blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
4523682dcf460318a9c7000cf83a526cfb0b40e8 | [
"states = [{' ': 0, 'sign': 1, 'digit': 2, '.': 4}, {'digit': 2, '.': 4}, {'digit': 2, '.': 3, 'e': 5, ' ': 8}, {'digit': 3, 'e': 5, ' ': 8}, {'digit': 3}, {'sign': 6, 'digit': 7}, {'digit': 7}, {'digit': 7, ' ': 8}, {' ': 8}]\nstate = 0\nfor c in s:\n if '0' <= c <= '9':\n target = 'digit'\n elif c in... | <|body_start_0|>
states = [{' ': 0, 'sign': 1, 'digit': 2, '.': 4}, {'digit': 2, '.': 4}, {'digit': 2, '.': 3, 'e': 5, ' ': 8}, {'digit': 3, 'e': 5, ' ': 8}, {'digit': 3}, {'sign': 6, 'digit': 7}, {'digit': 7}, {'digit': 7, ' ': 8}, {' ': 8}]
state = 0
for c in s:
if '0' <= c <= '9':... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isNumber(self, s: str) -> bool:
""":type s: str :rtype: bool"""
<|body_0|>
def isNumber_cheat(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
states = [{' ': 0, 'sign': 1, 'digit': 2, '.': 4}, {'d... | stack_v2_sparse_classes_75kplus_train_068400 | 1,950 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "isNumber",
"signature": "def isNumber(self, s: str) -> bool"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "isNumber_cheat",
"signature": "def isNumber_cheat(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isNumber(self, s: str) -> bool: :type s: str :rtype: bool
- def isNumber_cheat(self, s): :type s: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isNumber(self, s: str) -> bool: :type s: str :rtype: bool
- def isNumber_cheat(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def isNumber(self, s: st... | 8343f4258d20661f70f0462c358ef8b118a03de4 | <|skeleton|>
class Solution:
def isNumber(self, s: str) -> bool:
""":type s: str :rtype: bool"""
<|body_0|>
def isNumber_cheat(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isNumber(self, s: str) -> bool:
""":type s: str :rtype: bool"""
states = [{' ': 0, 'sign': 1, 'digit': 2, '.': 4}, {'digit': 2, '.': 4}, {'digit': 2, '.': 3, 'e': 5, ' ': 8}, {'digit': 3, 'e': 5, ' ': 8}, {'digit': 3}, {'sign': 6, 'digit': 7}, {'digit': 7}, {'digit': 7, ' ': 8}, ... | the_stack_v2_python_sparse | python/offer_20_isNumber.py | Aiooon/MyLeetcode | train | 0 | |
afe1f6fc453aafec31c5918572f6cbb9c6a7cc63 | [
"self.id = bag_files[0].split('_')[4].split('.')[0]\nself.bags = [bag.Bag(folder, bf, launch_file) for bf in bag_files]\nself.length = len(self.bags)\nself.area_poly = area_poly\nself.area_max = area_poly.area\nself.tmin = 0.0\nself.tmax = 0.0\nself.found = 0.0\nself.rescued = 0.0\nself.fov = 0.0",
"for i, b in e... | <|body_start_0|>
self.id = bag_files[0].split('_')[4].split('.')[0]
self.bags = [bag.Bag(folder, bf, launch_file) for bf in bag_files]
self.length = len(self.bags)
self.area_poly = area_poly
self.area_max = area_poly.area
self.tmin = 0.0
self.tmax = 0.0
se... | a class for storing the bag file contents of one (simulation) run with multiple UAVs | Run | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Run:
"""a class for storing the bag file contents of one (simulation) run with multiple UAVs"""
def __init__(self, folder, bag_files, launch_file, area_poly):
"""initialize class :param string folder: absolute path of the bag file directory :param string bag_files: name of the bag fi... | stack_v2_sparse_classes_75kplus_train_068401 | 5,444 | permissive | [
{
"docstring": "initialize class :param string folder: absolute path of the bag file directory :param string bag_files: name of the bag files for this run :param string launch_file: launch file that was launched to generate the bag files :param polygon area_poly: maximum coverable area",
"name": "__init__",... | 5 | stack_v2_sparse_classes_30k_train_004851 | Implement the Python class `Run` described below.
Class description:
a class for storing the bag file contents of one (simulation) run with multiple UAVs
Method signatures and docstrings:
- def __init__(self, folder, bag_files, launch_file, area_poly): initialize class :param string folder: absolute path of the bag f... | Implement the Python class `Run` described below.
Class description:
a class for storing the bag file contents of one (simulation) run with multiple UAVs
Method signatures and docstrings:
- def __init__(self, folder, bag_files, launch_file, area_poly): initialize class :param string folder: absolute path of the bag f... | 1b5fdbf42f027964b96a06e060f3a1757b91d9fd | <|skeleton|>
class Run:
"""a class for storing the bag file contents of one (simulation) run with multiple UAVs"""
def __init__(self, folder, bag_files, launch_file, area_poly):
"""initialize class :param string folder: absolute path of the bag file directory :param string bag_files: name of the bag fi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Run:
"""a class for storing the bag file contents of one (simulation) run with multiple UAVs"""
def __init__(self, folder, bag_files, launch_file, area_poly):
"""initialize class :param string folder: absolute path of the bag file directory :param string bag_files: name of the bag files for this ... | the_stack_v2_python_sparse | cpswarm_sar/scripts/modules/run.py | cpswarm/complex_behaviors | train | 4 |
81f70950637831e8dca13cac4198a0aa535444b8 | [
"self.file_name = file_name\nself.file_type = file_type\nself.data = {}\nself.config_dir = 'config/'\nself.parse_config_file()",
"log.info('Parsing configuration file: %s.%s' % (self.file_name, self.file_type))\nif 'xml' == self.file_type:\n path = self.config_dir + self.file_name + '.' + self.file_type\n s... | <|body_start_0|>
self.file_name = file_name
self.file_type = file_type
self.data = {}
self.config_dir = 'config/'
self.parse_config_file()
<|end_body_0|>
<|body_start_1|>
log.info('Parsing configuration file: %s.%s' % (self.file_name, self.file_type))
if 'xml' ==... | Config base class. Stores basic configuration information for a given subsytem. A given configuration will read its configuration input file and created a dictionary of the data stored. Example usage could be storing pin numbers of motors, ip addresses of hosts, etc. | Config | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Config:
"""Config base class. Stores basic configuration information for a given subsytem. A given configuration will read its configuration input file and created a dictionary of the data stored. Example usage could be storing pin numbers of motors, ip addresses of hosts, etc."""
def __init... | stack_v2_sparse_classes_75kplus_train_068402 | 6,119 | no_license | [
{
"docstring": "Initialize a configuration object.",
"name": "__init__",
"signature": "def __init__(self, file_name, file_type='xml')"
},
{
"docstring": "Parse configuration file and store data in data dictionary.",
"name": "parse_config_file",
"signature": "def parse_config_file(self)"
... | 2 | stack_v2_sparse_classes_30k_train_038112 | Implement the Python class `Config` described below.
Class description:
Config base class. Stores basic configuration information for a given subsytem. A given configuration will read its configuration input file and created a dictionary of the data stored. Example usage could be storing pin numbers of motors, ip addr... | Implement the Python class `Config` described below.
Class description:
Config base class. Stores basic configuration information for a given subsytem. A given configuration will read its configuration input file and created a dictionary of the data stored. Example usage could be storing pin numbers of motors, ip addr... | 6b2a26a9738c56228082030a75769eeb53cc2168 | <|skeleton|>
class Config:
"""Config base class. Stores basic configuration information for a given subsytem. A given configuration will read its configuration input file and created a dictionary of the data stored. Example usage could be storing pin numbers of motors, ip addresses of hosts, etc."""
def __init... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Config:
"""Config base class. Stores basic configuration information for a given subsytem. A given configuration will read its configuration input file and created a dictionary of the data stored. Example usage could be storing pin numbers of motors, ip addresses of hosts, etc."""
def __init__(self, file... | the_stack_v2_python_sparse | init.py | joshrands/smartspa-develop | train | 1 |
9cd2a7ebe7f3daf4783cfdd6ab2b091a822e36d7 | [
"filtered_paths = OrderedDict()\nfor path in paths:\n if not STATIC_POSTPROCESS_IGNORE_REGEX.match(path):\n filtered_paths[path] = paths[path]\nyield from super().post_process(filtered_paths, dry_run=dry_run, **options)",
"url = super().url(name, force=force)\ncdn_domain = getattr(settings, 'CDN_DOMAIN'... | <|body_start_0|>
filtered_paths = OrderedDict()
for path in paths:
if not STATIC_POSTPROCESS_IGNORE_REGEX.match(path):
filtered_paths[path] = paths[path]
yield from super().post_process(filtered_paths, dry_run=dry_run, **options)
<|end_body_0|>
<|body_start_1|>
... | Manifest static files storage backend that can be placed behing a CDN and ignores files that are already versioned by webpack. | CDNManifestStaticFilesStorage | [
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"AGPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CDNManifestStaticFilesStorage:
"""Manifest static files storage backend that can be placed behing a CDN and ignores files that are already versioned by webpack."""
def post_process(self, paths, dry_run=False, **options):
"""Remove paths from file to post process. Some js static files... | stack_v2_sparse_classes_75kplus_train_068403 | 2,168 | permissive | [
{
"docstring": "Remove paths from file to post process. Some js static files generated by webpack already have a unique name per build and may be referenced from within the js applications. We therefore don't want to hash their name and include them in the manifest file. We use a regex configurable via settings... | 2 | null | Implement the Python class `CDNManifestStaticFilesStorage` described below.
Class description:
Manifest static files storage backend that can be placed behing a CDN and ignores files that are already versioned by webpack.
Method signatures and docstrings:
- def post_process(self, paths, dry_run=False, **options): Rem... | Implement the Python class `CDNManifestStaticFilesStorage` described below.
Class description:
Manifest static files storage backend that can be placed behing a CDN and ignores files that are already versioned by webpack.
Method signatures and docstrings:
- def post_process(self, paths, dry_run=False, **options): Rem... | f2d46fc46b271eb3b4d565039a29c15ba15f027c | <|skeleton|>
class CDNManifestStaticFilesStorage:
"""Manifest static files storage backend that can be placed behing a CDN and ignores files that are already versioned by webpack."""
def post_process(self, paths, dry_run=False, **options):
"""Remove paths from file to post process. Some js static files... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CDNManifestStaticFilesStorage:
"""Manifest static files storage backend that can be placed behing a CDN and ignores files that are already versioned by webpack."""
def post_process(self, paths, dry_run=False, **options):
"""Remove paths from file to post process. Some js static files generated by... | the_stack_v2_python_sparse | cookiecutter/{{cookiecutter.organization}}-richie-site-factory/template/{{cookiecutter.site}}/src/backend/base/storage.py | openfun/richie | train | 238 |
f5f41b8b1c8b4dac5e3bcf693a8b5570a8e21a35 | [
"if 'lat' in udims and 'lon' in udims and self._dim_in(['lat', 'lon'], source_coordinates, eval_coordinates) and source_coordinates['lat'].is_uniform and source_coordinates['lon'].is_uniform and eval_coordinates['lat'].is_uniform and eval_coordinates['lon'].is_uniform:\n return udims\nreturn tuple()",
"if len(... | <|body_start_0|>
if 'lat' in udims and 'lon' in udims and self._dim_in(['lat', 'lon'], source_coordinates, eval_coordinates) and source_coordinates['lat'].is_uniform and source_coordinates['lon'].is_uniform and eval_coordinates['lat'].is_uniform and eval_coordinates['lon'].is_uniform:
return udims
... | Rasterio Interpolation Attributes ---------- {interpolator_attributes} rasterio_interpolators : list of str Interpolator methods available via rasterio | RasterioInterpolator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RasterioInterpolator:
"""Rasterio Interpolation Attributes ---------- {interpolator_attributes} rasterio_interpolators : list of str Interpolator methods available via rasterio"""
def can_interpolate(self, udims, source_coordinates, eval_coordinates):
"""{interpolator_can_interpolate... | stack_v2_sparse_classes_75kplus_train_068404 | 4,214 | permissive | [
{
"docstring": "{interpolator_can_interpolate}",
"name": "can_interpolate",
"signature": "def can_interpolate(self, udims, source_coordinates, eval_coordinates)"
},
{
"docstring": "{interpolator_interpolate}",
"name": "interpolate",
"signature": "def interpolate(self, udims, source_coord... | 2 | stack_v2_sparse_classes_30k_train_054484 | Implement the Python class `RasterioInterpolator` described below.
Class description:
Rasterio Interpolation Attributes ---------- {interpolator_attributes} rasterio_interpolators : list of str Interpolator methods available via rasterio
Method signatures and docstrings:
- def can_interpolate(self, udims, source_coor... | Implement the Python class `RasterioInterpolator` described below.
Class description:
Rasterio Interpolation Attributes ---------- {interpolator_attributes} rasterio_interpolators : list of str Interpolator methods available via rasterio
Method signatures and docstrings:
- def can_interpolate(self, udims, source_coor... | 66d8ec7a9086e39347e32922e15a3f59cb055415 | <|skeleton|>
class RasterioInterpolator:
"""Rasterio Interpolation Attributes ---------- {interpolator_attributes} rasterio_interpolators : list of str Interpolator methods available via rasterio"""
def can_interpolate(self, udims, source_coordinates, eval_coordinates):
"""{interpolator_can_interpolate... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RasterioInterpolator:
"""Rasterio Interpolation Attributes ---------- {interpolator_attributes} rasterio_interpolators : list of str Interpolator methods available via rasterio"""
def can_interpolate(self, udims, source_coordinates, eval_coordinates):
"""{interpolator_can_interpolate}"""
... | the_stack_v2_python_sparse | podpac/core/interpolation/rasterio_interpolator.py | creare-com/podpac | train | 48 |
85807e817813c4f6ed9e0f089ec36f1c8f2ee60e | [
"self.x = np.array(x)\nself.y = np.array(y)\nself.feature_names = x_feature_names\nself.label_names = y_label_names\nself.cv_parts = cv_parts",
"if x_test is None:\n x_test = self.x\nclf.fit(self.x, self.y)\ny_pred = clf.predict(x_test)\nreturn (clf, y_pred)",
"if one_vs_rest:\n clf = OneVsRestClassifier(... | <|body_start_0|>
self.x = np.array(x)
self.y = np.array(y)
self.feature_names = x_feature_names
self.label_names = y_label_names
self.cv_parts = cv_parts
<|end_body_0|>
<|body_start_1|>
if x_test is None:
x_test = self.x
clf.fit(self.x, self.y)
... | Base classifier for all implemented classifiers - parent class. All implemented classifiers needs to have implementation of its methods. | BaseClassifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseClassifier:
"""Base classifier for all implemented classifiers - parent class. All implemented classifiers needs to have implementation of its methods."""
def __init__(self, x, y, x_feature_names, y_label_names, cv_parts=5):
""":param x: list of x values/features in shape (number... | stack_v2_sparse_classes_75kplus_train_068405 | 4,977 | no_license | [
{
"docstring": ":param x: list of x values/features in shape (number of instances x number of features); x_train :param y: list of labels, 1D vector of numbers from 0 to N-1, where N is number of labels; y_train :param x_feature_names: list of feature names = x data column headers :param y_label_names: list of ... | 6 | null | Implement the Python class `BaseClassifier` described below.
Class description:
Base classifier for all implemented classifiers - parent class. All implemented classifiers needs to have implementation of its methods.
Method signatures and docstrings:
- def __init__(self, x, y, x_feature_names, y_label_names, cv_parts... | Implement the Python class `BaseClassifier` described below.
Class description:
Base classifier for all implemented classifiers - parent class. All implemented classifiers needs to have implementation of its methods.
Method signatures and docstrings:
- def __init__(self, x, y, x_feature_names, y_label_names, cv_parts... | 5630a5be624305b5db5f9daae8c66c32bfdfce42 | <|skeleton|>
class BaseClassifier:
"""Base classifier for all implemented classifiers - parent class. All implemented classifiers needs to have implementation of its methods."""
def __init__(self, x, y, x_feature_names, y_label_names, cv_parts=5):
""":param x: list of x values/features in shape (number... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseClassifier:
"""Base classifier for all implemented classifiers - parent class. All implemented classifiers needs to have implementation of its methods."""
def __init__(self, x, y, x_feature_names, y_label_names, cv_parts=5):
""":param x: list of x values/features in shape (number of instances... | the_stack_v2_python_sparse | classifiers/base_classifier.py | lukaszsus/memotion-images-analysis | train | 0 |
6a576e5319ac2dd4d542a18e16966eb85664ea0e | [
"if lang == 'en':\n self.__trans = None\nelse:\n self.__trans = gettext.translation(LOCALEDOMAIN, LOCALEDIR, [lang], fallback=True)",
"if self.__trans:\n return self.__trans.gettext(message)\nelse:\n return unicode(gettext.gettext(message))"
] | <|body_start_0|>
if lang == 'en':
self.__trans = None
else:
self.__trans = gettext.translation(LOCALEDOMAIN, LOCALEDIR, [lang], fallback=True)
<|end_body_0|>
<|body_start_1|>
if self.__trans:
return self.__trans.gettext(message)
else:
retu... | This class provides translated strings for the configured language. | Translator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Translator:
"""This class provides translated strings for the configured language."""
def __init__(self, lang='en'):
""":param lang: The language to translate to. The language can be: * The name of any installed .mo file * "en" to use the message strings in the code * "default" to us... | stack_v2_sparse_classes_75kplus_train_068406 | 17,715 | no_license | [
{
"docstring": ":param lang: The language to translate to. The language can be: * The name of any installed .mo file * \"en\" to use the message strings in the code * \"default\" to use the default translation being used by gettext. :type lang: string :return: nothing",
"name": "__init__",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_013456 | Implement the Python class `Translator` described below.
Class description:
This class provides translated strings for the configured language.
Method signatures and docstrings:
- def __init__(self, lang='en'): :param lang: The language to translate to. The language can be: * The name of any installed .mo file * "en"... | Implement the Python class `Translator` described below.
Class description:
This class provides translated strings for the configured language.
Method signatures and docstrings:
- def __init__(self, lang='en'): :param lang: The language to translate to. The language can be: * The name of any installed .mo file * "en"... | 222ebf6c9d4357af9e324a88d3aaa9641873853c | <|skeleton|>
class Translator:
"""This class provides translated strings for the configured language."""
def __init__(self, lang='en'):
""":param lang: The language to translate to. The language can be: * The name of any installed .mo file * "en" to use the message strings in the code * "default" to us... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Translator:
"""This class provides translated strings for the configured language."""
def __init__(self, lang='en'):
""":param lang: The language to translate to. The language can be: * The name of any installed .mo file * "en" to use the message strings in the code * "default" to use the default... | the_stack_v2_python_sparse | AncestorFill/AncestorFill.py | jralls/addons-source | train | 0 |
68ad5214491d94b3cadddcb31441c3ba95632f6d | [
"self.sensor = gateway.api.sensors[sensor_id]\nself.gateway = gateway\nself.description = description\nself.async_add_entities = async_add_entities\nself.unsubscribe = self.sensor.subscribe(self.async_update_callback)",
"if self.description.update_key in self.sensor.changed_keys:\n self.unsubscribe()\n self... | <|body_start_0|>
self.sensor = gateway.api.sensors[sensor_id]
self.gateway = gateway
self.description = description
self.async_add_entities = async_add_entities
self.unsubscribe = self.sensor.subscribe(self.async_update_callback)
<|end_body_0|>
<|body_start_1|>
if self.d... | Track sensors without a battery state and add entity when battery state exist. | DeconzBatteryTracker | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeconzBatteryTracker:
"""Track sensors without a battery state and add entity when battery state exist."""
def __init__(self, sensor_id: str, gateway: DeconzGateway, description: DeconzSensorDescription, async_add_entities: AddEntitiesCallback) -> None:
"""Set up tracker."""
... | stack_v2_sparse_classes_75kplus_train_068407 | 16,422 | permissive | [
{
"docstring": "Set up tracker.",
"name": "__init__",
"signature": "def __init__(self, sensor_id: str, gateway: DeconzGateway, description: DeconzSensorDescription, async_add_entities: AddEntitiesCallback) -> None"
},
{
"docstring": "Update the device's state.",
"name": "async_update_callbac... | 2 | stack_v2_sparse_classes_30k_train_001032 | Implement the Python class `DeconzBatteryTracker` described below.
Class description:
Track sensors without a battery state and add entity when battery state exist.
Method signatures and docstrings:
- def __init__(self, sensor_id: str, gateway: DeconzGateway, description: DeconzSensorDescription, async_add_entities: ... | Implement the Python class `DeconzBatteryTracker` described below.
Class description:
Track sensors without a battery state and add entity when battery state exist.
Method signatures and docstrings:
- def __init__(self, sensor_id: str, gateway: DeconzGateway, description: DeconzSensorDescription, async_add_entities: ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class DeconzBatteryTracker:
"""Track sensors without a battery state and add entity when battery state exist."""
def __init__(self, sensor_id: str, gateway: DeconzGateway, description: DeconzSensorDescription, async_add_entities: AddEntitiesCallback) -> None:
"""Set up tracker."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeconzBatteryTracker:
"""Track sensors without a battery state and add entity when battery state exist."""
def __init__(self, sensor_id: str, gateway: DeconzGateway, description: DeconzSensorDescription, async_add_entities: AddEntitiesCallback) -> None:
"""Set up tracker."""
self.sensor =... | the_stack_v2_python_sparse | homeassistant/components/deconz/sensor.py | home-assistant/core | train | 35,501 |
5caa4aa84954312f4e003054e7fc477ad9b7511a | [
"self._num_classes = num_classes\nself._per_class_metric = per_class_metric\nself._dice_op_overall = segmentation_losses.SegmentationLossDiceScore(metric_type=metric_type)\nself._dice_scores_overall = tf.Variable(0.0)\nself._count = tf.Variable(0.0)\nif self._per_class_metric:\n self._dice_op_per_class = segment... | <|body_start_0|>
self._num_classes = num_classes
self._per_class_metric = per_class_metric
self._dice_op_overall = segmentation_losses.SegmentationLossDiceScore(metric_type=metric_type)
self._dice_scores_overall = tf.Variable(0.0)
self._count = tf.Variable(0.0)
if self._p... | Dice score metric for semantic segmentation. This class follows the same function interface as tf.keras.metrics.Metric but does not derive from tf.keras.metrics.Metric or utilize its functions. The reason is a tf.keras.metrics.Metric object does not run well on CPU while created on GPU, when running with MirroredStrate... | DiceScore | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiceScore:
"""Dice score metric for semantic segmentation. This class follows the same function interface as tf.keras.metrics.Metric but does not derive from tf.keras.metrics.Metric or utilize its functions. The reason is a tf.keras.metrics.Metric object does not run well on CPU while created on ... | stack_v2_sparse_classes_75kplus_train_068408 | 5,352 | permissive | [
{
"docstring": "Constructs segmentation evaluator class. Args: num_classes: The number of classes. metric_type: An optional `str` of type of dice scores. per_class_metric: Whether to report per-class metric. name: A `str`, name of the metric instance.. dtype: The data type of the metric result.",
"name": "_... | 4 | stack_v2_sparse_classes_30k_train_043758 | Implement the Python class `DiceScore` described below.
Class description:
Dice score metric for semantic segmentation. This class follows the same function interface as tf.keras.metrics.Metric but does not derive from tf.keras.metrics.Metric or utilize its functions. The reason is a tf.keras.metrics.Metric object doe... | Implement the Python class `DiceScore` described below.
Class description:
Dice score metric for semantic segmentation. This class follows the same function interface as tf.keras.metrics.Metric but does not derive from tf.keras.metrics.Metric or utilize its functions. The reason is a tf.keras.metrics.Metric object doe... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class DiceScore:
"""Dice score metric for semantic segmentation. This class follows the same function interface as tf.keras.metrics.Metric but does not derive from tf.keras.metrics.Metric or utilize its functions. The reason is a tf.keras.metrics.Metric object does not run well on CPU while created on ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DiceScore:
"""Dice score metric for semantic segmentation. This class follows the same function interface as tf.keras.metrics.Metric but does not derive from tf.keras.metrics.Metric or utilize its functions. The reason is a tf.keras.metrics.Metric object does not run well on CPU while created on GPU, when run... | the_stack_v2_python_sparse | official/projects/volumetric_models/evaluation/segmentation_metrics.py | jianzhnie/models | train | 2 |
8ce7a4a2eda571f61fb19354435555f67422cd01 | [
"if len(self.pool.samples) == 0:\n raise LookupError('no samples for executing samtools')\nif self.chromosome not in self.pool.vcf:\n self.pool.vcf[self.chromosome] = VcfFile.VcfFile(self.pool, chrom=self.chromosome, bcf=True)\n inputFileString = ''\n for sample in self.pool.samples:\n inputFileS... | <|body_start_0|>
if len(self.pool.samples) == 0:
raise LookupError('no samples for executing samtools')
if self.chromosome not in self.pool.vcf:
self.pool.vcf[self.chromosome] = VcfFile.VcfFile(self.pool, chrom=self.chromosome, bcf=True)
inputFileString = ''
... | SamtoolsMpileup | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SamtoolsMpileup:
def callSnvs(self):
"""The method samtoolsMpileup calls the single nucleotide variations of a pool with samtools mpileup. :param pool: the pool to call all SNVs from :type pool: an instance of a :py:class:`Pool.Pool` object :raises: LookupError if the pool has no samples... | stack_v2_sparse_classes_75kplus_train_068409 | 3,327 | no_license | [
{
"docstring": "The method samtoolsMpileup calls the single nucleotide variations of a pool with samtools mpileup. :param pool: the pool to call all SNVs from :type pool: an instance of a :py:class:`Pool.Pool` object :raises: LookupError if the pool has no samples to execute samtools on",
"name": "callSnvs"... | 2 | stack_v2_sparse_classes_30k_train_006674 | Implement the Python class `SamtoolsMpileup` described below.
Class description:
Implement the SamtoolsMpileup class.
Method signatures and docstrings:
- def callSnvs(self): The method samtoolsMpileup calls the single nucleotide variations of a pool with samtools mpileup. :param pool: the pool to call all SNVs from :... | Implement the Python class `SamtoolsMpileup` described below.
Class description:
Implement the SamtoolsMpileup class.
Method signatures and docstrings:
- def callSnvs(self): The method samtoolsMpileup calls the single nucleotide variations of a pool with samtools mpileup. :param pool: the pool to call all SNVs from :... | 53315eca821785aa02218e903b60921ecf18246b | <|skeleton|>
class SamtoolsMpileup:
def callSnvs(self):
"""The method samtoolsMpileup calls the single nucleotide variations of a pool with samtools mpileup. :param pool: the pool to call all SNVs from :type pool: an instance of a :py:class:`Pool.Pool` object :raises: LookupError if the pool has no samples... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SamtoolsMpileup:
def callSnvs(self):
"""The method samtoolsMpileup calls the single nucleotide variations of a pool with samtools mpileup. :param pool: the pool to call all SNVs from :type pool: an instance of a :py:class:`Pool.Pool` object :raises: LookupError if the pool has no samples to execute sa... | the_stack_v2_python_sparse | pythonCodebase/src/programs/snvCallers/SamtoolsMpileup.py | JJacobi13/VLPB | train | 0 | |
790d98e00bb0145128e134623287e9008f58d3a6 | [
"if len(nums) <= 1:\n return 0\nfor i in range(len(nums)):\n if i == 0:\n if nums[i] > nums[i + 1]:\n return i\n elif i == len(nums) - 1:\n if nums[i] > nums[i - 1]:\n return i\n elif nums[i] > nums[i - 1] and nums[i] > nums[i + 1]:\n return i\nreturn -1",
"i... | <|body_start_0|>
if len(nums) <= 1:
return 0
for i in range(len(nums)):
if i == 0:
if nums[i] > nums[i + 1]:
return i
elif i == len(nums) - 1:
if nums[i] > nums[i - 1]:
return i
elif n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findPeakElement(self, nums: List[int]) -> int:
"""常规解法，O（n）时间复杂度"""
<|body_0|>
def findPeakElement_2(self, nums: List[int]) -> int:
"""时间复杂度为O（logn）的解法"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(nums) <= 1:
retu... | stack_v2_sparse_classes_75kplus_train_068410 | 2,327 | no_license | [
{
"docstring": "常规解法，O（n）时间复杂度",
"name": "findPeakElement",
"signature": "def findPeakElement(self, nums: List[int]) -> int"
},
{
"docstring": "时间复杂度为O（logn）的解法",
"name": "findPeakElement_2",
"signature": "def findPeakElement_2(self, nums: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_051345 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPeakElement(self, nums: List[int]) -> int: 常规解法，O（n）时间复杂度
- def findPeakElement_2(self, nums: List[int]) -> int: 时间复杂度为O（logn）的解法 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPeakElement(self, nums: List[int]) -> int: 常规解法，O（n）时间复杂度
- def findPeakElement_2(self, nums: List[int]) -> int: 时间复杂度为O（logn）的解法
<|skeleton|>
class Solution:
def f... | 13e7ec9fe7a92ab13b247bd4edeb1ada5de81a08 | <|skeleton|>
class Solution:
def findPeakElement(self, nums: List[int]) -> int:
"""常规解法，O（n）时间复杂度"""
<|body_0|>
def findPeakElement_2(self, nums: List[int]) -> int:
"""时间复杂度为O（logn）的解法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findPeakElement(self, nums: List[int]) -> int:
"""常规解法，O（n）时间复杂度"""
if len(nums) <= 1:
return 0
for i in range(len(nums)):
if i == 0:
if nums[i] > nums[i + 1]:
return i
elif i == len(nums) - 1:
... | the_stack_v2_python_sparse | Algorithms/162_Find_Peak_Element/Find_Peak_Element.py | lirui-ML/my_leetcode | train | 1 | |
bebd68cb51dcce31b359ff68edacb5bedfd905b0 | [
"text = 'Alignment tensors.\\n\\n'\ntext = text + '%-8s%-20s\\n' % ('Index', 'Name')\nfor i in range(len(self)):\n text = text + '%-8i%-20s\\n' % (i, self[i].name)\ntext = text + \"\\nThese can be accessed by typing 'pipe.align_tensor[index]'.\\n\"\nreturn text",
"obj = AlignTensorData(name)\nself.append(obj)\... | <|body_start_0|>
text = 'Alignment tensors.\n\n'
text = text + '%-8s%-20s\n' % ('Index', 'Name')
for i in range(len(self)):
text = text + '%-8i%-20s\n' % (i, self[i].name)
text = text + "\nThese can be accessed by typing 'pipe.align_tensor[index]'.\n"
return text
<|en... | List type data container for holding all the alignment tensors. The elements of the list should be AlignTensorData instances. | AlignTensorList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlignTensorList:
"""List type data container for holding all the alignment tensors. The elements of the list should be AlignTensorData instances."""
def __repr__(self):
"""Replacement function for displaying an instance of this class."""
<|body_0|>
def add_item(self, nam... | stack_v2_sparse_classes_75kplus_train_068411 | 47,193 | no_license | [
{
"docstring": "Replacement function for displaying an instance of this class.",
"name": "__repr__",
"signature": "def __repr__(self)"
},
{
"docstring": "Append a new AlignTensorData instance to the list. @param name: The tensor ID string. @type name: str @return: The tensor object. @rtype: Alig... | 5 | stack_v2_sparse_classes_30k_train_038644 | Implement the Python class `AlignTensorList` described below.
Class description:
List type data container for holding all the alignment tensors. The elements of the list should be AlignTensorData instances.
Method signatures and docstrings:
- def __repr__(self): Replacement function for displaying an instance of this... | Implement the Python class `AlignTensorList` described below.
Class description:
List type data container for holding all the alignment tensors. The elements of the list should be AlignTensorData instances.
Method signatures and docstrings:
- def __repr__(self): Replacement function for displaying an instance of this... | c317326ddeacd1a1c608128769676899daeae531 | <|skeleton|>
class AlignTensorList:
"""List type data container for holding all the alignment tensors. The elements of the list should be AlignTensorData instances."""
def __repr__(self):
"""Replacement function for displaying an instance of this class."""
