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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
BloomSkySensor.__init__ | (self, bs, device, sensor_name) | Initialize a BloomSky sensor. | Initialize a BloomSky sensor. | def __init__(self, bs, device, sensor_name):
"""Initialize a BloomSky sensor."""
self._bloomsky = bs
self._device_id = device["DeviceID"]
self._sensor_name = sensor_name
self._name = f"{device['DeviceName']} {sensor_name}"
self._state = None
self._unique_id = f"{s... | [
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BloomSkySensor.unique_id | (self) | Return a unique ID. | Return a unique ID. | def unique_id(self):
"""Return a unique ID."""
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BloomSkySensor.name | (self) | Return the name of the BloomSky device and this sensor. | Return the name of the BloomSky device and this sensor. | def name(self):
"""Return the name of the BloomSky device and this sensor."""
return self._name | [
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BloomSkySensor.state | (self) | Return the current state, eg. value, of this sensor. | Return the current state, eg. value, of this sensor. | def state(self):
"""Return the current state, eg. value, of this sensor."""
return self._state | [
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BloomSkySensor.unit_of_measurement | (self) | Return the sensor units. | Return the sensor units. | def unit_of_measurement(self):
"""Return the sensor units."""
if self._bloomsky.is_metric:
return SENSOR_UNITS_METRIC.get(self._sensor_name, None)
return SENSOR_UNITS_IMPERIAL.get(self._sensor_name, None) | [
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BloomSkySensor.update | (self) | Request an update from the BloomSky API. | Request an update from the BloomSky API. | def update(self):
"""Request an update from the BloomSky API."""
self._bloomsky.refresh_devices()
state = self._bloomsky.devices[self._device_id]["Data"][self._sensor_name]
if self._sensor_name in FORMAT_NUMBERS:
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setup_platform | (hass, config, add_entities, discovery_info=None) | Set up the CPU speed sensor. | Set up the CPU speed sensor. | def setup_platform(hass, config, add_entities, discovery_info=None):
"""Set up the CPU speed sensor."""
name = config[CONF_NAME]
add_entities([CpuSpeedSensor(name)], True) | [
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CpuSpeedSensor.__init__ | (self, name) | Initialize the CPU sensor. | Initialize the CPU sensor. | def __init__(self, name):
"""Initialize the CPU sensor."""
self._name = name
self._state = None
self.info = None | [
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CpuSpeedSensor.name | (self) | Return the name of the sensor. | Return the name of the sensor. | def name(self):
"""Return the name of the sensor."""
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CpuSpeedSensor.state | (self) | Return the state of the sensor. | Return the state of the sensor. | def state(self):
"""Return the state of the sensor."""
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CpuSpeedSensor.unit_of_measurement | (self) | Return the unit the value is expressed in. | Return the unit the value is expressed in. | def unit_of_measurement(self):
"""Return the unit the value is expressed in."""
return FREQUENCY_GIGAHERTZ | [
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CpuSpeedSensor.device_state_attributes | (self) | Return the state attributes. | Return the state attributes. | def device_state_attributes(self):
"""Return the state attributes."""
if self.info is not None:
attrs = {
ATTR_ARCH: self.info["arch_string_raw"],
ATTR_BRAND: self.info["brand_raw"],
}
if HZ_ADVERTISED in self.info:
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CpuSpeedSensor.icon | (self) | Return the icon to use in the frontend, if any. | Return the icon to use in the frontend, if any. | def icon(self):
"""Return the icon to use in the frontend, if any."""
return ICON | [
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CpuSpeedSensor.update | (self) | Get the latest data and updates the state. | Get the latest data and updates the state. | def update(self):
"""Get the latest data and updates the state."""
self.info = cpuinfo.get_cpu_info()
if HZ_ACTUAL in self.info:
self._state = round(float(self.info[HZ_ACTUAL][0]) / 10 ** 9, 2)
else:
self._state = None | [
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BaseMutator.mutables | (self) |
A generator of all modules inheriting :class:`~nni.nas.pytorch.mutables.Mutable`.
Modules are yielded in the order that they are defined in ``__init__``.
For mutables with their keys appearing multiple times, only the first one will appear.
|
A generator of all modules inheriting :class:`~nni.nas.pytorch.mutables.Mutable`.
