Python collections.namedtuple方法代碼示例

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def __init__(self, config, flows_dir, ports_dir, num_timesteps, debug=False):
        self.logger = logging.getLogger("LogHistory")
        if debug:
            self.logger.setLevel(logging.DEBUG)

        self.log_entry = namedtuple("LogEntry", "source destination type")
        self.ports = defaultdict(list)
        self.flows = defaultdict(list)

        self.data = defaultdict(lambda: defaultdict(lambda: defaultdict(int)))
        self.current_timestep = 0
        self.total_timesteps = num_timesteps

        self.parse_config(config)
        self.parse_logs(num_timesteps, flows_dir, ports_dir)
        self.info()

        pretty(self.data) 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def __init__(self, datastore_client, storage_client, round_name):
    """Initializes CompetitionSubmissions.

    Args:
      datastore_client: instance of CompetitionDatastoreClient
      storage_client: instance of CompetitionStorageClient
      round_name: name of the round
    """
    self._datastore_client = datastore_client
    self._storage_client = storage_client
    self._round_name = round_name
    # each of the variables is a dictionary,
    # where key - submission ID
    # value - SubmissionDescriptor namedtuple
    self._attacks = None
    self._targeted_attacks = None
    self._defenses = None 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def test_construct_namedtuple():
    """Original Loader has a problem of building an object which state is set
    by __new__, instead of __init__.
    """
    from collections import namedtuple

    class FooClass(serialization.yaml.yaml.YAMLObject, namedtuple('Foo', "x, y")):
        yaml_tag = 'foo'
        yaml_constructor = serialization.CustomYamlLoader

        def __setstate__(self, data):
            self.data = data

    contents = (
        "---\n"
        "foo: !<foo> {x: 1, y: 2}\n"
    )
    foo_object = serialization.load_yaml(contents)['foo']
    assert isinstance(foo_object, FooClass)
    assert foo_object.data == {'x': 1, 'y': 2} 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def test_forward_types():
    #Test forward with other data batch API
    Batch = namedtuple('Batch', ['data'])
    data = mx.sym.Variable('data')
    out = data * 2
    mod = mx.mod.Module(symbol=out, label_names=None)
    mod.bind(data_shapes=[('data', (1, 10))])
    mod.init_params()
    data1 = [mx.nd.ones((1, 10))]
    mod.forward(Batch(data1))
    assert mod.get_outputs()[0].shape == (1, 10)
    data2 = [mx.nd.ones((3, 5))]
    mod.forward(Batch(data2))
    assert mod.get_outputs()[0].shape == (3, 5)

    #Test forward with other NDArray and np.ndarray inputs
    data = mx.sym.Variable('data')
    out = data * 2
    mod = mx.mod.Module(symbol=out, label_names=None)
    mod.bind(data_shapes=[('data', (1, 10))])
    mod.init_params()
    data1 = mx.nd.ones((1, 10))
    assert mod.predict(data1).shape == (1, 10)
    data2 = np.ones((1, 10))
    assert mod.predict(data1).shape == (1, 10) 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def read_names(names_path):
    """read data from downloaded file. See SmallNames.txt for example format
    or go to https://www.kaggle.com/kaggle/us-baby-names for full lists

    Args:
        names_path: path to the csv file similar to the example type
    Returns:
        Dataset: a namedtuple of two elements: deduped names and their associated
            counts. The names contain only 26 chars and are all lower case
    """
    names_data = pd.read_csv(names_path)
    names_data.Name = names_data.Name.str.lower()

    name_data = names_data.groupby(by=["Name"])["Count"].sum()
    name_counts = np.array(name_data.tolist())
    names_deduped = np.array(name_data.index.tolist())

    Dataset = collections.namedtuple('Dataset', ['Name', 'Count'])
    return Dataset(names_deduped, name_counts) 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def _optimize_clone(optimizer, clone, num_clones, regularization_losses,
                    **kwargs):
  """Compute losses and gradients for a single clone.

