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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
LMShuffledIterator.__init__ | (self, data, bsz, bptt, device="cpu", ext_len=None, shuffle=False) |
data -- list[LongTensor] -- there is no order among the LongTensors
|
data -- list[LongTensor] -- there is no order among the LongTensors
| def __init__(self, data, bsz, bptt, device="cpu", ext_len=None, shuffle=False):
"""
data -- list[LongTensor] -- there is no order among the LongTensors
"""
self.data = data
self.bsz = bsz
self.bptt = bptt
self.ext_len = ext_len if ext_len is not None else 0
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TransfoXLCorpus.from_pretrained | (cls, pretrained_model_name_or_path, cache_dir=None, *inputs, **kwargs) |
Instantiate a pre-processed corpus.
|
Instantiate a pre-processed corpus.
| def from_pretrained(cls, pretrained_model_name_or_path, cache_dir=None, *inputs, **kwargs):
"""
Instantiate a pre-processed corpus.
"""
vocab = TransfoXLTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
if pretrained_model_name_or_path in PRETRAINED_CORP... | [
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setup | (hass, config) | Set up the Feedreader component. | Set up the Feedreader component. | def setup(hass, config):
"""Set up the Feedreader component."""
urls = config.get(DOMAIN)[CONF_URLS]
scan_interval = config.get(DOMAIN).get(CONF_SCAN_INTERVAL)
max_entries = config.get(DOMAIN).get(CONF_MAX_ENTRIES)
data_file = hass.config.path(f"{DOMAIN}.pickle")
storage = StoredData(data_file)
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FeedManager.__init__ | (self, url, scan_interval, max_entries, hass, storage) | Initialize the FeedManager object, poll as per scan interval. | Initialize the FeedManager object, poll as per scan interval. | def __init__(self, url, scan_interval, max_entries, hass, storage):
"""Initialize the FeedManager object, poll as per scan interval."""
self._url = url
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self._max_entries = max_entries
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FeedManager._log_no_entries | (self) | Send no entries log at debug level. | Send no entries log at debug level. | def _log_no_entries(self):
"""Send no entries log at debug level."""
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FeedManager._init_regular_updates | (self, hass) | Schedule regular updates at the top of the clock. | Schedule regular updates at the top of the clock. | def _init_regular_updates(self, hass):
"""Schedule regular updates at the top of the clock."""
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FeedManager.last_update_successful | (self) | Return True if the last feed update was successful. | Return True if the last feed update was successful. | def last_update_successful(self):
"""Return True if the last feed update was successful."""
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FeedManager._update | (self) | Update the feed and publish new entries to the event bus. | Update the feed and publish new entries to the event bus. | def _update(self):
"""Update the feed and publish new entries to the event bus."""
_LOGGER.info("Fetching new data from feed %s", self._url)
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FeedManager._filter_entries | (self) | Filter the entries provided and return the ones to keep. | Filter the entries provided and return the ones to keep. | def _filter_entries(self):
"""Filter the entries provided and return the ones to keep."""
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FeedManager._update_and_fire_entry | (self, entry) | Update last_entry_timestamp and fire entry. | Update last_entry_timestamp and fire entry. | def _update_and_fire_entry(self, entry):
"""Update last_entry_timestamp and fire entry."""
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FeedManager._publish_new_entries | (self) | Publish new entries to the event bus. | Publish new entries to the event bus. | def _publish_new_entries(self):
"""Publish new entries to the event bus."""
new_entries = False
self._last_entry_timestamp = self._storage.get_timestamp(self._feed_id)
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StoredData.__init__ | (self, data_file) | Initialize pickle data storage. | Initialize pickle data storage. | def __init__(self, data_file):
"""Initialize pickle data storage."""
self._data_file = data_file
self._lock = Lock()
self._cache_outdated = True
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StoredData._fetch_data | (self) | Fetch data stored into pickle file. | Fetch data stored into pickle file. | def _fetch_data(self):
"""Fetch data stored into pickle file."""
if self._cache_outdated and exists(self._data_file):
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StoredData.get_timestamp | (self, feed_id) | Return stored timestamp for given feed id (usually the url). | Return stored timestamp for given feed id (usually the url). | def get_timestamp(self, feed_id):
"""Return stored timestamp for given feed id (usually the url)."""
self._fetch_data()
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StoredData.put_timestamp | (self, feed_id, timestamp) | Update timestamp for given feed id (usually the url). | Update timestamp for given feed id (usually the url). | def put_timestamp(self, feed_id, timestamp):
"""Update timestamp for given feed id (usually the url)."""
