blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
95c565c23cab7bcf5bda89ff2fb81b0448f06c6e | [
"args = self.parse(args)\nset_seed(args.seed)\nconfig, tokenizer, maxlength = self.load(base, maxlength)\nlabels = None\nif task == 'question-answering':\n process = Questions(tokenizer, columns, maxlength, stride)\nelse:\n process = Labels(tokenizer, columns, maxlength)\n labels = process.labels(train)\nt... | <|body_start_0|>
args = self.parse(args)
set_seed(args.seed)
config, tokenizer, maxlength = self.load(base, maxlength)
labels = None
if task == 'question-answering':
process = Questions(tokenizer, columns, maxlength, stride)
else:
process = Labels(... | Trains a new Hugging Face Transformer model using the Trainer framework. | HFTrainer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HFTrainer:
"""Trains a new Hugging Face Transformer model using the Trainer framework."""
def __call__(self, base, train, validation=None, columns=None, maxlength=None, stride=128, task='text-classification', **args):
"""Builds a new model using arguments. Args: base: path to base mo... | stack_v2_sparse_classes_36k_train_029100 | 5,472 | permissive | [
{
"docstring": "Builds a new model using arguments. Args: base: path to base model, accepts Hugging Face model hub id, local path or (model, tokenizer) tuple train: training data validation: validation data columns: tuple of columns to use for text/label, defaults to (text, None, label) maxlength: maximum seque... | 4 | stack_v2_sparse_classes_30k_train_016002 | Implement the Python class `HFTrainer` described below.
Class description:
Trains a new Hugging Face Transformer model using the Trainer framework.
Method signatures and docstrings:
- def __call__(self, base, train, validation=None, columns=None, maxlength=None, stride=128, task='text-classification', **args): Builds... | Implement the Python class `HFTrainer` described below.
Class description:
Trains a new Hugging Face Transformer model using the Trainer framework.
Method signatures and docstrings:
- def __call__(self, base, train, validation=None, columns=None, maxlength=None, stride=128, task='text-classification', **args): Builds... | 1fb384912795dc9592a9df494ed2337e16fe4bd4 | <|skeleton|>
class HFTrainer:
"""Trains a new Hugging Face Transformer model using the Trainer framework."""
def __call__(self, base, train, validation=None, columns=None, maxlength=None, stride=128, task='text-classification', **args):
"""Builds a new model using arguments. Args: base: path to base mo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HFTrainer:
"""Trains a new Hugging Face Transformer model using the Trainer framework."""
def __call__(self, base, train, validation=None, columns=None, maxlength=None, stride=128, task='text-classification', **args):
"""Builds a new model using arguments. Args: base: path to base model, accepts ... | the_stack_v2_python_sparse | src/python/txtai/pipeline/hftrainer.py | hi019/txtai | train | 1 |
caff89b3f93b828492a757b749bb3d3878f668d2 | [
"headers = {'Content-Type': 'application/json;charset=UTF-8'}\nresponse = requests.post(url=url, headers=headers, data=json.dumps(data))\nif response.status_code != 200:\n raise RequestException(str(response.json()))\nif response.json().get('code') != 100:\n raise MyException('目标服务错误:' + response.json().get('... | <|body_start_0|>
headers = {'Content-Type': 'application/json;charset=UTF-8'}
response = requests.post(url=url, headers=headers, data=json.dumps(data))
if response.status_code != 200:
raise RequestException(str(response.json()))
if response.json().get('code') != 100:
... | RestTemplate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestTemplate:
def do_post(url, data):
"""发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:"""
<|body_0|>
def do_post_for_jcos(url, data):
"""发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
he... | stack_v2_sparse_classes_36k_train_029101 | 1,618 | no_license | [
{
"docstring": "发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:",
"name": "do_post",
"signature": "def do_post(url, data)"
},
{
"docstring": "发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:",
"name": "do_post_for_jcos",
"signature": "def do_post_for_jcos(url, data)"
}
] | 2 | null | Implement the Python class `RestTemplate` described below.
Class description:
Implement the RestTemplate class.