Modules are yielded in the order that they are defined in ``__init__``.
For mutables with their keys appearing multiple times, only the first one will appear.
| def mutables(self):
"""
A generator of all modules inheriting :class:`~nni.nas.pytorch.mutables.Mutable`.
Modules are yielded in the order that they are defined in ``__init__``.
For mutables with their keys appearing multiple times, only the first one will appear.
"""
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BaseMutator.forward | (self, *inputs) |
Warnings
--------
Don't call forward of a mutator.
|
Warnings
--------
Don't call forward of a mutator.
| def forward(self, *inputs):
"""
Warnings
--------
Don't call forward of a mutator.
"""
raise RuntimeError("Forward is undefined for mutators.") | [
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BaseMutator.enter_mutable_scope | (self, mutable_scope) |
Callback when forward of a MutableScope is entered.
Parameters
----------
mutable_scope : MutableScope
The mutable scope that is entered.
|
Callback when forward of a MutableScope is entered. | def enter_mutable_scope(self, mutable_scope):
"""
Callback when forward of a MutableScope is entered.
Parameters
----------
mutable_scope : MutableScope
The mutable scope that is entered.
"""
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BaseMutator.exit_mutable_scope | (self, mutable_scope) |
Callback when forward of a MutableScope is exited.
Parameters
----------
mutable_scope : MutableScope
The mutable scope that is exited.
|
Callback when forward of a MutableScope is exited. | def exit_mutable_scope(self, mutable_scope):
"""
Callback when forward of a MutableScope is exited.
Parameters
----------
mutable_scope : MutableScope
The mutable scope that is exited.
"""
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BaseMutator.on_forward_layer_choice | (self, mutable, *args, **kwargs) |
Callbacks of forward in LayerChoice.
Parameters
----------
mutable : nni.nas.pytorch.mutables.LayerChoice
Module whose forward is called.
args : list of torch.Tensor
The arguments of its forward function.
kwargs : dict
The keyword arg... |
Callbacks of forward in LayerChoice. | def on_forward_layer_choice(self, mutable, *args, **kwargs):
"""
Callbacks of forward in LayerChoice.
Parameters
----------
mutable : nni.nas.pytorch.mutables.LayerChoice
Module whose forward is called.
args : list of torch.Tensor
The arguments of... | [
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BaseMutator.on_forward_input_choice | (self, mutable, tensor_list) |
Callbacks of forward in InputChoice.
Parameters
----------
mutable : nni.nas.pytorch.mutables.InputChoice
Mutable that is called.
tensor_list : list of torch.Tensor
The arguments mutable is called with.
Returns
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Callbacks of forward in InputChoice. | def on_forward_input_choice(self, mutable, tensor_list):
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Callbacks of forward in InputChoice.
Parameters
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Mutable that is called.
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BaseMutator.export | (self) |
Export the data of all decisions. This should output the decisions of all the mutables, so that the whole
network can be fully determined with these decisions for further training from scratch.
Returns
-------
dict
Mappings from mutable keys to decisions.
|
Export the data of all decisions. This should output the decisions of all the mutables, so that the whole
network can be fully determined with these decisions for further training from scratch. | def export(self):
"""
Export the data of all decisions. This should output the decisions of all the mutables, so that the whole
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Returns
-------
dict
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PFLDInference.__init__ | (self, lookup_table, num_points=106) |
Parameters
----------
lookup_table : class
to manage the candidate ops, layer information and layer perf
num_points : int
the number of landmarks for prediction
|
Parameters
----------
lookup_table : class
to manage the candidate ops, layer information and layer perf
num_points : int
the number of landmarks for prediction
| def __init__(self, lookup_table, num_points=106):
"""
Parameters
----------
lookup_table : class
to manage the candidate ops, layer information and layer perf
num_points : int
the number of landmarks for prediction
"""
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PFLDInference.forward | (self, x) |
Parameters
----------
x : tensor
input image
Returns
-------
output: tensor
the predicted landmarks
output: tensor
the intermediate features
|
Parameters
----------
x : tensor
input image | def forward(self, x):
"""
Parameters
----------
x : tensor
input image
Returns
-------
output: tensor
the predicted landmarks
output: tensor
the intermediate features
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x, y1 = self.stem(x)
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AuxiliaryNet.forward | (self, x) |
Parameters
----------
x : tensor
input intermediate features
Returns
-------
output: tensor
the predicted pose angles
|
Parameters
----------
x : tensor
input intermediate features | def forward(self, x):
"""
Parameters
----------
x : tensor
input intermediate features
Returns
-------
output: tensor
the predicted pose angles
"""
x = self.conv1(x)
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get_service | (hass, config, discovery_info=None) | Get the Synology Chat notification service. | Get the Synology Chat notification service. | def get_service(hass, config, discovery_info=None):
"""Get the Synology Chat notification service."""