self._fetch_data()
with self._lock, open(self._data_file, "wb") as myfile:
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async_setup_entry | (
hass: HomeAssistantType, entry: ConfigEntry, async_add_entities
) | Get all devices and setup the switch devices via config entry. | Get all devices and setup the switch devices via config entry. | async def async_setup_entry(
hass: HomeAssistantType, entry: ConfigEntry, async_add_entities
) -> None:
"""Get all devices and setup the switch devices via config entry."""
entities = []
for gateway in hass.data[DOMAIN][entry.entry_id]["gateways"]:
for device in gateway.binary_switch_devices:
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DevoloSwitch.__init__ | (self, homecontrol, device_instance, element_uid) | Initialize an devolo Switch. | Initialize an devolo Switch. | def __init__(self, homecontrol, device_instance, element_uid):
"""Initialize an devolo Switch."""
super().__init__(
homecontrol=homecontrol,
device_instance=device_instance,
element_uid=element_uid,
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DevoloSwitch.is_on | (self) | Return the state. | Return the state. | def is_on(self):
"""Return the state."""
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DevoloSwitch.current_power_w | (self) | Return the current consumption. | Return the current consumption. | def current_power_w(self):
"""Return the current consumption."""
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DevoloSwitch.turn_on | (self, **kwargs) | Switch on the device. | Switch on the device. | def turn_on(self, **kwargs):
"""Switch on the device."""
self._is_on = True
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DevoloSwitch.turn_off | (self, **kwargs) | Switch off the device. | Switch off the device. | def turn_off(self, **kwargs):
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DevoloSwitch._sync | (self, message) | Update the binary switch state and consumption. | Update the binary switch state and consumption. | def _sync(self, message):
"""Update the binary switch state and consumption."""
if message[0].startswith("devolo.BinarySwitch"):
self._is_on = self._device_instance.binary_switch_property[message[0]].state
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upsample | (x, stride, target_len, separate_cls=True, truncate_seq=False) |
Upsample tensor `x` to match `target_len` by repeating the tokens `stride` time on the sequence length dimension.
|
Upsample tensor `x` to match `target_len` by repeating the tokens `stride` time on the sequence length dimension.
| def upsample(x, stride, target_len, separate_cls=True, truncate_seq=False):
"""
Upsample tensor `x` to match `target_len` by repeating the tokens `stride` time on the sequence length dimension.
"""
if stride == 1:
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TFFunnelEmbeddings.call | (self, input_ids=None, inputs_embeds=None, training=False) |
Applies embedding based on inputs tensor.
Returns:
final_embeddings (:obj:`tf.Tensor`): output embedding tensor.
|
Applies embedding based on inputs tensor. | def call(self, input_ids=None, inputs_embeds=None, training=False):
"""
Applies embedding based on inputs tensor.
Returns:
final_embeddings (:obj:`tf.Tensor`): output embedding tensor.
"""
assert not (input_ids is None and inputs_embeds is None)
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TFFunnelAttentionStructure.init_attention_inputs | (self, inputs_embeds, attention_mask=None, token_type_ids=None, training=False) | Returns the attention inputs associated to the inputs of the model. | Returns the attention inputs associated to the inputs of the model. | def init_attention_inputs(self, inputs_embeds, attention_mask=None, token_type_ids=None, training=False):
""" Returns the attention inputs associated to the inputs of the model. """
# inputs_embeds has shape batch_size x seq_len x d_model
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TFFunnelAttentionStructure.token_type_ids_to_mat | (self, token_type_ids) | Convert `token_type_ids` to `token_type_mat`. | Convert `token_type_ids` to `token_type_mat`. | def token_type_ids_to_mat(self, token_type_ids):
"""Convert `token_type_ids` to `token_type_mat`."""
token_type_mat = tf.equal(tf.expand_dims(token_type_ids, -1), tf.expand_dims(token_type_ids, -2))
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cls_ids = tf.equal(token_type_ids, tf.... | [
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TFFunnelAttentionStructure.get_position_embeds | (self, seq_len, training=False) |
Create and cache inputs related to relative position encoding. Those are very different depending on whether we
are using the factorized or the relative shift attention:
For the factorized attention, it returns the matrices (phi, pi, psi, omega) used in the paper, appendix A.2.2,
final... |
Create and cache inputs related to relative position encoding. Those are very different depending on whether we
are using the factorized or the relative shift attention: | def get_position_embeds(self, seq_len, training=False):
"""
Create and cache inputs related to relative position encoding. Those are very different depending on whether we
are using the factorized or the relative shift attention:
For the factorized attention, it returns the matrices (ph... | [
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TFFunnelAttentionStructure.stride_pool_pos | (self, pos_id, block_index) |
Pool `pos_id` while keeping the cls token separate (if `self.separate_cls=True`).