  Args:
    optimizer: A tf.Optimizer  object.
    clone: A Clone namedtuple.
    num_clones: The number of clones being deployed.
    regularization_losses: Possibly empty list of regularization_losses
      to add to the clone losses.
    **kwargs: Dict of kwarg to pass to compute_gradients().

  Returns:
    A tuple (clone_loss, clone_grads_and_vars).
      - clone_loss: A tensor for the total loss for the clone.  Can be None.
      - clone_grads_and_vars: List of (gradient, variable) for the clone.
        Can be empty.
  """
  sum_loss = _gather_clone_loss(clone, num_clones, regularization_losses)
  clone_grad = None
  if sum_loss is not None:
    with tf.device(clone.device):
      clone_grad = optimizer.compute_gradients(sum_loss, **kwargs)
  return sum_loss, clone_grad 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def create_loss(self, data, endpoints):
    """Creates all losses required to train the model.

    Args:
      data: InputEndpoints namedtuple.
      endpoints: Model namedtuple.

    Returns:
      Total loss.
    """
    # NOTE: the return value of ModelLoss is not used directly for the
    # gradient computation because under the hood it calls slim.losses.AddLoss,
    # which registers the loss in an internal collection and later returns it
    # as part of GetTotalLoss. We need to use total loss because model may have
    # multiple losses including regularization losses.
    self.sequence_loss_fn(endpoints.chars_logit, data.labels)
    total_loss = slim.losses.get_total_loss()
    tf.summary.scalar('TotalLoss', total_loss)
    return total_loss 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def test_decodes_example_proto(self):
    expected_label = range(37)
    expected_image, encoded = unittest_utils.create_random_image(
        'PNG', shape=(150, 600, 3))
    serialized = unittest_utils.create_serialized_example({
        'image/encoded': [encoded],
        'image/format': ['PNG'],
        'image/class':
        expected_label,
        'image/unpadded_class':
        range(10),
        'image/text': ['Raw text'],
        'image/orig_width': [150],
        'image/width': [600]
    })

    decoder = fsns.get_split('train', dataset_dir()).decoder
    with self.test_session() as sess:
      data_tuple = collections.namedtuple('DecodedData', decoder.list_items())
      data = sess.run(data_tuple(*decoder.decode(serialized)))

    self.assertAllEqual(expected_image, data.image)
    self.assertAllEqual(expected_label, data.label)
    self.assertEqual(['Raw text'], data.text)
    self.assertEqual([1], data.num_of_views) 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def _reset(self):
    # TODO(b/73666007): Use composition instead of inheritance.
    # (http://go/design-for-testability-no-inheritance).
    init_pose = MinitaurPose(
        swing_angle_1=INIT_SWING_POS,
        swing_angle_2=INIT_SWING_POS,
        swing_angle_3=INIT_SWING_POS,
        swing_angle_4=INIT_SWING_POS,
        extension_angle_1=INIT_EXTENSION_POS,
        extension_angle_2=INIT_EXTENSION_POS,
        extension_angle_3=INIT_EXTENSION_POS,
        extension_angle_4=INIT_EXTENSION_POS)
    # TODO(b/73734502): Refactor input of _convert_from_leg_model to namedtuple.
    initial_motor_angles = self._convert_from_leg_model(list(init_pose))
    super(MinitaurReactiveEnv, self)._reset(
        initial_motor_angles=initial_motor_angles, reset_duration=0.5)
    return self._get_observation() 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def as_namedtuple(name, d, deep=True, name_func=None, excludes=None):
    name_func = name_func if name_func is not None else tuple_name_func

    if not isinstance(d, dict) or getattr(d, "keys") is None:
        return d

    if excludes is None:
        excludes = []

    dest = {}

    if deep:
        # deep copy to avoid modifications on input dictionaries
        for key in list(d.keys()):
            key_name = name_func(key)
            if is_dict(d[key]) and key not in excludes:
                dest[key_name] = as_namedtuple(key, d[key], deep=True, name_func=name_func, excludes=excludes)
            elif is_array(d[key]) and key not in excludes:
                dest[key_name] = [as_namedtuple(key, i, deep=True, name_func=name_func, excludes=excludes) for i in d[key]]
            else:
                dest[key_name] = d[key]
    else:
        dest = {name_func(key): d[key] for key in list(d.keys())}

