Search is not available for this dataset
identifier stringlengths 1 155 | parameters stringlengths 2 6.09k | docstring stringlengths 11 63.4k | docstring_summary stringlengths 0 63.4k | function stringlengths 29 99.8k | function_tokens list | start_point list | end_point list | language stringclasses 1
value | docstring_language stringlengths 2 7 | docstring_language_predictions stringlengths 18 23 | is_langid_reliable stringclasses 2
values |
|---|---|---|---|---|---|---|---|---|---|---|---|
pad_physical_address | (addr) | Right-pad a physical address. | Right-pad a physical address. | def pad_physical_address(addr):
"""Right-pad a physical address."""
return addr + [0] * (4 - len(addr)) | [
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parse_mapping | (mapping, parents=None) | Parse configuration device mapping. | Parse configuration device mapping. | def parse_mapping(mapping, parents=None):
"""Parse configuration device mapping."""
if parents is None:
parents = []
for addr, val in mapping.items():
if isinstance(addr, (str,)) and isinstance(val, (str,)):
yield (addr, PhysicalAddress(val))
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setup | (hass: HomeAssistant, base_config) | Set up the CEC capability. | Set up the CEC capability. | def setup(hass: HomeAssistant, base_config):
"""Set up the CEC capability."""
# Parse configuration into a dict of device name to physical address
# represented as a list of four elements.
device_aliases = {}
devices = base_config[DOMAIN].get(CONF_DEVICES, {})
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CecEntity.__init__ | (self, device, logical) | Initialize the device. | Initialize the device. | def __init__(self, device, logical) -> None:
"""Initialize the device."""
self._device = device
self._icon = None
self._state = None
self._logical_address = logical
self.entity_id = "%s.%d" % (DOMAIN, self._logical_address) | [
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CecEntity.update | (self) | Update device status. | Update device status. | def update(self):
"""Update device status."""
device = self._device
if device.power_status in [POWER_OFF, 3]:
self._state = STATE_OFF
elif device.status == STATUS_PLAY:
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CecEntity.async_added_to_hass | (self) | Register HDMI callbacks after initialization. | Register HDMI callbacks after initialization. | async def async_added_to_hass(self):
"""Register HDMI callbacks after initialization."""
self._device.set_update_callback(self._update) | [
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CecEntity._update | (self, device=None) | Device status changed, schedule an update. | Device status changed, schedule an update. | def _update(self, device=None):
"""Device status changed, schedule an update."""
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CecEntity.should_poll | (self) |
Return false.
CecEntity.update() is called by the HDMI network when there is new data.
|
Return false. | def should_poll(self):
"""
Return false.
CecEntity.update() is called by the HDMI network when there is new data.
"""
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CecEntity.name | (self) | Return the name of the device. | Return the name of the device. | def name(self):
"""Return the name of the device."""
return (
f"{self.vendor_name} {self._device.osd_name}"
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CecEntity.vendor_id | (self) | Return the ID of the device's vendor. | Return the ID of the device's vendor. | def vendor_id(self):
"""Return the ID of the device's vendor."""
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CecEntity.vendor_name | (self) | Return the name of the device's vendor. | Return the name of the device's vendor. | def vendor_name(self):
"""Return the name of the device's vendor."""
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CecEntity.physical_address | (self) | Return the physical address of device in HDMI network. | Return the physical address of device in HDMI network. | def physical_address(self):
"""Return the physical address of device in HDMI network."""
return str(self._device.physical_address) | [
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CecEntity.type | (self) | Return a string representation of the device's type. | Return a string representation of the device's type. | def type(self):
"""Return a string representation of the device's type."""
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CecEntity.type_id | (self) | Return the type ID of device. | Return the type ID of device. | def type_id(self):
"""Return the type ID of device."""
return self._device.type | [
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CecEntity.icon | (self) | Return the icon for device by its type. | Return the icon for device by its type. | def icon(self):
"""Return the icon for device by its type."""
return (
self._icon
if self._icon is not None
else ICONS_BY_TYPE.get(self._device.type)
if self._device.type in ICONS_BY_TYPE
else ICON_UNKNOWN
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CecEntity.device_state_attributes | (self) | Return the state attributes. | Return the state attributes. | def device_state_attributes(self):
"""Return the state attributes."""
state_attr = {}
if self.vendor_id is not None:
state_attr[ATTR_VENDOR_ID] = self.vendor_id
state_attr[ATTR_VENDOR_NAME] = self.vendor_name
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467,
25
] | python | en | ['en', 'en', 'en'] | True |
create_learning_rate_scheduler | (
factors="constant * linear_warmup * rsqrt_decay",
base_learning_rate=0.5,
warmup_steps=1000,
decay_factor=0.5,
steps_per_decay=20000,
steps_per_cycle=100000,
) | Creates learning rate schedule.
