code stringlengths 20 4.93k | docstring stringlengths 33 1.27k | source stringclasses 3
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def __init__(self, func, argnames, func_name=None, grad_func=None, python_grad_func=None, out_names=None, **kwargs):
self._func = func
self._argnames = argnames
self._func_name = func_name
assert grad_func is None or isinstance(grad_func, _OverloadedFunction)
self._grad_func = grad_func
self._py... | Creates _DefinedFunction.
Args:
func: A python callable which constructs a tf function body.
argnames: A list of strings for function argument names.
func_name: The function name. Defaults to None, in which derives from
'func'.
grad_func: This function's gradient function, if not None. Defaults
to None.
python_grad_f... | github-repos |
def dstack(tup):
arrays = list(tup)
for i in range(len(arrays)):
if arrays[i].ndim is 1:
arrays[i] = arrays[i][np.newaxis, :]
if arrays[i].ndim is 2:
arrays[i] = arrays[i][:, :, np.newaxis]
return concatenate(arrays, axis=2) | Stack arrays in sequence depth wise (along third dimension),
handling ``RemoteArray`` and ``DistArray`` without moving data.
Args:
tup (sequence of array_like)
Returns:
res: `ndarray`, if inputs were all local
`RemoteArray`, if inputs were all on the same remote engine
`DistArray`, if inputs were already scattered on... | juraj-google-style |
def close(self, virtual_account_id, data={}, **kwargs):
url = "{}/{}".format(self.base_url, virtual_account_id)
data['status'] = 'closed'
return self.patch_url(url, data, **kwargs) | Close Virtual Account from given Id
Args:
virtual_account_id :
Id for which Virtual Account objects has to be Closed | juraj-google-style |
def query(self, query, additional_locals=None, safe_mode=False):
logger.debug('Attempting to execute database query: %s', query)
if (safe_mode and (not isinstance(query, dict))):
raise SafetyViolationError(context=self.error_context)
if isinstance(query, dict):
logger.debug('Executing query ... | Executes the given SQLAlchemy query string.
Args:
query: The SQLAlchemy ORM query (or Python code) to be executed.
additional_locals: Any additional local variables to inject into the execution context
when executing the query.
safe_mode: Boolean value indicating whether or not to execute queries in safe mode
only. If... | codesearchnet |
def order_by(self, key_selector=identity):
if self.closed():
raise ValueError('Attempt to call order_by() on a closed Queryable.')
if (not is_callable(key_selector)):
raise TypeError('order_by() parameter key_selector={key_selector} is not callable'.format(key_selector=repr(key_selector)))
r... | Sorts by a key in ascending order.
Introduces a primary sorting order to the sequence. Additional sort
criteria should be specified by subsequent calls to then_by() and
then_by_descending(). Calling order_by() or order_by_descending() on
the results of a call to order_by() will introduce a new primary
ordering which ... | codesearchnet |
def get_metrics_namespace(self) -> str:
return 'BeamML_TF_Numpy' | Returns:
A namespace for metrics collected by the RunInference transform. | github-repos |
def defaultStorable(self, python_type=None, storable_type=None, version=None, **kwargs):
if (python_type is None):
python_type = lookup_type(storable_type)
if self.verbose:
print('generating storable instance for type: {}'.format(python_type))
self.storables.registerStorable(default_storable... | Generate a default storable instance.
Arguments:
python_type (type): Python type of the object.
storable_type (str): storable type name.
version (tuple): version number of the storable handler.
Returns:
StorableHandler: storable instance.
Extra keyword arguments are passed to :meth:`registerStorable`. | codesearchnet |
def copy_pkg(self, filename, id_=-1):
for repo in self._children:
repo.copy_pkg(filename, id_) | Copy a pkg, dmg, or zip to all repositories.
Args:
filename: String path to the local file to copy.
id_: Integer ID you wish to associate package with for a JDS
or CDP only. Default is -1, which is used for creating
a new package object in the database. | juraj-google-style |
def en004(self, value=None):
if value is not None:
try:
value = float(value)
except ValueError:
raise ValueError('value {} need to be of type float '
'for field `en004`'.format(value))
self._en004 = value | Corresponds to IDD Field `en004`
mean coincident dry-bulb temperature to
Enthalpy corresponding to 0.4% annual cumulative frequency of occurrence
Args:
value (float): value for IDD Field `en004`
Unit: kJ/kg
if `value` is None it will not be checked against the
specification and is assumed to be a missing value
Raises... | juraj-google-style |
def sendMessage(self, exchange, routing_key, message, properties=None, UUID=None):
if (properties is None):
properties = pika.BasicProperties(content_type=self.content_type, delivery_mode=1, headers={})
if (UUID is not None):
if (properties.headers is None):
properties.headers = {}
... | With this function, you can send message to `exchange`.
Args:
exchange (str): name of exchange you want to message to be
delivered
routing_key (str): which routing key to use in headers of message
message (str): body of message
properties (dict ,optional): properties of message - if not used,
or set to ``None``, ``sel... | codesearchnet |
def where_function(function: _evaluation.WhereFunction, operand_result: Optional[_sql_data_types.Select], params_result: Collection[_sql_data_types.Select]) -> _sql_data_types.Select:
del function
if not operand_result:
return _sql_data_types.Select(select_part=_sql_data_types.RawExpression('NULL', _sql... | Returns a collection of all the items that match the criteria expression.
This function takes one param (`criteria`) in addition to the operand.
If the operand is not provided the matches function returns the empty set
which in this function translates to NULL.
Returns an error in the event that the `criteria` param... | github-repos |
def install_napp(cls, mgr):
try:
LOG.info(' Searching local NApp...')
mgr.install_local()
LOG.info(' Found and installed.')
except FileNotFoundError:
LOG.info(' Not found. Downloading from NApps Server...')
try:
mgr.install_remote()
LOG.in... | Install a NApp.