<|body_0|>
def add_item(self, nam... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AlignTensorList:
"""List type data container for holding all the alignment tensors. The elements of the list should be AlignTensorData instances."""
def __repr__(self):
"""Replacement function for displaying an instance of this class."""
text = 'Alignment tensors.\n\n'
text = text... | the_stack_v2_python_sparse | data_store/align_tensor.py | jlec/relax | train | 4 |
99a6742b6e158c89d0d84b799f8187795b2123c4 | [
"klassen = CompetitieIndivKlasse.objects.select_related('competitie').filter(competitie=comp).prefetch_related('regiocompetitiesporterboog_set').order_by('volgorde')\nfor obj in klassen:\n if obj.min_ag > AG_NUL:\n ag_str = '%5.3f' % obj.min_ag\n obj.min_ag_str = ag_str.replace('.', ',')\n if to... | <|body_start_0|>
klassen = CompetitieIndivKlasse.objects.select_related('competitie').filter(competitie=comp).prefetch_related('regiocompetitiesporterboog_set').order_by('volgorde')
for obj in klassen:
if obj.min_ag > AG_NUL:
ag_str = '%5.3f' % obj.min_ag
obj.... | deze view laat de vastgestelde aanvangsgemiddelden voor de volgende competitie zien | KlassengrenzenTonenView | [
"BSD-3-Clause-Clear"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KlassengrenzenTonenView:
"""deze view laat de vastgestelde aanvangsgemiddelden voor de volgende competitie zien"""
def _get_indiv_klassen(comp, toon_aantal):
"""geef een lijst van individuele competitie wedstrijdklassen terug met het AG geformatteerd voor presentatie."""
<|bo... | stack_v2_sparse_classes_75kplus_train_068412 | 4,879 | permissive | [
{
"docstring": "geef een lijst van individuele competitie wedstrijdklassen terug met het AG geformatteerd voor presentatie.",
"name": "_get_indiv_klassen",
"signature": "def _get_indiv_klassen(comp, toon_aantal)"
},
{
"docstring": "geef een lijst van team competitie wedstrijdklassen terug met he... | 3 | stack_v2_sparse_classes_30k_train_026389 | Implement the Python class `KlassengrenzenTonenView` described below.
Class description:
deze view laat de vastgestelde aanvangsgemiddelden voor de volgende competitie zien
Method signatures and docstrings:
- def _get_indiv_klassen(comp, toon_aantal): geef een lijst van individuele competitie wedstrijdklassen terug m... | Implement the Python class `KlassengrenzenTonenView` described below.
Class description:
deze view laat de vastgestelde aanvangsgemiddelden voor de volgende competitie zien
Method signatures and docstrings:
- def _get_indiv_klassen(comp, toon_aantal): geef een lijst van individuele competitie wedstrijdklassen terug m... | 5ed38165a231f0caa56f67e8faf2dd074916e500 | <|skeleton|>
class KlassengrenzenTonenView:
"""deze view laat de vastgestelde aanvangsgemiddelden voor de volgende competitie zien"""
def _get_indiv_klassen(comp, toon_aantal):
"""geef een lijst van individuele competitie wedstrijdklassen terug met het AG geformatteerd voor presentatie."""
<|bo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KlassengrenzenTonenView:
"""deze view laat de vastgestelde aanvangsgemiddelden voor de volgende competitie zien"""
def _get_indiv_klassen(comp, toon_aantal):
"""geef een lijst van individuele competitie wedstrijdklassen terug met het AG geformatteerd voor presentatie."""
klassen = Competi... | the_stack_v2_python_sparse | Competitie/views_klassengrenzen.py | RamonvdW/nhb-apps | train | 2 |
570f3cae1483e576b7f35e887ddcf378398fb5d5 | [
"super(TemporalConvNet, self).__init__()\nself.C = C\nself.X = X\nself.R = R\nself.mask_nonlinear = mask_nonlinear\nlayer_norm = ChannelwiseLayerNorm(N)\nbottleneck_conv1x1 = nn.Conv1d(N, B, 1, bias=False)\nrepeats = []\nfor r in range(R):\n blocks = []\n for x in range(X):\n dilation = 2 ** x\n ... | <|body_start_0|>
super(TemporalConvNet, self).__init__()
self.C = C
self.X = X
self.R = R
self.mask_nonlinear = mask_nonlinear
layer_norm = ChannelwiseLayerNorm(N)
bottleneck_conv1x1 = nn.Conv1d(N, B, 1, bias=False)
repeats = []
for r in range(R):
... | TemporalConvNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemporalConvNet:
def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu', locs=None, feat_loc='residual'):
"""Args: N: Number of filters in autoencoder B: Number of channels in bottleneck 1 × 1-conv block H: Number of channels in convolutional blocks ... | stack_v2_sparse_classes_75kplus_train_068413 | 14,028 | no_license | [
{
"docstring": "Args: N: Number of filters in autoencoder B: Number of channels in bottleneck 1 × 1-conv block H: Number of channels in convolutional blocks P: Kernel size in convolutional blocks X: Number of convolutional blocks in each repeat R: Number of repeats C: Number of speakers norm_type: BN, gLN, cLN ... | 3 | stack_v2_sparse_classes_30k_train_031801 | Implement the Python class `TemporalConvNet` described below.
Class description:
Implement the TemporalConvNet class.
Method signatures and docstrings:
- def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu', locs=None, feat_loc='residual'): Args: N: Number of filters in autoenc... | Implement the Python class `TemporalConvNet` described below.
Class description:
Implement the TemporalConvNet class.
Method signatures and docstrings:
- def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu', locs=None, feat_loc='residual'): Args: N: Number of filters in autoenc... | 01314d4f1f5bd35d5a4938969948dd4f0bf13ab2 | <|skeleton|>
class TemporalConvNet:
def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu', locs=None, feat_loc='residual'):
"""Args: N: Number of filters in autoencoder B: Number of channels in bottleneck 1 × 1-conv block H: Number of channels in convolutional blocks ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TemporalConvNet:
def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu', locs=None, feat_loc='residual'):
"""Args: N: Number of filters in autoencoder B: Number of channels in bottleneck 1 × 1-conv block H: Number of channels in convolutional blocks P: Kernel size... | the_stack_v2_python_sparse | src/da_conv_tasnet.py | henryhenrychen/speech_separation_domain_adaptation | train | 0 | |
33e548776cc0853b16741e70ac517fd549d35b84 | [
"super(StackedGCN, self).__init__()\nself.args = args\nself.input_channels = input_channels\nself.output_channels = output_channels\nself.setup_layers()",
"self.layers = []\nself.args.layers = [self.input_channels] + self.args.layers + [self.output_channels]\nfor i, _ in enumerate(self.args.layers[:-1]):\n sel... | <|body_start_0|>
super(StackedGCN, self).__init__()
self.args = args
self.input_channels = input_channels
self.output_channels = output_channels
self.setup_layers()
<|end_body_0|>
<|body_start_1|>
self.layers = []
self.args.layers = [self.input_channels] + self.a... | Multi-layer GCN model. | StackedGCN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StackedGCN:
"""Multi-layer GCN model."""
def __init__(self, args, input_channels, output_channels):
""":param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features."""
<|body_0|>
def setup_layers(self):
"""Creati... | stack_v2_sparse_classes_75kplus_train_068414 | 3,788 | no_license | [
{
"docstring": ":param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features.",
"name": "__init__",
"signature": "def __init__(self, args, input_channels, output_channels)"
},
{
"docstring": "Creating the layes based on the args.",
"name": "... | 3 | stack_v2_sparse_classes_30k_test_001112 | Implement the Python class `StackedGCN` described below.
Class description:
Multi-layer GCN model.
Method signatures and docstrings:
- def __init__(self, args, input_channels, output_channels): :param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features.
- def setup... | Implement the Python class `StackedGCN` described below.
Class description:
Multi-layer GCN model.
Method signatures and docstrings:
- def __init__(self, args, input_channels, output_channels): :param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features.
- def setup... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class StackedGCN:
"""Multi-layer GCN model."""
def __init__(self, args, input_channels, output_channels):
""":param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features."""
<|body_0|>
def setup_layers(self):
"""Creati... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StackedGCN:
"""Multi-layer GCN model."""
def __init__(self, args, input_channels, output_channels):
""":param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features."""
super(StackedGCN, self).__init__()
self.args = args
se... | the_stack_v2_python_sparse | generated/test_benedekrozemberczki_ClusterGCN.py | jansel/pytorch-jit-paritybench | train | 35 |
16f9664f34326755cc256a0606a3f32728fae5f3 | [
"input1 = tf.random.stateless_normal([4, 4, 4], [234, 231])\nlayer1 = preproc_layers.Transpose(perm=perm, conjugate=conjugate)\noutput1 = layer1(input1)\nself.assertAllEqual(output1, tf.transpose(input1, perm=perm, conjugate=conjugate))",
"config = dict(perm=[1, 0], conjugate=True, name='transpose', dtype='float3... | <|body_start_0|>
input1 = tf.random.stateless_normal([4, 4, 4], [234, 231])
layer1 = preproc_layers.Transpose(perm=perm, conjugate=conjugate)
output1 = layer1(input1)
self.assertAllEqual(output1, tf.transpose(input1, perm=perm, conjugate=conjugate))
<|end_body_0|>
<|body_start_1|>
... | Tests for layer `Transpose`. | TransposeTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransposeTest:
"""Tests for layer `Transpose`."""
def test_result(self, perm, conjugate):
"""Test result shapes."""
<|body_0|>
def test_serialize_deserialize(self):
"""Test de/serialization."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
input1... | stack_v2_sparse_classes_75kplus_train_068415 | 6,474 | permissive | [
{
"docstring": "Test result shapes.",
"name": "test_result",
"signature": "def test_result(self, perm, conjugate)"
},
{
"docstring": "Test de/serialization.",
"name": "test_serialize_deserialize",
"signature": "def test_serialize_deserialize(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002572 | Implement the Python class `TransposeTest` described below.
Class description:
Tests for layer `Transpose`.
Method signatures and docstrings:
- def test_result(self, perm, conjugate): Test result shapes.
- def test_serialize_deserialize(self): Test de/serialization. | Implement the Python class `TransposeTest` described below.
Class description:
Tests for layer `Transpose`.
Method signatures and docstrings:
- def test_result(self, perm, conjugate): Test result shapes.
- def test_serialize_deserialize(self): Test de/serialization.
<|skeleton|>
class TransposeTest:
"""Tests for... | cfd8930ee5281e7f6dceb17c4a5acaf625fd3243 | <|skeleton|>
class TransposeTest:
"""Tests for layer `Transpose`."""
def test_result(self, perm, conjugate):
"""Test result shapes."""
<|body_0|>
def test_serialize_deserialize(self):
"""Test de/serialization."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TransposeTest:
"""Tests for layer `Transpose`."""
def test_result(self, perm, conjugate):
"""Test result shapes."""
input1 = tf.random.stateless_normal([4, 4, 4], [234, 231])
layer1 = preproc_layers.Transpose(perm=perm, conjugate=conjugate)
output1 = layer1(input1)
... | the_stack_v2_python_sparse | tensorflow_mri/python/layers/preproc_layers_test.py | mrphys/tensorflow-mri | train | 29 |
a8059bf4412b8d3615ec1e4fa1e8e88d5a6906dc | [
"def dfs(arr, index):\n if sum(arr) == target:\n res.append(arr)\n return\n for i, num in enumerate(candidates):\n if i >= index and sum(arr) + num <= target:\n dfs(arr + [num], i)\nres = []\ndfs([], 0)\nreturn res",
"candidates.sort()\nn = len(candidates)\nres = []\n\ndef ba... | <|body_start_0|>
def dfs(arr, index):
if sum(arr) == target:
res.append(arr)
return
for i, num in enumerate(candidates):
if i >= index and sum(arr) + num <= target:
dfs(arr + [num], i)
res = []
dfs([], 0)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
"""思路：1. :param candidates: :param target: :return:"""
<|body_0|>
def combinationSum2(self, candidates: List[int], target: int) -> List[List[int]]:
"""执行用时 :52 ms, 在所有 Python3 ... | stack_v2_sparse_classes_75kplus_train_068416 | 2,275 | no_license | [
{
"docstring": "思路：1. :param candidates: :param target: :return:",
"name": "combinationSum",
"signature": "def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]"
},
{
"docstring": "执行用时 :52 ms, 在所有 Python3 提交中击败了89.99%的用户 内存消耗 :13.8 MB, 在所有 Python3 提交中击败了5.00%的用户 :param... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]: 思路：1. :param candidates: :param target: :return:
- def combinationSum2(self, candidates: List[int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]: 思路：1. :param candidates: :param target: :return:
- def combinationSum2(self, candidates: List[int... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
"""思路：1. :param candidates: :param target: :return:"""
<|body_0|>
def combinationSum2(self, candidates: List[int], target: int) -> List[List[int]]:
"""执行用时 :52 ms, 在所有 Python3 ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
"""思路：1. :param candidates: :param target: :return:"""
def dfs(arr, index):
if sum(arr) == target:
res.append(arr)
return
for i, num in enumerate(c... | the_stack_v2_python_sparse | LeetCode/回溯法/39. Combination Sum.py | yiming1012/MyLeetCode | train | 2 | |
53b2d13537d0c70e9e253dcf50b2dfb1088e9a3a | [
"mit.Mit.__init__(self)\nself.regist_moc(OraSyncPriority.OraSyncPriority, OraSyncPriority.OraSyncPriorityRule)\nself.open_oracle(**db_cfg_info.get_configure(db_cfg_info.ORACLE_SYNC_CON_NAME))\nself.init_mit_lock()",
"data = self.rdm_find('OraSyncPriority', ne_id=ne_id, priority=priority)\nif len(data) > 0:\n r... | <|body_start_0|>
mit.Mit.__init__(self)
self.regist_moc(OraSyncPriority.OraSyncPriority, OraSyncPriority.OraSyncPriorityRule)
self.open_oracle(**db_cfg_info.get_configure(db_cfg_info.ORACLE_SYNC_CON_NAME))
self.init_mit_lock()
<|end_body_0|>
<|body_start_1|>
data = self.rdm_find... | Class: DBSyncPriorityMit Description: ͬȼܵmit Base: mit.Mit Others: | DBSyncPriorityMit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DBSyncPriorityMit:
"""Class: DBSyncPriorityMit Description: ͬȼܵmit Base: mit.Mit Others:"""
def __init__(self):
"""Method: __init__ Description: 캯 Parameter: Return: Others:"""
<|body_0|>
def get_priority_info(self, ne_id, priority):
"""Method: get_priority_info ... | stack_v2_sparse_classes_75kplus_train_068417 | 2,686 | no_license | [
{
"docstring": "Method: __init__ Description: 캯 Parameter: Return: Others:",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Method: get_priority_info Description: ȼȡͬ¼ Paramters: ne_id: ԪID priority: ȼ Return: ͬ¼ҲNone",
"name": "get_priority_info",
"signature": ... | 4 | null | Implement the Python class `DBSyncPriorityMit` described below.
Class description:
Class: DBSyncPriorityMit Description: ͬȼܵmit Base: mit.Mit Others:
Method signatures and docstrings:
- def __init__(self): Method: __init__ Description: 캯 Parameter: Return: Others:
- def get_priority_info(self, ne_id, priority): Metho... | Implement the Python class `DBSyncPriorityMit` described below.
Class description:
Class: DBSyncPriorityMit Description: ͬȼܵmit Base: mit.Mit Others:
Method signatures and docstrings:
- def __init__(self): Method: __init__ Description: 캯 Parameter: Return: Others:
- def get_priority_info(self, ne_id, priority): Metho... | e78df71fbc5d73dd93ba9452d4b54183fe1e7e1f | <|skeleton|>
class DBSyncPriorityMit:
"""Class: DBSyncPriorityMit Description: ͬȼܵmit Base: mit.Mit Others:"""
def __init__(self):
"""Method: __init__ Description: 캯 Parameter: Return: Others:"""
<|body_0|>
def get_priority_info(self, ne_id, priority):
"""Method: get_priority_info ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DBSyncPriorityMit:
"""Class: DBSyncPriorityMit Description: ͬȼܵmit Base: mit.Mit Others:"""
def __init__(self):
"""Method: __init__ Description: 캯 Parameter: Return: Others:"""
mit.Mit.__init__(self)
self.regist_moc(OraSyncPriority.OraSyncPriority, OraSyncPriority.OraSyncPriorityR... | the_stack_v2_python_sparse | weixin/code/rfid_plt/db_sync/db_sync_update_app/db_sync_priority_mit.py | allenforrest/wxbiz | train | 0 |
204837e6365227f2b5c9259cee61720831530093 | [
"m = MultiFileInput()\nself.assertTrue(m.needs_multipart_form)\nself.assertFalse(m.is_hidden)",
"m = MultiFileInput({'count': 0})\nr = m.render(name='blah', value='bla', attrs={'id': 'test'})\nself.assert_('<input type=\"file\" name=\"blah[]\" id=\"test0\" />' in r)",
"m = MultiFileInput()\nr = m.render(name='b... | <|body_start_0|>
m = MultiFileInput()
self.assertTrue(m.needs_multipart_form)
self.assertFalse(m.is_hidden)
<|end_body_0|>
<|body_start_1|>
m = MultiFileInput({'count': 0})
r = m.render(name='blah', value='bla', attrs={'id': 'test'})
self.assert_('<input type="file" name... | Tests for the widget itself. | MultiFileInputTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiFileInputTest:
"""Tests for the widget itself."""
def testBasics(self):
"""Make sure the basics are correct (needs_multipart_form & is_hidden)."""
<|body_0|>
def testNoRender(self):
"""Makes sure we show a minimum of 1 input box."""
<|body_1|>
d... | stack_v2_sparse_classes_75kplus_train_068418 | 3,598 | no_license | [
{
"docstring": "Make sure the basics are correct (needs_multipart_form & is_hidden).",
"name": "testBasics",
"signature": "def testBasics(self)"
},
{
"docstring": "Makes sure we show a minimum of 1 input box.",
"name": "testNoRender",
"signature": "def testNoRender(self)"
},
{
"d... | 4 | stack_v2_sparse_classes_30k_test_000555 | Implement the Python class `MultiFileInputTest` described below.
Class description:
Tests for the widget itself.
Method signatures and docstrings:
- def testBasics(self): Make sure the basics are correct (needs_multipart_form & is_hidden).
- def testNoRender(self): Makes sure we show a minimum of 1 input box.
- def t... | Implement the Python class `MultiFileInputTest` described below.
Class description:
Tests for the widget itself.
Method signatures and docstrings:
- def testBasics(self): Make sure the basics are correct (needs_multipart_form & is_hidden).
- def testNoRender(self): Makes sure we show a minimum of 1 input box.
- def t... | 2791145f62a7e296be859a400499812b394249e9 | <|skeleton|>
class MultiFileInputTest:
"""Tests for the widget itself."""
def testBasics(self):
"""Make sure the basics are correct (needs_multipart_form & is_hidden)."""
<|body_0|>
def testNoRender(self):
"""Makes sure we show a minimum of 1 input box."""
<|body_1|>
d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiFileInputTest:
"""Tests for the widget itself."""
def testBasics(self):
"""Make sure the basics are correct (needs_multipart_form & is_hidden)."""
m = MultiFileInput()
self.assertTrue(m.needs_multipart_form)
self.assertFalse(m.is_hidden)
def testNoRender(self):
... | the_stack_v2_python_sparse | combaragi/ccboard/tests.py | yonseics/yonseics | train | 1 |
30d30150ac10063ee1a4e816b3ba2661930c94c1 | [
"checksum = crc(path, content)\ntry:\n fobj = File.objects.get(path=path)\nexcept File.DoesNotExist:\n return True\nelse:\n return str(fobj.checksum) != checksum",
"checksum = crc(path, content)\ntry:\n fobj = File.objects.get(path=path)\nexcept File.DoesNotExist:\n fobj = File(path=path)\nfobj.che... | <|body_start_0|>
checksum = crc(path, content)
try:
fobj = File.objects.get(path=path)
except File.DoesNotExist:
return True
else:
return str(fobj.checksum) != checksum
<|end_body_0|>
<|body_start_1|>
checksum = crc(path, content)
try:... | FileManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileManager:
def is_changed(self, path, content=None):
"""Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file is stored in DB."""
<|body_0|>
def save_file(self, path, content=None):
"""Save ... | stack_v2_sparse_classes_75kplus_train_068419 | 1,644 | no_license | [
{
"docstring": "Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file is stored in DB.",
"name": "is_changed",
"signature": "def is_changed(self, path, content=None)"
},
{
"docstring": "Save checksum of the file.",
"n... | 2 | stack_v2_sparse_classes_30k_train_019978 | Implement the Python class `FileManager` described below.
Class description:
Implement the FileManager class.
Method signatures and docstrings:
- def is_changed(self, path, content=None): Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file i... | Implement the Python class `FileManager` described below.
Class description:
Implement the FileManager class.
Method signatures and docstrings:
- def is_changed(self, path, content=None): Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file i... | 40313d4b413a219ff2f7dfc9775258f23608b2cc | <|skeleton|>
class FileManager:
def is_changed(self, path, content=None):
"""Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file is stored in DB."""
<|body_0|>
def save_file(self, path, content=None):
"""Save ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FileManager:
def is_changed(self, path, content=None):
"""Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file is stored in DB."""
checksum = crc(path, content)
try:
fobj = File.objects.get(path=pat... | the_stack_v2_python_sparse | parser/models.py | govtrack/govtrack.us-web | train | 310 | |
343d7d2e05a4a3f2296b2e3bb30e15285a7f66fb | [
"self.target = target\nif self.target is not None and self.target not in self.SUPPORTED_LINE_NOTATIONS:\n raise ValueError(f'{target} is not a supported line representation. Choose from {self.SUPPORTED_LINE_NOTATIONS}')\nif self.target == 'smiles' or (self.target is None or self.target == 'none'):\n self.conv... | <|body_start_0|>
self.target = target
if self.target is not None and self.target not in self.SUPPORTED_LINE_NOTATIONS:
raise ValueError(f'{target} is not a supported line representation. Choose from {self.SUPPORTED_LINE_NOTATIONS}')
if self.target == 'smiles' or (self.target is None ... | Molecule line notation conversion from smiles to selfies or inchi | SmilesConverter | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmilesConverter:
"""Molecule line notation conversion from smiles to selfies or inchi"""
def __init__(self, target: str=None):
"""Convert input smiles to a target line notation Args: target: target representation."""
<|body_0|>
def decode(self, inp: str):
"""Deco... | stack_v2_sparse_classes_75kplus_train_068420 | 1,998 | permissive | [
{
"docstring": "Convert input smiles to a target line notation Args: target: target representation.",
"name": "__init__",
"signature": "def __init__(self, target: str=None)"
},
{
"docstring": "Decode inputs into smiles Args: inp: input representation to decode",
"name": "decode",
"signat... | 3 | stack_v2_sparse_classes_30k_train_021771 | Implement the Python class `SmilesConverter` described below.
Class description:
Molecule line notation conversion from smiles to selfies or inchi
Method signatures and docstrings:
- def __init__(self, target: str=None): Convert input smiles to a target line notation Args: target: target representation.
- def decode(... | Implement the Python class `SmilesConverter` described below.
Class description:
Molecule line notation conversion from smiles to selfies or inchi
Method signatures and docstrings:
- def __init__(self, target: str=None): Convert input smiles to a target line notation Args: target: target representation.
- def decode(... | 4390f9fce25fa2da94338227f7c8f33a23e25b2a | <|skeleton|>
class SmilesConverter:
"""Molecule line notation conversion from smiles to selfies or inchi"""
def __init__(self, target: str=None):
"""Convert input smiles to a target line notation Args: target: target representation."""
<|body_0|>
def decode(self, inp: str):
"""Deco... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SmilesConverter:
"""Molecule line notation conversion from smiles to selfies or inchi"""
def __init__(self, target: str=None):
"""Convert input smiles to a target line notation Args: target: target representation."""
self.target = target
if self.target is not None and self.target ... | the_stack_v2_python_sparse | molfeat/utils/converters.py | datamol-io/molfeat | train | 111 |
5f5f1bcec45a0c98deb62d8df1cb3a9b2adc02b2 | [
"self.dynamodb = boto3.client('dynamodb', region_name=region)\nself.table = table_name\nself.max_items = max_items\nself.worker_num = worker_num\nself.num_workers = num_workers\nif worker_num >= num_workers:\n raise ValueError('worker_num must be less than num_workers')",
"exclusive_start_key = None\ndone = Fa... | <|body_start_0|>
self.dynamodb = boto3.client('dynamodb', region_name=region)
self.table = table_name
self.max_items = max_items
self.worker_num = worker_num
self.num_workers = num_workers
if worker_num >= num_workers:
raise ValueError('worker_num must be less... | Adds lookup key to legacy items in the S3 index table. The lookup key is collection&experiment&channel&resolution. A global secondary index (GSI) will use the lookup key to allow finding all cuboids that belong to a particular channel via a DynamoDB query. An instance of this class may be used as one worker in a parall... | LookupKeyWriter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LookupKeyWriter:
"""Adds lookup key to legacy items in the S3 index table. The lookup key is collection&experiment&channel&resolution. A global secondary index (GSI) will use the lookup key to allow finding all cuboids that belong to a particular channel via a DynamoDB query. An instance of this ... | stack_v2_sparse_classes_75kplus_train_068421 | 9,145 | permissive | [
{
"docstring": "Constructor. If parallelizing, supply worker_num and num_workers. See the AWS documentation for parallel scan here: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Scan.html#Scan.ParallelScan Args: table_name (str): Name of Dynamo S3 index table to operate on. region (str): AWS ... | 4 | stack_v2_sparse_classes_30k_train_015264 | Implement the Python class `LookupKeyWriter` described below.
Class description:
Adds lookup key to legacy items in the S3 index table. The lookup key is collection&experiment&channel&resolution. A global secondary index (GSI) will use the lookup key to allow finding all cuboids that belong to a particular channel via... | Implement the Python class `LookupKeyWriter` described below.
Class description:
Adds lookup key to legacy items in the S3 index table. The lookup key is collection&experiment&channel&resolution. A global secondary index (GSI) will use the lookup key to allow finding all cuboids that belong to a particular channel via... | 44d41e2b7a7b961e55746e1a5527d5419a74c2ce | <|skeleton|>
class LookupKeyWriter:
"""Adds lookup key to legacy items in the S3 index table. The lookup key is collection&experiment&channel&resolution. A global secondary index (GSI) will use the lookup key to allow finding all cuboids that belong to a particular channel via a DynamoDB query. An instance of this ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LookupKeyWriter:
"""Adds lookup key to legacy items in the S3 index table. The lookup key is collection&experiment&channel&resolution. A global secondary index (GSI) will use the lookup key to allow finding all cuboids that belong to a particular channel via a DynamoDB query. An instance of this class may be ... | the_stack_v2_python_sparse | spdb/spatialdb/utils/add_lookup_keys_to_s3_index.py | jhuapl-boss/spdb | train | 6 |
d14e4bb1ae99503d6df80c16ae31726bcee433d0 | [
"self.path = os.getcwd()\nself.stdscr = stdscr\nself.scroll = 0\nself.cursor = 0\nself.allow_file = allow_file\nself.allow_folder = allow_folder",
"self.stdscr.erase()\nself.stdscr.addstr(0, 0, self.path, curses.COLOR_WHITE + curses.A_UNDERLINE)\nfor i, v in enumerate(self.dirs + self.files):\n if i - self.scr... | <|body_start_0|>
self.path = os.getcwd()
self.stdscr = stdscr
self.scroll = 0
self.cursor = 0
self.allow_file = allow_file
self.allow_folder = allow_folder
<|end_body_0|>
<|body_start_1|>
self.stdscr.erase()
self.stdscr.addstr(0, 0, self.path, curses.COLO... | FileSelectMenu | [
"MIT",
"BSL-1.0",
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileSelectMenu:
def __init__(self, stdscr, allow_file=True, allow_folder=False):
"""Initialize the file select menu. Args: stdscr (_type_): The screen handle allow_file (bool, optional): Whether to allow file selection. Defaults to True. allow_folder (bool, optional): Whether to allow fo... | stack_v2_sparse_classes_75kplus_train_068422 | 33,878 | permissive | [
{
"docstring": "Initialize the file select menu. Args: stdscr (_type_): The screen handle allow_file (bool, optional): Whether to allow file selection. Defaults to True. allow_folder (bool, optional): Whether to allow folder selection. Defaults to False.",
"name": "__init__",
"signature": "def __init__(... | 5 | stack_v2_sparse_classes_30k_train_002859 | Implement the Python class `FileSelectMenu` described below.
Class description:
Implement the FileSelectMenu class.
Method signatures and docstrings:
- def __init__(self, stdscr, allow_file=True, allow_folder=False): Initialize the file select menu. Args: stdscr (_type_): The screen handle allow_file (bool, optional)... | Implement the Python class `FileSelectMenu` described below.
Class description:
Implement the FileSelectMenu class.
Method signatures and docstrings:
- def __init__(self, stdscr, allow_file=True, allow_folder=False): Initialize the file select menu. Args: stdscr (_type_): The screen handle allow_file (bool, optional)... | efa24e27f09b707865326fe4a30f4a65b7a031fe | <|skeleton|>
class FileSelectMenu:
def __init__(self, stdscr, allow_file=True, allow_folder=False):
"""Initialize the file select menu. Args: stdscr (_type_): The screen handle allow_file (bool, optional): Whether to allow file selection. Defaults to True. allow_folder (bool, optional): Whether to allow fo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FileSelectMenu:
def __init__(self, stdscr, allow_file=True, allow_folder=False):
"""Initialize the file select menu. Args: stdscr (_type_): The screen handle allow_file (bool, optional): Whether to allow file selection. Defaults to True. allow_folder (bool, optional): Whether to allow folder selection... | the_stack_v2_python_sparse | scripts/configure_build.py | graphcore/popart | train | 73 | |
9b20852090e7a9d15cc07a6ac5478a92a261a55e | [
"if algorithm == 1:\n reg = linear_model.ARDRegression()\nelif algorithm == 2:\n reg = linear_model.SGDRegressor()\nelif algorithm == 3:\n reg = linear_model.PassiveAggressiveRegressor()\nreturn reg",
"if algorithm == 1:\n reg = linear_model.RANSACRegressor()\nelif algorithm == 2:\n reg = linear_mo... | <|body_start_0|>
if algorithm == 1:
reg = linear_model.ARDRegression()
elif algorithm == 2:
reg = linear_model.SGDRegressor()
elif algorithm == 3:
reg = linear_model.PassiveAggressiveRegressor()
return reg
<|end_body_0|>
<|body_start_1|>
if al... | expand edition of linear model from sklearn library. | ExpandLinearRegressor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExpandLinearRegressor:
"""expand edition of linear model from sklearn library."""
def estimate(self, algorithm=None):
"""1. automatic relevance determination, Compared to the OLS (ordinary least squares) estimator, the coefficient weights are slightly shifted toward zeros, which stab... | stack_v2_sparse_classes_75kplus_train_068423 | 11,649 | permissive | [
{
"docstring": "1. automatic relevance determination, Compared to the OLS (ordinary least squares) estimator, the coefficient weights are slightly shifted toward zeros, which stabilises them. 2. stochastic gradient descent method NOTE: could used for different penalty 3. online passive-aggressive They are simil... | 2 | null | Implement the Python class `ExpandLinearRegressor` described below.
Class description:
expand edition of linear model from sklearn library.
Method signatures and docstrings:
- def estimate(self, algorithm=None): 1. automatic relevance determination, Compared to the OLS (ordinary least squares) estimator, the coeffici... | Implement the Python class `ExpandLinearRegressor` described below.
Class description:
expand edition of linear model from sklearn library.
Method signatures and docstrings:
- def estimate(self, algorithm=None): 1. automatic relevance determination, Compared to the OLS (ordinary least squares) estimator, the coeffici... | 5bcfd68e30477f36736e040e1cdcd26086d325c1 | <|skeleton|>
class ExpandLinearRegressor:
"""expand edition of linear model from sklearn library."""
def estimate(self, algorithm=None):
"""1. automatic relevance determination, Compared to the OLS (ordinary least squares) estimator, the coefficient weights are slightly shifted toward zeros, which stab... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExpandLinearRegressor:
"""expand edition of linear model from sklearn library."""
def estimate(self, algorithm=None):
"""1. automatic relevance determination, Compared to the OLS (ordinary least squares) estimator, the coefficient weights are slightly shifted toward zeros, which stabilises them. ... | the_stack_v2_python_sparse | MetReg/models/ml/linear.py | gaoyunqing/MetReg | train | 0 |
337d7d236dcfabaef1c90e43810b21073d0be51b | [
"env_session = os.getenv('SESSION_DURATION')\nif env_session:\n try:\n self.session_duration = int(env_session)\n except Exception:\n pass",
"if user_id:\n session = super().create_session(user_id)\n user_id = self.user_id_by_session_id.get(session)\n session_dictionary = {'user_id': ... | <|body_start_0|>
env_session = os.getenv('SESSION_DURATION')
if env_session:
try:
self.session_duration = int(env_session)
except Exception:
pass
<|end_body_0|>
<|body_start_1|>
if user_id:
session = super().create_session(user... | [simple auth] Args: Auth ([class]): [class auth] | SessionExpAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionExpAuth:
"""[simple auth] Args: Auth ([class]): [class auth]"""
def __init__(self):
"""[constructor]"""
<|body_0|>
def create_session(self, user_id=None):
"""[create session with time] Args: user_id ([type], optional): [id user]. Defaults to None. Returns:... | stack_v2_sparse_classes_75kplus_train_068424 | 1,992 | no_license | [
{
"docstring": "[constructor]",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "[create session with time] Args: user_id ([type], optional): [id user]. Defaults to None. Returns: [type]: [sesion id]",
"name": "create_session",
"signature": "def create_session(sel... | 3 | null | Implement the Python class `SessionExpAuth` described below.
