"as_usm_ndarray" ,
"check_limitations" ,
"check_supported_arrays_type" ,
- "convert_single_elem_array_to_scalar" ,
"default_float_type" ,
"from_dlpack" ,
"get_dpnp_descriptor" ,
@@ -498,15 +497,6 @@ Source code for dpnp.dpnp_iface
return True
-def convert_single_elem_array_to_scalar ( obj , keepdims = False ):
- """Convert array with single element to scalar."""
-
- if ( obj . ndim > 0 ) and ( obj . size == 1 ) and ( keepdims is False ):
- return obj . dtype . type ( obj [ 0 ])
-
- return obj
-
-
def default_float_type ( device = None , sycl_queue = None ):
"""
Return a floating type used by default in DPNP depending on device
diff --git a/pull/2116/_modules/dpnp/dpnp_iface_arraycreation.html b/pull/2116/_modules/dpnp/dpnp_iface_arraycreation.html
index 03019294618..24787ce39dd 100644
--- a/pull/2116/_modules/dpnp/dpnp_iface_arraycreation.html
+++ b/pull/2116/_modules/dpnp/dpnp_iface_arraycreation.html
@@ -14,14 +14,14 @@
dpnp.dpnp_iface_arraycreation — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_arraycreation — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_counting — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_counting — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_histograms — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_histograms — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_indexing — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_indexing — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_libmath — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_libmath — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_linearalgebra — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_linearalgebra — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_logic — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_logic — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
Source code for dpnp.dpnp_iface_logic
"iscomplex" ,
"iscomplexobj" ,
"isfinite" ,
+ "isfortran" ,
"isinf" ,
"isnan" ,
"isneginf" ,
@@ -1100,6 +1101,79 @@ Source code for dpnp.dpnp_iface_logic
)
+
+
[docs]
+
def isfortran ( a ):
+
"""
+
Check if the array is Fortran contiguous but *not* C contiguous.
+
+
This function is obsolete. If you only want to check if an array is Fortran
+
contiguous use ``a.flags.f_contiguous`` instead.
+
+
For full documentation refer to :obj:`numpy.isfortran`.
+
+
Parameters
+
----------
+
a : {dpnp.ndarray, usm_ndarray}
+
Input array.
+
+
Returns
+
-------
+
isfortran : bool
+
Returns ``True`` if the array is Fortran contiguous
+
but *not* C contiguous.
+
+
Examples
+
--------
+
:obj:`dpnp.array` allows to specify whether the array is written in
+
C-contiguous order (last index varies the fastest), or FORTRAN-contiguous
+
order in memory (first index varies the fastest).
+
+
>>> import dpnp as np
+
>>> a = np.array([[1, 2, 3], [4, 5, 6]], order='C')
+
>>> a
+
array([[1, 2, 3],
+
[4, 5, 6]])
+
>>> np.isfortran(a)
+
False
+
+
>>> b = np.array([[1, 2, 3], [4, 5, 6]], order='F')
+
>>> b
+
array([[1, 2, 3],
+
[4, 5, 6]])
+
>>> np.isfortran(b)
+
True
+
+
The transpose of a C-ordered array is a FORTRAN-ordered array.
+
+
>>> a = np.array([[1, 2, 3], [4, 5, 6]], order='C')
+
>>> a
+
array([[1, 2, 3],
+
[4, 5, 6]])
+
>>> np.isfortran(a)
+
False
+
>>> b = a.T
+
>>> b
+
array([[1, 4],
+
[2, 5],
+
[3, 6]])
+
>>> np.isfortran(b)
+
True
+
+
C-ordered arrays evaluate as ``False`` even if they are also
+
FORTRAN-ordered.
+
+
>>> np.isfortran(np.array([1, 2], order='F'))
+
False
+
+
"""
+
+
dpnp . check_supported_arrays_type ( a )
+
+
return a . flags . fnc _ISINF_DOCSTRING = """
Test if each element of input array is an infinity.
diff --git a/pull/2116/_modules/dpnp/dpnp_iface_manipulation.html b/pull/2116/_modules/dpnp/dpnp_iface_manipulation.html
index 34b3f6173e6..aa713a55c06 100644
--- a/pull/2116/_modules/dpnp/dpnp_iface_manipulation.html
+++ b/pull/2116/_modules/dpnp/dpnp_iface_manipulation.html
@@ -14,14 +14,14 @@
dpnp.dpnp_iface_manipulation — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_manipulation — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_mathematical — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_mathematical — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
Source code for dpnp.dpnp_iface_mathematical from .dpnp_algo.dpnp_elementwise_common import (
DPNPAngle ,
DPNPBinaryFunc ,
+ DPNPImag ,
DPNPReal ,
DPNPRound ,
DPNPUnaryFunc ,
@@ -155,6 +156,7 @@ Source code for dpnp.dpnp_iface_mathematical acceptance_fn_positive,
acceptance_fn_sign ,
acceptance_fn_subtract ,
+ resolve_weak_types_2nd_arg_int ,
)
from .dpnp_array import dpnp_array
from .dpnp_utils import call_origin , get_usm_allocations
@@ -192,6 +194,7 @@ Source code for dpnp.dpnp_iface_mathematical "heaviside",
"imag" ,
"lcm" ,
+ "ldexp" ,
"maximum" ,
"minimum" ,
"mod" ,
@@ -573,6 +576,9 @@ Source code for dpnp.dpnp_iface_mathematical ----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have a complex-valued floating-point data type.
+deg : bool, optional
+ Return angle in degrees if ``True``, radians if ``False``.
+ Default: ``False``.
out : {None, dpnp.ndarray, usm_ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
@@ -1559,6 +1565,12 @@ Source code for dpnp.dpnp_iface_mathematical will have a data type that depends on the capabilities of the device
on which the array resides.
+Limitations
+-----------
+Parameters `where` and `subok` are supported with their default values.
+Keyword argument `kwargs` is currently unsupported.
+Otherwise ``NotImplementedError`` exception will be raised.
+
See Also
--------
:obj:`dpnp.absolute` : Absolute values including `complex` types.
@@ -1611,6 +1623,12 @@ Source code for dpnp.dpnp_iface_mathematical Otherwise the result is stored there and the return value `out` is
a reference to that array.
+Limitations
+-----------
+Parameters `where` and `subok` are supported with their default values.
+Keyword argument `kwargs` is currently unsupported.
+Otherwise ``NotImplementedError`` exception will be raised.
+
See Also
--------
:obj:`dpnp.round` : Round to given number of decimals.
@@ -2138,6 +2156,12 @@ Source code for dpnp.dpnp_iface_mathematical out : dpnp.ndarray
The greatest common divisor of the absolute value of the inputs.
+Limitations
+-----------
+Parameters `where` and `subok` are supported with their default values.
+Keyword argument `kwargs` is currently unsupported.
+Otherwise ``NotImplementedError`` exception will be raised.
+
See Also
--------
:obj:`dpnp.lcm` : The lowest common multiple.
@@ -2471,7 +2495,7 @@ Source code for dpnp.dpnp_iface_mathematical array(1.)
"""
-imag = DPNPUnaryFunc (
+imag = DPNPImag (
"imag" ,
ti . _imag_result_type ,
ti . _imag ,
@@ -2505,6 +2529,12 @@ Source code for dpnp.dpnp_iface_mathematical out : dpnp.ndarray
The lowest common multiple of the absolute value of the inputs.
+Limitations
+-----------
+Parameters `where` and `subok` are supported with their default values.
+Keyword argument `kwargs` is currently unsupported.
+Otherwise ``NotImplementedError`` exception will be raised.
+
See Also
--------
:obj:`dpnp.gcd` : The greatest common divisor.
@@ -2527,6 +2557,68 @@ Source code for dpnp.dpnp_iface_mathematical )
+_LDEXP_DOCSTRING = """
+Returns x1 * 2**x2, element-wise.
+
+The mantissas `x1` and exponents of two `x2` are used to construct floating point
+numbers ``x1 * 2**x2``.
+
+For full documentation refer to :obj:`numpy.ldexp`.
+
+Parameters
+----------
+x1 : {dpnp.ndarray, usm_ndarray, scalar}
+ Array of multipliers, expected to have floating-point data types.
+ Both inputs `x1` and `x2` can not be scalars at the same time.
+x2 : {dpnp.ndarray, usm_ndarray, scalar}
+ Array of exponents of two, expected to have an integer data type.
+ Both inputs `x1` and `x2` can not be scalars at the same time.
+out : {None, dpnp.ndarray, usm_ndarray}, optional
+ Output array to populate. Array must have the correct shape and
+ the expected data type.
+ Default: ``None``.
+order : {"C", "F", "A", "K"}, optional
+ Memory layout of the newly output array, if parameter `out` is ``None``.
+ Default: ``"K"``.
+
+Returns
+-------
+out : dpnp.ndarray
+ The result of ``x1 * 2**x2``.
+
+Limitations
+-----------
+Parameters `where` and `subok` are supported with their default values.
+Keyword argument `kwargs` is currently unsupported.
+Otherwise ``NotImplementedError`` exception will be raised.
+
+See Also
+--------
+:obj:`dpnp.frexp` : Return (y1, y2) from ``x = y1 * 2**y2``, inverse to :obj:`dpnp.ldexp`.
+
+Notes
+-----
+Complex dtypes are not supported, they will raise a ``TypeError``.
+
+:obj:`dpnp.ldexp` is useful as the inverse of :obj:`dpnp.frexp`, if used by
+itself it is more clear to simply use the expression ``x1 * 2**x2``.
+
+Examples
+--------
+>>> import dpnp as np
+>>> np.ldexp(5, np.arange(4))
+array([ 5., 10., 20., 40.])