Raises:
KytosException: If a NApp hasn't been found. | codesearchnet |
def read_meta_graph_file(filename):
meta_graph_def = meta_graph_pb2.MetaGraphDef()
if not file_io.file_exists(filename):
raise IOError(f'File does not exist. Received: {filename}.')
with file_io.FileIO(filename, 'rb') as f:
file_content = f.read()
try:
meta_graph_def.ParseFromStr... | Reads a file containing `MetaGraphDef` and returns the protocol buffer.
Args:
filename: `meta_graph_def` filename including the path.
Returns:
A `MetaGraphDef` protocol buffer.
Raises:
IOError: If the file doesn't exist, or cannot be successfully parsed. | github-repos |
def __init__(self, form, features):
self.form = form
self.features = features | Construct Segment objectself.
Args:
form (string): the segment as ipa
features (list): the segment as feature_names | juraj-google-style |
def __getitem__(self, id):
if id == slice(None, None):
return list(self)
response = backend.spreadsheet(self._sheets, id)
result = models.SpreadSheet._from_response(response, self._sheets)
result._api = self
return result | Fetch and return the spreadsheet with the given id.
Args:
id (str): unique alphanumeric id of the spreadsheet
Returns:
SpreadSheet: new SpreadSheet instance
Raises:
KeyError: if no spreadsheet with the given ``id`` is found | juraj-google-style |
def GetMessages(self, formatter_mediator, event):
if self.DATA_TYPE != event.data_type:
raise errors.WrongFormatter('Unsupported data type: {0:s}.'.format(
event.data_type))
event_values = event.CopyToDict()
return self._ConditionalFormatMessages(event_values) | Determines the formatted message strings for an event object.
Args:
formatter_mediator (FormatterMediator): mediates the interactions
between formatters and other components, such as storage and Windows
EventLog resources.
event (EventObject): event.
Returns:
tuple(str, str): formatted message string and short messag... | juraj-google-style |
def write_model(model_object, output_tflite_file):
if sys.byteorder == 'big':
model_object = copy.deepcopy(model_object)
byte_swap_tflite_model_obj(model_object, 'big', 'little')
model_bytearray = convert_object_to_bytearray(model_object)
with gfile.GFile(output_tflite_file, 'wb') as output_... | Writes the tflite model, a python object, into the output file.
NOTE: This API only works for TFLite generated with
_experimental_use_buffer_offset=false
Args:
model_object: A tflite model as a python object
output_tflite_file: Full path name to the output tflite file.
Raises:
IOError: If output_tflite_file path is ... | github-repos |
def _pre_run(self):
stage_name = STAGE_NAME_PRE_RUN
record = records.TestResultRecord(stage_name, self.TAG)
record.test_begin()
self.current_test_info = runtime_test_info.RuntimeTestInfo(stage_name, self.log_path, record)
try:
with self._log_test_stage(stage_name):
self.pre_run()... | Proxy function to guarantee the base implementation of `pre_run` is
called.
Returns:
True if setup is successful, False otherwise. | github-repos |
def approve(self, sha=None, **kwargs):
path = '%s/%s/approve' % (self.manager.path, self.get_id())
data = {}
if sha:
data['sha'] = sha
server_data = self.manager.gitlab.http_post(path, post_data=data,
**kwargs)
... | Approve the merge request.
Args:
sha (str): Head SHA of MR
**kwargs: Extra options to send to the server (e.g. sudo)
Raises:
GitlabAuthenticationError: If authentication is not correct
GitlabMRApprovalError: If the approval failed | juraj-google-style |
def get_text_features(self, input_ids: tf.Tensor | None=None, attention_mask: tf.Tensor | None=None, position_ids: tf.Tensor | None=None, return_dict: Optional[bool]=None) -> tf.Tensor:
return_dict = return_dict if return_dict is not None else self.config.use_return_dict
text_outputs = self.blip.text_model(inpu... | Returns:
text_features (`tf.Tensor` of shape `(batch_size, output_dim`): The text embeddings obtained by applying
the projection layer to the pooled output of [`TFBlipTextModel`].
Examples:
```python
>>> from transformers import AutoProcessor, TFBlipModel
>>> model = TFBlipModel.from_pretrained("Salesforce/blip-imag... | github-repos |
def _Read(self, input_file, schema, raw_binary=False):
raw_binary = ['--raw-binary'] if raw_binary else []
with TemporaryDirectoryResource() as tempdir:
basename = os.path.basename(input_file)
basename_no_extension, extension = os.path.splitext(basename)
if extension in ['.bin', '.tflite... | Read a tflite model assuming the given flatbuffer schema.
If `input_file` is in bin, then we must use flatc to convert the schema
from binary to json.
Args:
input_file: a binary (flatbuffer) or json file to read from. Extension
must be `.tflite`, `.bin`, or `.json` for FlatBuffer Binary or
FlatBuffer JSON.
schema: w... | github-repos |
def register_converter(src_type: Union[Type[Any], Tuple[Type[Any], ...]], dest_type: Union[Type[Any], Tuple[Type[Any], ...]], convert_fn: Callable[[Any], Any]) -> None:
_TYPE_CONVERTER_REGISTRY.register(src_type, dest_type, convert_fn) | Register converter from source type to destination type.
Examples::
# Add converter from int to float.
pg.typing.register_converter(int, float, float)
assert pg.typing.Float().apply(1) is 1.0
# Add converter from a dict to class A.
def from_dict(d):
return A(**d)
assert isinstance(pg.typing.Object(A).apply({'x': 1... | github-repos |
def _RemoveForwardedIps(self, forwarded_ips, interface):
for address in forwarded_ips:
self.ip_forwarding_utils.RemoveForwardedIp(address, interface) | Remove the forwarded IP addresses from the network interface.