Class description:
[simple auth] Args: Auth ([class]): [class auth]
Method signatures and docstrings:
- def __init__(self): [constructor]
- def create_session(self, user_id=None): [create session with time] Args: user_id ([type], optional): [id user]. Defau... | Implement the Python class `SessionExpAuth` described below.
Class description:
[simple auth] Args: Auth ([class]): [class auth]
Method signatures and docstrings:
- def __init__(self): [constructor]
- def create_session(self, user_id=None): [create session with time] Args: user_id ([type], optional): [id user]. Defau... | 0c235315b6c67e4cf26977c80f51e995da762fb1 | <|skeleton|>
class SessionExpAuth:
"""[simple auth] Args: Auth ([class]): [class auth]"""
def __init__(self):
"""[constructor]"""
<|body_0|>
def create_session(self, user_id=None):
"""[create session with time] Args: user_id ([type], optional): [id user]. Defaults to None. Returns:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SessionExpAuth:
"""[simple auth] Args: Auth ([class]): [class auth]"""
def __init__(self):
"""[constructor]"""
env_session = os.getenv('SESSION_DURATION')
if env_session:
try:
self.session_duration = int(env_session)
except Exception:
... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_exp_auth.py | abu-bakarr/holbertonschool-web_back_end | train | 0 |
c1a7bcfd8a21426397955b444e0c6edbc0b0dd8d | [
"if not isinstance(wrap_layers, (list, tuple)):\n wrap_layers = [wrap_layers]\nself._wrap_layers = wrap_layers",
"del state\n\ndef _sprite_to_polygons(layer, sprite):\n squared_polygons = [(sprite.vertices + np.array([i, j]), sprite.color, sprite.opacity) for i in [-1.0, 0.0, 1.0] for j in [-1.0, 0.0, 1.0]]... | <|body_start_0|>
if not isinstance(wrap_layers, (list, tuple)):
wrap_layers = [wrap_layers]
self._wrap_layers = wrap_layers
<|end_body_0|>
<|body_start_1|>
del state
def _sprite_to_polygons(layer, sprite):
squared_polygons = [(sprite.vertices + np.array([i, j]),... | Duplicates polygons at a grid of positions. Specifically, duplicates polygons at a 3x3 grid of positions centered around [0, 0] + polygon_position. This is used in torus environments to make a sprite appear to smoothly and incrementally disappear off one edge of the arena and reappear on the opposite edge. | TorusGeometry | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TorusGeometry:
"""Duplicates polygons at a grid of positions. Specifically, duplicates polygons at a 3x3 grid of positions centered around [0, 0] + polygon_position. This is used in torus environments to make a sprite appear to smoothly and incrementally disappear off one edge of the arena and re... | stack_v2_sparse_classes_75kplus_train_068425 | 3,127 | permissive | [
{
"docstring": "Constructor. Args: wrap_layers: String or iterable of strings. All sprites in these layers will be rendered as if the arena is a torus.",
"name": "__init__",
"signature": "def __init__(self, wrap_layers)"
},
{
"docstring": "Get polygon modifier rendering sprites as if the arena i... | 2 | stack_v2_sparse_classes_30k_train_019420 | Implement the Python class `TorusGeometry` described below.
Class description:
Duplicates polygons at a grid of positions. Specifically, duplicates polygons at a 3x3 grid of positions centered around [0, 0] + polygon_position. This is used in torus environments to make a sprite appear to smoothly and incrementally dis... | Implement the Python class `TorusGeometry` described below.
Class description:
Duplicates polygons at a grid of positions. Specifically, duplicates polygons at a 3x3 grid of positions centered around [0, 0] + polygon_position. This is used in torus environments to make a sprite appear to smoothly and incrementally dis... | 3e89e46a5918d59475851f9d4f1558956c110d38 | <|skeleton|>
class TorusGeometry:
"""Duplicates polygons at a grid of positions. Specifically, duplicates polygons at a 3x3 grid of positions centered around [0, 0] + polygon_position. This is used in torus environments to make a sprite appear to smoothly and incrementally disappear off one edge of the arena and re... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TorusGeometry:
"""Duplicates polygons at a grid of positions. Specifically, duplicates polygons at a 3x3 grid of positions centered around [0, 0] + polygon_position. This is used in torus environments to make a sprite appear to smoothly and incrementally disappear off one edge of the arena and reappear on the... | the_stack_v2_python_sparse | moog/observers/polygon_modifiers.py | hokysung/moog.github.io | train | 0 |
86c16f701ec7eaaf8eb37a443bce169eecb1aae9 | [
"try:\n self.data['dendrogram'] = script.unit_cell_dendrogram\nexcept AttributeError:\n pass\nself.data['experiments'] = script._experiments",
"d = OrderedDict()\nuc_params = uc_params_from_experiments(self.data['experiments'])\nd.update(plots.plot_uc_histograms(uc_params))\nif 'dendrogram' in self.data:\n ... | <|body_start_0|>
try:
self.data['dendrogram'] = script.unit_cell_dendrogram
except AttributeError:
pass
self.data['experiments'] = script._experiments
<|end_body_0|>
<|body_start_1|>
d = OrderedDict()
uc_params = uc_params_from_experiments(self.data['expe... | Observer to record unit cell clustering data and make plots. | UnitCellAnalysisObserver | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnitCellAnalysisObserver:
"""Observer to record unit cell clustering data and make plots."""
def update(self, script):
"""Update the data in the observer."""
<|body_0|>
def make_plots(self):
"""Generate plots of the unit cell clustering."""
<|body_1|>
<|... | stack_v2_sparse_classes_75kplus_train_068426 | 1,522 | permissive | [
{
"docstring": "Update the data in the observer.",
"name": "update",
"signature": "def update(self, script)"
},
{
"docstring": "Generate plots of the unit cell clustering.",
"name": "make_plots",
"signature": "def make_plots(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_002936 | Implement the Python class `UnitCellAnalysisObserver` described below.
Class description:
Observer to record unit cell clustering data and make plots.
Method signatures and docstrings:
- def update(self, script): Update the data in the observer.
- def make_plots(self): Generate plots of the unit cell clustering. | Implement the Python class `UnitCellAnalysisObserver` described below.
Class description:
Observer to record unit cell clustering data and make plots.
Method signatures and docstrings:
- def update(self, script): Update the data in the observer.
- def make_plots(self): Generate plots of the unit cell clustering.
<|s... | fb9672b91854f564cbbba6f1cceeefa18d135965 | <|skeleton|>
class UnitCellAnalysisObserver:
"""Observer to record unit cell clustering data and make plots."""
def update(self, script):
"""Update the data in the observer."""
<|body_0|>
def make_plots(self):
"""Generate plots of the unit cell clustering."""
<|body_1|>
<|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UnitCellAnalysisObserver:
"""Observer to record unit cell clustering data and make plots."""
def update(self, script):
"""Update the data in the observer."""
try:
self.data['dendrogram'] = script.unit_cell_dendrogram
except AttributeError:
pass
self... | the_stack_v2_python_sparse | algorithms/clustering/observers.py | jbeilstenedmands/dials | train | 0 |
f6c381f559878ca543d682b1628ef1b5ef23d07a | [
"if config:\n self.config = Config(config)\n raw_config = deepcopy(self.config)\nelse:\n self.config = LrScheduler.config\n raw_config = self.config.to_json()\nraw_config.type = self.config.type\nmap_dict = LrSchedulerMappingDict()\nself.map_config = ConfigBackendMapping(map_dict.type_mapping_dict, map_... | <|body_start_0|>
if config:
self.config = Config(config)
raw_config = deepcopy(self.config)
else:
self.config = LrScheduler.config
raw_config = self.config.to_json()
raw_config.type = self.config.type
map_dict = LrSchedulerMappingDict()
... | Register and call LrScheduler class. | LrScheduler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LrScheduler:
"""Register and call LrScheduler class."""
def __init__(self, config=None):
"""Initialize."""
<|body_0|>
def __call__(self, optimizer=None, epochs=None, steps=None):
"""Call lr scheduler class."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_75kplus_train_068427 | 2,364 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, config=None)"
},
{
"docstring": "Call lr scheduler class.",
"name": "__call__",
"signature": "def __call__(self, optimizer=None, epochs=None, steps=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_039441 | Implement the Python class `LrScheduler` described below.
Class description:
Register and call LrScheduler class.
Method signatures and docstrings:
- def __init__(self, config=None): Initialize.
- def __call__(self, optimizer=None, epochs=None, steps=None): Call lr scheduler class. | Implement the Python class `LrScheduler` described below.
Class description:
Register and call LrScheduler class.
Method signatures and docstrings:
- def __init__(self, config=None): Initialize.
- def __call__(self, optimizer=None, epochs=None, steps=None): Call lr scheduler class.
<|skeleton|>
class LrScheduler:
... | e4ef3a1c92d19d1d08c3ef0e2156b6fecefdbe04 | <|skeleton|>
class LrScheduler:
"""Register and call LrScheduler class."""
def __init__(self, config=None):
"""Initialize."""
<|body_0|>
def __call__(self, optimizer=None, epochs=None, steps=None):
"""Call lr scheduler class."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LrScheduler:
"""Register and call LrScheduler class."""
def __init__(self, config=None):
"""Initialize."""
if config:
self.config = Config(config)
raw_config = deepcopy(self.config)
else:
self.config = LrScheduler.config
raw_config =... | the_stack_v2_python_sparse | zeus/trainer/modules/lr_schedulers/lr_scheduler.py | huawei-noah/xingtian | train | 308 |
29e57a4f565e9897faf5446f054de4afc94d1fca | [
"sum = 0\nq = queue.Queue()\nq.put(root)\nwhile not q.empty():\n n = q.get()\n v = n.val\n if v >= L and v <= R:\n sum += v\n if n.left != None:\n q.put(n.left)\n if n.right != None:\n q.put(n.right)\nreturn sum",
"def dfs(nd):\n if not nd:\n return\n if nd.val <= ... | <|body_start_0|>
sum = 0
q = queue.Queue()
q.put(root)
while not q.empty():
n = q.get()
v = n.val
if v >= L and v <= R:
sum += v
if n.left != None:
q.put(n.left)
if n.right != None:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rangeSumBST1(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
<|body_0|>
def rangeSumBST2(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
<|body_1|>
def rangeSumBST3(sel... | stack_v2_sparse_classes_75kplus_train_068428 | 2,147 | no_license | [
{
"docstring": ":type root: TreeNode :type L: int :type R: int :rtype: int",
"name": "rangeSumBST1",
"signature": "def rangeSumBST1(self, root, L, R)"
},
{
"docstring": ":type root: TreeNode :type L: int :type R: int :rtype: int",
"name": "rangeSumBST2",
"signature": "def rangeSumBST2(se... | 3 | stack_v2_sparse_classes_30k_train_011284 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rangeSumBST1(self, root, L, R): :type root: TreeNode :type L: int :type R: int :rtype: int
- def rangeSumBST2(self, root, L, R): :type root: TreeNode :type L: int :type R: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rangeSumBST1(self, root, L, R): :type root: TreeNode :type L: int :type R: int :rtype: int
- def rangeSumBST2(self, root, L, R): :type root: TreeNode :type L: int :type R: in... | d3e8669f932fc2e22711e8b7590d3365d020e189 | <|skeleton|>
class Solution:
def rangeSumBST1(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
<|body_0|>
def rangeSumBST2(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
<|body_1|>
def rangeSumBST3(sel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rangeSumBST1(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
sum = 0
q = queue.Queue()
q.put(root)
while not q.empty():
n = q.get()
v = n.val
if v >= L and v <= R:
sum ... | the_stack_v2_python_sparse | leetcode/938.py | liuweilin17/algorithm | train | 3 | |
b4b382159df88cff885a9dc0dc23d1a6a7571eb4 | [
"self.settings = game.settings\nself.reset_stats()\nself.game_active = False\nself.high_score = self.file_score",
"self.ships_left = self.settings.ship_limit\nself.score = 0\nself.level = 1",
"with open(HIGH_SCORE_TXT, 'wt+') as f:\n try:\n score = int(f.read())\n except ValueError:\n score ... | <|body_start_0|>
self.settings = game.settings
self.reset_stats()
self.game_active = False
self.high_score = self.file_score
<|end_body_0|>
<|body_start_1|>
self.ships_left = self.settings.ship_limit
self.score = 0
self.level = 1
<|end_body_1|>
<|body_start_2|>
... | Track statistics for Alien Invaders game. | GameStats | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameStats:
"""Track statistics for Alien Invaders game."""
def __init__(self, game):
"""Initialize statistics."""
<|body_0|>
def reset_stats(self):
"""Set dynamic statistics for the game. Initialize statistics at the beginning of the game, or Reset the statistics... | stack_v2_sparse_classes_75kplus_train_068429 | 1,766 | permissive | [
{
"docstring": "Initialize statistics.",
"name": "__init__",
"signature": "def __init__(self, game)"
},
{
"docstring": "Set dynamic statistics for the game. Initialize statistics at the beginning of the game, or Reset the statistics as the game progresses.",
"name": "reset_stats",
"signa... | 4 | stack_v2_sparse_classes_30k_train_025023 | Implement the Python class `GameStats` described below.
Class description:
Track statistics for Alien Invaders game.
Method signatures and docstrings:
- def __init__(self, game): Initialize statistics.
- def reset_stats(self): Set dynamic statistics for the game. Initialize statistics at the beginning of the game, or... | Implement the Python class `GameStats` described below.
Class description:
Track statistics for Alien Invaders game.
Method signatures and docstrings:
- def __init__(self, game): Initialize statistics.
- def reset_stats(self): Set dynamic statistics for the game. Initialize statistics at the beginning of the game, or... | 152fbe43256a80905881055490167d6fe1e3e996 | <|skeleton|>
class GameStats:
"""Track statistics for Alien Invaders game."""
def __init__(self, game):
"""Initialize statistics."""
<|body_0|>
def reset_stats(self):
"""Set dynamic statistics for the game. Initialize statistics at the beginning of the game, or Reset the statistics... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GameStats:
"""Track statistics for Alien Invaders game."""
def __init__(self, game):
"""Initialize statistics."""
self.settings = game.settings
self.reset_stats()
self.game_active = False
self.high_score = self.file_score
def reset_stats(self):
"""Set ... | the_stack_v2_python_sparse | alieninvaders/game_stats.py | yatesmac/Alien-Invaders | train | 0 |
9abcf8f69c6e346c5af9f4dec995135ccd8567b6 | [
"super().__init__(states)\nif unk_token not in states:\n raise MsticpyException('`unk_token` should be a key in `states`')\nself.states = dict(states)\nself.unk_token = unk_token\nfor key, val in self.states.items():\n if isinstance(val, dict):\n self.states[key] = StateMatrix(self.states[key], unk_tok... | <|body_start_0|>
super().__init__(states)
if unk_token not in states:
raise MsticpyException('`unk_token` should be a key in `states`')
self.states = dict(states)
self.unk_token = unk_token
for key, val in self.states.items():
if isinstance(val, dict):
... | Class for storing trained counts/probabilities. | StateMatrix | [
"LicenseRef-scancode-generic-cla",
"LGPL-3.0-only",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown",
"ISC",
"LGPL-2.0-or-later",
"PSF-2.0",
"Apache-2.0",
"BSD-2-Clause",
"LGPL-2.1-only",
"Unlicense",
"Python-2.0",
"LicenseRef-scancode-python-cwi",
"MIT",
"LGPL-2.1-or-later",
"GPL-2.... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StateMatrix:
"""Class for storing trained counts/probabilities."""
def __init__(self, states: Union[dict, defaultdict], unk_token: str):
"""Containr for dict of counts/probs or dict of dicts of cond counts/probs. If you try and retrieve the count/probability for an unseen command/par... | stack_v2_sparse_classes_75kplus_train_068430 | 3,819 | permissive | [
{
"docstring": "Containr for dict of counts/probs or dict of dicts of cond counts/probs. If you try and retrieve the count/probability for an unseen command/param/value from the resulting object, it will return the value associated with the `unk_token` key. Parameters ---------- states: Union[dict, defaultdict]... | 2 | stack_v2_sparse_classes_30k_val_002355 | Implement the Python class `StateMatrix` described below.
Class description:
Class for storing trained counts/probabilities.
Method signatures and docstrings:
- def __init__(self, states: Union[dict, defaultdict], unk_token: str): Containr for dict of counts/probs or dict of dicts of cond counts/probs. If you try and... | Implement the Python class `StateMatrix` described below.
Class description:
Class for storing trained counts/probabilities.
Method signatures and docstrings:
- def __init__(self, states: Union[dict, defaultdict], unk_token: str): Containr for dict of counts/probs or dict of dicts of cond counts/probs. If you try and... | 44b1a390510f9be2772ec62cb95d0fc67dfc234b | <|skeleton|>
class StateMatrix:
"""Class for storing trained counts/probabilities."""
def __init__(self, states: Union[dict, defaultdict], unk_token: str):
"""Containr for dict of counts/probs or dict of dicts of cond counts/probs. If you try and retrieve the count/probability for an unseen command/par... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StateMatrix:
"""Class for storing trained counts/probabilities."""
def __init__(self, states: Union[dict, defaultdict], unk_token: str):
"""Containr for dict of counts/probs or dict of dicts of cond counts/probs. If you try and retrieve the count/probability for an unseen command/param/value from... | the_stack_v2_python_sparse | msticpy/analysis/anomalous_sequence/utils/data_structures.py | RiskIQ/msticpy | train | 1 |
8dff85610280916f2d850ea2af95297cfc4c2836 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.learningAssignment'.casefold():\n from .... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
try:
mapping_value = parse_node.get_child_node('@odata.type').get_str_value()
except AttributeError:
mapping_value = None
if mapping_value and mapping_value.casefold() ==... | LearningCourseActivity | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LearningCourseActivity:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LearningCourseActivity:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create ... | stack_v2_sparse_classes_75kplus_train_068431 | 5,069 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: LearningCourseActivity",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrimina... | 3 | stack_v2_sparse_classes_30k_train_031690 | Implement the Python class `LearningCourseActivity` described below.
Class description:
Implement the LearningCourseActivity class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LearningCourseActivity: Creates a new instance of the appropriate class b... | Implement the Python class `LearningCourseActivity` described below.
Class description:
Implement the LearningCourseActivity class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LearningCourseActivity: Creates a new instance of the appropriate class b... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class LearningCourseActivity:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LearningCourseActivity:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LearningCourseActivity:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LearningCourseActivity:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Ret... | the_stack_v2_python_sparse | msgraph/generated/models/learning_course_activity.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
f62098d359414a8df4399854e16ef6cc896f2563 | [
"_folder_id: int = request.query_params.get('folder_id')\nif _folder_id:\n _qs = self.get_queryset().filter(folder_id=_folder_id)\nelse:\n _save_id: str = request.query_params.get('save_id')\n _qs = self.get_queryset().filter(folder__project__save_id=_save_id, error__exact='')\n_page = self.paginate_querys... | <|body_start_0|>
_folder_id: int = request.query_params.get('folder_id')
if _folder_id:
_qs = self.get_queryset().filter(folder_id=_folder_id)
else:
_save_id: str = request.query_params.get('save_id')
_qs = self.get_queryset().filter(folder__project__save_id=_... | FileViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileViewSet:
def list(self, request, *args, **kwargs):
"""Filter files with pagination"""
<|body_0|>
def perform_destroy(self, instance):
"""Call celery task to delete"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
_folder_id: int = request.query_p... | stack_v2_sparse_classes_75kplus_train_068432 | 12,600 | no_license | [
{
"docstring": "Filter files with pagination",
"name": "list",
"signature": "def list(self, request, *args, **kwargs)"
},
{
"docstring": "Call celery task to delete",
"name": "perform_destroy",
"signature": "def perform_destroy(self, instance)"
}
] | 2 | null | Implement the Python class `FileViewSet` described below.
Class description:
Implement the FileViewSet class.
Method signatures and docstrings:
- def list(self, request, *args, **kwargs): Filter files with pagination
- def perform_destroy(self, instance): Call celery task to delete | Implement the Python class `FileViewSet` described below.
Class description:
Implement the FileViewSet class.
Method signatures and docstrings:
- def list(self, request, *args, **kwargs): Filter files with pagination
- def perform_destroy(self, instance): Call celery task to delete
<|skeleton|>
class FileViewSet:
... | e56936a884f14f5451b2fd5b2ab16621b73bbe69 | <|skeleton|>
class FileViewSet:
def list(self, request, *args, **kwargs):
"""Filter files with pagination"""
<|body_0|>
def perform_destroy(self, instance):
"""Call celery task to delete"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FileViewSet:
def list(self, request, *args, **kwargs):
"""Filter files with pagination"""
_folder_id: int = request.query_params.get('folder_id')
if _folder_id:
_qs = self.get_queryset().filter(folder_id=_folder_id)
else:
_save_id: str = request.query_pa... | the_stack_v2_python_sparse | back/core/views.py | meoook/Abyss-Translate | train | 0 | |
0913967e95e7e18b520463c450723508b42fccc2 | [
"lgt = len(A)\nrtn = sum(A)\nA = A + A\nidx = 0\ntotal = 0\nfor i in range(len(A)):\n if i - idx + 1 > lgt:\n total -= A[idx]\n idx += 1\n while A[idx] < 0 and idx <= i:\n total -= A[idx]\n idx += 1\n if A[i] >= total + A[i] and i < lgt:\n total = A[i]\n ... | <|body_start_0|>
lgt = len(A)
rtn = sum(A)
A = A + A
idx = 0
total = 0
for i in range(len(A)):
if i - idx + 1 > lgt:
total -= A[idx]
idx += 1
while A[idx] < 0 and idx <= i:
total -= A[idx]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubarraySumCircularOld(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def maxSubarraySumCircular(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
lgt = len(A)
rtn = sum(A... | stack_v2_sparse_classes_75kplus_train_068433 | 2,421 | no_license | [
{
"docstring": ":type A: List[int] :rtype: int",
"name": "maxSubarraySumCircularOld",
"signature": "def maxSubarraySumCircularOld(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: int",
"name": "maxSubarraySumCircular",
"signature": "def maxSubarraySumCircular(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubarraySumCircularOld(self, A): :type A: List[int] :rtype: int
- def maxSubarraySumCircular(self, A): :type A: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubarraySumCircularOld(self, A): :type A: List[int] :rtype: int
- def maxSubarraySumCircular(self, A): :type A: List[int] :rtype: int
<|skeleton|>
class Solution:
de... | 196e58cd38db846653fb074cfd0363997121a7cf | <|skeleton|>
class Solution:
def maxSubarraySumCircularOld(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def maxSubarraySumCircular(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxSubarraySumCircularOld(self, A):
""":type A: List[int] :rtype: int"""
lgt = len(A)
rtn = sum(A)
A = A + A
idx = 0
total = 0
for i in range(len(A)):
if i - idx + 1 > lgt:
total -= A[idx]
idx += ... | the_stack_v2_python_sparse | Maximum Sum Circular Subarray.py | nithinveer/leetcode-solutions | train | 0 | |
67817eb31ed57b64e7d19582c4323d63ab07cf8f | [
"if input_data.shape[-1] != neural_network.num_inputs:\n raise QiskitMachineLearningError(f'Invalid input dimension! Received {input_data.shape} and ' + f'expected input compatible to {neural_network.num_inputs}')\nctx.neural_network = neural_network\nctx.sparse = sparse\nctx.save_for_backward(input_data, weight... | <|body_start_0|>
if input_data.shape[-1] != neural_network.num_inputs:
raise QiskitMachineLearningError(f'Invalid input dimension! Received {input_data.shape} and ' + f'expected input compatible to {neural_network.num_inputs}')
ctx.neural_network = neural_network
ctx.sparse = sparse
... | _TorchNNFunction | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _TorchNNFunction:
def forward(ctx: Any, input_data: Tensor, weights: Tensor, neural_network: NeuralNetwork, sparse: bool) -> Tensor:
"""Forward pass computation. Args: ctx: The context to be passed to the backward pass. input_data: The input data. weights: The weights. neural_network: Th... | stack_v2_sparse_classes_75kplus_train_068434 | 12,051 | permissive | [
{
"docstring": "Forward pass computation. Args: ctx: The context to be passed to the backward pass. input_data: The input data. weights: The weights. neural_network: The neural network to be connected. sparse: Indicates whether to use sparse output or not. Returns: The resulting value of the forward pass. Raise... | 2 | stack_v2_sparse_classes_30k_train_027424 | Implement the Python class `_TorchNNFunction` described below.
Class description:
Implement the _TorchNNFunction class.
Method signatures and docstrings:
- def forward(ctx: Any, input_data: Tensor, weights: Tensor, neural_network: NeuralNetwork, sparse: bool) -> Tensor: Forward pass computation. Args: ctx: The contex... | Implement the Python class `_TorchNNFunction` described below.
Class description:
Implement the _TorchNNFunction class.
Method signatures and docstrings:
- def forward(ctx: Any, input_data: Tensor, weights: Tensor, neural_network: NeuralNetwork, sparse: bool) -> Tensor: Forward pass computation. Args: ctx: The contex... | 8a6e73beca8175e782d17d562f8e7b8642f7697a | <|skeleton|>
class _TorchNNFunction:
def forward(ctx: Any, input_data: Tensor, weights: Tensor, neural_network: NeuralNetwork, sparse: bool) -> Tensor:
"""Forward pass computation. Args: ctx: The context to be passed to the backward pass. input_data: The input data. weights: The weights. neural_network: Th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _TorchNNFunction:
def forward(ctx: Any, input_data: Tensor, weights: Tensor, neural_network: NeuralNetwork, sparse: bool) -> Tensor:
"""Forward pass computation. Args: ctx: The context to be passed to the backward pass. input_data: The input data. weights: The weights. neural_network: The neural netwo... | the_stack_v2_python_sparse | qiskit_machine_learning/connectors/torch_connector.py | jessica-angel7/qiskit-machine-learning | train | 1 | |
f65dd171a966438af0c99701e09a46e20f78cdd6 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn SectionGroup()",
"from .notebook import Notebook\nfrom .onenote_entity_hierarchy_model import OnenoteEntityHierarchyModel\nfrom .onenote_section import OnenoteSection\nfrom .notebook import Notebook\nfrom .onenote_entity_hierarchy_mode... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return SectionGroup()
<|end_body_0|>
<|body_start_1|>
from .notebook import Notebook
from .onenote_entity_hierarchy_model import OnenoteEntityHierarchyModel
from .onenote_section import... | SectionGroup | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SectionGroup:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SectionGroup:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: ... | stack_v2_sparse_classes_75kplus_train_068435 | 4,125 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: SectionGroup",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(... | 3 | stack_v2_sparse_classes_30k_train_003514 | Implement the Python class `SectionGroup` described below.
Class description:
Implement the SectionGroup class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SectionGroup: Creates a new instance of the appropriate class based on discriminator value Ar... | Implement the Python class `SectionGroup` described below.
Class description:
Implement the SectionGroup class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SectionGroup: Creates a new instance of the appropriate class based on discriminator value Ar... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class SectionGroup:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SectionGroup:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SectionGroup:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SectionGroup:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: SectionGroup""... | the_stack_v2_python_sparse | msgraph/generated/models/section_group.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
ad2fd511e1073b47f541f1a9c2ada5414f3f3ff9 | [
"self._gv = gv\nself._dlg = ElevatioBandsDialog()\nself._dlg.setWindowFlags(self._dlg.windowFlags() & ~Qt.WindowContextHelpButtonHint)\nself._dlg.move(self._gv.elevationBandsPos)\nself._dlg.okButton.clicked.connect(self.setBands)\nself._dlg.cancelButton.clicked.connect(self._dlg.close)\nself._dlg.elevBandsThreshold... | <|body_start_0|>
self._gv = gv
self._dlg = ElevatioBandsDialog()
self._dlg.setWindowFlags(self._dlg.windowFlags() & ~Qt.WindowContextHelpButtonHint)
self._dlg.move(self._gv.elevationBandsPos)
self._dlg.okButton.clicked.connect(self.setBands)
self._dlg.cancelButton.clicked... | Form and functions for defining elevation bands. | ElevationBands | [
"MIT",
"GPL-2.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElevationBands:
"""Form and functions for defining elevation bands."""
def __init__(self, gv):
"""Initialise class variables."""
<|body_0|>
def run(self):
"""Run the form."""
<|body_1|>
def setBands(self):
"""Save bands definition."""
... | stack_v2_sparse_classes_75kplus_train_068436 | 2,977 | permissive | [
{
"docstring": "Initialise class variables.",
"name": "__init__",
"signature": "def __init__(self, gv)"
},
{
"docstring": "Run the form.",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "Save bands definition.",
"name": "setBands",
"signature": "def setBand... | 3 | stack_v2_sparse_classes_30k_train_024670 | Implement the Python class `ElevationBands` described below.
Class description:
Form and functions for defining elevation bands.
Method signatures and docstrings:
- def __init__(self, gv): Initialise class variables.
- def run(self): Run the form.
- def setBands(self): Save bands definition. | Implement the Python class `ElevationBands` described below.
Class description:
Form and functions for defining elevation bands.
Method signatures and docstrings:
- def __init__(self, gv): Initialise class variables.
- def run(self): Run the form.
- def setBands(self): Save bands definition.
<|skeleton|>
class Eleva... | ddb3de70708687ca3167ec4b72ac432426175f45 | <|skeleton|>
class ElevationBands:
"""Form and functions for defining elevation bands."""
def __init__(self, gv):
"""Initialise class variables."""
<|body_0|>
def run(self):
"""Run the form."""
<|body_1|>
def setBands(self):
"""Save bands definition."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ElevationBands:
"""Form and functions for defining elevation bands."""
def __init__(self, gv):
"""Initialise class variables."""
self._gv = gv
self._dlg = ElevatioBandsDialog()
self._dlg.setWindowFlags(self._dlg.windowFlags() & ~Qt.WindowContextHelpButtonHint)
self... | the_stack_v2_python_sparse | qswatplus/elevationbands.py | celray/swatplus-automatic-workflow | train | 11 |
771ec820281805b5e5a7a0d06a5d59f11ab63ac5 | [
"usuarios = getAllApoyaFem()\nserializer = self.serializer_class(usuarios, many=True)\nreturn Response(serializer.data, status=status.HTTP_200_OK)",
"try:\n serializer = self.serializer_class(data=request.data)\n if serializer.is_valid():\n createApoyaFem(request.data)\n return Response(serial... | <|body_start_0|>
usuarios = getAllApoyaFem()
serializer = self.serializer_class(usuarios, many=True)
return Response(serializer.data, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
try:
serializer = self.serializer_class(data=request.data)
if serializ... | Maneja el List de usuario ApoyaFem Args: viewsets ([type]): [description] | usuarioApoyaFemViewList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class usuarioApoyaFemViewList:
"""Maneja el List de usuario ApoyaFem Args: viewsets ([type]): [description]"""
def get(self, request, format=None):
"""Metodo GET de usuario ApoyaFem Args: request ([type]): [description] format ([type], optional): [description]. Defaults to None. Returns: L... | stack_v2_sparse_classes_75kplus_train_068437 | 18,724 | no_license | [
{
"docstring": "Metodo GET de usuario ApoyaFem Args: request ([type]): [description] format ([type], optional): [description]. Defaults to None. Returns: Listado de todos los usuarios de ApoyaFem",
"name": "get",
"signature": "def get(self, request, format=None)"
},
{
"docstring": "Metodo POST d... | 2 | stack_v2_sparse_classes_30k_train_002082 | Implement the Python class `usuarioApoyaFemViewList` described below.
Class description:
Maneja el List de usuario ApoyaFem Args: viewsets ([type]): [description]
Method signatures and docstrings:
- def get(self, request, format=None): Metodo GET de usuario ApoyaFem Args: request ([type]): [description] format ([type... | Implement the Python class `usuarioApoyaFemViewList` described below.
