code stringlengths 4 4.48k | docstring stringlengths 1 6.45k | _id stringlengths 24 24 |
|---|---|---|
def song_similarity(self, songs, data): <NEW_LINE> <INDENT> data = data[data.media_id.isin(songs)] <NEW_LINE> data = data.drop_duplicates(['media_id'], keep='first') <NEW_LINE> data = data[['media_id', 'genre_id']] <NEW_LINE> data = data.drop_duplicates(['genre_id'], keep='first') <NEW_LINE> if len(data['media_id']) >=... | The function takes in a list of recommended songs and outputs a list
of serendipitous songs by genre. If the list of serendipitous songs is
too short(<= 5), we output the original recommendations.
:param songs: list of recommended songs
:return: list of serendipitous songs | 625941cf7c178a314d6ef5af |
def densenet121(pretrained=False, **kwargs): <NEW_LINE> <INDENT> model = DenseNet(num_init_features=64, growth_rate=32, block_config=(6, 12, 24, 16), **kwargs) <NEW_LINE> if pretrained: <NEW_LINE> <INDENT> pattern = re.compile(r'^(.*denselayer\d+\.(?:norm|relu|conv))\.((?:[12])\.(?:weight|bias|running_mean|running_var)... | Densenet-121 model from
`"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`_
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet | 625941cf91af0d3eaac9bb67 |
def __init__(self, region=None, rotation=None, sys=None, selection=None, keep_original=None): <NEW_LINE> <INDENT> self._region = None <NEW_LINE> self._rotation = None <NEW_LINE> self._sys = None <NEW_LINE> self._selection = None <NEW_LINE> self._keep_original = None <NEW_LINE> self.discriminator = None <NEW_LINE> if re... | RegionRequest - a model defined in Swagger | 625941cfa4f1c619b28b0186 |
def deduplicate(arrs): <NEW_LINE> <INDENT> unique = [] <NEW_LINE> indices = [] <NEW_LINE> inverse = [] <NEW_LINE> for arr in arrs: <NEW_LINE> <INDENT> found = False <NEW_LINE> for idx, seen in enumerate(unique): <NEW_LINE> <INDENT> if np.all(np.array(seen) == np.array(arr)): <NEW_LINE> <INDENT> found = True <NEW_LINE> ... | Find duplicate arrays in arrs
Implements a naive O(N**2) comparison of the current element
with previous elements.
Input:
arrs - iterable of arrays
Output:
unique - unique elements
indices - indices into unique that will restore the original array | 625941cf63b5f9789fde7234 |
def __init__(self, method, func): <NEW_LINE> <INDENT> super(MethodDecorator, self).__init__(func) <NEW_LINE> self._config = method.methods, method.options, method.h2g | Initialization
:Parameters:
- `method`: `Method` instance
- `func`: decorated callable
:Types:
- `method`: `Method`
- `func`: ``callable`` | 625941cfd58c6744b4257dae |
def split_catalog(catalog): <NEW_LINE> <INDENT> import copy <NEW_LINE> private_catalog = copy.deepcopy(catalog) <NEW_LINE> private_simulations = copy.deepcopy(catalog['simulations']) <NEW_LINE> public_catalog = { 'catalog_file_description': catalog['catalog_file_description'], 'modified': catalog['modified'], 'records'... | Split catalog four ways: private/public, and complete/simulations
This function splits the catalog into four separate parts:
1) The complete catalog for open-access systems
2) The SXS metadata for open-access systems
3) The complete catalog for all systems
4) The SXS metadata for all systems
The complete cat... | 625941cf046cf37aa974ce96 |
def __init__(self, sub_store, service_store, connection): <NEW_LINE> <INDENT> super(DBService, self).__init__(sub_store, service_store) <NEW_LINE> self.connection = connection | Create a new DBService that will use the given connection to execute the query. It will
create a new session and execute a transaction inside it.
:param connection: a :class:`neo4j.v1.GraphDataBase` object
:param sub_store: a SubscriptionStore
:param service_store: a ServiceStore | 625941cfa8ecb033257d321b |
def do_disconnect(self): <NEW_LINE> <INDENT> mutex.acquire() <NEW_LINE> try: <NEW_LINE> <INDENT> adapter.stop() <NEW_LINE> <DEDENT> except: <NEW_LINE> <INDENT> pass <NEW_LINE> <DEDENT> finally: <NEW_LINE> <INDENT> mutex.release() <NEW_LINE> <DEDENT> self.uuid = None <NEW_LINE> self.connected = False <NEW_LINE> self.upd... | Disconnect from the adapter
:return: | 625941cf82261d6c526ab5ee |
def play_music(self, key, state): <NEW_LINE> <INDENT> pg.mixer.music.load(self.music_dict[key]) <NEW_LINE> pg.mixer.music.play() <NEW_LINE> self.state = state | toca musica | 625941cf26238365f5f0efbd |
def get_table_metadata(self, table_name: str, aligned_volume_name: str = None): <NEW_LINE> <INDENT> if aligned_volume_name is None: <NEW_LINE> <INDENT> aligned_volume_name = self.aligned_volume_name <NEW_LINE> <DEDENT> endpoint_mapping = self.default_url_mapping <NEW_LINE> endpoint_mapping["aligned_volume_name"] = alig... | Get metadata about a table
Parameters
----------
table_name (str):
name of table to mark for deletion
aligned_volume_name: str or None, optional,
Name of the aligned_volume. If None, uses the one specified in the client.