|
Pool `pos_id` while keeping the cls token separate (if `self.separate_cls=True`).
| def stride_pool_pos(self, pos_id, block_index):
"""
Pool `pos_id` while keeping the cls token separate (if `self.separate_cls=True`).
"""
if self.separate_cls:
# Under separate <cls>, we treat the <cls> as the first token in
# the previous block of the 1st real bl... | [
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258,
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TFFunnelAttentionStructure.relative_pos | (self, pos, stride, pooled_pos=None, shift=1) |
Build the relative positional vector between `pos` and `pooled_pos`.
|
Build the relative positional vector between `pos` and `pooled_pos`.
| def relative_pos(self, pos, stride, pooled_pos=None, shift=1):
"""
Build the relative positional vector between `pos` and `pooled_pos`.
"""
if pooled_pos is None:
pooled_pos = pos
ref_point = pooled_pos[0] - pos[0]
num_remove = shift * shape_list(pooled_pos)[... | [
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TFFunnelAttentionStructure.stride_pool | (self, tensor, axis) |
Perform pooling by stride slicing the tensor along the given axis.
|
Perform pooling by stride slicing the tensor along the given axis.
| def stride_pool(self, tensor, axis):
"""
Perform pooling by stride slicing the tensor along the given axis.
"""
if tensor is None:
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# Do the stride pool recursively if axis is a list or a tuple of ints.
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TFFunnelAttentionStructure.pool_tensor | (self, tensor, mode="mean", stride=2) | Apply 1D pooling to a tensor of size [B x T (x H)]. | Apply 1D pooling to a tensor of size [B x T (x H)]. | def pool_tensor(self, tensor, mode="mean", stride=2):
"""Apply 1D pooling to a tensor of size [B x T (x H)]."""
if tensor is None:
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TFFunnelAttentionStructure.pre_attention_pooling | (self, output, attention_inputs) | Pool `output` and the proper parts of `attention_inputs` before the attention layer. | Pool `output` and the proper parts of `attention_inputs` before the attention layer. | def pre_attention_pooling(self, output, attention_inputs):
""" Pool `output` and the proper parts of `attention_inputs` before the attention layer. """
position_embeds, token_type_mat, attention_mask, cls_mask = attention_inputs
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TFFunnelAttentionStructure.post_attention_pooling | (self, attention_inputs) | Pool the proper parts of `attention_inputs` after the attention layer. | Pool the proper parts of `attention_inputs` after the attention layer. | def post_attention_pooling(self, attention_inputs):
""" Pool the proper parts of `attention_inputs` after the attention layer. """
position_embeds, token_type_mat, attention_mask, cls_mask = attention_inputs
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TFFunnelRelMultiheadAttention.relative_positional_attention | (self, position_embeds, q_head, context_len, cls_mask=None) | Relative attention score for the positional encodings | Relative attention score for the positional encodings | def relative_positional_attention(self, position_embeds, q_head, context_len, cls_mask=None):
""" Relative attention score for the positional encodings """
# q_head has shape batch_size x sea_len x n_head x d_head
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# Notations from the paper, ap... | [
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TFFunnelRelMultiheadAttention.relative_token_type_attention | (self, token_type_mat, q_head, cls_mask=None) | Relative attention score for the token_type_ids | Relative attention score for the token_type_ids | def relative_token_type_attention(self, token_type_mat, q_head, cls_mask=None):
""" Relative attention score for the token_type_ids """
if token_type_mat is None:
return 0
batch_size, seq_len, context_len = shape_list(token_type_mat)
# q_head has shape batch_size x seq_len x ... | [
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setup | () | Set up for tests. | Set up for tests. | def setup():
"""Set up for tests."""
global TMP_DIR
TMP_DIR = mkdtemp() | [
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teardown | () | Clean up after tests. | Clean up after tests. | def teardown():
"""Clean up after tests."""