Args:
forwarded_ips: list, the forwarded IP address strings to delete.
interface: string, the output device to use. | juraj-google-style |
def assets(self, asset_type=None):
if (not self.can_update()):
self._tcex.handle_error(910, [self.type])
if (not asset_type):
return self.tc_requests.adversary_assets(self.api_type, self.api_sub_type, self.unique_id)
if (asset_type == 'PHONE'):
return self.tc_requests.adversary_phone... | Retrieves all of the assets of a given asset_type
Args:
asset_type: (str) Either None, PHONE, HANDLER, or URL
Returns: | codesearchnet |
def inference(images):
with tf.variable_scope('conv1') as scope:
kernel = _variable_with_weight_decay('weights',
shape=[5, 5, 3, 64],
stddev=5e-2,
wd=0.0)
conv = tf.n... | Build the CIFAR-10 model.
Args:
images: Images returned from distorted_inputs() or inputs().
Returns:
Logits. | juraj-google-style |
def __init__(self, parent, module_name, module_ui):
super(ModuleUIBaseFrame, self).__init__(parent, padding=8)
self.columnconfigure(0, weight=1)
self.rowconfigure(1, weight=1)
if module_ui is not None:
module_ui.ModuleUIFrame(self).grid(row=0, column=0... | Create a new base for a module UI
Args:
parent: A tk or ttk object
module_name (str): The name of the module
module_ui: The _ui.py file to add for the module | juraj-google-style |
def parse_latitude(latitude, hemisphere):
latitude = int(latitude[:2]) + float(latitude[2:]) / 60
if hemisphere == 'S':
latitude = -latitude
elif not hemisphere == 'N':
raise ValueError('Incorrect North/South value %r' % hemisphere)
return latitude | Parse a NMEA-formatted latitude pair.
Args:
latitude (str): Latitude in DDMM.MMMM
hemisphere (str): North or South
Returns:
float: Decimal representation of latitude | juraj-google-style |
def container(self, container_name):
original_container = self._container
with ops.init_scope():
original_init_container = ops.get_default_graph()._container
try:
self._container = container_name
with ops.init_scope():
ops.get_default_graph()._container = container_name
... | Returns a context manager that specifies the resource container to use.
Overridden from `tf.Graph` to update both the init_scope container
and the present inner container. This is necessary to make sure setting
containers applies correctly both to created variables and to stateful
ops.
Args:
container_name: container... | github-repos |
def get_atten(self):
return self.attenuation_device.get_atten(self.idx) | Gets the current attenuation setting of Attenuator.
Returns:
A float that is the current attenuation value. Unit is db. | github-repos |
def setup_keyword(dist, _, value):
if value is not True:
return
dist.entry_points = _ensure_entry_points_is_dict(dist.entry_points)
for command, subcommands in six.iteritems(_get_commands(dist)):
entry_point = '{command} = rcli.dispatcher:main'.format(
command=command)... | Add autodetected commands as entry points.
Args:
dist: The distutils Distribution object for the project being
installed.
_: The keyword used in the setup function. Unused.
value: The value set to the keyword in the setup function. If the value
is not True, this function will do nothing. | juraj-google-style |
def convert_to_tensor_or_indexed_slices(value, dtype=None, name=None):
return internal_convert_to_tensor_or_indexed_slices(value=value, dtype=dtype, name=name, as_ref=False) | Converts the given object to a `Tensor` or an `IndexedSlices`.
If `value` is an `IndexedSlices` or `SparseTensor` it is returned
unmodified. Otherwise, it is converted to a `Tensor` using
`convert_to_tensor()`.
Args:
value: An `IndexedSlices`, `SparseTensor`, or an object that can be consumed
by `convert_to_tensor()`... | github-repos |
def modify_module(channel, module_name, module_state):
gui = ui_embed.UI(
channel,
"{} updated".format(module_name),
"{} is now {}".format(module_name, "activated" if module_state else "deactivated"),
modulename=modulename
)
return gui | Creates an embed UI containing the module modified message
Args:
channel (discord.Channel): The Discord channel to bind the embed to
module_name (str): The name of the module that was updated
module_state (bool): The current state of the module
Returns:
embed: The created embed | juraj-google-style |
def _SetBlankLinesBetweenCommentAndClassFunc(self, node):
index = 0
while pytree_utils.IsCommentStatement(node.children[index]):
self.Visit(node.children[index].children[0])
if not self.last_was_decorator:
_SetNumNewlines(node.children[index].children[0], _ONE_BLANK_LINE)
ind... | Set the number of blanks between a comment and class or func definition.
Class and function definitions have leading comments as children of the
classdef and functdef nodes.
Arguments:
node: (pytree.Node) The classdef or funcdef node.
Returns:
The index of the first child past the comment nodes. | github-repos |
def add_help_text(parent, filepath, prefix="!"):
import tkinter as tk
import tkinter.ttk as ttk
help_contents = get_help_data(filepath)
text = tk.Text(parent, wrap='word', font=("Helvetica", 10))
text.grid(row=0, column=0, sticky="W E N S")
text.tag_config("heading", font=("Helvetica", 1... | Load help text from a file and adds it to the parent
Args:
parent: A tk or ttk object
filepath (str): The file to load help text from
prefix (str): The prefix to use for commands | juraj-google-style |
def get_structure_from_mp(formula):
m = MPRester()
entries = m.get_entries(formula, inc_structure='final')
if (len(entries) == 0):
raise ValueError(('No structure with formula %s in Materials Project!' % formula))
elif (len(entries) > 1):
warnings.warn(('%d structures with formula %s fou... | Convenience method to get a crystal from the Materials Project database via
the API. Requires PMG_MAPI_KEY to be set.
Args:
formula (str): A formula
Returns:
(Structure) The lowest energy structure in Materials Project with that
formula. | codesearchnet |
def save_binary(self, data: Union[dict, List[dict]]) -> str:
path, _ = os.path.splitext(self.output_path)
binary_path = os.path.extsep.join((path, 'pickle'))
with open(binary_path, 'wb+') as f_output:
pickle.dump(data, f_output)
return binary_path | Save the provided data object as a pickle-formatted binary data on the disk.
Args:
data (`dict` or list of `dict`): The data to store.
Returns:
`str`: Path where the data has been saved. | github-repos |
def write_wav(path, samples, sr=16000):
max_value = np.abs(np.iinfo(np.int16).min)
data = (samples * max_value).astype(np.int16)
scipy.io.wavfile.write(path, sr, data) | Write to given samples to a wav file.