Interprets factors in the factors string which can consist of:
* constant: interpreted as the constant value,
* linear_warmup: interpreted as linear warmup until warmup_steps,
* rsqrt_decay: divide by square root of max(step, warmup_steps)
* rsqrt_normalized_decay: di... | Creates learning rate schedule.
Interprets factors in the factors string which can consist of:
* constant: interpreted as the constant value,
* linear_warmup: interpreted as linear warmup until warmup_steps,
* rsqrt_decay: divide by square root of max(step, warmup_steps)
* rsqrt_normalized_decay: di... | def create_learning_rate_scheduler(
factors="constant * linear_warmup * rsqrt_decay",
base_learning_rate=0.5,
warmup_steps=1000,
decay_factor=0.5,
steps_per_decay=20000,
steps_per_cycle=100000,
):
"""Creates learning rate schedule.
Interprets factors in the factors string which can consi... | [
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compute_metrics | (logits, labels, weights, label_smoothing=0.0) | Compute summary metrics. | Compute summary metrics. | def compute_metrics(logits, labels, weights, label_smoothing=0.0):
"""Compute summary metrics."""
loss, normalizer = cross_entropy(logits, labels, weights, label_smoothing)
acc, _ = accuracy(logits, labels, weights)
metrics = {"loss": loss, "accuracy": acc, "normalizer": normalizer}
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accuracy | (logits, targets, weights=None) | Compute weighted accuracy for log probs and targets.
Args:
logits: [batch, length, num_classes] float array.
targets: categorical targets [batch, length] int array.
weights: None or array of shape [batch, length]
Returns:
Tuple of scalar loss and batch normalizing factor.
| Compute weighted accuracy for log probs and targets.
Args:
logits: [batch, length, num_classes] float array.
targets: categorical targets [batch, length] int array.
weights: None or array of shape [batch, length]
Returns:
Tuple of scalar loss and batch normalizing factor.
| def accuracy(logits, targets, weights=None):
"""Compute weighted accuracy for log probs and targets.
Args:
logits: [batch, length, num_classes] float array.
targets: categorical targets [batch, length] int array.
weights: None or array of shape [batch, length]
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cross_entropy | (logits, targets, weights=None, label_smoothing=0.0) | Compute cross entropy and entropy for log probs and targets.
Args:
logits: [batch, length, num_classes] float array.
targets: categorical targets [batch, length] int array.
weights: None or array of shape [batch, length]
label_smoothing: label smoothing constant, used to determine the on and off... | Compute cross entropy and entropy for log probs and targets.
Args:
logits: [batch, length, num_classes] float array.
targets: categorical targets [batch, length] int array.
weights: None or array of shape [batch, length]
label_smoothing: label smoothing constant, used to determine the on and off... | def cross_entropy(logits, targets, weights=None, label_smoothing=0.0):
"""Compute cross entropy and entropy for log probs and targets.
Args:
logits: [batch, length, num_classes] float array.
targets: categorical targets [batch, length] int array.
weights: None or array of shape [batch, length]
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eval_step | (params, batch) |
Calculate evaluation metrics on a batch.
|
Calculate evaluation metrics on a batch.
| def eval_step(params, batch):
"""
Calculate evaluation metrics on a batch.
"""
targets = batch.pop("labels")
# Hide away tokens which doesn't participate in the optimization
token_mask = jnp.where(targets > 0, 1.0, 0.0)
logits = model(**batch, params=params, train=False)[0]
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AutoConfig.from_pretrained | (cls, pretrained_model_name_or_path, **kwargs) | r"""
Instantiate one of the configuration classes of the library from a pretrained model configuration.
