Python operator.__or__方法代碼示例

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def __or__(self, other):                                        
        '''
        Take a bitwise 'OR' of the bit vector on which the method is invoked with the
        argument bit vector.  Return the result as a new bit vector.  If the two bit
        vectors are not of the same size, pad the shorter one with zero's from the
        left.
        '''
        if self.size < other.size:                                  
            bv1 = self._resize_pad_from_left(other.size - self.size)
            bv2 = other                                             
        elif self.size > other.size:                                
            bv1 = self                                              
            bv2 = other._resize_pad_from_left(self.size - other.size)
        else:                                                       
            bv1 = self                                              
            bv2 = other                                             
        res = BitVector( size = bv1.size )                          
        lpb = map(operator.__or__, bv1.vector, bv2.vector)          
        res.vector = array.array( 'H', lpb )                        
        return res 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def shift_right_by_one(self):                                    
        '''
        For a one-bit in-place right non-circular shift.  Note that bitvector size
        does not change.  The rightmost bit that moves past the last element of the
        bitvector is discarded and leftmost bit of the returned vector is set to
        zero.
        '''
        size = len(self.vector)                                      
        right_most_bits = list(map( operator.__and__, self.vector, [0x8000]*size ))         
        self.vector = list(map( operator.__and__, self.vector, [~0x8000]*size )) 
        right_most_bits.insert(0, 0)                                 
        right_most_bits.pop()                                        
        self.vector = list(map(operator.__lshift__, self.vector, [1]*size))    
        self.vector = list(map( operator.__or__, self.vector, \
                                   list(map(operator.__rshift__,right_most_bits, [15]*size))))
        self._setbit(0, 0) 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def __init__(self):
        Backend.__init__(self)
        # self._make_raw_ops(set(expression_operations) - set(expression_set_operations), op_module=BackendVSA)
        self._make_expr_ops(set(expression_set_operations), op_class=self)
        self._make_raw_ops(set(backend_operations_vsa_compliant), op_module=BackendVSA)

        self._op_raw['StridedInterval'] = BackendVSA.CreateStridedInterval
        self._op_raw['ValueSet'] = ValueSet.__init__
        self._op_raw['AbstractLocation'] = AbstractLocation.__init__
        self._op_raw['Reverse'] = BackendVSA.Reverse
        self._op_raw['If'] = self.If
        self._op_expr['BVV'] = self.BVV
        self._op_expr['BoolV'] = self.BoolV
        self._op_expr['BVS'] = self.BVS

        # reduceable
        self._op_raw['__add__'] = self._op_add
        self._op_raw['__sub__'] = self._op_sub
        self._op_raw['__mul__'] = self._op_mul
        self._op_raw['__or__'] = self._op_or
        self._op_raw['__xor__'] = self._op_xor
        self._op_raw['__and__'] = self._op_and
        self._op_raw['__mod__'] = self._op_mod 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def __init__(self, sep_chars="=:", comment_chars="#;"):
        eol_chars = set("\n\r")
        sep_chars = set(sep_chars)
        comment_chars = set(comment_chars)
        key_chars = set(string.printable) - (sep_chars | eol_chars | comment_chars)
        value_chars = set(string.printable) - (eol_chars | comment_chars)

        OLC = reduce(operator.__or__, [OneLineComment(c) for c in comment_chars])
        Comment = (WS >> OLC).map(lambda x: None)
        Num = Number & (WSChar | LineEnd)
        Key = WS >> PosMarker(String(key_chars).map(lambda x: x.strip())) << WS
        Sep = InSet(sep_chars)
        Value = WS >> (Num | String(value_chars).map(lambda x: x.strip()))
        KVPair = (Key + Opt(Sep + Value, default=[None, None])).map(lambda a: (a[0], a[1][1]))
        Line = Comment | KVPair | EOL.map(lambda x: None)
        Doc = Many(Line).map(skip_none).map(to_entry)
        self.Top = Doc + EOF 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def __init__(self, sep_chars="=:", comment_chars="#;"):
        eol_chars = set("\n\r")
        sep_chars = set(sep_chars)
        comment_chars = set(comment_chars)
        key_chars = set(string.printable) - (sep_chars | eol_chars | comment_chars)
        value_chars = set(string.printable) - (eol_chars | comment_chars)