Class description:
Maneja el List de usuario ApoyaFem Args: viewsets ([type]): [description]
Method signatures and docstrings:
- def get(self, request, format=None): Metodo GET de usuario ApoyaFem Args: request ([type]): [description] format ([type... | 5edfc0fb9316c899dbd5cd5607989300c75ab4e8 | <|skeleton|>
class usuarioApoyaFemViewList:
"""Maneja el List de usuario ApoyaFem Args: viewsets ([type]): [description]"""
def get(self, request, format=None):
"""Metodo GET de usuario ApoyaFem Args: request ([type]): [description] format ([type], optional): [description]. Defaults to None. Returns: L... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class usuarioApoyaFemViewList:
"""Maneja el List de usuario ApoyaFem Args: viewsets ([type]): [description]"""
def get(self, request, format=None):
"""Metodo GET de usuario ApoyaFem Args: request ([type]): [description] format ([type], optional): [description]. Defaults to None. Returns: Listado de tod... | the_stack_v2_python_sparse | usuarios_API/views.py | MartinGalvanCastro/ApoyaFem-API | train | 0 |
72c10470840e55140f4d7fd1c6cda6aef61509e6 | [
"if n == 1:\n return 0\nif n % 2 == 0:\n return self.integerReplacement(n / 2) + 1\nelse:\n add = self.integerReplacement(n + 1) + 1\n subtract = self.integerReplacement(n - 1) + 1\n return min(add, subtract)",
"def min_operations(n: int):\n if n in dp:\n return dp[n]\n if n % 2 == 0:\... | <|body_start_0|>
if n == 1:
return 0
if n % 2 == 0:
return self.integerReplacement(n / 2) + 1
else:
add = self.integerReplacement(n + 1) + 1
subtract = self.integerReplacement(n - 1) + 1
return min(add, subtract)
<|end_body_0|>
<|body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def integerReplacement(self, n: int) -> int:
"""My Solution: Brute Force Solution IDEA: We explore all possibilities. Given the rules, integerReplacement(n) will converge to 1 for all integers. Thus, we can use recursion to see how many steps it will take. When odd, we explore ... | stack_v2_sparse_classes_75kplus_train_068438 | 1,715 | no_license | [
{
"docstring": "My Solution: Brute Force Solution IDEA: We explore all possibilities. Given the rules, integerReplacement(n) will converge to 1 for all integers. Thus, we can use recursion to see how many steps it will take. When odd, we explore BOTH possibilities of adding or subtracting, and take the route wi... | 2 | stack_v2_sparse_classes_30k_train_014668 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerReplacement(self, n: int) -> int: My Solution: Brute Force Solution IDEA: We explore all possibilities. Given the rules, integerReplacement(n) will converge to 1 for a... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerReplacement(self, n: int) -> int: My Solution: Brute Force Solution IDEA: We explore all possibilities. Given the rules, integerReplacement(n) will converge to 1 for a... | 8b11ceb675089a12a4a44f9b044dac7c3e666819 | <|skeleton|>
class Solution:
def integerReplacement(self, n: int) -> int:
"""My Solution: Brute Force Solution IDEA: We explore all possibilities. Given the rules, integerReplacement(n) will converge to 1 for all integers. Thus, we can use recursion to see how many steps it will take. When odd, we explore ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def integerReplacement(self, n: int) -> int:
"""My Solution: Brute Force Solution IDEA: We explore all possibilities. Given the rules, integerReplacement(n) will converge to 1 for all integers. Thus, we can use recursion to see how many steps it will take. When odd, we explore BOTH possibili... | the_stack_v2_python_sparse | Python_Solutions/397_Integer_Replacement.py | lw75251/leetcode | train | 0 | |
e9ad7b3c2636fb38e377a562443f6c87e2f8255b | [
"self.X_mn = self.load_base_connectome(base_filename)\nr_state = np.random.RandomState(signature_seed)\nself.sigs = self.generate_injury_signatures(self.X_mn, n_injuries, r_state)",
"X, Y = self.sample_injury_strengths(n_samples, self.X_mn, self.sigs[0], self.sigs[1], noise_weight)\nassert X.shape[0] == n_samples... | <|body_start_0|>
self.X_mn = self.load_base_connectome(base_filename)
r_state = np.random.RandomState(signature_seed)
self.sigs = self.generate_injury_signatures(self.X_mn, n_injuries, r_state)
<|end_body_0|>
<|body_start_1|>
X, Y = self.sample_injury_strengths(n_samples, self.X_mn, sel... | ConnectomeInjury | [
"LicenseRef-scancode-cecill-b-en"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConnectomeInjury:
def __init__(self, base_filename, n_injuries=2, signature_seed=333):
"""Use to create synthetic injury data."""
<|body_0|>
def generate_injury(self, n_samples=100, noise_weight=0.125):
"""Return n_samples of synthetic injury data and corresponding i... | stack_v2_sparse_classes_75kplus_train_068439 | 8,625 | permissive | [
{
"docstring": "Use to create synthetic injury data.",
"name": "__init__",
"signature": "def __init__(self, base_filename, n_injuries=2, signature_seed=333)"
},
{
"docstring": "Return n_samples of synthetic injury data and corresponding injury strength.",
"name": "generate_injury",
"sign... | 5 | stack_v2_sparse_classes_30k_train_025008 | Implement the Python class `ConnectomeInjury` described below.
Class description:
Implement the ConnectomeInjury class.
Method signatures and docstrings:
- def __init__(self, base_filename, n_injuries=2, signature_seed=333): Use to create synthetic injury data.
- def generate_injury(self, n_samples=100, noise_weight=... | Implement the Python class `ConnectomeInjury` described below.
Class description:
Implement the ConnectomeInjury class.
Method signatures and docstrings:
- def __init__(self, base_filename, n_injuries=2, signature_seed=333): Use to create synthetic injury data.
- def generate_injury(self, n_samples=100, noise_weight=... | 7a807ed690929563ce36086eaf0998d0e8856aea | <|skeleton|>
class ConnectomeInjury:
def __init__(self, base_filename, n_injuries=2, signature_seed=333):
"""Use to create synthetic injury data."""
<|body_0|>
def generate_injury(self, n_samples=100, noise_weight=0.125):
"""Return n_samples of synthetic injury data and corresponding i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConnectomeInjury:
def __init__(self, base_filename, n_injuries=2, signature_seed=333):
"""Use to create synthetic injury data."""
self.X_mn = self.load_base_connectome(base_filename)
r_state = np.random.RandomState(signature_seed)
self.sigs = self.generate_injury_signatures(sel... | the_stack_v2_python_sparse | pynet/datasets/connectome.py | Duplums/pynet | train | 0 | |
354dd1371ffcea6c1b3b9aa25d5f189e21dac658 | [
"\"\"\"如果在测试用例中使用了mock模拟这个接口的返回，那么就不会执行这个接口的代码\"\"\"\nprint('调用第三方支付接口*****')\nurl = 'http://third.payment.pay/'\ndata = {'card_num': card_num, 'amount': amount}\nresponse = requests.post(url, data=data)\nprint(response)\nreturn response.status_code",
"try:\n resp = self.requestOutofSystem(card_num, amount)\n ... | <|body_start_0|>
"""如果在测试用例中使用了mock模拟这个接口的返回，那么就不会执行这个接口的代码"""
print('调用第三方支付接口*****')
url = 'http://third.payment.pay/'
data = {'card_num': card_num, 'amount': amount}
response = requests.post(url, data=data)
print(response)
return response.status_code
<|end_body... | Payment | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Payment:
def requestOutofSystem(self, card_num, amount):
"""请求第三方支付接口"""
<|body_0|>
def doPay(self, user_id, card_num, amount):
"""支付:user_id 用户ID card_num 卡号 amount 支付金额"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
"""如果在测试用例中使用了mock模拟这个接口的返回，那么... | stack_v2_sparse_classes_75kplus_train_068440 | 1,489 | no_license | [
{
"docstring": "请求第三方支付接口",
"name": "requestOutofSystem",
"signature": "def requestOutofSystem(self, card_num, amount)"
},
{
"docstring": "支付:user_id 用户ID card_num 卡号 amount 支付金额",
"name": "doPay",
"signature": "def doPay(self, user_id, card_num, amount)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001818 | Implement the Python class `Payment` described below.
Class description:
Implement the Payment class.
Method signatures and docstrings:
- def requestOutofSystem(self, card_num, amount): 请求第三方支付接口
- def doPay(self, user_id, card_num, amount): 支付:user_id 用户ID card_num 卡号 amount 支付金额 | Implement the Python class `Payment` described below.
Class description:
Implement the Payment class.
Method signatures and docstrings:
- def requestOutofSystem(self, card_num, amount): 请求第三方支付接口
- def doPay(self, user_id, card_num, amount): 支付:user_id 用户ID card_num 卡号 amount 支付金额
<|skeleton|>
class Payment:
de... | 2f425a1263e78fba36bc1094175c1e967498cafc | <|skeleton|>
class Payment:
def requestOutofSystem(self, card_num, amount):
"""请求第三方支付接口"""
<|body_0|>
def doPay(self, user_id, card_num, amount):
"""支付:user_id 用户ID card_num 卡号 amount 支付金额"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Payment:
def requestOutofSystem(self, card_num, amount):
"""请求第三方支付接口"""
"""如果在测试用例中使用了mock模拟这个接口的返回，那么就不会执行这个接口的代码"""
print('调用第三方支付接口*****')
url = 'http://third.payment.pay/'
data = {'card_num': card_num, 'amount': amount}
response = requests.post(url, data=da... | the_stack_v2_python_sparse | python_1/study_mock/payment.py | KRIS123456654321/pytest | train | 2 | |
2eb55fcddea90bb15adb59172156b3272eb15d69 | [
"self.batch_request = self._parse_batch_request(batch_request, config)\nself.feature_ids = feature_ids\nsuper().__init__(AwsDownloadClient, data_folder=data_folder, config=config)",
"if isinstance(batch_request, BatchStatisticalRequest):\n return batch_request\nif isinstance(batch_request, dict):\n return B... | <|body_start_0|>
self.batch_request = self._parse_batch_request(batch_request, config)
self.feature_ids = feature_ids
super().__init__(AwsDownloadClient, data_folder=data_folder, config=config)
<|end_body_0|>
<|body_start_1|>
if isinstance(batch_request, BatchStatisticalRequest):
... | A utility class for downloading results of Batch Statistical API from an S3 bucket. | AwsBatchStatisticalResults | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AwsBatchStatisticalResults:
"""A utility class for downloading results of Batch Statistical API from an S3 bucket."""
def __init__(self, batch_request: BatchStatisticalRequestType, *, feature_ids: Optional[Sequence[Union[str, int]]]=None, data_folder: Optional[str]=None, config: Optional[SHC... | stack_v2_sparse_classes_75kplus_train_068441 | 4,135 | permissive | [
{
"docstring": ":param batch_request: Info about a batch request - either an instance of `BatchStatisticalRequest` or a batch ID or a raw payload of the batch response. :param feature_ids: A list of feature IDs of saved results on the bucket. If provided it will download only these results. If not provided it w... | 4 | null | Implement the Python class `AwsBatchStatisticalResults` described below.
Class description:
A utility class for downloading results of Batch Statistical API from an S3 bucket.
Method signatures and docstrings:
- def __init__(self, batch_request: BatchStatisticalRequestType, *, feature_ids: Optional[Sequence[Union[str... | Implement the Python class `AwsBatchStatisticalResults` described below.
Class description:
A utility class for downloading results of Batch Statistical API from an S3 bucket.
Method signatures and docstrings:
- def __init__(self, batch_request: BatchStatisticalRequestType, *, feature_ids: Optional[Sequence[Union[str... | 98d0327e3929999ec07645f77b16fceb7f9c88b9 | <|skeleton|>
class AwsBatchStatisticalResults:
"""A utility class for downloading results of Batch Statistical API from an S3 bucket."""
def __init__(self, batch_request: BatchStatisticalRequestType, *, feature_ids: Optional[Sequence[Union[str, int]]]=None, data_folder: Optional[str]=None, config: Optional[SHC... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AwsBatchStatisticalResults:
"""A utility class for downloading results of Batch Statistical API from an S3 bucket."""
def __init__(self, batch_request: BatchStatisticalRequestType, *, feature_ids: Optional[Sequence[Union[str, int]]]=None, data_folder: Optional[str]=None, config: Optional[SHConfig]=None):... | the_stack_v2_python_sparse | sentinelhub/aws/batch.py | sentinel-hub/sentinelhub-py | train | 704 |
f9af40cd2e25dc709b9306c7845924535e279107 | [
"super(Worker, self).__init__(parent)\nself._parent = parent\nself._func = func\nself._args = args\nself._kwargs = kwargs\nself._on_complete = on_complete",
"try:\n result = self._func(*self._args, **self._kwargs)\nexcept Exception as e:\n result = e\nfinally:\n WorkerCompletedEvent.post_to(self.parent()... | <|body_start_0|>
super(Worker, self).__init__(parent)
self._parent = parent
self._func = func
self._args = args
self._kwargs = kwargs
self._on_complete = on_complete
<|end_body_0|>
<|body_start_1|>
try:
result = self._func(*self._args, **self._kwargs)... | A worker thread to offload long running tasks. Raises WorkerCompletedEvent on completion of task. Event is posted on Qt event loop. | Worker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Worker:
"""A worker thread to offload long running tasks. Raises WorkerCompletedEvent on completion of task. Event is posted on Qt event loop."""
def __init__(self, parent, on_complete, func, *args, **kwargs):
"""Create an instance of the worker thread. Args: parent: owning widget/th... | stack_v2_sparse_classes_75kplus_train_068442 | 3,372 | permissive | [
{
"docstring": "Create an instance of the worker thread. Args: parent: owning widget/thread on_complete: callback on completion of task func: task method args: arguments for the task kwargs: keyword arguments for the task",
"name": "__init__",
"signature": "def __init__(self, parent, on_complete, func, ... | 2 | stack_v2_sparse_classes_30k_train_016395 | Implement the Python class `Worker` described below.
Class description:
A worker thread to offload long running tasks. Raises WorkerCompletedEvent on completion of task. Event is posted on Qt event loop.
Method signatures and docstrings:
- def __init__(self, parent, on_complete, func, *args, **kwargs): Create an inst... | Implement the Python class `Worker` described below.
Class description:
A worker thread to offload long running tasks. Raises WorkerCompletedEvent on completion of task. Event is posted on Qt event loop.
Method signatures and docstrings:
- def __init__(self, parent, on_complete, func, *args, **kwargs): Create an inst... | aa936982737e5ffe8ff808197d0896ee6e5239a8 | <|skeleton|>
class Worker:
"""A worker thread to offload long running tasks. Raises WorkerCompletedEvent on completion of task. Event is posted on Qt event loop."""
def __init__(self, parent, on_complete, func, *args, **kwargs):
"""Create an instance of the worker thread. Args: parent: owning widget/th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Worker:
"""A worker thread to offload long running tasks. Raises WorkerCompletedEvent on completion of task. Event is posted on Qt event loop."""
def __init__(self, parent, on_complete, func, *args, **kwargs):
"""Create an instance of the worker thread. Args: parent: owning widget/thread on_compl... | the_stack_v2_python_sparse | pomito/plugins/ui/qt/utils.py | codito/pomito | train | 1 |
8d953a5f437869a57749a0f2bf291073d34b8b97 | [
"_, i, O = (0, 1.0, 0.5)\npatch = np.array([[_, _, _, _, _, _, _, O, O, _, _, _, _, _, _, _], [_, _, _, _, _, _, O, i, i, O, _, _, _, _, _, _], [_, _, _, _, _, _, O, i, i, O, _, _, _, _, _, _], [_, _, _, _, _, O, i, i, i, i, O, _, _, _, _, _], [O, O, O, O, O, O, i, i, i, i, O, O, O, O, O, O], [O, i, i, i, i, i, i, ... | <|body_start_0|>
_, i, O = (0, 1.0, 0.5)
patch = np.array([[_, _, _, _, _, _, _, O, O, _, _, _, _, _, _, _], [_, _, _, _, _, _, O, i, i, O, _, _, _, _, _, _], [_, _, _, _, _, _, O, i, i, O, _, _, _, _, _, _], [_, _, _, _, _, O, i, i, i, i, O, _, _, _, _, _], [O, O, O, O, O, O, i, i, i, i, O, O, O, O, O,... | Rasters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rasters:
def superstar():
"""test data patch Ignore: >>> kwplot.autompl() >>> patch = Rasters.superstar() >>> data = np.clip(kwimage.imscale(patch, 2.2), 0, 1) >>> kwplot.imshow(data)"""
<|body_0|>
def eff():
"""test data patch Ignore: >>> kwplot.autompl() >>> eff = ... | stack_v2_sparse_classes_75kplus_train_068443 | 20,195 | permissive | [
{
"docstring": "test data patch Ignore: >>> kwplot.autompl() >>> patch = Rasters.superstar() >>> data = np.clip(kwimage.imscale(patch, 2.2), 0, 1) >>> kwplot.imshow(data)",
"name": "superstar",
"signature": "def superstar()"
},
{
"docstring": "test data patch Ignore: >>> kwplot.autompl() >>> eff... | 2 | stack_v2_sparse_classes_30k_train_011486 | Implement the Python class `Rasters` described below.
Class description:
Implement the Rasters class.
Method signatures and docstrings:
- def superstar(): test data patch Ignore: >>> kwplot.autompl() >>> patch = Rasters.superstar() >>> data = np.clip(kwimage.imscale(patch, 2.2), 0, 1) >>> kwplot.imshow(data)
- def ef... | Implement the Python class `Rasters` described below.
Class description:
Implement the Rasters class.
Method signatures and docstrings:
- def superstar(): test data patch Ignore: >>> kwplot.autompl() >>> patch = Rasters.superstar() >>> data = np.clip(kwimage.imscale(patch, 2.2), 0, 1) >>> kwplot.imshow(data)
- def ef... | 77b7b557960cbf4dc6cbc69674e3e32a5efaad0a | <|skeleton|>
class Rasters:
def superstar():
"""test data patch Ignore: >>> kwplot.autompl() >>> patch = Rasters.superstar() >>> data = np.clip(kwimage.imscale(patch, 2.2), 0, 1) >>> kwplot.imshow(data)"""
<|body_0|>
def eff():
"""test data patch Ignore: >>> kwplot.autompl() >>> eff = ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Rasters:
def superstar():
"""test data patch Ignore: >>> kwplot.autompl() >>> patch = Rasters.superstar() >>> data = np.clip(kwimage.imscale(patch, 2.2), 0, 1) >>> kwplot.imshow(data)"""
_, i, O = (0, 1.0, 0.5)
patch = np.array([[_, _, _, _, _, _, _, O, O, _, _, _, _, _, _, _], [_, _, ... | the_stack_v2_python_sparse | kwcoco/demo/toypatterns.py | Kitware/kwcoco | train | 20 | |
a979e7a4e0aaf52d45ace3c4d44a4d8301af3e14 | [
"def wrapper(*args, **kwargs):\n try:\n return int(self(*args, **kwargs))\n except ValueError as v_e:\n return f'{v_e} occured'\n except TypeError as t_e:\n return f'{t_e} occured'\nreturn wrapper",
"def wrapper(*args, **kwargs):\n try:\n return str(self(*args, **kwargs))\n... | <|body_start_0|>
def wrapper(*args, **kwargs):
try:
return int(self(*args, **kwargs))
except ValueError as v_e:
return f'{v_e} occured'
except TypeError as t_e:
return f'{t_e} occured'
return wrapper
<|end_body_0|>
<|bo... | Converts results of given functions to a specified type if possible. Otherwise raises ValueError | TypeDecorators | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TypeDecorators:
"""Converts results of given functions to a specified type if possible. Otherwise raises ValueError"""
def to_int(self):
"""Convert the result of a function to int"""
<|body_0|>
def to_str(self):
"""Convert the result of a function to int"""
... | stack_v2_sparse_classes_75kplus_train_068444 | 2,408 | no_license | [
{
"docstring": "Convert the result of a function to int",
"name": "to_int",
"signature": "def to_int(self)"
},
{
"docstring": "Convert the result of a function to int",
"name": "to_str",
"signature": "def to_str(self)"
},
{
"docstring": "Convert the result of a function to int",
... | 4 | stack_v2_sparse_classes_30k_train_039669 | Implement the Python class `TypeDecorators` described below.
Class description:
Converts results of given functions to a specified type if possible. Otherwise raises ValueError
Method signatures and docstrings:
- def to_int(self): Convert the result of a function to int
- def to_str(self): Convert the result of a fun... | Implement the Python class `TypeDecorators` described below.
Class description:
Converts results of given functions to a specified type if possible. Otherwise raises ValueError
Method signatures and docstrings:
- def to_int(self): Convert the result of a function to int
- def to_str(self): Convert the result of a fun... | 91ebe6a942b7bf3dd8891793e7796e3f2cebf8b1 | <|skeleton|>
class TypeDecorators:
"""Converts results of given functions to a specified type if possible. Otherwise raises ValueError"""
def to_int(self):
"""Convert the result of a function to int"""
<|body_0|>
def to_str(self):
"""Convert the result of a function to int"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TypeDecorators:
"""Converts results of given functions to a specified type if possible. Otherwise raises ValueError"""
def to_int(self):
"""Convert the result of a function to int"""
def wrapper(*args, **kwargs):
try:
return int(self(*args, **kwargs))
... | the_stack_v2_python_sparse | lesson_16/task_3.py | PrtagonistOne/Beetroot_Academy | train | 0 |
420e491b08374bb971f1828c385c84d36f78ebc5 | [
"pygame.sprite.Sprite.__init__(self)\nself.image = pygame.image.load('assets/images/grounds/electrostatics.png')\nself.image = self.image.convert()\nself.image.set_colorkey((0, 0, 0))\nself.rect = self.image.get_rect()\nself.rect.left = 0\nself.rect.bottom = 512\nself.dx = 40",
"self.rect.centerx += self.dx\nif s... | <|body_start_0|>
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load('assets/images/grounds/electrostatics.png')
self.image = self.image.convert()
self.image.set_colorkey((0, 0, 0))
self.rect = self.image.get_rect()
self.rect.left = 0
self.rect.bott... | Electrostatics | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Electrostatics:
def __init__(self):
"""Initialize the class"""
<|body_0|>
def update(self, screen):
"""Resets the shockwave's position whenever it exists the screen."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
pygame.sprite.Sprite.__init__(self)... | stack_v2_sparse_classes_75kplus_train_068445 | 976 | no_license | [
{
"docstring": "Initialize the class",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Resets the shockwave's position whenever it exists the screen.",
"name": "update",
"signature": "def update(self, screen)"
}
] | 2 | null | Implement the Python class `Electrostatics` described below.
Class description:
Implement the Electrostatics class.
Method signatures and docstrings:
- def __init__(self): Initialize the class
- def update(self, screen): Resets the shockwave's position whenever it exists the screen. | Implement the Python class `Electrostatics` described below.
Class description:
Implement the Electrostatics class.
Method signatures and docstrings:
- def __init__(self): Initialize the class
- def update(self, screen): Resets the shockwave's position whenever it exists the screen.
<|skeleton|>
class Electrostatics... | d8ead79d4661489095b4738b5725bcc8a3b15f38 | <|skeleton|>
class Electrostatics:
def __init__(self):
"""Initialize the class"""
<|body_0|>
def update(self, screen):
"""Resets the shockwave's position whenever it exists the screen."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Electrostatics:
def __init__(self):
"""Initialize the class"""
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load('assets/images/grounds/electrostatics.png')
self.image = self.image.convert()
self.image.set_colorkey((0, 0, 0))
self.rect = self.im... | the_stack_v2_python_sparse | electrostatics.py | DDSGrandjean/Python_aroundTheWorld_fall2016 | train | 0 | |
9e97e0220f093b63b4ebbbbfceef7434edd17751 | [
"try:\n found_item = ItemModel.find_item_by_name(name)\nexcept:\n return ({'message': SERVER_ERROR}, 500)\nif found_item:\n return (found_item.json(), 200)\nreturn ({'message': NOT_FOUND_ERROR.format(name)}, 404)",
"if ItemModel.find_item_by_name(name):\n return ({'message': ALREADY_EXISTS_ERROR.forma... | <|body_start_0|>
try:
found_item = ItemModel.find_item_by_name(name)
except:
return ({'message': SERVER_ERROR}, 500)
if found_item:
return (found_item.json(), 200)
return ({'message': NOT_FOUND_ERROR.format(name)}, 404)
<|end_body_0|>
<|body_start_1|>... | Resource for one particular item. | Item | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Item:
"""Resource for one particular item."""
def get(cls, name: str):
"""endpoint for getting one item by name"""
<|body_0|>
def post(cls, name: str):
"""endpoint for creating an item, it does not accept full json, but parses it and uses only {price: <float>}"""... | stack_v2_sparse_classes_75kplus_train_068446 | 3,074 | no_license | [
{
"docstring": "endpoint for getting one item by name",
"name": "get",
"signature": "def get(cls, name: str)"
},
{
"docstring": "endpoint for creating an item, it does not accept full json, but parses it and uses only {price: <float>}",
"name": "post",
"signature": "def post(cls, name: s... | 4 | stack_v2_sparse_classes_30k_train_047281 | Implement the Python class `Item` described below.
Class description:
Resource for one particular item.
Method signatures and docstrings:
- def get(cls, name: str): endpoint for getting one item by name
- def post(cls, name: str): endpoint for creating an item, it does not accept full json, but parses it and uses onl... | Implement the Python class `Item` described below.
Class description:
Resource for one particular item.
Method signatures and docstrings:
- def get(cls, name: str): endpoint for getting one item by name
- def post(cls, name: str): endpoint for creating an item, it does not accept full json, but parses it and uses onl... | 6f8dfbff5f06bead56b2c56122a533d1bd148c2b | <|skeleton|>
class Item:
"""Resource for one particular item."""
def get(cls, name: str):
"""endpoint for getting one item by name"""
<|body_0|>
def post(cls, name: str):
"""endpoint for creating an item, it does not accept full json, but parses it and uses only {price: <float>}"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Item:
"""Resource for one particular item."""
def get(cls, name: str):
"""endpoint for getting one item by name"""
try:
found_item = ItemModel.find_item_by_name(name)
except:
return ({'message': SERVER_ERROR}, 500)
if found_item:
return ... | the_stack_v2_python_sparse | section12/resources/item.py | ExperimentalHypothesis/flask-restful-web-api | train | 0 |
5c973be837ff985ae4f8e7674ce5f281875f7067 | [
"self.dimensions = dimensions\nself.r0 = r0\nself.ep = ep\nself.usf = usf\nself.r1bar = r1bar\nif r2bar is None:\n self.r2bar = NewPotential.r2bardef[dimensions]\nif rnnn is None:\n self.rnnn = NewPotential.rnnndef[dimensions]\nif alphabar is None:\n self.alphabar = NewPotential.alphabardef[dimensions]\nse... | <|body_start_0|>
self.dimensions = dimensions
self.r0 = r0
self.ep = ep
self.usf = usf
self.r1bar = r1bar
if r2bar is None:
self.r2bar = NewPotential.r2bardef[dimensions]
if rnnn is None:
self.rnnn = NewPotential.rnnndef[dimensions]
... | NewPotential | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewPotential:
def __init__(self, dimensions, r0, ep, usf=None, r1bar=1.05, r2bar=None, r3bar=None, rnnn=None, alphabar=None, offset=0.0, spline=None):
"""Creates/initializes instance of member of class, which represents a potential. Required arguments are the dimensionality, the equilibr... | stack_v2_sparse_classes_75kplus_train_068447 | 10,735 | no_license | [
{
"docstring": "Creates/initializes instance of member of class, which represents a potential. Required arguments are the dimensionality, the equilibrium separation (which can be set to 1 without loss of generality), and ep = phi(r2). Optional arguments (e.g. alphabar) are set using defaults if not specified.",... | 6 | stack_v2_sparse_classes_30k_train_039688 | Implement the Python class `NewPotential` described below.
Class description:
Implement the NewPotential class.
Method signatures and docstrings:
- def __init__(self, dimensions, r0, ep, usf=None, r1bar=1.05, r2bar=None, r3bar=None, rnnn=None, alphabar=None, offset=0.0, spline=None): Creates/initializes instance of m... | Implement the Python class `NewPotential` described below.
Class description:
Implement the NewPotential class.
Method signatures and docstrings:
- def __init__(self, dimensions, r0, ep, usf=None, r1bar=1.05, r2bar=None, r3bar=None, rnnn=None, alphabar=None, offset=0.0, spline=None): Creates/initializes instance of m... | 18eafe263026a2c00fc52fa537a70e595e68e9a7 | <|skeleton|>
class NewPotential:
def __init__(self, dimensions, r0, ep, usf=None, r1bar=1.05, r2bar=None, r3bar=None, rnnn=None, alphabar=None, offset=0.0, spline=None):
"""Creates/initializes instance of member of class, which represents a potential. Required arguments are the dimensionality, the equilibr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NewPotential:
def __init__(self, dimensions, r0, ep, usf=None, r1bar=1.05, r2bar=None, r3bar=None, rnnn=None, alphabar=None, offset=0.0, spline=None):
"""Creates/initializes instance of member of class, which represents a potential. Required arguments are the dimensionality, the equilibrium separation... | the_stack_v2_python_sparse | newpotential_publish.py | varunprajan/PythonModules | train | 2 | |
86c2cbf485fcf963beb15bd05a49ab82019c577c | [
"self.memo = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))]\nfor i in range(len(matrix)):\n for j in range(len(matrix[0])):\n total = matrix[i][j]\n left_added = False\n up_added = False\n if j - 1 >= 0:\n total += self.memo[i][j - 1]\n left_add... | <|body_start_0|>
self.memo = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))]
for i in range(len(matrix)):
for j in range(len(matrix[0])):
total = matrix[i][j]
left_added = False
up_added = False
if j - 1 >= 0:
... | NumMatrix | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_75kplus_train_068448 | 1,711 | permissive | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int",
"name": "sumRegion",
"signature": "def sumRegion(self, row1, col1, row2, col2)"
... | 2 | null | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | 1c3461cfc05deb930d0866428eb00362b4338aab | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
self.memo = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))]
for i in range(len(matrix)):
for j in range(len(matrix[0])):
total = matrix[i][j]
left_add... | the_stack_v2_python_sparse | problems/304_range_sum_query_2d.py | apoorvkk/LeetCodeSolutions | train | 1 | |
cc11777e512aea4474ca2beb00a4b960d34830d0 | [
"self.interval = interval\nthread = threading.Thread(target=self.run, args=())\nthread.daemon = True\nthread.start()",
"while True:\n print('Doing something imporant in the background')\n time.sleep(self.interval)"
] | <|body_start_0|>
self.interval = interval
thread = threading.Thread(target=self.run, args=())
thread.daemon = True
thread.start()
<|end_body_0|>
<|body_start_1|>
while True:
print('Doing something imporant in the background')
time.sleep(self.interval)
<|e... | Threading example class The run() method will be started and it will run in the background until the application exits. | ThreadingExample | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThreadingExample:
"""Threading example class The run() method will be started and it will run in the background until the application exits."""
def __init__(self, interval=1):
"""Constructor :type interval: int :param interval: Check interval, in seconds"""
<|body_0|>
de... | stack_v2_sparse_classes_75kplus_train_068449 | 911 | permissive | [
{
"docstring": "Constructor :type interval: int :param interval: Check interval, in seconds",
"name": "__init__",
"signature": "def __init__(self, interval=1)"
},
{
"docstring": "Method that runs forever",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_053096 | Implement the Python class `ThreadingExample` described below.
Class description:
Threading example class The run() method will be started and it will run in the background until the application exits.
Method signatures and docstrings:
- def __init__(self, interval=1): Constructor :type interval: int :param interval:... | Implement the Python class `ThreadingExample` described below.
Class description:
Threading example class The run() method will be started and it will run in the background until the application exits.