The configuration class to instantiate is selected based on the :obj:`model_type` property of the config object
that is loaded, or when it's missing, by falling back to using pattern matching... | r"""
Instantiate one of the configuration classes of the library from a pretrained model configuration. | def from_pretrained(cls, pretrained_model_name_or_path, **kwargs):
r"""
Instantiate one of the configuration classes of the library from a pretrained model configuration.
The configuration class to instantiate is selected based on the :obj:`model_type` property of the config object
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store | (hass) | Mock store. | Mock store. | def store(hass):
"""Mock store."""
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provider | (hass, store) | Mock provider. | Mock provider. | def provider(hass, store):
"""Mock provider."""
return insecure_example.ExampleAuthProvider(
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manager | (hass, store, provider) | Mock manager. | Mock manager. | def manager(hass, store, provider):
"""Mock manager."""
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test_create_new_credential | (manager, provider) | Test that we create a new credential. | Test that we create a new credential. | async def test_create_new_credential(manager, provider):
"""Test that we create a new credential."""
credentials = await provider.async_get_or_create_credentials(
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test_match_existing_credentials | (store, provider) | See if we match existing users. | See if we match existing users. | async def test_match_existing_credentials(store, provider):
"""See if we match existing users."""
existing = auth_models.Credentials(
id=uuid.uuid4(),
auth_provider_type="insecure_example",
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test_verify_username | (provider) | Test we raise if incorrect user specified. | Test we raise if incorrect user specified. | async def test_verify_username(provider):
"""Test we raise if incorrect user specified."""
with pytest.raises(insecure_example.InvalidAuthError):
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test_verify_password | (provider) | Test we raise if incorrect user specified. | Test we raise if incorrect user specified. | async def test_verify_password(provider):
"""Test we raise if incorrect user specified."""
with pytest.raises(insecure_example.InvalidAuthError):
await provider.async_validate_login("user-test", "incorrect-password") | [
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test_utf_8_username_password | (provider) | Test that we create a new credential. | Test that we create a new credential. | async def test_utf_8_username_password(provider):
"""Test that we create a new credential."""
credentials = await provider.async_get_or_create_credentials(
{"username": "🎉", "password": "😎"}
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setup_platform | (hass, config, add_entities, discovery_info=None) | Set up the Dlib Face detection platform. | Set up the Dlib Face detection platform. | def setup_platform(hass, config, add_entities, discovery_info=None):
"""Set up the Dlib Face detection platform."""
entities = []
for camera in config[CONF_SOURCE]:
entities.append(
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DlibFaceDetectEntity.__init__ | (self, camera_entity, name=None) | Initialize Dlib face entity. | Initialize Dlib face entity. | def __init__(self, camera_entity, name=None):
"""Initialize Dlib face entity."""
super().__init__()
self._camera = camera_entity
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self._name = name
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DlibFaceDetectEntity.camera_entity | (self) | Return camera entity id from process pictures. | Return camera entity id from process pictures. | def camera_entity(self):
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DlibFaceDetectEntity.name | (self) | Return the name of the entity. | Return the name of the entity. | def name(self):
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DlibFaceDetectEntity.process_image | (self, image) | Process image. | Process image. | def process_image(self, image):
"""Process image."""
fak_file = io.BytesIO(image)
fak_file.name = "snapshot.jpg"
fak_file.seek(0)
image = face_recognition.load_image_file(fak_file)
face_locations = face_recognition.face_locations(image)
face_locations = [{ATTR_... | [
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async_setup_entry | (hass, config_entry, async_add_entities) | Set up a Tradfri config entry. | Set up a Tradfri config entry. | async def async_setup_entry(hass, config_entry, async_add_entities):
"""Set up a Tradfri config entry."""
gateway_id = config_entry.data[CONF_GATEWAY_ID]
tradfri_data = hass.data[DOMAIN][config_entry.entry_id]
api = tradfri_data[KEY_API]
devices = tradfri_data[DEVICES]
sensors = (
dev
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TradfriSensor.__init__ | (self, device, api, gateway_id) | Initialize the device. | Initialize the device. | def __init__(self, device, api, gateway_id):
"""Initialize the device."""
super().__init__(device, api, gateway_id)
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TradfriSensor.device_class | (self) | Return the devices' state attributes. | Return the devices' state attributes. | def device_class(self):
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TradfriSensor.state | (self) | Return the current state of the device. | Return the current state of the device. | def state(self):
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TradfriSensor.unit_of_measurement | (self) | Return the unit_of_measurement of the device. | Return the unit_of_measurement of the device. | def unit_of_measurement(self):
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CitiBikeILP.__init__ | (
self, num_station: int, num_neighbor: int,
station_capacity: List[int], station_neighbor_list: List[List[int]],
decision_interval: int, config: DottableDict
) | A simple Linear Programming formulation for solving the bike repositioning problem.