The samples are expected to be floating point numbers
in the range of -1.0 to 1.0.
Args:
path (str): The path to write the wav to.
samples (np.array): A float array .
sr (int): The sampling rate. | juraj-google-style |
def SelectArtifacts(cls, os_name=None, cpe=None, labels=None, restrict_checks=None):
results = set()
for condition in cls.Conditions(None, os_name, cpe, labels):
trigger = condition[1:]
for chk in itervalues(cls.checks):
if (restrict_checks and (chk.check_id not in restrict_checks)):... | Takes targeting info, identifies artifacts to fetch.
Args:
os_name: 0+ OS names.
cpe: 0+ CPE identifiers.
labels: 0+ GRR labels.
restrict_checks: A list of check ids whose artifacts should be fetched.
Returns:
the artifacts that should be collected. | codesearchnet |
def __getitem__(self, thing: Any) -> np.ndarray:
if type(thing) is str:
return self.__getattr__(thing)
else:
lm = LayerManager(None)
for key, layer in self.items():
lm[key] = loompy.MemoryLoomLayer(key, layer[thing])
return lm | Access a layer by name, or slice through all the layers
Args:
thing: if string, return the specified layer ("" is the default layer)
if slice 2-tuple, return a new LayerManager with all layers sliced | juraj-google-style |
def _create_variables_and_slots(self) -> Dict[str, Dict[str, tf_variables.Variable]]:
self._track_restore_info_for_cpu()
variables = {}
stacked_variables = self._create_variables_from_stacked_tables()
for table in self._table_config:
if table.name in stacked_variables:
variables[tabl... | Create variables for TPU embeddings.
Returns:
A dict of dicts. The outer dict is keyed by the table names and the inner
dicts are keyed by 'parameters' and the slot variable names. | github-repos |
def DeregisterHelper(cls, helper_class):
helper_name = helper_class.NAME.lower()
if helper_name not in cls._helper_classes:
raise KeyError('Helper class not set for name: {0:s}.'.format(
helper_class.NAME))
del cls._helper_classes[helper_name] | Deregisters a helper class.
The helper classes are identified based on their lower case name.
Args:
helper_class (type): class object of the argument helper.
Raises:
KeyError: if helper class is not set for the corresponding name. | juraj-google-style |
def _GetFileSystemCacheIdentifier(self, path_spec):
string_parts = []
string_parts.append(getattr(path_spec.parent, 'comparable', ''))
string_parts.append('type: {0:s}'.format(path_spec.type_indicator))
return ''.join(string_parts) | Determines the file system cache identifier for the path specification.
Args:
path_spec (PathSpec): path specification.
Returns:
str: identifier of the VFS object. | juraj-google-style |
def penalize_boundary_complexity(shp, w=20, mask=None, C=0.5):
def inner(T):
arr = T("input")
if mask is None:
mask_ = np.ones(shp)
mask_[:, w:-w, w:-w] = 0
else:
mask_ = mask
blur = _tf_blur(arr, w=5)
diffs = (blur-arr)**2
diffs += 0.8*(arr-C)**2
return -tf.re... | Encourage the boundaries of an image to have less variation and of color C.
Args:
shp: shape of T("input") because this may not be known.
w: width of boundary to penalize. Ignored if mask is set.
mask: mask describing what area should be penalized.
Returns:
Objective. | juraj-google-style |
def modify_prefix(channel, new_prefix):
gui = ui_embed.UI(channel, 'Prefix updated', 'Modis prefix is now `{}`'.format(new_prefix), modulename=modulename)
return gui | Creates an embed UI containing the prefix modified message
Args:
channel (discord.Channel): The Discord channel to bind the embed to
new_prefix (str): The value of the new prefix
Returns:
embed: The created embed | codesearchnet |
def load_json(task: Task, file: str) -> Result:
kwargs: Dict[(str, Type[MutableMapping[(str, Any)]])] = {}
with open(file, 'r') as f:
data = json.loads(f.read(), **kwargs)
return Result(host=task.host, result=data) | Loads a json file.
Arguments:
file: path to the file containing the json file to load
Examples:
Simple example with ``ordered_dict``::
> nr.run(task=load_json,
file="mydata.json")
file: path to the file containing the json file to load
Returns:
Result object with the following attributes set:
* result (``dict``):... | codesearchnet |
def FindStartOfExpressionInLine(line, endpos, stack):
i = endpos
while i >= 0:
char = line[i]
if char in ')]}':
stack.append(char)
elif char == '>':
if (i > 0 and
(line[i - 1] == '-' or
Match(r'\s>=\s', line[i - 1:]) or
Search(r'... | Find position at the matching start of current expression.
This is almost the reverse of FindEndOfExpressionInLine, but note
that the input position and returned position differs by 1.
Args:
line: a CleansedLines line.
endpos: start searching at this position.
stack: nesting stack at endpos.
Returns:
On finding matc... | juraj-google-style |
def __init__(self, app=None, env=None, region='us-east-1', prop_path=None):
self.app_name = app
self.env = env
self.region = region
self.properties = get_properties(prop_path, env=self.env, region=self.region)
self.datapipeline_data = self.properties['datapipeline']
... | AWS Data Pipeline object.
Args:
app (str): Application name
env (str): Environment/Account
region (str): AWS Region
prop_path (str): Path of environment property file | juraj-google-style |
def get_image_tokens(self, pixel_values: torch.FloatTensor):
batch_size = pixel_values.shape[0]
_, _, image_toks = self.vqmodel.encode(pixel_values)
bpe_toks = self.vocabulary_mapping.convert_img2bpe(image_toks)
bpe_toks = bpe_toks.view(batch_size, -1)
return bpe_toks | Tokenizes images into discrete tokens with VQGAN module. Converts
obtained image tokens into BPE tokens and wraps with "boi" and "eoi"
special tokens.