    return collections.namedtuple(name_func(name), list(dest.keys()))(*list(dest.values())) 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def get_inventory_slots(slots :int) -> None:
        """Get coords for inventory slots from 1 to slots."""
        point = namedtuple("p", ("x", "y"))
        i = 1
        row = 1
        x_pos, y_pos = coords.INVENTORY_SLOTS
        res = []
        
        while i <= slots:
            x = x_pos + (i - (12 * (row - 1))) * 50
            y = y_pos + ((row - 1) * 50)
            res.append(point(x, y))
            if i % 12 == 0:
                row += 1
            i += 1
        return res 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def next(self):
        """Advances the iterator one step. Also returns the current value prior
        to moving the iterator

        @rtype: Row (namedtuple of key, value) if keys_only=False, otherwise
                string (the key)

        @raise StopIteration: if called on an iterator that is not valid
        """
        if not self.valid():
            raise StopIteration()
        if self._keys_only:
            rv = self.key()
        else:
            rv = Row(self.key(), self.value())
        self._impl.next()
        return rv 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def prev(self):
        """Backs the iterator up one step. Also returns the current value prior
        to moving the iterator.

        @rtype: Row (namedtuple of key, value) if keys_only=False, otherwise
                string (the key)

        @raise StopIteration: if called on an iterator that is not valid
        """
        if not self.valid():
            raise StopIteration()
        if self._keys_only:
            rv = self.key()
        else:
            rv = Row(self.key(), self.value())
        self._impl.prev()
        return rv 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def test_tuple_command_handler(self):
        handler = type("TestHandler", (TupleCommandHandler, object),
                       {"get_value": lambda s: namedtuple('test', 'a b')(10, 20)})('test')
        # normal execution
        self.assertEqual(10, handler.handle('a'))
        self.assertEqual({'a': 10, 'b': 20}, handler.handle('*'))
        self.assertEqual('{"a": 10, "b": 20}', handler.handle('*;'))
        # exceptions
        self.assertRaises(Exception, handler.handle, '')
        self.assertRaises(Exception, handler.handle, '/')
        self.assertRaises(Exception, handler.handle, '*/')
        self.assertRaises(Exception, handler.handle, '/*')
        self.assertRaises(Exception, handler.handle, 'blabla')
        self.assertRaises(Exception, handler.handle, 'bla/bla')
        self.assertRaises(Exception, handler.handle, 'bla/')
        self.assertRaises(Exception, handler.handle, '/bla') 

# 需要導入模塊: import collections [as 別名]
# 或者: from collections import namedtuple [as 別名]
def test_index_tuple_command_handler(self):
        r = [namedtuple('test', 'a b')(1, 2), namedtuple('test', 'a b')(3, 4)]
        handler = type("TestHandler", (IndexTupleCommandHandler, object),
                       {"get_value": lambda s: r})('test')
        # normal execution
        self.assertEqual([1, 3], handler.handle('a/*'))
        self.assertEqual("[1, 3]", handler.handle('a/*;'))
        self.assertEqual(3, handler.handle('a/1'))
        self.assertEqual({'a': 3, 'b': 4}, handler.handle('*/1'))
        self.assertEqual('{"a": 3, "b": 4}', handler.handle('*;/1'))
        # exceptions
        self.assertRaises(Exception, handler.handle, '')
        self.assertRaises(Exception, handler.handle, '*')
        self.assertRaises(Exception, handler.handle, '*;')
        self.assertRaises(Exception, handler.handle, 'a')
        self.assertRaises(Exception, handler.handle, 'a/')
        self.assertRaises(Exception, handler.handle, '/')
        self.assertRaises(Exception, handler.handle, '*/')
        self.assertRaises(Exception, handler.handle, '/*')
        self.assertRaises(Exception, handler.handle, 'blabla')
        self.assertRaises(Exception, handler.handle, 'bla/bla')
        self.assertRaises(Exception, handler.handle, 'bla/')
        self.assertRaises(Exception, handler.handle, '/bla')