Returns
-------
json
metadata about table | 625941cf31939e2706e4cfb8 |
def minDistance(self, houses, k): <NEW_LINE> <INDENT> N = len(houses) <NEW_LINE> if k >= N: <NEW_LINE> <INDENT> return 0 <NEW_LINE> <DEDENT> memo = dict() <NEW_LINE> houses.sort() <NEW_LINE> def dfs(start, end, boxes): <NEW_LINE> <INDENT> if boxes > end-start+1: <NEW_LINE> <INDENT> return float('inf') <NEW_LINE> <DEDEN... | :type houses: List[int]
:type k: int
:rtype: int | 625941cfbd1bec0571d9077e |
def tags(parsed_cg3): <NEW_LINE> <INDENT> return [_parsed_tags(s) for s in parsed_cg3] | Return a list of tags (as a list) from the parsed cg3 data. | 625941cff548e778e58cd6cc |
def get_vanadium_number(self, run_number): <NEW_LINE> <INDENT> if self._normByVanadium: <NEW_LINE> <INDENT> if run_number in self._vanRunNumberDict: <NEW_LINE> <INDENT> van_number = self._vanRunNumberDict[run_number] <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> raise RuntimeError('Run number {0} does not exist in vana... | get vanadium run number
:return: | 625941cf9c8ee82313fbb8c4 |
def hypothenuse(a, b): <NEW_LINE> <INDENT> return math.sqrt(a**2 + b**2) | returns the length of the
hypothenuse when given the lengths of
two other sides of a right-angled
triangle | 625941cf76e4537e8c3517c1 |
def _create_user(self, username, email, password, is_superuser, **extra_fields): <NEW_LINE> <INDENT> now = timezone.now() <NEW_LINE> if not username: <NEW_LINE> <INDENT> raise ValueError('The given username must be set') <NEW_LINE> <DEDENT> email = self.normalize_email(email) <NEW_LINE> utils.validate_email_unique(emai... | Creates and saves a User with the given username, email,
password and superuser status.
Adapted from the core ``auth.User`` model's ``UserManager``: we
have no use for the ``is_staff`` field. | 625941cf596a897236089c0f |
def DiscreteGaussian( image1: Image, variance: List[float] = [1] * 3, maximumKernelWidth: int = 32, maximumError: float = 0.01, useImageSpacing: bool = True, ) -> Image: <NEW_LINE> <INDENT> f = DiscreteGaussianImageFilter() <NEW_LINE> f.SetVariance(variance) <NEW_LINE> f.SetMaximumKernelWidth(maximumKernelWidth) <NEW_L... | Blurs an image by separable convolution with discrete
gaussian kernels. This filter performs Gaussian blurring by
separable convolution of an image and a discrete Gaussian
operator (kernel).
This function directly calls the execute method of DiscreteGaussianImageFilter
in order to support a procedural API.
Also ... | 625941cfbde94217f3682f3f |
def refresh(self) -> None: <NEW_LINE> <INDENT> self.job = self.session.get(self.links["self"]).json() | Refresh the local cache of the serverside job object | 625941cf8a43f66fc4b541b3 |
def falling(n, k): <NEW_LINE> <INDENT> fac_num = 1 <NEW_LINE> while k > 0: <NEW_LINE> <INDENT> fac_num *= n <NEW_LINE> k, n = k - 1, n - 1 <NEW_LINE> <DEDENT> return fac_num | Compute the falling factorial of n to depth k.
>>> falling(6, 3) # 6 * 5 * 4
120
>>> falling(4, 0)
1
>>> falling(4, 3) # 4 * 3 * 2
24
>>> falling(4, 1) # 4
4 | 625941cf67a9b606de4a8008 |
def test_star(self): <NEW_LINE> <INDENT> g = self.compile("xs = 'x'*") <NEW_LINE> self.assertEqual(g.xs(""), "") <NEW_LINE> self.assertEqual(g.xs("x"), "x") <NEW_LINE> self.assertEqual(g.xs("xxxx"), "xxxx") <NEW_LINE> self.assertRaises(_MaybeParseError, g.xs, "xy") | Input matches can be made on zero or more repetitions of a pattern. | 625941cfad47b63b2c50a0ce |
def __iter__(self): <NEW_LINE> <INDENT> return self | Return an iterator.
@rtype: iterator which yields L{bytes}
@return: An iterator over strings. | 625941cf9b70327d1c4e0f24 |
def heur_manhattan_distance(state): <NEW_LINE> <INDENT> sum = 0 <NEW_LINE> center = int((state.width-1)/2) <NEW_LINE> for i in state.xanadus: <NEW_LINE> <INDENT> sum+=(abs(i[0]-center) + abs(i[1]-center)) <NEW_LINE> <DEDENT> return sum | Manhattan distance LunarLockout heuristic | 625941cf097d151d1a222fa8 |
def is_valid_repository(self): <NEW_LINE> <INDENT> p = self._run_git(['ls-remote', self.path, 'HEAD']) <NEW_LINE> errmsg = p.stderr.read() <NEW_LINE> failure = p.wait() <NEW_LINE> if failure: <NEW_LINE> <INDENT> logging.error("Git: Failed to find valid repository %s: %s" % (self.path, errmsg)) <NEW_LINE> return False <... | Checks if this is a valid Git repository. | 625941cf3346ee7daa2b2ebb |
def SetGuid(self,item_name,*__args): <NEW_LINE> <INDENT> pass | SetGuid(self: GH_IWriter,item_name: str,item_index: int,item_value: Guid)
Add a new data item to this chunk.
The combination of name and index must be
unique or an exception will be thrown.
item_name: Name of item to add.
item_index: Index of item to add.
item_value: Value of item to add.
SetGuid(... | 625941cf283ffb24f3c55a4f |
def can_see(self, target): <NEW_LINE> <INDENT> if not target or not target.position: <NEW_LINE> <INDENT> return False <NEW_LINE> <DEDENT> return target.position in self.visible_tiles | Returns true if target entity is in sight | 625941cfbe383301e01b55d4 |
def testDrawAndChangeCurrentTime(self): <NEW_LINE> <INDENT> self._testName = 'ProxyShapeDrawTimeSampledTest' <NEW_LINE> mayaSceneFile = '%s.ma' % self._testName <NEW_LINE> mayaSceneFullPath = os.path.abspath(mayaSceneFile) <NEW_LINE> cmds.file(mayaSceneFullPath, open=True, force=True) <NEW_LINE> UsdMaya.LoadReferenceAs... | Tests drawing a USD proxy shape node that references USD with time
sampled data.
