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testgroup
pytensor
Commits
a1e290b7
提交
a1e290b7
authored
7月 13, 2015
作者:
Frédéric Bastien
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差异文件
Merge pull request #3128 from harlouci/flake8_sparse
Flake8 sparse
上级
11a78c73
21887b7d
全部展开
隐藏空白字符变更
内嵌
并排
正在显示
4 个修改的文件
包含
43 行增加
和
40 行删除
+43
-40
basic.py
theano/sparse/basic.py
+0
-0
opt.py
theano/sparse/opt.py
+32
-26
type.py
theano/sparse/type.py
+11
-11
test_flake8.py
theano/tests/test_flake8.py
+0
-3
没有找到文件。
theano/sparse/basic.py
浏览文件 @
a1e290b7
差异被折叠。
点击展开。
theano/sparse/opt.py
浏览文件 @
a1e290b7
...
...
@@ -12,6 +12,7 @@ from theano.sparse import (CSC, CSR, csm_properties,
from
theano.sparse
import
basic
as
sparse
_is_sparse_variable
=
sparse
.
_is_sparse_variable
_is_dense
=
sparse
.
_is_dense
# This is tested in tests/test_opt.py:test_local_csm_properties_csm
...
...
@@ -47,10 +48,11 @@ def local_inplace_remove0(node):
return
[
new_node
]
return
False
theano
.
compile
.
optdb
.
register
(
'local_inplace_remove0'
,
gof
.
TopoOptimizer
(
local_inplace_remove0
,
failure_callback
=
gof
.
TopoOptimizer
.
warn_inplace
),
60
,
'fast_run'
,
'inplace'
)
theano
.
compile
.
optdb
.
register
(
'local_inplace_remove0'
,
gof
.
TopoOptimizer
(
local_inplace_remove0
,
failure_callback
=
gof
.
TopoOptimizer
.
warn_inplace
),
60
,
'fast_run'
,
'inplace'
)
class
AddSD_ccode
(
gof
.
op
.
Op
):
...
...
@@ -174,10 +176,11 @@ def local_inplace_addsd_ccode(node):
inplace
=
True
)(
*
node
.
inputs
)
return
[
new_node
]
return
False
theano
.
compile
.
optdb
.
register
(
'local_inplace_addsd_ccode'
,
gof
.
TopoOptimizer
(
local_inplace_addsd_ccode
,
failure_callback
=
gof
.
TopoOptimizer
.
warn_inplace
),
60
,
'fast_run'
,
'inplace'
)
theano
.
compile
.
optdb
.
register
(
'local_inplace_addsd_ccode'
,
gof
.
TopoOptimizer
(
local_inplace_addsd_ccode
,
failure_callback
=
gof
.
TopoOptimizer
.
warn_inplace
),
60
,
'fast_run'
,
'inplace'
)
@register_canonicalize
(
"fast_compile"
)
...
...
@@ -234,16 +237,17 @@ class StructuredDotCSC(gof.Op):
def
make_node
(
self
,
a_val
,
a_ind
,
a_ptr
,
a_nrows
,
b
):
dtype_out
=
scalar
.
upcast
(
a_val
.
type
.
dtype
,
b
.
type
.
dtype
)
r
=
gof
.
Apply
(
self
,
[
a_val
,
a_ind
,
a_ptr
,
a_nrows
,
b
],
[
tensor
.
tensor
(
dtype_out
,
(
False
,
b
.
type
.
broadcastable
[
1
]))])
[
tensor
.
tensor
(
dtype_out
,
(
False
,
b
.
type
.
broadcastable
[
1
]))])
return
r
def
perform
(
self
,
node
,
inputs
,
outputs
):
(
a_val
,
a_ind
,
a_ptr
,
a_nrows
,
b
)
=
inputs
(
out
,)
=
outputs
a
=
scipy
.
sparse
.
csc_matrix
((
a_val
,
a_ind
,
a_ptr
),
(
a_nrows
,
b
.
shape
[
0
]),
copy
=
False
)
#out[0] = a.dot(b)
(
a_nrows
,
b
.
shape
[
0
]),
copy
=
False
)
#
out[0] = a.dot(b)
out
[
0
]
=
theano
.
