Mercurial > pylearn
changeset 670:63bcc7024378
removed Member calls from logistic regression
| author | James Bergstra <bergstrj@iro.umontreal.ca> |
|---|---|
| date | Mon, 30 Mar 2009 16:15:24 -0400 |
| parents | d17ebf9ac8c0 |
| children | 9e62fd6b6677 |
| files | pylearn/__init__.py pylearn/algorithms/logistic_regression.py pylearn/io/tests/test_filetensor.py |
| diffstat | 3 files changed, 14 insertions(+), 12 deletions(-) [+] |
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--- a/pylearn/__init__.py Mon Mar 30 16:00:29 2009 -0400 +++ b/pylearn/__init__.py Mon Mar 30 16:15:24 2009 -0400 @@ -1,4 +1,4 @@ -import exceptions +#import exceptions def __src_version__(): #todo - this is vulnerable to the bug in theano ticket #160
--- a/pylearn/algorithms/logistic_regression.py Mon Mar 30 16:00:29 2009 -0400 +++ b/pylearn/algorithms/logistic_regression.py Mon Mar 30 16:15:24 2009 -0400 @@ -36,15 +36,15 @@ self.input = input if input is not None else T.matrix() self.target = target if target is not None else T.lvector() - self.w = w if w is not None else module.Member(T.dmatrix()) - self.b = b if b is not None else module.Member(T.dvector()) + self.w = w if w is not None else (T.dmatrix()) + self.b = b if b is not None else (T.dvector()) #the params of the model are the ones we fit to the data self.params = [p for p in [self.w, self.b] if p.owner is None] #the hyper-parameters of the model are not fit to the data - self.l2 = l2 if l2 is not None else module.Member(T.dscalar()) - self.l1 = l1 if l1 is not None else module.Member(T.dscalar()) + self.l2 = l2 if l2 is not None else (T.dscalar()) + self.l1 = l1 if l1 is not None else (T.dscalar()) #here we actually build the model self.linear_output = T.dot(self.input, self.w) + self.b @@ -163,12 +163,12 @@ def __init__(self, input=None, targ=None, w=None, b=None, lr=None, regularize=False): super(LogReg2, self).__init__() #boilerplate - self.input = module.Member(input) if input is not None else T.matrix('input') - self.targ = module.Member(targ) if targ is not None else T.lcol() + self.input = (input) if input is not None else T.matrix('input') + self.targ = (targ) if targ is not None else T.lcol() - self.w = module.Member(w) if w is not None else module.Member(T.dmatrix()) - self.b = module.Member(b) if b is not None else module.Member(T.dvector()) - self.lr = module.Member(lr) if lr is not None else module.Member(T.dscalar()) + self.w = (w) if w is not None else (T.dmatrix()) + self.b = (b) if b is not None else (T.dvector()) + self.lr = (lr) if lr is not None else (T.dscalar()) self.params = [p for p in [self.w, self.b] if p.owner is None] @@ -254,8 +254,8 @@ self.n_in = n_in self.n_out = n_out - self.w = w if w is not None else module.Member(T.dmatrix()) - self.b = b if b is not None else module.Member(T.dvector()) + self.w = w if w is not None else (T.dmatrix()) + self.b = b if b is not None else (T.dvector()) def _instance_initialize(self, obj): obj.w = N.zeros((self.n_in, self.n_out))