Args:
pixel_values (`torch.FloatTensor` of shape `(batch_size, num_channels, image_size, image_size)):
The tensors corresponding to the input images. | github-repos |
def FindFirst(cls, setting_matcher, device_matcher=None, **kwargs):
try:
return next(cls.FindDevices(
setting_matcher, device_matcher=device_matcher, **kwargs))
except StopIteration:
raise usb_exceptions.DeviceNotFoundError(
'No device ava... | Find and return the first matching device.
Args:
setting_matcher: See cls.FindDevices.
device_matcher: See cls.FindDevices.
**kwargs: See cls.FindDevices.
Returns:
An instance of UsbHandle.
Raises:
DeviceNotFoundError: Raised if the device is not available. | juraj-google-style |
def set_snippet_client_verbose_logging(self, verbose):
self._ad.log.info('Set verbose logging to %s.', verbose)
self.verbose_logging = verbose | Switches verbose logging. True for logging full RPC response.
By default it will only write max_rpc_return_value_length for Rpc return
strings. If you need to see full message returned from Rpc, please turn
on verbose logging.
max_rpc_return_value_length will set to 1024 by default, the length
contains full Rpc respo... | github-repos |
def interface_required(interface):
def _interface_required(func):
@functools.wraps(func)
def wrapper(self, *args, **kwargs):
if self.tif != interface:
raise errors.JLinkException('Unsupported for current interface... | Decorator to specify that a particular interface type is required
for the given method to be used.
Args:
interface (int): attribute of ``JLinkInterfaces``
Returns:
A decorator function. | juraj-google-style |
def set_attr_text(self, attr_key, attr_val, el_idx=0):
self.get_element_by_attr_key(attr_key, el_idx).attrib[attr_key] = attr_val | Set the value of the selected attribute of the selected element.
Args:
attr_key : str
Name of attribute for which to search
attr_val : str
Text to set for the attribute.
el_idx : int
Index of element to use in the event that there are multiple sibling
elements with the same name. | juraj-google-style |
def data_groups(self, groups, entity_count):
data = []
for xid in groups.keys():
assoc_group_data = self.data_group_association(xid)
data += assoc_group_data
entity_count += len(assoc_group_data)
if (entity_count >= self._batch_max_chunk):
break
return (data, enti... | Process Group data.
Args:
groups (list): The list of groups to process.
Returns:
list: A list of groups including associations | codesearchnet |
def _publish_to_subscribers(event: Event):
subscribers = get_subscribers(event.object_type)
for sub in subscribers:
DB.prepend_to_list(_keys.published(event.object_type, sub),
event.id, pipeline=True)
event_dict = deepcopy(event.config)
event_dict.po... | Publish and event to all subscribers.
- Adds the event id to the published event list for all subscribers.
- Adds the event data to the published event data for all subscribers.
- Publishes the event id notification to all subscribers.
Args:
event (Event): Event object to publish. | juraj-google-style |
def _FormatDateTime(self, event):
try:
datetime_object = datetime.datetime(1970, 1, 1, 0, 0, 0, 0, tzinfo=pytz.UTC)
datetime_object += datetime.timedelta(microseconds=event.timestamp)
datetime_object.astimezone(self._output_mediator.timezone)
return datetime_object.replace(tzinfo=Non... | Formats the date to a datetime object without timezone information.
Note: timezone information must be removed due to lack of support
by xlsxwriter and Excel.
Args:
event (EventObject): event.
Returns:
datetime.datetime|str: date and time value or a string containing
"ERROR" on OverflowError. | codesearchnet |
def issuperset(self, other):
other = self._cast_to_frameset(other)
if (other is NotImplemented):
return NotImplemented
return (self.items >= other.items) | Check if the contents of `self` is a superset of the contents of
`other.`
Args:
other (:class:`FrameSet`):
Returns:
bool:
:class:`NotImplemented`: if `other` fails to convert to a :class:`FrameSet` | codesearchnet |
def select(self, field_paths):
query = query_mod.Query(self)
return query.select(field_paths) | Create a "select" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.select` for
more information on this method.
Args:
field_paths (Iterable[str, ...]): An iterable of field paths
(``.``-delimited list of field names) to use as a projection
of document fields in the query results.
Retu... | codesearchnet |
def get_candidates(self, input_ids: torch.LongTensor) -> Tuple[torch.LongTensor, Optional[torch.FloatTensor]]:
input_ids = input_ids.to(self.assistant_model.device)
min_new_tokens, max_new_tokens = self._calculate_new_tokens(input_ids)
if max_new_tokens == 0:
return (input_ids, None)
self._updat... | Fetches the candidates to be tried for the current input.
Args:
input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):
Indices of input sequence tokens in the vocabulary. [What are input IDs?](../glossary#input-ids)
Return:
`torch.LongTensor` of shape `(batch_size, candidate_length)` containing the ... | github-repos |
def _conv_general_param_type_converter(window_strides, lhs_dilation, rhs_dilation, dim):
def _as_list_of_size(item, size):
if item is None:
return None
return [item] * size if isinstance(item, int) else list(item)
return (_as_list_of_size(window_strides, dim), _as_list_of_size(lhs_d... | Convert strides, lhs_dilation, rhs_dilation to match TF convention.
For example,
in the 3D case, if lhs_dilation = 2, then convert it to [2, 2, 2]
if lhs_dilation = (2, 2, 2), convert it also to [2, 2, 2]
Args:
window_strides: window_strides to be converted
lhs_dilation: lhs_dilation to be converted
rhs_dilation: rhs... | github-repos |
def call_later(self, delay, callback):
if hasattr(self._connection.ioloop, 'call_later'):
self._connection.ioloop.call_later(delay, callback)
else:
self._connection.ioloop.add_timeout(delay, callback) | Schedule a one-shot timeout given delay seconds.
This method is only useful for compatibility with older versions of pika.
Args:
delay (float): Non-negative number of seconds from now until
expiration
callback (method): The callback method, having the signature
`callback()` | codesearchnet |
def add_one(self, url: str, url_properties: Optional[URLProperties]=None, url_data: Optional[URLData]=None):
self.add_many([AddURLInfo(url, url_properties, url_data)]) | Add a single URL to the table.