_asarray
(
a
*
b
,
dtype
=
node
.
outputs
[
0
]
.
type
.
dtype
)
assert
_is_dense
(
out
[
0
])
# scipy 0.7 automatically converts to dense
...
...
@@ -427,17 +431,18 @@ class StructuredDotCSR(gof.Op):
def
make_node
(
self
,
a_val
,
a_ind
,
a_ptr
,
b
):
self
.
dtype_out
=
scalar
.
upcast
(
a_val
.
type
.
dtype
,
b
.
type
.
dtype
)
r
=
gof
.
Apply
(
self
,
[
a_val
,
a_ind
,
a_ptr
,
b
],
[
tensor
.
tensor
(
self
.
dtype_out
,
(
False
,
b
.
type
.
broadcastable
[
1
]))])
[
tensor
.
tensor
(
self
.
dtype_out
,
(
False
,
b
.
type
.
broadcastable
[
1
]))])
return
r
def
perform
(
self
,
node
,
inputs
,
outputs
):
(
a_val
,
a_ind
,
a_ptr
,
b
)
=
inputs
(
out
,)
=
outputs
a
=
scipy
.
sparse
.
csr_matrix
((
a_val
,
a_ind
,
a_ptr
),
(
len
(
a_ptr
)
-
1
,
b
.
shape
[
0
]),
copy
=
True
)
# use view_map before setting this to False
#out[0] = a.dot(b)
a
=
scipy
.
sparse
.
csr_matrix
(
(
a_val
,
a_ind
,
a_ptr
),
(
len
(
a_ptr
)
-
1
,
b
.
shape
[
0
]),
copy
=
True
)
# use view_map before setting this to False
# out[0] = a.dot(b)
out
[
0
]
=
a
*
b
# scipy 0.7 automatically converts to dense, but not .6 sometimes
assert
_is_dense
(
out
[
0
])
...
...
@@ -634,7 +639,7 @@ class UsmmCscDense(gof.Op):
assert
z
.
ndim
==
2
dtype_out
=
scalar
.
upcast
(
alpha
.
type
.
dtype
,
x_val
.
type
.
dtype
,
y
.
type
.
dtype
,
z
.
type
.
dtype
)
y
.
type
.
dtype
,
z
.
type
.
dtype
)
if
dtype_out
not
in
(
'float32'
,
'float64'
):
raise
NotImplementedError
(
'only float types are supported in '
...
...
@@ -653,8 +658,9 @@ class UsmmCscDense(gof.Op):
if
dtype_out
!=
z
.
type
.
dtype
:
z
=
tensor
.
cast
(
z
,
dtype_out
)
r
=
gof
.
Apply
(
self
,
[
alpha
,
x_val
,
x_ind
,
x_ptr
,
x_nrows
,
y
,
z
],
[
tensor
.
tensor
(
dtype_out
,
(
False
,
y
.
type
.
broadcastable
[
1
]))])
r
=
gof
.
Apply
(
self
,
[
alpha
,
x_val
,
x_ind
,
x_ptr
,
x_nrows
,
y
,
z
],
[
tensor
.
tensor
(
dtype_out
,
(
False
,
y
.
type
.
broadcastable
[
1
]))])
return
r
def
c_support_code
(
self
):
...
...
@@ -841,7 +847,7 @@ local_usmm = gof.opt.PatternSub(
{
'pattern'
:
'alpha'
,
'constraint'
:
lambda
expr
:
(
numpy
.
all
(
expr
.
type
.
broadcastable
)
and
theano
.
config
.
blas
.
ldflags
)},
(
sparse
.
_dot
,
'x'
,
'y'
))),
(
sparse
.
_dot
,
'x'
,
'y'
))),
(
usmm
,
(
theano
.
tensor
.
neg
,
'alpha'
),
'x'
,
'y'
,
'z'
))
register_specialize
(
local_usmm
,
name
=
"local_usmm"
)
...
...
@@ -896,7 +902,7 @@ class CSMGradC(gof.Op):
def
make_node
(
self
,
a_val
,
a_ind
,
a_ptr
,
a_dim
,
b_val
,
b_ind
,
b_ptr
,
b_dim
):
return
gof
.