Method signatures and docstrings:
- def do_post(url, data): 发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:
- def do_post_for_jcos(url, data): 发送post请求 :param url:请求地址 :param data:字典或字典列表 :return: | Implement the Python class `RestTemplate` described below.
Class description:
Implement the RestTemplate class.
Method signatures and docstrings:
- def do_post(url, data): 发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:
- def do_post_for_jcos(url, data): 发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:
<|... | 5fb62820fa697ffc45931c4c19a9b0775feb1fc5 | <|skeleton|>
class RestTemplate:
def do_post(url, data):
"""发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:"""
<|body_0|>
def do_post_for_jcos(url, data):
"""发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestTemplate:
def do_post(url, data):
"""发送post请求 :param url:请求地址 :param data:字典或字典列表 :return:"""
headers = {'Content-Type': 'application/json;charset=UTF-8'}
response = requests.post(url=url, headers=headers, data=json.dumps(data))
if response.status_code != 200:
r... | the_stack_v2_python_sparse | app/util/rest_template.py | 9Echo/gc-goods-allocation | train | 0 | |
404a72285610e0bc52b6301e6dc3a3078b1d6fbf | [
"post_ = Post.objects.get(slug=slug, is_deleted=False)\ninfographic_post = post_.infographic\nis_user_article = False\nif request.user.is_authenticated():\n user_prof = UserProfile.objects.get(user=request.user)\n contributor = user_can_contribute(request.user)\n if user_prof:\n if user_prof.is_cont... | <|body_start_0|>
post_ = Post.objects.get(slug=slug, is_deleted=False)
infographic_post = post_.infographic
is_user_article = False
if request.user.is_authenticated():
user_prof = UserProfile.objects.get(user=request.user)
contributor = user_can_contribute(request... | InfographicView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InfographicView:
def get(self, request, slug):
"""Gets the view for viewing an individual infographic. Login no longer required, non-users can now access posts. :param slug: Unique slug for the infographic"""
<|body_0|>
def post(self, request, slug):
"""For when the ... | stack_v2_sparse_classes_36k_train_029102 | 10,751 | no_license | [
{
"docstring": "Gets the view for viewing an individual infographic. Login no longer required, non-users can now access posts. :param slug: Unique slug for the infographic",
"name": "get",
"signature": "def get(self, request, slug)"
},
{
"docstring": "For when the unpublish button is pressed, in... | 2 | stack_v2_sparse_classes_30k_train_003202 | Implement the Python class `InfographicView` described below.
Class description:
Implement the InfographicView class.
Method signatures and docstrings:
- def get(self, request, slug): Gets the view for viewing an individual infographic. Login no longer required, non-users can now access posts. :param slug: Unique slu... | Implement the Python class `InfographicView` described below.
Class description:
Implement the InfographicView class.
Method signatures and docstrings:
- def get(self, request, slug): Gets the view for viewing an individual infographic. Login no longer required, non-users can now access posts. :param slug: Unique slu... | 8296c49dfa8771b47965c24b6b49a2b6e8ace6cf | <|skeleton|>
class InfographicView:
def get(self, request, slug):
"""Gets the view for viewing an individual infographic. Login no longer required, non-users can now access posts. :param slug: Unique slug for the infographic"""
<|body_0|>
def post(self, request, slug):
"""For when the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InfographicView:
def get(self, request, slug):
"""Gets the view for viewing an individual infographic. Login no longer required, non-users can now access posts. :param slug: Unique slug for the infographic"""
post_ = Post.objects.get(slug=slug, is_deleted=False)
infographic_post = post... | the_stack_v2_python_sparse | relevate_web_app/apps/contribution/views/infographics_view.py | jhock/Relevate | train | 1 | |
45f5ef3cc47674d3c2b7e9a7d6bc6d700dc24d0d | [
"fleet_veh = self.pool.get('fleet.vehicle')\nrangs = fleet_veh._selection_year(self, cr, uid)\nlist_year = []\nfor years in rangs[1:len(rangs)]:\n list_year.append(years)\nreturn list_year",
"data = self.read(cr, uid, ids, [], context=context)[0]\ndatas = {'ids': [], 'model': 'fleet.vehicle.log.contract', 'for... | <|body_start_0|>
fleet_veh = self.pool.get('fleet.vehicle')
rangs = fleet_veh._selection_year(self, cr, uid)
list_year = []
for years in rangs[1:len(rangs)]:
list_year.append(years)
return list_year
<|end_body_0|>
<|body_start_1|>
data = self.read(cr, uid, id... | To manage rented cars reports | rented_cars_wiz | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class rented_cars_wiz:
"""To manage rented cars reports"""
def _year(self, cr, uid, context=None):
"""Select cars manufacturing years between 1970 and Current year. @return: list of years"""
<|body_0|>
def print_report(self, cr, uid, ids, context=None):
"""Print report... | stack_v2_sparse_classes_36k_train_029103 | 2,273 | no_license | [
{
"docstring": "Select cars manufacturing years between 1970 and Current year. @return: list of years",
"name": "_year",
"signature": "def _year(self, cr, uid, context=None)"
},
{
"docstring": "Print report. @return: Dictionary of print attributes",
"name": "print_report",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_018760 | Implement the Python class `rented_cars_wiz` described below.