+"""
+
+ldexp = DPNPBinaryFunc (
+ "_ldexp" ,
+ ufi . _ldexp_result_type ,
+ ufi . _ldexp ,
+ _LDEXP_DOCSTRING ,
+ weak_type_resolver = resolve_weak_types_2nd_arg_int ,
+)
+
+
_MAXIMUM_DOCSTRING = """
Compares two input arrays `x1` and `x2` and returns a new array containing the
element-wise maxima.
@@ -3322,7 +3414,7 @@ Source code for dpnp.dpnp_iface_mathematical Limitations
-----------
-Parameters `where' and `subok` are supported with their default values.
+Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
@@ -3358,6 +3450,13 @@ Source code for dpnp.dpnp_iface_mathematical ----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
+out : {None, dpnp.ndarray, usm_ndarray}, optional
+ Output array to populate.
+ Array must have the correct shape and the expected data type.
+ Default: ``None``.
+order : {"C", "F", "A", "K"}, optional
+ Memory layout of the newly output array, if parameter `out` is ``None``.
+ Default: ``"K"``.
Returns
-------
@@ -3572,6 +3671,7 @@ Source code for dpnp.dpnp_iface_mathematical Limitations
-----------
+Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
diff --git a/pull/2116/_modules/dpnp/dpnp_iface_nanfunctions.html b/pull/2116/_modules/dpnp/dpnp_iface_nanfunctions.html
index 4ddeea0e7c2..33a8756d409 100644
--- a/pull/2116/_modules/dpnp/dpnp_iface_nanfunctions.html
+++ b/pull/2116/_modules/dpnp/dpnp_iface_nanfunctions.html
@@ -14,14 +14,14 @@
dpnp.dpnp_iface_nanfunctions — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_nanfunctions — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_searching — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_searching — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_sorting — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_sorting — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
Source code for dpnp.dpnp_iface_sorting
__all__ = [ "argsort" , "partition" , "sort" , "sort_complex" ]
-def _wrap_sort_argsort ( a , _sorting_fn , axis =- 1 , kind = None , order = None ):
+def _wrap_sort_argsort (
+ a , _sorting_fn , axis =- 1 , kind = None , order = None , stable = True
+):
"""Wrap a sorting call from dpctl.tensor interface."""
if order is not None :
@@ -160,13 +162,13 @@ Source code for dpnp.dpnp_iface_sorting
axis = - 1
axis = normalize_axis_index ( axis , ndim = usm_a . ndim )
- usm_res = _sorting_fn ( usm_a , axis = axis )
+ usm_res = _sorting_fn ( usm_a , axis = axis , stable = stable )
return dpnp_array . _create_from_usm_ndarray ( usm_res )
[docs]
-
def argsort ( a , axis =- 1 , kind = None , order = None ):
+
def argsort ( a , axis =- 1 , kind = None , order = None , * , stable = True ):
"""
Returns the indices that would sort an array.
@@ -176,12 +178,18 @@
Source code for dpnp.dpnp_iface_sorting
----------
a : {dpnp.ndarray, usm_ndarray}
Array to be sorted.
- axis : int or None, optional
+ axis : {None, int}, optional
Axis along which to sort. If ``None``, the array is flattened before
- sorting. The default is -1, which sorts along the last axis.
+ sorting. The default is ``-1``, which sorts along the last axis.
kind : {None, "stable"}, optional
- Default is ``None``, which is equivalent to `"stable"`.
- Unlike NumPy, no other option is accepted here.
+ Sorting algorithm. Default is ``None``, which is equivalent to
+ ``"stable"``. Unlike NumPy, no other option is accepted here.
+ stable : {None, bool}, optional
+ Sort stability. If ``True``, the returned array will maintain
+ the relative order of ``a`` values which compare as equal.
+ The same behavior applies when set to ``False`` or ``None``.
+ Internally, this option selects ``kind="stable"``.
+ Default: ``None``.
Returns
-------
@@ -194,14 +202,13 @@ Source code for dpnp.dpnp_iface_sorting
Notes
-----
- For zero-dimensional arrays, if `axis=None`, output is a one-dimensional
+ For zero-dimensional arrays, if ``axis=None``, output is a one-dimensional
array with a single zero element. Otherwise, an ``AxisError`` is raised.
Limitations
-----------
Parameters `order` is only supported with its default value.
- Parameters `kind` can only be ``None`` or ``"stable"`` which
- are equivalent.
+ Parameter `kind` can only be ``None`` or ``"stable"`` which are equivalent.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
@@ -243,7 +250,9 @@ Source code for dpnp.dpnp_iface_sorting
"""
- return _wrap_sort_argsort ( a , dpt . argsort , axis = axis , kind = kind , order = order ) return _wrap_sort_argsort (
+ a , dpt . argsort , axis = axis , kind = kind , order = order , stable = stable
+ ) Source code for dpnp.dpnp_iface_sorting
[docs]
-
def sort ( a , axis =- 1 , kind = None , order = None ):
+
def sort ( a , axis =- 1 , kind = None , order = None , * , stable = True ):
"""
Return a sorted copy of an array.
@@ -297,12 +306,18 @@
Source code for dpnp.dpnp_iface_sorting
----------
a : {dpnp.ndarray, usm_ndarray}
Array to be sorted.
- axis : int or None, optional
+ axis : {None, int}, optional
Axis along which to sort. If ``None``, the array is flattened before
- sorting. The default is -1, which sorts along the last axis.
+ sorting. The default is ``-1``, which sorts along the last axis.
kind : {None, "stable"}, optional
- Default is ``None``, which is equivalent to `"stable"`.
- Unlike in NumPy any other options are not accepted here.
+ Sorting algorithm. Default is ``None``, which is equivalent to
+ ``"stable"``. Unlike NumPy, no other option is accepted here.
+ stable : {None, bool}, optional
+ Sort stability. If ``True``, the returned array will maintain
+ the relative order of ``a`` values which compare as equal.
+ The same behavior applies when set to ``False`` or ``None``.
+ Internally, this option selects ``kind="stable"``.
+ Default: ``None``.
Returns
-------
@@ -311,14 +326,13 @@ Source code for dpnp.dpnp_iface_sorting
Notes
-----
- For zero-dimensional arrays, if `axis=None`, output is the input array
+ For zero-dimensional arrays, if ``axis=None``, output is the input array
returned as a one-dimensional array. Otherwise, an ``AxisError`` is raised.
Limitations
-----------
Parameters `order` is only supported with its default value.
- Parameters `kind` can only be ``None`` or ``"stable"`` which
- are equivalent.
+ Parameter `kind` can only be ``None`` or ``"stable"`` which are equivalent.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
@@ -344,7 +358,9 @@ Source code for dpnp.dpnp_iface_sorting
"""
- return _wrap_sort_argsort ( a , dpt . sort , axis = axis , kind = kind , order = order ) return _wrap_sort_argsort (
+ a , dpt . sort , axis = axis , kind = kind , order = order , stable = stable
+ ) dpnp.dpnp_iface_statistics — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_statistics — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
Source code for dpnp.dpnp_iface_statistics
"""
-
import dpctl.tensor as dpt
import numpy
-from dpctl.tensor._numpy_helper import normalize_axis_index
+from dpctl.tensor._numpy_helper import (
+ normalize_axis_index ,
+ normalize_axis_tuple ,
+)
import dpnp
# pylint: disable=no-name-in-module
from .dpnp_algo import (
dpnp_correlate ,
- dpnp_median ,
)
from .dpnp_array import dpnp_array
from .dpnp_utils import (
@@ -204,6 +205,22 @@ Source code for dpnp.dpnp_iface_statistics
return items
+def _flatten_array_along_axes ( arr , axes_to_flatten ):
+ """Flatten an array along a specific set of axes."""
+
+ axes_to_keep = (
+ axis for axis in range ( arr . ndim ) if axis not in axes_to_flatten
+ )
+
+ # Move the axes_to_flatten to the front
+ arr_moved = dpnp . moveaxis ( arr , axes_to_flatten , range ( len ( axes_to_flatten )))
+
+ new_shape = ( - 1 ,) + tuple ( arr . shape [ axis ] for axis in axes_to_keep )
+ flattened_arr = arr_moved . reshape ( new_shape )
+
+ return flattened_arr
+
+
def _get_comparison_res_dt ( a , _dtype , _out ):
"""Get a data type used by dpctl for result array in comparison function."""
@@ -452,7 +469,7 @@ Source code for dpnp.dpnp_iface_statistics
-----------
Input arrays are supported as :obj:`dpnp.ndarray`.
Size and shape of input arrays are supported to be equal.
- Parameter `mode` is supported only with default value ``"valid``.
+ Parameter `mode` is supported only with default value ``"valid"``.
Otherwise the function will be executed sequentially on CPU.
Input array data types are limited by supported DPNP :ref:`Data types`.
@@ -677,13 +694,15 @@ Source code for dpnp.dpnp_iface_statistics
out : {None, dpnp.ndarray, usm_ndarray}, optional
Alternative output array in which to place the result. It must have
the same shape as the expected output but the type (of the calculated
- values) will be cast if necessary. Default: ``None``.
+ values) will be cast if necessary.
+ Default: ``None``.
keepdims : {None, bool}, optional
If ``True``, the reduced axes (dimensions) are included in the result
as singleton dimensions, so that the returned array remains
compatible with the input array according to Array Broadcasting
rules. Otherwise, if ``False``, the reduced axes are not included in
- the returned array. Default: ``False``.
+ the returned array.
+ Default: ``False``.