resource = config.get(CONF_RESOURCE)
verify_ssl = config.get(CONF_VERIFY_SSL)
return SynologyChatNotificationService(resource, verify_ssl) | [
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SynologyChatNotificationService.__init__ | (self, resource, verify_ssl) | Initialize the service. | Initialize the service. | def __init__(self, resource, verify_ssl):
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self._resource = resource
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SynologyChatNotificationService.send_message | (self, message="", **kwargs) | Send a message to a user. | Send a message to a user. | def send_message(self, message="", **kwargs):
"""Send a message to a user."""
data = {"text": message}
extended_data = kwargs.get(ATTR_DATA)
file_url = extended_data.get(ATTR_FILE_URL) if extended_data else None
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async_setup_entry | (hass, config_entry, async_add_entities) | Set up a Axis light. | Set up a Axis light. | async def async_setup_entry(hass, config_entry, async_add_entities):
"""Set up a Axis light."""
device = hass.data[AXIS_DOMAIN][config_entry.unique_id]
if not device.api.vapix.light_control:
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@callback
def async_add_sensor(event_id):
"""Add light from Axis device."""
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AxisLight.__init__ | (self, event, device) | Initialize the Axis light. | Initialize the Axis light. | def __init__(self, event, device):
"""Initialize the Axis light."""
super().__init__(event, device)
self.light_id = f"led{self.event.id}"
self.current_intensity = 0
self.max_intensity = 0
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AxisLight.async_added_to_hass | (self) | Subscribe lights events. | Subscribe lights events. | async def async_added_to_hass(self) -> None:
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await super().async_added_to_hass()
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AxisLight.supported_features | (self) | Flag supported features. | Flag supported features. | def supported_features(self):
"""Flag supported features."""
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AxisLight.name | (self) | Return the name of the light. | Return the name of the light. | def name(self):
"""Return the name of the light."""
light_type = self.device.api.vapix.light_control[self.light_id].light_type
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AxisLight.is_on | (self) | Return true if light is on. | Return true if light is on. | def is_on(self):
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AxisLight.brightness | (self) | Return the brightness of this light between 0..255. | Return the brightness of this light between 0..255. | def brightness(self):
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AxisLight.async_turn_on | (self, **kwargs) | Turn on light. | Turn on light. | async def async_turn_on(self, **kwargs):
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AxisLight.async_turn_off | (self, **kwargs) | Turn off light. | Turn off light. | async def async_turn_off(self, **kwargs):
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AxisLight.async_update | (self) | Update brightness. | Update brightness. | async def async_update(self):
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AxisLight.should_poll | (self) | Brightness needs polling. | Brightness needs polling. | def should_poll(self):
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async_register | (hass: HomeAssistantType, handler: "IntentHandler") | Register an intent with Home Assistant. | Register an intent with Home Assistant. | def async_register(hass: HomeAssistantType, handler: "IntentHandler") -> None:
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async_handle | (
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async_match_state | (
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) | Find a state that matches the name. | Find a state that matches the name. | def async_match_state(
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async_test_feature | (state: State, feature: int, feature_name: str) | Test is state supports a feature. | Test is state supports a feature. | def async_test_feature(state: State, feature: int, feature_name: str) -> None:
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_fuzzymatch | (name: str, items: Iterable[T], key: Callable[[T], str]) | Fuzzy matching function. | Fuzzy matching function. | def _fuzzymatch(name: str, items: Iterable[T], key: Callable[[T], str]) -> Optional[T]:
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IntentHandler.async_can_handle | (self, intent_obj: "Intent") | Test if an intent can be handled. | Test if an intent can be handled. | def async_can_handle(self, intent_obj: "Intent") -> bool:
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IntentHandler.async_validate_slots | (self, slots: _SlotsType) | Validate slot information. | Validate slot information. | def async_validate_slots(self, slots: _SlotsType) -> _SlotsType:
