/test_fft.py
@@ -0,0 +1,298 @@
+import math
+from typing import List, Optional
+from unittest.mock import MagicMock
+
+import pytest
+from hypothesis import assume, given
+from hypothesis import strategies as st
+
+from array_api_tests.typing import Array, DataType
+
+from . import api_version
+from . import dtype_helpers as dh
+from . import hypothesis_helpers as hh
+from . import pytest_helpers as ph
+from . import shape_helpers as sh
+from . import xps
+from ._array_module import mod as xp
+
+pytestmark = [
+    pytest.mark.ci,
+    pytest.mark.xp_extension("fft"),
+    pytest.mark.min_version("2022.12"),
+]
+
+
+# Using xps.complex_dtypes() raises an AttributeError for 2021.12 instances of
+# xps, hence this hack. TODO: figure out a better way to manage this!
+if api_version < "2022.12":
+    xps = MagicMock(xps)
+
+fft_shapes_strat = hh.shapes(min_dims=1).filter(lambda s: math.prod(s) > 1)
+
+
+def draw_n_axis_norm_kwargs(x: Array, data: st.DataObject, *, size_gt_1=False) -> tuple:
+    size = math.prod(x.shape)
+    n = data.draw(
+        st.none() | st.integers((size // 2), math.ceil(size * 1.5)), label="n"
+    )
+    axis = data.draw(st.integers(-1, x.ndim - 1), label="axis")
+    if size_gt_1:
+        _axis = x.ndim - 1 if axis == -1 else axis
+        assume(x.shape[_axis] > 1)
+    norm = data.draw(st.sampled_from(["backward", "ortho", "forward"]), label="norm")
+    kwargs = data.draw(
+        hh.specified_kwargs(
+            ("n", n, None),
+            ("axis", axis, -1),
+            ("norm", norm, "backward"),
+        ),
+        label="kwargs",
+    )
+    return n, axis, norm, kwargs
+
+
+def draw_s_axes_norm_kwargs(x: Array, data: st.DataObject, *, size_gt_1=False) -> tuple:
+    all_axes = list(range(x.ndim))
+    axes = data.draw(
+        st.none() | st.lists(st.sampled_from(all_axes), min_size=1, unique=True),
+        label="axes",
+    )
+    _axes = all_axes if axes is None else axes
+    axes_sides = [x.shape[axis] for axis in _axes]
+    s_strat = st.tuples(
+        *[st.integers(max(side // 2, 1), math.ceil(side * 1.5)) for side in axes_sides]
+    )
+    if axes is None:
+        s_strat = st.none() | s_strat
+    s = data.draw(s_strat, label="s")
+    if size_gt_1:
+        _s = x.shape if s is None else s
+        for i in range(x.ndim):
+            if i in _axes:
+                side = _s[_axes.index(i)]
+            else:
+                side = x.shape[i]
+                assume(side > 1)
+    norm = data.draw(st.sampled_from(["backward", "ortho", "forward"]), label="norm")
+    kwargs = data.draw(
+        hh.specified_kwargs(
+            ("s", s, None),
+            ("axes", axes, None),
+            ("norm", norm, "backward"),
+        ),
+        label="kwargs",
+    )
+    return s, axes, norm, kwargs
+
+
+def assert_fft_dtype(func_name: str, *, in_dtype: DataType, out_dtype: DataType):
+    if in_dtype == xp.float32:
+        expected = xp.complex64
+    elif in_dtype == xp.float64:
+        expected = xp.complex128
+    else:
+        assert dh.is_float_dtype(in_dtype)  # sanity check
+        expected = in_dtype
+    ph.assert_dtype(
+        func_name, in_dtype=in_dtype, out_dtype=out_dtype, expected=expected