Apply
(
self
,
[
a_val
,
a_ind
,
a_ptr
,
a_dim
,
b_val
,
b_ind
,
b_ptr
,
b_dim
],
[
b_val
.
type
()])
b_val
,
b_ind
,
b_ptr
,
b_dim
],
[
b_val
.
type
()])
def
c_code
(
self
,
node
,
name
,
inputs
,
outputs
,
sub
):
# retrieve dtype number
...
...
@@ -1019,7 +1025,7 @@ def local_csm_grad_c(node):
return
[
csm_grad_c
(
*
node
.
inputs
)]
return
False
# DISABLED AS IT IS BROKEN FOR UNSORTED INDICES!
#register_specialize(local_csm_grad_c, 'cxx_only')
#
register_specialize(local_csm_grad_c, 'cxx_only')
class
MulSDCSC
(
gof
.
Op
):
...
...
@@ -1572,7 +1578,7 @@ def local_structured_add_s_v(node):
x
,
y
=
node
.
inputs
x_is_sparse_variable
=
_is_sparse_variable
(
x
)
#y_is_sparse_variable = _is_sparse_variable(y)
#
y_is_sparse_variable = _is_sparse_variable(y)
if
x_is_sparse_variable
:
svar
=
x
...
...
@@ -1840,7 +1846,7 @@ def local_sampling_dot_csr(node):
p_data
,
p_ind
,
p_ptr
,
p_shape
=
sparse
.
csm_properties
(
p
)
z_data
,
z_ind
,
z_ptr
=
sampling_dot_csr
(
x
,
y
,
p_data
,
p_ind
,
p_ptr
,
p_shape
[
1
])
p_ind
,
p_ptr
,
p_shape
[
1
])
return
[
sparse
.
CSR
(
z_data
,
z_ind
,
z_ptr
,
p_shape
)]
return
False
...
...
theano/sparse/type.py
浏览文件 @
a1e290b7
...
...
@@ -100,8 +100,8 @@ class SparseType(gof.Type):
a
,
b
=
b
,
a
if
_is_sparse
(
a
)
and
isinstance
(
b
,
numpy
.
ndarray
):
if
(
numpy
.
may_share_memory
(
a
.
data
,
b
)
or
numpy
.
may_share_memory
(
a
.
indices
,
b
)
or
numpy
.
may_share_memory
(
a
.
indptr
,
b
)):
numpy
.
may_share_memory
(
a
.
indices
,
b
)
or
numpy
.
may_share_memory
(
a
.
indptr
,
b
)):
# currently we can't share memory with a.shape as it is a tuple
return
True
return
False
...
...
@@ -143,8 +143,8 @@ class SparseType(gof.Type):
# we definitely do not want to be doing this un-necessarily during
# a FAST_RUN computation..
return
scipy
.
sparse
.
issparse
(
a
)
\
and
scipy
.
sparse
.
issparse
(
b
)
\
and
abs
(
a
-
b
)
.
sum
()
==
0.0
and
scipy
.
sparse
.
issparse
(
b
)
\
and
abs
(
a
-
b
)
.
sum
()
==
0.0
def
is_valid_value
(
self
,
a
):
return
scipy
.
sparse
.
issparse
(
a
)
and
(
a
.
format
==
self
.
format
)
...
...
@@ -162,10 +162,10 @@ class SparseType(gof.Type):
# Register SparseType's C code for ViewOp.
theano
.
compile
.
register_view_op_c_code
(
SparseType
,
"""
Py_XDECREF(
%(oname)
s);
%(oname)
s =
%(iname)
s;
Py_XINCREF(
%(oname)
s);
"""
,
1
)
SparseType
,
"""
Py_XDECREF(
%(oname)
s);
%(oname)
s =
%(iname)
s;
Py_XINCREF(
%(oname)
s);
"""
,
1
)
theano/tests/test_flake8.py
浏览文件 @
a1e290b7
...
...
@@ -228,10 +228,7 @@ whitelist_flake8 = [
"misc/tests/test_pycuda_example.py"
,
"misc/hooks/reindent.py"
,
"misc/hooks/check_whitespace.py"
,
"sparse/type.py"
,
"sparse/__init__.py"
,
"sparse/opt.py"
,
"sparse/basic.py"
,
"sparse/tests/test_utils.py"
,
"sparse/tests/test_opt.py"
,
"sparse/tests/test_basic.py"
,
...
...
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