for fname in os.listdir(TMP_DIR):
os.remove(os.path.join(TMP_DIR, fname))
os.rmdir(TMP_DIR) | [
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test_save_and_load | () | Test saving and loading back. | Test saving and loading back. | def test_save_and_load():
"""Test saving and loading back."""
yaml = YAML(typ="rt")
fname = _path_for("test1")
open(fname, "w+").close()
util_yaml.save_yaml(fname, yaml.load(TEST_YAML_A))
data = util_yaml.load_yaml(fname, True)
assert data == yaml.load(TEST_YAML_A) | [
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test_overwrite_and_reload | () | Test that we can overwrite an existing file and read back. | Test that we can overwrite an existing file and read back. | def test_overwrite_and_reload():
"""Test that we can overwrite an existing file and read back."""
yaml = YAML(typ="rt")
fname = _path_for("test2")
open(fname, "w+").close()
util_yaml.save_yaml(fname, yaml.load(TEST_YAML_A))
util_yaml.save_yaml(fname, yaml.load(TEST_YAML_B))
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test_load_bad_data | () | Test error from trying to load unserialisable data. | Test error from trying to load unserialisable data. | def test_load_bad_data():
"""Test error from trying to load unserialisable data."""
fname = _path_for("test3")
with open(fname, "w") as fh:
fh.write(TEST_BAD_YAML)
with pytest.raises(HomeAssistantError):
util_yaml.load_yaml(fname, True) | [
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threshold_log | (count: int, *args, **kwargs) | Log at warn level after WARN_THRESHOLD failures, debug otherwise. | Log at warn level after WARN_THRESHOLD failures, debug otherwise. | def threshold_log(count: int, *args, **kwargs) -> None:
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_LOGGER.warning(*args, **kwargs)
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BrData.__init__ | (self, hass, coordinates, timeframe, devices) | Initialize the data object. | Initialize the data object. | def __init__(self, hass, coordinates, timeframe, devices):
"""Initialize the data object."""
self.devices = devices
self.data = {}
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BrData.update_devices | (self) | Update all devices/sensors. | Update all devices/sensors. | async def update_devices(self):
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if not self.devices:
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BrData.schedule_update | (self, minute=1) | Schedule an update after minute minutes. | Schedule an update after minute minutes. | async def schedule_update(self, minute=1):
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BrData.get_data | (self, url) | Load data from specified url. | Load data from specified url. | async def get_data(self, url):
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_LOGGER.debug("Calling url: %s...", url)
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BrData.async_update | (self, *_) | Update the data from buienradar. | Update the data from buienradar. | async def async_update(self, *_):
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content = await self.get_data(JSON_FEED_URL)
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BrData.attribution | (self) | Return the attribution. | Return the attribution. | def attribution(self):
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BrData.stationname | (self) | Return the name of the selected weatherstation. | Return the name of the selected weatherstation. | def stationname(self):
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BrData.condition | (self) | Return the condition. | Return the condition. | def condition(self):
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BrData.temperature | (self) | Return the temperature, or None. | Return the temperature, or None. | def temperature(self):
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BrData.pressure | (self) | Return the pressure, or None. | Return the pressure, or None. | def pressure(self):
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BrData.humidity | (self) | Return the humidity, or None. | Return the humidity, or None. | def humidity(self):
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BrData.visibility | (self) | Return the visibility, or None. | Return the visibility, or None. | def visibility(self):
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BrData.wind_speed | (self) | Return the windspeed, or None. | Return the windspeed, or None. | def wind_speed(self):
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216,
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221,
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BrData.wind_bearing | (self) | Return the wind bearing, or None. | Return the wind bearing, or None. | def wind_bearing(self):
"""Return the wind bearing, or None."""
try:
return int(self.data.get(WINDAZIMUTH))
except (ValueError, TypeError):
return None | [
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BrData.forecast | (self) | Return the forecast data. | Return the forecast data. | def forecast(self):
"""Return the forecast data."""
return self.data.get(FORECAST) | [
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Env.step | (self, action) | Push the environment to next step with action.
Args:
action (Action): Action(s) from agent.
Returns:
tuple: a tuple of (metrics, decision event, is_done).
| Push the environment to next step with action. | def step(self, action):
"""Push the environment to next step with action.
Args:
action (Action): Action(s) from agent.
Returns:
tuple: a tuple of (metrics, decision event, is_done).
"""
try:
metrics, decision_event, _is_done = self._simulate_... | [
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Env.dump | (self) | Dump environment for restore.