This test ensures that the shape is redrawn correctly when upstream
connections are dirtied. The built in "time1" object's "outTime" plug
is the source of the connection to the assembly node's "time" plug,
which is then the source of the ... | 625941cfa219f33f34628ab8 |
def _items(self, request, do_authz=False, parent_id=None): <NEW_LINE> <INDENT> original_fields, fields_to_add = self._do_field_list( api_common.list_args(request, 'fields')) <NEW_LINE> filters = api_common.get_filters( request, self._attr_info, ['fields', 'sort_key', 'sort_dir', 'limit', 'marker', 'page_reverse'], is_f... | Retrieves and formats a list of elements of the requested entity. | 625941cfa934411ee37517e2 |
def _render_exception(self, error_code, values): <NEW_LINE> <INDENT> assert error_code in [400, 401, 404, 500] <NEW_LINE> values['status_code'] = error_code <NEW_LINE> if (self.payload is not None or self.GET_HANDLER_ERROR_RETURN_TYPE == feconf.HANDLER_TYPE_JSON): <NEW_LINE> <INDENT> self.render_json(values) <NEW_LINE>... | Renders an error page, or an error JSON response.
Args:
error_code: int. The HTTP status code (expected to be one of
400, 401, 404 or 500).
values: dict. The key-value pairs to include in the response. | 625941cf0a50d4780f666fe1 |
def test_data_data_id_export_get(self): <NEW_LINE> <INDENT> response = self.client.open('//data/{data_id}/export'.format(data_id='data_id_example'), method='GET') <NEW_LINE> self.assert200(response, "Response body is : " + response.data.decode('utf-8')) | Test case for data_data_id_export_get
def _exportDataProvenance(data_id): | 625941cf287bf620b61d3bb2 |
@click.command("Update the name attribute of a Cadnano JSON file to match its current filename.") <NEW_LINE> @click.argument("jsonfile") <NEW_LINE> @click.option("--include-ext/--no-include-ext", default=True) <NEW_LINE> def reset_cadnano_json_name_cli(jsonfile, include_ext=True): <NEW_LINE> <INDENT> with open(jsonfile... | cadnano-reset-json-name | 625941cf6fece00bbac2d88e |
def tiles_under(self, x, y): <NEW_LINE> <INDENT> tiles = [] <NEW_LINE> tier = self.top_tier(x, y) <NEW_LINE> if tier: <NEW_LINE> <INDENT> for name in tier.layer_names: <NEW_LINE> <INDENT> tile = tier.layers[name].get_tile(x, y) <NEW_LINE> tiles.append(tile) <NEW_LINE> <DEDENT> <DEDENT> return tiles | Returns a list of tiles on the top tier under the coordinates given, from bottom layer to top. | 625941cf99fddb7c1c9de4e0 |
def main(): <NEW_LINE> <INDENT> args = parse_arguments() <NEW_LINE> if not args.train and not args.test: <NEW_LINE> <INDENT> print("If we are not training, and not testing, what is the point?") <NEW_LINE> <DEDENT> crnn = None <NEW_LINE> if args.train: <NEW_LINE> <INDENT> crnn = CRNN( args.batch_size, args.model_path, a... | Entry point when using CRNN from the commandline | 625941cf99cbb53fe6792d35 |
def quantity(self, asset, include_held=False): <NEW_LINE> <INDENT> if isinstance(asset, str): <NEW_LINE> <INDENT> asset = self.__getitem__(asset) <NEW_LINE> <DEDENT> if isinstance(asset, Currency): <NEW_LINE> <INDENT> assets = self.get_assets(include_positions=False, include_holdings=True, include_held=include_held) <N... | Get owned quantity of asset
Args:
asset: (Currency | Stock | str) the query currency/stock or symbol
include_held: (bool, optional) whether to included held assets in the tally
Returns:
(Decimal) Quantity of asset owned
Raises:
UsageError: If the asset is not valid | 625941cf3cc13d1c6d3c74c9 |
def calc_storage(Q, alpha, beta, gamma, lb_correction = 0.1): <NEW_LINE> <INDENT> import scipy.integrate as integrate <NEW_LINE> def int_gQdQ(Q, alpha, beta, gamma): <NEW_LINE> <INDENT> gQ = gQ_fun(Q, alpha, beta, gamma) <NEW_LINE> int_gQ = 1 / gQ <NEW_LINE> return int_gQ <NEW_LINE> <DEDENT> def set_par(param, idx): <N... | Calcate the storage by numerically integrating 1/gQ over [0, Q], using
scipy.integrate.quad. This function requires a lower and upper boundary
for the integration. Since a value of 0 for the lower boundary will result
in an error (when gamma != 0), so a value close to zero is preferred. In
this case, the lower boundary... | 625941cf4428ac0f6e5ba941 |
def accepts_drops(self, dragged): <NEW_LINE> <INDENT> return False | Reimplement this to evaluate if this Movable should accept drops from dragged. Default returns False.
:param dragged: Item that is being dragged. You may want to look into what kind of object
this is and decide from that.
:return: | 625941cf56b00c62f0f147a9 |
def read_table_header_top(table): <NEW_LINE> <INDENT> transpose = [[] for key in table[0]] <NEW_LINE> for row in table[1:]: <NEW_LINE> <INDENT> for ncol, val in enumerate(row): <NEW_LINE> <INDENT> transpose[ncol].append(val) <NEW_LINE> <DEDENT> for i in range(len(row), len(transpose)): <NEW_LINE> <INDENT> transpose[i].... | Read a table with header in first row.
@param table Matrix format
@return dict Dictionary with header as key | 625941cf66673b3332b921e0 |
def cases(self): <NEW_LINE> <INDENT> import pyark.subclients.cases_client <NEW_LINE> if self._cases_client is None: <NEW_LINE> <INDENT> self._cases_client = pyark.subclients.cases_client.CasesClient( url_base=self._url_base, token=self._token, user=self._user, password=self._password) <NEW_LINE> <DEDENT> return self._c... | :return:
:rtype: CasesClient | 625941cf50812a4eaa59c470 |
def getTimeList(day, categoryList): <NEW_LINE> <INDENT> timelist = [] <NEW_LINE> for cat in categoryList: <NEW_LINE> <INDENT> time = 0 <NEW_LINE> for event in cat['items']: <NEW_LINE> <INDENT> eventDay, daystr = getDay(event['start']['dateTime']) <NEW_LINE> if eventDay != day: <NEW_LINE> <INDENT> continue <NEW_LINE> <D... | for this day:
traverse all category
calculate each category's time
return timeList store each category's time | 625941cf283ffb24f3c55a50 |
def get_weights(self, weight_tensor): <NEW_LINE> <INDENT> return weight_tensor.eval(self.trainer.session) | Get weights.