Returns
-------
@@ -729,27 +748,57 @@ Source code for dpnp.dpnp_iface_statistics
if dtype is not None :
usm_res = dpt . astype ( usm_res , dtype )
- return dpnp . get_result_array ( usm_res , out , casting = "same_kind" ) return dpnp . get_result_array ( usm_res , out , casting = "unsafe" ) dpnp.dpnp_iface_trigonometric — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_trigonometric — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.dpnp_iface_types — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.dpnp_iface_types — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.fft.dpnp_iface_fft — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.fft.dpnp_iface_fft — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.linalg.dpnp_iface_linalg — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.linalg.dpnp_iface_linalg — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.random.dpnp_iface_random — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.random.dpnp_iface_random — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
dpnp.random.dpnp_random_state — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ dpnp.random.dpnp_random_state — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
Overview: module code — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ Overview: module code — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
C HeavisideFunctor ▼ N lcm C LcmFunctor ▼ N logaddexp2 C Logaddexp2Functor ▼ N radians C RadiansFunctor ▼ N ldexp C LdexpFunctor ▼ N logaddexp2 C Logaddexp2Functor ▼ N radians C RadiansFunctor C are_same C backend_sycl C dpnp_less_comp "<" comparison with complex types support C func_type_map_factory_t C func_type_pair_t C is_any C is_complex C mcg59_struct C mt19937_struct C python_constants C mcg59_struct C mt19937_struct C python_constants "<" comparison with complex types support.
Note return a result of lexicographical "<" comparison for complex types.
-
Definition at line 239 of file dpnp_fptr.hpp .
+
Definition at line 227 of file dpnp_fptr.hpp .
◆
diff --git a/pull/2116/backend_doc/classes.html b/pull/2116/backend_doc/classes.html
index e7024c18863..3d5eada9939 100644
--- a/pull/2116/backend_doc/classes.html
+++ b/pull/2116/backend_doc/classes.html
@@ -118,10 +118,10 @@
HeavisideFunctor (dpnp::kernels::heaviside)HeevdTypePairSupportFactory (dpnp::extensions::lapack::types)
I is_any is_complex
+
is_any
L LcmFunctor (dpnp::kernels::lcm)LinAlgError (dpnp::extensions::lapack)Logaddexp2Functor (dpnp::kernels::logaddexp2)
+
LcmFunctor (dpnp::kernels::lcm)LdexpFunctor (dpnp::kernels::ldexp)LinAlgError (dpnp::extensions::lapack)Logaddexp2Functor (dpnp::kernels::logaddexp2)
M mcg59_struct mt19937_struct
diff --git a/pull/2116/backend_doc/dir_2dc4cca66e7325a4fed455b9bcd79a3e.html b/pull/2116/backend_doc/dir_2dc4cca66e7325a4fed455b9bcd79a3e.html
index 463ff941598..79457bdf65e 100644
--- a/pull/2116/backend_doc/dir_2dc4cca66e7325a4fed455b9bcd79a3e.html
+++ b/pull/2116/backend_doc/dir_2dc4cca66e7325a4fed455b9bcd79a3e.html
@@ -123,6 +123,8 @@
lcm.hpp
+
ldexp.hpp
+
logaddexp2.hpp radians.hpp
diff --git a/pull/2116/backend_doc/dir_2dc4cca66e7325a4fed455b9bcd79a3e.js b/pull/2116/backend_doc/dir_2dc4cca66e7325a4fed455b9bcd79a3e.js
index 824270c6aef..e18ff61c2b8 100644
--- a/pull/2116/backend_doc/dir_2dc4cca66e7325a4fed455b9bcd79a3e.js
+++ b/pull/2116/backend_doc/dir_2dc4cca66e7325a4fed455b9bcd79a3e.js
@@ -9,6 +9,7 @@ var dir_2dc4cca66e7325a4fed455b9bcd79a3e =
[ "gcd.hpp", "kernels_2elementwise__functions_2gcd_8hpp_source.html", null ],
[ "heaviside.hpp", "kernels_2elementwise__functions_2heaviside_8hpp_source.html", null ],
[ "lcm.hpp", "kernels_2elementwise__functions_2lcm_8hpp_source.html", null ],
+ [ "ldexp.hpp", "kernels_2elementwise__functions_2ldexp_8hpp_source.html", null ],
[ "logaddexp2.hpp", "kernels_2elementwise__functions_2logaddexp2_8hpp_source.html", null ],
[ "radians.hpp", "kernels_2elementwise__functions_2radians_8hpp_source.html", null ]
];
\ No newline at end of file
diff --git a/pull/2116/backend_doc/dir_4f4d020a650a668743abea55668e1676.html b/pull/2116/backend_doc/dir_4f4d020a650a668743abea55668e1676.html
index 2236d56f931..27b2da88053 100644
--- a/pull/2116/backend_doc/dir_4f4d020a650a668743abea55668e1676.html
+++ b/pull/2116/backend_doc/dir_4f4d020a650a668743abea55668e1676.html
@@ -127,6 +127,8 @@
lcm.hpp
+
ldexp.hpp
+
logaddexp2.hpp populate.hpp
diff --git a/pull/2116/backend_doc/dir_4f4d020a650a668743abea55668e1676.js b/pull/2116/backend_doc/dir_4f4d020a650a668743abea55668e1676.js
index 70a09afac14..4c163b13e62 100644
--- a/pull/2116/backend_doc/dir_4f4d020a650a668743abea55668e1676.js
+++ b/pull/2116/backend_doc/dir_4f4d020a650a668743abea55668e1676.js
@@ -11,6 +11,7 @@ var dir_4f4d020a650a668743abea55668e1676 =
[ "gcd.hpp", "extensions_2ufunc_2elementwise__functions_2gcd_8hpp_source.html", null ],
[ "heaviside.hpp", "extensions_2ufunc_2elementwise__functions_2heaviside_8hpp_source.html", null ],
[ "lcm.hpp", "extensions_2ufunc_2elementwise__functions_2lcm_8hpp_source.html", null ],
+ [ "ldexp.hpp", "extensions_2ufunc_2elementwise__functions_2ldexp_8hpp_source.html", null ],
[ "logaddexp2.hpp", "extensions_2ufunc_2elementwise__functions_2logaddexp2_8hpp_source.html", null ],
[ "populate.hpp", "populate_8hpp_source.html", null ],
[ "radians.hpp", "extensions_2ufunc_2elementwise__functions_2radians_8hpp_source.html", null ]
diff --git a/pull/2116/backend_doc/dpnp__fptr_8hpp_source.html b/pull/2116/backend_doc/dpnp__fptr_8hpp_source.html
index aa6a506f222..409712987ea 100644
--- a/pull/2116/backend_doc/dpnp__fptr_8hpp_source.html
+++ b/pull/2116/backend_doc/dpnp__fptr_8hpp_source.html
@@ -250,110 +250,56 @@
219 using dpnp_remove_cvref_t =
220 typename std::remove_cv_t<typename std::remove_reference_t<_Tp>>;
-
226 template <
typename _Tp>
-
-
-
229 std::is_same_v<_Tp, std::complex<float>> ||
-
230 std::is_same_v<_Tp, std::complex<double>>>
-
-
-
-
-
-
-
-
-
242 template <
typename _Xp,
typename _Yp>
-
243 bool operator()(_Xp &&__x, _Yp &&__y)
const
-
-
245 if constexpr (both_types_are_same<
-
246 dpnp_remove_cvref_t<_Xp>, dpnp_remove_cvref_t<_Yp>,
-
247 std::complex<float>, std::complex<double>>)
-
-
-
250 _Xp a = std::forward<_Xp>(__x);
-
251 _Yp b = std::forward<_Yp>(__y);
-
-
253 if (a.real() < b.real()) {
-
254 ret = (a.imag() == a.imag() || b.imag() != b.imag());
-
-
256 else if (a.real() > b.real()) {
-
257 ret = (b.imag() != b.imag() && a.imag() == a.imag());
-
-
259 else if (a.real() == b.real() ||
-
260 (a.real() != a.real() && b.real() != b.real())) {
-
261 ret = (a.imag() < b.imag() ||
-
262 (b.imag() != b.imag() && a.imag() == a.imag()));
-
-
-
265 ret = (b.real() != b.real());
-
-
-
-
-
270 return std::forward<_Xp>(__x) < std::forward<_Yp>(__y);
-
-
-
+
+
+
+
230 template <
typename _Xp,
typename _Yp>
+
231 bool operator()(_Xp &&__x, _Yp &&__y)
const
+
+
233 if constexpr (both_types_are_same<
+
234 dpnp_remove_cvref_t<_Xp>, dpnp_remove_cvref_t<_Yp>,
+
235 std::complex<float>, std::complex<double>>)
+
+
+
238 _Xp a = std::forward<_Xp>(__x);
+
239 _Yp b = std::forward<_Yp>(__y);
+
+
241 if (a.real() < b.real()) {
+
242 ret = (a.imag() == a.imag() || b.imag() != b.imag());
+
+
244 else if (a.real() > b.real()) {
+
245 ret = (b.imag() != b.imag() && a.imag() == a.imag());
+
+
247 else if (a.real() == b.real() ||
+
248 (a.real() != a.real() && b.real() != b.real())) {
+
249 ret = (a.imag() < b.imag() ||
+
250 (b.imag() != b.imag() && a.imag() == a.imag()));
+
+
+
253 ret = (b.real() != b.real());
+
+
+
+
+
258 return std::forward<_Xp>(__x) < std::forward<_Yp>(__y);
+
+
+
+
+
266 void func_map_init_arraycreation(func_map_t &fmap);
+
267 void func_map_init_elemwise(func_map_t &fmap);
+
268 void func_map_init_indexing_func(func_map_t &fmap);
+
269 void func_map_init_linalg(func_map_t &fmap);
+
270 void func_map_init_mathematical(func_map_t &fmap);
+
271 void func_map_init_random(func_map_t &fmap);
+
272 void func_map_init_sorting(func_map_t &fmap);
+
273 void func_map_init_statistics(func_map_t &fmap);
-
279 template <
typename has_fp64 = std::true_type>
-
280 static constexpr DPNPFuncType get_default_floating_type()
-
-
-
-
-
-
-
-
292 typename has_fp64 = std::true_type,
-
293 typename keep_int = std::false_type>
-
-
-
296 constexpr auto widest_type = populate_func_types<FT1, FT2>();
-
297 constexpr auto shortes_type = (widest_type == FT1) ? FT2 : FT1;
-
-
-
300 if constexpr (keep_int::value) {
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
322 return get_default_floating_type<has_fp64>();
-
-
-
328 void func_map_init_arraycreation(func_map_t &fmap);
-
329 void func_map_init_elemwise(func_map_t &fmap);
-
330 void func_map_init_indexing_func(func_map_t &fmap);
-
331 void func_map_init_linalg(func_map_t &fmap);
-
332 void func_map_init_mathematical(func_map_t &fmap);
-
333 void func_map_init_random(func_map_t &fmap);
-
334 void func_map_init_reduction(func_map_t &fmap);
-
335 void func_map_init_searching(func_map_t &fmap);
-
336 void func_map_init_sorting(func_map_t &fmap);
-
337 void func_map_init_statistics(func_map_t &fmap);
-
-
-
"<" comparison with complex types support.