Method signatures and docstrings:
- def __init__(self, interval=1): Constructor :type interval: int :param interval:... | 665d39a2bd82543d5196555f0801ef8fd4a3ee48 | <|skeleton|>
class ThreadingExample:
"""Threading example class The run() method will be started and it will run in the background until the application exits."""
def __init__(self, interval=1):
"""Constructor :type interval: int :param interval: Check interval, in seconds"""
<|body_0|>
de... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ThreadingExample:
"""Threading example class The run() method will be started and it will run in the background until the application exits."""
def __init__(self, interval=1):
"""Constructor :type interval: int :param interval: Check interval, in seconds"""
self.interval = interval
... | the_stack_v2_python_sparse | all-gists/832219525541e059aefa/snippet.py | gistable/gistable | train | 76 |
1e174db90be2a847d657b207c5e3e078888b4b81 | [
"i = 0\nm = 0\nwhile i < len(words):\n j = i + 1\n while j < len(words):\n f = True\n for c in words[i]:\n if c in words[j]:\n f = False\n break\n if f:\n m = max(m, len(words[i]) * len(words[j]))\n j += 1\n i += 1\nreturn m",
... | <|body_start_0|>
i = 0
m = 0
while i < len(words):
j = i + 1
while j < len(words):
f = True
for c in words[i]:
if c in words[j]:
f = False
break
if f:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProduct1(self, words):
""":type words: List[str] :rtype: int"""
<|body_0|>
def maxProduct(self, words):
""":type words: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i = 0
m = 0
while i < len(... | stack_v2_sparse_classes_75kplus_train_068450 | 1,149 | no_license | [
{
"docstring": ":type words: List[str] :rtype: int",
"name": "maxProduct1",
"signature": "def maxProduct1(self, words)"
},
{
"docstring": ":type words: List[str] :rtype: int",
"name": "maxProduct",
"signature": "def maxProduct(self, words)"
}
] | 2 | stack_v2_sparse_classes_30k_test_002508 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct1(self, words): :type words: List[str] :rtype: int
- def maxProduct(self, words): :type words: List[str] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct1(self, words): :type words: List[str] :rtype: int
- def maxProduct(self, words): :type words: List[str] :rtype: int
<|skeleton|>
class Solution:
def maxProdu... | e5b018493bbd12edcdcd0434f35d9c358106d391 | <|skeleton|>
class Solution:
def maxProduct1(self, words):
""":type words: List[str] :rtype: int"""
<|body_0|>
def maxProduct(self, words):
""":type words: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxProduct1(self, words):
""":type words: List[str] :rtype: int"""
i = 0
m = 0
while i < len(words):
j = i + 1
while j < len(words):
f = True
for c in words[i]:
if c in words[j]:
... | the_stack_v2_python_sparse | py/leetcode/318.py | wfeng1991/learnpy | train | 0 | |
0d9bb132537ebfa52623d11993c9f439c404b163 | [
"self.initial_value = initial_value\nself.target_value = target_value\nself.target_epoch = target_epoch\nself.decay_rate = target_value / initial_value",
"if self.target_epoch == 0:\n return self.target_value\nvalue = self.initial_value * np.power(self.decay_rate, epoch / self.target_epoch)\nreturn max(value, ... | <|body_start_0|>
self.initial_value = initial_value
self.target_value = target_value
self.target_epoch = target_epoch
self.decay_rate = target_value / initial_value
<|end_body_0|>
<|body_start_1|>
if self.target_epoch == 0:
return self.target_value
value = se... | This schedule applies an exponential decay function to an epoch index, considering a provided `initial_value` value. It is computed as: current_value = initial_value * decay_rate ^ (epoch / target_epoch), where `decay_rate` is equal to target_value / initial_value. | ExponentialDecaySchedule | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExponentialDecaySchedule:
"""This schedule applies an exponential decay function to an epoch index, considering a provided `initial_value` value. It is computed as: current_value = initial_value * decay_rate ^ (epoch / target_epoch), where `decay_rate` is equal to target_value / initial_value."""... | stack_v2_sparse_classes_75kplus_train_068451 | 10,292 | permissive | [
{
"docstring": "Initializes a schedule with an exponential decay function. :param initial_value: The initial value at which the schedule begins. :param target_value: The final value at which the schedule end. :param target_epoch: Zero-based index of the epoch from which the function value will be equal to the `... | 2 | null | Implement the Python class `ExponentialDecaySchedule` described below.
Class description:
This schedule applies an exponential decay function to an epoch index, considering a provided `initial_value` value. It is computed as: current_value = initial_value * decay_rate ^ (epoch / target_epoch), where `decay_rate` is eq... | Implement the Python class `ExponentialDecaySchedule` described below.
Class description:
This schedule applies an exponential decay function to an epoch index, considering a provided `initial_value` value. It is computed as: current_value = initial_value * decay_rate ^ (epoch / target_epoch), where `decay_rate` is eq... | c027c8b43c4865d46b8de01d8350dd338ec5a874 | <|skeleton|>
class ExponentialDecaySchedule:
"""This schedule applies an exponential decay function to an epoch index, considering a provided `initial_value` value. It is computed as: current_value = initial_value * decay_rate ^ (epoch / target_epoch), where `decay_rate` is equal to target_value / initial_value."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExponentialDecaySchedule:
"""This schedule applies an exponential decay function to an epoch index, considering a provided `initial_value` value. It is computed as: current_value = initial_value * decay_rate ^ (epoch / target_epoch), where `decay_rate` is equal to target_value / initial_value."""
def __i... | the_stack_v2_python_sparse | nncf/common/schedulers.py | openvinotoolkit/nncf | train | 558 |
cf30f048b85778437349548ef8b938323084d52e | [
"R_SPEED = 0.1\nT_SPEED = 0.05\nDIST_WHEEL_2_CENTER = 0.09\nWHEEL_RADIUS = 0.04\nA1, A2, A3 = (20, 160, 270)\n\ndef wheel_omega(wheel_angle):\n radians = math.pi * wheel_angle / 180\n return (math.sin(radians) * x * T_SPEED + math.cos(radians) * y * T_SPEED + DIST_WHEEL_2_CENTER * omega * R_SPEED) / WHEEL_RAD... | <|body_start_0|>
R_SPEED = 0.1
T_SPEED = 0.05
DIST_WHEEL_2_CENTER = 0.09
WHEEL_RADIUS = 0.04
A1, A2, A3 = (20, 160, 270)
def wheel_omega(wheel_angle):
radians = math.pi * wheel_angle / 180
return (math.sin(radians) * x * T_SPEED + math.cos(radians... | DriveSystem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DriveSystem:
def set_desired_motion(self, x, y, omega):
"""Power the motors in such a way that theoretically we achieve the desired translational acceleration and rotational velocity (omega)"""
<|body_0|>
def drive_motors(self, a, b, c):
"""Drives the motors using PW... | stack_v2_sparse_classes_75kplus_train_068452 | 2,849 | permissive | [
{
"docstring": "Power the motors in such a way that theoretically we achieve the desired translational acceleration and rotational velocity (omega)",
"name": "set_desired_motion",
"signature": "def set_desired_motion(self, x, y, omega)"
},
{
"docstring": "Drives the motors using PWM and toggling... | 2 | null | Implement the Python class `DriveSystem` described below.
Class description:
Implement the DriveSystem class.
Method signatures and docstrings:
- def set_desired_motion(self, x, y, omega): Power the motors in such a way that theoretically we achieve the desired translational acceleration and rotational velocity (omeg... | Implement the Python class `DriveSystem` described below.
Class description:
Implement the DriveSystem class.
Method signatures and docstrings:
- def set_desired_motion(self, x, y, omega): Power the motors in such a way that theoretically we achieve the desired translational acceleration and rotational velocity (omeg... | 6dde6b5d2f72fac3928c5042a27dc50e978c3425 | <|skeleton|>
class DriveSystem:
def set_desired_motion(self, x, y, omega):
"""Power the motors in such a way that theoretically we achieve the desired translational acceleration and rotational velocity (omega)"""
<|body_0|>
def drive_motors(self, a, b, c):
"""Drives the motors using PW... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DriveSystem:
def set_desired_motion(self, x, y, omega):
"""Power the motors in such a way that theoretically we achieve the desired translational acceleration and rotational velocity (omega)"""
R_SPEED = 0.1
T_SPEED = 0.05
DIST_WHEEL_2_CENTER = 0.09
WHEEL_RADIUS = 0.04
... | the_stack_v2_python_sparse | DriveSystem/DriveSystem.py | CallumJHays/g26-egb320-2019 | train | 0 | |
8ce47345a5b3e9be28aff1618a2ef79edd482e34 | [
"self.config_entry = entry\nself.lametric = LaMetricDevice(host=entry.data[CONF_HOST], api_key=entry.data[CONF_API_KEY], session=async_get_clientsession(hass))\nsuper().__init__(hass, LOGGER, name=DOMAIN, update_interval=SCAN_INTERVAL)",
"try:\n return await self.lametric.device()\nexcept LaMetricAuthenticatio... | <|body_start_0|>
self.config_entry = entry
self.lametric = LaMetricDevice(host=entry.data[CONF_HOST], api_key=entry.data[CONF_API_KEY], session=async_get_clientsession(hass))
super().__init__(hass, LOGGER, name=DOMAIN, update_interval=SCAN_INTERVAL)
<|end_body_0|>
<|body_start_1|>
try:
... | The LaMetric Data Update Coordinator. | LaMetricDataUpdateCoordinator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LaMetricDataUpdateCoordinator:
"""The LaMetric Data Update Coordinator."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Initialize the LaMatric coordinator."""
<|body_0|>
async def _async_update_data(self) -> Device:
"""Fetch device inf... | stack_v2_sparse_classes_75kplus_train_068453 | 1,627 | permissive | [
{
"docstring": "Initialize the LaMatric coordinator.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None"
},
{
"docstring": "Fetch device information of the LaMetric device.",
"name": "_async_update_data",
"signature": "async def _async... | 2 | stack_v2_sparse_classes_30k_train_001743 | Implement the Python class `LaMetricDataUpdateCoordinator` described below.
Class description:
The LaMetric Data Update Coordinator.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None: Initialize the LaMatric coordinator.
- async def _async_update_data(self) -> Dev... | Implement the Python class `LaMetricDataUpdateCoordinator` described below.
Class description:
The LaMetric Data Update Coordinator.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None: Initialize the LaMatric coordinator.
- async def _async_update_data(self) -> Dev... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class LaMetricDataUpdateCoordinator:
"""The LaMetric Data Update Coordinator."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Initialize the LaMatric coordinator."""
<|body_0|>
async def _async_update_data(self) -> Device:
"""Fetch device inf... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LaMetricDataUpdateCoordinator:
"""The LaMetric Data Update Coordinator."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Initialize the LaMatric coordinator."""
self.config_entry = entry
self.lametric = LaMetricDevice(host=entry.data[CONF_HOST], api_key=e... | the_stack_v2_python_sparse | homeassistant/components/lametric/coordinator.py | home-assistant/core | train | 35,501 |
30d2b0b1cf973edc2df016f7856a4ad03f37f3f4 | [
"parent = request.GET.get('parent', '')\nddlDmlType = request.GET.get('type', '')\nfilterInputValue = request.GET.get('filterInputValue', '')\nversion = request.GET.get('version', '')\ndic = {'parent': parent, 'ddlDmlType': ddlDmlType}\nobj = SqlCaseManage.objects.filter(**dic)\nif version:\n obj = obj.filter(ve... | <|body_start_0|>
parent = request.GET.get('parent', '')
ddlDmlType = request.GET.get('type', '')
filterInputValue = request.GET.get('filterInputValue', '')
version = request.GET.get('version', '')
dic = {'parent': parent, 'ddlDmlType': ddlDmlType}
obj = SqlCaseManage.obje... | SqlCaseManageList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SqlCaseManageList:
def get(self, request, *args, **kwargs):
"""SQL测试用例列表"""
<|body_0|>
def put(self, request, *args, **kwargs):
"""编辑SQL测试用例"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""创建SQL测试用例 级联更新结构表ddl/dml的数量"""
<|body_... | stack_v2_sparse_classes_75kplus_train_068454 | 14,029 | no_license | [
{
"docstring": "SQL测试用例列表",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "编辑SQL测试用例",
"name": "put",
"signature": "def put(self, request, *args, **kwargs)"
},
{
"docstring": "创建SQL测试用例 级联更新结构表ddl/dml的数量",
"name": "post",
"signatu... | 4 | stack_v2_sparse_classes_30k_train_015293 | Implement the Python class `SqlCaseManageList` described below.
Class description:
Implement the SqlCaseManageList class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): SQL测试用例列表
- def put(self, request, *args, **kwargs): 编辑SQL测试用例
- def post(self, request, *args, **kwargs): 创建SQL测试用例 级联... | Implement the Python class `SqlCaseManageList` described below.
Class description:
Implement the SqlCaseManageList class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): SQL测试用例列表
- def put(self, request, *args, **kwargs): 编辑SQL测试用例
- def post(self, request, *args, **kwargs): 创建SQL测试用例 级联... | f2523d6e51cde1b53ac6f453f8066b4b90c523b9 | <|skeleton|>
class SqlCaseManageList:
def get(self, request, *args, **kwargs):
"""SQL测试用例列表"""
<|body_0|>
def put(self, request, *args, **kwargs):
"""编辑SQL测试用例"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""创建SQL测试用例 级联更新结构表ddl/dml的数量"""
<|body_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SqlCaseManageList:
def get(self, request, *args, **kwargs):
"""SQL测试用例列表"""
parent = request.GET.get('parent', '')
ddlDmlType = request.GET.get('type', '')
filterInputValue = request.GET.get('filterInputValue', '')
version = request.GET.get('version', '')
dic = ... | the_stack_v2_python_sparse | api/db/rest/sqlCaseManage.py | zhuzhanhao1/backend | train | 0 | |
81f0d921f6bda0dcc0fd4617ba98e08ac85130a3 | [
"super(BasicAligner, self).__init__()\nself._extensions = [palign().extension]\nself._outext = palign().extension\nself._name = 'basic'",
"if isinstance(input_wav, float) is True:\n duration = input_wav\nelse:\n try:\n wav_speech = sppas.src.audiodata.aio.open(input_wav)\n duration = wav_speec... | <|body_start_0|>
super(BasicAligner, self).__init__()
self._extensions = [palign().extension]
self._outext = palign().extension
self._name = 'basic'
<|end_body_0|>
<|body_start_1|>
if isinstance(input_wav, float) is True:
duration = input_wav
else:
... | Basic automatic alignment system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi This segmentation assign the same duration to each phoneme. In case of phonetic variants, the fir... | BasicAligner | [
"GFDL-1.1-or-later",
"GPL-3.0-only",
"GPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicAligner:
"""Basic automatic alignment system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi This segmentation assign the same duration to each phonem... | stack_v2_sparse_classes_75kplus_train_068455 | 6,949 | permissive | [
{
"docstring": "Create a BasicAligner instance. This class allows to align one unit assigning the same duration to each phoneme. It selects the shortest sequence in case of variants. :param model_dir: (str) Ignored.",
"name": "__init__",
"signature": "def __init__(self, model_dir=None)"
},
{
"do... | 5 | stack_v2_sparse_classes_30k_train_051764 | Implement the Python class `BasicAligner` described below.
Class description:
Basic automatic alignment system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi This segmentation ... | Implement the Python class `BasicAligner` described below.
Class description:
Basic automatic alignment system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi This segmentation ... | 3167b65f576abcc27a8767d24c274a04712bd948 | <|skeleton|>
class BasicAligner:
"""Basic automatic alignment system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi This segmentation assign the same duration to each phonem... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BasicAligner:
"""Basic automatic alignment system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi This segmentation assign the same duration to each phoneme. In case of... | the_stack_v2_python_sparse | sppas/sppas/src/annotations/Align/aligners/basicalign.py | mirfan899/MTTS | train | 0 |
5b0c7f99a1d8bcf527c666e999693637d85072ce | [
"if item not in ('load', 'unload', 'reload'):\n raise ValueError('Invalid plugin type \"{queue_name}\"'.format(queue_name=item))\nif not self:\n Delay(0, self._loop_through_queues)\nvalue = self[item] = set()\nreturn value",
"if 'unload' in self:\n self._unload_plugins()\n del self['unload']\nif 'load... | <|body_start_0|>
if item not in ('load', 'unload', 'reload'):
raise ValueError('Invalid plugin type "{queue_name}"'.format(queue_name=item))
if not self:
Delay(0, self._loop_through_queues)
value = self[item] = set()
return value
<|end_body_0|>
<|body_start_1|>
... | Plugin queue class used to load/unload plugins. | _PluginQueue | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _PluginQueue:
"""Plugin queue class used to load/unload plugins."""
def __missing__(self, item):
"""Add the item to its queue and loop through queues after 1 tick."""
<|body_0|>
def _loop_through_queues(self):
"""Loop through all queues to properly load/unload pl... | stack_v2_sparse_classes_75kplus_train_068456 | 5,183 | no_license | [
{
"docstring": "Add the item to its queue and loop through queues after 1 tick.",
"name": "__missing__",
"signature": "def __missing__(self, item)"
},
{
"docstring": "Loop through all queues to properly load/unload plugins.",
"name": "_loop_through_queues",
"signature": "def _loop_throug... | 4 | stack_v2_sparse_classes_30k_train_000766 | Implement the Python class `_PluginQueue` described below.
Class description:
Plugin queue class used to load/unload plugins.
Method signatures and docstrings:
- def __missing__(self, item): Add the item to its queue and loop through queues after 1 tick.
- def _loop_through_queues(self): Loop through all queues to pr... | Implement the Python class `_PluginQueue` described below.
Class description:
Plugin queue class used to load/unload plugins.
Method signatures and docstrings:
- def __missing__(self, item): Add the item to its queue and loop through queues after 1 tick.
- def _loop_through_queues(self): Loop through all queues to pr... | cead3639bab2acce9da55a4e7f196c750160b27f | <|skeleton|>
class _PluginQueue:
"""Plugin queue class used to load/unload plugins."""
def __missing__(self, item):
"""Add the item to its queue and loop through queues after 1 tick."""
<|body_0|>
def _loop_through_queues(self):
"""Loop through all queues to properly load/unload pl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _PluginQueue:
"""Plugin queue class used to load/unload plugins."""
def __missing__(self, item):
"""Add the item to its queue and loop through queues after 1 tick."""
if item not in ('load', 'unload', 'reload'):
raise ValueError('Invalid plugin type "{queue_name}"'.format(queu... | the_stack_v2_python_sparse | srcds/addons/source-python/plugins/admin/core/plugins/queue.py | Source-Python-Dev-Team/Source.Python.Admin | train | 8 |
dc44f9fa36d9243accc60100661a258409ad21f2 | [
"params = {'part': enf_parts(resource='channels', value=parts), 'hl': hl, 'maxResults': max_results, 'onBehalfOfContentOwner': on_behalf_of_content_owner, 'pageToken': page_token, **kwargs}\nif for_username is not None:\n params['forUsername'] = for_username\nelif channel_id is not None:\n params['id'] = enf_... | <|body_start_0|>
params = {'part': enf_parts(resource='channels', value=parts), 'hl': hl, 'maxResults': max_results, 'onBehalfOfContentOwner': on_behalf_of_content_owner, 'pageToken': page_token, **kwargs}
if for_username is not None:
params['forUsername'] = for_username
elif channel... | A channel resource contains information about a YouTube channel. References: https://developers.google.com/youtube/v3/docs/channels | ChannelsResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChannelsResource:
"""A channel resource contains information about a YouTube channel. References: https://developers.google.com/youtube/v3/docs/channels"""
def list(self, parts: Optional[Union[str, list, tuple, set]]=None, for_username: Optional[str]=None, channel_id: Optional[Union[str, lis... | stack_v2_sparse_classes_75kplus_train_068457 | 7,718 | permissive | [
{
"docstring": "Returns a collection of zero or more channel resources that match the request criteria. Args: parts: Comma-separated list of one or more channel resource properties. Accepted values: id,auditDetails,brandingSettings,contentDetails,contentOwnerDetails, localizations,snippet,statistics,status,topi... | 2 | null | Implement the Python class `ChannelsResource` described below.
Class description:
A channel resource contains information about a YouTube channel. References: https://developers.google.com/youtube/v3/docs/channels
Method signatures and docstrings:
- def list(self, parts: Optional[Union[str, list, tuple, set]]=None, f... | Implement the Python class `ChannelsResource` described below.
Class description:
A channel resource contains information about a YouTube channel. References: https://developers.google.com/youtube/v3/docs/channels
Method signatures and docstrings:
- def list(self, parts: Optional[Union[str, list, tuple, set]]=None, f... | 1ed2f67a55b8df75c5fab9aacd7d9ff4d460812a | <|skeleton|>
class ChannelsResource:
"""A channel resource contains information about a YouTube channel. References: https://developers.google.com/youtube/v3/docs/channels"""
def list(self, parts: Optional[Union[str, list, tuple, set]]=None, for_username: Optional[str]=None, channel_id: Optional[Union[str, lis... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ChannelsResource:
"""A channel resource contains information about a YouTube channel. References: https://developers.google.com/youtube/v3/docs/channels"""
def list(self, parts: Optional[Union[str, list, tuple, set]]=None, for_username: Optional[str]=None, channel_id: Optional[Union[str, list, tuple, set... | the_stack_v2_python_sparse | pyyoutube/resources/channels.py | sns-sdks/python-youtube | train | 249 |
b18c34502918b94175ea56a6a68f003f5132f416 | [
"nic_attributes = {}\nnic_plugin_attributes_query = db().query(cls.model.id, models.Plugin.name, models.Plugin.title, cls.model.attributes).join(models.ClusterPlugin, models.Plugin).filter(cls.model.interface_id == interface.id).filter(models.ClusterPlugin.enabled.is_(True)).all()\nfor nic_plugin_id, name, title, a... | <|body_start_0|>
nic_attributes = {}
nic_plugin_attributes_query = db().query(cls.model.id, models.Plugin.name, models.Plugin.title, cls.model.attributes).join(models.ClusterPlugin, models.Plugin).filter(cls.model.interface_id == interface.id).filter(models.ClusterPlugin.enabled.is_(True)).all()
... | NodeNICInterfaceClusterPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodeNICInterfaceClusterPlugin:
def get_all_enabled_attributes_by_interface(cls, interface):
"""Returns plugin enabled attributes for specific NIC. :param interface: Interface instance :type interface: models.node.NodeNICInterface :returns: dict -- Dict object with plugin NIC attributes""... | stack_v2_sparse_classes_75kplus_train_068458 | 24,356 | permissive | [
{
"docstring": "Returns plugin enabled attributes for specific NIC. :param interface: Interface instance :type interface: models.node.NodeNICInterface :returns: dict -- Dict object with plugin NIC attributes",
"name": "get_all_enabled_attributes_by_interface",
"signature": "def get_all_enabled_attribute... | 3 | stack_v2_sparse_classes_30k_val_002094 | Implement the Python class `NodeNICInterfaceClusterPlugin` described below.
Class description:
Implement the NodeNICInterfaceClusterPlugin class.
Method signatures and docstrings:
- def get_all_enabled_attributes_by_interface(cls, interface): Returns plugin enabled attributes for specific NIC. :param interface: Inter... | Implement the Python class `NodeNICInterfaceClusterPlugin` described below.
Class description:
Implement the NodeNICInterfaceClusterPlugin class.
Method signatures and docstrings:
- def get_all_enabled_attributes_by_interface(cls, interface): Returns plugin enabled attributes for specific NIC. :param interface: Inter... | 768ac74a420f822261c4eb8da72f1d8af3c6bbff | <|skeleton|>
class NodeNICInterfaceClusterPlugin:
def get_all_enabled_attributes_by_interface(cls, interface):
"""Returns plugin enabled attributes for specific NIC. :param interface: Interface instance :type interface: models.node.NodeNICInterface :returns: dict -- Dict object with plugin NIC attributes""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NodeNICInterfaceClusterPlugin:
def get_all_enabled_attributes_by_interface(cls, interface):
"""Returns plugin enabled attributes for specific NIC. :param interface: Interface instance :type interface: models.node.NodeNICInterface :returns: dict -- Dict object with plugin NIC attributes"""
nic_... | the_stack_v2_python_sparse | nailgun/nailgun/objects/plugin.py | dis-xcom/fuel-web | train | 0 | |
e8ae744d3ac1d8c8dbeabbc7cacef45c85d8778d | [
"tail = []\nfor num in nums:\n if not tail or num > tail[-1]:\n tail.append(num)\n elif num in tail:\n continue\n else:\n left = 0\n right = len(tail) - 1\n while left < right:\n mid = (left + right) // 2\n if tail[mid] > num:\n right ... | <|body_start_0|>
tail = []
for num in nums:
if not tail or num > tail[-1]:
tail.append(num)
elif num in tail:
continue
else:
left = 0
right = len(tail) - 1
while left < right:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def lengthOfLIS2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
tail = []
for num in nums:
... | stack_v2_sparse_classes_75kplus_train_068459 | 1,748 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "lengthOfLIS2",
"signature": "def lengthOfLIS2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013936 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
- def lengthOfLIS2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
- def lengthOfLIS2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def lengthOfLI... | 2866df7587ee867a958a2b4fc02345bc3ef56999 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def lengthOfLIS2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
tail = []
for num in nums:
if not tail or num > tail[-1]:
tail.append(num)
elif num in tail:
continue
else:
left = 0
... | the_stack_v2_python_sparse | 中级算法/lengthOfLIS.py | OrangeJessie/Fighting_Leetcode | train | 1 | |
8fb8a228c08dc5a74701271bd6db5937c47f0de2 | [
"use_openssl_only = os.getenv('SF_USE_OPENSSL_ONLY', 'False') == 'True'\nCHUNK_SIZE = 64 * kilobyte\nif not use_openssl_only:\n m = SHA256.new()\nelse:\n backend = default_backend()\n chosen_hash = hashes.SHA256()\n hasher = hashes.Hash(chosen_hash, backend)\nwhile True:\n chunk = src.read(CHUNK_SIZE... | <|body_start_0|>
use_openssl_only = os.getenv('SF_USE_OPENSSL_ONLY', 'False') == 'True'
CHUNK_SIZE = 64 * kilobyte
if not use_openssl_only:
m = SHA256.new()
else:
backend = default_backend()
chosen_hash = hashes.SHA256()
hasher = hashes.Has... | SnowflakeFileUtil | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnowflakeFileUtil:
def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]:
"""Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's size in bytes."""
<|body_0|>
def compress_with_gzip_from_stream(src_stream: IO[bytes]) -> tupl... | stack_v2_sparse_classes_75kplus_train_068460 | 5,427 | permissive | [
{
"docstring": "Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's size in bytes.",
"name": "get_digest_and_size",
"signature": "def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]"
},
{
"docstring": "Compresses a stream of bytes with GZIP. ... | 6 | stack_v2_sparse_classes_30k_train_033989 | Implement the Python class `SnowflakeFileUtil` described below.
Class description:
Implement the SnowflakeFileUtil class.
Method signatures and docstrings:
- def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]: Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's s... | Implement the Python class `SnowflakeFileUtil` described below.
Class description:
Implement the SnowflakeFileUtil class.
Method signatures and docstrings:
- def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]: Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's s... | da1ae4ed1e940e4210348c59c9c660ebaa78fc2e | <|skeleton|>
class SnowflakeFileUtil:
def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]:
"""Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's size in bytes."""
<|body_0|>
def compress_with_gzip_from_stream(src_stream: IO[bytes]) -> tupl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SnowflakeFileUtil:
def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]:
"""Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's size in bytes."""
use_openssl_only = os.getenv('SF_USE_OPENSSL_ONLY', 'False') == 'True'
CHUNK_SIZE = 64 ... | the_stack_v2_python_sparse | src/snowflake/connector/file_util.py | snowflakedb/snowflake-connector-python | train | 492 | |
c6992478c7dcc7b645135dcf7ed4c1e77f31f589 | [
"if not head:\n return head\nlast = None\nwhile head.next:\n later = head.next\n head.next = last\n last = head\n head = later\nhead.next = last\nreturn head\nprev = None\nwhile head:\n cur = head\n head = head.next\n cur.next = prev\n prev = cur\nreturn prev",
"if not head:\n return... | <|body_start_0|>
if not head:
return head
last = None
while head.next:
later = head.next
head.next = last
last = head
head = later
head.next = last
return head
prev = None
while head:
cur = he... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseList2(self, head, last=None):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not head:
... | stack_v2_sparse_classes_75kplus_train_068461 | 1,595 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList",
"signature": "def reverseList(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList2",
"signature": "def reverseList2(self, head, last=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010252 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def reverseList2(self, head, last=None): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def reverseList2(self, head, last=None): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
... | b4dccd3d1c59aa1e92f10ed5c4f7a3e1d08897d8 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseList2(self, head, last=None):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
if not head:
return head
last = None
while head.next:
later = head.next
head.next = last
last = head
head = later
head.next = l... | the_stack_v2_python_sparse | ReverseLinkedList.py | janewjy/Leetcode | train | 1 | |
6f39c3f052c4588ea6cc831c745044adddd662bd | [
"super(OpenStackBaseTest, cls).setUpClass(application_name, model_alias)\ncls.keystone_session = openstack_utils.get_overcloud_keystone_session(model_name=cls.model_name)\ncls.cacert = openstack_utils.get_cacert()\ncls.nova_client = openstack_utils.get_nova_session_client(cls.keystone_session)",
"try:\n loggin... | <|body_start_0|>
super(OpenStackBaseTest, cls).setUpClass(application_name, model_alias)
cls.keystone_session = openstack_utils.get_overcloud_keystone_session(model_name=cls.model_name)
cls.cacert = openstack_utils.get_cacert()
cls.nova_client = openstack_utils.get_nova_session_client(cl... | Generic helpers for testing OpenStack API charms. | OpenStackBaseTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpenStackBaseTest:
"""Generic helpers for testing OpenStack API charms."""
def setUpClass(cls, application_name=None, model_alias=None):
"""Run setup for test class to create common resources."""
<|body_0|>
def resource_cleanup(self):
"""Remove test resources."""... | stack_v2_sparse_classes_75kplus_train_068462 | 22,129 | permissive | [
{
"docstring": "Run setup for test class to create common resources.",
"name": "setUpClass",
"signature": "def setUpClass(cls, application_name=None, model_alias=None)"
},
{
"docstring": "Remove test resources.",
"name": "resource_cleanup",
"signature": "def resource_cleanup(self)"
},
... | 6 | stack_v2_sparse_classes_30k_train_024259 | Implement the Python class `OpenStackBaseTest` described below.
Class description:
Generic helpers for testing OpenStack API charms.
Method signatures and docstrings:
- def setUpClass(cls, application_name=None, model_alias=None): Run setup for test class to create common resources.
- def resource_cleanup(self): Remo... | Implement the Python class `OpenStackBaseTest` described below.
Class description:
Generic helpers for testing OpenStack API charms.
Method signatures and docstrings:
- def setUpClass(cls, application_name=None, model_alias=None): Run setup for test class to create common resources.
- def resource_cleanup(self): Remo... | b0f5a2430a19b4e2835c2ccb9482d0831ffe3483 | <|skeleton|>
class OpenStackBaseTest:
"""Generic helpers for testing OpenStack API charms."""
def setUpClass(cls, application_name=None, model_alias=None):
"""Run setup for test class to create common resources."""
<|body_0|>
def resource_cleanup(self):
"""Remove test resources."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OpenStackBaseTest:
"""Generic helpers for testing OpenStack API charms."""
def setUpClass(cls, application_name=None, model_alias=None):
"""Run setup for test class to create common resources."""
super(OpenStackBaseTest, cls).setUpClass(application_name, model_alias)
cls.keystone_... | the_stack_v2_python_sparse | zaza/openstack/charm_tests/test_utils.py | camille-rodriguez/zaza-openstack-tests | train | 1 |
a8fc39d4c595b3829992f6ee4fbab9648b01373c | [
"if os.path.isfile(Config.CR_CONFIG_FULL_PATH):\n log.log_debug('Configuration file: Found. Reading it.')\n self.read_config_file()\nelse:\n log.log_info('Configuration file: Not found. Creating it.')\n self.write_config_file()",
"log.log_debug('Reading the config file...')\nConfig.config.read(Config.... | <|body_start_0|>
if os.path.isfile(Config.CR_CONFIG_FULL_PATH):
log.log_debug('Configuration file: Found. Reading it.')
self.read_config_file()
else:
log.log_info('Configuration file: Not found. Creating it.')
self.write_config_file()
<|end_body_0|>
<|bod... | Manages CentralReport configuration. | Config | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Config:
"""Manages CentralReport configuration."""
def __init__(self):
"""Constructor"""
<|body_0|>
def read_config_file(self):
"""Reads the configuration file."""
<|body_1|>
def write_config_file(self):
"""Writes the actual configuration int... | stack_v2_sparse_classes_75kplus_train_068463 | 6,426 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Reads the configuration file.",
"name": "read_config_file",
"signature": "def read_config_file(self)"
},
{
"docstring": "Writes the actual configuration into the config file.",
... | 5 | stack_v2_sparse_classes_30k_train_027665 | Implement the Python class `Config` described below.
Class description:
Manages CentralReport configuration.
Method signatures and docstrings:
- def __init__(self): Constructor
- def read_config_file(self): Reads the configuration file.
