(self)
Generator that can be used to iterate over this dataset.

        Yields:
            tuple, tuple: first tuple contains image features and empty input Tensor
                          second tuple contains list of reference sentences and
                          placeholder for mask.
Generator that can be used to iterate over this dataset.
Generator that can be used to iterate over this dataset .
def __iter__(self):
        """
        Generator that can be used to iterate over this dataset.

        Yields:
            tuple, tuple: first tuple contains image features and empty input Tensor
                          second tuple contains list of reference sentences and
                          placeholder for mask.
        """
        for batch_idx in xrange(self.nbatches):

            start = batch_idx * self.be.bsz
            end = (batch_idx + 1) * self.be.bsz

            image_batch = self.images[start:end, :].T.astype(np.float32, order='C')
            self.dev_image.set(image_batch)

            yield (self.dev_image, self.dev_X), (self.ref_sents[start:end], None)
def __iter__ ( self ) : for batch_idx in xrange ( self . nbatches ) : start = batch_idx * self . be . bsz end = ( batch_idx + 1 ) * self . be . bsz image_batch = self . images [ start : end , : ] . T . astype ( np . float32 , order = 'C' ) self . dev_image . set ( image_batch ) yield ( self . dev_image , self . dev_X ) , ( self . ref_sents [ start : end ] , None )