-
DPNPFuncType
Template types which are used in this interface.
+
+
"<" comparison with complex types support.
+
DPNPFuncType
Template types which are used in this interface.
@@ -366,7 +312,6 @@
-
diff --git a/pull/2116/backend_doc/dpnp__iface_8hpp_source.html b/pull/2116/backend_doc/dpnp__iface_8hpp_source.html
index 4ff2f2db0d6..4c328939f9b 100644
--- a/pull/2116/backend_doc/dpnp__iface_8hpp_source.html
+++ b/pull/2116/backend_doc/dpnp__iface_8hpp_source.html
@@ -217,341 +217,205 @@
163 const shape_elem_type *input2_shape,
164 const shape_elem_type *input2_strides);
-
189 template <
typename _DataType_output,
typename _DataType_input>
-
190 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
193 const void *input_in,
-
194 const shape_elem_type *input_shape,
-
195 const size_t input_shape_ndim,
-
196 const shape_elem_type *axes,
-
197 const size_t axes_ndim,
-
-
-
200 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
202 template <
typename _DataType_output,
typename _DataType_input>
-
203 INP_DLLEXPORT
void dpnp_sum_c (
void *result_out,
-
204 const void *input_in,
-
205 const shape_elem_type *input_shape,
-
206 const size_t input_shape_ndim,
-
207 const shape_elem_type *axes,
-
208 const size_t axes_ndim,
-
-
-
-
225 template <
typename _DataType>
-
226 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
-
-
-
232 const shape_elem_type *shape,
-
-
234 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
236 template <
typename _DataType>
-
-
-
-
-
241 const shape_elem_type *shape,
-
-
-
267 template <
typename _DataType_output,
typename _DataType_input>
-
268 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
271 const void *input_in,
-
272 const shape_elem_type *input_shape,
-
273 const size_t input_shape_ndim,
-
274 const shape_elem_type *axes,
-
275 const size_t axes_ndim,
-
-
-
278 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
280 template <
typename _DataType_output,
typename _DataType_input>
-
-
282 const void *input_in,
-
283 const shape_elem_type *input_shape,
-
284 const size_t input_shape_ndim,
-
285 const shape_elem_type *axes,
-
286 const size_t axes_ndim,
-
-
-
-
301 template <
typename _DataType,
typename _
id x_DataType>
-
302 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
-
-
307 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
309 template <
typename _DataType,
typename _
id x_DataType>
-
310 INP_DLLEXPORT
void dpnp_argsort_c (
void *array,
void *result,
size_t size);
-
-
326 template <
typename _DataType,
typename _IndexingType>
-
327 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
-
-
-
333 const size_t arr_size,
-
-
335 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
337 template <
typename _DataType,
typename _IndexingType>
-
-
-
-
-
342 const size_t arr_size,
-
343 const size_t v_size);
-
-
355 template <
typename _DataType>
-
356 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
-
-
361 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
363 template <
typename _DataType>
-
364 INP_DLLEXPORT
void dpnp_sort_c (
void *array,
void *result,
size_t size);
-
-
383 template <
typename _DataType_output,
-
384 typename _DataType_input1,
-
385 typename _DataType_input2>
-
386 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
389 const void *input1_in,
-
390 const size_t input1_size,
-
391 const shape_elem_type *input1_shape,
-
392 const size_t input1_shape_ndim,
-
393 const void *input2_in,
-
394 const size_t input2_size,
-
395 const shape_elem_type *input2_shape,
-
396 const size_t input2_shape_ndim,
-
-
398 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
400 template <
typename _DataType_output,
-
401 typename _DataType_input1,
-
402 typename _DataType_input2>
-
-
404 const void *input1_in,
-
405 const size_t input1_size,
-
406 const shape_elem_type *input1_shape,
-
407 const size_t input1_shape_ndim,
-
408 const void *input2_in,
-
409 const size_t input2_size,
-
410 const shape_elem_type *input2_shape,
-
411 const size_t input2_shape_ndim,
-
412 const size_t *where);
+
179 template <
typename _DataType>
+
180 INP_DLLEXPORT DPCTLSyclEventRef
+
+
+
+
+
+
186 const shape_elem_type *shape,
+
+
188 const DPCTLEventVectorRef dep_event_vec_ref);
+
+
190 template <
typename _DataType>
+
+
+
+
+
195 const shape_elem_type *shape,
+
+
+
215 template <
typename _DataType_output,
+
216 typename _DataType_input1,
+
217 typename _DataType_input2>
+
218 INP_DLLEXPORT DPCTLSyclEventRef
+
+
+
221 const void *input1_in,
+
222 const size_t input1_size,
+
223 const shape_elem_type *input1_shape,
+
224 const size_t input1_shape_ndim,
+
225 const void *input2_in,
+
226 const size_t input2_size,
+
227 const shape_elem_type *input2_shape,
+
228 const size_t input2_shape_ndim,
+
+
230 const DPCTLEventVectorRef dep_event_vec_ref);
+
+
232 template <
typename _DataType_output,
+
233 typename _DataType_input1,
+
234 typename _DataType_input2>
+
+
236 const void *input1_in,
+
237 const size_t input1_size,
+
238 const shape_elem_type *input1_shape,
+
239 const size_t input1_shape_ndim,
+
240 const void *input2_in,
+
241 const size_t input2_size,
+
242 const shape_elem_type *input2_shape,
+
243 const size_t input2_shape_ndim,
+
244 const size_t *where);
+
+
260 template <
typename _DataType1,
typename _DataType2>
+
261 INP_DLLEXPORT DPCTLSyclEventRef
+
+
+
+
+
+
+
+
269 const DPCTLEventVectorRef dep_event_vec_ref);
+
+
271 template <
typename _DataType1,
typename _DataType2>
+
+
+
+
+
+
+
+
289 template <
typename _DataType>
+
290 INP_DLLEXPORT DPCTLSyclEventRef
+
+
+
+
+
295 const DPCTLEventVectorRef dep_event_vec_ref);
+
+
297 template <
typename _DataType>
+
298 INP_DLLEXPORT
void dpnp_initval_c (
void *result1,
void *value,
size_t size);
+
+
300 #define MACRO_1ARG_1TYPE_OP(__name__, __operation1__, __operation2__) \
+
301 template <typename _DataType> \
+
302 INP_DLLEXPORT DPCTLSyclEventRef __name__( \
+
303 DPCTLSyclQueueRef q_ref, void *result_out, const size_t result_size, \
+
304 const size_t result_ndim, const shape_elem_type *result_shape, \
+
305 const shape_elem_type *result_strides, const void *input1_in, \
+
306 const size_t input1_size, const size_t input1_ndim, \
+
307 const shape_elem_type *input1_shape, \
+
308 const shape_elem_type *input1_strides, const size_t *where, \
+
309 const DPCTLEventVectorRef dep_event_vec_ref); \
+
+
311 template <typename _DataType> \
+
312 INP_DLLEXPORT void __name__( \
+
313 void *result_out, const size_t result_size, const size_t result_ndim, \
+
314 const shape_elem_type *result_shape, \
+
315 const shape_elem_type *result_strides, const void *input1_in, \
+
316 const size_t input1_size, const size_t input1_ndim, \
+
317 const shape_elem_type *input1_shape, \
+
318 const shape_elem_type *input1_strides, const size_t *where);
+
+
320 #include <dpnp_gen_1arg_1type_tbl.hpp>
+
+
322 #define MACRO_2ARG_3TYPES_OP(__name__, __operation__, __vec_operation__, \
+
323 __vec_types__, __mkl_operation__, __mkl_types__) \
+
324 template <typename _DataType_output, typename _DataType_input1, \
+
325 typename _DataType_input2> \
+
326 INP_DLLEXPORT DPCTLSyclEventRef __name__( \
+
327 DPCTLSyclQueueRef q_ref, void *result_out, const size_t result_size, \
+
328 const size_t result_ndim, const shape_elem_type *result_shape, \
+
329 const shape_elem_type *result_strides, const void *input1_in, \
+
330 const size_t input1_size, const size_t input1_ndim, \
+
331 const shape_elem_type *input1_shape, \
+
332 const shape_elem_type *input1_strides, const void *input2_in, \
+
333 const size_t input2_size, const size_t input2_ndim, \
+
334 const shape_elem_type *input2_shape, \
+
335 const shape_elem_type *input2_strides, const size_t *where, \
+
336 const DPCTLEventVectorRef dep_event_vec_ref); \
+
+
338 template <typename _DataType_output, typename _DataType_input1, \
+
339 typename _DataType_input2> \
+
340 INP_DLLEXPORT void __name__( \
+
341 void *result_out, const size_t result_size, const size_t result_ndim, \
+
342 const shape_elem_type *result_shape, \
+
343 const shape_elem_type *result_strides, const void *input1_in, \
+
344 const size_t input1_size, const size_t input1_ndim, \
+
345 const shape_elem_type *input1_shape, \
+
346 const shape_elem_type *input1_strides, const void *input2_in, \
+
347 const size_t input2_size, const size_t input2_ndim, \
+
348 const shape_elem_type *input2_shape, \
+
349 const shape_elem_type *input2_strides, const size_t *where);
+
+
351 #include <dpnp_gen_2arg_3type_tbl.hpp>
+
+
364 template <
typename _DataType_input,
typename _DataType_output>
+
365 INP_DLLEXPORT DPCTLSyclEventRef
+
+
+
+
+
+
371 const DPCTLEventVectorRef dep_event_vec_ref);
+
+
373 template <
typename _DataType_input,
typename _DataType_output>
+
+
+
+
+
+
388 template <
typename _DataType>
+
389 INP_DLLEXPORT DPCTLSyclEventRef
+
+
+
+
393 const DPCTLEventVectorRef dep_event_vec_ref);
+
+
395 template <
typename _DataType>
+
396 INP_DLLEXPORT
void dpnp_ones_c (
void *result,
size_t size);
+
+
407 template <
typename _DataType>
+
408 INP_DLLEXPORT DPCTLSyclEventRef
+
+
+
+
412 const DPCTLEventVectorRef dep_event_vec_ref);
-
428 template <
typename _DataType1,
typename _DataType2>
-
429 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
-
-
-
-
-
437 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
439 template <
typename _DataType1,
typename _DataType2>
-
-
-
-
-
-
-
-
457 template <
typename _DataType>
-
458 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
-
-
463 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
465 template <
typename _DataType>
-
466 INP_DLLEXPORT
void dpnp_initval_c (
void *result1,
void *value,
size_t size);
-
-
481 template <
typename _DataType,
typename _ResultType>
-
482 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
-
486 const shape_elem_type *shape,
-
-
488 const shape_elem_type *axis,
-
-
490 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
492 template <
typename _DataType,
typename _ResultType>
-
-
-
495 const shape_elem_type *shape,
-
-
497 const shape_elem_type *axis,
-
-
-
510 template <
typename _DataType,
typename _
id x_DataType>
-
511 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
-
-
516 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
518 template <
typename _DataType,
typename _
id x_DataType>
-
519 INP_DLLEXPORT
void dpnp_argmax_c (
void *array,
void *result,
size_t size);
-
-
531 template <
typename _DataType,
typename _
id x_DataType>
-
532 INP_DLLEXPORT DPCTLSyclEventRef
-
-
-
-
-
537 const DPCTLEventVectorRef dep_event_vec_ref);
-
-
539 template <
typename _DataType,
typename _
id x_DataType>
-
540 INP_DLLEXPORT