- def write_config_file(self): Writes the actual configuration into the config fi... | Implement the Python class `Config` described below.
Class description:
Manages CentralReport configuration.
Method signatures and docstrings:
- def __init__(self): Constructor
- def read_config_file(self): Reads the configuration file.
- def write_config_file(self): Writes the actual configuration into the config fi... | 421447f31d07321f65198c5b5746baa16c9d9725 | <|skeleton|>
class Config:
"""Manages CentralReport configuration."""
def __init__(self):
"""Constructor"""
<|body_0|>
def read_config_file(self):
"""Reads the configuration file."""
<|body_1|>
def write_config_file(self):
"""Writes the actual configuration int... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Config:
"""Manages CentralReport configuration."""
def __init__(self):
"""Constructor"""
if os.path.isfile(Config.CR_CONFIG_FULL_PATH):
log.log_debug('Configuration file: Found. Reading it.')
self.read_config_file()
else:
log.log_info('Configura... | the_stack_v2_python_sparse | centralreport/cr/tools.py | haiyangd/CentralReport | train | 0 |
1390d0e7272e1e101fd32cfa60a3f7d69555b372 | [
"cmd = 'fleetrun --gpu=0,1 dist_fleet_dygraph_api.py'\npro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\npro.wait()\npro.returncode == 0",
"cmd = 'fleetrun --gpu=0 dist_fleet_dygraph_api.py'\npro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.P... | <|body_start_0|>
cmd = 'fleetrun --gpu=0,1 dist_fleet_dygraph_api.py'
pro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
pro.wait()
pro.returncode == 0
<|end_body_0|>
<|body_start_1|>
cmd = 'fleetrun --gpu=0 dist_fleet_dygraph_api.py'
... | Test dygraph | TestDygraph | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDygraph:
"""Test dygraph"""
def test_dist_fleet_dygraph_api_2gpus(self):
"""test_dist_fleet_dygraph_api_2gpus."""
<|body_0|>
def test_dist_fleet_dygraph_api_1gpus(self):
"""test_dist_fleet_dygraph_api_1gpus"""
<|body_1|>
def test_dist_fleet_dygra... | stack_v2_sparse_classes_75kplus_train_068464 | 1,941 | no_license | [
{
"docstring": "test_dist_fleet_dygraph_api_2gpus.",
"name": "test_dist_fleet_dygraph_api_2gpus",
"signature": "def test_dist_fleet_dygraph_api_2gpus(self)"
},
{
"docstring": "test_dist_fleet_dygraph_api_1gpus",
"name": "test_dist_fleet_dygraph_api_1gpus",
"signature": "def test_dist_fle... | 4 | stack_v2_sparse_classes_30k_train_024535 | Implement the Python class `TestDygraph` described below.
Class description:
Test dygraph
Method signatures and docstrings:
- def test_dist_fleet_dygraph_api_2gpus(self): test_dist_fleet_dygraph_api_2gpus.
- def test_dist_fleet_dygraph_api_1gpus(self): test_dist_fleet_dygraph_api_1gpus
- def test_dist_fleet_dygraph_l... | Implement the Python class `TestDygraph` described below.
Class description:
Test dygraph
Method signatures and docstrings:
- def test_dist_fleet_dygraph_api_2gpus(self): test_dist_fleet_dygraph_api_2gpus.
- def test_dist_fleet_dygraph_api_1gpus(self): test_dist_fleet_dygraph_api_1gpus
- def test_dist_fleet_dygraph_l... | e3562ab40b574f06bba68df6895a055fa31a085d | <|skeleton|>
class TestDygraph:
"""Test dygraph"""
def test_dist_fleet_dygraph_api_2gpus(self):
"""test_dist_fleet_dygraph_api_2gpus."""
<|body_0|>
def test_dist_fleet_dygraph_api_1gpus(self):
"""test_dist_fleet_dygraph_api_1gpus"""
<|body_1|>
def test_dist_fleet_dygra... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestDygraph:
"""Test dygraph"""
def test_dist_fleet_dygraph_api_2gpus(self):
"""test_dist_fleet_dygraph_api_2gpus."""
cmd = 'fleetrun --gpu=0,1 dist_fleet_dygraph_api.py'
pro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
pro.wait()
... | the_stack_v2_python_sparse | dist_cts/dist_fleet_pipeline/test_dist_fleet_dygraph_api.py | gentelyang/scripts | train | 0 |
d3621d82aad1d0a68f2502c47792103df57ae7c5 | [
"to_return = []\nfor module in modules.values():\n try:\n if module.meta.allow_today:\n today = module.today()\n if today:\n to_return.append({'name': module.meta.display_name, 'renderable': today, 'destroy_func': lambda: emit(f'{module.meta.name}.destroy')})\n exce... | <|body_start_0|>
to_return = []
for module in modules.values():
try:
if module.meta.allow_today:
today = module.today()
if today:
to_return.append({'name': module.meta.display_name, 'renderable': today, 'destroy_... | TodayModule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TodayModule:
def _get_today() -> List[dict]:
"""Generator to get the Today items from each module"""
<|body_0|>
def card(cls):
"""Returns the today card"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
to_return = []
for module in modules.val... | stack_v2_sparse_classes_75kplus_train_068465 | 1,941 | permissive | [
{
"docstring": "Generator to get the Today items from each module",
"name": "_get_today",
"signature": "def _get_today() -> List[dict]"
},
{
"docstring": "Returns the today card",
"name": "card",
"signature": "def card(cls)"
}
] | 2 | stack_v2_sparse_classes_30k_train_044739 | Implement the Python class `TodayModule` described below.
Class description:
Implement the TodayModule class.
Method signatures and docstrings:
- def _get_today() -> List[dict]: Generator to get the Today items from each module
- def card(cls): Returns the today card | Implement the Python class `TodayModule` described below.
Class description:
Implement the TodayModule class.
Method signatures and docstrings:
- def _get_today() -> List[dict]: Generator to get the Today items from each module
- def card(cls): Returns the today card
<|skeleton|>
class TodayModule:
def _get_tod... | 9962f09b543a3c52929501dba29aa48b495db578 | <|skeleton|>
class TodayModule:
def _get_today() -> List[dict]:
"""Generator to get the Today items from each module"""
<|body_0|>
def card(cls):
"""Returns the today card"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TodayModule:
def _get_today() -> List[dict]:
"""Generator to get the Today items from each module"""
to_return = []
for module in modules.values():
try:
if module.meta.allow_today:
today = module.today()
if today:
... | the_stack_v2_python_sparse | trash_dash/modules/today.py | manjunaath5583/respectful_racoons | train | 2 | |
bee60778f293ac7988cd143b9f45fa91645e7059 | [
"if n == 1:\n return 1\nelif n == 2:\n return 2\nelse:\n return self.rec_climbStairs(n - 1) + self.rec_climbStairs(n - 2)",
"if n == 1:\n return 1\na = 1\nb = 2\nfor i in range(n - 2):\n tmp = a + b\n a = b\n b = tmp\nreturn b"
] | <|body_start_0|>
if n == 1:
return 1
elif n == 2:
return 2
else:
return self.rec_climbStairs(n - 1) + self.rec_climbStairs(n - 2)
<|end_body_0|>
<|body_start_1|>
if n == 1:
return 1
a = 1
b = 2
for i in range(n - 2)... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rec_climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def dp_climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 1:
return 1
elif n == 2:
... | stack_v2_sparse_classes_75kplus_train_068466 | 820 | permissive | [
{
"docstring": ":type n: int :rtype: int",
"name": "rec_climbStairs",
"signature": "def rec_climbStairs(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "dp_climbStairs",
"signature": "def dp_climbStairs(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_034743 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rec_climbStairs(self, n): :type n: int :rtype: int
- def dp_climbStairs(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rec_climbStairs(self, n): :type n: int :rtype: int
- def dp_climbStairs(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def rec_climbStairs(self, n):
... | e93f93fd58d1945708d6aa300dcbcd17d0708274 | <|skeleton|>
class Solution:
def rec_climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def dp_climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rec_climbStairs(self, n):
""":type n: int :rtype: int"""
if n == 1:
return 1
elif n == 2:
return 2
else:
return self.rec_climbStairs(n - 1) + self.rec_climbStairs(n - 2)
def dp_climbStairs(self, n):
""":type n: int ... | the_stack_v2_python_sparse | LeetCode/Python/DP/70. Climbing Stairs.py | Alfonsxh/LeetCode-Challenge-python | train | 1 | |
91093f8de2b68e57eb4a7a9666f6aa9c23dbc50d | [
"if sideAngle is None:\n if len(loop) > 0:\n sideAngle = 2.0 * math.pi / float(len(loop))\n else:\n sideAngle = 1.0\n print('Warning, loop has no sides in SideLoop in lineation.')\nif sideLength is None:\n if len(loop) > 0:\n sideLength = euclidean.getLoopLength(loop) / float(le... | <|body_start_0|>
if sideAngle is None:
if len(loop) > 0:
sideAngle = 2.0 * math.pi / float(len(loop))
else:
sideAngle = 1.0
print('Warning, loop has no sides in SideLoop in lineation.')
if sideLength is None:
if len(loop... | Class to handle loop, side angle and side length. | SideLoop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SideLoop:
"""Class to handle loop, side angle and side length."""
def __init__(self, loop, sideAngle=None, sideLength=None):
"""Initialize."""
<|body_0|>
def getManipulationPluginLoops(self, elementNode):
"""Get loop manipulated by the plugins in the manipulation... | stack_v2_sparse_classes_75kplus_train_068467 | 12,603 | no_license | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, loop, sideAngle=None, sideLength=None)"
},
{
"docstring": "Get loop manipulated by the plugins in the manipulation paths folder.",
"name": "getManipulationPluginLoops",
"signature": "def getManipulationPlu... | 3 | stack_v2_sparse_classes_30k_test_001169 | Implement the Python class `SideLoop` described below.
Class description:
Class to handle loop, side angle and side length.
Method signatures and docstrings:
- def __init__(self, loop, sideAngle=None, sideLength=None): Initialize.
- def getManipulationPluginLoops(self, elementNode): Get loop manipulated by the plugin... | Implement the Python class `SideLoop` described below.
Class description:
Class to handle loop, side angle and side length.
Method signatures and docstrings:
- def __init__(self, loop, sideAngle=None, sideLength=None): Initialize.
- def getManipulationPluginLoops(self, elementNode): Get loop manipulated by the plugin... | ef1732ade7b1ae3c676e5321333c7ca88c9db514 | <|skeleton|>
class SideLoop:
"""Class to handle loop, side angle and side length."""
def __init__(self, loop, sideAngle=None, sideLength=None):
"""Initialize."""
<|body_0|>
def getManipulationPluginLoops(self, elementNode):
"""Get loop manipulated by the plugins in the manipulation... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SideLoop:
"""Class to handle loop, side angle and side length."""
def __init__(self, loop, sideAngle=None, sideLength=None):
"""Initialize."""
if sideAngle is None:
if len(loop) > 0:
sideAngle = 2.0 * math.pi / float(len(loop))
else:
... | the_stack_v2_python_sparse | fabmetheus_utilities/geometry/creation/lineation.py | joewalnes/SFACT | train | 1 |
3d51bbd22301245944d5baca5906efa0e09e1dbe | [
"super().__init__()\nif background_color is None:\n background_color = torch.full((3,), -1, dtype=torch.float32)\nself.register_buffer('bg_color', background_color)\nself.noise_std = noise_std",
"p_distances = z_vals[..., 1:] - z_vals[..., :-1]\nlast_elem = torch.as_tensor([10000000000.0])[None, :].expand(p_di... | <|body_start_0|>
super().__init__()
if background_color is None:
background_color = torch.full((3,), -1, dtype=torch.float32)
self.register_buffer('bg_color', background_color)
self.noise_std = noise_std
<|end_body_0|>
<|body_start_1|>
p_distances = z_vals[..., 1:] -... | Color aggregation function. Takes the raw predictions obtained from a NIF model, the depth values and a ray direction to produce the final color of a pixel. Please refer to the original NeRF paper for more information. Usage: .. code-block:: python # Assume the models are given. nif_model = NeRFModel() renderer = Point... | NeRFAggregator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeRFAggregator:
"""Color aggregation function. Takes the raw predictions obtained from a NIF model, the depth values and a ray direction to produce the final color of a pixel. Please refer to the original NeRF paper for more information. Usage: .. code-block:: python # Assume the models are given... | stack_v2_sparse_classes_75kplus_train_068468 | 4,738 | permissive | [
{
"docstring": "Args: background_color (torch.Tensor): The background color to be added for rendering. If set to None, no background will be added. Default is None. noise_std (float): The standard deviation of the noise to be added to alpha. Set 0 to disable the noise addition. Default is 0.",
"name": "__in... | 2 | stack_v2_sparse_classes_30k_test_001831 | Implement the Python class `NeRFAggregator` described below.
Class description:
Color aggregation function. Takes the raw predictions obtained from a NIF model, the depth values and a ray direction to produce the final color of a pixel. Please refer to the original NeRF paper for more information. Usage: .. code-block... | Implement the Python class `NeRFAggregator` described below.
Class description:
Color aggregation function. Takes the raw predictions obtained from a NIF model, the depth values and a ray direction to produce the final color of a pixel. Please refer to the original NeRF paper for more information. Usage: .. code-block... | da3680cce7e8fc4c194f13a1528cddbad9a18ab0 | <|skeleton|>
class NeRFAggregator:
"""Color aggregation function. Takes the raw predictions obtained from a NIF model, the depth values and a ray direction to produce the final color of a pixel. Please refer to the original NeRF paper for more information. Usage: .. code-block:: python # Assume the models are given... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NeRFAggregator:
"""Color aggregation function. Takes the raw predictions obtained from a NIF model, the depth values and a ray direction to produce the final color of a pixel. Please refer to the original NeRF paper for more information. Usage: .. code-block:: python # Assume the models are given. nif_model =... | the_stack_v2_python_sparse | pynif3d/aggregation/nerf_aggregator.py | pfnet/pynif3d | train | 72 |
487d8725374bfb0bd04c29b639f883de29abbb7c | [
"row_length = len(matrix)\nif row_length == 0:\n return\ncol_length = len(matrix[0])\nupdate_place = []\nfor i in range(row_length):\n for j in range(col_length):\n if matrix[i][j] == 0:\n update_place.append((i, j))\nfor row, col in update_place:\n for i in range(row_length):\n ma... | <|body_start_0|>
row_length = len(matrix)
if row_length == 0:
return
col_length = len(matrix[0])
update_place = []
for i in range(row_length):
for j in range(col_length):
if matrix[i][j] == 0:
update_place.append((i, j))... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def setZeroes(self, matrix: [[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_0|>
def setZeroes_2(self, matrix: [[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_75kplus_train_068469 | 1,986 | permissive | [
{
"docstring": "Do not return anything, modify matrix in-place instead.",
"name": "setZeroes",
"signature": "def setZeroes(self, matrix: [[int]]) -> None"
},
{
"docstring": "Do not return anything, modify matrix in-place instead.",
"name": "setZeroes_2",
"signature": "def setZeroes_2(sel... | 2 | stack_v2_sparse_classes_30k_train_041149 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def setZeroes(self, matrix: [[int]]) -> None: Do not return anything, modify matrix in-place instead.
- def setZeroes_2(self, matrix: [[int]]) -> None: Do not return anything, mo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def setZeroes(self, matrix: [[int]]) -> None: Do not return anything, modify matrix in-place instead.
- def setZeroes_2(self, matrix: [[int]]) -> None: Do not return anything, mo... | 735e782742fab15bdb046eb6d5fc7b03502cc92d | <|skeleton|>
class Solution:
def setZeroes(self, matrix: [[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_0|>
def setZeroes_2(self, matrix: [[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def setZeroes(self, matrix: [[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
row_length = len(matrix)
if row_length == 0:
return
col_length = len(matrix[0])
update_place = []
for i in range(row_length):
... | the_stack_v2_python_sparse | LeetCode/_0051_0100/_073_SetMatrixZeroes.py | BigEggStudy/LeetCode-Py | train | 1 | |
a233129b361ef71013245e3d5f4aedc5f66d6d03 | [
"@tff_math.make_val_and_grad_fn\ndef himmelblau(coord):\n x, y = (coord[..., 0], coord[..., 1])\n return (x * x + y - 11) ** 2 + (x + y * y - 7) ** 2\nstart = tf.constant([[1, 1], [-2, 2], [-1, -1], [1, -2]], dtype='float64')\nresults = self.evaluate(tff_math.optimizer.bfgs_minimize(himmelblau, initial_positi... | <|body_start_0|>
@tff_math.make_val_and_grad_fn
def himmelblau(coord):
x, y = (coord[..., 0], coord[..., 1])
return (x * x + y - 11) ** 2 + (x + y * y - 7) ** 2
start = tf.constant([[1, 1], [-2, 2], [-1, -1], [1, -2]], dtype='float64')
results = self.evaluate(tff_... | Tests for optimization algorithms. | OptimizerTest | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptimizerTest:
"""Tests for optimization algorithms."""
def test_bfgs_minimize(self):
"""Use BFGS algorithm to find all four minima of Himmelblau's function."""
<|body_0|>
def test_lbfgs_minimize(self):
"""Use L-BFGS algorithm to optimize randomly generated quadr... | stack_v2_sparse_classes_75kplus_train_068470 | 3,979 | permissive | [
{
"docstring": "Use BFGS algorithm to find all four minima of Himmelblau's function.",
"name": "test_bfgs_minimize",
"signature": "def test_bfgs_minimize(self)"
},
{
"docstring": "Use L-BFGS algorithm to optimize randomly generated quadratic bowls.",
"name": "test_lbfgs_minimize",
"signa... | 4 | stack_v2_sparse_classes_30k_train_039013 | Implement the Python class `OptimizerTest` described below.
Class description:
Tests for optimization algorithms.
Method signatures and docstrings:
- def test_bfgs_minimize(self): Use BFGS algorithm to find all four minima of Himmelblau's function.
- def test_lbfgs_minimize(self): Use L-BFGS algorithm to optimize ran... | Implement the Python class `OptimizerTest` described below.
Class description:
Tests for optimization algorithms.
Method signatures and docstrings:
- def test_bfgs_minimize(self): Use BFGS algorithm to find all four minima of Himmelblau's function.
- def test_lbfgs_minimize(self): Use L-BFGS algorithm to optimize ran... | 0d3a2193c0f2d320b65e602cf01d7a617da484df | <|skeleton|>
class OptimizerTest:
"""Tests for optimization algorithms."""
def test_bfgs_minimize(self):
"""Use BFGS algorithm to find all four minima of Himmelblau's function."""
<|body_0|>
def test_lbfgs_minimize(self):
"""Use L-BFGS algorithm to optimize randomly generated quadr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OptimizerTest:
"""Tests for optimization algorithms."""
def test_bfgs_minimize(self):
"""Use BFGS algorithm to find all four minima of Himmelblau's function."""
@tff_math.make_val_and_grad_fn
def himmelblau(coord):
x, y = (coord[..., 0], coord[..., 1])
retu... | the_stack_v2_python_sparse | tf_quant_finance/math/optimizer/optimizer_test.py | google/tf-quant-finance | train | 4,165 |
f6163f73acfc79fcc6e4a3f99366478820560295 | [
"fewshot_re_kit.framework.FewShotREModel.__init__(self, sentence_encoder)\nself.hidden_size = hidden_size\nself.node_dim = hidden_size + N\nself.gnn_obj = gnn_iclr.GNN_nl(N, self.node_dim, nf=96, J=1)",
"support = self.sentence_encoder(support)\nquery = self.sentence_encoder(query)\nsupport = support.view(-1, N, ... | <|body_start_0|>
fewshot_re_kit.framework.FewShotREModel.__init__(self, sentence_encoder)
self.hidden_size = hidden_size
self.node_dim = hidden_size + N
self.gnn_obj = gnn_iclr.GNN_nl(N, self.node_dim, nf=96, J=1)
<|end_body_0|>
<|body_start_1|>
support = self.sentence_encoder(s... | GNN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GNN:
def __init__(self, sentence_encoder, N, hidden_size=230):
"""N: Num of classes"""
<|body_0|>
def forward(self, support, query, N, K, NQ):
"""support: Inputs of the support set. query: Inputs of the query set. N: Num of classes K: Num of instances for each class ... | stack_v2_sparse_classes_75kplus_train_068471 | 1,805 | permissive | [
{
"docstring": "N: Num of classes",
"name": "__init__",
"signature": "def __init__(self, sentence_encoder, N, hidden_size=230)"
},
{
"docstring": "support: Inputs of the support set. query: Inputs of the query set. N: Num of classes K: Num of instances for each class in the support set Q: Num of... | 2 | stack_v2_sparse_classes_30k_train_054558 | Implement the Python class `GNN` described below.
Class description:
Implement the GNN class.
Method signatures and docstrings:
- def __init__(self, sentence_encoder, N, hidden_size=230): N: Num of classes
- def forward(self, support, query, N, K, NQ): support: Inputs of the support set. query: Inputs of the query se... | Implement the Python class `GNN` described below.
Class description:
Implement the GNN class.
Method signatures and docstrings:
- def __init__(self, sentence_encoder, N, hidden_size=230): N: Num of classes
- def forward(self, support, query, N, K, NQ): support: Inputs of the support set. query: Inputs of the query se... | 278a2315d2138810a379cd8d5718914dc56e2582 | <|skeleton|>
class GNN:
def __init__(self, sentence_encoder, N, hidden_size=230):
"""N: Num of classes"""
<|body_0|>
def forward(self, support, query, N, K, NQ):
"""support: Inputs of the support set. query: Inputs of the query set. N: Num of classes K: Num of instances for each class ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GNN:
def __init__(self, sentence_encoder, N, hidden_size=230):
"""N: Num of classes"""
fewshot_re_kit.framework.FewShotREModel.__init__(self, sentence_encoder)
self.hidden_size = hidden_size
self.node_dim = hidden_size + N
self.gnn_obj = gnn_iclr.GNN_nl(N, self.node_dim... | the_stack_v2_python_sparse | models/gnn.py | thunlp/FewRel | train | 752 | |
31e0b0aa64493ae4785a99201a9d65df4806e9cb | [
"super().__init__()\nself._n_pts_per_ray = n_pts_per_ray\nself._min_depth = min_depth\nself._max_depth = max_depth\nself._n_rays_per_image = n_rays_per_image\nself._unit_directions = unit_directions\nself._stratified_sampling = stratified_sampling\nself._lin_disp = lin_disp\n_xy_grid = torch.stack(tuple(reversed(me... | <|body_start_0|>
super().__init__()
self._n_pts_per_ray = n_pts_per_ray
self._min_depth = min_depth
self._max_depth = max_depth
self._n_rays_per_image = n_rays_per_image
self._unit_directions = unit_directions
self._stratified_sampling = stratified_sampling
... | Samples a fixed number of points along rays which are regularly distributed in a batch of rectangular image grids. Points along each ray have uniformly-spaced z-coordinates between a predefined minimum and maximum depth. The raysampler first generates a 3D coordinate grid of the following form: ``` / min_x, min_y, max_... | MultinomialRaysampler | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultinomialRaysampler:
"""Samples a fixed number of points along rays which are regularly distributed in a batch of rectangular image grids. Points along each ray have uniformly-spaced z-coordinates between a predefined minimum and maximum depth. The raysampler first generates a 3D coordinate gri... | stack_v2_sparse_classes_75kplus_train_068472 | 35,564 | permissive | [
{
"docstring": "Args: min_x: The leftmost x-coordinate of each ray's source pixel's center. max_x: The rightmost x-coordinate of each ray's source pixel's center. min_y: The topmost y-coordinate of each ray's source pixel's center. max_y: The bottommost y-coordinate of each ray's source pixel's center. image_wi... | 2 | stack_v2_sparse_classes_30k_train_010917 | Implement the Python class `MultinomialRaysampler` described below.
Class description:
Samples a fixed number of points along rays which are regularly distributed in a batch of rectangular image grids. Points along each ray have uniformly-spaced z-coordinates between a predefined minimum and maximum depth. The raysamp... | Implement the Python class `MultinomialRaysampler` described below.
Class description:
Samples a fixed number of points along rays which are regularly distributed in a batch of rectangular image grids. Points along each ray have uniformly-spaced z-coordinates between a predefined minimum and maximum depth. The raysamp... | af9f9be8786c69c68308013f68e527f3fddb88be | <|skeleton|>
class MultinomialRaysampler:
"""Samples a fixed number of points along rays which are regularly distributed in a batch of rectangular image grids. Points along each ray have uniformly-spaced z-coordinates between a predefined minimum and maximum depth. The raysampler first generates a 3D coordinate gri... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultinomialRaysampler:
"""Samples a fixed number of points along rays which are regularly distributed in a batch of rectangular image grids. Points along each ray have uniformly-spaced z-coordinates between a predefined minimum and maximum depth. The raysampler first generates a 3D coordinate grid of the foll... | the_stack_v2_python_sparse | pytorch3d/renderer/implicit/raysampling.py | angshine/pytorch3d | train | 1 |
c8152e029f6c81d613270fe69b7cb3ad92907c4c | [
"if flag:\n GroupTree(self.driver).click_menu_by_name('Default', '创建同级')\n title_name = '创建同级'\nelse:\n GroupTree(self.driver).click_menu_by_name('Default', '创建下一级')\n title_name = '创建下一级'\nreturn title_name",
"INPUT_TEXT = (By.XPATH, f'//span[contains(text(),\"{til_name}\")]/parent::div/following-sib... | <|body_start_0|>
if flag:
GroupTree(self.driver).click_menu_by_name('Default', '创建同级')
title_name = '创建同级'
else:
GroupTree(self.driver).click_menu_by_name('Default', '创建下一级')
title_name = '创建下一级'
return title_name
<|end_body_0|>
<|body_start_1|>
... | UserPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserPage:
def add_department_by_root_name(self, flag=True):
"""从根部门 - Default 下创建 同级 / 下一级 分组 :param flag: 判断是创建同级分组还是下一级分组 :return: 当前需要创建的分组类别"""
<|body_0|>
def create_department_group(self, group_name, til_name, confirm=True):
"""方法封装：用于创建 同级/下一级 分组 :param dep_nam... | stack_v2_sparse_classes_75kplus_train_068473 | 7,356 | no_license | [
{
"docstring": "从根部门 - Default 下创建 同级 / 下一级 分组 :param flag: 判断是创建同级分组还是下一级分组 :return: 当前需要创建的分组类别",
"name": "add_department_by_root_name",
"signature": "def add_department_by_root_name(self, flag=True)"
},
{
"docstring": "方法封装：用于创建 同级/下一级 分组 :param dep_name: 部分分组名称 :param til_name: dialog弹框中的标题 ... | 2 | stack_v2_sparse_classes_30k_train_005932 | Implement the Python class `UserPage` described below.
Class description:
Implement the UserPage class.
Method signatures and docstrings:
- def add_department_by_root_name(self, flag=True): 从根部门 - Default 下创建 同级 / 下一级 分组 :param flag: 判断是创建同级分组还是下一级分组 :return: 当前需要创建的分组类别
- def create_department_group(self, group_name... | Implement the Python class `UserPage` described below.
Class description:
Implement the UserPage class.
Method signatures and docstrings:
- def add_department_by_root_name(self, flag=True): 从根部门 - Default 下创建 同级 / 下一级 分组 :param flag: 判断是创建同级分组还是下一级分组 :return: 当前需要创建的分组类别
- def create_department_group(self, group_name... | 53ffcfc63447b4462c788d5620872fa54a9283a1 | <|skeleton|>
class UserPage:
def add_department_by_root_name(self, flag=True):
"""从根部门 - Default 下创建 同级 / 下一级 分组 :param flag: 判断是创建同级分组还是下一级分组 :return: 当前需要创建的分组类别"""
<|body_0|>
def create_department_group(self, group_name, til_name, confirm=True):
"""方法封装：用于创建 同级/下一级 分组 :param dep_nam... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserPage:
def add_department_by_root_name(self, flag=True):
"""从根部门 - Default 下创建 同级 / 下一级 分组 :param flag: 判断是创建同级分组还是下一级分组 :return: 当前需要创建的分组类别"""
if flag:
GroupTree(self.driver).click_menu_by_name('Default', '创建同级')
title_name = '创建同级'
else:
GroupT... | the_stack_v2_python_sparse | guard/pages/user_backup.py | qinwenzhu/selenium_pytest_actual | train | 0 | |
3e0cc80ab4346315fef500193508119b535343dd | [
"if not user_id:\n return\nsession_id = super().create_session(user_id)\nif not session_id:\n return\nuser_session = UserSession(user_id=user_id, session_id=session_id)\nuser_session.save()\nUserSession.save_to_file()\nreturn session_id",
"if not session_id:\n return None\nUserSession.load_from_file()\nu... | <|body_start_0|>
if not user_id:
return
session_id = super().create_session(user_id)
if not session_id:
return
user_session = UserSession(user_id=user_id, session_id=session_id)
user_session.save()
UserSession.save_to_file()
return session_... | SessionDBAuth Class | SessionDBAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionDBAuth:
"""SessionDBAuth Class"""
def create_session(self, user_id=None):
"""creates and stores new instance of UserSession and returns the Session ID"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""returns the User ID by requesting Use... | stack_v2_sparse_classes_75kplus_train_068474 | 1,904 | no_license | [
{
"docstring": "creates and stores new instance of UserSession and returns the Session ID",
"name": "create_session",
"signature": "def create_session(self, user_id=None)"
},
{
"docstring": "returns the User ID by requesting UserSession in the database based on session_id",
"name": "user_id_... | 3 | null | Implement the Python class `SessionDBAuth` described below.
Class description:
SessionDBAuth Class
Method signatures and docstrings:
- def create_session(self, user_id=None): creates and stores new instance of UserSession and returns the Session ID
- def user_id_for_session_id(self, session_id=None): returns the User... | Implement the Python class `SessionDBAuth` described below.
Class description:
SessionDBAuth Class
Method signatures and docstrings:
- def create_session(self, user_id=None): creates and stores new instance of UserSession and returns the Session ID
- def user_id_for_session_id(self, session_id=None): returns the User... | a09732a4f270d3dbeaf6ff1eb46c7bc0b71eaf4a | <|skeleton|>
class SessionDBAuth:
"""SessionDBAuth Class"""
def create_session(self, user_id=None):
"""creates and stores new instance of UserSession and returns the Session ID"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""returns the User ID by requesting Use... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SessionDBAuth:
"""SessionDBAuth Class"""
def create_session(self, user_id=None):
"""creates and stores new instance of UserSession and returns the Session ID"""
if not user_id:
return
session_id = super().create_session(user_id)
if not session_id:
r... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_db_auth.py | I7RANK/holbertonschool-web_back_end | train | 0 |
b38f7ab24d7864cec3427a547e05ed5d1a8e57bf | [
"super(Loss, self).__init__()\nself.model_name = model_name\nself.loss_name = loss_name\nself.loss_struct = []\nfor loss in self.loss_name.split('+'):\n weight, loss_type = loss.split('*')\n if loss_type == 'CrossEntropy':\n loss_function = nn.CrossEntropyLoss()\n elif loss_type == 'SmoothCrossEntro... | <|body_start_0|>
super(Loss, self).__init__()
self.model_name = model_name
self.loss_name = loss_name
self.loss_struct = []
for loss in self.loss_name.split('+'):
weight, loss_type = loss.split('*')
if loss_type == 'CrossEntropy':
loss_func... | Loss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Loss:
def __init__(self, model_name, loss_name, num_classes):
""":param model_name: 模型的名称；类型为str :param loss_name: 损失的名称；类型为str :param num_classes: 网络的参数"""
<|body_0|>
def forward(self, outputs, labels):
""":param outputs: 网络的输出，具体维度和网络有关 :param labels: 数据的真实类标，具体维度和... | stack_v2_sparse_classes_75kplus_train_068475 | 5,001 | permissive | [
{
"docstring": ":param model_name: 模型的名称；类型为str :param loss_name: 损失的名称；类型为str :param num_classes: 网络的参数",
"name": "__init__",
"signature": "def __init__(self, model_name, loss_name, num_classes)"
},
{
"docstring": ":param outputs: 网络的输出，具体维度和网络有关 :param labels: 数据的真实类标，具体维度和网络有关 :return loss_su... | 4 | stack_v2_sparse_classes_30k_train_023882 | Implement the Python class `Loss` described below.
Class description:
Implement the Loss class.
Method signatures and docstrings:
- def __init__(self, model_name, loss_name, num_classes): :param model_name: 模型的名称；类型为str :param loss_name: 损失的名称；类型为str :param num_classes: 网络的参数
- def forward(self, outputs, labels): :pa... | Implement the Python class `Loss` described below.
