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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
test_invalid_name_does_not_create | (hass, caplog) | Test invalid name. | Test invalid name. | async def test_invalid_name_does_not_create(hass, caplog):
"""Test invalid name."""
await setup.async_setup_component(
hass,
"alarm_control_panel",
{
"alarm_control_panel": {
"platform": "template",
"panels": {
"bad name her... | [
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... | [
282,
0
] | [
324,
51
] | python | en | ['en', 'et', 'en'] | True |
test_invalid_panel_does_not_create | (hass, caplog) | Test invalid alarm control panel. | Test invalid alarm control panel. | async def test_invalid_panel_does_not_create(hass, caplog):
"""Test invalid alarm control panel."""
await setup.async_setup_component(
hass,
"alarm_control_panel",
{
"alarm_control_panel": {
"platform": "template",
"wibble": {"test_panel": "Inv... | [
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327,
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345,
59
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test_no_panels_does_not_create | (hass, caplog) | Test if there are no panels -> no creation. | Test if there are no panels -> no creation. | async def test_no_panels_does_not_create(hass, caplog):
"""Test if there are no panels -> no creation."""
await setup.async_setup_component(
hass,
"alarm_control_panel",
{"alarm_control_panel": {"platform": "template"}},
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await hass.async_block_till_done()
await hass.async_... | [
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348,
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361,
72
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test_name | (hass) | Test the accessibility of the name attribute. | Test the accessibility of the name attribute. | async def test_name(hass):
"""Test the accessibility of the name attribute."""
await setup.async_setup_component(
hass,
"alarm_control_panel",
{
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"platform": "template",
"panels": {
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"\"t... | [
364,
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409,
74
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test_arm_home_action | (hass) | Test arm home action. | Test arm home action. | async def test_arm_home_action(hass):
"""Test arm home action."""
await setup.async_setup_component(
hass,
"alarm_control_panel",
{
"alarm_control_panel": {
"platform": "template",
"panels": {
"test_template_panel": {
... | [
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... | [
412,
0
] | [
456,
34
] | python | en | ['en', 'en', 'en'] | True |
test_arm_away_action | (hass) | Test arm away action. | Test arm away action. | async def test_arm_away_action(hass):
"""Test arm away action."""
await setup.async_setup_component(
hass,
"alarm_control_panel",
{
"alarm_control_panel": {
"platform": "template",
"panels": {
"test_template_panel": {
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459,
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] | [
503,
34
] | python | en | ['en', 'en', 'en'] | True |
test_arm_night_action | (hass) | Test arm night action. | Test arm night action. | async def test_arm_night_action(hass):
"""Test arm night action."""
await setup.async_setup_component(
hass,
"alarm_control_panel",
{
"alarm_control_panel": {
"platform": "template",
"panels": {
"test_template_panel": {
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... | [
506,
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] | [
550,
34
] | python | en | ['en', 'en', 'en'] | True |
test_disarm_action | (hass) | Test disarm action. | Test disarm action. | async def test_disarm_action(hass):
"""Test disarm action."""
await setup.async_setup_component(
hass,
"alarm_control_panel",
{
"alarm_control_panel": {
"platform": "template",
"panels": {
"test_template_panel": {
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"{... | [
553,
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] | [
597,
34
] | python | en | ['fr', 'en', 'en'] | True |
test_unique_id | (hass) | Test unique_id option only creates one alarm control panel per id. | Test unique_id option only creates one alarm control panel per id. | async def test_unique_id(hass):
"""Test unique_id option only creates one alarm control panel per id."""
await setup.async_setup_component(
hass,
"alarm_control_panel",
{
"alarm_control_panel": {
"platform": "template",
"panels": {
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... | [
600,
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] | [
626,
44
] | python | en | ['en', 'en', 'en'] | True |
async_setup_platform | (hass, config, async_add_entities, discovery_info) | Set up Netgear LTE sensor devices. | Set up Netgear LTE sensor devices. | async def async_setup_platform(hass, config, async_add_entities, discovery_info):
"""Set up Netgear LTE sensor devices."""
if discovery_info is None:
return
modem_data = hass.data[DATA_KEY].get_modem_data(discovery_info)
if not modem_data or not modem_data.data:
raise PlatformNotReady
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8,
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] | [
32,
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] | python | en | ['oc', 'fr', 'en'] | False |
LTESensor.unit_of_measurement | (self) | Return the unit of measurement. | Return the unit of measurement. | def unit_of_measurement(self):
"""Return the unit of measurement."""
return SENSOR_UNITS[self.sensor_type] | [
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SMSUnreadSensor.state | (self) | Return the state of the sensor. | Return the state of the sensor. | def state(self):
"""Return the state of the sensor."""
return sum(1 for x in self.modem_data.data.sms if x.unread) | [
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SMSTotalSensor.state | (self) | Return the state of the sensor. | Return the state of the sensor. | def state(self):
"""Return the state of the sensor."""
return len(self.modem_data.data.sms) | [
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UsageSensor.state | (self) | Return the state of the sensor. | Return the state of the sensor. | def state(self):
"""Return the state of the sensor."""