void dpnp_argmin_c (
void *array,
void *result,
size_t size);
-
-
542 #define MACRO_1ARG_1TYPE_OP(__name__, __operation1__, __operation2__) \
-
543 template <typename _DataType> \
-
544 INP_DLLEXPORT DPCTLSyclEventRef __name__( \
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545 DPCTLSyclQueueRef q_ref, void *result_out, const size_t result_size, \
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546 const size_t result_ndim, const shape_elem_type *result_shape, \
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547 const shape_elem_type *result_strides, const void *input1_in, \
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548 const size_t input1_size, const size_t input1_ndim, \
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549 const shape_elem_type *input1_shape, \
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550 const shape_elem_type *input1_strides, const size_t *where, \
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551 const DPCTLEventVectorRef dep_event_vec_ref); \
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553 template <typename _DataType> \
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554 INP_DLLEXPORT void __name__( \
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555 void *result_out, const size_t result_size, const size_t result_ndim, \
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556 const shape_elem_type *result_shape, \
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557 const shape_elem_type *result_strides, const void *input1_in, \
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558 const size_t input1_size, const size_t input1_ndim, \
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559 const shape_elem_type *input1_shape, \
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560 const shape_elem_type *input1_strides, const size_t *where);
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562 #include <dpnp_gen_1arg_1type_tbl.hpp>
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564 #define MACRO_2ARG_3TYPES_OP(__name__, __operation__, __vec_operation__, \
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565 __vec_types__, __mkl_operation__, __mkl_types__) \
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566 template <typename _DataType_output, typename _DataType_input1, \
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567 typename _DataType_input2> \
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568 INP_DLLEXPORT DPCTLSyclEventRef __name__( \
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569 DPCTLSyclQueueRef q_ref, void *result_out, const size_t result_size, \
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570 const size_t result_ndim, const shape_elem_type *result_shape, \
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571 const shape_elem_type *result_strides, const void *input1_in, \
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572 const size_t input1_size, const size_t input1_ndim, \
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573 const shape_elem_type *input1_shape, \
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574 const shape_elem_type *input1_strides, const void *input2_in, \
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575 const size_t input2_size, const size_t input2_ndim, \
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576 const shape_elem_type *input2_shape, \
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577 const shape_elem_type *input2_strides, const size_t *where, \
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578 const DPCTLEventVectorRef dep_event_vec_ref); \
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580 template <typename _DataType_output, typename _DataType_input1, \
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581 typename _DataType_input2> \
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582 INP_DLLEXPORT void __name__( \
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583 void *result_out, const size_t result_size, const size_t result_ndim, \
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584 const shape_elem_type *result_shape, \
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585 const shape_elem_type *result_strides, const void *input1_in, \
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586 const size_t input1_size, const size_t input1_ndim, \
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587 const shape_elem_type *input1_shape, \
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588 const shape_elem_type *input1_strides, const void *input2_in, \
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589 const size_t input2_size, const size_t input2_ndim, \
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590 const shape_elem_type *input2_shape, \
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591 const shape_elem_type *input2_strides, const size_t *where);
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593 #include <dpnp_gen_2arg_3type_tbl.hpp>
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606 template <
typename _DataType_input,
typename _DataType_output>
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607 INP_DLLEXPORT DPCTLSyclEventRef
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613 const DPCTLEventVectorRef dep_event_vec_ref);
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615 template <
typename _DataType_input,
typename _DataType_output>
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630 template <
typename _DataType>
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631 INP_DLLEXPORT DPCTLSyclEventRef
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635 const DPCTLEventVectorRef dep_event_vec_ref);
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637 template <
typename _DataType>
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638 INP_DLLEXPORT
void dpnp_ones_c (
void *result,
size_t size);
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649 template <
typename _DataType>
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650 INP_DLLEXPORT DPCTLSyclEventRef
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654 const DPCTLEventVectorRef dep_event_vec_ref);
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656 template <
typename _DataType>
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668 template <
typename _DataType>
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669 INP_DLLEXPORT DPCTLSyclEventRef
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673 const DPCTLEventVectorRef dep_event_vec_ref);
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675 template <
typename _DataType>
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676 INP_DLLEXPORT
void dpnp_zeros_c (
void *result,
size_t size);
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687 template <
typename _DataType>
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688 INP_DLLEXPORT DPCTLSyclEventRef
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692 const DPCTLEventVectorRef dep_event_vec_ref);
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694 template <
typename _DataType>
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DPCTLSyclEventRef dpnp_searchsorted_c(DPCTLSyclQueueRef q_ref, void *result, const void *array, const void *v, bool side, const size_t arr_size, const size_t v_size, const DPCTLEventVectorRef dep_event_vec_ref)
math library implementation of searchsorted function
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DPCTLSyclEventRef dpnp_argmax_c(DPCTLSyclQueueRef q_ref, void *array, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
math library implementation of argmax function
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DPCTLSyclEventRef dpnp_median_c(DPCTLSyclQueueRef q_ref, void *array, void *result, const shape_elem_type *shape, size_t ndim, const shape_elem_type *axis, size_t naxis, const DPCTLEventVectorRef dep_event_vec_ref)
math library implementation of median function
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DPCTLSyclEventRef dpnp_sort_c(DPCTLSyclQueueRef q_ref, void *array, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
math library implementation of sort function
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414 template <
typename _DataType>
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426 template <
typename _DataType>
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427 INP_DLLEXPORT DPCTLSyclEventRef
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431 const DPCTLEventVectorRef dep_event_vec_ref);
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433 template <
typename _DataType>
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434 INP_DLLEXPORT
void dpnp_zeros_c (
void *result,
size_t size);
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445 template <
typename _DataType>
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446 INP_DLLEXPORT DPCTLSyclEventRef
+
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450 const DPCTLEventVectorRef dep_event_vec_ref);
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452 template <
typename _DataType>
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DPCTLSyclEventRef dpnp_initval_c(DPCTLSyclQueueRef q_ref, void *result1, void *value, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
implementation of creating filled with value array function
size_t dpnp_queue_is_cpu_c()
SYCL queue device status.
-
DPCTLSyclEventRef dpnp_prod_c(DPCTLSyclQueueRef q_ref, void *result_out, const void *input_in, const shape_elem_type *input_shape, const size_t input_shape_ndim, const shape_elem_type *axes, const size_t axes_ndim, const void *initial, const long *where, const DPCTLEventVectorRef dep_event_vec_ref)
Compute Product of input array elements.
DPCTLSyclEventRef dpnp_zeros_like_c(DPCTLSyclQueueRef q_ref, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
Implementation of zeros_like function.
DPCTLSyclEventRef dpnp_ones_c(DPCTLSyclQueueRef q_ref, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
Implementation of ones function.
DPCTLSyclEventRef dpnp_ones_like_c(DPCTLSyclQueueRef q_ref, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
Implementation of ones_like function.
char * dpnp_memory_alloc_c(DPCTLSyclQueueRef q_ref, size_t size_in_bytes)
SYCL queue memory allocation.
DPCTLSyclEventRef dpnp_modf_c(DPCTLSyclQueueRef q_ref, void *array1_in, void *result1_out, void *result2_out, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
modf function.
