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comparison pylearn/sandbox/scan_inputs_groups.py @ 770:742972b6906a

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scall optimisation to FillMissing.
author Frederic Bastien <bastienf@iro.umontreal.ca>
date Tue, 09 Jun 2009 21:39:50 -0400
parents bd95e8ea99d8
children 72730f38d1fb
comparison
equal deleted inserted replaced
769:0ff7ac3253b3 770:742972b6906a
605 def perform(self, node, (input, ), output_storage): 605 def perform(self, node, (input, ), output_storage):
606 out = output_storage[0] 606 out = output_storage[0]
607 out[0] = input.copy() 607 out[0] = input.copy()
608 out = out[0] 608 out = out[0]
609 mask = output_storage[1] 609 mask = output_storage[1]
610 mask[0] = numpy.ones(input.shape) 610
611 if mask[0] is None or mask[0].shape!=input.shape:
612 mask[0] = numpy.ones(input.shape)
613
611 mask = mask[0] 614 mask = mask[0]
612 if self.fill_with_is_array: 615 if self.fill_with_is_array:
613 ignore_k = len(out.shape) - len(self.fill_with.shape) 616 ignore_k = len(out.shape) - len(self.fill_with.shape)
614 assert ignore_k >= 0 617 assert ignore_k >= 0
615 for (idx, v) in numpy.ndenumerate(out): 618
616 if numpy.isnan(v): 619 if self.fill_with_is_array:
617 if self.fill_with_is_array: 620 for (idx, v) in numpy.ndenumerate(out):
621 if numpy.isnan(v):
618 out[idx] = self.fill_with[idx[ignore_k:]] 622 out[idx] = self.fill_with[idx[ignore_k:]]
619 else: 623 mask[idx] = 0
624 else:
625 for (idx, v) in numpy.ndenumerate(out):
626 if numpy.isnan(v):
620 out[idx] = self.fill_with 627 out[idx] = self.fill_with
621 mask[idx] = 0 628 mask[idx] = 0
622 629
623 def grad(self, inputs, (out_grad, mask_grad, )): 630 def grad(self, inputs, (out_grad, mask_grad, )):
624 return [out_grad] 631 return [out_grad]
625 632
626 fill_missing_with_zeros = FillMissing(0) 633 fill_missing_with_zeros = FillMissing(0)