Class description:
Implement the Loss class.
Method signatures and docstrings:
- def __init__(self, model_name, loss_name, num_classes): :param model_name: 模型的名称；类型为str :param loss_name: 损失的名称；类型为str :param num_classes: 网络的参数
- def forward(self, outputs, labels): :pa... | d479b772f446033d32a124b80a1f9cd835988020 | <|skeleton|>
class Loss:
def __init__(self, model_name, loss_name, num_classes):
""":param model_name: 模型的名称；类型为str :param loss_name: 损失的名称；类型为str :param num_classes: 网络的参数"""
<|body_0|>
def forward(self, outputs, labels):
""":param outputs: 网络的输出，具体维度和网络有关 :param labels: 数据的真实类标，具体维度和... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Loss:
def __init__(self, model_name, loss_name, num_classes):
""":param model_name: 模型的名称；类型为str :param loss_name: 损失的名称；类型为str :param num_classes: 网络的参数"""
super(Loss, self).__init__()
self.model_name = model_name
self.loss_name = loss_name
self.loss_struct = []
... | the_stack_v2_python_sparse | losses/get_loss.py | XiangqianMa/AI-Competition-HuaWei | train | 13 | |
cc2ef5ad5295dd3d39293af95e4b38cf8afa8ebf | [
"ctrlpanel.ControlPanel.__init__(self, parent, overlayList, displayCtx, frame)\nif showHistory:\n self.__notebook = notebook.Notebook(self, style=wx.LEFT | wx.VERTICAL, border=0)\n subparent = self.__notebook\nelse:\n subparent = self\n self.__notebook = None\nself.__info = LocationInfoPanel(subparent, ... | <|body_start_0|>
ctrlpanel.ControlPanel.__init__(self, parent, overlayList, displayCtx, frame)
if showHistory:
self.__notebook = notebook.Notebook(self, style=wx.LEFT | wx.VERTICAL, border=0)
subparent = self.__notebook
else:
subparent = self
self.... | The ``LocationPanel`` is a panel which contains controls allowing the user to view and modify the :attr:`.DisplayContext.location` property. A ``LocationPanel`` is intended to be contained within a :class:`.CanvasPanel`, and looks something like this: .. image:: images/locationpanel.png :scale: 50% :align: center By de... | LocationPanel | [
"BSD-3-Clause",
"CC-BY-3.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocationPanel:
"""The ``LocationPanel`` is a panel which contains controls allowing the user to view and modify the :attr:`.DisplayContext.location` property. A ``LocationPanel`` is intended to be contained within a :class:`.CanvasPanel`, and looks something like this: .. image:: images/locationp... | stack_v2_sparse_classes_75kplus_train_068476 | 44,415 | permissive | [
{
"docstring": "Creat a ``LocationPanel``. :arg parent: The :mod:`wx` parent object, assumed to be a :class:`.CanvasPanel`. :arg overlayList: The :class:`.OverlayList` instance. :arg displayCtx: The :class:`.DisplayContext` instance. :arg frame: The :class:`.FSLeyesFrame` instance. :arg showHistory: Defaults to... | 2 | stack_v2_sparse_classes_30k_train_023534 | Implement the Python class `LocationPanel` described below.
Class description:
The ``LocationPanel`` is a panel which contains controls allowing the user to view and modify the :attr:`.DisplayContext.location` property. A ``LocationPanel`` is intended to be contained within a :class:`.CanvasPanel`, and looks something... | Implement the Python class `LocationPanel` described below.
Class description:
The ``LocationPanel`` is a panel which contains controls allowing the user to view and modify the :attr:`.DisplayContext.location` property. A ``LocationPanel`` is intended to be contained within a :class:`.CanvasPanel`, and looks something... | 46ccb4fe2b2346eb57576247f49714032b61307a | <|skeleton|>
class LocationPanel:
"""The ``LocationPanel`` is a panel which contains controls allowing the user to view and modify the :attr:`.DisplayContext.location` property. A ``LocationPanel`` is intended to be contained within a :class:`.CanvasPanel`, and looks something like this: .. image:: images/locationp... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LocationPanel:
"""The ``LocationPanel`` is a panel which contains controls allowing the user to view and modify the :attr:`.DisplayContext.location` property. A ``LocationPanel`` is intended to be contained within a :class:`.CanvasPanel`, and looks something like this: .. image:: images/locationpanel.png :sca... | the_stack_v2_python_sparse | fsleyes/controls/locationpanel.py | sanjayankur31/fsleyes | train | 1 |
a639412340c7c976da22e0ae2f1cb875ddf94df8 | [
"r = Round.query.get(round_id)\nif r is not None:\n return r.json()\nabort(404, 'Unknown round_id')",
"r = Round.query.get(round_id)\nif r is not None:\n if r.deletable():\n c = r.competition\n db.session.delete(r)\n db.session.commit()\n return c.json()\n abort(400, 'Cannot d... | <|body_start_0|>
r = Round.query.get(round_id)
if r is not None:
return r.json()
abort(404, 'Unknown round_id')
<|end_body_0|>
<|body_start_1|>
r = Round.query.get(round_id)
if r is not None:
if r.deletable():
c = r.competition
... | RoundAPISpecific | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoundAPISpecific:
def get(self, round_id):
"""Fetch a specific Round"""
<|body_0|>
def delete(self, round_id):
"""Delete a specific Round"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
r = Round.query.get(round_id)
if r is not None:
... | stack_v2_sparse_classes_75kplus_train_068477 | 25,303 | no_license | [
{
"docstring": "Fetch a specific Round",
"name": "get",
"signature": "def get(self, round_id)"
},
{
"docstring": "Delete a specific Round",
"name": "delete",
"signature": "def delete(self, round_id)"
}
] | 2 | stack_v2_sparse_classes_30k_test_002864 | Implement the Python class `RoundAPISpecific` described below.
Class description:
Implement the RoundAPISpecific class.
Method signatures and docstrings:
- def get(self, round_id): Fetch a specific Round
- def delete(self, round_id): Delete a specific Round | Implement the Python class `RoundAPISpecific` described below.
Class description:
Implement the RoundAPISpecific class.
Method signatures and docstrings:
- def get(self, round_id): Fetch a specific Round
- def delete(self, round_id): Delete a specific Round
<|skeleton|>
class RoundAPISpecific:
def get(self, rou... | 079b109fd13683a31d1d632faa5ab72cf0e78ddf | <|skeleton|>
class RoundAPISpecific:
def get(self, round_id):
"""Fetch a specific Round"""
<|body_0|>
def delete(self, round_id):
"""Delete a specific Round"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RoundAPISpecific:
def get(self, round_id):
"""Fetch a specific Round"""
r = Round.query.get(round_id)
if r is not None:
return r.json()
abort(404, 'Unknown round_id')
def delete(self, round_id):
"""Delete a specific Round"""
r = Round.query.get(... | the_stack_v2_python_sparse | backend/apis/round/apis.py | AlenAlic/DANCE | train | 0 | |
75a54f872b0ca5f5205d49de4190ba6a1fcc5623 | [
"dummy = ListNode(-1)\ndummy.next = head\nnode = dummy\nfor __ in range(m - 1):\n node = node.next\nprev = node.next\ncurr = prev.next\nfor __ in range(n - m):\n next = curr.next\n curr.next = prev\n prev = curr\n curr = next\nnode.next.next = curr\nnode.next = prev\nreturn dummy.next",
"if not hea... | <|body_start_0|>
dummy = ListNode(-1)
dummy.next = head
node = dummy
for __ in range(m - 1):
node = node.next
prev = node.next
curr = prev.next
for __ in range(n - m):
next = curr.next
curr.next = prev
prev = curr
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseBetween(self, head, m, n):
""":type head: ListNode :type m: int :type n: int :rtype: ListNode"""
<|body_0|>
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
du... | stack_v2_sparse_classes_75kplus_train_068478 | 1,022 | no_license | [
{
"docstring": ":type head: ListNode :type m: int :type n: int :rtype: ListNode",
"name": "reverseBetween",
"signature": "def reverseBetween(self, head, m, n)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList",
"signature": "def reverseList(self, head)"
}... | 2 | stack_v2_sparse_classes_30k_train_014933 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseBetween(self, head, m, n): :type head: ListNode :type m: int :type n: int :rtype: ListNode
- def reverseList(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseBetween(self, head, m, n): :type head: ListNode :type m: int :type n: int :rtype: ListNode
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
<|skel... | acf2395f3b946054009d4543f2a13e83402323d3 | <|skeleton|>
class Solution:
def reverseBetween(self, head, m, n):
""":type head: ListNode :type m: int :type n: int :rtype: ListNode"""
<|body_0|>
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reverseBetween(self, head, m, n):
""":type head: ListNode :type m: int :type n: int :rtype: ListNode"""
dummy = ListNode(-1)
dummy.next = head
node = dummy
for __ in range(m - 1):
node = node.next
prev = node.next
curr = prev.ne... | the_stack_v2_python_sparse | Problem_92/learning_solution.py | chenshanghao/LeetCode_learning | train | 0 | |
3a3561f612bfba87a7ad1f869c49ab5ce8dee96a | [
"self.L = data.shape[0]\nself.method = method\nself.data = data\nself.data_list = [data[x, :].tolist() for x in range(data.shape[0])]\nnp.random.seed(random_state)\nself.levels = 11\nself.ccore = True\nself.density_threshold = 0.01\nself.amount_threshold = 3\nself.amount_intervals = 1\nreturn",
"for p in keywords... | <|body_start_0|>
self.L = data.shape[0]
self.method = method
self.data = data
self.data_list = [data[x, :].tolist() for x in range(data.shape[0])]
np.random.seed(random_state)
self.levels = 11
self.ccore = True
self.density_threshold = 0.01
self.am... | All grid based algorithms are implemened here. | GBased | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GBased:
"""All grid based algorithms are implemened here."""
def __init__(self, method, data, random_state=0):
"""Initialize all the parameters. method: Name of the algorithms (lower case joined by underscore) data: Data (2D Matrix) random_state: Random initial state"""
<|bod... | stack_v2_sparse_classes_75kplus_train_068479 | 2,932 | permissive | [
{
"docstring": "Initialize all the parameters. method: Name of the algorithms (lower case joined by underscore) data: Data (2D Matrix) random_state: Random initial state",
"name": "__init__",
"signature": "def __init__(self, method, data, random_state=0)"
},
{
"docstring": "Setup the algorithms"... | 4 | stack_v2_sparse_classes_30k_train_002132 | Implement the Python class `GBased` described below.
Class description:
All grid based algorithms are implemened here.
Method signatures and docstrings:
- def __init__(self, method, data, random_state=0): Initialize all the parameters. method: Name of the algorithms (lower case joined by underscore) data: Data (2D Ma... | Implement the Python class `GBased` described below.
Class description:
All grid based algorithms are implemened here.
Method signatures and docstrings:
- def __init__(self, method, data, random_state=0): Initialize all the parameters. method: Name of the algorithms (lower case joined by underscore) data: Data (2D Ma... | d7427ba609fb7f5e50c26f52364e5e9e118bbc31 | <|skeleton|>
class GBased:
"""All grid based algorithms are implemened here."""
def __init__(self, method, data, random_state=0):
"""Initialize all the parameters. method: Name of the algorithms (lower case joined by underscore) data: Data (2D Matrix) random_state: Random initial state"""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GBased:
"""All grid based algorithms are implemened here."""
def __init__(self, method, data, random_state=0):
"""Initialize all the parameters. method: Name of the algorithms (lower case joined by underscore) data: Data (2D Matrix) random_state: Random initial state"""
self.L = data.shap... | the_stack_v2_python_sparse | sd/algorithms/gridbased.py | shibaji7/SuperDARN-Clustering | train | 1 |
43b1d55b4ef923dd4f1a788cb08bc2b9de3a2371 | [
"if activity.creator == self.current_user:\n return True\nraise ApiException(403, '权限错误')",
"activity = Activity.get_or_404(id=activity_id)\nserializer = ActivitySerializer(instance=activity)\nself.write(serializer.data)",
"activity = Activity.get_or_404(id=activity_id)\nform = self.validated_arguments\nself... | <|body_start_0|>
if activity.creator == self.current_user:
return True
raise ApiException(403, '权限错误')
<|end_body_0|>
<|body_start_1|>
activity = Activity.get_or_404(id=activity_id)
serializer = ActivitySerializer(instance=activity)
self.write(serializer.data)
<|end_... | 活动 object handler | ActivityObjectHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActivityObjectHandler:
"""活动 object handler"""
def has_patch_permission(self, activity):
"""是否具有又该活动的权限 Args: activity: Returns: bool"""
<|body_0|>
def get(self, activity_id):
"""获取活动详情 Args: activity_id: 活动 ID"""
<|body_1|>
def patch(self, activity_... | stack_v2_sparse_classes_75kplus_train_068480 | 24,746 | no_license | [
{
"docstring": "是否具有又该活动的权限 Args: activity: Returns: bool",
"name": "has_patch_permission",
"signature": "def has_patch_permission(self, activity)"
},
{
"docstring": "获取活动详情 Args: activity_id: 活动 ID",
"name": "get",
"signature": "def get(self, activity_id)"
},
{
"docstring": "修改活... | 3 | null | Implement the Python class `ActivityObjectHandler` described below.
Class description:
活动 object handler
Method signatures and docstrings:
- def has_patch_permission(self, activity): 是否具有又该活动的权限 Args: activity: Returns: bool
- def get(self, activity_id): 获取活动详情 Args: activity_id: 活动 ID
- def patch(self, activity_id):... | Implement the Python class `ActivityObjectHandler` described below.
Class description:
活动 object handler
Method signatures and docstrings:
- def has_patch_permission(self, activity): 是否具有又该活动的权限 Args: activity: Returns: bool
- def get(self, activity_id): 获取活动详情 Args: activity_id: 活动 ID
- def patch(self, activity_id):... | 49c31d9cce6ca451ff069697913b33fe55028a46 | <|skeleton|>
class ActivityObjectHandler:
"""活动 object handler"""
def has_patch_permission(self, activity):
"""是否具有又该活动的权限 Args: activity: Returns: bool"""
<|body_0|>
def get(self, activity_id):
"""获取活动详情 Args: activity_id: 活动 ID"""
<|body_1|>
def patch(self, activity_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ActivityObjectHandler:
"""活动 object handler"""
def has_patch_permission(self, activity):
"""是否具有又该活动的权限 Args: activity: Returns: bool"""
if activity.creator == self.current_user:
return True
raise ApiException(403, '权限错误')
def get(self, activity_id):
"""获取... | the_stack_v2_python_sparse | PaiDuiGuanJia/yiyun/handlers/rest/activity.py | haoweiking/image_tesseract_private | train | 0 |
1fff5836adaabc5434a045f4b7c8399d072072cc | [
"citations.sort()\ni = 0\nwhile i < len(citations) and citations[len(citations) - 1 - i] > i:\n i += 1\nreturn i",
"n = len(citations)\npapers = [0] * (n + 1)\nfor c in citations:\n papers[min(n, c)] += 1\nk = n\ns = papers[n]\nwhile k > s:\n k -= 1\n s += papers[k]\nreturn k"
] | <|body_start_0|>
citations.sort()
i = 0
while i < len(citations) and citations[len(citations) - 1 - i] > i:
i += 1
return i
<|end_body_0|>
<|body_start_1|>
n = len(citations)
papers = [0] * (n + 1)
for c in citations:
papers[min(n, c)] += ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hIndex(self, citations):
"""offical solution: https://leetcode.com/problems/h-index/solution/ o(nlogn),o(1) :type citations: List[int] :rtype: int"""
<|body_0|>
def hIndex2(self, citations):
"""o(n) o(n) :param citations: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_068481 | 1,600 | no_license | [
{
"docstring": "offical solution: https://leetcode.com/problems/h-index/solution/ o(nlogn),o(1) :type citations: List[int] :rtype: int",
"name": "hIndex",
"signature": "def hIndex(self, citations)"
},
{
"docstring": "o(n) o(n) :param citations: :return:",
"name": "hIndex2",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_010717 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hIndex(self, citations): offical solution: https://leetcode.com/problems/h-index/solution/ o(nlogn),o(1) :type citations: List[int] :rtype: int
- def hIndex2(self, citations)... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hIndex(self, citations): offical solution: https://leetcode.com/problems/h-index/solution/ o(nlogn),o(1) :type citations: List[int] :rtype: int
- def hIndex2(self, citations)... | 2526f8c0dec7101123123740e146ee4081e979ee | <|skeleton|>
class Solution:
def hIndex(self, citations):
"""offical solution: https://leetcode.com/problems/h-index/solution/ o(nlogn),o(1) :type citations: List[int] :rtype: int"""
<|body_0|>
def hIndex2(self, citations):
"""o(n) o(n) :param citations: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def hIndex(self, citations):
"""offical solution: https://leetcode.com/problems/h-index/solution/ o(nlogn),o(1) :type citations: List[int] :rtype: int"""
citations.sort()
i = 0
while i < len(citations) and citations[len(citations) - 1 - i] > i:
i += 1
... | the_stack_v2_python_sparse | 274. H-Index.py | zhangpengGenedock/leetcode_python | train | 1 | |
0e2229b616d9f49e9080b271842340ed4c456852 | [
"b = x.max(axis=1, keepdims=True)\ny = np.exp(x - b)\nout = y / y.sum(axis=1, keepdims=True)\nself.out = out\nreturn out",
"x = self.out\nbatch, features = x.shape\nidxs = np.arange(features)\nshape = (batch, features, features)\ndiagonal = np.zeros(shape)\ndiagonal[:, idxs, idxs] = x\ndxdtx = diagonal - np.einsu... | <|body_start_0|>
b = x.max(axis=1, keepdims=True)
y = np.exp(x - b)
out = y / y.sum(axis=1, keepdims=True)
self.out = out
return out
<|end_body_0|>
<|body_start_1|>
x = self.out
batch, features = x.shape
idxs = np.arange(features)
shape = (batch, ... | Softmax activation module. | SoftMaxModule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SoftMaxModule:
"""Softmax activation module."""
def forward(self, x):
"""Forward pass. Args: x: input to the module Returns: out: output of the module"""
<|body_0|>
def backward(self, dout):
"""Backward pass. Args: dout: gradients of the previous modul Returns: d... | stack_v2_sparse_classes_75kplus_train_068482 | 5,181 | no_license | [
{
"docstring": "Forward pass. Args: x: input to the module Returns: out: output of the module",
"name": "forward",
"signature": "def forward(self, x)"
},
{
"docstring": "Backward pass. Args: dout: gradients of the previous modul Returns: dx: gradients with respect to the input of the module",
... | 2 | stack_v2_sparse_classes_30k_train_033405 | Implement the Python class `SoftMaxModule` described below.
Class description:
Softmax activation module.
Method signatures and docstrings:
- def forward(self, x): Forward pass. Args: x: input to the module Returns: out: output of the module
- def backward(self, dout): Backward pass. Args: dout: gradients of the prev... | Implement the Python class `SoftMaxModule` described below.
Class description:
Softmax activation module.
Method signatures and docstrings:
- def forward(self, x): Forward pass. Args: x: input to the module Returns: out: output of the module
- def backward(self, dout): Backward pass. Args: dout: gradients of the prev... | b2cd0d67337b101f3e204e519625e1aaf3cea43b | <|skeleton|>
class SoftMaxModule:
"""Softmax activation module."""
def forward(self, x):
"""Forward pass. Args: x: input to the module Returns: out: output of the module"""
<|body_0|>
def backward(self, dout):
"""Backward pass. Args: dout: gradients of the previous modul Returns: d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SoftMaxModule:
"""Softmax activation module."""
def forward(self, x):
"""Forward pass. Args: x: input to the module Returns: out: output of the module"""
b = x.max(axis=1, keepdims=True)
y = np.exp(x - b)
out = y / y.sum(axis=1, keepdims=True)
self.out = out
... | the_stack_v2_python_sparse | assignment_1/code/modules.py | Ivan-Yovchev/uvadlc_practicals_2019 | train | 0 |
0e94a289e58b0a482b98a3e90e58a74ef970597d | [
"result = self.plugin.weighted_mean(self.cube, self.weights1d)\nexpected = np.full((2, 2), 1.5)\nself.assertIsInstance(result, iris.cube.Cube)\nself.assertArrayAlmostEqual(result.data, expected)",
"result = self.plugin.weighted_mean(self.cube, self.weights3d)\nexpected = np.array([[2.7, 2.1], [2.4, 1.8]])\nself.a... | <|body_start_0|>
result = self.plugin.weighted_mean(self.cube, self.weights1d)
expected = np.full((2, 2), 1.5)
self.assertIsInstance(result, iris.cube.Cube)
self.assertArrayAlmostEqual(result.data, expected)
<|end_body_0|>
<|body_start_1|>
result = self.plugin.weighted_mean(self... | Test the weighted_mean function. | Test_weighted_mean | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_weighted_mean:
"""Test the weighted_mean function."""
def test_with_weights(self):
"""Test function when a data cube and a weights cube are provided."""
<|body_0|>
def test_with_spatially_varying_weights(self):
"""Test function when a data cube and a multi d... | stack_v2_sparse_classes_75kplus_train_068483 | 23,864 | permissive | [
{
"docstring": "Test function when a data cube and a weights cube are provided.",
"name": "test_with_weights",
"signature": "def test_with_weights(self)"
},
{
"docstring": "Test function when a data cube and a multi dimensional weights cube are provided. This tests spatially varying weights, whe... | 4 | stack_v2_sparse_classes_30k_train_046590 | Implement the Python class `Test_weighted_mean` described below.
Class description:
Test the weighted_mean function.
Method signatures and docstrings:
- def test_with_weights(self): Test function when a data cube and a weights cube are provided.
- def test_with_spatially_varying_weights(self): Test function when a da... | Implement the Python class `Test_weighted_mean` described below.
Class description:
Test the weighted_mean function.
Method signatures and docstrings:
- def test_with_weights(self): Test function when a data cube and a weights cube are provided.
- def test_with_spatially_varying_weights(self): Test function when a da... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_weighted_mean:
"""Test the weighted_mean function."""
def test_with_weights(self):
"""Test function when a data cube and a weights cube are provided."""
<|body_0|>
def test_with_spatially_varying_weights(self):
"""Test function when a data cube and a multi d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_weighted_mean:
"""Test the weighted_mean function."""
def test_with_weights(self):
"""Test function when a data cube and a weights cube are provided."""
result = self.plugin.weighted_mean(self.cube, self.weights1d)
expected = np.full((2, 2), 1.5)
self.assertIsInstance... | the_stack_v2_python_sparse | improver_tests/blending/weighted_blend/test_WeightedBlendAcrossWholeDimension.py | metoppv/improver | train | 101 |
f7c0618e8b1af213f6594ad1a6496f5de699e589 | [
"height_points = np.array([5.0, 10.0, 20.0])\ncube = _set_up_height_cube(height_points)\nself.plugin_positive = Integration('height', positive_integration=True)\nself.plugin_positive.input_cube = cube.copy()\nself.plugin_negative = Integration('height')\nself.plugin_negative.input_cube = cube.copy()",
"result = s... | <|body_start_0|>
height_points = np.array([5.0, 10.0, 20.0])
cube = _set_up_height_cube(height_points)
self.plugin_positive = Integration('height', positive_integration=True)
self.plugin_positive.input_cube = cube.copy()
self.plugin_negative = Integration('height')
self.p... | Test the prepare_for_integration method. | Test_prepare_for_integration | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_prepare_for_integration:
"""Test the prepare_for_integration method."""
def setUp(self):
"""Set up the cube."""
<|body_0|>
def test_basic(self):
"""Test that the type of the returned value is as expected and the expected number of items are returned."""
... | stack_v2_sparse_classes_75kplus_train_068484 | 25,011 | permissive | [
{
"docstring": "Set up the cube.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test that the type of the returned value is as expected and the expected number of items are returned.",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring... | 4 | stack_v2_sparse_classes_30k_train_033211 | Implement the Python class `Test_prepare_for_integration` described below.
Class description:
Test the prepare_for_integration method.
Method signatures and docstrings:
- def setUp(self): Set up the cube.
- def test_basic(self): Test that the type of the returned value is as expected and the expected number of items ... | Implement the Python class `Test_prepare_for_integration` described below.
Class description:
Test the prepare_for_integration method.
Method signatures and docstrings:
- def setUp(self): Set up the cube.
- def test_basic(self): Test that the type of the returned value is as expected and the expected number of items ... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_prepare_for_integration:
"""Test the prepare_for_integration method."""
def setUp(self):
"""Set up the cube."""
<|body_0|>
def test_basic(self):
"""Test that the type of the returned value is as expected and the expected number of items are returned."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_prepare_for_integration:
"""Test the prepare_for_integration method."""
def setUp(self):
"""Set up the cube."""
height_points = np.array([5.0, 10.0, 20.0])
cube = _set_up_height_cube(height_points)
self.plugin_positive = Integration('height', positive_integration=True... | the_stack_v2_python_sparse | improver_tests/utilities/test_mathematical_operations.py | metoppv/improver | train | 101 |
0bd24d04ee281b3ab80a925e0270c4aa7750a7ba | [
"if user_id:\n return f'{console_url}/api/3/users/{user_id}'\nelse:\n return f'{console_url}/api/3/users'",
"if asset_group_id:\n return f'{console_url}/api/3/users/{user_id}/asset_groups/{asset_group_id}'\nelse:\n return f'{console_url}/api/3/users/{user_id}/asset_groups'",
"if site_id:\n return... | <|body_start_0|>
if user_id:
return f'{console_url}/api/3/users/{user_id}'
else:
return f'{console_url}/api/3/users'
<|end_body_0|>
<|body_start_1|>
if asset_group_id:
return f'{console_url}/api/3/users/{user_id}/asset_groups/{asset_group_id}'
else:
... | User | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class User:
def users(console_url, user_id=None):
"""Interacts with users endpoint :param console_url: URL to the InsightVM console :param user_id: ID of the user with which to interact :return: pre-populated /api/3/users endpoint"""
<|body_0|>
def user_asset_groups(console_url, u... | stack_v2_sparse_classes_75kplus_train_068485 | 22,639 | permissive | [
{
"docstring": "Interacts with users endpoint :param console_url: URL to the InsightVM console :param user_id: ID of the user with which to interact :return: pre-populated /api/3/users endpoint",
"name": "users",
"signature": "def users(console_url, user_id=None)"
},
{
"docstring": "Interacts wi... | 3 | null | Implement the Python class `User` described below.
Class description:
Implement the User class.
Method signatures and docstrings:
- def users(console_url, user_id=None): Interacts with users endpoint :param console_url: URL to the InsightVM console :param user_id: ID of the user with which to interact :return: pre-po... | Implement the Python class `User` described below.
Class description:
Implement the User class.
Method signatures and docstrings:
- def users(console_url, user_id=None): Interacts with users endpoint :param console_url: URL to the InsightVM console :param user_id: ID of the user with which to interact :return: pre-po... | 718d15ca36c57231bb89df0aebc53d0210db400c | <|skeleton|>
class User:
def users(console_url, user_id=None):
"""Interacts with users endpoint :param console_url: URL to the InsightVM console :param user_id: ID of the user with which to interact :return: pre-populated /api/3/users endpoint"""
<|body_0|>
def user_asset_groups(console_url, u... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class User:
def users(console_url, user_id=None):
"""Interacts with users endpoint :param console_url: URL to the InsightVM console :param user_id: ID of the user with which to interact :return: pre-populated /api/3/users endpoint"""
if user_id:
return f'{console_url}/api/3/users/{user_i... | the_stack_v2_python_sparse | plugins/rapid7_insightvm/komand_rapid7_insightvm/util/endpoints.py | rapid7/insightconnect-plugins | train | 61 | |
28ebc1f0afe528a5f6321a0b2496465dda18e7ff | [
"if post.get('Body', False) and post.get('From', False):\n message_type = 'sms'\n if 'whatsapp' in post.get('From'):\n message_type = 'whatsapp'\n params_sms_id = {'body': post.get('Body'), 'number': helpers.sanitize_mobile(post.get('From')), 'message_type': message_type, 'message_id': post.get('Sms... | <|body_start_0|>
if post.get('Body', False) and post.get('From', False):
message_type = 'sms'
if 'whatsapp' in post.get('From'):
message_type = 'whatsapp'
params_sms_id = {'body': post.get('Body'), 'number': helpers.sanitize_mobile(post.get('From')), 'message_... | TwilioWebhooks | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwilioWebhooks:
def twilio_input_message(self, **post):
"""Webhoock para receber mensagens do whatsapp sandbox https://www.twilio.com/console/sms/whatsapp/sandbox POST from Twilio: { 'SmsMessageSid': 'SMe8f1366da573cdc95485b7d1143ff1ef', 'NumMedia': '0', 'SmsSid': 'SMe8f1366da573cdc95485... | stack_v2_sparse_classes_75kplus_train_068486 | 3,535 | no_license | [
{
"docstring": "Webhoock para receber mensagens do whatsapp sandbox https://www.twilio.com/console/sms/whatsapp/sandbox POST from Twilio: { 'SmsMessageSid': 'SMe8f1366da573cdc95485b7d1143ff1ef', 'NumMedia': '0', 'SmsSid': 'SMe8f1366da573cdc95485b7d1143ff1ef', 'SmsStatus': 'received', 'Body': 'Corpo da mensagem'... | 2 | stack_v2_sparse_classes_30k_train_012384 | Implement the Python class `TwilioWebhooks` described below.
Class description:
Implement the TwilioWebhooks class.
Method signatures and docstrings:
- def twilio_input_message(self, **post): Webhoock para receber mensagens do whatsapp sandbox https://www.twilio.com/console/sms/whatsapp/sandbox POST from Twilio: { 'S... | Implement the Python class `TwilioWebhooks` described below.
Class description:
Implement the TwilioWebhooks class.
Method signatures and docstrings:
- def twilio_input_message(self, **post): Webhoock para receber mensagens do whatsapp sandbox https://www.twilio.com/console/sms/whatsapp/sandbox POST from Twilio: { 'S... | 68019d063765508e8de00466f2dd5909a9d0b304 | <|skeleton|>
class TwilioWebhooks:
def twilio_input_message(self, **post):
"""Webhoock para receber mensagens do whatsapp sandbox https://www.twilio.com/console/sms/whatsapp/sandbox POST from Twilio: { 'SmsMessageSid': 'SMe8f1366da573cdc95485b7d1143ff1ef', 'NumMedia': '0', 'SmsSid': 'SMe8f1366da573cdc95485... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TwilioWebhooks:
def twilio_input_message(self, **post):
"""Webhoock para receber mensagens do whatsapp sandbox https://www.twilio.com/console/sms/whatsapp/sandbox POST from Twilio: { 'SmsMessageSid': 'SMe8f1366da573cdc95485b7d1143ff1ef', 'NumMedia': '0', 'SmsSid': 'SMe8f1366da573cdc95485b7d1143ff1ef',... | the_stack_v2_python_sparse | sms_twilio/controllers/sms_api_input.py | marcelsavegnago/social | train | 0 | |
271522da66065e77ba710d952907f78a75fc3536 | [
"if not nums:\n return 0\ncum_sum = [0]\nfor num in nums:\n cum_sum.append(cum_sum[-1] + num)\nres = 0\nfor i in range(len(cum_sum) - 1):\n for j in range(i + 1, len(cum_sum)):\n if cum_sum[j] - cum_sum[i] == k:\n res += 1\nreturn res",
"if not nums:\n return 0\ncounts_map = {0: 1}\n... | <|body_start_0|>
if not nums:
return 0
cum_sum = [0]
for num in nums:
cum_sum.append(cum_sum[-1] + num)
res = 0
for i in range(len(cum_sum) - 1):
for j in range(i + 1, len(cum_sum)):
if cum_sum[j] - cum_sum[i] == k:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subarray_sum(self, nums: List[int], k: int) -> int:
"""Time complexity O(n**2). Although this is faster than O(n**3) solution (brutal force without cumulative array), it is still not fast enough to pass the test."""
<|body_0|>
def subarray_sum_hash_map(self, nu... | stack_v2_sparse_classes_75kplus_train_068487 | 1,152 | no_license | [
{
"docstring": "Time complexity O(n**2). Although this is faster than O(n**3) solution (brutal force without cumulative array), it is still not fast enough to pass the test.",
"name": "subarray_sum",
"signature": "def subarray_sum(self, nums: List[int], k: int) -> int"
},
{
"docstring": "O(n) so... | 2 | stack_v2_sparse_classes_30k_train_054135 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subarray_sum(self, nums: List[int], k: int) -> int: Time complexity O(n**2). Although this is faster than O(n**3) solution (brutal force without cumulative array), it is stil... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subarray_sum(self, nums: List[int], k: int) -> int: Time complexity O(n**2). Although this is faster than O(n**3) solution (brutal force without cumulative array), it is stil... | 5625e6396b746255f3343253c75447ead95879c7 | <|skeleton|>
class Solution:
def subarray_sum(self, nums: List[int], k: int) -> int:
"""Time complexity O(n**2). Although this is faster than O(n**3) solution (brutal force without cumulative array), it is still not fast enough to pass the test."""
