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implement maximum and minimum #1558

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merged 5 commits into from
Sep 29, 2023
Merged

implement maximum and minimum #1558

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8f716c4
implement maximum and minimum
vtavana Sep 6, 2023
2c91a90
address comments
vtavana Sep 15, 2023
c80e404
add new tests
vtavana Sep 21, 2023
8df6821
Merge branch 'master' into minimum_maximum_dpctl_to_dpnp
vtavana Sep 28, 2023
833808f
Merge branch 'master' into minimum_maximum_dpctl_to_dpnp
vtavana Sep 29, 2023
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8 changes: 4 additions & 4 deletions dpnp/backend/include/dpnp_iface_fptr.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -242,17 +242,17 @@ enum class DPNPFuncName : size_t
requires extra parameters */
DPNP_FN_MAX, /**< Used in numpy.max() impl */
DPNP_FN_MAX_EXT, /**< Used in numpy.max() impl, requires extra parameters */
DPNP_FN_MAXIMUM, /**< Used in numpy.maximum() impl */
DPNP_FN_MAXIMUM_EXT, /**< Used in numpy.maximum() impl , requires extra
DPNP_FN_MAXIMUM, /**< Used in numpy.fmax() impl */
DPNP_FN_MAXIMUM_EXT, /**< Used in numpy.fmax() impl , requires extra
parameters */
DPNP_FN_MEAN, /**< Used in numpy.mean() impl */
DPNP_FN_MEDIAN, /**< Used in numpy.median() impl */
DPNP_FN_MEDIAN_EXT, /**< Used in numpy.median() impl, requires extra
parameters */
DPNP_FN_MIN, /**< Used in numpy.min() impl */
DPNP_FN_MIN_EXT, /**< Used in numpy.min() impl, requires extra parameters */
DPNP_FN_MINIMUM, /**< Used in numpy.minimum() impl */
DPNP_FN_MINIMUM_EXT, /**< Used in numpy.minimum() impl, requires extra
DPNP_FN_MINIMUM, /**< Used in numpy.fmin() impl */
DPNP_FN_MINIMUM_EXT, /**< Used in numpy.fmax() impl, requires extra
parameters */
DPNP_FN_MODF, /**< Used in numpy.modf() impl */
DPNP_FN_MODF_EXT, /**< Used in numpy.modf() impl, requires extra parameters
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5 changes: 2 additions & 3 deletions dpnp/dpnp_algo/dpnp_algo.pxd
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Original file line number Diff line number Diff line change
Expand Up @@ -386,11 +386,10 @@ Mathematical functions
"""
cpdef dpnp_descriptor dpnp_hypot(dpnp_descriptor x1_obj, dpnp_descriptor x2_obj, object dtype=*,
dpnp_descriptor out=*, object where=*)
cpdef dpnp_descriptor dpnp_maximum(dpnp_descriptor x1_obj, dpnp_descriptor x2_obj, object dtype=*,
cpdef dpnp_descriptor dpnp_fmax(dpnp_descriptor x1_obj, dpnp_descriptor x2_obj, object dtype=*,
dpnp_descriptor out=*, object where=*)
cpdef dpnp_descriptor dpnp_minimum(dpnp_descriptor x1_obj, dpnp_descriptor x2_obj, object dtype=*,
cpdef dpnp_descriptor dpnp_fmin(dpnp_descriptor x1_obj, dpnp_descriptor x2_obj, object dtype=*,
dpnp_descriptor out=*, object where=*)

"""
Array manipulation routines
"""
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8 changes: 4 additions & 4 deletions dpnp/dpnp_algo/dpnp_algo_mathematical.pxi
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Original file line number Diff line number Diff line change
Expand Up @@ -47,8 +47,8 @@ __all__ += [
"dpnp_fmod",
"dpnp_gradient",
'dpnp_hypot',
"dpnp_maximum",
"dpnp_minimum",
"dpnp_fmax",
"dpnp_fmin",
"dpnp_modf",
"dpnp_nancumprod",
"dpnp_nancumsum",
Expand Down Expand Up @@ -281,15 +281,15 @@ cpdef utils.dpnp_descriptor dpnp_hypot(utils.dpnp_descriptor x1_obj,
return call_fptr_2in_1out_strides(DPNP_FN_HYPOT_EXT, x1_obj, x2_obj, dtype, out, where)