NOTE:
Not implemented.
| Dump environment for restore. | def dump(self):
"""Dump environment for restore.
NOTE:
Not implemented.
"""
return | [
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Env.reset | (self) | Reset environment. | Reset environment. | def reset(self):
"""Reset environment."""
self._tick = self._start_tick
self._simulate_generator.close()
self._simulate_generator = self._simulate()
self._event_buffer.reset()
if ("enable-dump-snapshot" in self._additional_options) and (self._business_engine._frame is ... | [
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118,
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Env.configs | (self) | dict: Configurations of current environment. | dict: Configurations of current environment. | def configs(self) -> dict:
"""dict: Configurations of current environment."""
return self._business_engine.configs | [
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Env.summary | (self) | dict: Summary about current simulator, including node details and mappings. | dict: Summary about current simulator, including node details and mappings. | def summary(self) -> dict:
"""dict: Summary about current simulator, including node details and mappings."""
return {
"node_mapping": self._business_engine.get_node_mapping(),
"node_detail": self.current_frame.get_node_info(),
"event_payload": self._business_engine.ge... | [
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Env.name | (self) | str: Name of current environment. | str: Name of current environment. | def name(self) -> str:
"""str: Name of current environment."""
return self._name | [
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Env.current_frame | (self) | Frame: Frame of current environment. | Frame: Frame of current environment. | def current_frame(self) -> FrameBase:
"""Frame: Frame of current environment."""
return self._business_engine.frame | [
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Env.tick | (self) | int: Current tick of environment. | int: Current tick of environment. | def tick(self) -> int:
"""int: Current tick of environment."""
return self._tick | [
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Env.frame_index | (self) | int: Frame index in snapshot list for current tick. | int: Frame index in snapshot list for current tick. | def frame_index(self) -> int:
"""int: Frame index in snapshot list for current tick."""
return tick_to_frame_index(self._start_tick, self._tick, self._snapshot_resolution) | [
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Env.snapshot_list | (self) | SnapshotList: A snapshot list containing all the snapshots of frame at each dump point.
NOTE: Due to different environment configurations, the resolution of the snapshot may be different.
| SnapshotList: A snapshot list containing all the snapshots of frame at each dump point. | def snapshot_list(self) -> SnapshotList:
"""SnapshotList: A snapshot list containing all the snapshots of frame at each dump point.
NOTE: Due to different environment configurations, the resolution of the snapshot may be different.
"""
return self._business_engine.snapshots | [
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160,
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Env.agent_idx_list | (self) | List[int]: Agent index list that related to this environment. | List[int]: Agent index list that related to this environment. | def agent_idx_list(self) -> List[int]:
"""List[int]: Agent index list that related to this environment."""
return self._business_engine.get_agent_idx_list() | [
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Env.set_seed | (self, seed: int) | Set random seed used by simulator.
NOTE:
This will not set seed for Python random or other packages' seed, such as NumPy.
Args:
seed (int): Seed to set.
| Set random seed used by simulator. | def set_seed(self, seed: int):
"""Set random seed used by simulator.
NOTE:
This will not set seed for Python random or other packages' seed, such as NumPy.
Args:
seed (int): Seed to set.
"""
if seed is not None:
sim_seed(seed) | [
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Env.metrics | (self) | Some statistics information provided by business engine.
Returns:
dict: Dictionary of metrics, content and format is determined by business engine.
| Some statistics information provided by business engine. | def metrics(self) -> dict:
"""Some statistics information provided by business engine.
Returns:
dict: Dictionary of metrics, content and format is determined by business engine.
"""
return self._business_engine.get_metrics() | [
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Env.get_finished_events | (self) | List[Event]: All events finished so far. | List[Event]: All events finished so far. | def get_finished_events(self):
"""List[Event]: All events finished so far."""
return self._event_buffer.get_finished_events() | [
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Env.get_pending_events | (self, tick) | Pending events at certain tick.
Args:
tick (int): Specified tick to query.
| Pending events at certain tick. | def get_pending_events(self, tick):
"""Pending events at certain tick.
Args:
tick (int): Specified tick to query.
"""
return self._event_buffer.get_pending_events(tick) | [
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Env._init_business_engine | (self) | Initialize business engine object.
NOTE:
1. For built-in scenarios, they will always under "maro/simulator/scenarios" folder.
2. For external scenarios, the business engine instance is built with the loaded business engine class.
| Initialize business engine object. | def _init_business_engine(self):
"""Initialize business engine object.