return round(self.modem_data.data.usage / 1024 ** 2, 1) | [
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GenericSensor.state | (self) | Return the state of the sensor. | Return the state of the sensor. | def state(self):
"""Return the state of the sensor."""
return getattr(self.modem_data.data, self.sensor_type) | [
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_async_reproduce_state | (
hass: HomeAssistantType,
state: State,
*,
context: Optional[Context] = None,
reproduce_options: Optional[Dict[str, Any]] = None,
) | Reproduce a single state. | Reproduce a single state. | async def _async_reproduce_state(
hass: HomeAssistantType,
state: State,
*,
context: Optional[Context] = None,
reproduce_options: Optional[Dict[str, Any]] = None,
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async_reproduce_states | (
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states: Iterable[State],
*,
context: Optional[Context] = None,
reproduce_options: Optional[Dict[str, Any]] = None,
) | Reproduce Input text states. | Reproduce Input text states. | async def async_reproduce_states(
hass: HomeAssistantType,
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*,
context: Optional[Context] = None,
reproduce_options: Optional[Dict[str, Any]] = None,
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"""Reproduce Input text states."""
# Reproduce states in parallel.
await asyncio.gather(
*(
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create_group | (hass, name) | Create a new person group.
This is a legacy helper method. Do not use it for new tests.
| Create a new person group. | def create_group(hass, name):
"""Create a new person group.
This is a legacy helper method. Do not use it for new tests.
"""
data = {ATTR_NAME: name}
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delete_group | (hass, name) | Delete a person group.
This is a legacy helper method. Do not use it for new tests.
| Delete a person group. | def delete_group(hass, name):
"""Delete a person group.
This is a legacy helper method. Do not use it for new tests.
"""
data = {ATTR_NAME: name}
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train_group | (hass, group) | Train a person group.
This is a legacy helper method. Do not use it for new tests.
| Train a person group. | def train_group(hass, group):
"""Train a person group.
This is a legacy helper method. Do not use it for new tests.
"""
data = {ATTR_GROUP: group}
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create_person | (hass, group, name) | Create a person in a group.
This is a legacy helper method. Do not use it for new tests.
| Create a person in a group. | def create_person(hass, group, name):
"""Create a person in a group.
This is a legacy helper method. Do not use it for new tests.
"""
data = {ATTR_GROUP: group, ATTR_NAME: name}
hass.services.call(DOMAIN, SERVICE_CREATE_PERSON, data) | [
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delete_person | (hass, group, name) | Delete a person in a group.
This is a legacy helper method. Do not use it for new tests.
| Delete a person in a group. | def delete_person(hass, group, name):
"""Delete a person in a group.
This is a legacy helper method. Do not use it for new tests.
"""
data = {ATTR_GROUP: group, ATTR_NAME: name}
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face_person | (hass, group, person, camera_entity) | Add a new face picture to a person.
This is a legacy helper method. Do not use it for new tests.
| Add a new face picture to a person. | def face_person(hass, group, person, camera_entity):
"""Add a new face picture to a person.
This is a legacy helper method. Do not use it for new tests.
"""
data = {ATTR_GROUP: group, ATTR_PERSON: person, ATTR_CAMERA_ENTITY: camera_entity}
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TestMicrosoftFaceSetup.setup_method | (self) | Set up things to be run when tests are started. | Set up things to be run when tests are started. | def setup_method(self):
"""Set up things to be run when tests are started."""
self.hass = get_test_home_assistant()
self.config = {mf.DOMAIN: {"api_key": "12345678abcdef"}}
self.endpoint_url = f"https://westus.{mf.FACE_API_URL}" | [
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TestMicrosoftFaceSetup.teardown_method | (self) | Stop everything that was started. | Stop everything that was started. | def teardown_method(self):
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TestMicrosoftFaceSetup.test_setup_component | (self, mock_update) | Set up component. | Set up component. | def test_setup_component(self, mock_update):
"""Set up component."""
with assert_setup_component(3, mf.DOMAIN):
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TestMicrosoftFaceSetup.test_setup_component_wrong_api_key | (self, mock_update) | Set up component without api key. | Set up component without api key. | def test_setup_component_wrong_api_key(self, mock_update):
"""Set up component without api key."""
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"... | [
105,
4
] | [
108,
66
] | python | en | ['en', 'zu', 'en'] | True |
TestMicrosoftFaceSetup.test_setup_component_test_service | (self, mock_update) | Set up component. | Set up component. | def test_setup_component_test_service(self, mock_update):
"""Set up component."""
with assert_setup_component(3, mf.DOMAIN):
setup_component(self.hass, mf.DOMAIN, self.config)
assert self.hass.services.has_service(mf.DOMAIN, "create_group")
assert self.hass.services.has_serv... | [
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TestMicrosoftFaceSetup.test_setup_component_test_entities | (self, aioclient_mock) | Set up component. | Set up component. | def test_setup_component_test_entities(self, aioclient_mock):
"""Set up component."""
aioclient_mock.get(
self.endpoint_url.format("persongroups"),
text=load_fixture("microsoft_face_persongroups.json"),
)
aioclient_mock.get(
self.endpoint_url.format("p... | [
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TestMicrosoftFaceSetup.test_service_groups | (self, mock_update, aioclient_mock) | Set up component, test groups services. | Set up component, test groups services. | def test_service_groups(self, mock_update, aioclient_mock):
"""Set up component, test groups services."""
