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pytensor
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cdddc7da
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cdddc7da
authored
8月 14, 2015
作者:
Iban Harlouchet
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差异文件
numpydoc for theano/compile/mode.py
上级
3ca1e9ab
隐藏空白字符变更
内嵌
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1 个修改的文件
包含
40 行增加
和
22 行删除
+40
-22
mode.py
theano/compile/mode.py
+40
-22
没有找到文件。
theano/compile/mode.py
浏览文件 @
cdddc7da
"""WRITEME
"""
WRITEME
"""
from
__future__
import
print_function
import
logging
...
...
@@ -34,8 +36,9 @@ AddConfigVar('optimizer_requiring',
def
check_equal
(
x
,
y
):
"""
Returns True iff x[0] and y[0] are equal (checks the dtype and
shape if x and y are numpy.ndarray instances). Used internally.
Returns True iff x[0] and y[0] are equal (checks the dtype and shape if x
and y are numpy.ndarray instances). Used internally.
"""
# I put the import here to allow using theano without scipy.
import
scipy.sparse
as
sp
...
...
@@ -125,17 +128,19 @@ def register_optimizer(name, opt):
class
AddDestroyHandler
(
gof
.
Optimizer
):
"""This optimizer performs two important functions:
"""
This optimizer performs two important functions:
1) It has a 'requirement' of the destroyhandler. This means that the fgraph
will include it as a feature for this optimization, and keep this feature
enabled for subsequent optimizations.
All optimizations that work inplace
enabled for subsequent optimizations. All optimizations that work inplace
on any of their inputs must run *after* this optimization to ensure that
the DestroyHandler has been included in the fgraph.
2) It tries to replace each output with an Op that purports to destroy it
(but it won't I promise). If this replacement succeeds it means that
there is a bug in theano. It should not be possible to destroy outputs.
(but it won't I promise). If this replacement succeeds it means that
there is a bug in theano. It should not be possible to destroy outputs.
"""
def
apply
(
self
,
fgraph
):
for
o
in
fgraph
.
outputs
:
...
...
@@ -157,11 +162,13 @@ class AddDestroyHandler(gof.Optimizer):
class
AddNoOutputFromInplace
(
gof
.
Optimizer
):
"""This optimizer adds to the fgraph a feature that will prevent outputs
"""
This optimizer adds to the fgraph a feature that will prevent outputs
of a fgraph to be created by performing inplace operations on intermediary
variables. This is useful when the outputs of the fgraph are preallocated
to prevent useless copying of the data. Currently, scan preallocates its
outputs
"""
def
add_requirements
(
self
,
fgraph
):
super
(
AddNoOutputFromInplace
,
self
)
.
add_requirements
(
fgraph
)
...
...
@@ -169,10 +176,12 @@ class AddNoOutputFromInplace(gof.Optimizer):
class
PrintCurrentFunctionGraph
(
gof
.
Optimizer
):
"""This optimizer is for debugging.
"""
This optimizer is for debugging.
Toss it into the optimization pipeline to see the state of things at any
given point.
"""
def
__init__
(
self
,
header
):
self
.
header
=
header
...
...
@@ -233,18 +242,23 @@ optdb.register('merge3', gof.MergeOptimizer(),
class
Mode
(
object
):
"""
The Mode represents a way to optimize and then link a computation
graph.
* optimizer -> a structure of type Optimizer. An Optimizer may
simplify the math, put similar computations together, improve
numerical stability and various other improvements.
* linker -> a structure of type Linker. A Linker decides which
implementations to use (C or Python, for example) and how to
string them together to perform the computation.
See predefined_linkers, predefined_optimizers and also
predefined_modes.
The Mode represents a way to optimize and then link a computation graph.
Parameters
----------
optimizer : a structure of type Optimizer
An Optimizer may simplify the math, put similar computations together,
improve numerical stability and various other improvements.
linker : a structure of type Linker
A Linker decides which implementations to use (C or Python, for example)
and how to string them together to perform the computation.
See Also
--------
predefined_linkers
predefined_optimizers
predefined_modes
"""
def
__init__
(
self
,
linker
=
None
,
optimizer
=
'default'
):
...
...
@@ -326,6 +340,7 @@ class Mode(object):
Keyword arguments can be provided for the linker,
in which case its `clone` method will be called with these
arguments.
"""
new_linker
=
self
.
linker
.
clone
(
**
link_kwargs
)
new_optimizer
=
self
.
provided_optimizer
...
...
@@ -412,7 +427,10 @@ def get_default_mode():
def
register_mode
(
name
,
mode
):
"""Add a `Mode` which can be referred to by `name` in `function`."""
"""
Add a `Mode` which can be referred to by `name` in `function`.
"""
if
name
in
predefined_modes
:
raise
ValueError
(
'Mode name already taken:
%
s'
%
name
)
predefined_modes
[
name
]
=
mode
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