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DPCTLSyclEventRef dpnp_argmin_c(DPCTLSyclQueueRef q_ref, void *array, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
math library implementation of argmin function
-
DPCTLSyclEventRef dpnp_sum_c(DPCTLSyclQueueRef q_ref, void *result_out, const void *input_in, const shape_elem_type *input_shape, const size_t input_shape_ndim, const shape_elem_type *axes, const size_t axes_ndim, const void *initial, const long *where, const DPCTLEventVectorRef dep_event_vec_ref)
Compute summary of input array elements.
DPCTLSyclEventRef dpnp_correlate_c(DPCTLSyclQueueRef q_ref, void *result_out, const void *input1_in, const size_t input1_size, const shape_elem_type *input1_shape, const size_t input1_shape_ndim, const void *input2_in, const size_t input2_size, const shape_elem_type *input2_shape, const size_t input2_shape_ndim, const size_t *where, const DPCTLEventVectorRef dep_event_vec_ref)
correlate function
DPCTLSyclEventRef dpnp_zeros_c(DPCTLSyclQueueRef q_ref, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
Implementation of zeros function.
DPCTLSyclEventRef dpnp_partition_c(DPCTLSyclQueueRef q_ref, void *array, void *array2, void *result, const size_t kth, const shape_elem_type *shape, const size_t ndim, const DPCTLEventVectorRef dep_event_vec_ref)
Return a partitioned copy of an array.
-
DPCTLSyclEventRef dpnp_argsort_c(DPCTLSyclQueueRef q_ref, void *array, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
math library implementation of argsort function
DPCTLSyclEventRef dpnp_dot_c(DPCTLSyclQueueRef q_ref, void *result_out, const size_t result_size, const size_t result_ndim, const shape_elem_type *result_shape, const shape_elem_type *result_strides, const void *input1_in, const size_t input1_size, const size_t input1_ndim, const shape_elem_type *input1_shape, const shape_elem_type *input1_strides, const void *input2_in, const size_t input2_size, const size_t input2_ndim, const shape_elem_type *input2_shape, const shape_elem_type *input2_strides, const DPCTLEventVectorRef dep_event_vec_ref)
Custom implementation of dot function.
DPCTLSyclEventRef dpnp_choose_c(DPCTLSyclQueueRef q_ref, void *result1, void *array1_in, void **choices, size_t size, size_t choices_size, size_t choice_size, const DPCTLEventVectorRef dep_event_vec_ref)
Construct an array from an index array and a list of arrays to choose from.
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INP_DLLEXPORT DPNPFuncData_t get_dpnp_function_ptr(DPNPFuncName name, DPNPFuncType first_type, DPNPFuncType second_type=DPNPFuncType::DPNP_FT_NONE)
get runtime pointer to selected function
INP_DLLEXPORT void * get_dpnp_function_ptr1(DPNPFuncType &result_type, DPNPFuncName name, DPNPFuncType first_type, DPNPFuncType second_type=DPNPFuncType::DPNP_FT_NONE)
get runtime pointer to selected function
struct DPNPFuncData DPNPFuncData_t
Contains information about the C++ backend function.
DPNPFuncName
Function names to request via this interface.
-
DPNPFuncType
Template types which are used in this interface.
+
DPNPFuncType
Template types which are used in this interface.
@ DPNP_FN_RNG_MULTIVARIATE_NORMAL
@@ -328,7 +319,6 @@
@ DPNP_FN_RNG_BINOMIAL_EXT
-
@ DPNP_FN_RNG_POISSON_EXT
@@ -336,30 +326,24 @@
@ DPNP_FN_RNG_MULTINOMIAL_EXT
-
-
@ DPNP_FN_RNG_GAUSSIAN_EXT
@ DPNP_FN_RNG_CHISQUARE_EXT
-
@ DPNP_FN_RNG_SHUFFLE_EXT
-
@ DPNP_FN_RNG_GEOMETRIC_EXT
@ DPNP_FN_RNG_NEGATIVE_BINOMIAL_EXT
-
@ DPNP_FN_RNG_EXPONENTIAL
-
@ DPNP_FN_RNG_VONMISES_EXT
@@ -368,7 +352,6 @@
@ DPNP_FN_RNG_HYPERGEOMETRIC
@ DPNP_FN_RNG_STANDARD_GAMMA
-
@ DPNP_FN_RNG_NONCENTRAL_CHISQUARE
@ DPNP_FN_RNG_NEGATIVE_BINOMIAL
@@ -392,7 +375,6 @@
@ DPNP_FN_RNG_UNIFORM_EXT
-
@ DPNP_FN_RNG_STANDARD_GAMMA_EXT
@@ -414,11 +396,11 @@
-
Contains information about the C++ backend function.
-
DPNPFuncType return_type_no_fp64
-
-
-
+
Contains information about the C++ backend function.
+
DPNPFuncType return_type_no_fp64
+
+
+
199 template <
typename _DataType>
-
-
-
202 const _DataType *offsets)
-
-
204 size_t global_id = 0;
-
-
-
207 for (
size_t it = 0; it < xyz_size; ++it) {
-
208 global_id += (xyz[it] * offsets[it]);
-
-
-
-
-
197 broadcastable(
const std::vector<shape_elem_type> &input_shape,
198 const std::vector<shape_elem_type> &output_shape)
200 if (input_shape.size() > output_shape.size()) {
204 std::vector<shape_elem_type>::const_reverse_iterator irit =
205 input_shape.rbegin();
206 std::vector<shape_elem_type>::const_reverse_iterator orit =
207 output_shape.rbegin();
208 for (; irit != input_shape.rend(); ++irit, ++orit) {
209 if (*irit != 1 && *irit != *orit) {
225 broadcastable(
const std::vector<shape_elem_type> &input_shape,
226 const std::vector<shape_elem_type> &output_shape)
228 if (input_shape.size() > output_shape.size()) {
232 std::vector<shape_elem_type>::const_reverse_iterator irit =
233 input_shape.rbegin();
234 std::vector<shape_elem_type>::const_reverse_iterator orit =
235 output_shape.rbegin();
236 for (; irit != input_shape.rend(); ++irit, ++orit) {
237 if (*irit != 1 && *irit != *orit) {
246 broadcastable(
const shape_elem_type *input_shape,
247 const size_t input_shape_size,
248 const std::vector<shape_elem_type> &output_shape)
250 const std::vector<shape_elem_type> input_shape_vec(
251 input_shape, input_shape + input_shape_size);
252 return broadcastable(input_shape_vec, output_shape);
266 template <
typename _DataType>
267 static inline bool array_equal(
const _DataType *input1,
268 const size_t input1_size,
269 const _DataType *input2,
270 const size_t input2_size)
272 if (input1_size != input2_size)
275 const std::vector<_DataType> input1_vec(input1, input1 + input1_size);
276 const std::vector<_DataType> input2_vec(input2, input2 + input2_size);
278 return std::equal(std::begin(input1_vec), std::end(input1_vec),
279 std::begin(input2_vec));
292 [[maybe_unused]] std::vector<sycl::event>
293 cast_event_vector(
const DPCTLEventVectorRef event_vec_ref)
295 const size_t event_vec_size = DPCTLEventVector_Size(event_vec_ref);
297 std::vector<sycl::event> event_vec;
298 event_vec.reserve(event_vec_size);
299 for (
size_t i = 0; i < event_vec_size; ++i) {
300 DPCTLSyclEventRef event_ref = DPCTLEventVector_GetAt(event_vec_ref, i);
301 sycl::event
event = *(
reinterpret_cast< sycl::event *
> (event_ref));
302 event_vec.push_back(event);
325 template <
typename _DataType>
326 static inline std::vector<_DataType>
327 get_result_shape(
const _DataType *input1_shape,
328 const size_t input1_shape_size,
329 const _DataType *input2_shape,
330 const size_t input2_shape_size)
332 const size_t result_shape_size = (input2_shape_size > input1_shape_size)
335 std::vector<_DataType> result_shape;
336 result_shape.reserve(result_shape_size);
338 for (
int irit1 = input1_shape_size - 1, irit2 = input2_shape_size - 1;
339 irit1 >= 0 || irit2 >= 0; --irit1, --irit2)
341 _DataType input1_val = (irit1 >= 0) ? input1_shape[irit1] : 1;
342 _DataType input2_val = (irit2 >= 0) ? input2_shape[irit2] : 1;
344 if (input1_val == input2_val || input1_val == 1) {
345 result_shape.insert(result_shape.begin(), input2_val);
347 else if (input2_val == 1) {
348 result_shape.insert(result_shape.begin(), input1_val);
351 throw std::domain_error(
"DPNP Error: get_common_shape() failed " 352 "with input shapes check" );
378 static inline std::vector<shape_elem_type>
379 get_validated_axes(
const std::vector<shape_elem_type> &__axes,
380 const size_t __shape_size,
381 const bool __allow_duplicate =
false )
383 std::vector<shape_elem_type> result;
385 if (__axes.empty()) {
389 if (__axes.size() > __shape_size) {
393 result.reserve(__axes.size());
394 for (std::vector<shape_elem_type>::const_iterator it = __axes.cbegin();
395 it != __axes.cend(); ++it)
397 const shape_elem_type _axis = *it;
398 const shape_elem_type input_shape_size_signed =
399 static_cast< shape_elem_type
> (__shape_size);
400 if (_axis >= input_shape_size_signed) {
218 broadcastable(
const shape_elem_type *input_shape,
219 const size_t input_shape_size,
220 const std::vector<shape_elem_type> &output_shape)
222 const std::vector<shape_elem_type> input_shape_vec(
223 input_shape, input_shape + input_shape_size);
224 return broadcastable(input_shape_vec, output_shape);
238 template <
typename _DataType>
239 static inline bool array_equal(
const _DataType *input1,
240 const size_t input1_size,
241 const _DataType *input2,
242 const size_t input2_size)
244 if (input1_size != input2_size)
247 const std::vector<_DataType> input1_vec(input1, input1 + input1_size);
248 const std::vector<_DataType> input2_vec(input2, input2 + input2_size);
250 return std::equal(std::begin(input1_vec), std::end(input1_vec),
251 std::begin(input2_vec));
264 [[maybe_unused]] std::vector<sycl::event>
265 cast_event_vector(
const DPCTLEventVectorRef event_vec_ref)
267 const size_t event_vec_size = DPCTLEventVector_Size(event_vec_ref);
269 std::vector<sycl::event> event_vec;
270 event_vec.reserve(event_vec_size);
271 for (
size_t i = 0; i < event_vec_size; ++i) {
272 DPCTLSyclEventRef event_ref = DPCTLEventVector_GetAt(event_vec_ref, i);
273 sycl::event
event = *(
reinterpret_cast< sycl::event *
> (event_ref));
274 event_vec.push_back(event);
299 static inline std::vector<shape_elem_type>
