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testgroup
pytensor
Commits
0039353e
提交
0039353e
authored
7月 23, 2009
作者:
James Bergstra
浏览文件
操作
浏览文件
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差异文件
test_elemwise4 just passed
上级
ff24c985
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
37 行增加
和
5 行删除
+37
-5
opt.py
opt.py
+36
-4
test_basic_ops.py
tests/test_basic_ops.py
+1
-1
没有找到文件。
opt.py
浏览文件 @
0039353e
...
@@ -18,17 +18,33 @@ tensor.opt.register_specialize(local_host_gpu_host, 'gpu')
...
@@ -18,17 +18,33 @@ tensor.opt.register_specialize(local_host_gpu_host, 'gpu')
@gof.local_optimizer
([])
@gof.local_optimizer
([])
def
local_gpu_elemwise
(
node
):
def
local_gpu_elemwise
_0
(
node
):
if
isinstance
(
node
.
op
,
tensor
.
Elemwise
):
if
isinstance
(
node
.
op
,
tensor
.
Elemwise
):
if
any
(
hasattr
(
i
.
owner
,
'op'
)
and
isinstance
(
i
.
owner
.
op
,
HostFromGpu
)
for
i
in
node
.
inputs
):
if
any
(
hasattr
(
i
.
owner
,
'op'
)
and
isinstance
(
i
.
owner
.
op
,
HostFromGpu
)
for
i
in
node
.
inputs
):
# move the add to a GpuAdd
# move the add to a GpuAdd
new_op
=
GpuElemwise
(
node
.
op
.
scalar_op
,
node
.
op
.
inplace_pattern
)
new_op
=
GpuElemwise
(
node
.
op
.
scalar_op
,
node
.
op
.
inplace_pattern
)
return
[
host_from_gpu
(
new_op
(
*
(
gpu_from_host
(
i
)
for
i
in
node
.
inputs
)))]
return
[
host_from_gpu
(
new_op
(
*
(
gpu_from_host
(
i
)
for
i
in
node
.
inputs
)))]
return
False
return
False
tensor
.
opt
.
register_specialize
(
local_gpu_elemwise
,
'gpu'
)
tensor
.
opt
.
register_specialize
(
local_gpu_elemwise_0
,
'gpu'
)
@gof.local_optimizer
([])
def
local_gpu_elemwise_1
(
node
):
"""
gpu_from_host(Elemwise)) -> GpuElemwise(gpu_from_host(...))
"""
if
node
.
op
==
gpu_from_host
:
host_i
,
=
node
.
inputs
if
host_i
.
owner
and
isinstance
(
host_i
.
owner
.
op
,
tensor
.
Elemwise
)
and
len
(
host_i
.
clients
)
==
1
:
elemwise_node
=
host_i
.
owner
new_op
=
GpuElemwise
(
elemwise_node
.
op
.
scalar_op
,
elemwise_node
.
op
.
inplace_pattern
)
return
[
new_op
(
*
(
gpu_from_host
(
i
)
for
i
in
elemwise_node
.
inputs
))]
return
False
tensor
.
opt
.
register_specialize
(
local_gpu_elemwise_1
,
'gpu'
)
@gof.local_optimizer
([])
@gof.local_optimizer
([])
def
local_gpu_dimshuffle
(
node
):
def
local_gpu_dimshuffle_0
(
node
):
"""
dimshuffle(host_from_gpu()) -> host_from_gpu(gpu_dimshuffle)
"""
if
isinstance
(
node
.
op
,
tensor
.
DimShuffle
):
if
isinstance
(
node
.
op
,
tensor
.
DimShuffle
):
input
,
=
node
.
inputs
input
,
=
node
.
inputs
if
input
.
owner
and
isinstance
(
input
.
owner
.
op
,
HostFromGpu
):
if
input
.
owner
and
isinstance
(
input
.
owner
.
op
,
HostFromGpu
):
...
@@ -40,4 +56,20 @@ def local_gpu_dimshuffle(node):
...
@@ -40,4 +56,20 @@ def local_gpu_dimshuffle(node):
else
:
else
:
return
[
host_from_gpu
(
new_op
(
gpu_from_host
(
tensor
.
tensor_copy
(
input
))))]
return
[
host_from_gpu
(
new_op
(
gpu_from_host
(
tensor
.
tensor_copy
(
input
))))]
return
False
return
False
tensor
.
opt
.
register_specialize
(
local_gpu_dimshuffle
,
'gpu'
)
tensor
.
opt
.
register_specialize
(
local_gpu_dimshuffle_0
,
'gpu'
)
@gof.local_optimizer
([])
def
local_gpu_dimshuffle_1
(
node
):
"""
gpu_from_host(dimshuffle) -> gpu_dimshuffle(gpu_from_host)
"""
if
node
.
op
==
gpu_from_host
:
host_input
=
node
.
inputs
[
0
]
if
host_input
.
owner
and
isinstance
(
host_input
.
owner
.
op
,
tensor
.
DimShuffle
):
dimshuffle_node
=
host_input
.
owner
new_op
=
GpuDimShuffle
(
dimshuffle_node
.
op
.
input_broadcastable
,
dimshuffle_node
.
op
.
new_order
)
return
[
new_op
(
gpu_from_host
(
dimshuffle_node
.
inputs
[
0
]))]
return
False
tensor
.
opt
.
register_specialize
(
local_gpu_dimshuffle_1
,
'gpu'
)
tests/test_basic_ops.py
浏览文件 @
0039353e
...
@@ -110,7 +110,7 @@ def test_elemwise4():
...
@@ -110,7 +110,7 @@ def test_elemwise4():
a
=
tcn
.
shared_constructor
(
numpy
.
random
.
rand
(
*
shape
),
'a'
)
a
=
tcn
.
shared_constructor
(
numpy
.
random
.
rand
(
*
shape
),
'a'
)
b
=
tensor
.
fvector
()
b
=
tensor
.
fvector
()
c
=
tensor
.
fvector
()
c
=
tensor
.
fvector
()
f
=
pfunc
([
b
,
c
],
[],
updates
=
[(
a
,
(
a
+
b
.
dimshuffle
(
'x'
,
0
)
*
x
.
dimshuffle
(
0
,
'x'
)))])
f
=
pfunc
([
b
,
c
],
[],
updates
=
[(
a
,
(
a
+
b
.
dimshuffle
(
'x'
,
0
)
*
c
.
dimshuffle
(
0
,
'x'
)))])
has_elemwise
=
False
has_elemwise
=
False
for
i
,
node
in
enumerate
(
f
.
maker
.
env
.
toposort
()):
for
i
,
node
in
enumerate
(
f
.
maker
.
env
.
toposort
()):
print
>>
sys
.
stderr
,
i
,
node
print
>>
sys
.
stderr
,
i
,
node
...
...
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