aioclient_mock.put(
self.endpoint_url.format("persongroups/service_group"),
status=200,
text="{}",
)
aioclient_mock.delete(
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198,
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TestMicrosoftFaceSetup.test_service_person | (self, aioclient_mock) | Set up component, test person services. | Set up component, test person services. | def test_service_person(self, aioclient_mock):
"""Set up component, test person services."""
aioclient_mock.get(
self.endpoint_url.format("persongroups"),
text=load_fixture("microsoft_face_persongroups.json"),
)
aioclient_mock.get(
self.endpoint_url.fo... | [
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251,
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TestMicrosoftFaceSetup.test_service_train | (self, mock_update, aioclient_mock) | Set up component, test train groups services. | Set up component, test train groups services. | def test_service_train(self, mock_update, aioclient_mock):
"""Set up component, test train groups services."""
with assert_setup_component(3, mf.DOMAIN):
setup_component(self.hass, mf.DOMAIN, self.config)
aioclient_mock.post(
self.endpoint_url.format("persongroups/servic... | [
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271,
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TestMicrosoftFaceSetup.test_service_face | (self, camera_mock, aioclient_mock) | Set up component, test person face services. | Set up component, test person face services. | def test_service_face(self, camera_mock, aioclient_mock):
"""Set up component, test person face services."""
aioclient_mock.get(
self.endpoint_url.format("persongroups"),
text=load_fixture("microsoft_face_persongroups.json"),
)
aioclient_mock.get(
self... | [
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277,
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] | [
311,
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TestMicrosoftFaceSetup.test_service_status_400 | (self, mock_update, aioclient_mock) | Set up component, test groups services with error. | Set up component, test groups services with error. | def test_service_status_400(self, mock_update, aioclient_mock):
"""Set up component, test groups services with error."""
aioclient_mock.put(
self.endpoint_url.format("persongroups/service_group"),
status=400,
text="{'error': {'message': 'Error'}}",
)
... | [
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] | [
333,
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TestMicrosoftFaceSetup.test_service_status_timeout | (self, mock_update, aioclient_mock) | Set up component, test groups services with timeout. | Set up component, test groups services with timeout. | def test_service_status_timeout(self, mock_update, aioclient_mock):
"""Set up component, test groups services with timeout."""
aioclient_mock.put(
self.endpoint_url.format("persongroups/service_group"),
status=400,
exc=asyncio.TimeoutError(),
)
with a... | [
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"ex... | [
339,
4
] | [
355,
50
] | python | en | ['en', 'en', 'en'] | True |
nonnegative_softmax_kernel_feature_creator | (
data, projection_matrix, attention_dims_t, batch_dims_t, precision, is_query, normalize_data=True, eps=0.0001
) |
Constructs nonnegative kernel features for fast softmax attention
Args:
data: input for which features are computes
projection_matrix: random matrix used to compute features
attention_dims_t: tuple of attention dimensions
batch_dims_t: tuple of batch dimensions
precision: precisi... |
Constructs nonnegative kernel features for fast softmax attention | def nonnegative_softmax_kernel_feature_creator(
data, projection_matrix, attention_dims_t, batch_dims_t, precision, is_query, normalize_data=True, eps=0.0001
):
"""
Constructs nonnegative kernel features for fast softmax attention
Args:
data: input for which features are computes
projection... | [
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40,
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91,
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sincos_softmax_kernel_feature_creator | (
data, projection_matrix, attention_dims_t, batch_dims_t, precision, normalize_data=True
) |
Constructs kernel sin-cos features for fast softmax attention
Args:
data: input for which features are computes
projection_matrix: random matrix used to compute features
attention_dims_t: tuple of attention dimensions
batch_dims_t: tuple of batch dimensions
precision: precision p... |
Constructs kernel sin-cos features for fast softmax attention | def sincos_softmax_kernel_feature_creator(
data, projection_matrix, attention_dims_t, batch_dims_t, precision, normalize_data=True
):
"""
Constructs kernel sin-cos features for fast softmax attention
Args:
data: input for which features are computes
projection_matrix: random matrix used to ... | [
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94,
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141,
21
] | python | en | ['en', 'error', 'th'] | False |
generalized_kernel_feature_creator | (
data, projection_matrix, batch_dims_t, precision, kernel_fn, kernel_epsilon, normalize_data
) |
Constructs kernel features for fast generalized attention
Args:
data: input for which features are computes
projection_matrix: matrix used to compute features
batch_dims_t: tuple of batch dimensions
precision: precision parameter
kernel_fn: kernel function used
kernel_epsil... |
Constructs kernel features for fast generalized attention | def generalized_kernel_feature_creator(
data, projection_matrix, batch_dims_t, precision, kernel_fn, kernel_epsilon, normalize_data
):
"""
Constructs kernel features for fast generalized attention
Args:
data: input for which features are computes
projection_matrix: matrix used to compute fe... | [
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144,
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179,
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make_fast_softmax_attention | (
qkv_dim,
renormalize_attention=True,