NOTE:
1. For built-in scenarios, they will always under "maro/simulator/scenarios" folder.
2. For external scenarios, the business engine instance is built with the loaded business engine class.
"""
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Env._simulate | (self) | This is the generator to wrap each episode process. | This is the generator to wrap each episode process. | def _simulate(self):
"""This is the generator to wrap each episode process."""
is_end_tick = False
self._streamit_episode += 1
streamit.episode(self._streamit_episode)
while True:
# Ask business engine to do thing for this tick, such as generating and pushing event... | [
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327,
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restore_ts | () | Restore default TZ. | Restore default TZ. | def restore_ts():
"""Restore default TZ."""
yield
dt_util.DEFAULT_TIME_ZONE = ORIG_TZ | [
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test_intervals | (hass) | Test timing intervals of sensors. | Test timing intervals of sensors. | async def test_intervals(hass):
"""Test timing intervals of sensors."""
device = time_date.TimeDateSensor(hass, "time")
now = dt_util.utc_from_timestamp(45.5)
with patch("homeassistant.util.dt.utcnow", return_value=now):
next_time = device.get_next_interval()
assert next_time == dt_util.utc_... | [
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test_states | (hass) | Test states of sensors. | Test states of sensors. | async def test_states(hass):
"""Test states of sensors."""
now = dt_util.utc_from_timestamp(1495068856)
device = time_date.TimeDateSensor(hass, "time")
device._update_internal_state(now)
assert device.state == "00:54"
device = time_date.TimeDateSensor(hass, "date")
device._update_internal_s... | [
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test_states_non_default_timezone | (hass) | Test states of sensors in a timezone other than UTC. | Test states of sensors in a timezone other than UTC. | async def test_states_non_default_timezone(hass):
"""Test states of sensors in a timezone other than UTC."""
new_tz = dt_util.get_time_zone("America/New_York")
assert new_tz is not None
dt_util.set_default_time_zone(new_tz)
now = dt_util.utc_from_timestamp(1495068856)
device = time_date.TimeDat... | [
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test_timezone_intervals | (hass) | Test date sensor behavior in a timezone besides UTC. | Test date sensor behavior in a timezone besides UTC. | async def test_timezone_intervals(hass):
"""Test date sensor behavior in a timezone besides UTC."""
new_tz = dt_util.get_time_zone("America/New_York")
assert new_tz is not None
dt_util.set_default_time_zone(new_tz)
device = time_date.TimeDateSensor(hass, "date")
now = dt_util.utc_from_timestamp... | [
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test_timezone_intervals_empty_parameter | (hass) | Test get_interval() without parameters. | Test get_interval() without parameters. | async def test_timezone_intervals_empty_parameter(hass):
"""Test get_interval() without parameters."""
new_tz = dt_util.get_time_zone("America/Edmonton")
assert new_tz is not None
dt_util.set_default_time_zone(new_tz)
device = time_date.TimeDateSensor(hass, "date")
next_time = device.get_next_in... | [
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test_icons | (hass) | Test attributes of sensors. | Test attributes of sensors. | async def test_icons(hass):
"""Test attributes of sensors."""
device = time_date.TimeDateSensor(hass, "time")
assert device.icon == "mdi:clock"
device = time_date.TimeDateSensor(hass, "date")
assert device.icon == "mdi:calendar"
device = time_date.TimeDateSensor(hass, "date_time")
assert dev... | [
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generate_ssp_set | (size, subset_size, sumto) |
Generate random set of Decimals such that a subset sums to a given value.
https://en.wikipedia.org/wiki/Subset_sum_problem
|
Generate random set of Decimals such that a subset sums to a given value.
https://en.wikipedia.org/wiki/Subset_sum_problem
| def generate_ssp_set(size, subset_size, sumto):
"""
Generate random set of Decimals such that a subset sums to a given value.
https://en.wikipedia.org/wiki/Subset_sum_problem
"""
# Generate set with entries uniformly distributed between 0 and 2*average
average = sumto / Decimal(size)
ssp_se... | [
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keygen | () |
Generate private and public keys for the "greased", bootstrappable encryption scheme.
The main idea here is that we want to minimize computation during decryption because it originally contains
an expensive modulus operation (c % p) that is too much for our somewhat homomorphic encryption system to ha... |
Generate private and public keys for the "greased", bootstrappable encryption scheme.
