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testgroup
pytensor
Commits
e1809275
提交
e1809275
authored
12月 28, 2023
作者:
Ricardo Vieira
提交者:
Ricardo Vieira
1月 02, 2024
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电子邮件补丁
差异文件
Fix bug where ShapeFeature would create circular shape graph
上级
f951743d
显示空白字符变更
内嵌
并排
正在显示
2 个修改的文件
包含
31 行增加
和
2 行删除
+31
-2
shape.py
pytensor/tensor/rewriting/shape.py
+11
-1
test_shape.py
tests/tensor/rewriting/test_shape.py
+20
-1
没有找到文件。
pytensor/tensor/rewriting/shape.py
浏览文件 @
e1809275
...
...
@@ -423,7 +423,17 @@ class ShapeFeature(Feature):
# This mean the shape is equivalent
# We do not want to do the ancestor check in those cases
merged_shape
.
append
(
r_shape
[
i
])
elif
r_shape
[
i
]
in
ancestors
([
other_shape
[
i
]]):
elif
any
(
(
r_shape
[
i
]
==
anc
or
(
anc
.
owner
and
isinstance
(
anc
.
owner
.
op
,
Shape
)
and
anc
.
owner
.
inputs
[
0
]
==
r
)
)
for
anc
in
ancestors
([
other_shape
[
i
]])
):
# Another case where we want to use r_shape[i] is when
# other_shape[i] actually depends on r_shape[i]. In that case,
# we do not want to substitute an expression with another that
...
...
tests/tensor/rewriting/test_shape.py
浏览文件 @
e1809275
...
...
@@ -15,7 +15,7 @@ from pytensor.graph.op import Op
from
pytensor.graph.rewriting.basic
import
check_stack_trace
,
node_rewriter
,
out2in
from
pytensor.graph.rewriting.utils
import
rewrite_graph
from
pytensor.graph.type
import
Type
from
pytensor.tensor.basic
import
as_tensor_variable
from
pytensor.tensor.basic
import
a
lloc
,
a
s_tensor_variable
from
pytensor.tensor.elemwise
import
DimShuffle
,
Elemwise
from
pytensor.tensor.math
import
add
,
exp
,
maximum
from
pytensor.tensor.rewriting.basic
import
register_specialize
...
...
@@ -239,6 +239,25 @@ class TestShapeRewriter:
# FIXME: This is not a good test.
f
([[
1
,
2
],
[
2
,
3
]])
def
test_shape_of_useless_alloc
(
self
):
"""Test that local_shape_to_shape_i does not create circular graph.
Regression test for #565
"""
alpha
=
vector
(
shape
=
(
None
,),
dtype
=
"float64"
)
channel
=
vector
(
shape
=
(
None
,),
dtype
=
"float64"
)
broadcast_channel
=
alloc
(
channel
,
maximum
(
shape
(
alpha
)[
0
],
shape
(
channel
)[
0
],
),
)
out
=
shape
(
broadcast_channel
)
fn
=
function
([
alpha
,
channel
],
out
)
assert
fn
([
1.0
,
2
,
3
],
[
1.0
,
2
,
3
])
==
(
3
,)
class
TestReshape
:
def
setup_method
(
self
):
...
...
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