Class description:
To manage rented cars reports
Method signatures and docstrings:
- def _year(self, cr, uid, context=None): Select cars manufacturing years between 1970 and Current year. @return: list of years
- def print_report(self, cr, uid, ids, contex... | Implement the Python class `rented_cars_wiz` described below.
Class description:
To manage rented cars reports
Method signatures and docstrings:
- def _year(self, cr, uid, context=None): Select cars manufacturing years between 1970 and Current year. @return: list of years
- def print_report(self, cr, uid, ids, contex... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class rented_cars_wiz:
"""To manage rented cars reports"""
def _year(self, cr, uid, context=None):
"""Select cars manufacturing years between 1970 and Current year. @return: list of years"""
<|body_0|>
def print_report(self, cr, uid, ids, context=None):
"""Print report... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class rented_cars_wiz:
"""To manage rented cars reports"""
def _year(self, cr, uid, context=None):
"""Select cars manufacturing years between 1970 and Current year. @return: list of years"""
fleet_veh = self.pool.get('fleet.vehicle')
rangs = fleet_veh._selection_year(self, cr, uid)
... | the_stack_v2_python_sparse | v_7/Dongola/admin_affairs/service/wizard/rented_cars.py | musabahmed/baba | train | 0 |
f45439be1eb9a030ef6790a49840485b15078c72 | [
"with open(filename, 'r') as file:\n num_nodes = None\n graph = {}\n for line in file:\n if num_nodes is None:\n num_nodes = int(line)\n graph = {id_: node_cls(id_) for id_ in range(1, num_nodes + 1)}\n else:\n m, n, dist = line.split(' ')\n m = int... | <|body_start_0|>
with open(filename, 'r') as file:
num_nodes = None
graph = {}
for line in file:
if num_nodes is None:
num_nodes = int(line)
graph = {id_: node_cls(id_) for id_ in range(1, num_nodes + 1)}
... | IOManager handles converting between dictionaries of GraphNode objects and .ecegraph files. | IOManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IOManager:
"""IOManager handles converting between dictionaries of GraphNode objects and .ecegraph files."""
def import_graph(cls, filename, node_cls=GraphNode):
"""Returns a dictionary of GraphNode objects. Parameters: filename: Name of .ecegraph file to import (ie. map.ecegraph) Re... | stack_v2_sparse_classes_36k_train_029104 | 2,331 | no_license | [
{
"docstring": "Returns a dictionary of GraphNode objects. Parameters: filename: Name of .ecegraph file to import (ie. map.ecegraph) Returns: Dictionary where keys are ids and values are GraphNode objects. Example: graph = IOManager.import_graph('g.ecegraph')",
"name": "import_graph",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_010565 | Implement the Python class `IOManager` described below.
Class description:
IOManager handles converting between dictionaries of GraphNode objects and .ecegraph files.