numerical_stabilizer=0.000001,
nb_features=256,
ortho_features=True,
ortho_scaling=0.0,
redraw_features=True,
unidirectional=False,
nonnegative_features=True,
lax_scan_unroll=1,
) | Construct a fast softmax attention method. | Construct a fast softmax attention method. | def make_fast_softmax_attention(
qkv_dim,
renormalize_attention=True,
numerical_stabilizer=0.000001,
nb_features=256,
ortho_features=True,
ortho_scaling=0.0,
redraw_features=True,
unidirectional=False,
nonnegative_features=True,
lax_scan_unroll=1,
):
"""Construct a fast softm... | [
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182,
0
] | [
240,
23
] | python | en | ['en', 'en', 'en'] | True |
make_fast_generalized_attention | (
qkv_dim,
renormalize_attention=True,
numerical_stabilizer=0.0,
nb_features=256,
features_type="deterministic",
kernel_fn=jax.nn.relu,
kernel_epsilon=0.001,
redraw_features=False,
unidirectional=False,
lax_scan_unroll=1,
) | Construct a fast generalized attention menthod. | Construct a fast generalized attention menthod. | def make_fast_generalized_attention(
qkv_dim,
renormalize_attention=True,
numerical_stabilizer=0.0,
nb_features=256,
features_type="deterministic",
kernel_fn=jax.nn.relu,
kernel_epsilon=0.001,
redraw_features=False,
unidirectional=False,
lax_scan_unroll=1,
):
"""Construct a f... | [
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243,
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284,
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FastAttention.dot_product_attention | (
self,
query,
key,
value,
dtype=jnp.float32,
bias=None,
axis=None,
broadcast_dropout=True,
dropout_rng=None,
dropout_rate=0.0,
deterministic=False,
precision=None,
) |
Computes dot-product attention given query, key, and value. This is the core function for applying fast
approximate dot-product attention. It calculates the attention weights given query and key and combines the
values using the attention weights. This function supports multi-dimensional inputs... |
Computes dot-product attention given query, key, and value. This is the core function for applying fast
approximate dot-product attention. It calculates the attention weights given query and key and combines the
values using the attention weights. This function supports multi-dimensional inputs | def dot_product_attention(
self,
query,
key,
value,
dtype=jnp.float32,
bias=None,
axis=None,
broadcast_dropout=True,
dropout_rng=None,
dropout_rate=0.0,
deterministic=False,
precision=None,
):
"""
Compute... | [
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"... | [
360,
4
] | [
400,
52
] | python | en | ['en', 'error', 'th'] | False |
test_user_form | (hass, cfupdate_flow) | Test we get the user initiated form. | Test we get the user initiated form. | async def test_user_form(hass, cfupdate_flow):
"""Test we get the user initiated form."""
await async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.flow.async_init(
DOMAIN, context={CONF_SOURCE: SOURCE_USER}
)
assert result["type"] == RESULT_TYPE_FO... | [
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29,
0
] | [
79,
48
] | python | en | ['en', 'en', 'en'] | True |
test_user_form_cannot_connect | (hass, cfupdate_flow) | Test we handle cannot connect error. | Test we handle cannot connect error. | async def test_user_form_cannot_connect(hass, cfupdate_flow):
"""Test we handle cannot connect error."""
instance = cfupdate_flow.return_value
result = await hass.config_entries.flow.async_init(
DOMAIN, context={CONF_SOURCE: SOURCE_USER}
)
instance.get_zones.side_effect = CloudflareConnect... | [
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] | [
97,
57
] | python | en | ['en', 'en', 'en'] | True |
test_user_form_invalid_auth | (hass, cfupdate_flow) | Test we handle invalid auth error. | Test we handle invalid auth error. | async def test_user_form_invalid_auth(hass, cfupdate_flow):
"""Test we handle invalid auth error."""
instance = cfupdate_flow.return_value
result = await hass.config_entries.flow.async_init(
DOMAIN, context={CONF_SOURCE: SOURCE_USER}
)
instance.get_zones.side_effect = CloudflareAuthenticat... | [
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115,
55
] | python | de | ['de', 'et', 'en'] | False |
test_user_form_invalid_zone | (hass, cfupdate_flow) | Test we handle invalid zone error. | Test we handle invalid zone error. | async def test_user_form_invalid_zone(hass, cfupdate_flow):
"""Test we handle invalid zone error."""
instance = cfupdate_flow.return_value
result = await hass.config_entries.flow.async_init(
DOMAIN, context={CONF_SOURCE: SOURCE_USER}
)
instance.get_zones.side_effect = CloudflareZoneExcepti... | [
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test_user_form_unexpected_exception | (hass, cfupdate_flow) | Test we handle unexpected exception. | Test we handle unexpected exception. | async def test_user_form_unexpected_exception(hass, cfupdate_flow):
"""Test we handle unexpected exception."""
instance = cfupdate_flow.return_value
result = await hass.config_entries.flow.async_init(
DOMAIN, context={CONF_SOURCE: SOURCE_USER}
)
instance.get_zones.side_effect = Exception()... | [
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151,
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test_user_form_single_instance_allowed | (hass) | Test that configuring more than one instance is rejected. | Test that configuring more than one instance is rejected. | async def test_user_form_single_instance_allowed(hass):
"""Test that configuring more than one instance is rejected."""
entry = MockConfigEntry(domain=DOMAIN, data=ENTRY_CONFIG)
entry.add_to_hass(hass)
result = await hass.config_entries.flow.async_init(
DOMAIN,
context={CONF_SOURCE: SOU... | [
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shift_tokens_right | (input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int) |
Shift input ids one token to the right.
|
Shift input ids one token to the right.
| def shift_tokens_right(input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int):
"""
Shift input ids one token to the right.