The main idea here is that we want to minimize computation during decryption because it originally contains
an expensive modulus operation (c % p) that is too much for our somewhat homomorphic encryption system to ha... | def keygen():
"""
Generate private and public keys for the "greased", bootstrappable encryption scheme.
The main idea here is that we want to minimize computation during decryption because it originally contains
an expensive modulus operation (c % p) that is too much for our somewhat homomorphic en... | [
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encrypt | (pk_z, pk_y, b) | Encrypt a bit b into an array of integers based on the provided public key. | Encrypt a bit b into an array of integers based on the provided public key. | def encrypt(pk_z, pk_y, b):
"""Encrypt a bit b into an array of integers based on the provided public key."""
# Perform regular asymmetric encryption
c = asymmetric.encrypt(pk_z, b)
# Post process the cypher text to generate the appropriate 1/p SPP set
cy = post_process(c, pk_y)
return (c, cy... | [
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67,
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] | python | en | ['en', 'en', 'en'] | True |
post_process | (c, pk_y) |
Post-process the cyphertext with pk_y to simplify computation during decryption.
We compute and return the 1/p SSP set for the provided cyphertext before decryption takes place.
This is one of the key steps in making our homomorphic encryption scheme bootstrappable.
|
Post-process the cyphertext with pk_y to simplify computation during decryption.
We compute and return the 1/p SSP set for the provided cyphertext before decryption takes place.
This is one of the key steps in making our homomorphic encryption scheme bootstrappable.
| def post_process(c, pk_y):
"""
Post-process the cyphertext with pk_y to simplify computation during decryption.
We compute and return the 1/p SSP set for the provided cyphertext before decryption takes place.
This is one of the key steps in making our homomorphic encryption scheme bootstrappable.
... | [
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] | [
70,
0
] | [
77,
50
] | python | en | ['en', 'error', 'th'] | False |
decrypt | (sk, c, cy) | Decrypt a bit (c, cz) based on sk. | Decrypt a bit (c, cz) based on sk. | def decrypt(sk, c, cy):
"""Decrypt a bit (c, cz) based on sk."""
# Decode/compute hidden subset sum given secret key
x = round(sum([cy[i] if sk[i] > 0 else 0 for i in range(HINT_SIZE)]))
lsb_x = x & 1
lsb_c = c & 1
# XOR the least significant bits together
return lsb_c ^ lsb_x | [
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"ra... | [
80,
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] | [
90,
24
] | python | en | ['en', 'cy', 'en'] | True |
validate_input | (hass: core.HomeAssistant, data) | Validate the user input allows us to connect.
Data has the keys from DATA_SCHEMA with values provided by the user.
| Validate the user input allows us to connect. | async def validate_input(hass: core.HomeAssistant, data):
"""Validate the user input allows us to connect.
Data has the keys from DATA_SCHEMA with values provided by the user.
"""
session = async_get_clientsession(hass)
try:
api = await async_get_api(
data[CONF_USERNAME], data[... | [
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... | [
18,
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] | [
36,
47
] | python | en | ['en', 'en', 'en'] | True |
ConfigFlow.async_step_user | (self, user_input=None) | Handle the initial step. | Handle the initial step. | async def async_step_user(self, user_input=None):
"""Handle the initial step."""
errors = {}
if user_input is not None:
await self.async_set_unique_id(user_input[CONF_USERNAME])
self._abort_if_unique_id_configured()
try:
info = await validate_i... | [
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45,
4
] | [
59,
9
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.setUp | (self) | Initialize values for this testcase class. | Initialize values for this testcase class. | def setUp(self):
"""Initialize values for this testcase class."""
self.hass = get_test_home_assistant()
self.addCleanup(self.tear_down_cleanup) | [
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] | [
37,
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] | [
40,
47
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.tear_down_cleanup | (self) | Clean up files and stop Home Assistant. | Clean up files and stop Home Assistant. | def tear_down_cleanup(self):
"""Clean up files and stop Home Assistant."""
data_file = self.hass.config.path(f"{feedreader.DOMAIN}.pickle")
if exists(data_file):
remove(data_file)
self.hass.stop() | [
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] | [
47,
24
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_setup_one_feed | (self) | Test the general setup of this component. | Test the general setup of this component. | def test_setup_one_feed(self):
"""Test the general setup of this component."""
