Python pickle.loads方法代碼示例

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def _deserialize(self, data, type_):

        if self.compress:
        # decompress the data if needed
            data = lz4.frame.decompress(data)

        if type_ == _NUMPY:
        # deserialize numpy arrays
            buf = io.BytesIO(data)
            data = np.load(buf)

        elif type_ == _PICKLE:
        # deserialize other python objects
            data = pickle.loads(data)

        else:
        # Otherwise we just return data as it is (bytes)
            pass

        return data 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def run(self):
        print("VEDIO server starts...")
        self.sock.bind(self.ADDR)
        self.sock.listen(1)
        conn, addr = self.sock.accept()
        print("remote VEDIO client success connected...")
        data = "".encode("utf-8")
        payload_size = struct.calcsize("L")
        cv2.namedWindow('Remote', cv2.WINDOW_AUTOSIZE)
        while True:
            while len(data) < payload_size:
                data += conn.recv(81920)
            packed_size = data[:payload_size]
            data = data[payload_size:]
            msg_size = struct.unpack("L", packed_size)[0]
            while len(data) < msg_size:
                data += conn.recv(81920)
            zframe_data = data[:msg_size]
            data = data[msg_size:]
            frame_data = zlib.decompress(zframe_data)
            frame = pickle.loads(frame_data)
            cv2.imshow('Remote', frame)
            if cv2.waitKey(1) & 0xFF == 27:
                break 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def recv_data(self):
        data_remaining = struct.unpack("I", self.conn.recv(4))[0]
        if not data_remaining:
            log.debug("no data?!")
            return None
        log.debug("<- recving %d bytes", data_remaining)
        data = []
        while data_remaining:
            recv_bytes = data_remaining if data_remaining < self.SOCK_BUF else self.SOCK_BUF
            data.append(self.conn.recv(recv_bytes))
            data_len = len(data[-1])
            if data_len == 0:
                break
            data_remaining -= data_len
        data = pickle.loads("".join(data))
        if data["cmd"] != self.ACK:
            self.send_ack()
        return data 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def _controller(self):
        """Return the server controller."""
        def server_controller(cmd_id, cmd_body, _):
            """Server controler."""
            if not self.init_logginig:
                # the reason put the codes here is because we cannot get
                # kvstore.rank earlier
                head = '%(asctime)-15s Server[' + str(
                    self.kvstore.rank) + '] %(message)s'
                logging.basicConfig(level=logging.DEBUG, format=head)
                self.init_logginig = True

            if cmd_id == 0:
                try:
                    optimizer = pickle.loads(cmd_body)
                except:
                    raise
                self.kvstore.set_optimizer(optimizer)
            else:
                print("server %d, unknown command (%d, %s)" % (
                    self.kvstore.rank, cmd_id, cmd_body))
        return server_controller 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def test_attr_basic():
    with mx.AttrScope(group='4', data='great'):
        data = mx.symbol.Variable('data',
                                  attr={'dtype':'data',
                                        'group': '1',
                                        'force_mirroring': 'True'},
                                  lr_mult=1)
        gdata = mx.symbol.Variable('data2')
    assert gdata.attr('group') == '4'
    assert data.attr('group') == '1'
    assert data.attr('lr_mult') == '1'
    assert data.attr('__lr_mult__') == '1'
    assert data.attr('force_mirroring') == 'True'
    assert data.attr('__force_mirroring__') == 'True'
    data2 = pkl.loads(pkl.dumps(data))
    assert data.attr('dtype') == data2.attr('dtype') 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def test_sparse_nd_pickle():
    dim0 = 40
    dim1 = 40
    stypes = ['row_sparse', 'csr']
    densities = [0, 0.5]
    stype_dict = {'row_sparse': RowSparseNDArray, 'csr': CSRNDArray}
    shape = rand_shape_2d(dim0, dim1)
    for stype in stypes:
        for density in densities:
            a, _ = rand_sparse_ndarray(shape, stype, density)
            assert isinstance(a, stype_dict[stype])
            data = pkl.dumps(a)
            b = pkl.loads(data)
            assert isinstance(b, stype_dict[stype])
            assert same(a.asnumpy(), b.asnumpy())


# @kalyc: Getting rid of fixed seed as flakiness could not be reproduced
# tracked at https://github.com/apache/incubator-mxnet/issues/11741 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def load(self, ctx, save=None):
        """loads current team's save. defaults to most recent"""
        server = ctx.message.server
        author = ctx.message.author
        channel = ctx.message.channel

        try:
            team = self.splayers[server.id][channel.id][author.id]
        except:
            team = None

        await self.embark.callback(self, ctx, team, save)
        