"""
shifted_input_ids = input_ids.new_zeros(input_ids.shape)
shifted_input_ids[:, 1:] = input_ids[:, :-1].clone()
shifted_input_ids[:, 0] = decoder_start_t... | [
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_make_causal_mask | (input_ids_shape: torch.Size, dtype: torch.dtype, past_key_values_length: int = 0) |
Make causal mask used for bi-directional self-attention.
|
Make causal mask used for bi-directional self-attention.
| def _make_causal_mask(input_ids_shape: torch.Size, dtype: torch.dtype, past_key_values_length: int = 0):
"""
Make causal mask used for bi-directional self-attention.
"""
bsz, tgt_len = input_ids_shape
mask = torch.full((tgt_len, tgt_len), float("-inf"))
mask_cond = torch.arange(mask.size(-1))
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79,
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91,
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_expand_mask | (mask: torch.Tensor, dtype: torch.dtype, tgt_len: Optional[int] = None) |
Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`.
|
Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`.
| def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Optional[int] = None):
"""
Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`.
"""
bsz, src_len = mask.size()
tgt_len = tgt_len if tgt_len is not None else src_len
expanded_mask = mask[:, None, N... | [
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BlenderbotLearnedPositionalEmbedding.forward | (self, input_ids_shape: torch.Size, past_key_values_length: int = 0) | `input_ids_shape` is expected to be [bsz x seqlen]. | `input_ids_shape` is expected to be [bsz x seqlen]. | def forward(self, input_ids_shape: torch.Size, past_key_values_length: int = 0):
"""`input_ids_shape` is expected to be [bsz x seqlen]."""
bsz, seq_len = input_ids_shape[:2]
positions = torch.arange(
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BlenderbotAttention.forward | (
self,
hidden_states: torch.Tensor,
key_value_states: Optional[torch.Tensor] = None,
past_key_value: Optional[Tuple[torch.Tensor]] = None,
attention_mask: Optional[torch.Tensor] = None,
layer_head_mask: Optional[torch.Tensor] = None,
output_attentions: bool = Fal... | Input shape: Batch x Time x Channel | Input shape: Batch x Time x Channel | def forward(
self,
hidden_states: torch.Tensor,
key_value_states: Optional[torch.Tensor] = None,
past_key_value: Optional[Tuple[torch.Tensor]] = None,
attention_mask: Optional[torch.Tensor] = None,
layer_head_mask: Optional[torch.Tensor] = None,
output_attentions:... | [
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266,
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BlenderbotEncoderLayer.forward | (
self,
hidden_states: torch.Tensor,
attention_mask: torch.Tensor,
layer_head_mask: torch.Tensor,
output_attentions: bool = False,
) |
Args:
hidden_states (:obj:`torch.FloatTensor`): input to the layer of shape `(seq_len, batch, embed_dim)`
attention_mask (:obj:`torch.FloatTensor`): attention mask of size
`(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
... |
Args:
hidden_states (:obj:`torch.FloatTensor`): input to the layer of shape `(seq_len, batch, embed_dim)`
attention_mask (:obj:`torch.FloatTensor`): attention mask of size
`(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
... | def forward(
self,
hidden_states: torch.Tensor,
attention_mask: torch.Tensor,
layer_head_mask: torch.Tensor,
output_attentions: bool = False,
):
"""
Args:
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BlenderbotDecoderLayer.forward | (
self,
hidden_states: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
encoder_hidden_states: Optional[torch.Tensor] = None,
encoder_attention_mask: Optional[torch.Tensor] = None,
layer_head_mask: Optional[torch.Tensor] = None,
encoder_layer_head_mask... |
Args:
hidden_states (:obj:`torch.FloatTensor`): input to the layer of shape `(seq_len, batch, embed_dim)`
attention_mask (:obj:`torch.FloatTensor`): attention mask of size
`(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
... |
Args:
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attention_mask (:obj:`torch.FloatTensor`): attention mask of size
`(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
... | def forward(
self,
hidden_states: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
encoder_hidden_states: Optional[torch.Tensor] = None,
encoder_attention_mask: Optional[torch.Tensor] = None,
layer_head_mask: Optional[torch.Tensor] = None,
encoder_laye... | [
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BlenderbotEncoder.forward | (
self,
input_ids=None,
attention_mask=None,
head_mask=None,
inputs_embeds=None,
output_attentions=None,
output_hidden_states=None,
return_dict=None,
) | r"""
Args:
input_ids (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`):
Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you
provide it.