Args:
num_station (int): Number of stations in current topology.
num_neighbor (int): Number of neighbors that needed to consider when repositioning.
station_capacity (List[int]): The capacity... | A simple Linear Programming formulation for solving the bike repositioning problem. | def __init__(
self, num_station: int, num_neighbor: int,
station_capacity: List[int], station_neighbor_list: List[List[int]],
decision_interval: int, config: DottableDict
):
"""A simple Linear Programming formulation for solving the bike repositioning problem.
Args:
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CitiBikeILP.get_transfer_list | (
self, env_tick: int, init_inventory: np.ndarray, demand: np.ndarray, supply: np.ndarray
) | Get the transfer list for the given env_tick.
Args:
env_tick (int): The environment tick when calling this function.
init_inventory (np.ndarray): The initial inventory of each station.
Shape: (num_station).
demand (np.ndarray): The demand for each station in ... | Get the transfer list for the given env_tick. | def get_transfer_list(
self, env_tick: int, init_inventory: np.ndarray, demand: np.ndarray, supply: np.ndarray
) -> List[Tuple[int, int, int]]:
"""Get the transfer list for the given env_tick.
Args:
env_tick (int): The environment tick when calling this function.
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setup_platform | (hass, platform) | Set up the TotalConnect platform. | Set up the TotalConnect platform. | async def setup_platform(hass, platform):
"""Set up the TotalConnect platform."""
# first set up a config entry and add it to hass
mock_entry = MockConfigEntry(
domain=DOMAIN,
data={CONF_USERNAME: "user@email.com", CONF_PASSWORD: "password"},
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mock_entry.add_to_hass(hass)
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BaseCrawler.crawl | (self) |
crawl main method
|
crawl main method
| def crawl(self):
"""
crawl main method
"""
for url in self.urls:
logger.info(f'fetching {url}')
html = self.fetch(url, **self.kwargs)
for proxy in self.parse(html):
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device_reg | (hass) | Return an empty, loaded, registry. | Return an empty, loaded, registry. | def device_reg(hass):
"""Return an empty, loaded, registry."""
return mock_device_registry(hass) | [
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entity_reg | (hass) | Return an empty, loaded, registry. | Return an empty, loaded, registry. | def entity_reg(hass):
"""Return an empty, loaded, registry."""
return mock_registry(hass) | [
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calls | (hass) | Track calls to a mock service. | Track calls to a mock service. | def calls(hass):
"""Track calls to a mock service."""
return async_mock_service(hass, "test", "automation") | [
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test_get_conditions | (hass, device_reg, entity_reg) | Test we get the expected conditions from a lock. | Test we get the expected conditions from a lock. | async def test_get_conditions(hass, device_reg, entity_reg):
"""Test we get the expected conditions from a lock."""
config_entry = MockConfigEntry(domain="test", data={})
config_entry.add_to_hass(hass)
device_entry = device_reg.async_get_or_create(
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test_if_state | (hass, calls) | Test for turn_on and turn_off conditions. | Test for turn_on and turn_off conditions. | async def test_if_state(hass, calls):
"""Test for turn_on and turn_off conditions."""
hass.states.async_set("lock.entity", STATE_LOCKED)
assert await async_setup_component(
hass,
automation.DOMAIN,
{
automation.DOMAIN: [
{
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125,
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async_setup | (hass: HomeAssistant, config: dict) | Set up configured Dexcom. | Set up configured Dexcom. | async def async_setup(hass: HomeAssistant, config: dict):
"""Set up configured Dexcom."""
hass.data[DOMAIN] = {}
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async_setup_entry | (hass: HomeAssistant, entry: ConfigEntry) | Set up Dexcom from a config entry. | Set up Dexcom from a config entry. | async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry):
"""Set up Dexcom from a config entry."""
