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Added dpctl.tensor.tril and dpctl.tensor.triu feature #910

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Merged
oleksandr-pavlyk merged 6 commits into from
Sep 17, 2022
Merged

Added dpctl.tensor.tril and dpctl.tensor.triu feature #910

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1c67f18
Add tril and triu function
npolina4 Sep 15, 2022
82b4186
Minor changes
npolina4 Sep 16, 2022
ef5f615
Added special case for order=f
npolina4 Sep 16, 2022
d660147
Added memory overlap check
npolina4 Sep 16, 2022
d9371ff
Minor changes
npolina4 Sep 16, 2022
b9c560a
Added tests for tril() and triu() functions
npolina4 Sep 16, 2022
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4 changes: 4 additions & 0 deletions dpctl/tensor/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,8 @@
linspace,
ones,
ones_like,
tril,
triu,
zeros,
zeros_like,
)
Expand Down Expand Up @@ -83,4 +85,6 @@
"to_numpy",
"asnumpy",
"from_dlpack",
"tril",
"triu",
]
82 changes: 82 additions & 0 deletions dpctl/tensor/_ctors.py
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Expand Up @@ -1116,3 +1116,85 @@ def eye(
hev, _ = ti._eye(k, dst=res, sycl_queue=sycl_queue)
hev.wait()
return res


def tril(X, k=0):
"""
tril(X: usm_ndarray, k: int) -> usm_ndarray

Returns the lower triangular part of a matrix (or a stack of matrices) X.
"""
if type(X) is not dpt.usm_ndarray:
raise TypeError

k = operator.index(k)

# F_CONTIGUOUS = 2
order = "f" if (X.flags & 2) else "c"
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shape = X.shape
nd = X.ndim
if nd < 2:
raise ValueError("Array dimensions less than 2.")

if k >= shape[nd - 1] - 1:
res = dpt.empty(
X.shape, dtype=X.dtype, order=order, sycl_queue=X.sycl_queue
)
hev, _ = ti._copy_usm_ndarray_into_usm_ndarray(
src=X, dst=res, sycl_queue=X.sycl_queue
)
hev.wait()
elif k < -shape[nd - 2]:
res = dpt.zeros(
X.shape, dtype=X.dtype, order=order, sycl_queue=X.sycl_queue
)
else:
res = dpt.empty(
X.shape, dtype=X.dtype, order=order, sycl_queue=X.sycl_queue
)
hev, _ = ti._tril(src=X, dst=res, k=k, sycl_queue=X.sycl_queue)
hev.wait()

return res


def triu(X, k=0):
"""
triu(X: usm_ndarray, k: int) -> usm_ndarray

Returns the upper triangular part of a matrix (or a stack of matrices) X.
"""
if type(X) is not dpt.usm_ndarray:
raise TypeError

k = operator.index(k)

# F_CONTIGUOUS = 2
order = "f" if (X.flags & 2) else "c"
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shape = X.shape
nd = X.ndim
if nd < 2:
raise ValueError("Array dimensions less than 2.")

if k > shape[nd - 1]:
res = dpt.zeros(
X.shape, dtype=X.dtype, order=order, sycl_queue=X.sycl_queue
)
elif k <= -shape[nd - 2] + 1:
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res = dpt.empty(
X.shape, dtype=X.dtype, order=order, sycl_queue=X.sycl_queue
)
hev, _ = ti._copy_usm_ndarray_into_usm_ndarray(
src=X, dst=res, sycl_queue=X.sycl_queue
)
hev.wait()
else:
res = dpt.empty(
X.shape, dtype=X.dtype, order=order, sycl_queue=X.sycl_queue
)
hev, _ = ti._triu(src=X, dst=res, k=k, sycl_queue=X.sycl_queue)
hev.wait()

return res
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