Indices can be obtained using :class:`~transfor... | r"""
Args:
input_ids (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`):
Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you
provide it. | def forward(
self,
input_ids=None,
attention_mask=None,
head_mask=None,
inputs_embeds=None,
output_attentions=None,
output_hidden_states=None,
return_dict=None,
):
r"""
Args:
input_ids (:obj:`torch.LongTensor` of shape :obj:... | [
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BlenderbotDecoder.forward | (
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encoder_head_mask=None,
past_key_values=None,
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... | r"""
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Indices can be obtained using :class:`~transfor... | r"""
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BlenderbotForCausalLM.forward | (
self,
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attention_mask=None,
encoder_hidden_states=None,
encoder_attention_mask=None,
head_mask=None,
encoder_head_mask=None,
past_key_values=None,
inputs_embeds=None,
labels=None,
use_cache=None,
output_atte... | r"""
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Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you
provide it.
Indices can be obtained using :class:`~transfor... | r"""
Args:
input_ids (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`):
Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you
provide it. | def forward(
self,
input_ids=None,
attention_mask=None,
encoder_hidden_states=None,
encoder_attention_mask=None,
head_mask=None,
encoder_head_mask=None,
past_key_values=None,
inputs_embeds=None,
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ecobee_date | (date_string) | Validate a date_string as valid for the ecobee API. | Validate a date_string as valid for the ecobee API. | def ecobee_date(date_string):
"""Validate a date_string as valid for the ecobee API."""
try:
datetime.strptime(date_string, "%Y-%m-%d")
except ValueError as err:
raise vol.Invalid("Date does not match ecobee date format YYYY-MM-DD") from err
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ecobee_time | (time_string) | Validate a time_string as valid for the ecobee API. | Validate a time_string as valid for the ecobee API. | def ecobee_time(time_string):
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try:
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async_setup_platform | (hass, config, async_add_entities, discovery_info=None) | Discover and configure Somfy covers. | Discover and configure Somfy covers. | async def async_setup_platform(hass, config, async_add_entities, discovery_info=None):
"""Discover and configure Somfy covers."""
if discovery_info is None:
return
somfy_mylink = hass.data[DATA_SOMFY_MYLINK]
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SomfyShade.__init__ | (
self,
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target_id,
name="SomfyShade",
reverse=False,
device_class=DEVICE_CLASS_WINDOW,
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target_id,
name="SomfyShade",
reverse=False,
device_class=DEVICE_CLASS_WINDOW,
):
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self.somfy_mylink = somfy_mylink
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self._name = name
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SomfyShade.unique_id | (self) | Return the unique ID of this cover. | Return the unique ID of this cover. | def unique_id(self):
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SomfyShade.name | (self) | Return the name of the cover. | Return the name of the cover. | def name(self):
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SomfyShade.is_closed | (self) | Return if the cover is closed. | Return if the cover is closed. | def is_closed(self):
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SomfyShade.assumed_state | (self) | Let HA know the integration is assumed state. | Let HA know the integration is assumed state. | def assumed_state(self):
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SomfyShade.device_class | (self) | Return the class of this device, from component DEVICE_CLASSES. | Return the class of this device, from component DEVICE_CLASSES. | def device_class(self):
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SomfyShade.async_open_cover | (self, **kwargs) | Wrap Homeassistant calls to open the cover. | Wrap Homeassistant calls to open the cover. | async def async_open_cover(self, **kwargs):
"""Wrap Homeassistant calls to open the cover."""
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SomfyShade.async_close_cover | (self, **kwargs) | Wrap Homeassistant calls to close the cover. | Wrap Homeassistant calls to close the cover. | async def async_close_cover(self, **kwargs):
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SomfyShade.async_stop_cover | (self, **kwargs) | Stop the cover. | Stop the cover. | async def async_stop_cover(self, **kwargs):
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AlexaCapability.__init__ | (self, entity: State, instance: Optional[str] = None) | Initialize an Alexa capability. | Initialize an Alexa capability. | def __init__(self, entity: State, instance: Optional[str] = None):
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AlexaCapability.name | (self) | Return the Alexa API name of this interface. | Return the Alexa API name of this interface. | def name(self) -> str:
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AlexaCapability.properties_supported | () | Return what properties this entity supports. | Return what properties this entity supports. | def properties_supported() -> List[dict]:
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AlexaCapability.properties_proactively_reported | () | Return True if properties asynchronously reported. | Return True if properties asynchronously reported. | def properties_proactively_reported() -> bool:
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AlexaCapability.properties_retrievable | () | Return True if properties can be retrieved. | Return True if properties can be retrieved. | def properties_retrievable() -> bool:
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AlexaCapability.properties_non_controllable | () | Return True if non controllable. | Return True if non controllable. | def properties_non_controllable() -> bool:
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4
] | [
102,
19
] | python | it | ['it', 'en', 'it'] | True |
AlexaCapability.get_property | (name) | Read and return a property.
Return value should be a dict, or raise UnsupportedProperty.
Properties can also have a timeOfSample and uncertaintyInMilliseconds,
but returning those metadata is not yet implemented.
| Read and return a property. | def get_property(name):
"""Read and return a property.
Return value should be a dict, or raise UnsupportedProperty.