cpdef utils.dpnp_descriptor dpnp_maximum(utils.dpnp_descriptor x1_obj,
cpdef utils.dpnp_descriptor dpnp_fmax(utils.dpnp_descriptor x1_obj,
utils.dpnp_descriptor x2_obj,
object dtype=None,
utils.dpnp_descriptor out=None,
object where=True):
return call_fptr_2in_1out_strides(DPNP_FN_MAXIMUM_EXT, x1_obj, x2_obj, dtype, out, where)


cpdef utils.dpnp_descriptor dpnp_minimum(utils.dpnp_descriptor x1_obj,
cpdef utils.dpnp_descriptor dpnp_fmin(utils.dpnp_descriptor x1_obj,
utils.dpnp_descriptor x2_obj,
object dtype=None,
utils.dpnp_descriptor out=None,
Expand Down
94 changes: 94 additions & 0 deletions dpnp/dpnp_algo/dpnp_elementwise_common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,6 +76,8 @@
"dpnp_logical_not",
"dpnp_logical_or",
"dpnp_logical_xor",
"dpnp_maximum",
"dpnp_minimum",
"dpnp_multiply",
"dpnp_negative",
"dpnp_positive",
Expand Down Expand Up @@ -1813,6 +1815,98 @@ def dpnp_logical_xor(x1, x2, out=None, order="K"):
return dpnp_array._create_from_usm_ndarray(res_usm)


_maximum_docstring_ = """
maximum(x1, x2, out=None, order='K')

Compares two input arrays `x1` and `x2` and returns
a new array containing the element-wise maxima.

Args:
x1 (dpnp.ndarray):
First input array, expected to have numeric data type.
x2 (dpnp.ndarray):
Second input array, also expected to have numeric data type.
out ({None, dpnp.ndarray}, optional):
Output array to populate.
Array have the correct shape and the expected data type.
order ("C","F","A","K", optional):
Memory layout of the newly output array, if parameter `out` is `None`.
Default: "K".
Returns:
dpnp.ndarray:
An array containing the element-wise maxima. The data type of
the returned array is determined by the Type Promotion Rules.
"""


maximum_func = BinaryElementwiseFunc(
"maximum",
ti._maximum_result_type,
ti._maximum,
_maximum_docstring_,
)


def dpnp_maximum(x1, x2, out=None, order="K"):
"""Invokes maximum() from dpctl.tensor implementation for maximum() function."""

# dpctl.tensor only works with usm_ndarray or scalar
x1_usm_or_scalar = dpnp.get_usm_ndarray_or_scalar(x1)
x2_usm_or_scalar = dpnp.get_usm_ndarray_or_scalar(x2)
out_usm = None if out is None else dpnp.get_usm_ndarray(out)

res_usm = maximum_func(
x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
)
return dpnp_array._create_from_usm_ndarray(res_usm)


_minimum_docstring_ = """
minimum(x1, x2, out=None, order='K')

Compares two input arrays `x1` and `x2` and returns
a new array containing the element-wise minima.

Args:
x1 (dpnp.ndarray):
First input array, expected to have numeric data type.
x2 (dpnp.ndarray):
Second input array, also expected to have numeric data type.
out ({None, dpnp.ndarray}, optional):
Output array to populate.
Array have the correct shape and the expected data type.
order ("C","F","A","K", optional):
Memory layout of the newly output array, if parameter `out` is `None`.
Default: "K".
Returns:
dpnp.ndarray:
An array containing the element-wise minima. The data type of
the returned array is determined by the Type Promotion Rules.
"""


minimum_func = BinaryElementwiseFunc(
"minimum",
ti._minimum_result_type,
ti._minimum,
_minimum_docstring_,
)


def dpnp_minimum(x1, x2, out=None, order="K"):
"""Invokes minimum() from dpctl.tensor implementation for minimum() function."""

# dpctl.tensor only works with usm_ndarray or scalar
x1_usm_or_scalar = dpnp.get_usm_ndarray_or_scalar(x1)
x2_usm_or_scalar = dpnp.get_usm_ndarray_or_scalar(x2)
out_usm = None if out is None else dpnp.get_usm_ndarray(out)

res_usm = minimum_func(
x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
)
return dpnp_array._create_from_usm_ndarray(res_usm)


_multiply_docstring_ = """
multiply(x1, x2, out=None, order="K")

Expand Down
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