try:
dexcom = await hass.async_add_executor_job(
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async_unload_entry | (hass: HomeAssistant, entry: ConfigEntry) | Unload a config entry. | Unload a config entry. | async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry):
"""Unload a config entry."""
unload_ok = all(
await asyncio.gather(
*[
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update_listener | (hass, entry) | Handle options update. | Handle options update. | async def update_listener(hass, entry):
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await hass.config_entries.async_reload(entry.entry_id) | [
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TFAttention.causal_attention_mask | (nd, ns, dtype) |
1's in the lower triangle, counting from the lower right corner. Same as tf.matrix_band_part(tf.ones([nd, ns]),
-1, ns-nd), but doesn't produce garbage on TPUs.
|
1's in the lower triangle, counting from the lower right corner. Same as tf.matrix_band_part(tf.ones([nd, ns]),
-1, ns-nd), but doesn't produce garbage on TPUs.
| def causal_attention_mask(nd, ns, dtype):
"""
1's in the lower triangle, counting from the lower right corner. Same as tf.matrix_band_part(tf.ones([nd, ns]),
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i = tf.range(nd)[:, None]
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config | (*args, **kwargs) | r"""
# Using torch.hub !
import torch
config = torch.hub.load('huggingface/transformers', 'config', 'bert-base-uncased') # Download configuration from huggingface.co and cache.
config = torch.hub.load('huggingface/transformers', 'config', './test/bert_sa... | r"""
# Using torch.hub !
import torch | def config(*args, **kwargs):
r"""
# Using torch.hub !
import torch
config = torch.hub.load('huggingface/transformers', 'config', 'bert-base-uncased') # Download configuration from huggingface.co and cache.
config = torch.hub.load('huggingface/transfo... | [
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tokenizer | (*args, **kwargs) | r"""
# Using torch.hub !
import torch
tokenizer = torch.hub.load('huggingface/transformers', 'tokenizer', 'bert-base-uncased') # Download vocabulary from huggingface.co and cache.
tokenizer = torch.hub.load('huggingface/transformers', 'tokenizer', './test/bert_saved_model/') # E.g. ... | r"""
# Using torch.hub !
import torch | def tokenizer(*args, **kwargs):
r"""
# Using torch.hub !
import torch
tokenizer = torch.hub.load('huggingface/transformers', 'tokenizer', 'bert-base-uncased') # Download vocabulary from huggingface.co and cache.
tokenizer = torch.hub.load('huggingface/transformers', 'tokenizer', ... | [
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# Using torch.hub !
import torch
model = torch.hub.load('huggingface/transformers', 'model', 'bert-base-uncased') # Download model and configuration from huggingface.co and cache.
model = torch.hub.load('huggingface/transformers', 'model', './test/bert_model/') ... | r"""
# Using torch.hub !
import torch | def model(*args, **kwargs):
r"""
# Using torch.hub !
import torch
model = torch.hub.load('huggingface/transformers', 'model', 'bert-base-uncased') # Download model and configuration from huggingface.co and cache.
model = torch.hub.load('huggingface/transformers', ... | [
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modelWithLMHead | (*args, **kwargs) | r"""
# Using torch.hub !
import torch
model = torch.hub.load('huggingface/transformers', 'modelWithLMHead', 'bert-base-uncased') # Download model and configuration from huggingface.co and cache.
model = torch.hub.load('huggingface/transformers', 'modelWithLMHead', './test/bert_model/... | r"""
# Using torch.hub !
import torch | def modelWithLMHead(*args, **kwargs):
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# Using torch.hub !
import torch
model = torch.hub.load('huggingface/transformers', 'modelWithLMHead', 'bert-base-uncased') # Download model and configuration from huggingface.co and cache.
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modelForSequenceClassification | (*args, **kwargs) | r"""
# Using torch.hub !
import torch
model = torch.hub.load('huggingface/transformers', 'modelForSequenceClassification', 'bert-base-uncased') # Download model and configuration from huggingface.co and cache.
model = torch.hub.load('huggingface/transformers', 'modelF... | r"""
# Using torch.hub !
import torch | def modelForSequenceClassification(*args, **kwargs):
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# Using torch.hub !
import torch
model = torch.hub.load('huggingface/transformers', 'modelForSequenceClassification', 'bert-base-uncased') # Download model and configuration from huggingface.co and cache.