Method signatures and docstrings:
- def import_graph(cls, filename, node_cls=GraphNode): Returns a dictionary of GraphNode objects. Parameters: filenam... | Implement the Python class `IOManager` described below.
Class description:
IOManager handles converting between dictionaries of GraphNode objects and .ecegraph files.
Method signatures and docstrings:
- def import_graph(cls, filename, node_cls=GraphNode): Returns a dictionary of GraphNode objects. Parameters: filenam... | faf065e0aae8e242d05f6940ba98be102f6ff6e5 | <|skeleton|>
class IOManager:
"""IOManager handles converting between dictionaries of GraphNode objects and .ecegraph files."""
def import_graph(cls, filename, node_cls=GraphNode):
"""Returns a dictionary of GraphNode objects. Parameters: filename: Name of .ecegraph file to import (ie. map.ecegraph) Re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IOManager:
"""IOManager handles converting between dictionaries of GraphNode objects and .ecegraph files."""
def import_graph(cls, filename, node_cls=GraphNode):
"""Returns a dictionary of GraphNode objects. Parameters: filename: Name of .ecegraph file to import (ie. map.ecegraph) Returns: Dictio... | the_stack_v2_python_sparse | graph/iomanager.py | andrew-zhou/ece457a | train | 0 |
c70a5faadd2aef0fe5978fc378df727cdfe07e1d | [
"if root is None:\n return []\nsum_root = self.SumofLevel(root)\nreturn [i[0] / i[1] for i in sum_root]",
"if root is None:\n return []\nsum_l = self.SumofLevel(root.left)\nsum_r = self.SumofLevel(root.right)\nsum_root = [(root.val, 1)]\nfor i in range(max(len(sum_l), len(sum_r))):\n if i >= len(sum_l):\... | <|body_start_0|>
if root is None:
return []
sum_root = self.SumofLevel(root)
return [i[0] / i[1] for i in sum_root]
<|end_body_0|>
<|body_start_1|>
if root is None:
return []
sum_l = self.SumofLevel(root.left)
sum_r = self.SumofLevel(root.right)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def averageOfLevels(self, root):
""":type root: TreeNode :rtype: List[float]"""
<|body_0|>
def SumofLevel(self, root):
""":type root: TreeNode :rtype: List[float]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is None:
... | stack_v2_sparse_classes_36k_train_029105 | 1,801 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[float]",
"name": "averageOfLevels",
"signature": "def averageOfLevels(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[float]",
"name": "SumofLevel",
"signature": "def SumofLevel(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012789 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def averageOfLevels(self, root): :type root: TreeNode :rtype: List[float]
- def SumofLevel(self, root): :type root: TreeNode :rtype: List[float] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def averageOfLevels(self, root): :type root: TreeNode :rtype: List[float]
- def SumofLevel(self, root): :type root: TreeNode :rtype: List[float]
<|skeleton|>
class Solution:
... | 4e137a6a860fc5ce1d32befd0886a22fd67d2293 | <|skeleton|>
class Solution:
def averageOfLevels(self, root):
""":type root: TreeNode :rtype: List[float]"""
<|body_0|>
def SumofLevel(self, root):
""":type root: TreeNode :rtype: List[float]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def averageOfLevels(self, root):
""":type root: TreeNode :rtype: List[float]"""
if root is None:
return []
sum_root = self.SumofLevel(root)
return [i[0] / i[1] for i in sum_root]
def SumofLevel(self, root):
""":type root: TreeNode :rtype: List... | the_stack_v2_python_sparse | src/637_Average_of_Levels_in_Binary_Tree.py | HuJiawei1990/LeetCode | train | 0 | |
f1f1617b69267399b90f989cb1ffaf1e7f911d32 | [
"BaseMailingProcess.__init__(self)\nself.preview_problem = None\nself.mail_preview = None",
"self.unit_problem = problem\nself.mail_preview = mail_preview\nbackslash_string = \"Ce problème est inspiré d'une interview donnée par\"\ncustom_company_message = f\"{('Cette interview est une création originale' if self.... | <|body_start_0|>
BaseMailingProcess.__init__(self)
self.preview_problem = None
self.mail_preview = None
<|end_body_0|>
<|body_start_1|>
self.unit_problem = problem
self.mail_preview = mail_preview
backslash_string = "Ce problème est inspiré d'une interview donnée par"
... | PreviewMailingProcess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreviewMailingProcess:
def __init__(self):
"""The PreviewMailingProcess handle the core logic for sending one mail for a preview given a problem. It's used when doing email previews when adding/updating a Problem model in the admin page."""