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IntentHandler.async_handle | (self, intent_obj: "Intent") | Handle the intent. | Handle the intent. | async def async_handle(self, intent_obj: "Intent") -> "IntentResponse":
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IntentHandler.__repr__ | (self) | Represent a string of an intent handler. | Represent a string of an intent handler. | def __repr__(self) -> str:
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ServiceIntentHandler.__init__ | (
self, intent_type: str, domain: str, service: str, speech: str
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ServiceIntentHandler.async_handle | (self, intent_obj: "Intent") | Handle the hass intent. | Handle the hass intent. | async def async_handle(self, intent_obj: "Intent") -> "IntentResponse":
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Intent.__init__ | (
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slots: _SlotsType,
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Intent.create_response | (self) | Create a response. | Create a response. | def create_response(self) -> "IntentResponse":
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IntentResponse.__init__ | (self, intent: Optional[Intent] = None) | Initialize an IntentResponse. | Initialize an IntentResponse. | def __init__(self, intent: Optional[Intent] = None) -> None:
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IntentResponse.async_set_speech | (
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IntentResponse.async_set_card | (
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IntentResponse.as_dict | (self) | Return a dictionary representation of an intent response. | Return a dictionary representation of an intent response. | def as_dict(self) -> Dict[str, Dict[str, Dict[str, Any]]]:
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mock_disco | () | Mock discovery service. | Mock discovery service. | def mock_disco():
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test_not_found | (hass, mock_disco) | Test not finding iZone controller. | Test not finding iZone controller. | async def test_not_found(hass, mock_disco):
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test_found | (hass, mock_disco) | Test not finding iZone controller. | Test not finding iZone controller. | async def test_found(hass, mock_disco):
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async_setup_entry | (
hass: HomeAssistantType, entry: ConfigEntry, async_add_entities
) | Set up ESPHome fans based on a config entry. | Set up ESPHome fans based on a config entry. | async def async_setup_entry(
hass: HomeAssistantType, entry: ConfigEntry, async_add_entities
) -> None:
"""Set up ESPHome fans based on a config entry."""
await platform_async_setup_entry(
hass,
entry,
async_add_entities,
component_key="fan",
info_type=FanInfo,
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EsphomeFan.async_set_speed | (self, speed: str) | Set the speed of the fan. | Set the speed of the fan. | async def async_set_speed(self, speed: str) -> None:
"""Set the speed of the fan."""
if speed == SPEED_OFF:
await self.async_turn_off()
return
await self._client.fan_command(
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EsphomeFan.async_turn_on | (self, speed: Optional[str] = None, **kwargs) | Turn on the fan. | Turn on the fan. | async def async_turn_on(self, speed: Optional[str] = None, **kwargs) -> None:
"""Turn on the fan."""
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EsphomeFan.async_turn_off | (self, **kwargs) | Turn off the fan. | Turn off the fan. | async def async_turn_off(self, **kwargs) -> None:
"""Turn off the fan."""
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EsphomeFan.async_oscillate | (self, oscillating: bool) | Oscillate the fan. | Oscillate the fan. | async def async_oscillate(self, oscillating: bool) -> None:
"""Oscillate the fan."""
await self._client.fan_command(
key=self._static_info.key, oscillating=oscillating
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EsphomeFan.is_on | (self) | Return true if the entity is on. | Return true if the entity is on. | def is_on(self) -> Optional[bool]:
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EsphomeFan.speed | (self) | Return the current speed. | Return the current speed. | def speed(self) -> Optional[str]:
"""Return the current speed."""
if not self._static_info.supports_speed:
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return _fan_speeds.from_esphome(self._state.speed) | [
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EsphomeFan.oscillating | (self) | Return the oscillation state. | Return the oscillation state. | def oscillating(self) -> None:
"""Return the oscillation state."""
if not self._static_info.supports_oscillation:
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EsphomeFan.speed_list | (self) | Get the list of available speeds. | Get the list of available speeds. | def speed_list(self) -> Optional[List[str]]:
"""Get the list of available speeds."""