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modelForQuestionAnswering | (*args, **kwargs) | r"""
# Using torch.hub !
import torch
model = torch.hub.load('huggingface/transformers', 'modelForQuestionAnswering', 'bert-base-uncased') # Download model and configuration from huggingface.co and cache.
model = torch.hub.load('huggingface/transformers', 'modelForQuestionAnswering',... | r"""
# Using torch.hub !
import torch | def modelForQuestionAnswering(*args, **kwargs):
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# Using torch.hub !
import torch
model = torch.hub.load('huggingface/transformers', 'modelForQuestionAnswering', 'bert-base-uncased') # Download model and configuration from huggingface.co and cache.
model = torch.hub.load('hug... | [
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PickledCorpusReader.__init__ | (self, root, fileids=PKL_PATTERN, **kwargs) |
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PickledCorpusReader._resolve | (self, fileids, categories) |
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PickledCorpusReader.docs | (self, fileids=None, categories=None) |
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async_setup_platform | (hass, config, async_add_entities, discovery_info=None) | Set up the mysensors climate. | Set up the mysensors climate. | async def async_setup_platform(hass, config, async_add_entities, discovery_info=None):
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MySensorsHVAC.supported_features | (self) | Return the list of supported features. | Return the list of supported features. | def supported_features(self):
"""Return the list of supported features."""
features = 0
set_req = self.gateway.const.SetReq
if set_req.V_HVAC_SPEED in self._values:
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MySensorsHVAC.assumed_state | (self) | Return True if unable to access real state of entity. | Return True if unable to access real state of entity. | def assumed_state(self):
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MySensorsHVAC.temperature_unit | (self) | Return the unit of measurement. | Return the unit of measurement. | def temperature_unit(self):
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MySensorsHVAC.current_temperature | (self) | Return the current temperature. | Return the current temperature. | def current_temperature(self):
"""Return the current temperature."""
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MySensorsHVAC.target_temperature | (self) | Return the temperature we try to reach. | Return the temperature we try to reach. | def target_temperature(self):
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MySensorsHVAC.target_temperature_high | (self) | Return the highbound target temperature we try to reach. | Return the highbound target temperature we try to reach. | def target_temperature_high(self):
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MySensorsHVAC.target_temperature_low | (self) | Return the lowbound target temperature we try to reach. | Return the lowbound target temperature we try to reach. | def target_temperature_low(self):
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MySensorsHVAC.hvac_mode | (self) | Return current operation ie. heat, cool, idle. | Return current operation ie. heat, cool, idle. | def hvac_mode(self):
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MySensorsHVAC.hvac_modes | (self) | List of available operation modes. | List of available operation modes. | def hvac_modes(self):
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MySensorsHVAC.fan_mode | (self) | Return the fan setting. | Return the fan setting. | def fan_mode(self):
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MySensorsHVAC.fan_modes | (self) | List of available fan modes. | List of available fan modes. | def fan_modes(self):
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MySensorsHVAC.async_set_temperature | (self, **kwargs) | Set new target temperature. | Set new target temperature. | async def async_set_temperature(self, **kwargs):
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set_req = self.gateway.const.SetReq
temp = kwargs.get(ATTR_TEMPERATURE)
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MySensorsHVAC.async_set_fan_mode | (self, fan_mode) | Set new target temperature. | Set new target temperature. | async def async_set_fan_mode(self, fan_mode):
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set_req = self.gateway.const.SetReq
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MySensorsHVAC.async_set_hvac_mode | (self, hvac_mode) | Set new target temperature. | Set new target temperature. | async def async_set_hvac_mode(self, hvac_mode):
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MySensorsHVAC.async_update | (self) | Update the controller with the latest value from a sensor. | Update the controller with the latest value from a sensor. | async def async_update(self):
"""Update the controller with the latest value from a sensor."""