<|body_0|>
def run(self, problem, ... | stack_v2_sparse_classes_36k_train_029106 | 24,237 | no_license | [
{
"docstring": "The PreviewMailingProcess handle the core logic for sending one mail for a preview given a problem. It's used when doing email previews when adding/updating a Problem model in the admin page.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Run the unit ... | 2 | stack_v2_sparse_classes_30k_train_018689 | Implement the Python class `PreviewMailingProcess` described below.
Class description:
Implement the PreviewMailingProcess class.
Method signatures and docstrings:
- def __init__(self): The PreviewMailingProcess handle the core logic for sending one mail for a preview given a problem. It's used when doing email previ... | Implement the Python class `PreviewMailingProcess` described below.
Class description:
Implement the PreviewMailingProcess class.
Method signatures and docstrings:
- def __init__(self): The PreviewMailingProcess handle the core logic for sending one mail for a preview given a problem. It's used when doing email previ... | 048e349a413b075da9cc0e0b497c40ab6620e245 | <|skeleton|>
class PreviewMailingProcess:
def __init__(self):
"""The PreviewMailingProcess handle the core logic for sending one mail for a preview given a problem. It's used when doing email previews when adding/updating a Problem model in the admin page."""
<|body_0|>
def run(self, problem, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PreviewMailingProcess:
def __init__(self):
"""The PreviewMailingProcess handle the core logic for sending one mail for a preview given a problem. It's used when doing email previews when adding/updating a Problem model in the admin page."""
BaseMailingProcess.__init__(self)
self.previe... | the_stack_v2_python_sparse | 1interviewparjour/oneinterviewparjour/mail_scheduler/engine.py | gabrielmougard/1interviewparjour | train | 1 | |
10ec79b81992964c09d8dd1830229b7b322274fc | [
"super().__init__()\nself.lstm_cell = tf.keras.layers.LSTMCell(lstm_units, dropout=0.3, kernel_regularizer=tf.keras.regularizers.l2(l=0.02), recurrent_regularizer=tf.keras.regularizers.l2(l=0.02))\nself.dense1 = tf.keras.layers.Dense(1)\nself.dense2 = tf.keras.layers.Dense(10, activation='relu', kernel_regularizer=... | <|body_start_0|>
super().__init__()
self.lstm_cell = tf.keras.layers.LSTMCell(lstm_units, dropout=0.3, kernel_regularizer=tf.keras.regularizers.l2(l=0.02), recurrent_regularizer=tf.keras.regularizers.l2(l=0.02))
self.dense1 = tf.keras.layers.Dense(1)
self.dense2 = tf.keras.layers.Dense(1... | Simple RNN based CF model. | RNNCFModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNCFModel:
"""Simple RNN based CF model."""
def __init__(self, maxhd, maxv, mina, maxa, lstm_units=20, dt=0.1):
"""Inits RNN based CF model. Args: maxhd: max headway (for nomalization of inputs) maxv: max velocity (for nomalization of inputs) mina: minimum acceleration (for nomaliza... | stack_v2_sparse_classes_36k_train_029107 | 20,223 | permissive | [
{
"docstring": "Inits RNN based CF model. Args: maxhd: max headway (for nomalization of inputs) maxv: max velocity (for nomalization of inputs) mina: minimum acceleration (for nomalization of outputs) maxa: maximum acceleration (for nomalization of outputs) dt: timestep",
"name": "__init__",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_012377 | Implement the Python class `RNNCFModel` described below.
Class description:
Simple RNN based CF model.