+    )
+
+
+def assert_n_axis_shape(
+    func_name: str,
+    *,
+    x: Array,
+    n: Optional[int],
+    axis: int,
+    out: Array,
+    size_gt_1: bool = False,
+):
+    _axis = len(x.shape) - 1 if axis == -1 else axis
+    if n is None:
+        if size_gt_1:
+            axis_side = 2 * (x.shape[_axis] - 1)
+        else:
+            axis_side = x.shape[_axis]
+    else:
+        axis_side = n
+    expected = x.shape[:_axis] + (axis_side,) + x.shape[_axis + 1 :]
+    ph.assert_shape(func_name, out_shape=out.shape, expected=expected)
+
+
+def assert_s_axes_shape(
+    func_name: str,
+    *,
+    x: Array,
+    s: Optional[List[int]],
+    axes: Optional[List[int]],
+    out: Array,
+    size_gt_1: bool = False,
+):
+    _axes = sh.normalise_axis(axes, x.ndim)
+    _s = x.shape if s is None else s
+    expected = []
+    for i in range(x.ndim):
+        if i in _axes:
+            side = _s[_axes.index(i)]
+        else:
+            side = x.shape[i]
+        expected.append(side)
+    if size_gt_1:
+        last_axis = _axes[-1]
+        expected[last_axis] = 2 * (expected[last_axis] - 1)
+        assume(expected[last_axis] > 0)  # TODO: generate valid examples
+    ph.assert_shape(func_name, out_shape=out.shape, expected=tuple(expected))
+
+
+@given(
+    x=xps.arrays(dtype=hh.all_floating_dtypes(), shape=fft_shapes_strat),
+    data=st.data(),
+)
+def test_fft(x, data):
+    n, axis, norm, kwargs = draw_n_axis_norm_kwargs(x, data)
+
+    out = xp.fft.fft(x, **kwargs)
+
+    assert_fft_dtype("fft", in_dtype=x.dtype, out_dtype=out.dtype)
+    assert_n_axis_shape("fft", x=x, n=n, axis=axis, out=out)
+
+
+@given(
+    x=xps.arrays(dtype=hh.all_floating_dtypes(), shape=fft_shapes_strat),
+    data=st.data(),
+)
+def test_ifft(x, data):
+    n, axis, norm, kwargs = draw_n_axis_norm_kwargs(x, data)
+
+    out = xp.fft.ifft(x, **kwargs)
+
+    assert_fft_dtype("ifft", in_dtype=x.dtype, out_dtype=out.dtype)
+    assert_n_axis_shape("ifft", x=x, n=n, axis=axis, out=out)
+
+
+@given(
+    x=xps.arrays(dtype=hh.all_floating_dtypes(), shape=fft_shapes_strat),
+    data=st.data(),
+)
+def test_fftn(x, data):
+    s, axes, norm, kwargs = draw_s_axes_norm_kwargs(x, data)
+
+    out = xp.fft.fftn(x, **kwargs)
+
+    assert_fft_dtype("fftn", in_dtype=x.dtype, out_dtype=out.dtype)
+    assert_s_axes_shape("fftn", x=x, s=s, axes=axes, out=out)
+
+
+@given(
+    x=xps.arrays(dtype=hh.all_floating_dtypes(), shape=fft_shapes_strat),
+    data=st.data(),
+)
+def test_ifftn(x, data):
+    s, axes, norm, kwargs = draw_s_axes_norm_kwargs(x, data)
+
+    out = xp.fft.ifftn(x, **kwargs)
+
+    assert_fft_dtype("ifftn", in_dtype=x.dtype, out_dtype=out.dtype)
+    assert_s_axes_shape("ifftn", x=x, s=s, axes=axes, out=out)
+
+
+@given(
+    x=xps.arrays(dtype=xps.complex_dtypes(), shape=fft_shapes_strat),
+    data=st.data(),
+)
+def test_rfft(x, data):
+    n, axis, norm, kwargs = draw_n_axis_norm_kwargs(x, data)
+
+    out = xp.fft.rfft(x, **kwargs)
+
+    assert_fft_dtype("rfft", in_dtype=x.dtype, out_dtype=out.dtype)
+    assert_n_axis_shape("rfft", x=x, n=n, axis=axis, out=out)
+
+
+@given(
+    x=xps.arrays(dtype=xps.complex_dtypes(), shape=fft_shapes_strat),