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194,
85
] | python | en | ['en', 'en', 'en'] | True |
async_setup | (hass, config) | Initialize of The Things Network component. | Initialize of The Things Network component. | async def async_setup(hass, config):
"""Initialize of The Things Network component."""
conf = config[DOMAIN]
app_id = conf.get(CONF_APP_ID)
access_key = conf.get(CONF_ACCESS_KEY)
hass.data[DATA_TTN] = {TTN_ACCESS_KEY: access_key, TTN_APP_ID: app_id}
return True | [
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load_tf_weights_in_convbert | (model, config, tf_checkpoint_path) | Load tf checkpoints in a pytorch model. | Load tf checkpoints in a pytorch model. | def load_tf_weights_in_convbert(model, config, tf_checkpoint_path):
"""Load tf checkpoints in a pytorch model."""
try:
import tensorflow as tf
except ImportError:
logger.error(
"Loading a TensorFlow model in PyTorch, requires TensorFlow to be installed. Please see "
"... | [
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182,
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] | python | en | ['en', 'en', 'en'] | True |
ConvBertPreTrainedModel._init_weights | (self, module) | Initialize the weights | Initialize the weights | def _init_weights(self, module):
""" Initialize the weights """
if isinstance(module, nn.Linear):
# Slightly different from the TF version which uses truncated_normal for initialization
# cf https://github.com/pytorch/pytorch/pull/5617
module.weight.data.normal_(mean=... | [
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... | [
239,
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253,
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] | python | en | ['en', 'en', 'en'] | True |
get_scanner | (hass, config) | Validate the configuration and return a DD-WRT scanner. | Validate the configuration and return a DD-WRT scanner. | def get_scanner(hass, config):
"""Validate the configuration and return a DD-WRT scanner."""
try:
return DdWrtDeviceScanner(config[DOMAIN])
except ConnectionError:
return None | [
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] | python | en | ['en', 'en', 'en'] | True |
_parse_ddwrt_response | (data_str) | Parse the DD-WRT data format. | Parse the DD-WRT data format. | def _parse_ddwrt_response(data_str):
"""Parse the DD-WRT data format."""
return dict(_DDWRT_DATA_REGEX.findall(data_str)) | [
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167,
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169,
52
] | python | en | ['en', 'en', 'en'] | True |
DdWrtDeviceScanner.__init__ | (self, config) | Initialize the DD-WRT scanner. | Initialize the DD-WRT scanner. | def __init__(self, config):
"""Initialize the DD-WRT scanner."""
self.protocol = "https" if config[CONF_SSL] else "http"
self.verify_ssl = config[CONF_VERIFY_SSL]
self.host = config[CONF_HOST]
self.username = config[CONF_USERNAME]
self.password = config[CONF_PASSWORD]
... | [
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] | [
72,
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] | python | en | ['en', 'en', 'en'] | True |
DdWrtDeviceScanner.scan_devices | (self) | Scan for new devices and return a list with found device IDs. | Scan for new devices and return a list with found device IDs. | def scan_devices(self):
"""Scan for new devices and return a list with found device IDs."""
self._update_info()
return self.last_results | [
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32
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DdWrtDeviceScanner.get_device_name | (self, device) | Return the name of the given device or None if we don't know. | Return the name of the given device or None if we don't know. | def get_device_name(self, device):
"""Return the name of the given device or None if we don't know."""
# If not initialised and not already scanned and not found.
if device not in self.mac2name:
url = f"{self.protocol}://{self.host}/Status_Lan.live.asp"
data = self.get_dd... | [
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] | [
109,
40
] | python | en | ['en', 'en', 'en'] | True |
DdWrtDeviceScanner._update_info | (self) | Ensure the information from the DD-WRT router is up to date.
Return boolean if scanning successful.
| Ensure the information from the DD-WRT router is up to date. | def _update_info(self):
"""Ensure the information from the DD-WRT router is up to date.
Return boolean if scanning successful.
"""
_LOGGER.debug("Checking ARP")
endpoint = "Wireless" if self.wireless_only else "Lan"
url = f"{self.protocol}://{self.host}/Status_{endpoint... | [
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142,
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] | python | en | ['en', 'en', 'en'] | True |
DdWrtDeviceScanner.get_ddwrt_data | (self, url) | Retrieve data from DD-WRT and return parsed result. | Retrieve data from DD-WRT and return parsed result. | def get_ddwrt_data(self, url):
"""Retrieve data from DD-WRT and return parsed result."""
try:
response = requests.get(
url,
auth=(self.username, self.password),
timeout=4,
verify=self.verify_ssl,
)
except req... | [
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] | [
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test_attributes | (hass) | Test weather attributes. | Test weather attributes. | async def test_attributes(hass):
"""Test weather attributes."""