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EsphomeFan.supported_features | (self) | Flag supported features. | Flag supported features. | def supported_features(self) -> int:
"""Flag supported features."""
flags = 0
if self._static_info.supports_oscillation:
flags |= SUPPORT_OSCILLATE
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async_setup_entry | (hass, config_entry, async_add_entities) | Set up Z-Wave Fan from Config Entry. | Set up Z-Wave Fan from Config Entry. | async def async_setup_entry(hass, config_entry, async_add_entities):
"""Set up Z-Wave Fan from Config Entry."""
@callback
def async_add_fan(fan):
"""Add Z-Wave Fan."""
async_add_entities([fan])
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get_device | (values, **kwargs) | Create Z-Wave entity device. | Create Z-Wave entity device. | def get_device(values, **kwargs):
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ZwaveFan.__init__ | (self, values) | Initialize the Z-Wave fan device. | Initialize the Z-Wave fan device. | def __init__(self, values):
"""Initialize the Z-Wave fan device."""
ZWaveDeviceEntity.__init__(self, values, DOMAIN)
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ZwaveFan.update_properties | (self) | Handle data changes for node values. | Handle data changes for node values. | def update_properties(self):
"""Handle data changes for node values."""
value = math.ceil(self.values.primary.data * 3 / 100)
self._state = VALUE_TO_SPEED[value] | [
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ZwaveFan.set_speed | (self, speed) | Set the speed of the fan. | Set the speed of the fan. | def set_speed(self, speed):
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ZwaveFan.turn_on | (self, speed=None, **kwargs) | Turn the device on. | Turn the device on. | def turn_on(self, speed=None, **kwargs):
"""Turn the device on."""
if speed is None:
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ZwaveFan.turn_off | (self, **kwargs) | Turn the device off. | Turn the device off. | def turn_off(self, **kwargs):
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ZwaveFan.speed | (self) | Return the current speed. | Return the current speed. | def speed(self):
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ZwaveFan.speed_list | (self) | Get the list of available speeds. | Get the list of available speeds. | def speed_list(self):
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ZwaveFan.supported_features | (self) | Flag supported features. | Flag supported features. | def supported_features(self):
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adjust_learning_rate | (optimizer, decay=0.1) | Sets the learning rate to the initial LR decayed by 0.5 every 20 epochs | Sets the learning rate to the initial LR decayed by 0.5 every 20 epochs | def adjust_learning_rate(optimizer, decay=0.1):
"""Sets the learning rate to the initial LR decayed by 0.5 every 20 epochs"""
for param_group in optimizer.param_groups:
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GrassAzureExecutor.create | (create_deployment: dict) | Create MARO Cluster with create_deployment.
Args:
create_deployment (dict): create_deployment of grass/azure. See lib/deployments/internal for reference.
Returns:
None.
| Create MARO Cluster with create_deployment. | def create(create_deployment: dict) -> None:
"""Create MARO Cluster with create_deployment.
Args:
create_deployment (dict): create_deployment of grass/azure. See lib/deployments/internal for reference.
Returns:
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GrassAzureExecutor._standardize_cluster_details | (create_deployment: dict) | Standardize cluster_details from create_deployment.
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create_deployment (dict): create_deployment of grass/azure. See lib/deployments/internal for reference.
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GrassAzureExecutor._create_resource_group | (cluster_details: dict) | Create the resource group if it does not exist.
Args:
cluster_details (dict): details of the cluster.
Returns:
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| Create the resource group if it does not exist. | def _create_resource_group(cluster_details: dict) -> None:
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GrassAzureExecutor._create_vnet | (cluster_details: dict) | Create vnet for the MARO Cluster.
Args:
cluster_details (dict): details of the MARO Cluster.
Returns:
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| Create vnet for the MARO Cluster. | def _create_vnet(cluster_details: dict) -> None:
"""Create vnet for the MARO Cluster.
Args:
cluster_details (dict): details of the MARO Cluster.
Returns:
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logger.info("Creating vnet")
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GrassAzureExecutor._build_node_image | (cluster_details: dict) | Build Azure Image for MARO Node.
