提交 65d74e55 authored 作者: Olivier Delalleau's avatar Olivier Delalleau

Merged (hopefully properly this time)

...@@ -395,7 +395,7 @@ Windows V1 (Installing from Scratch) ...@@ -395,7 +395,7 @@ Windows V1 (Installing from Scratch)
You can keep the default install options (except for the installation directory). You can keep the default install options (except for the installation directory).
- Install Mercurial. You can download it - Install Mercurial. You can download it
`here <http://mercurial.selenic.com/downloads>`_. You may get either the command `here <http://mercurial.selenic.com/downloads>`__. You may get either the command
line Windows version or the TortoiseHG GUI version: it does not matter as line Windows version or the TortoiseHG GUI version: it does not matter as
far as installing Theano is concerned. far as installing Theano is concerned.
...@@ -451,7 +451,7 @@ compile GotoBLAS2 (ATLAS may work too, but was not tested, and is ...@@ -451,7 +451,7 @@ compile GotoBLAS2 (ATLAS may work too, but was not tested, and is
usually reported to be slower and more difficult to compile -- especially usually reported to be slower and more difficult to compile -- especially
on Windows). on Windows).
GotoBLAS2 can be downloaded GotoBLAS2 can be downloaded
`here <http://www.tacc.utexas.edu/tacc-projects/gotoblas2/downloads>`_ `here <http://www.tacc.utexas.edu/tacc-projects/gotoblas2/downloads>`__
after registering on the website (we tested v1.13). after registering on the website (we tested v1.13).
To compile it, you will also need to install MSYS and Perl, To compile it, you will also need to install MSYS and Perl,
as described below. as described below.
...@@ -539,8 +539,7 @@ Windows: Using the GPU ...@@ -539,8 +539,7 @@ Windows: Using the GPU
Please note that these are tentative instructions (we have not yet been able to Please note that these are tentative instructions (we have not yet been able to
get the GPU to work under Windows with Theano). get the GPU to work under Windows with Theano).
Please report your own successes / failures on the Please report your own successes / failures on the `theano-users`_ mailing list.
`theano-users <http://groups.google.com/group/theano-users>`_ mailing list.
Those are instructions for the 32-bit version of Python (the one that comes Those are instructions for the 32-bit version of Python (the one that comes
with Python(x,y) is 32-bit). with Python(x,y) is 32-bit).
......
...@@ -33,6 +33,9 @@ def _info(*msg): ...@@ -33,6 +33,9 @@ def _info(*msg):
def _warn(*msg): def _warn(*msg):
_logger.warn(' '.join(msg)) _logger.warn(' '.join(msg))
#This is needed as we will hide it later
python_complex=complex
def check_equal_numpy(x, y): def check_equal_numpy(x, y):
""" """
Returns True iff x and y are equal (checks the dtype and Returns True iff x and y are equal (checks the dtype and
...@@ -388,6 +391,20 @@ def get_constant_value(v): ...@@ -388,6 +391,20 @@ def get_constant_value(v):
ret = get_constant_value(ret) ret = get_constant_value(ret)
#join can cast implicitly its input in some case. #join can cast implicitly its input in some case.
return theano._asarray(ret, dtype=v.type.dtype) return theano._asarray(ret, dtype=v.type.dtype)
if (v.owner.inputs[0].owner and
isinstance(v.owner.inputs[0].owner.op,
theano.tensor.opt.MakeVector) and
# MakeVector normally accept only scalar as input.
# We put this check in case there is change in the future
all(var.ndim==0 for var in v.owner.inputs[0].owner.inputs)):
# The index list 'idx_list' should have length one
# since joining scalar variables results in a 1D vector.
assert len(v.owner.op.idx_list) == 1
ret = v.owner.inputs[0].owner.inputs[v.owner.op.idx_list[0]]
ret = get_constant_value(ret)
#MakeVector can cast implicitly its input in some case.
return theano._asarray(ret, dtype=v.type.dtype)
raise TypeError(v) raise TypeError(v)
...@@ -3269,11 +3286,18 @@ def stack(*tensors): ...@@ -3269,11 +3286,18 @@ def stack(*tensors):
raise Exception('theano.tensor.stack(*tensors) must have at least one parameter') raise Exception('theano.tensor.stack(*tensors) must have at least one parameter')
# If all tensors are scalars of the same type, call make_vector. # If all tensors are scalars of the same type, call make_vector.
# It makes the graph simpler, by not adding DimShuffles and Rebroadcasts # It makes the graph simpler, by not adding DimShuffles and Rebroadcasts
if numpy.all([isinstance(t, Variable) and\ if isinstance(tensors[0], (numpy.number, float, int, python_complex)):
isinstance(t.type, TensorType) and\ tensors=list(tensors)
t.ndim==0 and t.type==tensors[0].type\ tensors[0]=as_tensor_variable(tensors[0])
if numpy.all([isinstance(t, (numpy.number, float, int, python_complex))#in case their is direct int
or (isinstance(t, Variable) and
isinstance(t.type, TensorType) and
t.ndim==0 and
t.type.__class__==tensors[0].type.__class__)
for t in tensors]): for t in tensors]):
return theano.tensor.opt.MakeVector(scal.upcast(*[i.dtype for i in tensors]))(*tensors) tensors = map(as_tensor_variable,tensors)#in case their is direct int
dtype = scal.upcast(*[i.dtype for i in tensors])
return theano.tensor.opt.MakeVector(dtype)(*tensors)
return join(0, *[shape_padleft(t, 1) for t in tensors]) return join(0, *[shape_padleft(t, 1) for t in tensors])
@constructor @constructor
......