Get a variable weights.
Examples:
sgen = SequenceGenerator(...)
w = sgen.get_weights(denselayer.W) -- get a dense layer weights
Arguments:
weight_tensor: `tf.Tensor`. A Variable.
Returns:
`np.array`. The provided variable weights. | 625941cfbe7bc26dc91cd74e |
def acquire(self, blocking=False, timeout=None): <NEW_LINE> <INDENT> raise NotImplemented() | Acquire a lock at the Lock's path.
Return True if acquired, False otherwise
`blocking` (bool) If False, return immediately if we got lock.
If True, wait up to `timeout` seconds to acquire a lock
`timeout` (int) number of seconds. By default, wait indefinitely | 625941cf460517430c3942d3 |
def load_data(file_path): <NEW_LINE> <INDENT> raw_data = pd.read_csv(DATA_FILE_PATH) <NEW_LINE> raw_data.fillna(0, inplace=True) <NEW_LINE> raw_data.columns = [col.lower() for col in raw_data.columns] <NEW_LINE> with open(file_path) as file: <NEW_LINE> <INDENT> json_file = json.load(file) <NEW_LINE> <DEDENT> return raw... | Loads X and y data from resources using predetermined features
Returns two DataFrames, X and y data
:param string file_path: specifies which model's final values to utilize
:return: tuple(DataFrame, DataFrame) | 625941cf73bcbd0ca4b2c1c5 |
def temperature_elevation(self, link_area_m: float) -> float: <NEW_LINE> <INDENT> return (self.emission_quantity() / 3600 / link_area_m) * (0.8 / 100) | Get the expected ambient temperature elevation for this link due to
vehicle exhaust.
Parameters:
link_area_m (float): Square area of link in meters^2.
Returns:
Ambient temperature elevation for this link, in degrees Celcius. | 625941cf5fc7496912cc3acd |
def execute_yara_task(mqueue): <NEW_LINE> <INDENT> while True: <NEW_LINE> <INDENT> yara_task = mqueue.get(True) <NEW_LINE> if yara_task is None: <NEW_LINE> <INDENT> return False <NEW_LINE> <DEDENT> try: <NEW_LINE> <INDENT> result = yara_task.execute() <NEW_LINE> if result: <NEW_LINE> <INDENT> result = yara_task.apply_r... | Special dedicated YARA worker. Dispatches newly created yara rules on the
samples pool. There is no analysis in this case,
nor priority considerations, that's why it has been separated. | 625941cf2eb69b55b151c9ff |
def SetParticleImage(self, *args): <NEW_LINE> <INDENT> return _itkSmoothColorFieldImageFilterPython.itkSmoothColorFieldImageFilterIUS2ICVF22_SetParticleImage(self, *args) | SetParticleImage(self, itkImageUS2 arg0) -> int | 625941cfa219f33f34628ab9 |
def editor_test(): <NEW_LINE> <INDENT> app = qapplication() <NEW_LINE> dialog = CollectionsEditor() <NEW_LINE> dialog.setup(get_test_data()) <NEW_LINE> dialog.show() <NEW_LINE> app.exec_() <NEW_LINE> print("out:", dialog.get_value()) | Collections editor test | 625941cf7d43ff24873a2df0 |
def printBoard(self): <NEW_LINE> <INDENT> currBoard = numpy.full((8, 8), 0) <NEW_LINE> currKings = numpy.full((8, 8), 0) <NEW_LINE> print("\tBoard:\n") <NEW_LINE> index = 0 <NEW_LINE> for piece in self.currPlayer.pieces: <NEW_LINE> <INDENT> x, y, isKing = piece <NEW_LINE> loc = x, y <NEW_LINE> currBoard[loc] = self.cur... | Print the board i.e. prints the positions of the player and the opposition and also returns the pieces remaining
| 625941cfb57a9660fec339d3 |
def n(self): <NEW_LINE> <INDENT> return self.__nx | returns the number of frames | 625941cf5166f23b2e1a52a8 |
def find_nearest_color_hexstr(hexdigits, color_table=None): <NEW_LINE> <INDENT> triplet = [] <NEW_LINE> try: <NEW_LINE> <INDENT> if len(hexdigits) == 3: <NEW_LINE> <INDENT> for digit in hexdigits: <NEW_LINE> <INDENT> digit = int(digit, 16) <NEW_LINE> triplet.append((digit * 16) + digit) <NEW_LINE> <DEDENT> <DEDENT> eli... | Given a three or six-character hex digit string, return the nearest
color index.
Arguments:
hexdigits: a three/6 digit hex string, e.g. 'b0b'
Returns:
int, None: index, or None on error. | 625941cf5166f23b2e1a52a9 |
def disable_snmp(self, snmp_community, action_map=None, error_map=None): <NEW_LINE> <INDENT> return CommandTemplateExecutor(cli_service=self._cli_service, command_template=aireos_enbl_disbl_snmp.DISABLE_SNMP, action_map=action_map, error_map=error_map).execute_command(snmp_community=snmp_community) | Disable SNMP on the device
:param snmp_community: community name
:param action_map: actions will be taken during executing commands, i.e. handles yes/no prompts
:param error_map: errors will be raised during executing commands, i.e. handles Invalid Commands errors | 625941cf23e79379d52ee6b3 |
def setFirstEvent(self, firstEv): <NEW_LINE> <INDENT> self.data.firstEvent = CfgTypes.untracked( CfgTypes.uint32(int(firstEv))) | set first event number | 625941cf8e05c05ec3eea4c5 |
@cached_for_request <NEW_LINE> @requires_login <NEW_LINE> def can_create_organizations(user): <NEW_LINE> <INDENT> if user.is_superuser: <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> result = plugins.first('has_perm', user, 'add_organization') <NEW_LINE> if result is False: <NEW_LINE> <INDENT> return result <NEW_L... | Returns a boolean describing whether a user has the ability to
create new organizations. | 625941cf293b9510aa2c33e5 |
def find_email(self, email): <NEW_LINE> <INDENT> emailIsStr = type(email) == str <NEW_LINE> if(emailIsStr): <NEW_LINE> <INDENT> result = db.session.query(User).filter(User.email==email).all() <NEW_LINE> return(result) <NEW_LINE> <DEDENT> return([]) | @brief Funcion que realiza la busqueda del usuario cuyo email sea
"email"
@param email: Correo del usuario a buscar.