300 get_validated_axes(
const std::vector<shape_elem_type> &__axes,
301 const size_t __shape_size,
302 const bool __allow_duplicate =
false )
304 std::vector<shape_elem_type> result;
306 if (__axes.empty()) {
310 if (__axes.size() > __shape_size) {
314 result.reserve(__axes.size());
315 for (std::vector<shape_elem_type>::const_iterator it = __axes.cbegin();
316 it != __axes.cend(); ++it)
318 const shape_elem_type _axis = *it;
319 const shape_elem_type input_shape_size_signed =
320 static_cast< shape_elem_type
> (__shape_size);
321 if (_axis >= input_shape_size_signed) {
325 if (_axis < -input_shape_size_signed) {
329 const shape_elem_type positive_axis =
330 _axis < 0 ? (_axis + input_shape_size_signed) : _axis;
332 if (!__allow_duplicate) {
333 if (std::find(result.begin(), result.end(), positive_axis) !=
339 result.push_back(positive_axis);
348 throw std::range_error(
349 "DPNP Error: validate_axes() failed with axis check" );
363 static inline void validate_type_for_device(
const sycl::device &d)
365 if constexpr (std::is_same_v<T, double>) {
366 if (!d.has(sycl::aspect::fp64)) {
367 throw std::runtime_error(
"Device " +
368 d.get_info<sycl::info::device::name>() +
369 " does not support type 'double'" );
372 else if constexpr (std::is_same_v<T, std::complex<double>>) {
373 if (!d.has(sycl::aspect::fp64)) {
374 throw std::runtime_error(
375 "Device " + d.get_info<sycl::info::device::name>() +
376 " does not support type 'complex<double>'" );
379 else if constexpr (std::is_same_v<T, sycl::half>) {
380 if (!d.has(sycl::aspect::fp16)) {
381 throw std::runtime_error(
"Device " +
382 d.get_info<sycl::info::device::name>() +
383 " does not support type 'half'" );
399 static inline void validate_type_for_device(
const sycl::queue &q)
401 validate_type_for_device<T>(q.get_device());
404 if (_axis < -input_shape_size_signed) {
408 const shape_elem_type positive_axis =
409 _axis < 0 ? (_axis + input_shape_size_signed) : _axis;
411 if (!__allow_duplicate) {
412 if (std::find(result.begin(), result.end(), positive_axis) !=
418 result.push_back(positive_axis);
427 throw std::range_error(
428 "DPNP Error: validate_axes() failed with axis check" );
+
413 std::ostream &
operator<< (std::ostream &out,
const std::vector<T> &vec)
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415 std::string delimiter;
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420 for (
auto &elem : vec) {
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421 out << delimiter << elem;
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422 if (delimiter.empty()) {
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423 delimiter.assign(
", " );
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442 static inline void validate_type_for_device(
const sycl::device &d)
-
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444 if constexpr (std::is_same_v<T, double>) {
-
445 if (!d.has(sycl::aspect::fp64)) {
-
446 throw std::runtime_error(
"Device " +
-
447 d.get_info<sycl::info::device::name>() +
-
448 " does not support type 'double'" );
-
-
-
451 else if constexpr (std::is_same_v<T, std::complex<double>>) {
-
452 if (!d.has(sycl::aspect::fp64)) {
-
453 throw std::runtime_error(
-
454 "Device " + d.get_info<sycl::info::device::name>() +
-
455 " does not support type 'complex<double>'" );
-
-
-
458 else if constexpr (std::is_same_v<T, sycl::half>) {
-
459 if (!d.has(sycl::aspect::fp16)) {
-
460 throw std::runtime_error(
"Device " +
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461 d.get_info<sycl::info::device::name>() +
-
462 " does not support type 'half'" );
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478 static inline void validate_type_for_device(
const sycl::queue &q)
-
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480 validate_type_for_device<T>(q.get_device());
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492 std::ostream &
operator<< (std::ostream &out,
const std::vector<T> &vec)
-
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494 std::string delimiter;
-
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499 for (
auto &elem : vec) {
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500 out << delimiter << elem;
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501 if (delimiter.empty()) {
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502 delimiter.assign(
", " );
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522 out << static_cast<size_t>(elem);
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443 out << static_cast<size_t>(elem);
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DPNPFuncType
Template types which are used in this interface.
-
size_t get_id_by_xyz_inkernel(const _DataType *xyz, size_t xyz_size, const _DataType *offsets)
Calculate linear index from ids array.
-
std::ostream & operator<<(std::ostream &out, const std::vector< T > &vec)
print std::vector to std::ostream.
+
+
+
DPNPFuncType
Template types which are used in this interface.
+
std::ostream & operator<<(std::ostream &out, const std::vector< T > &vec)
print std::vector to std::ostream.
void get_shape_offsets_inkernel(const _DataType *shape, size_t shape_size, _DataType *offsets)
Shape offset calculation used in kernels.
void get_xyz_by_id(size_t idx, size_t ndim, const _DataType *offsets, _DataType *xyz)
Calculation of indices in array.
_DataType get_xyz_id_by_id_inkernel(size_t global_id, const _DataType *offsets, size_t offsets_size, size_t axis)
Calculate xyz id for given axis from linear index.
diff --git a/pull/2116/backend_doc/extensions_2ufunc_2elementwise__functions_2ldexp_8hpp_source.html b/pull/2116/backend_doc/extensions_2ufunc_2elementwise__functions_2ldexp_8hpp_source.html
new file mode 100644
index 00000000000..e18855f8f0e
--- /dev/null
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DPNP C++ backend kernel library: /github/workspace/dpnp/backend/extensions/ufunc/elementwise_functions/ldexp.hpp Source File
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+ Data Parallel Extension for NumPy*
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28 #include <pybind11/pybind11.h>
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30 namespace py = pybind11;
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32 namespace dpnp::extensions::ufunc
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34 void init_ldexp(py::module_ m);
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diff --git a/pull/2116/backend_doc/files.html b/pull/2116/backend_doc/files.html
index a16f3f0bc8c..e8f1d19caf4 100644
--- a/pull/2116/backend_doc/files.html
+++ b/pull/2116/backend_doc/files.html
@@ -148,9 +148,10 @@
gcd.hpp heaviside.hpp lcm.hpp
-
logaddexp2.hpp
-
populate.hpp
-
radians.hpp
+
ldexp.hpp
+
logaddexp2.hpp
+
populate.hpp
+
radians.hpp ► vm abs.hpp acos.hpp
@@ -209,8 +210,9 @@
gcd.hpp heaviside.hpp lcm.hpp
-
logaddexp2.hpp
-
radians.hpp
+
ldexp.hpp
+
logaddexp2.hpp
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radians.hpp ▼ src constants.hpp dpnp_fptr.hpp
diff --git a/pull/2116/backend_doc/group___b_a_c_k_e_n_d___a_p_i.html b/pull/2116/backend_doc/group___b_a_c_k_e_n_d___a_p_i.html
index b14c3a52690..0d09ede18b3 100644
--- a/pull/2116/backend_doc/group___b_a_c_k_e_n_d___a_p_i.html
+++ b/pull/2116/backend_doc/group___b_a_c_k_e_n_d___a_p_i.html
@@ -113,30 +113,10 @@
DPCTLSyclEventRef dpnp_dot_c (DPCTLSyclQueueRef q_ref, void *result_out, const size_t result_size, const size_t result_ndim, const shape_elem_type *result_shape, const shape_elem_type *result_strides, const void *input1_in, const size_t input1_size, const size_t input1_ndim, const shape_elem_type *input1_shape, const shape_elem_type *input1_strides, const void *input2_in, const size_t input2_size, const size_t input2_ndim, const shape_elem_type *input2_shape, const shape_elem_type *input2_strides, const DPCTLEventVectorRef dep_event_vec_ref) Custom implementation of dot function.
-
template<typename _DataType_output , typename _DataType_input >
-
DPCTLSyclEventRef dpnp_sum_c (DPCTLSyclQueueRef q_ref, void *result_out, const void *input_in, const shape_elem_type *input_shape, const size_t input_shape_ndim, const shape_elem_type *axes, const size_t axes_ndim, const void *initial, const long *where, const DPCTLEventVectorRef dep_event_vec_ref)
-
Compute summary of input array elements.
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template<typename _DataType > DPCTLSyclEventRef dpnp_partition_c (DPCTLSyclQueueRef q_ref, void *array, void *array2, void *result, const size_t kth, const shape_elem_type *shape, const size_t ndim, const DPCTLEventVectorRef dep_event_vec_ref) Return a partitioned copy of an array.
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template<typename _DataType_output , typename _DataType_input >
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DPCTLSyclEventRef dpnp_prod_c (DPCTLSyclQueueRef q_ref, void *result_out, const void *input_in, const shape_elem_type *input_shape, const size_t input_shape_ndim, const shape_elem_type *axes, const size_t axes_ndim, const void *initial, const long *where, const DPCTLEventVectorRef dep_event_vec_ref)
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Compute Product of input array elements.