Args:
url: The URL to be added
url_properties: Additional values to be saved
url_data: Additional data to be saved | codesearchnet |
def __init__(self, session, max_retries, retry_backoff_base):
self.on_connect = event.Event('Channel.on_connect')
self.on_reconnect = event.Event('Channel.on_reconnect')
self.on_disconnect = event.Event('Channel.on_disconnect')
self.on_receiv... | Create a new channel.
Args:
session (http_utils.Session): Request session.
max_retries (int): Number of retries for long-polling request.
retry_backoff_base (int): The base term for the long-polling
exponential backoff. | juraj-google-style |
def save_counter(self):
self._maybe_create_save_counter()
return self._save_counter | An integer variable which starts at zero and is incremented on save.
Used to number checkpoints.
Returns:
The save counter variable. | github-repos |
def deterministic_shuffle(list_, seed=0, rng=None):
r
rng = ensure_rng(seed if rng is None else rng)
rng.shuffle(list_)
return list_ | r"""
Args:
list_ (list):
seed (int):
Returns:
list: list_
CommandLine:
python -m utool.util_numpy --test-deterministic_shuffle
Example:
>>> # ENABLE_DOCTEST
>>> from utool.util_numpy import * # NOQA
>>> list_ = [1, 2, 3, 4, 5, 6]
>>> seed = 1
>>> list_ = deterministic_shuffle(list_, seed)
>>> result = str(list_)
>>... | juraj-google-style |
def truepath_relative(path, otherpath=None):
if (otherpath is None):
otherpath = os.getcwd()
otherpath = truepath(otherpath)
path_ = normpath(relpath(path, otherpath))
return path_ | Normalizes and returns absolute path with so specs
Args:
path (str): path to file or directory
otherpath (None): (default = None)
Returns:
str: path_
CommandLine:
python -m utool.util_path --exec-truepath_relative --show
Example:
>>> # ENABLE_DOCTEST
>>> from utool.util_path import * # NOQA
>>> import utool as ut... | codesearchnet |
def remove(self, node, dirty=True):
if (node.id in self._children):
self._children[node.id].parent = None
del self._children[node.id]
if dirty:
self.touch() | Remove the given child node.
Args:
node (gkeepapi.Node): Node to remove.
dirty (bool): Whether this node should be marked dirty. | codesearchnet |
def _get_child_class(self, path):
if self._child_entity is None:
return BIDSNode
for i, child_ent in enumerate(listify(self._child_entity)):
template = self.available_entities[child_ent].directory
if template is None:
return BIDSNode
... | Return the appropriate child class given a subdirectory path.
Args:
path (str): The path to the subdirectory.
Returns: An uninstantiated BIDSNode or one of its subclasses. | juraj-google-style |
def line_starts_subpgm(line: str) -> Tuple[bool, Optional[str]]:
match = RE_SUB_START.match(line)
if match != None:
f_name = match.group(1)
return (True, f_name)
match = RE_FN_START.match(line)
if match != None:
f_name = match.group(1)
return (True, f_name)
re... | Indicates whether a line in the program is the first line of a subprogram
definition.
Args:
line
Returns:
(True, f_name) if line begins a definition for subprogram f_name;
(False, None) if line does not begin a subprogram definition. | juraj-google-style |
def hpo_terms(self, query=None, hpo_term=None, text=None, limit=None):
query_dict = {}
search_term = None
if query:
query_dict = {'$or':
[
{'hpo_id': {'$regex': query, '$options':'i'}},
{'description': {'$regex': query,... | Return all HPO terms
If a query is sent hpo_terms will try to match with regex on term or
description.
Args:
query(str): Part of a hpoterm or description
hpo_term(str): Search for a specific hpo term
limit(int): the number of desired results
Returns:
result(pymongo.Cursor): A cursor with hpo terms | juraj-google-style |
def release_client(self, client):
if isinstance(client, Client):
if not self._is_expired_client(client):
LOG.debug('Client is not expired. Adding back to pool')
self.__pool.append(client)
elif client.is_connected():
LOG.debug('Clie... | Releases a client object to the pool.
Args:
client: Client object. | juraj-google-style |
def dismiss_confirm(self, text=None, wait=None):
with self.driver.dismiss_modal('confirm', text=text, wait=wait):
(yield) | Execute the wrapped code, dismissing a confirm.
Args:
text (str | RegexObject, optional): Text to match against the text in the modal.
wait (int | float, optional): Maximum time to wait for the modal to appear after
executing the wrapped code.
Raises:
ModalNotFound: If a modal dialog hasn't been found. | codesearchnet |
def xslt_transformation(xml, template):
transformer = ET.XSLT(
_read_template(template)
)
newdom = transformer(
_read_marcxml(xml)
)
return ET.tostring(newdom, pretty_print=True, encoding="utf-8") | Transform `xml` using XSLT `template`.
Args:
xml (str): Filename or XML string. Don't use ``\\n`` in case of
filename.
template (str): Filename or XML string. Don't use ``\\n`` in case of
filename.
Returns:
str: Transformed `xml` as string. | juraj-google-style |
def extract_response(self, extractors):
if not extractors:
return {}
logger.log_debug("start to extract from response object.")
extracted_variables_mapping = OrderedDict()
extract_binds_order_dict = utils.ensure_mapping_format(extractors)
for key, field in ... | extract value from requests.Response and store in OrderedDict.
Args:
extractors (list):
[
{"resp_status_code": "status_code"},
{"resp_headers_content_type": "headers.content-type"},
{"resp_content": "content"},
{"resp_content_person_first_name": "content.person.name.first_name"}
]
Returns:
OrderDict: variable binds ... | juraj-google-style |
def merge_all_models_into_first_model(biop_structure):
from string import ascii_uppercase
idx = 1
first_model = biop_structure[0]
for m in biop_structure.get_models():
if first_model.id == m.id:
continue
for c in m.get_chains():
c.id = ascii_upperca... | Merge all existing models into a Structure's first_model attribute.
