提交 a7f94e0d authored 作者: nouiz's avatar nouiz

Merge pull request #829 from lamblin/fix_profile_py24

Fix test failure involving ProfileMode with python 2.4 NEWS.txt: fix python 2.4 problem with 1 tests (PL)
...@@ -1560,7 +1560,7 @@ class _Linker(gof.link.LocalLinker): ...@@ -1560,7 +1560,7 @@ class _Linker(gof.link.LocalLinker):
no_recycling = [] no_recycling = []
if self.fgraph is not None and self.fgraph is not fgraph: if self.fgraph is not None and self.fgraph is not fgraph:
assert type(self) is _Linker assert type(self) is _Linker
return type(self)(self.fgraph, self.maker).accept(fgraph, no_recycling) return type(self)(maker=self.maker).accept(fgraph, no_recycling)
self.fgraph = fgraph self.fgraph = fgraph
self.no_recycling = no_recycling self.no_recycling = no_recycling
return self return self
......
...@@ -328,7 +328,7 @@ class Mode(object): ...@@ -328,7 +328,7 @@ class Mode(object):
self.linker_time = 0 self.linker_time = 0
def __str__(self): def __str__(self):
return "Mode(linker = %s, optimizer = %s)" % ( return "%s(linker = %s, optimizer = %s)" % (self.__class__.__name__,
self.provided_linker, self.provided_optimizer) self.provided_linker, self.provided_optimizer)
def __get_optimizer(self): def __get_optimizer(self):
......
""" """
Test compilation modes Test compilation modes
""" """
import copy
import unittest import unittest
import theano import theano
...@@ -25,7 +26,6 @@ class T_bunch_of_modes(unittest.TestCase): ...@@ -25,7 +26,6 @@ class T_bunch_of_modes(unittest.TestCase):
modes = predef_modes + [Mode(linker, 'fast_run') for linker in linkers] modes = predef_modes + [Mode(linker, 'fast_run') for linker in linkers]
for mode in modes: for mode in modes:
x = T.matrix() x = T.matrix()
y = T.vector() y = T.vector()
f = theano.function([x, y], x + y, mode=mode) f = theano.function([x, y], x + y, mode=mode)
...@@ -33,6 +33,7 @@ class T_bunch_of_modes(unittest.TestCase): ...@@ -33,6 +33,7 @@ class T_bunch_of_modes(unittest.TestCase):
f([[1, 2], [3, 4]], [5, 6]) f([[1, 2], [3, 4]], [5, 6])
linker_classes_involved.append(f.maker.mode.linker.__class__) linker_classes_involved.append(f.maker.mode.linker.__class__)
#print 'MODE:', mode, f.maker.mode.linker, 'stop' #print 'MODE:', mode, f.maker.mode.linker, 'stop'
# regression check: # regression check:
# there should be # there should be
# - VM_Linker # - VM_Linker
...@@ -42,5 +43,26 @@ class T_bunch_of_modes(unittest.TestCase): ...@@ -42,5 +43,26 @@ class T_bunch_of_modes(unittest.TestCase):
# - DebugMode's Linker (DEBUG_MODE) # - DebugMode's Linker (DEBUG_MODE)
assert 5 == len(set(linker_classes_involved)) assert 5 == len(set(linker_classes_involved))
class T_ProfileMode_WrapLinker(unittest.TestCase):
def test_1(self):
# First, compile a function with a new ProfileMode() object
# No need to call that function
x = T.matrix()
mode = ProfileMode()
theano.function([x], x * 2, mode=mode)
# Then, build a mode with the same linker, and a modified optimizer
default_mode = theano.compile.mode.get_default_mode()
modified_mode = default_mode.including('specialize')
# The following line used to fail, with Python 2.4, in July 2012,
# because an fgraph was associated to the default linker
copy.deepcopy(modified_mode)
# More straightforward test
assert theano.compile.mode.get_default_mode().linker.fgraph is None
if __name__ == '__main__': if __name__ == '__main__':
unittest.main() unittest.main()
...@@ -1408,8 +1408,11 @@ class OpWiseCLinker(link.LocalLinker): ...@@ -1408,8 +1408,11 @@ class OpWiseCLinker(link.LocalLinker):
if no_recycling is None: if no_recycling is None:
no_recycling = [] no_recycling = []
if self.fgraph is not None and self.fgraph is not fgraph: if self.fgraph is not None and self.fgraph is not fgraph:
return type(self)(self.fallback_on_perform).accept(fgraph, return type(self)(
no_recycling) fallback_on_perform=self.fallback_on_perform,
allow_gc=self.allow_gc,
nice_errors=self.nice_errors
).accept(fgraph, no_recycling)
#raise Exception("Cannot accept from a Linker that is #raise Exception("Cannot accept from a Linker that is
#already tied to another FunctionGraph.") #already tied to another FunctionGraph.")
self.fgraph = fgraph self.fgraph = fgraph
......
...@@ -433,7 +433,7 @@ class PerformLinker(LocalLinker): ...@@ -433,7 +433,7 @@ class PerformLinker(LocalLinker):
if no_recycling is None: if no_recycling is None:
no_recycling = [] no_recycling = []
if self.fgraph is not None and self.fgraph is not fgraph: if self.fgraph is not None and self.fgraph is not fgraph:
return type(self)().accept(fgraph, no_recycling) return type(self)(allow_gc=self.allow_gc).accept(fgraph, no_recycling)
#raise Exception("Cannot accept from a Linker that is already tied to another FunctionGraph.") #raise Exception("Cannot accept from a Linker that is already tied to another FunctionGraph.")
self.fgraph = fgraph self.fgraph = fgraph
self.no_recycling = no_recycling self.no_recycling = no_recycling
...@@ -553,6 +553,22 @@ class WrapLinker(Linker): ...@@ -553,6 +553,22 @@ class WrapLinker(Linker):
self.linkers = linkers self.linkers = linkers
self.wrapper = wrapper self.wrapper = wrapper
def __copy__(self):
"""
Shallow copy of a WrapLinker.
@returns: A copy of self, where each of the linkers in self.linkers
have been shallow-copied.
It is useful because in FunctionMaker, copy.copy is called on the
Mode's linker, so that it is not modified inplace when linker.accept()
is called. In this case, we want the wrapped linkers to be copied too.
"""
other = self.__class__(
linkers=[copy(l) for l in self.linkers],
wrapper=self.wrapper)
return other
def accept(self, fgraph, no_recycling=None): def accept(self, fgraph, no_recycling=None):
""" """
@type fgraph: gof.FunctionGraph @type fgraph: gof.FunctionGraph
......
...@@ -9,6 +9,7 @@ if there exists an assignment to all unification variables such that ...@@ -9,6 +9,7 @@ if there exists an assignment to all unification variables such that
""" """
from copy import copy from copy import copy
from python25 import partial
from utils import * from utils import *
......
...@@ -179,17 +179,6 @@ def from_return_values(values): ...@@ -179,17 +179,6 @@ def from_return_values(values):
return [values] return [values]
def partial(func, *args, **keywords):
def newfunc(*fargs, **fkeywords):
newkeywords = keywords.copy()
newkeywords.update(fkeywords)
return func(*(args + fargs), **newkeywords)
newfunc.func = func
newfunc.args = args
newfunc.keywords = keywords
return newfunc
class ClsInit(type): class ClsInit(type):
"""Class initializer for L{Op} subclasses""" """Class initializer for L{Op} subclasses"""
def __init__(cls, name, bases, dct): def __init__(cls, name, bases, dct):
......
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