Properties can also have a timeOfSample and uncertaintyInMilliseconds,
but returning those metadata is not yet implemented.
"""
raise UnsupportedProperty(... | [
"def",
"get_property",
"(",
"name",
")",
":",
"raise",
"UnsupportedProperty",
"(",
"name",
")"
] | [
105,
4
] | [
113,
39
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.supports_deactivation | () | Applicable only to scenes. | Applicable only to scenes. | def supports_deactivation():
"""Applicable only to scenes."""
return None | [
"def",
"supports_deactivation",
"(",
")",
":",
"return",
"None"
] | [
116,
4
] | [
118,
19
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.capability_proactively_reported | () | Return True if the capability is proactively reported.
Set properties_proactively_reported() for proactively reported properties.
Applicable to DoorbellEventSource.
| Return True if the capability is proactively reported. | def capability_proactively_reported():
"""Return True if the capability is proactively reported.
Set properties_proactively_reported() for proactively reported properties.
Applicable to DoorbellEventSource.
"""
return None | [
"def",
"capability_proactively_reported",
"(",
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"return",
"None"
] | [
121,
4
] | [
127,
19
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.capability_resources | () | Return the capability object.
Applicable to ToggleController, RangeController, and ModeController interfaces.
| Return the capability object. | def capability_resources():
"""Return the capability object.
Applicable to ToggleController, RangeController, and ModeController interfaces.
"""
return [] | [
"def",
"capability_resources",
"(",
")",
":",
"return",
"[",
"]"
] | [
130,
4
] | [
135,
17
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.configuration | () | Return the configuration object.
Applicable to the ThermostatController, SecurityControlPanel, ModeController, RangeController,
and EventDetectionSensor.
| Return the configuration object. | def configuration():
"""Return the configuration object.
Applicable to the ThermostatController, SecurityControlPanel, ModeController, RangeController,
and EventDetectionSensor.
"""
return [] | [
"def",
"configuration",
"(",
")",
":",
"return",
"[",
"]"
] | [
138,
4
] | [
144,
17
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.configurations | () | Return the configurations object.
The plural configurations object is different that the singular configuration object.
Applicable to EqualizerController interface.
| Return the configurations object. | def configurations():
"""Return the configurations object.
The plural configurations object is different that the singular configuration object.
Applicable to EqualizerController interface.
"""
return [] | [
"def",
"configurations",
"(",
")",
":",
"return",
"[",
"]"
] | [
147,
4
] | [
153,
17
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.inputs | () | Applicable only to media players. | Applicable only to media players. | def inputs():
"""Applicable only to media players."""
return [] | [
"def",
"inputs",
"(",
")",
":",
"return",
"[",
"]"
] | [
156,
4
] | [
158,
17
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.semantics | () | Return the semantics object.
Applicable to ToggleController, RangeController, and ModeController interfaces.
| Return the semantics object. | def semantics():
"""Return the semantics object.
Applicable to ToggleController, RangeController, and ModeController interfaces.
"""
return [] | [
"def",
"semantics",
"(",
")",
":",
"return",
"[",
"]"
] | [
161,
4
] | [
166,
17
] | python | en | ['en', 'ja', 'en'] | True |
AlexaCapability.supported_operations | () | Return the supportedOperations object. | Return the supportedOperations object. | def supported_operations():
"""Return the supportedOperations object."""
return [] | [
"def",
"supported_operations",
"(",
")",
":",
"return",
"[",
"]"
] | [
169,
4
] | [
171,
17
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.camera_stream_configurations | () | Applicable only to CameraStreamController. | Applicable only to CameraStreamController. | def camera_stream_configurations():
"""Applicable only to CameraStreamController."""
return None | [
"def",
"camera_stream_configurations",
"(",
")",
":",
"return",
"None"
] | [
174,
4
] | [
176,
19
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.serialize_discovery | (self) | Serialize according to the Discovery API. | Serialize according to the Discovery API. | def serialize_discovery(self):
"""Serialize according to the Discovery API."""
result = {"type": "AlexaInterface", "interface": self.name(), "version": "3"}
instance = self.instance
if instance is not None:
result["instance"] = instance
properties_supported = self.p... | [
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"serialize_discovery",
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"if",... | [
178,
4
] | [
235,
21
] | python | en | ['en', 'en', 'en'] | True |
AlexaCapability.serialize_properties | (self) | Return properties serialized for an API response. | Return properties serialized for an API response. | def serialize_properties(self):
"""Return properties serialized for an API response."""
for prop in self.properties_supported():
prop_name = prop["name"]
try:
prop_value = self.get_property(prop_name)
except UnsupportedProperty:
raise
... | [
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")"... | [
237,
4
] | [
268,
24
] | python | en | ['en', 'no', 'en'] | True |
Alexa.name | (self) | Return the Alexa API name of this interface. | Return the Alexa API name of this interface. | def name(self):
"""Return the Alexa API name of this interface."""
return "Alexa" | [
"def",
"name",
"(",
"self",
")",
":",
"return",
"\"Alexa\""
] | [
295,
4
] | [
297,
22
] | python | en | ['en', 'mi', 'en'] | True |
AlexaEndpointHealth.__init__ | (self, hass, entity) | Initialize the entity. | Initialize the entity. | def __init__(self, hass, entity):
"""Initialize the entity."""