This directly modifies the Biopython Structure object. Chains IDs will start from A and increment for each new
chain (model that is converted).
Args:
biop_structure (Structure): Structure with multiple models that should be merged | juraj-google-style |
def __init__(self, **kwargs):
super(functionTagProcessor, self).__init__(**kwargs)
self.include_function_signatures = kwargs.get(
'include_function_signatures', False) | Initializer.
Args:
**include_function_signatures: bool. See get_name() for more info. | juraj-google-style |
def get_many(self, query: Mapping[(str, Any)], context: PipelineContext=None, streaming: bool=False) -> Iterable[T]:
result = self._source.get_many(self._source_type, deepcopy(query), context)
LOGGER.info('Got results "{result}" from query "{query}" of source "{source}"'.format(result=result, query=query, sourc... | Gets a query from the data source, where the query contains multiple elements to be extracted.
1) Extracts the query from the data source.
2) Inserts the result into any data sinks.
3) Transforms the results into the requested type if it wasn't already.
4) Inserts the transformed result into any data sinks.
Args:
que... | codesearchnet |
def __init__(self, channel):
self.ListInstanceConfigs = channel.unary_unary(
"/google.spanner.admin.instance.v1.InstanceAdmin/ListInstanceConfigs",
request_serializer=google_dot_cloud_dot_spanner_dot_admin_dot_instance__v1_dot_proto_dot_spanner__instance__admin__pb2.ListInstance... | Constructor.
Args:
channel: A grpc.Channel. | juraj-google-style |
def remove_from_list(self, key: str, value, count: int = 0,
pipeline: bool = False):
if pipeline:
if redis.__version__ == '2.10.6':
self._pipeline.lrem(name=key, value=value, num=count)
else:
self._pipeline.lrem(key, count... | Remove specified value(s) from the list stored at key.
Args:
key (str): Key where the list is stored.
value: value to remove
count (int): Number of entries to remove, default 0 == all
pipeline(bool): If True, start a transaction block. Default False. | juraj-google-style |
def delete_project(self, resource):
self.project_service.set_auth(self._token_project)
self.project_service.delete(resource) | Deletes the entity described by the given resource.
Args:
resource (intern.resource.boss.BossResource)
Raises:
requests.HTTPError on a failure. | juraj-google-style |
def mock(self, slot, rpc_id, value):
address = slot.address
if (address not in self.mock_rpcs):
self.mock_rpcs[address] = {}
self.mock_rpcs[address][rpc_id] = value | Store a mock return value for an RPC
Args:
slot (SlotIdentifier): The slot we are mocking
rpc_id (int): The rpc we are mocking
value (int): The value that should be returned
when the RPC is called. | codesearchnet |
def extract_signature(func, ignore_first=False):
sig_params = get_signature_params(func)
if ignore_first:
if (len(sig_params) == 0):
raise Exception("Methods must take a 'self' argument, but the method '{}' does not have one.".format(func.__name__))
sig_params = sig_params[1:]
ar... | Extract the function signature from the function.
Args:
func: The function whose signature should be extracted.
ignore_first: True if the first argument should be ignored. This should
be used when func is a method of a class.
Returns:
A function signature object, which includes the names of the keyword
arguments as w... | codesearchnet |
def _supervised_signature_def(method_name, inputs, loss=None, predictions=None, metrics=None):
if inputs is None or not inputs:
raise ValueError(f'{method_name} `inputs` cannot be None or empty.')
signature_inputs = {key: utils.build_tensor_info(tensor) for key, tensor in inputs.items()}
signature_o... | Creates a signature for training and eval data.
This function produces signatures that describe the inputs and outputs
of a supervised process, such as training or evaluation, that
results in loss, metrics, and the like. Note that this function only requires
inputs to be not None.
Args:
method_name: Method name of th... | github-repos |
def __init__(self, endpoint, project, token, api_base="api/v1",
is_skipped_an_issue=True, verify_ssl=True):
super(ReportPortalService, self).__init__()
self.endpoint = endpoint
self.api_base = api_base
self.project = project
self.token = token
se... | Init the service class.
Args:
endpoint: endpoint of report portal service.
project: project name to use for launch names.
token: authorization token.
api_base: defaults to api/v1, can be changed to other version.
is_skipped_an_issue: option to mark skipped tests as not
'To Investigate' items on Server side.
verify_ssl... | juraj-google-style |
def record_markdown(text, cellid):
from acorn.logging.database import record
from time import time
ekey = 'nb-{}'.format(cellid)
global _cellid_map
if (cellid not in _cellid_map):
from acorn.logging.database import active_db
from difflib import SequenceMatcher
from acorn.logg... | Records the specified markdown text to the acorn database.
Args:
text (str): the *raw* markdown text entered into the cell in the ipython
notebook. | codesearchnet |
def validate_env(app):
if not hasattr(app.env, 'javalink_config_cache'):
app.env.javalink_config_cache = {}
for conf_attr, (_, _, env_attr) in ref.CONFIG_VALUES.iteritems():
if not env_attr:
continue
value = getattr(app.config, conf_attr)
cached = app.env.java... | Purge expired values from the environment.
When certain configuration values change, related values in the
environment must be cleared. While Sphinx can rebuild documents on
configuration changes, it does not notify extensions when this
happens. Instead, cache relevant values in the environment in order
to detect when... | juraj-google-style |
def convert(self):
return super(TFLiteConverter, self).convert() | Converts a TensorFlow GraphDef based on instance variables.
Returns:
The converted data in serialized format, either a TFLite Flatbuffer or
a Graphviz graph depending on value in `output_format`.
Raises:
ValueError:
Input shape is not specified.
None value for dimension in input_tensor. | github-repos |
def touch(self, key, expire=0, noreply=None):
if noreply is None:
noreply = self.default_noreply
key = self.check_key(key)
cmd = b'touch ' + key + b' ' + six.text_type(expire).encode('ascii')
if noreply:
cmd += b' noreply'
cmd += b'\r\n'
r... | The memcached "touch" command.
