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comparison pylearn/algorithms/mcRBM.py @ 1499:f82b80c841b2

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Remove deprecation warning.
author Frederic Bastien <nouiz@nouiz.org>
date Fri, 09 Sep 2011 10:49:54 -0400
parents 54b2268db0d7
children 517f4c02dde9
comparison
equal deleted inserted replaced
1498:0f326860210e 1499:f82b80c841b2
373 For an RBM made from shared variables, this will return an integer, 373 For an RBM made from shared variables, this will return an integer,
374 for a purely symbolic RBM this will return a theano expression. 374 for a purely symbolic RBM this will return a theano expression.
375 375
376 """ 376 """
377 try: 377 try:
378 return self.W.value.shape[0] 378 return self.W.get_value(borrow=True, return_internal_type=True).shape[0]
379 except AttributeError: 379 except AttributeError:
380 return self.W.shape[0] 380 return self.W.shape[0]
381 381
382 def n_hidden_cov_units(self): 382 def n_hidden_cov_units(self):
383 """Return the number of hidden units for the covariance in this RBM 383 """Return the number of hidden units for the covariance in this RBM
385 For an RBM made from shared variables, this will return an integer, 385 For an RBM made from shared variables, this will return an integer,
386 for a purely symbolic RBM this will return a theano expression. 386 for a purely symbolic RBM this will return a theano expression.
387 387
388 """ 388 """
389 try: 389 try:
390 return self.U.value.shape[1] 390 return self.U.get_value(borrow=True, return_internal_type=True).shape[1]
391 except AttributeError: 391 except AttributeError:
392 return self.U.shape[1] 392 return self.U.shape[1]
393 393
394 def n_hidden_mean_units(self): 394 def n_hidden_mean_units(self):
395 """Return the number of hidden units for the mean in this RBM 395 """Return the number of hidden units for the mean in this RBM
397 For an RBM made from shared variables, this will return an integer, 397 For an RBM made from shared variables, this will return an integer,
398 for a purely symbolic RBM this will return a theano expression. 398 for a purely symbolic RBM this will return a theano expression.
399 399
400 """ 400 """
401 try: 401 try:
402 return self.W.value.shape[1] 402 return self.W.get_value(borrow=True, return_internal_type=True).shape[1]
403 except AttributeError: 403 except AttributeError:
404 return self.W.shape[1] 404 return self.W.shape[1]
405 405
406 def CD1_sampler(self, v, n_particles, n_visible=None, rng=8923984): 406 def CD1_sampler(self, v, n_particles, n_visible=None, rng=8923984):
407 """Return a symbolic negative-phase particle obtained by simulating the Hamiltonian 407 """Return a symbolic negative-phase particle obtained by simulating the Hamiltonian
578 For an RBM made from shared variables, this will return an integer, 578 For an RBM made from shared variables, this will return an integer,
579 for a purely symbolic RBM this will return a theano expression. 579 for a purely symbolic RBM this will return a theano expression.
580 580
581 """ 581 """
582 try: 582 try:
583 return self.P.value.shape[1] 583 return self.P.get_value(borrow=True, return_internal_type=True).shape[1]
584 except AttributeError: 584 except AttributeError:
585 return self.P.shape[1] 585 return self.P.shape[1]
586 586
587 @classmethod 587 @classmethod
588 def alloc(cls, n_I, n_K, n_J, *args, **kwargs): 588 def alloc(cls, n_I, n_K, n_J, *args, **kwargs):
667 else: 667 else:
668 p_lr = None 668 p_lr = None
669 rval = cls.alloc(rbm, visible_batch, batchsize, initial_lr_per_example, rng, l1_penalty, 669 rval = cls.alloc(rbm, visible_batch, batchsize, initial_lr_per_example, rng, l1_penalty,
670 l1_penalty_start, learn_rate_multipliers, lr_anneal_start, persistent_chains) 670 l1_penalty_start, learn_rate_multipliers, lr_anneal_start, persistent_chains)
671 671
672 rval.p_mask = sharedX((rbm.P.value!=0).astype('float32'), 'p_mask') 672 rval.p_mask = sharedX((rbm.P.get_value(borrow=True)!=0).astype('float32'), 'p_mask')
673 673
674 rval.p_lr = p_lr 674 rval.p_lr = p_lr
675 rval.p_training_start=p_training_start 675 rval.p_training_start=p_training_start
676 rval.p_training_lr=p_training_lr 676 rval.p_training_lr=p_training_lr
677 return rval 677 return rval