@return lista con la consulta solicitada. | 625941cfe5267d203edcddec |
def balance_samples(x_samples, y_samples): <NEW_LINE> <INDENT> pass | Balances samples between OTHER output token and the rest. As it turns out,
most samples don't have punctuation in the middle, so we need to weigh training more
heavily towards punctuation-rich samples so the model learns that. | 625941cf4e696a04525c959b |
def get_audio_video_urls(dom_tree): <NEW_LINE> <INDENT> urls = [] <NEW_LINE> for el in dom_tree('video, audio, embed, source'): <NEW_LINE> <INDENT> src = el.attrib.get('src', '').strip() <NEW_LINE> if src: <NEW_LINE> <INDENT> urls.append(src) <NEW_LINE> <DEDENT> <DEDENT> return urls | Return urls listed in video/audio/embed/source tag src attributes. | 625941cf099cdd3c635f0dab |
def release_all_connection(self, delete=False): <NEW_LINE> <INDENT> self._condition.acquire() <NEW_LINE> for connection in self._active_connection[:]: <NEW_LINE> <INDENT> self._active_connection.remove(connection) <NEW_LINE> if delete is False: <NEW_LINE> <INDENT> self._idle_connection.append(connection) <NEW_LINE> <DE... | The method can be used to release all the connection from the
connection pool. If the delete flag is passed as True, the
connections inside the active connection will be release and
deleted and will not be added inside the idle connection list.
If the delete flag is false, the connections will be released
from the acti... | 625941cf0c0af96317bb8338 |
def undo_pending_song_deletion(self, coresong, position): <NEW_LINE> <INDENT> self._songs_todelete.remove(coresong) <NEW_LINE> self._model.insert(position, coresong) <NEW_LINE> self.props.count += 1 | Removes song from the list of songs to delete
:param CoreSong coresong: song to delete
:param int position: Song position in the playlist | 625941cf99cbb53fe6792d36 |
def p_loop3(p): <NEW_LINE> <INDENT> pass | loop3 : TO_LLAABRE bloque TO_LLACIERRA | 625941cfe76e3b2f99f3a95a |
def do_OPTIONS(self): <NEW_LINE> <INDENT> self.send_response(200, "ok") <NEW_LINE> self.send_header('Access-Control-Allow-Origin', '*') <NEW_LINE> self.send_header('Access-Control-Allow-Methods', 'GET, OPTIONS, POST, HEAD') <NEW_LINE> self.send_header("Access-Control-Allow-Headers", "*") <NEW_LINE> self.end_headers() | Enable CORS while running on a different host | 625941cf56ac1b37e626431e |
def plot_lstm_prediction(actual, prediction, chart_name='Plot.png', title='Actual vs Prediction', y_label='Price USD', x_label='Trading Days'): <NEW_LINE> <INDENT> title = chart_name <NEW_LINE> fig = plt.figure() <NEW_LINE> ax = fig.add_subplot(111) <NEW_LINE> plt.ylabel(y_label) <NEW_LINE> plt.xlabel(x_label) <NEW_LIN... | Plots train, test and prediction
:param chart_name: Name of the chart being plotted
:param actual: DataFrame containing actual data
:param prediction: DataFrame containing predicted values
:param title: Title of the plot
:param y_label: yLabel of the plot
:param x_label: xLabel of the plot
:return: prints a Pyplot aga... | 625941cf71ff763f4b5497dc |
def test_day_init() -> None: <NEW_LINE> <INDENT> p = Player("bob", 5000) <NEW_LINE> nyc = Day("NYC", p) <NEW_LINE> assert len(nyc._drugs) == 10 <NEW_LINE> for _, drug in nyc._drugs.items(): <NEW_LINE> <INDENT> assert isinstance(drug, Drug) | Tests that day initializes properly | 625941cf8e7ae83300e4b11d |
def generate_sftp_file(username, password, direcories=None): <NEW_LINE> <INDENT> file_content = generate_sftp_user_line(username, password, direcories) <NEW_LINE> create_or_replace_config_file(EDIT_FILES['sftp_users'], file_content) | Generates a sftp password file
:username: username to use
:password: password that will be used
:directories: list of directories which the user should have | 625941cfb7558d58953c5063 |
def test_http_head(self): <NEW_LINE> <INDENT> self.spy_on(self.client.build_http_request) <NEW_LINE> response = self.client.http_head( url='http://example.com', headers={ 'Foo': 'bar', }, username='username', password='password') <NEW_LINE> self.assertIsInstance(response, HostingServiceHTTPResponse) <NEW_LINE> self.ass... | Testing HostingServiceClient.http_head | 625941cf94891a1f4081bbfa |
def wd_get_left_hand_guv(): <NEW_LINE> <INDENT> return np.array([0, -1, 0]) | Returns the gravity unit vector for the wearable device placed on the
left hand wrist.
Syntax:
guv = wd_get_left_hand_guv()
Parameters:
None
Returns:
the three axis vector for the wearable device properly placed on the left
hand wrist, which is [0, -1, 0].
This is because of how the axis of the 3D... | 625941cf3317a56b86939da8 |
def get_total(self): <NEW_LINE> <INDENT> fee = 0 <NEW_LINE> self.base_price = self.get_base_price() <NEW_LINE> fee += self.get_date_time_surge_fee() <NEW_LINE> if self.species == "christmas": <NEW_LINE> <INDENT> self.base_price = 1.5 * self.base_price <NEW_LINE> <DEDENT> if self.order_type == 'international' and self.q... | Calculate price, including tax. | 625941cfadb09d7d5db6c8e0 |
def choose_desktop(self, swipe, current_desktop, total_desktop): <NEW_LINE> <INDENT> total = total_desktop - 1 <NEW_LINE> action = current_desktop + swipe <NEW_LINE> if action < 0: <NEW_LINE> <INDENT> return total <NEW_LINE> <DEDENT> elif action > total: <NEW_LINE> <INDENT> return 0 <NEW_LINE> <DEDENT> else: <NEW_LINE>... | Calculate the desktop to move to.