    # @adventure.command(pass_context=True)
    # async def save(self, ctx, file):
    #     pass

    # if no team and no save, if user doesn't have a save, new game. otherwise new game must specify team and save 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def _load_data(self):
        extra_get_args = {}
        if self.data_byte_range is not None:
            range_str = 'bytes={}-{}'.format(*self.data_byte_range)
            extra_get_args['Range'] = range_str

        logger.debug("Getting function data")
        data_download_start_tstamp = time.time()
        data_obj = self.internal_storage.get_data(self.data_key, extra_get_args=extra_get_args)
        logger.debug("Finished getting Function data")
        logger.debug("Unpickle Function data")
        loaded_data = pickle.loads(data_obj)
        logger.debug("Finished unpickle Function data")
        data_download_end_tstamp = time.time()
        self.stats.write('data_download_time', round(data_download_end_tstamp-data_download_start_tstamp, 8))

        return loaded_data 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def testPickle(self):
        # Issue 10326

        # Can't use TestCase classes defined in Test class as
        # pickle does not work with inner classes
        test = unittest.TestCase('run')
        for protocol in range(pickle.HIGHEST_PROTOCOL + 1):

            # blew up prior to fix
            pickled_test = pickle.dumps(test, protocol=protocol)
            unpickled_test = pickle.loads(pickled_test)
            self.assertEqual(test, unpickled_test)

            # exercise the TestCase instance in a way that will invoke
            # the type equality lookup mechanism
            unpickled_test.assertEqual(set(), set()) 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def test_pickle(self):
        # Test that images pickle
        # Image that is not proxied can pickle
        img_klass = self.image_class
        img = img_klass(np.zeros((2,3,4)), None)
        img_str = pickle.dumps(img)
        img2 = pickle.loads(img_str)
        assert_array_equal(img.get_data(), img2.get_data())
        assert_equal(img.get_header(), img2.get_header())
        # Save / reload using bytes IO objects
        for key, value in img.file_map.items():
            value.fileobj = BytesIO()
        img.to_file_map()
        img_prox = img.from_file_map(img.file_map)
        img_str = pickle.dumps(img_prox)
        img2_prox = pickle.loads(img_str)
        assert_array_equal(img.get_data(), img2_prox.get_data()) 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def handle_read(self):
        try:
            data = self.recv(self.dlen)
            if len(data) == 0:
                return
        except socket.error as e:
            if e[0] in (errno.EWOULDBLOCK, errno.EAGAIN):
                return

        self.data += data
        self.dlen -= len(data)
        if self.dlen > 0:
            # don't have complete record yet. wait for more data to read
            return

        if self.rlen == 0:
            self.dlen = self.rlen = struct.unpack('>L', self.data)[0]
            self.data = ''
            # got record length. now read record
            return

        # got complete record
        obj = pickle.loads(self.data)
        record = logging.makeLogRecord(obj)

        # Note: EVERY record gets logged. This is because Logger.handle
        # is normally called AFTER logger-level filtering.
        # Filter (e.g., only WARNING or higher)
        # at the sender to save network bandwidth.
        globalLogger.handle(record)

        # reset for next record
        self.data = ''
        self.rlen = 0
        self.dlen = 4 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def collect_results_gpu(result_part, size):
    rank, world_size = get_dist_info()
    # dump result part to tensor with pickle
    part_tensor = torch.tensor(
        bytearray(pickle.dumps(result_part)), dtype=torch.uint8, device='cuda')
    # gather all result part tensor shape
    shape_tensor = torch.tensor(part_tensor.shape, device='cuda')
    shape_list = [shape_tensor.clone() for _ in range(world_size)]
    dist.all_gather(shape_list, shape_tensor)
    # padding result part tensor to max length
    shape_max = torch.tensor(shape_list).max()
    part_send = torch.zeros(shape_max, dtype=torch.uint8, device='cuda')
    part_send[:shape_tensor[0]] = part_tensor
    part_recv_list = [
        part_tensor.new_zeros(shape_max) for _ in range(world_size)
    ]
    # gather all result part
    dist.all_gather(part_recv_list, part_send)

    if rank == 0:
        part_list = []
        for recv, shape in zip(part_recv_list, shape_list):
            part_list.append(
                pickle.loads(recv[:shape[0]].cpu().numpy().tobytes()))
        # sort the results
        ordered_results = []
        for res in zip(*part_list):
            ordered_results.extend(list(res))
        # the dataloader may pad some samples
        ordered_results = ordered_results[:size]
        return ordered_results 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def test_pickle():
    set1 = OrderedSet('abracadabra')
    roundtrip = pickle.loads(pickle.dumps(set1))
    assert roundtrip == set1 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def test_empty_pickle():
    empty_oset = OrderedSet()
    empty_roundtrip = pickle.loads(pickle.dumps(empty_oset))
    assert empty_roundtrip == empty_oset 

# 需要導入模塊: import pickle [as 別名]
# 或者: from pickle import loads [as 別名]
def deserialize(pickle_serialized=''):
        """ddserialize"""
        return pickle.loads(pickle_serialized)