+    data=st.data(),
+)
+def test_irfft(x, data):
+    n, axis, norm, kwargs = draw_n_axis_norm_kwargs(x, data, size_gt_1=True)
+
+    out = xp.fft.irfft(x, **kwargs)
+
+    assert_fft_dtype("irfft", in_dtype=x.dtype, out_dtype=out.dtype)
+
+    _axis = x.ndim - 1 if axis == -1 else axis
+    if n is None:
+        axis_side = 2 * (x.shape[_axis] - 1)
+    else:
+        axis_side = n
+    expected_shape = x.shape[:_axis] + (axis_side,) + x.shape[_axis + 1 :]
+    ph.assert_shape("irfft", out_shape=out.shape, expected=expected_shape)
+
+
+@given(
+    x=xps.arrays(dtype=xps.complex_dtypes(), shape=fft_shapes_strat),
+    data=st.data(),
+)
+def test_rfftn(x, data):
+    s, axes, norm, kwargs = draw_s_axes_norm_kwargs(x, data)
+
+    out = xp.fft.rfftn(x, **kwargs)
+
+    assert_fft_dtype("rfftn", in_dtype=x.dtype, out_dtype=out.dtype)
+    assert_s_axes_shape("rfftn", x=x, s=s, axes=axes, out=out)
+
+
+@given(
+    x=xps.arrays(
+        dtype=xps.complex_dtypes(), shape=fft_shapes_strat.filter(lambda s: s[-1] > 1)
+    ),
+    data=st.data(),
+)
+def test_irfftn(x, data):
+    s, axes, norm, kwargs = draw_s_axes_norm_kwargs(x, data, size_gt_1=True)
+
+    out = xp.fft.irfftn(x, **kwargs)
+
+    assert_fft_dtype("irfftn", in_dtype=x.dtype, out_dtype=out.dtype)
+    assert_s_axes_shape("rfftn", x=x, s=s, axes=axes, out=out, size_gt_1=True)
+
+
+@given(
+    x=xps.arrays(dtype=hh.all_floating_dtypes(), shape=fft_shapes_strat),
+    data=st.data(),
+)
+def test_hfft(x, data):
+    n, axis, norm, kwargs = draw_n_axis_norm_kwargs(x, data, size_gt_1=True)
+
+    out = xp.fft.hfft(x, **kwargs)
+
+    assert_fft_dtype("hfft", in_dtype=x.dtype, out_dtype=out.dtype)
+
+    _axis = x.ndim - 1 if axis == -1 else axis
+    if n is None:
+        axis_side = 2 * (x.shape[_axis] - 1)
+    else:
+        axis_side = n
+    expected_shape = x.shape[:_axis] + (axis_side,) + x.shape[_axis + 1 :]
+    ph.assert_shape("hfft", out_shape=out.shape, expected=expected_shape)
+
+
+@given(
+    x=xps.arrays(dtype=hh.all_floating_dtypes(), shape=fft_shapes_strat),
+    data=st.data(),
+)
+def test_ihfft(x, data):
+    n, axis, norm, kwargs = draw_n_axis_norm_kwargs(x, data)
+
+    out = xp.fft.ihfft(x, **kwargs)
+
+    assert_fft_dtype("ihfft", in_dtype=x.dtype, out_dtype=out.dtype)
+    assert_n_axis_shape("ihfft", x=x, n=n, axis=axis, out=out, size_gt_1=True)
+
+
+# TODO:
+# fftfreq
+# rfftfreq
+# fftshift
+# ifftshift
diff --git a/array_api_tests/test_operators_and_elementwise_functions.py b/array_api_tests/test_operators_and_elementwise_functions.py
index 4d803bb0..39905456 100644
--- a/array_api_tests/test_operators_and_elementwise_functions.py
+++ b/array_api_tests/test_operators_and_elementwise_functions.py
@@ -33,13 +33,6 @@ def boolean_and_all_integer_dtypes() -> st.SearchStrategy[DataType]:
     return xps.boolean_dtypes() | all_integer_dtypes()
 
 
-def all_floating_dtypes() -> st.SearchStrategy[DataType]:
-    strat = xps.floating_dtypes()
-    if api_version >= "2022.12":
-        strat |= xps.complex_dtypes()
-    return strat
-
-
 def mock_int_dtype(n: int, dtype: DataType) -> int:
     """Returns equivalent of `n` that mocks `dtype` behaviour."""
