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add support for Boolean dtypes for dpctl.tensor.ceil, dpctl.tensor.floor, and dpctl.tensor.trunc #2033

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Merged
merged 3 commits into from
Mar 31, 2025
Merged

add support for Boolean dtypes for dpctl.tensor.ceil, dpctl.tensor.floor, and dpctl.tensor.trunc #2033

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d6779ee
add support for boolean dtypes for dpt.ceil, dpt.floor, and dpt.trunc
vtavana Mar 27, 2025
2fd8eeb
update changelog
vtavana Mar 27, 2025
9a79047
update docstring
vtavana Mar 31, 2025
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2 changes: 2 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -12,6 +12,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

### Changed

* Support for Boolean data-type is added to `dpctl.tensor.ceil`, `dpctl.tensor.floor`, and `dpctl.tensor.trunc` [gh-2033](https://github.com/IntelPython/dpctl/pull/2033)

### Fixed

## [0.19.0] - Feb. 26, 2025
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6 changes: 3 additions & 3 deletions dpctl/tensor/_elementwise_funcs.py
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Expand Up @@ -528,7 +528,7 @@

Args:
x (usm_ndarray):
Input array, expected to have a real-valued data type.
Input array, expected to have a boolean or real-valued data type.
out (Union[usm_ndarray, None], optional):
Output array to populate.
Array must have the correct shape and the expected data type.
Expand Down Expand Up @@ -767,7 +767,7 @@

Args:
x (usm_ndarray):
Input array, expected to have a real-valued data type.
Input array, expected to have a boolean or real-valued data type.
out (Union[usm_ndarray, None], optional):
Output array to populate.
Array must have the correct shape and the expected data type.
Expand Down Expand Up @@ -2017,7 +2017,7 @@

Args:
x (usm_ndarray):
Input array, expected to have a real-valued data type.
Input array, expected to have a boolean or real-valued data type.
out (Union[usm_ndarray, None], optional):
Output array to populate.
Array must have the correct shape and the expected data type.
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3 changes: 2 additions & 1 deletion dpctl/tensor/libtensor/include/kernels/elementwise_functions/ceil.hpp
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Expand Up @@ -99,7 +99,8 @@ using CeilStridedFunctor = elementwise_common::
template <typename T> struct CeilOutputType
{
using value_type =
typename std::disjunction<td_ns::TypeMapResultEntry<T, std::uint8_t>,
typename std::disjunction<td_ns::TypeMapResultEntry<T, bool>,
td_ns::TypeMapResultEntry<T, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::uint16_t>,
td_ns::TypeMapResultEntry<T, std::uint32_t>,
td_ns::TypeMapResultEntry<T, std::uint64_t>,
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3 changes: 2 additions & 1 deletion dpctl/tensor/libtensor/include/kernels/elementwise_functions/floor.hpp
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Expand Up @@ -99,7 +99,8 @@ using FloorStridedFunctor = elementwise_common::
template <typename T> struct FloorOutputType
{
using value_type =
typename std::disjunction<td_ns::TypeMapResultEntry<T, std::uint8_t>,
typename std::disjunction<td_ns::TypeMapResultEntry<T, bool>,
td_ns::TypeMapResultEntry<T, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::uint16_t>,
td_ns::TypeMapResultEntry<T, std::uint32_t>,
td_ns::TypeMapResultEntry<T, std::uint64_t>,
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3 changes: 2 additions & 1 deletion dpctl/tensor/libtensor/include/kernels/elementwise_functions/trunc.hpp
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Expand Up @@ -96,7 +96,8 @@ using TruncStridedFunctor = elementwise_common::
template <typename T> struct TruncOutputType
{
using value_type =
typename std::disjunction<td_ns::TypeMapResultEntry<T, std::uint8_t>,
typename std::disjunction<td_ns::TypeMapResultEntry<T, bool>,
td_ns::TypeMapResultEntry<T, std::uint8_t>,
td_ns::TypeMapResultEntry<T, std::uint16_t>,
td_ns::TypeMapResultEntry<T, std::uint32_t>,
td_ns::TypeMapResultEntry<T, std::uint64_t>,
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10 changes: 5 additions & 5 deletions dpctl/tests/elementwise/test_floor_ceil_trunc.py
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Expand Up @@ -24,13 +24,13 @@
import dpctl.tensor as dpt
from dpctl.tests.helper import get_queue_or_skip, skip_if_dtype_not_supported

from .utils import _map_to_device_dtype, _real_value_dtypes
from .utils import _map_to_device_dtype, _no_complex_dtypes, _real_value_dtypes

_all_funcs = [(np.floor, dpt.floor), (np.ceil, dpt.ceil), (np.trunc, dpt.trunc)]


@pytest.mark.parametrize("dpt_call", [dpt.floor, dpt.ceil, dpt.trunc])
@pytest.mark.parametrize("dtype", _real_value_dtypes)
@pytest.mark.parametrize("dtype", _no_complex_dtypes)
def test_floor_ceil_trunc_out_type(dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)
Expand Down Expand Up @@ -69,7 +69,7 @@ def test_floor_ceil_trunc_usm_type(np_call, dpt_call, usm_type):


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", _real_value_dtypes)
@pytest.mark.parametrize("dtype", _no_complex_dtypes)
def test_floor_ceil_trunc_order(np_call, dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)
Expand Down Expand Up @@ -102,7 +102,7 @@ def test_floor_ceil_trunc_error_dtype(dpt_call, dtype):


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", _real_value_dtypes)
@pytest.mark.parametrize("dtype", _no_complex_dtypes)
def test_floor_ceil_trunc_contig(np_call, dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)
Expand All @@ -123,7 +123,7 @@ def test_floor_ceil_trunc_contig(np_call, dpt_call, dtype):


@pytest.mark.parametrize("np_call, dpt_call", _all_funcs)
@pytest.mark.parametrize("dtype", _real_value_dtypes)
@pytest.mark.parametrize("dtype", _no_complex_dtypes)
def test_floor_ceil_trunc_strided(np_call, dpt_call, dtype):
q = get_queue_or_skip()
skip_if_dtype_not_supported(dtype, q)
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