:param swipe: number (-1 or 1, swipe left or right)
:param current_desktop: number
:param total_desktop: total number of desktops | 625941cf76d4e153a657ec81 |
def build(): <NEW_LINE> <INDENT> includes = ['static', 'templates', 'transwarp', 'favicon.ico', '*.py'] <NEW_LINE> excludes = ['test', '.*', '*.pyc', '*.pyo'] <NEW_LINE> local('rm -f dist/%s' % _TAR_FILE) <NEW_LINE> with lcd(os.path.join(_current_path(), 'www')): <NEW_LINE> <INDENT> cmd = ['tar', '--dereference', '-czv... | Build dist package. | 625941cf3cc13d1c6d3c74ca |
def __statistics_submenu(self): <NEW_LINE> <INDENT> menu_string = "Statistics submenu\n" <NEW_LINE> menu_string += "\t1. Students enrolled at a discipline\n" <NEW_LINE> menu_string += "\t2. Students failing at a discipline\n" <NEW_LINE> menu_string += "\t3. Students with best school situation\n" <NEW_LINE> menu_string ... | Submenu for the statistics functionality. Prints the available options and then reads the command from the user
and calls the corresponding method
:return: | 625941cf091ae356686670ae |
def push(self, entry): <NEW_LINE> <INDENT> LOGGER.debug("push(%r)", entry) <NEW_LINE> if self.on_push: <NEW_LINE> <INDENT> self.on_push(self, entry) <NEW_LINE> <DEDENT> ck = hashlib.sha256() <NEW_LINE> self.stack.append((entry, ck)) | Adds an empty subdirectory at the end of the stack,
with a new cksum.
>>> ds = DirHashStack()
>>> ds.push(b'a')
>>> ds.push(b'b')
>>> ds.entries() # doctest: +NORMALIZE_WHITESPACE
[(b'a', 'e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855'),
(b'b', 'e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca4959... | 625941cf7d847024c06be40c |
def get_version(self, revision, required=False): <NEW_LINE> <INDENT> for version in reversed(self.versions): <NEW_LINE> <INDENT> if version.identifier == revision: <NEW_LINE> <INDENT> break <NEW_LINE> <DEDENT> <DEDENT> else: <NEW_LINE> <INDENT> if required: <NEW_LINE> <INDENT> raise exceptions.VersionNotFoundError(revi... | Find a version with identifier revision
:returns: FileVersion or None
:raises: VersionNotFoundError if required is True | 625941cf38b623060ff0af3e |
def get_search_results(query): <NEW_LINE> <INDENT> global index, doc_names <NEW_LINE> result = ranked = list() <NEW_LINE> doc_list = set(doc_names.keys()) <NEW_LINE> flag = 0 <NEW_LINE> for word in query: <NEW_LINE> <INDENT> if word in index: <NEW_LINE> <INDENT> flag = 1 <NEW_LINE> doc_list = doc_list.intersection(inde... | Search for the query in the positional index.
Args -
query: List of processed words
Return -
ranked: List of (doc_id, start_position) for the query. | 625941cf8c0ade5d55d3eb0c |
def __init__(self, action_size, buffer_size, batch_size, seed, alpha, beta): <NEW_LINE> <INDENT> self.action_size = action_size <NEW_LINE> self.memory = {} <NEW_LINE> self.batch_size = batch_size <NEW_LINE> self.experience = namedtuple("Experience", field_names=["state", "action", "reward", "next_state", "done" ,"prior... | Initialize a ReplayBuffer object.
Params
======
action_size (int): dimension of each action
buffer_size (int): maximum size of buffer
batch_size (int): size of each training batch
seed (int): random seed
alpha (float): sampling exponent (between 0 and 1)
beta(float): importance sampling exponen... | 625941cf046cf37aa974ce98 |
def convert_nodes(context, graph): <NEW_LINE> <INDENT> for node in _tqdm(graph.nodes, desc="Converting Frontend ==> MIL Ops", unit=" ops"): <NEW_LINE> <INDENT> _add_op = _TORCH_OPS_REGISTRY.get(node.kind, None) <NEW_LINE> _logging.info("Converting op {} : {}".format(node.name, node.kind)) <NEW_LINE> if _add_op is None:... | Iterate over the nodes of a graph or block and convert to MIL.
Arguments:
context: A TranscriptionContext object to pull node inputs and
assign node outputs.
graph: An InternalTorchIRGraph or InternalTorchIRBlock object. | 625941cf26238365f5f0efbf |
def test_is_in_set(): <NEW_LINE> <INDENT> trials = 10000 <NEW_LINE> count = 0 <NEW_LINE> j = 5 <NEW_LINE> for i in range(trials): <NEW_LINE> <INDENT> if is_in_set(1,i,j,seed=0): <NEW_LINE> <INDENT> count += 1 <NEW_LINE> <DEDENT> <DEDENT> assert abs((count/trials) - 2**(-j)) < (1/math.sqrt(trials)) <NEW_LINE> count = 0 ... | Test if is_in_set works properly (If produces correct probabilities). | 625941cffbf16365ca6f6316 |
def migration_exchange( self, *, users: List[str], **kwargs ) -> Union[Future, SlackResponse]: <NEW_LINE> <INDENT> kwargs.update({"users": users}) <NEW_LINE> return self.api_call("migration.exchange", http_verb="GET", params=kwargs) | For Enterprise Grid workspaces, map local user IDs to global user IDs
Args:
users (list): A list of user ids, up to 400 per request.
