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implement dpnp.argmin and dpnp.argmax using dpctl.tensor #1610

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merged 17 commits into from
Nov 23, 2023
Merged

implement dpnp.argmin and dpnp.argmax using dpctl.tensor #1610

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2a38192
rework implementation of diag, diagflat, vander, and ptp
vtavana Sep 29, 2023
6d3f817
address comments - first round
vtavana Oct 22, 2023
0b86691
address comments - second round
vtavana Oct 26, 2023
bd6fcb0
add tests for negative use cases to improve covergae
vtavana Oct 30, 2023
8e870e8
fixed missing merge conflicts
vtavana Nov 8, 2023
5b5439d
fix pre-commit
vtavana Nov 8, 2023
fd38502
implement dpnp.argmin and dpnp.argmax using dpctl.tensor
vtavana Oct 16, 2023
14f043f
address comments
vtavana Oct 27, 2023
e026c37
add tests for negative use cases to improve coverage
vtavana Oct 30, 2023
dec3e57
remove unneccessary parts with updates in dpctl #1465
vtavana Nov 9, 2023
9ebb8a6
Merge branch 'master' into argmin_argmax
vtavana Nov 20, 2023
3eb40d6
add paramater section in doc
vtavana Nov 20, 2023
ccdf3c4
update ndarray.argmin and ndarray.argmax function signature
vtavana Nov 20, 2023
655182a
use a utility func for returning output
vtavana Nov 20, 2023
30f87eb
add tests for ndarray implementation
vtavana Nov 21, 2023
df98a82
Place new function acc to lexicographical order
antonwolfy Nov 22, 2023
618aba0
Merge branch 'master' into argmin_argmax
antonwolfy Nov 23, 2023
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4 changes: 2 additions & 2 deletions dpnp/dpnp_array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -486,7 +486,7 @@ def any(self, axis=None, out=None, keepdims=False, *, where=True):
self, axis=axis, out=out, keepdims=keepdims, where=where
)

def argmax(self, axis=None, out=None):
def argmax(self, axis=None, out=None, *, keepdims=False):
"""
Returns array of indices of the maximum values along the given axis.

Expand All @@ -495,7 +495,7 @@ def argmax(self, axis=None, out=None):
"""
return dpnp.argmax(self, axis, out)
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def argmin(self, axis=None, out=None):
def argmin(self, axis=None, out=None, *, keepdims=False):
"""
Return array of indices to the minimum values along the given axis.

Expand Down
44 changes: 44 additions & 0 deletions dpnp/dpnp_iface.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,6 +69,7 @@
"get_usm_ndarray_or_scalar",
"is_supported_array_or_scalar",
"is_supported_array_type",
"_copyto",
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]

from dpnp import float64, isscalar
Expand Down Expand Up @@ -516,3 +517,46 @@ def is_supported_array_type(a):
"""

return isinstance(a, (dpnp_array, dpt.usm_ndarray))


def _copyto(a, out=None):
"""
If `out` is provided, `a` will be inserted into this array.
Otherwise, `a` is returned.
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Parameters
----------
a : {dpnp_array}
An input array.

out : {dpnp_array, usm_ndarray}
If provided, the input will be inserted into this array.
It should be of the appropriate shape.

Returns
-------
out : {dpnp_array}
Return `out` if provided, otherwise return `a`.

"""

if out is None:
return a
else:
if out.shape != a.shape:
raise ValueError(
f"Output array of shape {a.shape} is needed, got {out.shape}."
)
elif not isinstance(out, dpnp_array):
if isinstance(out, dpt.usm_ndarray):
out = dpnp_array._create_from_usm_ndarray(out)
else:
raise TypeError(
"Output array must be any of supported type, but got {}".format(
type(out)
)
)

dpnp.copyto(out, a, casting="safe")

return out
21 changes: 1 addition & 20 deletions dpnp/dpnp_iface_mathematical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2158,26 +2158,7 @@ def prod(
dpt.prod(dpt_array, axis=axis, dtype=dtype, keepdims=keepdims)
)