...@@ -1552,6 +1552,36 @@ class T_Join_and_Split(unittest.TestCase): ...@@ -1552,6 +1552,36 @@ class T_Join_and_Split(unittest.TestCase):
assert len([n for n in e if isinstance(n, Join)]) == 0 assert len([n for n in e if isinstance(n, Join)]) == 0
assert f.maker.env.outputs[0].dtype == config.floatX assert f.maker.env.outputs[0].dtype == config.floatX
def test_stack_scalar_make_vector_dtype(self):
'''Test that calling stack() on scalars instantiates MakeVector,
event when the scalar don't have the same dtype.'''
a = tensor.iscalar('a')
b = tensor.lscalar('b')
s = stack(a, b, a, b)
f = function([a,b], s)
val = f(1,2)
self.failUnless(numpy.all(val == [1,2,1,2]))
e = f.maker.env.toposort()
assert len([n for n in e if isinstance(n.op,opt.MakeVector)]) > 0
assert len([n for n in e if isinstance(n, Join)]) == 0
assert f.maker.env.outputs[0].dtype == 'int64'
def test_stack_scalar_make_vector_constant(self):
'''Test that calling stack() on scalars instantiates MakeVector,
event when the scalar are simple int type.'''
a = tensor.iscalar('a')
b = tensor.lscalar('b')
#test when the constant is the first element.
#The first element is used in a special way
s = stack(10,a,b, numpy.int8(3))
f = function([a,b], s)
val = f(1,2)
self.failUnless(numpy.all(val == [10,1,2,3]))
e = f.maker.env.toposort()
assert len([n for n in e if isinstance(n.op,opt.MakeVector)]) > 0
assert len([n for n in e if isinstance(n, Join)]) == 0
assert f.maker.env.outputs[0].dtype == 'int64'
def test_join_vector(self): def test_join_vector(self):
a = as_tensor_variable(numpy.array([1, 2, 3])) a = as_tensor_variable(numpy.array([1, 2, 3]))
b = as_tensor_variable(numpy.array([7, 8, 9])) b = as_tensor_variable(numpy.array([7, 8, 9]))
...@@ -3440,6 +3470,28 @@ def test_dimshuffle_duplicate(): ...@@ -3440,6 +3470,28 @@ def test_dimshuffle_duplicate():
assert success assert success
class T_get_constant_value(unittest.TestCase):
def test_get_constant_value(self):
a = tensor.stack(1,2,3)
assert get_constant_value(a[0])==1
assert get_constant_value(a[1])==2
assert get_constant_value(a[2])==3
b = tensor.iscalar()
a = tensor.stack(b,2,3)
self.assertRaises(TypeError, get_constant_value, a[0])
assert get_constant_value(a[1])==2
assert get_constant_value(a[2])==3
#For now get_constant_value got throught only MakeVector and Join of scalar.
v = tensor.ivector()
a = tensor.stack(v,2,3)
self.assertRaises(TypeError, get_constant_value, a[0])
self.assertRaises(TypeError, get_constant_value, a[1])
self.assertRaises(TypeError, get_constant_value, a[2])
if __name__ == '__main__': if __name__ == '__main__':
if 1: if 1:
unittest.main() unittest.main()
...@@ -3449,5 +3501,3 @@ if __name__ == '__main__': ...@@ -3449,5 +3501,3 @@ if __name__ == '__main__':
suite = unittest.TestLoader() suite = unittest.TestLoader()
suite = suite.loadTestsFromTestCase(testcase) suite = suite.loadTestsFromTestCase(testcase)
unittest.TextTestRunner(verbosity=2).run(suite) unittest.TextTestRunner(verbosity=2).run(suite)
...@@ -316,20 +316,20 @@ def makeSharedTester(shared_constructor_, ...@@ -316,20 +316,20 @@ def makeSharedTester(shared_constructor_,
#Test that we forward the input #Test that we forward the input
specify_shape_fct = theano.function([],x1_specify_shape) specify_shape_fct = theano.function([],x1_specify_shape)
theano.printing.debugprint(specify_shape_fct) #theano.printing.debugprint(specify_shape_fct)
assert numpy.all(self.ref_fct(specify_shape_fct()) assert numpy.all(self.ref_fct(specify_shape_fct())
==self.ref_fct(x1_2)) ==self.ref_fct(x1_2))
topo_specify = specify_shape_fct.maker.env.toposort() topo_specify = specify_shape_fct.maker.env.toposort()
if theano.config.mode!='FAST_COMPILE': if theano.config.mode!='FAST_COMPILE':
assert len(topo_specify)==6 assert len(topo_specify)==4
#Test that we put the shape info into the graph #Test that we put the shape info into the graph
shape_constant_fct = theano.function([],x1_specify_shape.shape) shape_constant_fct = theano.function([],x1_specify_shape.shape)
theano.printing.debugprint(shape_constant_fct) #theano.printing.debugprint(shape_constant_fct)
assert numpy.all(shape_constant_fct()==shape_op_fct()) assert numpy.all(shape_constant_fct()==shape_op_fct())
topo_cst = shape_constant_fct.maker.env.toposort() topo_cst = shape_constant_fct.maker.env.toposort()
if theano.config.mode!='FAST_COMPILE': if theano.config.mode!='FAST_COMPILE':
assert len(topo_cst)==6 assert len(topo_cst)==2
#Test that we can replace with values of the different shape #Test that we can replace with values of the different shape
# but that will raise an error in some case, but not all # but that will raise an error in some case, but not all
......
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