e.g. ['W1234567890', 'U2345678901', 'U3456789012'] | 625941cf507cdc57c6306e2c |
def get_var_name(ins, allow_empty=False): <NEW_LINE> <INDENT> name = '' <NEW_LINE> d = skip_white_read(ins).upper() <NEW_LINE> if not (d >= 'A' and d <= 'Z'): <NEW_LINE> <INDENT> ins.seek(-len(d), 1) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> while (d>='A' and d<='Z') or (d>='0' and d<='9') or d=='.': <NEW_LINE> <IN... | Get variable name from token stream. | 625941cf379a373c97cfac95 |
def fourUp(image): <NEW_LINE> <INDENT> newImage = image.copy() <NEW_LINE> pixels = newImage.load() <NEW_LINE> minX, minY, width, height = image.getbbox() <NEW_LINE> for y in range(0, height, 2): <NEW_LINE> <INDENT> for x in range(0, width, 2): <NEW_LINE> <INDENT> rgb = pixels[x,y] <NEW_LINE> pixels[x/2,y/2] = pixels[x,... | Takes in an image and returns a image that has four 1/4 sized versions of the original in it. | 625941cf596a897236089c11 |
def get_biases(ckpt): <NEW_LINE> <INDENT> tf.reset_default_graph() <NEW_LINE> with tf.Session() as sess: <NEW_LINE> <INDENT> saver = tf.train.import_meta_graph('{}.meta'.format(ckpt)) <NEW_LINE> saver.restore(sess, tf.train.latest_checkpoint(os.path.dirname(ckpt))) <NEW_LINE> biases = tf.get_collection(tf.GraphKeys.BIA... | ckptに保存された学習結果networkのバイアス情報を取得する | 625941cfbde94217f3682f41 |
def setCursor(echo_visibility = False): <NEW_LINE> <INDENT> if echo_visibility: <NEW_LINE> <INDENT> curses.echo() <NEW_LINE> curses.curs_set(1) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> curses.noecho() <NEW_LINE> curses.curs_set(0) | Convenience function to turn echo and cursor visibility on/off.
Arguments:
echo_visibility: [Boolean] True for echo on/cursor visible, false
otherwise. | 625941cf2c8b7c6e89b35911 |
def check_name_availability( self, location, name, custom_headers=None, raw=False, **operation_config): <NEW_LINE> <INDENT> digital_twins_instance_check_name = models.CheckNameRequest(name=name) <NEW_LINE> url = self.check_name_availability.metadata['url'] <NEW_LINE> path_format_arguments = { 'subscriptionId': self._se... | Check if a DigitalTwinsInstance name is available.
:param location: Location of DigitalTwinsInstance.
:type location: str
:param name: Resource name.
:type name: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:... | 625941cf67a9b606de4a800a |
def process_event(event, assistant): <NEW_LINE> <INDENT> if event.type == EventType.ON_CONVERSATION_TURN_STARTED: <NEW_LINE> <INDENT> print("Listening ...") <NEW_LINE> bell() <NEW_LINE> amixer.set_low_sound_level() <NEW_LINE> <DEDENT> l.info(event) <NEW_LINE> if event.type == EventType.ON_RECOGNIZING_SPEECH_FINISHED: <... | Pretty prints events.
Prints all events that occur with two spaces between each new
conversation and a single space between turns of a conversation.
Args:
event(event.Event): The current event to process. | 625941cfc4546d3d9de72b85 |
def update_fileswitcher_dlg(self): <NEW_LINE> <INDENT> if self.fileswitcher_dlg: <NEW_LINE> <INDENT> self.fileswitcher_dlg.setup() | Synchronize file list dialog box with editor widget tabs | 625941cf1b99ca400220ac02 |
def __init__(self, api_version=None, kind=None, metadata=None, spec=None, status=None): <NEW_LINE> <INDENT> self._api_version = None <NEW_LINE> self._kind = None <NEW_LINE> self._metadata = None <NEW_LINE> self._spec = None <NEW_LINE> self._status = None <NEW_LINE> self.discriminator = None <NEW_LINE> if api_version is... | V1beta1DaemonSet - a model defined in Swagger | 625941cf16aa5153ce3625c8 |
def refraction(n1, n2, θ1): <NEW_LINE> <INDENT> θ2 = arcsind(n1 / n2 * sind(θ1)) <NEW_LINE> return θ2 | Return the refracted angle of light (degrees) where n1 is the refractive index of incident medium (units),
n2 is the refractive index of the transmission medium (units) and θ1 is the incident angle to the normal | 625941cf91af0d3eaac9bb6a |
def __init__(self, sprite, life, position, velocity, acceleration): <NEW_LINE> <INDENT> self.life = life <NEW_LINE> self.sprite = sprite <NEW_LINE> self.position = position <NEW_LINE> self.velocity = velocity <NEW_LINE> self.acceleration = acceleration <NEW_LINE> self.angle = 0 | :param sprite: graphical representation for the particle
:type sprite: type of your choice
:param life: lifetime of the particle in frames
:type life: int
:param position: initial vector for position of a particle
:type position: 2d list
:param velocity: velocity vector
:type velocity: 2d list
:param acceleration: init... | 625941cf0383005118ecf733 |
def find_next_action(self, child): <NEW_LINE> <INDENT> found = False <NEW_LINE> for dchild in self.children(): <NEW_LINE> <INDENT> if found: <NEW_LINE> <INDENT> if isinstance(dchild, WxAction): <NEW_LINE> <INDENT> return dchild.widget <NEW_LINE> <DEDENT> if isinstance(dchild, WxActionGroup): <NEW_LINE> <INDENT> acts = ... | Locate the wxAction object which logically follows the child.
Parameters
----------
child : WxToolkitObject
The child object of interest.
Returns
-------
result : wxAction or None
The wxAction which logically follows the position of the
child in the list of children. None will be returned if
a relevan... | 625941cf8a43f66fc4b541b6 |
def test_less_0(self): <NEW_LINE> <INDENT> self.assertEqual(get_sequence(-10), []) | test with numbers less than 0 | 625941cf63f4b57ef0001269 |
def lrange(self, name, start, end): <NEW_LINE> <INDENT> return self.server.lrange(name, start, end) | This method returns a slice of the redis list between the slice
bounds. | 625941cf287bf620b61d3bb4 |
def __init__(self, callback): <NEW_LINE> <INDENT> super(ThreadedXMLRPCServer, self).__init__(callback) <NEW_LINE> self._rpc_thread = None <NEW_LINE> self._xmlrpc_server = None | Initialize a threaded RPC server.