super().__init__(entity)
self.hass = hass | [
"def",
"__init__",
"(",
"self",
",",
"hass",
",",
"entity",
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"(",
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"entity",
")",
"self",
".",
"hass",
"=",
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] | [
319,
4
] | [
322,
24
] | python | en | ['en', 'en', 'en'] | True |
AlexaEndpointHealth.name | (self) | Return the Alexa API name of this interface. | Return the Alexa API name of this interface. | def name(self):
"""Return the Alexa API name of this interface."""
return "Alexa.EndpointHealth" | [
"def",
"name",
"(",
"self",
")",
":",
"return",
"\"Alexa.EndpointHealth\""
] | [
324,
4
] | [
326,
37
] | python | en | ['en', 'mi', 'en'] | True |
AlexaEndpointHealth.properties_supported | (self) | Return what properties this entity supports. | Return what properties this entity supports. | def properties_supported(self):
"""Return what properties this entity supports."""
return [{"name": "connectivity"}] | [
"def",
"properties_supported",
"(",
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"[",
"{",
"\"name\"",
":",
"\"connectivity\"",
"}",
"]"
] | [
328,
4
] | [
330,
41
] | python | en | ['en', 'en', 'en'] | True |
AlexaEndpointHealth.properties_proactively_reported | (self) | Return True if properties asynchronously reported. | Return True if properties asynchronously reported. | def properties_proactively_reported(self):
"""Return True if properties asynchronously reported."""
return True | [
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"properties_proactively_reported",
"(",
"self",
")",
":",
"return",
"True"
] | [
332,
4
] | [
334,
19
] | python | en | ['en', 'en', 'en'] | True |
AlexaEndpointHealth.properties_retrievable | (self) | Return True if properties can be retrieved. | Return True if properties can be retrieved. | def properties_retrievable(self):
"""Return True if properties can be retrieved."""
return True | [
"def",
"properties_retrievable",
"(",
"self",
")",
":",
"return",
"True"
] | [
336,
4
] | [
338,
19
] | python | en | ['en', 'af', 'en'] | True |
AlexaEndpointHealth.get_property | (self, name) | Read and return a property. | Read and return a property. | def get_property(self, name):
"""Read and return a property."""
if name != "connectivity":
raise UnsupportedProperty(name)
if self.entity.state == STATE_UNAVAILABLE:
return {"value": "UNREACHABLE"}
return {"value": "OK"} | [
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... | [
340,
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] | [
347,
30
] | python | en | ['en', 'en', 'en'] | True |
AlexaPowerController.name | (self) | Return the Alexa API name of this interface. | Return the Alexa API name of this interface. | def name(self):
"""Return the Alexa API name of this interface."""
return "Alexa.PowerController" | [
"def",
"name",
"(",
"self",
")",
":",
"return",
"\"Alexa.PowerController\""
] | [
369,
4
] | [
371,
38
] | python | en | ['en', 'mi', 'en'] | True |
AlexaPowerController.properties_supported | (self) | Return what properties this entity supports. | Return what properties this entity supports. | def properties_supported(self):
"""Return what properties this entity supports."""
return [{"name": "powerState"}] | [
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"[",
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"}",
"]"
] | [
373,
4
] | [
375,
39
] | python | en | ['en', 'en', 'en'] | True |
AlexaPowerController.properties_proactively_reported | (self) | Return True if properties asynchronously reported. | Return True if properties asynchronously reported. | def properties_proactively_reported(self):
"""Return True if properties asynchronously reported."""
return True | [
"def",
"properties_proactively_reported",
"(",
"self",
")",
":",
"return",
"True"
] | [
377,
4
] | [
379,
19
] | python | en | ['en', 'en', 'en'] | True |
AlexaPowerController.properties_retrievable | (self) | Return True if properties can be retrieved. | Return True if properties can be retrieved. | def properties_retrievable(self):
"""Return True if properties can be retrieved."""
return True | [
"def",
"properties_retrievable",
"(",
"self",
")",
":",
"return",
"True"
] | [
381,
4
] | [
383,
19
] | python | en | ['en', 'af', 'en'] | True |
AlexaPowerController.get_property | (self, name) | Read and return a property. | Read and return a property. | def get_property(self, name):
"""Read and return a property."""
if name != "powerState":
raise UnsupportedProperty(name)
if self.entity.domain == climate.DOMAIN:
is_on = self.entity.state != climate.HVAC_MODE_OFF
elif self.entity.domain == vacuum.DOMAIN:
... | [
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385,
4
] | [
400,
39
] | python | en | ['en', 'en', 'en'] | True |
AlexaLockController.name | (self) | Return the Alexa API name of this interface. | Return the Alexa API name of this interface. | def name(self):
"""Return the Alexa API name of this interface."""
return "Alexa.LockController" | [
"def",
"name",
"(",
"self",
")",
":",
"return",
"\"Alexa.LockController\""
] | [
427,
4
] | [
429,
37
] | python | en | ['en', 'mi', 'en'] | True |
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