assert await async_setup_component(
hass, weather.DOMAIN, {"weather": {"platform": "demo"}}
)
hass.config.units = METRIC_SYSTEM
await hass.async_block_till_done()
state = hass.states.get("weather.demo_weather_south")
as... | [
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] | [
54,
44
] | python | en | ['en', 'en', 'en'] | True |
test_temperature_convert | (hass) | Test temperature conversion. | Test temperature conversion. | async def test_temperature_convert(hass):
"""Test temperature conversion."""
assert await async_setup_component(
hass, weather.DOMAIN, {"weather": {"platform": "demo"}}
)
hass.config.units = METRIC_SYSTEM
await hass.async_block_till_done()
state = hass.states.get("weather.demo_weather_n... | [
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57,
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] | [
71,
52
] | python | en | ['en', 'la', 'en'] | True |
async_setup_entry | (hass: HomeAssistantType, config_entry: ConfigEntry) | Set up Huawei LTE component from config entry. | Set up Huawei LTE component from config entry. | async def async_setup_entry(hass: HomeAssistantType, config_entry: ConfigEntry) -> bool:
"""Set up Huawei LTE component from config entry."""
url = config_entry.data[CONF_URL]
# Override settings from YAML config, but only if they're changed in it
# Old values are stored as *_from_yaml in the config en... | [
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301,
0
] | [
450,
15
] | python | en | ['en', 'en', 'en'] | True |
async_unload_entry | (
hass: HomeAssistantType, config_entry: ConfigEntry
) | Unload config entry. | Unload config entry. | async def async_unload_entry(
hass: HomeAssistantType, config_entry: ConfigEntry
) -> bool:
"""Unload config entry."""
# Forward config entry unload to platforms
for domain in CONFIG_ENTRY_PLATFORMS:
await hass.config_entries.async_forward_entry_unload(config_entry, domain)
# Forget about ... | [
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"con... | [
453,
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] | [
466,
15
] | python | da | ['da', 'es', 'en'] | False |
async_setup | (hass: HomeAssistantType, config: ConfigType) | Set up Huawei LTE component. | Set up Huawei LTE component. | async def async_setup(hass: HomeAssistantType, config: ConfigType) -> bool:
"""Set up Huawei LTE component."""
# dicttoxml (used by huawei-lte-api) has uselessly verbose INFO level.
# https://github.com/quandyfactory/dicttoxml/issues/60
logging.getLogger("dicttoxml").setLevel(logging.WARNING)
# Ar... | [
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"# https://github.com/quandyfactory/dicttoxml/issues/60",
"logging",
".",
"g... | [
469,
0
] | [
549,
15
] | python | en | ['en', 'en', 'en'] | True |
async_signal_options_update | (
hass: HomeAssistantType, config_entry: ConfigEntry
) | Handle config entry options update. | Handle config entry options update. | async def async_signal_options_update(
hass: HomeAssistantType, config_entry: ConfigEntry
) -> None:
"""Handle config entry options update."""
async_dispatcher_send(hass, UPDATE_OPTIONS_SIGNAL, config_entry) | [
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] | [
556,
68
] | python | en | ['en', 'en', 'en'] | True |
async_migrate_entry | (
hass: HomeAssistantType, config_entry: ConfigEntry
) | Migrate config entry to new version. | Migrate config entry to new version. | async def async_migrate_entry(
hass: HomeAssistantType, config_entry: ConfigEntry
) -> bool:
"""Migrate config entry to new version."""
if config_entry.version == 1:
options = dict(config_entry.options)
recipient = options.get(CONF_RECIPIENT)
if isinstance(recipient, str):
... | [
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... | [
559,
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] | [
571,
15
] | python | en | ['en', 'en', 'en'] | True |
SimpliSafeFlowHandler.__init__ | (self) | Initialize the config flow. | Initialize the config flow. | def __init__(self):
"""Initialize the config flow."""
self.full_data_schema = vol.Schema(
{
vol.Required(CONF_USERNAME): str,
vol.Required(CONF_PASSWORD): str,
vol.Optional(CONF_CODE): str,
}
)
self.password_data_sch... | [
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"v... | [
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] | [
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] | python | en | ['en', 'en', 'en'] | True |
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