Args:
callback (function): callback function to invoke on get status RPC
request. | 625941cf99fddb7c1c9de4e2 |
def all_segments(n): <NEW_LINE> <INDENT> return [(_i, _j) for _i in range(1, n) for _j in range(_i + 2, n)] | Generate all pair nodes combinations
:param n:
:return: | 625941cf4e4d5625662d4528 |
def build(self, x, x_mask, C, C_mask, h_init=None): <NEW_LINE> <INDENT> self._input = x <NEW_LINE> self._input_mask = x_mask <NEW_LINE> self._input_context = C <NEW_LINE> self._input_context_mask = C_mask <NEW_LINE> if x_mask is None: <NEW_LINE> <INDENT> x_mask = T.ones_like(x, dtype='float32') <NEW_LINE> <DEDENT> x_W ... | Function to build the GRU using the initialized parameters
:param x: the input to the layer
:param x_mask: the input mask
:param C: context matrix for each sample (3-D tensor), to use attention on.
dim = #timesteps x #samles x context_dim | 625941cf21bff66bcd684aa3 |
def spinbox(self, title, value=None, *args, **kwargs): <NEW_LINE> <INDENT> return self.spinBox(title, value, *args, **kwargs) | simpleGUI - shortner for spinBox() | 625941cf21a7993f00bc7e41 |
@pytest.mark.parametrize('code', [ raise_not_implemented_method, raise_not_implemented_function, raise_not_implemented_raw, raise_not_implemented_property, ]) <NEW_LINE> @pytest.mark.parametrize('exception', [ 'NotImplementedError', 'NotImplementedError()', ]) <NEW_LINE> def test_raise_not_implemented_error( assert_err... | Testing that `raise NotImplementedError` is allowed. | 625941cf236d856c2ad4492c |
def iter_available_types(self, name, bp_args, bp_kwargs): <NEW_LINE> <INDENT> if name not in self._reg: <NEW_LINE> <INDENT> return iter([]) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> ret = [] <NEW_LINE> for prim in self._reg[name].values(): <NEW_LINE> <INDENT> if prim.gradable(bp_args, bp_kwargs): <NEW_LINE> <INDENT... | Find primitives of the given name that have gradients defined for the arguments.
Parameters
----------
name : str
Primitive name.
bp_args : tuple
Positional arguments that need back propagation.
bp_kwargs : tuple
Keyword arguments that need back propagation.
Returns
-------
Primitives that satisfy the req... | 625941cf187af65679ca5270 |
def result(self): <NEW_LINE> <INDENT> for value in self.__result.itervalues(): <NEW_LINE> <INDENT> value.sort(key = _humanSortKey) <NEW_LINE> <DEDENT> return self.__result | Formats the result. | 625941cf30dc7b7665901ab7 |
def AddCustomPersonImage(self, request): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> params = request._serialize() <NEW_LINE> body = self.call("AddCustomPersonImage", params) <NEW_LINE> response = json.loads(body) <NEW_LINE> if "Error" not in response["Response"]: <NEW_LINE> <INDENT> model = models.AddCustomPersonImag... | 增加自定义人脸图片，每个自定义人物最多可包含10张人脸图片
请注意，与创建自定义人物一样，图片数据优先级优于图片URL优先级
:param request: Request instance for AddCustomPersonImage.
:type request: :class:`tencentcloud.ivld.v20210903.models.AddCustomPersonImageRequest`
:rtype: :class:`tencentcloud.ivld.v20210903.models.AddCustomPersonImageResponse` | 625941cf73bcbd0ca4b2c1c7 |
def test_fit_notallzeros(lfrfitmodel): <NEW_LINE> <INDENT> expected = False <NEW_LINE> all_zeros = not np.any(lfrfitmodel) <NEW_LINE> print("allzeros:" + str(all_zeros)) <NEW_LINE> assert all_zeros == expected | Should not be all zeros.
| 625941cfd164cc6175782e9f |
@app.route("/update/<building>") <NEW_LINE> def update(building): <NEW_LINE> <INDENT> logger.info("更新" + building + "数据") <NEW_LINE> fc = factory(db) <NEW_LINE> controller = fc.getController(building) <NEW_LINE> return controller.update() | 测试用
:param building: 宿舍楼
:return: 更新成功与否 | 625941cf57b8e32f524835ec |
def __rmul__(self, other): <NEW_LINE> <INDENT> return multiply(other, self) | Multiply other by self, and return a new masked array. | 625941cf63f4b57ef000126a |
def url2pathname(url): <NEW_LINE> <INDENT> from . import urllib_red as urllib <NEW_LINE> if not '|' in url: <NEW_LINE> <INDENT> if url[:4] == '////': <NEW_LINE> <INDENT> url = url[2:] <NEW_LINE> <DEDENT> components = url.split('/') <NEW_LINE> return urllib.parse.unquote('\\'.join(components)) <NEW_LINE> <DEDENT> comp =... | Convert a URL to a DOS path.
///C|/foo/bar/spam.foo
becomes
C:\foo\bar\spam.foo | 625941cfa4f1c619b28b0189 |
def model(X_train, Y_train, X_test, Y_test, learning_rate = 0.00015, num_epochs = 25000, minibatch_size = 2041, print_cost = True): <NEW_LINE> <INDENT> ops.reset_default_graph() <NEW_LINE> (n_x, m) = X_train.shape <NEW_LINE> n_y = Y_train.shape[0] <NEW_LINE> costs = [] <NEW_LINE> learning_rate_origin = learning_rate <N... | Implements a three-layer tensorflow neural network: LINEAR->RELU->LINEAR->RELU->LINEAR->SOFTMAX.
Arguments:
X_train -- training set, of shape (input size = 17, number of training examples = 2113)
Y_train -- test set, of shape (output size = 5, number of training examples = 2113)
X_test -- training set, of shape (input... | 625941cf7b25080760e395aa |
def handle(self, *args, **options): <NEW_LINE> <INDENT> sample_object = User.objects.create(id=id, real_name=real_name, tz=tz) <NEW_LINE> sample_object.activity_periods.set(ap) | :param args: arguments.
:param options: options if necessary
:return: creates user objects | 625941cf956e5f7376d70fbe |
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