if out is None:
return result
else:
if out.shape != result.shape:
raise ValueError(
f"Output array of shape {result.shape} is needed, got {out.shape}."
)
elif not isinstance(out, dpnp_array):
if isinstance(out, dpt.usm_ndarray):
out = dpnp_array._create_from_usm_ndarray(out)
else:
raise TypeError(
"Output array must be any of supported type, but got {}".format(
type(out)
)
)

dpnp.copyto(out, result, casting="safe")

return out
return dpnp._copyto(result, out)


def proj(
Expand Down
42 changes: 2 additions & 40 deletions dpnp/dpnp_iface_searching.py
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Original file line number Diff line number Diff line change
Expand Up @@ -126,26 +126,7 @@ def argmax(a, axis=None, out=None, *, keepdims=False):
dpt.argmax(dpt_array, axis=axis, keepdims=keepdims)
)

if out is None:
return result
else:
if out.shape != result.shape:
raise ValueError(
f"Output array of shape {result.shape} is needed, got {out.shape}."
)
elif not isinstance(out, dpnp_array):
if isinstance(out, dpt.usm_ndarray):
out = dpnp_array._create_from_usm_ndarray(out)
else:
raise TypeError(
"Output array must be any of supported type, but got {}".format(
type(out)
)
)

dpnp.copyto(out, result, casting="safe")

return out
return dpnp._copyto(result, out)


def argmin(a, axis=None, out=None, *, keepdims=False):
Expand Down Expand Up @@ -225,26 +206,7 @@ def argmin(a, axis=None, out=None, *, keepdims=False):
dpt.argmin(dpt_array, axis=axis, keepdims=keepdims)
)

if out is None:
return result
else:
if out.shape != result.shape:
raise ValueError(
f"Output array of shape {result.shape} is needed, got {out.shape}."
)
elif not isinstance(out, dpnp_array):
if isinstance(out, dpt.usm_ndarray):
out = dpnp_array._create_from_usm_ndarray(out)
else:
raise TypeError(
"Output array must be any of supported type, but got {}".format(
type(out)
)
)

dpnp.copyto(out, result, casting="safe")

return out
return dpnp._copyto(result, out)


def searchsorted(a, v, side="left", sorter=None):
Expand Down
44 changes: 3 additions & 41 deletions dpnp/dpnp_iface_statistics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -414,26 +414,7 @@ def max(a, axis=None, out=None, keepdims=False, initial=None, where=True):
dpt.max(dpt_array, axis=axis, keepdims=keepdims)
)

if out is None:
return result
else:
if out.shape != result.shape:
raise ValueError(
f"Output array of shape {result.shape} is needed, got {out.shape}."
)
elif not isinstance(out, dpnp_array):
if isinstance(out, dpt.usm_ndarray):
out = dpnp_array._create_from_usm_ndarray(out)
else:
raise TypeError(
"Output array must be any of supported type, but got {}".format(
type(out)
)
)

dpnp.copyto(out, result, casting="safe")

return out
return dpnp._copyto(result, out)


def mean(x, /, *, axis=None, dtype=None, keepdims=False, out=None, where=True):
Expand Down Expand Up @@ -638,34 +619,15 @@ def min(a, axis=None, out=None, keepdims=False, initial=None, where=True):
)
elif where is not True:
raise NotImplementedError(
"where keyword argument is only supported by its default values."
"where keyword argument is only supported by its default value."
)
else:
dpt_array = dpnp.get_usm_ndarray(a)
result = dpnp_array._create_from_usm_ndarray(
dpt.min(dpt_array, axis=axis, keepdims=keepdims)
)

if out is None:
return result
else:
if out.shape != result.shape:
raise ValueError(
f"Output array of shape {result.shape} is needed, got {out.shape}."
)
elif not isinstance(out, dpnp_array):
if isinstance(out, dpt.usm_ndarray):
out = dpnp_array._create_from_usm_ndarray(out)
else:
raise TypeError(
"Output array must be any of supported type, but got {}".format(
type(out)
)
)

dpnp.copyto(out, result, casting="safe")

return out
return dpnp._copyto(result, out)


def ptp(
Expand Down
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