Method signatures and docstrings:
- def __init__(self, maxhd, maxv, mina, maxa, lstm_units=20, dt=0.1): Inits RNN based CF model. Args: maxhd: max headway (for nomalization of inputs) maxv: max velocity (for nomaliz... | Implement the Python class `RNNCFModel` described below.
Class description:
Simple RNN based CF model.
Method signatures and docstrings:
- def __init__(self, maxhd, maxv, mina, maxa, lstm_units=20, dt=0.1): Inits RNN based CF model. Args: maxhd: max headway (for nomalization of inputs) maxv: max velocity (for nomaliz... | 0aaf9674e987822ff2dc90c74613d5e68e8ef0ce | <|skeleton|>
class RNNCFModel:
"""Simple RNN based CF model."""
def __init__(self, maxhd, maxv, mina, maxa, lstm_units=20, dt=0.1):
"""Inits RNN based CF model. Args: maxhd: max headway (for nomalization of inputs) maxv: max velocity (for nomalization of inputs) mina: minimum acceleration (for nomaliza... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNCFModel:
"""Simple RNN based CF model."""
def __init__(self, maxhd, maxv, mina, maxa, lstm_units=20, dt=0.1):
"""Inits RNN based CF model. Args: maxhd: max headway (for nomalization of inputs) maxv: max velocity (for nomalization of inputs) mina: minimum acceleration (for nomalization of outpu... | the_stack_v2_python_sparse | scripts/meng/deep learning/DL2_relax.py | seccode/havsim | train | 0 |
884ba1b274da0f5736845de349da2a4c344ef87c | [
"super(SGDBenchmark, self).__init__(config_path, config)\nif not self.config:\n self.config = objdict(SGD_DEFAULTS.copy())\nfor key in SGD_DEFAULTS:\n if key not in self.config:\n self.config[key] = SGD_DEFAULTS[key]",
"if 'instance_set' not in self.config.keys():\n self.read_instance_set()\nif 't... | <|body_start_0|>
super(SGDBenchmark, self).__init__(config_path, config)
if not self.config:
self.config = objdict(SGD_DEFAULTS.copy())
for key in SGD_DEFAULTS:
if key not in self.config:
self.config[key] = SGD_DEFAULTS[key]
<|end_body_0|>
<|body_start_1|... | Benchmark with default configuration & relevant functions for SGD | SGDBenchmark | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SGDBenchmark:
"""Benchmark with default configuration & relevant functions for SGD"""
def __init__(self, config_path=None, config=None):
"""Initialize SGD Benchmark Parameters ------- config_path : str Path to config file (optional)"""
<|body_0|>
def get_environment(self... | stack_v2_sparse_classes_36k_train_029108 | 6,789 | permissive | [
{
"docstring": "Initialize SGD Benchmark Parameters ------- config_path : str Path to config file (optional)",
"name": "__init__",
"signature": "def __init__(self, config_path=None, config=None)"
},
{
"docstring": "Return SGDEnv env with current configuration Returns ------- SGDEnv SGD environme... | 4 | stack_v2_sparse_classes_30k_train_010371 | Implement the Python class `SGDBenchmark` described below.
Class description:
Benchmark with default configuration & relevant functions for SGD
Method signatures and docstrings:
- def __init__(self, config_path=None, config=None): Initialize SGD Benchmark Parameters ------- config_path : str Path to config file (opti... | Implement the Python class `SGDBenchmark` described below.