The built image will contain required Node runtime environment including GPU support.
See https://docs.microsoft.com/en-us/azure/virtual-machines/linux/capture-image for reference.
Args:
cluster_details (dict): details of the MARO Cluster.
... | Build Azure Image for MARO Node. | def _build_node_image(cluster_details: dict) -> None:
"""Build Azure Image for MARO Node.
The built image will contain required Node runtime environment including GPU support.
See https://docs.microsoft.com/en-us/azure/virtual-machines/linux/capture-image for reference.
Args:
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GrassAzureExecutor._create_and_init_master | (cluster_details: dict) | Create and init MARO Master.
Args:
cluster_details (dict): details of the MARO Cluster.
Returns:
None.
| Create and init MARO Master. | def _create_and_init_master(cluster_details: dict) -> None:
"""Create and init MARO Master.
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cluster_details (dict): details of the MARO Cluster.
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GrassAzureExecutor._create_master_vm | (cluster_details: dict) | Create MARO Master VM.
Args:
cluster_details (dict): details of the MARO Cluster.
Returns:
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| Create MARO Master VM. | def _create_master_vm(cluster_details: dict) -> None:
"""Create MARO Master VM.
Args:
cluster_details (dict): details of the MARO Cluster.
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GrassAzureExecutor.delete | (self) | Delete the MARO Cluster.
Returns:
None.
| Delete the MARO Cluster. | def delete(self) -> None:
"""Delete the MARO Cluster.
Returns:
None.
"""
logger.info(f"Deleting cluster '{self.cluster_name}'")
# Get resource list
resource_list = AzureController.list_resources(resource_group=self.resource_group)
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GrassAzureExecutor.scale_node | (self, replicas: int, node_size: str) | Scale up/down MARO Node using predefined Node Image.
Args:
replicas (int): desired number of MARO Node in specific node_size.
node_size (str): size of the MARO Node VM, see https://docs.microsoft.com/en-us/azure/virtual-machines/sizes
for reference.
Returns:
... | Scale up/down MARO Node using predefined Node Image. | def scale_node(self, replicas: int, node_size: str):
"""Scale up/down MARO Node using predefined Node Image.
Args:
replicas (int): desired number of MARO Node in specific node_size.
node_size (str): size of the MARO Node VM, see https://docs.microsoft.com/en-us/azure/virtual-mac... | [
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GrassAzureExecutor._create_nodes | (self, num: int, node_size: str) | Create MARO Nodes in parallel.
Args:
num (int): number of MARO Nodes (with specific node_size) to create.
node_size (str): size of the MARO Node VM.
Returns:
None.
| Create MARO Nodes in parallel. | def _create_nodes(self, num: int, node_size: str) -> None:
"""Create MARO Nodes in parallel.
Args:
num (int): number of MARO Nodes (with specific node_size) to create.
node_size (str): size of the MARO Node VM.
Returns:
None.
"""
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GrassAzureExecutor._create_node | (self, node_size: str) | Create a MARO Node.
Args:
node_size (str): size of the MARO Node VM.
Returns:
None.
| Create a MARO Node. | def _create_node(self, node_size: str) -> None:
"""Create a MARO Node.
Args:
node_size (str): size of the MARO Node VM.
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"""
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GrassAzureExecutor._delete_nodes | (self, num: int, node_size: str) | Delete MARO Nodes in parallel.
Args:
num (int): number of MARO Nodes (with specific node_size) to delete.
node_size (str): size of the MARO Node VM.
Returns:
None.
| Delete MARO Nodes in parallel. | def _delete_nodes(self, num: int, node_size: str) -> None:
"""Delete MARO Nodes in parallel.
Args:
num (int): number of MARO Nodes (with specific node_size) to delete.
node_size (str): size of the MARO Node VM.
Returns:
None.
"""
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GrassAzureExecutor._create_vm | (self, node_name: str, node_size: str) | Create MARO Node VM.
Args:
node_name (str): name of the MARO Node. Also the id of the MARO Node.
node_size (str): size of the MARO Node VM.
Returns:
dict: join_cluster_deployment that needed in "join cluster" operation.