Args:
key: str, see class docs for details.
expire: optional int, number of seconds until the item is expired
from the cache, or zero for no expiry (the default).
noreply: optional bool, True to not wait for the reply (defaults to
self.default_noreply).
Returns:
True if the expiration t... | juraj-google-style |
def _is_quantized_function(self, func: function_pb2.FunctionDef) -> bool:
return func.signature.name.startswith('quantized_') | Determine whether a FunctionDef is quantized.
Args:
func: A FunctionDef object.
Returns:
True iff `func` is quantized. | github-repos |
def FoldByteStream(self, mapped_value, context=None, **unused_kwargs):
elements_data_size = self._CalculateElementsDataSize(context)
if elements_data_size is not None:
if elements_data_size != len(mapped_value):
raise errors.FoldingError(
'Mismatch between elements data size and m... | Folds the data type into a byte stream.
Args:
mapped_value (object): mapped value.
context (Optional[DataTypeMapContext]): data type map context.
Returns:
bytes: byte stream.
Raises:
FoldingError: if the data type definition cannot be folded into
the byte stream. | juraj-google-style |
def _GetStringValue(self, data_dict, name, default_value=None):
values = data_dict.get(name, None)
if (not values):
return default_value
for (index, value) in enumerate(values):
if (',' in value):
values[index] = '"{0:s}"'.format(value)
return ', '.join(values) | Retrieves a specific string value from the data dict.
Args:
data_dict (dict[str, list[str]): values per name.
name (str): name of the value to retrieve.
default_value (Optional[object]): value to return if the name has no value
set in data_dict.
Returns:
str: value represented as a string. | codesearchnet |
def _insert_back_keep_dims(x, axis):
for i in sorted(axis):
x = tf.expand_dims(x, axis=i)
return x | Insert the dims in `axis` back as singletons after being removed.
Args:
x: `Tensor`.
axis: Python list of integers.
Returns:
`Tensor` with same values as `x`, but additional singleton dimensions. | juraj-google-style |
def read_uint16(self, little_endian=True):
if little_endian:
endian = '<'
else:
endian = '>'
return self.unpack(('%sH' % endian), 2) | Read 2 byte as an unsigned integer value from the stream.
Args:
little_endian (bool): specify the endianness. (Default) Little endian.
Returns:
int: | codesearchnet |
def start_time_distance(item_a, item_b, max_value):
start_time_diff = np.abs((item_a.times[0] - item_b.times[0]))
return (np.minimum(start_time_diff, max_value) / float(max_value)) | Absolute difference between the starting times of each item.
Args:
item_a: STObject from the first set in TrackMatcher
item_b: STObject from the second set in TrackMatcher
max_value: Maximum distance value used as scaling value and upper constraint.
Returns:
Distance value between 0 and 1. | codesearchnet |
def __parse(self, function_meta):
self._func = get_mapping_function(function_meta['func_name'], self.functions_mapping)
self.func_name = self._func.__name__
self._args = prepare_lazy_data(function_meta.get('args', []), self.functions_mapping, self.check_variables_set)
self._kwargs = prepare_lazy_data(fu... | init func as lazy functon instance
Args:
function_meta (dict): function meta including name, args and kwargs | codesearchnet |
def ParseCall(self, parser_mediator, query, row, **unused_kwargs):
query_hash = hash(query)
guid = self._GetRowValue(query_hash, row, 'guid')
is_incoming = self._GetRowValue(query_hash, row, 'is_incoming')
videostatus = self._GetRowValue(query_hash, row, 'videostatus')
try:
aux = guid
... | Parses a call.
Args:
parser_mediator (ParserMediator): mediates interactions between parsers
and other components, such as storage and dfvfs.
query (str): query that created the row.
row (sqlite3.Row): row resulting from query.
query (Optional[str]): query. | juraj-google-style |
def order_by(self, *args):
if self._solr_locked:
raise Exception("Query already executed, no changes can be made."
"%s %s" % (self._solr_query, self._solr_params)
)
for arg in args:
if arg.startswith('-'):
... | Applies query ordering.
New parameters are appended to current ones, overwriting existing ones.
Args:
**args: Order by fields names.
Defaults to ascending, prepend with hypen (-) for desecending ordering. | juraj-google-style |
def write_label_list(path, label_list):
entries = []
for label in label_list:
entries.append([label.start, label.end, label.value])
textfile.write_separated_lines(path, entries, separator='\t') | Writes the given `label_list` to an audacity label file.
Args:
path (str): Path to write the file to.
label_list (audiomate.annotations.LabelList): Label list | juraj-google-style |
def get_info(
self,
userSpecifier,
**kwargs
):
request = Request(
'GET',
'/v3/users/{userSpecifier}'
)
request.set_path_param(
'userSpecifier',
userSpecifier
)
response = self.ctx.request(requ... | Fetch the user information for the specified user. This endpoint is
intended to be used by the user themself to obtain their own
information.
Args:
userSpecifier:
The User Specifier
Returns:
v20.response.Response containing the results from submitting the
request | juraj-google-style |
def _GetPathSegmentIndexForOccurrenceWeights(
self, occurrence_weights, value_weights):
largest_weight = occurrence_weights.GetLargestWeight()
if largest_weight > 0:
occurrence_weight_indexes = occurrence_weights.GetIndexesForWeight(
largest_weight)
number_of_occurrence_indexes... | Retrieves the index of the path segment based on occurrence weights.
Args:
occurrence_weights: the occurrence weights object (instance of
_PathSegmentWeights).
value_weights: the value weights object (instance of _PathSegmentWeights).
Returns:
An integer containing the path segment index. | juraj-google-style |
def get_nested_streams(dmap):
return list({s for dmap in get_nested_dmaps(dmap) for s in dmap.streams}) | Recurses supplied DynamicMap to find all streams
Args:
dmap: DynamicMap to recurse to look for streams
Returns:
List of streams that were found | juraj-google-style |
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