with patch(
"homeassistant.components.feedreader.track_time_interval"
) as track_method:
assert setup_component(self.hass, feedreader.DOMAIN, VALID_CONFIG_1)
track_method.assert_cal... | [
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49,
4
] | [
57,
13
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_setup_scan_interval | (self) | Test the setup of this component with scan interval. | Test the setup of this component with scan interval. | def test_setup_scan_interval(self):
"""Test the setup of this component with scan interval."""
with patch(
"homeassistant.components.feedreader.track_time_interval"
) as track_method:
assert setup_component(self.hass, feedreader.DOMAIN, VALID_CONFIG_2)
track_m... | [
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",",... | [
59,
4
] | [
67,
13
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_setup_max_entries | (self) | Test the setup of this component with max entries. | Test the setup of this component with max entries. | def test_setup_max_entries(self):
"""Test the setup of this component with max entries."""
assert setup_component(self.hass, feedreader.DOMAIN, VALID_CONFIG_3) | [
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] | [
69,
4
] | [
71,
76
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.setup_manager | (self, feed_data, max_entries=DEFAULT_MAX_ENTRIES) | Set up feed manager. | Set up feed manager. | def setup_manager(self, feed_data, max_entries=DEFAULT_MAX_ENTRIES):
"""Set up feed manager."""
events = []
@callback
def record_event(event):
"""Add recorded event to set."""
events.append(event)
self.hass.bus.listen(EVENT_FEEDREADER, record_event)
... | [
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"ap... | [
73,
4
] | [
104,
30
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_feed | (self) | Test simple feed with valid data. | Test simple feed with valid data. | def test_feed(self):
"""Test simple feed with valid data."""
feed_data = load_fixture("feedreader.xml")
manager, events = self.setup_manager(feed_data)
assert len(events) == 1
assert events[0].data.title == "Title 1"
assert events[0].data.description == "Description 1"
... | [
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106,
4
] | [
120,
53
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_feed_updates | (self) | Test feed updates. | Test feed updates. | def test_feed_updates(self):
"""Test feed updates."""
# 1. Run
feed_data = load_fixture("feedreader.xml")
manager, events = self.setup_manager(feed_data)
assert len(events) == 1
# 2. Run
feed_data2 = load_fixture("feedreader1.xml")
# Must patch 'get_timest... | [
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122,
4
] | [
145,
36
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_feed_default_max_length | (self) | Test long feed beyond the default 20 entry limit. | Test long feed beyond the default 20 entry limit. | def test_feed_default_max_length(self):
"""Test long feed beyond the default 20 entry limit."""
feed_data = load_fixture("feedreader2.xml")
manager, events = self.setup_manager(feed_data)
assert len(events) == 20 | [
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"20"... | [
147,
4
] | [
151,
32
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_feed_max_length | (self) | Test long feed beyond a configured 5 entry limit. | Test long feed beyond a configured 5 entry limit. | def test_feed_max_length(self):
"""Test long feed beyond a configured 5 entry limit."""
feed_data = load_fixture("feedreader2.xml")
manager, events = self.setup_manager(feed_data, max_entries=5)
assert len(events) == 5 | [
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"... | [
153,
4
] | [
157,
31
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_feed_without_publication_date_and_title | (self) | Test simple feed with entry without publication date and title. | Test simple feed with entry without publication date and title. | def test_feed_without_publication_date_and_title(self):
"""Test simple feed with entry without publication date and title."""
feed_data = load_fixture("feedreader3.xml")
manager, events = self.setup_manager(feed_data)
assert len(events) == 3 | [
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159,
4
] | [
163,
31
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_feed_with_unrecognized_publication_date | (self) | Test simple feed with entry with unrecognized publication date. | Test simple feed with entry with unrecognized publication date. | def test_feed_with_unrecognized_publication_date(self):
"""Test simple feed with entry with unrecognized publication date."""
feed_data = load_fixture("feedreader4.xml")
manager, events = self.setup_manager(feed_data)
assert len(events) == 1 | [
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165,
4
] | [
169,
31
] | python | en | ['en', 'en', 'en'] | True |
TestFeedreaderComponent.test_feed_invalid_data | (self) | Test feed with invalid data. | Test feed with invalid data. | def test_feed_invalid_data(self):
"""Test feed with invalid data."""
feed_data = "INVALID DATA"
manager, events = self.setup_manager(feed_data)
assert len(events) == 0
assert manager.last_update_successful is True | [
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"last_... | [
171,
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] | [
176,
53
] | python | en | ['en', 'en', 'en'] | True |
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