     nbits = dh.dtype_nbits[dtype]
@@ -714,7 +707,7 @@ def test_abs(ctx, data):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_acos(x):
     out = xp.acos(x)
     ph.assert_dtype("acos", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -724,7 +717,7 @@ def test_acos(x):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_acosh(x):
     out = xp.acosh(x)
     ph.assert_dtype("acosh", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -748,7 +741,7 @@ def test_add(ctx, data):
     binary_param_assert_against_refimpl(ctx, left, right, res, "+", operator.add)
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_asin(x):
     out = xp.asin(x)
     ph.assert_dtype("asin", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -758,7 +751,7 @@ def test_asin(x):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_asinh(x):
     out = xp.asinh(x)
     ph.assert_dtype("asinh", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -766,7 +759,7 @@ def test_asinh(x):
     unary_assert_against_refimpl("asinh", x, out, math.asinh)
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_atan(x):
     out = xp.atan(x)
     ph.assert_dtype("atan", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -782,7 +775,7 @@ def test_atan2(x1, x2):
     binary_assert_against_refimpl("atan2", x1, x2, out, math.atan2)
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_atanh(x):
     out = xp.atanh(x)
     ph.assert_dtype("atanh", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -932,7 +925,7 @@ def test_conj(x):
         unary_assert_against_refimpl("conj", x, out, operator.methodcaller("conjugate"))
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_cos(x):
     out = xp.cos(x)
     ph.assert_dtype("cos", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -940,7 +933,7 @@ def test_cos(x):
     unary_assert_against_refimpl("cos", x, out, math.cos)
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_cosh(x):
     out = xp.cosh(x)
     ph.assert_dtype("cosh", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1001,7 +994,7 @@ def test_equal(ctx, data):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_exp(x):
     out = xp.exp(x)
     ph.assert_dtype("exp", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1009,7 +1002,7 @@ def test_exp(x):
     unary_assert_against_refimpl("exp", x, out, math.exp)
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_expm1(x):
     out = xp.expm1(x)
     ph.assert_dtype("expm1", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1158,7 +1151,7 @@ def test_less_equal(ctx, data):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_log(x):
     out = xp.log(x)
     ph.assert_dtype("log", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1168,7 +1161,7 @@ def test_log(x):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_log1p(x):
     out = xp.log1p(x)
     ph.assert_dtype("log1p", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1178,7 +1171,7 @@ def test_log1p(x):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_log2(x):
     out = xp.log2(x)
     ph.assert_dtype("log2", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1188,7 +1181,7 @@ def test_log2(x):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_log10(x):
     out = xp.log10(x)
     ph.assert_dtype("log10", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1379,7 +1372,7 @@ def test_sign(x):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_sin(x):
     out = xp.sin(x)
     ph.assert_dtype("sin", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1387,7 +1380,7 @@ def test_sin(x):
     unary_assert_against_refimpl("sin", x, out, math.sin)
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_sinh(x):
     out = xp.sinh(x)
     ph.assert_dtype("sinh", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1405,7 +1398,7 @@ def test_square(x):
     )
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_sqrt(x):
     out = xp.sqrt(x)
     ph.assert_dtype("sqrt", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1429,7 +1422,7 @@ def test_subtract(ctx, data):
     binary_param_assert_against_refimpl(ctx, left, right, res, "-", operator.sub)
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_tan(x):
     out = xp.tan(x)
     ph.assert_dtype("tan", in_dtype=x.dtype, out_dtype=out.dtype)
@@ -1437,7 +1430,7 @@ def test_tan(x):
     unary_assert_against_refimpl("tan", x, out, math.tan)
 
 
-@given(xps.arrays(dtype=all_floating_dtypes(), shape=hh.shapes()))
+@given(xps.arrays(dtype=hh.all_floating_dtypes(), shape=hh.shapes()))
 def test_tanh(x):
     out = xp.tanh(x)
     ph.assert_dtype("tanh", in_dtype=x.dtype, out_dtype=out.dtype)