        OLC = reduce(operator.__or__, [OneLineComment(c) for c in comment_chars])
        Comment = (WS >> OLC).map(lambda x: None)
        Num = Number & (WSChar | LineEnd)
        Key = WS >> PosMarker(String(key_chars).map(str.strip)) << WS
        Sep = InSet(sep_chars)
        Value = WS >> (Num | String(value_chars).map(str.strip))
        KVPair = (Key + Opt(Sep + Value, default=[None, None])).map(
            lambda a: (a[0], a[1][1])
        )
        Line = Comment | KVPair | EOL.map(lambda x: None)
        Doc = Many(Line).map(skip_none).map(to_entry)
        self.Top = Doc + EOF 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def circular_rotate_left_by_one(self):                         
        'For a one-bit in-place left circular shift'
        size = len(self.vector)                                    
        bitstring_leftmost_bit = self.vector[0] & 1                
        left_most_bits = list(map(operator.__and__, self.vector, [1]*size)) 
        left_most_bits.append(left_most_bits[0])                   
        del(left_most_bits[0])                                     
        self.vector = list(map(operator.__rshift__, self.vector, [1]*size)) 
        self.vector = list(map( operator.__or__, self.vector, \
                              list( map(operator.__lshift__, left_most_bits, [15]*size) )))   
                                                                   
        self._setbit(self.size -1, bitstring_leftmost_bit) 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def circular_rotate_right_by_one(self):                        
        'For a one-bit in-place right circular shift'
        size = len(self.vector)                                    
        bitstring_rightmost_bit = self[self.size - 1]              
        right_most_bits = list(map( operator.__and__,
                               self.vector, [0x8000]*size ))       
        self.vector = list(map( operator.__and__, self.vector, [~0x8000]*size ))
        right_most_bits.insert(0, bitstring_rightmost_bit)         
        right_most_bits.pop()                                      
        self.vector = list(map(operator.__lshift__, self.vector, [1]*size))
        self.vector = list(map( operator.__or__, self.vector, \
                                list(map(operator.__rshift__, right_most_bits, [15]*size))))  
                                                                   
        self._setbit(0, bitstring_rightmost_bit) 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def shift_left_by_one(self):                                
        '''
        For a one-bit in-place left non-circular shift.  Note that bitvector size
        does not change.  The leftmost bit that moves past the first element of the
        bitvector is discarded and rightmost bit of the returned vector is set to
        zero.
        '''
        size = len(self.vector)                                 
        left_most_bits = list(map(operator.__and__, self.vector, [1]*size))  
        left_most_bits.append(left_most_bits[0])                    
        del(left_most_bits[0])                                      
        self.vector = list(map(operator.__rshift__, self.vector, [1]*size)) 
        self.vector = list(map( operator.__or__, self.vector, \
                               list(map(operator.__lshift__, left_most_bits, [15]*size))))
        self._setbit(self.size -1, 0) 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def _op_or(*args):
        return reduce(operator.__or__, args) 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def __init__(self):
        Backend.__init__(self)
        self._make_raw_ops(set(backend_operations) - { 'If' }, op_module=bv)
        self._make_raw_ops(backend_strings_operations, op_module=strings)
        self._make_raw_ops(backend_fp_operations, op_module=fp)
        self._op_raw['If'] = self._If
        self._op_raw['BVV'] = self.BVV
        self._op_raw['StringV'] = self.StringV
        self._op_raw['FPV'] = self.FPV

        # reduceable
        self._op_raw['__add__'] = self._op_add
        self._op_raw['__sub__'] = self._op_sub
        self._op_raw['__mul__'] = self._op_mul
        self._op_raw['__or__'] = self._op_or
        self._op_raw['__xor__'] = self._op_xor
        self._op_raw['__and__'] = self._op_and