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template<typename _DataType , typename _idx_DataType >
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DPCTLSyclEventRef dpnp_argsort_c (DPCTLSyclQueueRef q_ref, void *array, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
-
math library implementation of argsort function
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template<typename _DataType , typename _IndexingType >
-
DPCTLSyclEventRef dpnp_searchsorted_c (DPCTLSyclQueueRef q_ref, void *result, const void *array, const void *v, bool side, const size_t arr_size, const size_t v_size, const DPCTLEventVectorRef dep_event_vec_ref)
-
math library implementation of searchsorted function
-
-
template<typename _DataType >
-
DPCTLSyclEventRef dpnp_sort_c (DPCTLSyclQueueRef q_ref, void *array, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
-
math library implementation of sort function
-
template<typename _DataType_output , typename _DataType_input1 , typename _DataType_input2 > DPCTLSyclEventRef dpnp_correlate_c (DPCTLSyclQueueRef q_ref, void *result_out, const void *input1_in, const size_t input1_size, const shape_elem_type *input1_shape, const size_t input1_shape_ndim, const void *input2_in, const size_t input2_size, const shape_elem_type *input2_shape, const size_t input2_shape_ndim, const size_t *where, const DPCTLEventVectorRef dep_event_vec_ref) correlate function
@@ -149,18 +129,6 @@
DPCTLSyclEventRef dpnp_initval_c (DPCTLSyclQueueRef q_ref, void *result1, void *value, size_t size, const DPCTLEventVectorRef dep_event_vec_ref) implementation of creating filled with value array function
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template<typename _DataType , typename _ResultType >
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DPCTLSyclEventRef dpnp_median_c (DPCTLSyclQueueRef q_ref, void *array, void *result, const shape_elem_type *shape, size_t ndim, const shape_elem_type *axis, size_t naxis, const DPCTLEventVectorRef dep_event_vec_ref)
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math library implementation of median function
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template<typename _DataType , typename _idx_DataType >
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DPCTLSyclEventRef dpnp_argmax_c (DPCTLSyclQueueRef q_ref, void *array, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
-
math library implementation of argmax function
-
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template<typename _DataType , typename _idx_DataType >
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DPCTLSyclEventRef dpnp_argmin_c (DPCTLSyclQueueRef q_ref, void *array, void *result, size_t size, const DPCTLEventVectorRef dep_event_vec_ref)
-
math library implementation of argmin function
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template<typename _DataType_input , typename _DataType_output > DPCTLSyclEventRef dpnp_modf_c (DPCTLSyclQueueRef q_ref, void *array1_in, void *result1_out, void *result2_out, size_t size, const DPCTLEventVectorRef dep_event_vec_ref) modf function.
@@ -209,186 +177,6 @@
This section describes Backend API.
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- DPCTLSyclEventRef dpnp_argmax_c
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- DPCTLSyclQueueRef
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- array ,
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- size_t
- size ,
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- dep_event_vec_ref
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- )
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math library implementation of argmax function
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Parameters
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- [in] q_ref Reference to SYCL queue. [in] array Input array with data. [out] result Output array with indices. [in] size Number of elements in input array. [in] dep_event_vec_ref Reference to vector of SYCL events.
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- DPCTLSyclEventRef dpnp_argmin_c
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- DPCTLSyclQueueRef
- q_ref ,
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- result ,
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math library implementation of argmin function
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Parameters
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- [in] q_ref Reference to SYCL queue. [in] array Input array with data. [out] result Output array with indices. [in] size Number of elements in input array. [in] dep_event_vec_ref Reference to vector of SYCL events.
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math library implementation of argsort function
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Parameters
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- [in] q_ref Reference to SYCL queue. [in] array Input array with data. [out] result Output array with indices. [in] size Number of elements in input arrays. [in] dep_event_vec_ref Reference to vector of SYCL events.
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@@ -781,87 +569,6 @@
DPNP C++ backend kernel library: /github/workspace/dpnp/backend/kernels/elementwise_functions/ldexp.hpp Source File
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+ DPNP C++ backend kernel library 0.17.0dev0
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+ Data Parallel Extension for NumPy*
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28 #include <sycl/sycl.hpp>
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31 #include "utils/math_utils.hpp"
+
32 #include "utils/type_utils.hpp"
+
+
34 namespace dpnp::kernels::ldexp
+
+
36 template <
typename argT1,
typename argT2,
typename resT>
+
+
+
+
39 using supports_sg_loadstore =
typename std::true_type;
+
40 using supports_vec =
typename std::false_type;
+
+
42 resT operator()(
const argT1 &in1,
const argT2 &in2)
const
+
+
44 if (((
int )in2) == in2) {
+
45 return sycl::ldexp(in1, in2);
+
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50 return std::numeric_limits<resT>::infinity();
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Contains information about the C++ backend function.
The structure defines the types that are used by get_dpnp_function_ptr .
-
Definition at line 252 of file dpnp_iface_fptr.hpp .
+
Definition at line 242 of file dpnp_iface_fptr.hpp .
◆ [1/3] DPNP C++ backend kernel library: Member List
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+ Data Parallel Extension for NumPy*
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This is the complete list of members for dpnp::kernels::ldexp::LdexpFunctor< argT1, argT2, resT > , including all inherited members.
+
+ operator() (const argT1 &in1, const argT2 &in2) const (defined in dpnp::kernels::ldexp::LdexpFunctor< argT1, argT2, resT > )dpnp::kernels::ldexp::LdexpFunctor< argT1, argT2, resT > inline supports_sg_loadstore typedef (defined in dpnp::kernels::ldexp::LdexpFunctor< argT1, argT2, resT > )dpnp::kernels::ldexp::LdexpFunctor< argT1, argT2, resT > supports_vec typedef (defined in dpnp::kernels::ldexp::LdexpFunctor< argT1, argT2, resT > )dpnp::kernels::ldexp::LdexpFunctor< argT1, argT2, resT >
+
DPNP C++ backend kernel library: dpnp::kernels::ldexp::LdexpFunctor< argT1, argT2, resT > Struct Template Reference
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+ DPNP C++ backend kernel library 0.17.0dev0
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+ Data Parallel Extension for NumPy*
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+resT operator() (const argT1 &in1, const argT2 &in2) const
+
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template<typename argT1, typename argT2, typename resT>
+
Definition at line 37 of file ldexp.hpp .
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The documentation for this struct was generated from the following file:
+/github/workspace/dpnp/backend/kernels/elementwise_functions/ldexp.hpp
+
+
+
Interplay with the Data Parallel Control Library — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ Interplay with the Data Parallel Control Library — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
C++ backend API Reference — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ C++ backend API Reference — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
Index — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+ Index — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
I
iscomplexobj() (in module dpnp)
isfinite() (in module dpnp)
+
+
isfortran() (in module dpnp)
isinf() (in module dpnp)
@@ -962,6 +964,8 @@
L
laplace() (in module dpnp.random)
lcm() (in module dpnp)
+
+
ldexp() (in module dpnp)
left_shift() (in module dpnp)
diff --git a/pull/2116/index.html b/pull/2116/index.html
index e57849673ba..0ac1a8a355e 100644
--- a/pull/2116/index.html
+++ b/pull/2116/index.html
@@ -15,14 +15,14 @@
-
Data Parallel Extension for NumPy* — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+
Data Parallel Extension for NumPy* — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
-
+
diff --git a/pull/2116/objects.inv b/pull/2116/objects.inv
index 14f18efe13d..ce97c3a5f39 100644
Binary files a/pull/2116/objects.inv and b/pull/2116/objects.inv differ
diff --git a/pull/2116/overview.html b/pull/2116/overview.html
index 6114c06ecc8..4dfbb1a7dce 100644
--- a/pull/2116/overview.html
+++ b/pull/2116/overview.html
@@ -15,14 +15,14 @@
-
Overview — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+
Overview — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
-
+
diff --git a/pull/2116/py-modindex.html b/pull/2116/py-modindex.html
index da6262b016c..f38e1edd9f8 100644
--- a/pull/2116/py-modindex.html
+++ b/pull/2116/py-modindex.html
@@ -14,14 +14,14 @@
-
Python Module Index — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+
Python Module Index — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
-
+
diff --git a/pull/2116/quick_start_guide.html b/pull/2116/quick_start_guide.html
index ab2043d7f18..f2922c6a21a 100644
--- a/pull/2116/quick_start_guide.html
+++ b/pull/2116/quick_start_guide.html
@@ -15,14 +15,14 @@
-
Quick Start Guide — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+
Quick Start Guide — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
-
+
diff --git a/pull/2116/reference/binary.html b/pull/2116/reference/binary.html
index 2e15569a104..9849a2ec8c7 100644
--- a/pull/2116/reference/binary.html
+++ b/pull/2116/reference/binary.html
@@ -15,14 +15,14 @@
-
Bit-wise operations — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+
Bit-wise operations — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
-
+
diff --git a/pull/2116/reference/comparison.html b/pull/2116/reference/comparison.html
index 7130888125a..ef2bde8efae 100644
--- a/pull/2116/reference/comparison.html
+++ b/pull/2116/reference/comparison.html
@@ -15,14 +15,14 @@
-
Comparison Table NumPy/ DPNP/ CuPy — Data Parallel Extension for NumPy 0.17.0dev0+69.gd22f8d5af09 documentation
+
Comparison Table NumPy/ DPNP/ CuPy — Data Parallel Extension for NumPy 0.17.0dev0+83.g25fb080b039 documentation
-
+
@@ -107,7 +107,7 @@
Comparison Table NumPy/ DPNP/ CuPy
Here is a list of NumPy and CuPy APIs and its corresponding DPNP implementations.
-
-
NumPy(v1.23.5) / DPNP(v0.17.0dev0+69.gd22f8d5af09) / CuPy(v9.6.0) APIs
+
NumPy(v1.23.5) / DPNP(v0.17.0dev0+83.g25fb080b039) / CuPy(v9.6.0) APIs
Summary
@@ -119,7 +119,7 @@ Summary
+