See /lib/scripts/join_cluster.... | Create MARO Node VM. | def _create_vm(self, node_name: str, node_size: str) -> dict:
"""Create MARO Node VM.
Args:
node_name (str): name of the MARO Node. Also the id of the MARO Node.
node_size (str): size of the MARO Node VM.
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GrassAzureExecutor._delete_node | (self, node_name: str) | Delete the MARO Node.
Args:
node_name (str): name of the MARO Node.
Returns:
None.
| Delete the MARO Node. | def _delete_node(self, node_name: str) -> None:
"""Delete the MARO Node.
Args:
node_name (str): name of the MARO Node.
Returns:
None.
"""
logger.info(f"Deleting node '{node_name}'")
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GrassAzureExecutor._join_cluster | (self, node_details: dict) | Join the cluster using node_details.
Args:
node_details (str): details of the MARO Node.
Returns:
None.
| Join the cluster using node_details. | def _join_cluster(self, node_details: dict) -> None:
"""Join the cluster using node_details.
Args:
node_details (str): details of the MARO Node.
Returns:
None.
"""
node_name = node_details["name"]
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GrassAzureExecutor.start_node | (self, replicas: int, node_size: str) | Start MARO Node VMs in parallel.
Args:
replicas (int): number of MARO Node in specific node_size to start.
node_size (str): size of the MARO Node VM, see https://docs.microsoft.com/en-us/azure/virtual-machines/sizes
for reference.
Returns:
None.
... | Start MARO Node VMs in parallel. | def start_node(self, replicas: int, node_size: str):
"""Start MARO Node VMs in parallel.
Args:
replicas (int): number of MARO Node in specific node_size to start.
node_size (str): size of the MARO Node VM, see https://docs.microsoft.com/en-us/azure/virtual-machines/sizes
... | [
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GrassAzureExecutor._start_node | (self, node_name: str) | Start the MARO Node VM.
Args:
node_name (str): name of the MARO Node.
Returns:
None.
| Start the MARO Node VM. | def _start_node(self, node_name: str):
"""Start the MARO Node VM.
Args:
node_name (str): name of the MARO Node.
Returns:
None.
"""
logger.info(f"Starting node '{node_name}'")
# Start node vm
AzureController.start_vm(
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GrassAzureExecutor.stop_node | (self, replicas: int, node_size: str) | Stop MARO Node VMs in parallel.
Args:
replicas (int): number of MARO Node in specific node_size to stop.
node_size (str): size of the MARO Node VM,
see https://docs.microsoft.com/en-us/azure/virtual-machines/sizes for reference.
Returns:
None.
... | Stop MARO Node VMs in parallel. | def stop_node(self, replicas: int, node_size: str):
"""Stop MARO Node VMs in parallel.
Args:
replicas (int): number of MARO Node in specific node_size to stop.
node_size (str): size of the MARO Node VM,
see https://docs.microsoft.com/en-us/azure/virtual-machines/... | [
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GrassAzureExecutor._stop_node | (self, node_details: dict) | Stop MARO Node VM.
Args:
node_details (dict): details of the MARO Node.
Returns:
None.
| Stop MARO Node VM. | def _stop_node(self, node_details: dict):
"""Stop MARO Node VM.
Args:
node_details (dict): details of the MARO Node.
Returns:
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"""
node_name = node_details["name"]
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# Stop node
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GrassAzureExecutor._get_node_size_to_spec | (self) | Get node_size to spec mapping of Azure VM.
Returns:
dict: node_size to spec mapping.
| Get node_size to spec mapping of Azure VM. | def _get_node_size_to_spec(self) -> dict:
"""Get node_size to spec mapping of Azure VM.
Returns:
dict: node_size to spec mapping.
"""
# List available sizes for VMs
specs = AzureController.list_vm_sizes(location=self.location)
# Get node_size_to_spec
... | [
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GrassAzureExecutor._count_running_containers | (node_details: dict) | Count running containers based on field "Status".
Args:
node_details (dict): details of the MARO Node.
Returns:
int: num of running containers.
| Count running containers based on field "Status". | def _count_running_containers(node_details: dict) -> int:
"""Count running containers based on field "Status".
Args:
node_details (dict): details of the MARO Node.
Returns:
int: num of running containers.
"""
# Extract details
containers_details ... | [
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