        # unary
        self._op_raw['__invert__'] = self._op_not
        self._op_raw['__neg__'] = self._op_neg

        # boolean ops
        self._op_raw['And'] = self._op_and
        self._op_raw['Or'] = self._op_or
        self._op_raw['Xor'] = self._op_xor
        self._op_raw['Not'] = self._op_boolnot

        self._cache_objects = False 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def fromParams(method, num_regs):
    isstatic = method.access & flags.ACC_STATIC
    full_ptypes = method.id.getSpacedParamTypes(isstatic)
    offset = num_regs - len(full_ptypes)

    prims = TreeList(scalars.INVALID, operator.__and__)
    arrs = TreeList(arrays.INVALID, arrays.merge)
    tainted = TreeList(False, operator.__or__)

    for i, desc in enumerate(full_ptypes):
        if desc is not None:
            prims[offset + i] = scalars.fromDesc(desc)
            arrs[offset + i] = arrays.fromDesc(desc)
    return TypeInfo(prims, arrs, tainted) 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def _combine_requests(self):
        """Create single request that combines keys and filters of all subscribers"""
        if not self.has_subscribers:
            # Don't request anything
            log.debug('No subscribers - setting request to None')
            self.set_request(None)
        else:
            kwargs = {}

            all_filters = tuple(self._tfilters.values())
            if not all_filters or None in all_filters:
                # No subscribers or at least one subscriber wants all torrents
                kwargs['torrents'] = None
            else:
                kwargs['torrents'] = reduce(operator.__or__, all_filters)

            # Combine keys of all requests
            kwargs['keys'] = reduce(lambda a,b: {*a,*b}, self._keys.values())

            # Filters also need certain keys
            for f in all_filters:
                if f is not None:
                    kwargs['keys'].update(f.needed_keys)

            log.debug('Combined filters: %s', kwargs['torrents'])
            log.debug('Combined keys: %s', kwargs['keys'])
            self.set_request(self._api.torrents, **kwargs) 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def propagateOr(x, y):
    return propagateBitwise(x, y, operator.__or__, True, False) 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def intersection(self, geometry):
            try:
                geoms = geometry.geoms
            except AttributeError:
                return set(self._index.intersection(geometry.bounds))
            else:
                return reduce(operator.__or__, (self.intersection(geom) for geom in geoms), set()) 

# 需要導入模塊: import operator [as 別名]
# 或者: from operator import __or__ [as 別名]
def get_mnist(location="./", batch_size=64, labels_per_class=100):
    from functools import reduce
    from operator import __or__
    from torch.utils.data.sampler import SubsetRandomSampler
    from torchvision.datasets import MNIST
    import torchvision.transforms as transforms
    from utils import onehot

    flatten_bernoulli = lambda x: transforms.ToTensor()(x).view(-1).bernoulli()

    mnist_train = MNIST(location, train=True, download=True,
                        transform=flatten_bernoulli, target_transform=onehot(n_labels))
    mnist_valid = MNIST(location, train=False, download=True,
                        transform=flatten_bernoulli, target_transform=onehot(n_labels))

    def get_sampler(labels, n=None):
        # Only choose digits in n_labels
        (indices,) = np.where(reduce(__or__, [labels == i for i in np.arange(n_labels)]))

        # Ensure uniform distribution of labels
        np.random.shuffle(indices)
        indices = np.hstack([list(filter(lambda idx: labels[idx] == i, indices))[:n] for i in range(n_labels)])

        indices = torch.from_numpy(indices)
        sampler = SubsetRandomSampler(indices)
        return sampler

    # Dataloaders for MNIST
    labelled = torch.utils.data.DataLoader(mnist_train, batch_size=batch_size, num_workers=2, pin_memory=cuda,
                                           sampler=get_sampler(mnist_train.train_labels.numpy(), labels_per_class))
    unlabelled = torch.utils.data.DataLoader(mnist_train, batch_size=batch_size, num_workers=2, pin_memory=cuda,
                                             sampler=get_sampler(mnist_train.train_labels.numpy()))
    validation = torch.utils.data.DataLoader(mnist_valid, batch_size=batch_size, num_workers=2, pin_memory=cuda,
                                             sampler=get_sampler(mnist_valid.test_labels.numpy()))

    return labelled, unlabelled, validation