<|body_0|>
def subarray_sum_hash_map(self, nu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def subarray_sum(self, nums: List[int], k: int) -> int:
"""Time complexity O(n**2). Although this is faster than O(n**3) solution (brutal force without cumulative array), it is still not fast enough to pass the test."""
if not nums:
return 0
cum_sum = [0]
... | the_stack_v2_python_sparse | 560_subarray_sum_equals_k/solution.py | FluffyFu/Leetcode | train | 0 | |
292f5a957a9579b79672c2bc95ae1e6ddd34a533 | [
"self.x = length\nself.y = width\nself.z = height\nself.GraphList = []",
"graph = nx.grid_graph([self.x, self.y, self.z])\nfor edge in self.GraphList:\n graph.add_edge(edge[0], edge[1])\nif graph_layout == 'spring':\n graph_pos = nx.spring_layout(graph)\nelif graph_layout == 'spectral':\n graph_pos = nx.... | <|body_start_0|>
self.x = length
self.y = width
self.z = height
self.GraphList = []
<|end_body_0|>
<|body_start_1|>
graph = nx.grid_graph([self.x, self.y, self.z])
for edge in self.GraphList:
graph.add_edge(edge[0], edge[1])
if graph_layout == 'spring... | LatticeGraphics | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LatticeGraphics:
def __init__(self, length, width, height):
"""Creates a CayleyTree object in order to create an image of the graph."""
<|body_0|>
def drawLattice(self, labels=None, graph_layout='spring', node_size=1000, node_color='blue', node_alpha=0.3, node_text_size=12, ... | stack_v2_sparse_classes_75kplus_train_068488 | 3,101 | permissive | [
{
"docstring": "Creates a CayleyTree object in order to create an image of the graph.",
"name": "__init__",
"signature": "def __init__(self, length, width, height)"
},
{
"docstring": "Method that physically draws the lattice graph based on length, width, and height.",
"name": "drawLattice",
... | 2 | stack_v2_sparse_classes_30k_val_000930 | Implement the Python class `LatticeGraphics` described below.
Class description:
Implement the LatticeGraphics class.
Method signatures and docstrings:
- def __init__(self, length, width, height): Creates a CayleyTree object in order to create an image of the graph.
- def drawLattice(self, labels=None, graph_layout='... | Implement the Python class `LatticeGraphics` described below.
Class description:
Implement the LatticeGraphics class.
Method signatures and docstrings:
- def __init__(self, length, width, height): Creates a CayleyTree object in order to create an image of the graph.
- def drawLattice(self, labels=None, graph_layout='... | dbd60c6fa04f00aa995094acc76ef0d06a0346b1 | <|skeleton|>
class LatticeGraphics:
def __init__(self, length, width, height):
"""Creates a CayleyTree object in order to create an image of the graph."""
<|body_0|>
def drawLattice(self, labels=None, graph_layout='spring', node_size=1000, node_color='blue', node_alpha=0.3, node_text_size=12, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LatticeGraphics:
def __init__(self, length, width, height):
"""Creates a CayleyTree object in order to create an image of the graph."""
self.x = length
self.y = width
self.z = height
self.GraphList = []
def drawLattice(self, labels=None, graph_layout='spring', node... | the_stack_v2_python_sparse | graphics/latticegraphics.py | noe98/Cayley | train | 5 | |
1fb39bc8c5b7e308817e17e1e760f2286a5a6b8f | [
"length = len(heights)\nstack = []\nrect_map = collections.OrderedDict()\nfor i, item in enumerate(heights):\n stack = [inum for inum in stack if inum[1] < item]\n rect_map[i, item] = {}\n if not stack:\n rect_map[i, item]['left'] = -1\n else:\n rect_map[i, item]['left'] = stack[-1][0]\n ... | <|body_start_0|>
length = len(heights)
stack = []
rect_map = collections.OrderedDict()
for i, item in enumerate(heights):
stack = [inum for inum in stack if inum[1] < item]
rect_map[i, item] = {}
if not stack:
rect_map[i, item]['left'] ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
"""*** TLE *** for each height, find the closest height that is less than it on both left and right side. A dictionary to map current height with the index of left closest smaller height and right closest smaller height. map[cur_height] ... | stack_v2_sparse_classes_75kplus_train_068489 | 2,818 | no_license | [
{
"docstring": "*** TLE *** for each height, find the closest height that is less than it on both left and right side. A dictionary to map current height with the index of left closest smaller height and right closest smaller height. map[cur_height] = {\"left\":i, \"right\":j} use a stack to update the store he... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): *** TLE *** for each height, find the closest height that is less than it on both left and right side. A dictionary to map current height... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): *** TLE *** for each height, find the closest height that is less than it on both left and right side. A dictionary to map current height... | 49d0831387227e69ae4067c1f5b7e828976377b4 | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
"""*** TLE *** for each height, find the closest height that is less than it on both left and right side. A dictionary to map current height with the index of left closest smaller height and right closest smaller height. map[cur_height] ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def largestRectangleArea(self, heights):
"""*** TLE *** for each height, find the closest height that is less than it on both left and right side. A dictionary to map current height with the index of left closest smaller height and right closest smaller height. map[cur_height] = {"left":i, "... | the_stack_v2_python_sparse | DataStructure/84_largest_rectangle_in_histogram.py | libinjungle/LeetCode_Python | train | 0 | |
0bb88da0966acdc0d54d431f09621cc8ae9bfde6 | [
"assert stage in ('normalizer', 'converter', 'keywords'), \"stage should be 'normalizer'/'converter'/'keywords'\"\nfrom Utilities.movoto.logger import MLogger\nself._failures_logger = MLogger().getLogger('log_null_values_{stage}_{mls_id}'.format(stage=stage, mls_id=mls_id), mls_id)\nreturn self._failures_logger",
... | <|body_start_0|>
assert stage in ('normalizer', 'converter', 'keywords'), "stage should be 'normalizer'/'converter'/'keywords'"
from Utilities.movoto.logger import MLogger
self._failures_logger = MLogger().getLogger('log_null_values_{stage}_{mls_id}'.format(stage=stage, mls_id=mls_id), mls_id)
... | MLS mapping failure logs Accroding to DATA-1531 Usage: :: opt.setup_failure_logger(stage, mls_id) opt.record_failure_log(mls_sysid, mls_number, column_name, column_value, exc_info) # will record log to ``log_null_values_{stage}_{mls_id}.log`` | ConvertFailureLog | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvertFailureLog:
"""MLS mapping failure logs Accroding to DATA-1531 Usage: :: opt.setup_failure_logger(stage, mls_id) opt.record_failure_log(mls_sysid, mls_number, column_name, column_value, exc_info) # will record log to ``log_null_values_{stage}_{mls_id}.log``"""
def setup_failure_logger... | stack_v2_sparse_classes_75kplus_train_068490 | 3,064 | permissive | [
{
"docstring": "Setup failures logger Args: stage (str): normalizer/converter/keywords mls_id (int): Returns: logger: the failure logger",
"name": "setup_failure_logger",
"signature": "def setup_failure_logger(self, stage, mls_id)"
},
{
"docstring": "Format arguments to log message Args: mls_sys... | 3 | stack_v2_sparse_classes_30k_train_014107 | Implement the Python class `ConvertFailureLog` described below.
Class description:
MLS mapping failure logs Accroding to DATA-1531 Usage: :: opt.setup_failure_logger(stage, mls_id) opt.record_failure_log(mls_sysid, mls_number, column_name, column_value, exc_info) # will record log to ``log_null_values_{stage}_{mls_id}... | Implement the Python class `ConvertFailureLog` described below.
Class description:
MLS mapping failure logs Accroding to DATA-1531 Usage: :: opt.setup_failure_logger(stage, mls_id) opt.record_failure_log(mls_sysid, mls_number, column_name, column_value, exc_info) # will record log to ``log_null_values_{stage}_{mls_id}... | 9d0ef176629f18a4fd52bc2ef25e019f7be4317c | <|skeleton|>
class ConvertFailureLog:
"""MLS mapping failure logs Accroding to DATA-1531 Usage: :: opt.setup_failure_logger(stage, mls_id) opt.record_failure_log(mls_sysid, mls_number, column_name, column_value, exc_info) # will record log to ``log_null_values_{stage}_{mls_id}.log``"""
def setup_failure_logger... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConvertFailureLog:
"""MLS mapping failure logs Accroding to DATA-1531 Usage: :: opt.setup_failure_logger(stage, mls_id) opt.record_failure_log(mls_sysid, mls_number, column_name, column_value, exc_info) # will record log to ``log_null_values_{stage}_{mls_id}.log``"""
def setup_failure_logger(self, stage,... | the_stack_v2_python_sparse | kipp/options/mlogger.py | gladuo/kipp | train | 0 |
001912067a0907aa4f306a28c4582b3ceb3ad172 | [
"self.type = type\nself.concat_properties = concat_properties\nself.is_concat = bool(concat_properties)\nself.is_static = is_static\nself.is_state = is_state\nself.is_identity = is_identity",
"tests = [self.is_static, self.is_state, self.is_identity]\npositives = [t for t in tests if t]\nreturn len(positives) == ... | <|body_start_0|>
self.type = type
self.concat_properties = concat_properties
self.is_concat = bool(concat_properties)
self.is_static = is_static
self.is_state = is_state
self.is_identity = is_identity
<|end_body_0|>
<|body_start_1|>
tests = [self.is_static, self.... | Convenience class to keep track of properties in a model. | VersionedProperty | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VersionedProperty:
"""Convenience class to keep track of properties in a model."""
def __init__(self, type=str, concat_properties=None, is_static=False, is_state=False, is_identity=False):
"""Init the property. A property should be only one of is_static, is_state, or is_identity :par... | stack_v2_sparse_classes_75kplus_train_068491 | 18,798 | permissive | [
{
"docstring": "Init the property. A property should be only one of is_static, is_state, or is_identity :param type: Expected type of value for this property. :type type: Class :param concat_fields: List of fields that this property is composed of :type concast_fields: list :param is_static: Is this property a ... | 2 | null | Implement the Python class `VersionedProperty` described below.
Class description:
Convenience class to keep track of properties in a model.
Method signatures and docstrings:
- def __init__(self, type=str, concat_properties=None, is_static=False, is_state=False, is_identity=False): Init the property. A property shoul... | Implement the Python class `VersionedProperty` described below.
Class description:
Convenience class to keep track of properties in a model.
Method signatures and docstrings:
- def __init__(self, type=str, concat_properties=None, is_static=False, is_state=False, is_identity=False): Init the property. A property shoul... | aaab76706c8268d3ff3e87c275baee9dd4714314 | <|skeleton|>
class VersionedProperty:
"""Convenience class to keep track of properties in a model."""
def __init__(self, type=str, concat_properties=None, is_static=False, is_state=False, is_identity=False):
"""Init the property. A property should be only one of is_static, is_state, or is_identity :par... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VersionedProperty:
"""Convenience class to keep track of properties in a model."""
def __init__(self, type=str, concat_properties=None, is_static=False, is_state=False, is_identity=False):
"""Init the property. A property should be only one of is_static, is_state, or is_identity :param type: Expe... | the_stack_v2_python_sparse | cloud_snitch/models/base.py | rcbops/FleetDeploymentReporting | train | 1 |
abe8d3058ece639f5e75f8f22e0649d94d1399a5 | [
"import numpy as np\nself.positions = np.array(positions)\nself.position_value = 1000 / self.positions\nself.num_trials = num_trials",
"import numpy as np\np = 0.51\ncumu_ret = []\nfor i, position in enumerate(self.positions):\n position_return = 2 * self.position_value[i] * np.random.binomial(position, p)\n ... | <|body_start_0|>
import numpy as np
self.positions = np.array(positions)
self.position_value = 1000 / self.positions
self.num_trials = num_trials
<|end_body_0|>
<|body_start_1|>
import numpy as np
p = 0.51
cumu_ret = []
for i, position in enumerate(self.p... | Class represents a string of $1000 investments and their daily returns | investment | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class investment:
"""Class represents a string of $1000 investments and their daily returns"""
def __init__(self, positions=[1], num_trials=1):
"""Constructor for interval class inputs: positions: A list of integers of number of shares to buy. Each entry must be a factor of 1000. num_trial... | stack_v2_sparse_classes_75kplus_train_068492 | 1,980 | no_license | [
{
"docstring": "Constructor for interval class inputs: positions: A list of integers of number of shares to buy. Each entry must be a factor of 1000. num_trials: An integer representing the number of days to simulate investment",
"name": "__init__",
"signature": "def __init__(self, positions=[1], num_tr... | 3 | stack_v2_sparse_classes_30k_train_005910 | Implement the Python class `investment` described below.
Class description:
Class represents a string of $1000 investments and their daily returns
Method signatures and docstrings:
- def __init__(self, positions=[1], num_trials=1): Constructor for interval class inputs: positions: A list of integers of number of shar... | Implement the Python class `investment` described below.
Class description:
Class represents a string of $1000 investments and their daily returns
Method signatures and docstrings:
- def __init__(self, positions=[1], num_trials=1): Constructor for interval class inputs: positions: A list of integers of number of shar... | 5b904060e8bced7f91547ad7f7819773a7450a1e | <|skeleton|>
class investment:
"""Class represents a string of $1000 investments and their daily returns"""
def __init__(self, positions=[1], num_trials=1):
"""Constructor for interval class inputs: positions: A list of integers of number of shares to buy. Each entry must be a factor of 1000. num_trial... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class investment:
"""Class represents a string of $1000 investments and their daily returns"""
def __init__(self, positions=[1], num_trials=1):
"""Constructor for interval class inputs: positions: A list of integers of number of shares to buy. Each entry must be a factor of 1000. num_trials: An integer... | the_stack_v2_python_sparse | jt2276/investment_package/investment.py | ds-ga-1007/assignment8 | train | 1 |
128ef5d80c9748b0e88f2b4bdd1bfcbfefcefd1f | [
"self.db = SqliteDB()\nself.code_list = []\nself.data = self.get_data()\nself.data_for_table = {}",
"with self.db as cur:\n cur.execute('SELECT * FROM salaries')\nreturn cur.fetchall()",
"for string in self.data:\n if string[1] not in self.code_list:\n self.code_list.append(string[1])\nfor i in sel... | <|body_start_0|>
self.db = SqliteDB()
self.code_list = []
self.data = self.get_data()
self.data_for_table = {}
<|end_body_0|>
<|body_start_1|>
with self.db as cur:
cur.execute('SELECT * FROM salaries')
return cur.fetchall()
<|end_body_1|>
<|body_start_2|>
... | Класс, рассчитывающий общую численность персонала по категориям | PersonelSummary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersonelSummary:
"""Класс, рассчитывающий общую численность персонала по категориям"""
def __init__(self) -> None:
"""Метод инициализации класса"""
<|body_0|>
def get_data(self) -> tuple:
"""Метод, получающий из БД данные о всех записях :return: self.cur.fetchall... | stack_v2_sparse_classes_75kplus_train_068493 | 3,002 | no_license | [
{
"docstring": "Метод инициализации класса",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Метод, получающий из БД данные о всех записях :return: self.cur.fetchall() - список с результами запроса",
"name": "get_data",
"signature": "def get_data(self) ->... | 4 | stack_v2_sparse_classes_30k_train_010031 | Implement the Python class `PersonelSummary` described below.
Class description:
Класс, рассчитывающий общую численность персонала по категориям
Method signatures and docstrings:
- def __init__(self) -> None: Метод инициализации класса
- def get_data(self) -> tuple: Метод, получающий из БД данные о всех записях :retu... | Implement the Python class `PersonelSummary` described below.
Class description:
Класс, рассчитывающий общую численность персонала по категориям
Method signatures and docstrings:
- def __init__(self) -> None: Метод инициализации класса
- def get_data(self) -> tuple: Метод, получающий из БД данные о всех записях :retu... | f63d5db6780cc02cb064e70d2076eba94cb45785 | <|skeleton|>
class PersonelSummary:
"""Класс, рассчитывающий общую численность персонала по категориям"""
def __init__(self) -> None:
"""Метод инициализации класса"""
<|body_0|>
def get_data(self) -> tuple:
"""Метод, получающий из БД данные о всех записях :return: self.cur.fetchall... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PersonelSummary:
"""Класс, рассчитывающий общую численность персонала по категориям"""
def __init__(self) -> None:
"""Метод инициализации класса"""
self.db = SqliteDB()
self.code_list = []
self.data = self.get_data()
self.data_for_table = {}
def get_data(self)... | the_stack_v2_python_sparse | counting/personel_summary.py | Pheeneek/Salary | train | 0 |
8dc18a314224c615306e6e0f8b3b93d9062d961f | [
"client = LdapClient({'ldap_server_vendor': 'OpenLDAP', 'host': 'server_ip', 'connection_type': 'SSL', 'ssl_version': ssl_version})\nssl_version_value = client._get_ssl_version()\nassert ssl_version_value == expected_ssl_version",
"client = LdapClient({'ldap_server_vendor': 'OpenLDAP', 'host': 'server_ip', 'conne... | <|body_start_0|>
client = LdapClient({'ldap_server_vendor': 'OpenLDAP', 'host': 'server_ip', 'connection_type': 'SSL', 'ssl_version': ssl_version})
ssl_version_value = client._get_ssl_version()
assert ssl_version_value == expected_ssl_version
<|end_body_0|>
<|body_start_1|>
client = Lda... | Contains unit tests for general functions that deal with both OpenLDAP and Active Directory servers. | TestLDAPAuthentication | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestLDAPAuthentication:
"""Contains unit tests for general functions that deal with both OpenLDAP and Active Directory servers."""
def test_get_ssl_version(self, ssl_version, expected_ssl_version):
"""Given: - An ssl protocol version: 1. TLS 2. TLSv1 3. TLSv1_1 4. TLSv1_2 5. TLS_CLIE... | stack_v2_sparse_classes_75kplus_train_068494 | 12,670 | permissive | [
{
"docstring": "Given: - An ssl protocol version: 1. TLS 2. TLSv1 3. TLSv1_1 4. TLSv1_2 5. TLS_CLIENT 6. None 7. 'None' When: - Running the '_get_ssl_version()' function. Then: - Verify that the returned ssl version value is as expected: 1. TLS - 2 2. TLSv1 - 3 3. TLSv1_1 - 4 4. TLSv1_2 - 5 5. TLS_CLIENT - 16 6... | 3 | stack_v2_sparse_classes_30k_train_006255 | Implement the Python class `TestLDAPAuthentication` described below.
Class description:
Contains unit tests for general functions that deal with both OpenLDAP and Active Directory servers.
Method signatures and docstrings:
- def test_get_ssl_version(self, ssl_version, expected_ssl_version): Given: - An ssl protocol v... | Implement the Python class `TestLDAPAuthentication` described below.
Class description:
Contains unit tests for general functions that deal with both OpenLDAP and Active Directory servers.
Method signatures and docstrings:
- def test_get_ssl_version(self, ssl_version, expected_ssl_version): Given: - An ssl protocol v... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class TestLDAPAuthentication:
"""Contains unit tests for general functions that deal with both OpenLDAP and Active Directory servers."""
def test_get_ssl_version(self, ssl_version, expected_ssl_version):
"""Given: - An ssl protocol version: 1. TLS 2. TLSv1 3. TLSv1_1 4. TLSv1_2 5. TLS_CLIE... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestLDAPAuthentication:
"""Contains unit tests for general functions that deal with both OpenLDAP and Active Directory servers."""
def test_get_ssl_version(self, ssl_version, expected_ssl_version):
"""Given: - An ssl protocol version: 1. TLS 2. TLSv1 3. TLSv1_1 4. TLSv1_2 5. TLS_CLIENT 6. None 7.... | the_stack_v2_python_sparse | Packs/OpenLDAP/Integrations/OpenLDAP/OpenLDAP_test.py | demisto/content | train | 1,023 |
bba167eab6302db1318c271f291acd6d4cb5e417 | [
"res = []\nfor i in range(0, len(nums) - 1):\n for j in range(i + 1, len(nums)):\n if nums[i] + nums[j] == target:\n res.append(nums[i])\n res.append(nums[j])\nreturn res",
"lookup = {}\nfor i, num in enumerate(nums):\n if target - num in lookup:\n return [lookup[target -... | <|body_start_0|>
res = []
for i in range(0, len(nums) - 1):
for j in range(i + 1, len(nums)):
if nums[i] + nums[j] == target:
res.append(nums[i])
res.append(nums[j])
return res
<|end_body_0|>
<|body_start_1|>
lookup = {... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum_ugly(self, nums, target):
""":param nums: list[int] :param target: int :return: list[int]"""
<|body_0|>
def twoSum(self, nums, target):
""":param nums: :param target: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res ... | stack_v2_sparse_classes_75kplus_train_068495 | 755 | no_license | [
{
"docstring": ":param nums: list[int] :param target: int :return: list[int]",
"name": "twoSum_ugly",
"signature": "def twoSum_ugly(self, nums, target)"
},
{
"docstring": ":param nums: :param target: :return:",
"name": "twoSum",
"signature": "def twoSum(self, nums, target)"
}
] | 2 | stack_v2_sparse_classes_30k_train_038729 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum_ugly(self, nums, target): :param nums: list[int] :param target: int :return: list[int]
- def twoSum(self, nums, target): :param nums: :param target: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum_ugly(self, nums, target): :param nums: list[int] :param target: int :return: list[int]
- def twoSum(self, nums, target): :param nums: :param target: :return:
<|skelet... | 84bd4a00160e6b2a723a57e149474c6bb38bcce2 | <|skeleton|>
class Solution:
def twoSum_ugly(self, nums, target):
""":param nums: list[int] :param target: int :return: list[int]"""
<|body_0|>
def twoSum(self, nums, target):
""":param nums: :param target: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def twoSum_ugly(self, nums, target):
""":param nums: list[int] :param target: int :return: list[int]"""
res = []
for i in range(0, len(nums) - 1):
for j in range(i + 1, len(nums)):
if nums[i] + nums[j] == target:
res.append(nums... | the_stack_v2_python_sparse | 1_num2sum.py | yanghongkai/yhkleetcode | train | 0 | |
22ef2b0ef2fd54e04c079274f902d878a79fc345 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserExperienceAnalyticsDeviceStartupHistory()",
"from .entity import Entity\nfrom .user_experience_analytics_operating_system_restart_category import UserExperienceAnalyticsOperatingSystemRestartCategory\nfrom .entity import Entity\nfr... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserExperienceAnalyticsDeviceStartupHistory()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .user_experience_analytics_operating_system_restart_category import UserExpe... | The user experience analytics device startup history entity contains device boot performance history details. | UserExperienceAnalyticsDeviceStartupHistory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserExperienceAnalyticsDeviceStartupHistory:
"""The user experience analytics device startup history entity contains device boot performance history details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsDeviceStartupHistory:
"... | stack_v2_sparse_classes_75kplus_train_068496 | 8,363 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: UserExperienceAnalyticsDeviceStartupHistory",
"name": "create_from_discriminator_value",
"signature": "def c... | 3 | stack_v2_sparse_classes_30k_val_001299 | Implement the Python class `UserExperienceAnalyticsDeviceStartupHistory` described below.
Class description:
The user experience analytics device startup history entity contains device boot performance history details.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseN... | Implement the Python class `UserExperienceAnalyticsDeviceStartupHistory` described below.
Class description:
The user experience analytics device startup history entity contains device boot performance history details.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseN... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserExperienceAnalyticsDeviceStartupHistory:
"""The user experience analytics device startup history entity contains device boot performance history details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsDeviceStartupHistory:
"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserExperienceAnalyticsDeviceStartupHistory:
"""The user experience analytics device startup history entity contains device boot performance history details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsDeviceStartupHistory:
"""Creates a n... | the_stack_v2_python_sparse | msgraph/generated/models/user_experience_analytics_device_startup_history.py | microsoftgraph/msgraph-sdk-python | train | 135 |
b05c36d26a1c55056627cec0b1fc2295229f3a32 | [
"if model_id:\n try:\n model = self._model.find(int(model_id))\n except ValueError:\n self.status.BAD_REQUEST('Bad id %s' % model_id)\n else:\n if model:\n self.render_json(model)\n else:\n self.status.NOT_FOUND('Not found by id %s' % model_id)\nelse:\n ... | <|body_start_0|>
if model_id:
try:
model = self._model.find(int(model_id))
except ValueError:
self.status.BAD_REQUEST('Bad id %s' % model_id)
else:
if model:
self.render_json(model)
else:
... | RESTfulNested | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RESTfulNested:
def get(self, parent_id, model_id=None):
"""READ or LIST."""
<|body_0|>
def post(self, parent_id):
"""CREATE."""
<|body_1|>
def put(self, parent_id, model_id):
"""EDIT."""
<|body_2|>
def delete(self, parent_id, model_i... | stack_v2_sparse_classes_75kplus_train_068497 | 7,053 | no_license | [
{
"docstring": "READ or LIST.",
"name": "get",
"signature": "def get(self, parent_id, model_id=None)"
},
{
"docstring": "CREATE.",
"name": "post",
"signature": "def post(self, parent_id)"
},
{
"docstring": "EDIT.",
"name": "put",
"signature": "def put(self, parent_id, mod... | 4 | null | Implement the Python class `RESTfulNested` described below.
Class description:
Implement the RESTfulNested class.
Method signatures and docstrings:
- def get(self, parent_id, model_id=None): READ or LIST.
- def post(self, parent_id): CREATE.
- def put(self, parent_id, model_id): EDIT.
- def delete(self, parent_id, mo... | Implement the Python class `RESTfulNested` described below.
Class description:
Implement the RESTfulNested class.
Method signatures and docstrings:
- def get(self, parent_id, model_id=None): READ or LIST.
- def post(self, parent_id): CREATE.
- def put(self, parent_id, model_id): EDIT.
- def delete(self, parent_id, mo... | 04e7ee88bb9d085c78b2a05b0492d45b6176d166 | <|skeleton|>
class RESTfulNested:
def get(self, parent_id, model_id=None):
"""READ or LIST."""
<|body_0|>
def post(self, parent_id):
"""CREATE."""
<|body_1|>
def put(self, parent_id, model_id):
"""EDIT."""
<|body_2|>
def delete(self, parent_id, model_i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RESTfulNested:
def get(self, parent_id, model_id=None):
"""READ or LIST."""
if model_id:
try:
model = self._model.find(int(model_id))
except ValueError:
self.status.BAD_REQUEST('Bad id %s' % model_id)
else:
if ... | the_stack_v2_python_sparse | backend/plaft/interfaces/newrest.py | gcca/plaft_carinae | train | 0 | |
d318fbed9392837edd71967e45d25aa827dc9bf5 | [
"Sprite.__init__(self)\nself.pose = np.array([x, y, theta])\nself.pose_velocity = np.array([0, 0, 0])\nself.mask = mask\nself.color = color\nself.image = Surface([width, height])\nself.image.set_colorkey(simulation.SIMULATION_BG_COLOR)\nself.dims = [width, height]\nself.rect = self.image.get_rect()\nself.autoscale ... | <|body_start_0|>
Sprite.__init__(self)
self.pose = np.array([x, y, theta])
self.pose_velocity = np.array([0, 0, 0])
self.mask = mask
self.color = color
self.image = Surface([width, height])
self.image.set_colorkey(simulation.SIMULATION_BG_COLOR)
self.dims ... | Abstraction of a simulated object with a pose and a sprite. | SimulationObject | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimulationObject:
"""Abstraction of a simulated object with a pose and a sprite."""
def __init__(self, x, y, theta, width=0, height=0, color=(0, 0, 0), mask=MASK_RECT):
"""Parameters ---------- x: float horizontal position in units y: float vertical position in units theta: heading i... | stack_v2_sparse_classes_75kplus_train_068498 | 4,642 | permissive | [
{
"docstring": "Parameters ---------- x: float horizontal position in units y: float vertical position in units theta: heading in radians width: float width in units height: float height in units color: tuple (r, g, b) mask: int sprite mask (circle or rectangle)",
"name": "__init__",
"signature": "def _... | 5 | stack_v2_sparse_classes_30k_train_039375 | Implement the Python class `SimulationObject` described below.
Class description:
Abstraction of a simulated object with a pose and a sprite.
Method signatures and docstrings:
- def __init__(self, x, y, theta, width=0, height=0, color=(0, 0, 0), mask=MASK_RECT): Parameters ---------- x: float horizontal position in u... | Implement the Python class `SimulationObject` described below.
Class description:
Abstraction of a simulated object with a pose and a sprite.
Method signatures and docstrings:
- def __init__(self, x, y, theta, width=0, height=0, color=(0, 0, 0), mask=MASK_RECT): Parameters ---------- x: float horizontal position in u... | 4e91e86c86bfbdd8d4639b0994e96e890a2f741e | <|skeleton|>
class SimulationObject:
"""Abstraction of a simulated object with a pose and a sprite."""
def __init__(self, x, y, theta, width=0, height=0, color=(0, 0, 0), mask=MASK_RECT):
"""Parameters ---------- x: float horizontal position in units y: float vertical position in units theta: heading i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimulationObject:
"""Abstraction of a simulated object with a pose and a sprite."""
def __init__(self, x, y, theta, width=0, height=0, color=(0, 0, 0), mask=MASK_RECT):
"""Parameters ---------- x: float horizontal position in units y: float vertical position in units theta: heading in radians wid... | the_stack_v2_python_sparse | tools/simulator/r5engine/object.py | ut-ras/r5-2019 | train | 5 |
079e6154245ad9024ab8b89e4c1e41e31ab644e1 | [
"obj = ContactType(name='Test', slug='test')\nobj.save()\nself.assertEquals('Test', obj.name)\nself.assertNotEquals(obj.id, None)\nobj.delete()",
"type = ContactType(name='Test', slug='test')\ntype.save()\nobj = Contact(name='Test', contact_type=type)\nobj.save()\nself.assertEquals('Test', obj.name)\nself.assertN... | <|body_start_0|>
obj = ContactType(name='Test', slug='test')
obj.save()
self.assertEquals('Test', obj.name)
self.assertNotEquals(obj.id, None)
obj.delete()
<|end_body_0|>
<|body_start_1|>
type = ContactType(name='Test', slug='test')
type.save()
obj = Cont... | Identities Model Tests | IdentitiesModelsTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IdentitiesModelsTest:
"""Identities Model Tests"""
def test_model_contacttype(self):
"""Test ContactType model"""
<|body_0|>
def test_model_contact(self):
"""Test Contact model"""
<|body_1|>
def test_model_field(self):
"""Test Field model"""
... | stack_v2_sparse_classes_75kplus_train_068499 | 16,679 | permissive | [
{
"docstring": "Test ContactType model",
"name": "test_model_contacttype",
"signature": "def test_model_contacttype(self)"
},
{
"docstring": "Test Contact model",
"name": "test_model_contact",
"signature": "def test_model_contact(self)"
},
{
"docstring": "Test Field model",
"... | 3 | stack_v2_sparse_classes_30k_train_016749 | Implement the Python class `IdentitiesModelsTest` described below.
Class description:
Identities Model Tests
Method signatures and docstrings:
- def test_model_contacttype(self): Test ContactType model
- def test_model_contact(self): Test Contact model
- def test_model_field(self): Test Field model | Implement the Python class `IdentitiesModelsTest` described below.
Class description:
Identities Model Tests
Method signatures and docstrings:
- def test_model_contacttype(self): Test ContactType model
- def test_model_contact(self): Test Contact model
- def test_model_field(self): Test Field model
<|skeleton|>
clas... | 001e85eaf489c93b565efe679eb159cfcfef4c67 | <|skeleton|>
class IdentitiesModelsTest:
"""Identities Model Tests"""
def test_model_contacttype(self):
"""Test ContactType model"""
<|body_0|>
def test_model_contact(self):
"""Test Contact model"""
<|body_1|>
def test_model_field(self):
"""Test Field model"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IdentitiesModelsTest:
"""Identities Model Tests"""
def test_model_contacttype(self):
"""Test ContactType model"""
obj = ContactType(name='Test', slug='test')
obj.save()
self.assertEquals('Test', obj.name)
self.assertNotEquals(obj.id, None)
obj.delete()
... | the_stack_v2_python_sparse | identities/tests.py | alejo8591/maker | train | 0 |
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