Class description:
Benchmark with default configuration & relevant functions for SGD
Method signatures and docstrings:
- def __init__(self, config_path=None, config=None): Initialize SGD Benchmark Parameters ------- config_path : str Path to config file (opti... | d99b21ec844a46d6e18e729ab299f8e9051a68e8 | <|skeleton|>
class SGDBenchmark:
"""Benchmark with default configuration & relevant functions for SGD"""
def __init__(self, config_path=None, config=None):
"""Initialize SGD Benchmark Parameters ------- config_path : str Path to config file (optional)"""
<|body_0|>
def get_environment(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SGDBenchmark:
"""Benchmark with default configuration & relevant functions for SGD"""
def __init__(self, config_path=None, config=None):
"""Initialize SGD Benchmark Parameters ------- config_path : str Path to config file (optional)"""
super(SGDBenchmark, self).__init__(config_path, confi... | the_stack_v2_python_sparse | dacbench/benchmarks/sgd_benchmark.py | automl/DACBench | train | 19 |
aaf832c4c2152b897ec65c25877615a4098a1680 | [
"try:\n self.store_records(table=Platform, data=data)\n if autosave:\n self.commit_session()\nexcept:\n self.rollback_session()\n raise",
"try:\n column = [column for column in Platform.__table__.columns if column.key == target_column_name][0]\n platform = self.fetch_records_by_column(tab... | <|body_start_0|>
try:
self.store_records(table=Platform, data=data)
if autosave:
self.commit_session()
except:
self.rollback_session()
raise
<|end_body_0|>
<|body_start_1|>
try:
column = [column for column in Platform._... | An adaptor class for Platform tables | PlatformAdaptor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlatformAdaptor:
"""An adaptor class for Platform tables"""
def store_platform_data(self, data, autosave=True):
"""Load data to Platform table"""
<|body_0|>
def fetch_platform_records_igf_id(self, platform_igf_id, target_column_name='platform_igf_id', output_mode='one'):... | stack_v2_sparse_classes_36k_train_029109 | 2,442 | permissive | [
{
"docstring": "Load data to Platform table",
"name": "store_platform_data",
"signature": "def store_platform_data(self, data, autosave=True)"
},
{
"docstring": "A method for fetching data for Platform table :param platform_igf_id: an igf id :param target_column_name: column name in the Platform... | 3 | stack_v2_sparse_classes_30k_train_000728 | Implement the Python class `PlatformAdaptor` described below.
Class description:
An adaptor class for Platform tables
Method signatures and docstrings:
- def store_platform_data(self, data, autosave=True): Load data to Platform table
- def fetch_platform_records_igf_id(self, platform_igf_id, target_column_name='platf... | Implement the Python class `PlatformAdaptor` described below.
Class description:
An adaptor class for Platform tables
Method signatures and docstrings:
- def store_platform_data(self, data, autosave=True): Load data to Platform table
- def fetch_platform_records_igf_id(self, platform_igf_id, target_column_name='platf... | 01063828f2983e790aafde592d1a2a3af088a6a9 | <|skeleton|>
class PlatformAdaptor:
"""An adaptor class for Platform tables"""
def store_platform_data(self, data, autosave=True):
"""Load data to Platform table"""
<|body_0|>
def fetch_platform_records_igf_id(self, platform_igf_id, target_column_name='platform_igf_id', output_mode='one'):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PlatformAdaptor:
"""An adaptor class for Platform tables"""
def store_platform_data(self, data, autosave=True):
"""Load data to Platform table"""
try:
self.store_records(table=Platform, data=data)
if autosave:
self.commit_session()
except:
... | the_stack_v2_python_sparse | igf_data/igfdb/platformadaptor.py | bballamudi/data-management-python | train | 0 |
734dfb90aa36e313b993b584aa43139193fc8621 | [
"customer_data = self.parse_request()\ncustomer = Customer.objects.create(**customer_data)\nsession.auth.set_data(self.request, customer)\nreturn http.HttpResponse()",
"customer = session.auth.get_data(self.request)\nif customer is None:\n return http.HttpResponseForbidden()\npassword_old = kwargs.pop('passwor... | <|body_start_0|>
customer_data = self.parse_request()
customer = Customer.objects.create(**customer_data)
session.auth.set_data(self.request, customer)
return http.HttpResponse()
<|end_body_0|>
<|body_start_1|>
customer = session.auth.get_data(self.request)
if customer i... | CustomerView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomerView:
def post(self, request, *args, **kwargs):
"""Create customer. Automatically logins."""
<|body_0|>
def put(self, request, *args, **kwargs):
"""Update customer fields. 404 if not logged in. If want to set password, old password has to be provided in 'pass... | stack_v2_sparse_classes_36k_train_029110 | 5,815 | no_license | [
{
"docstring": "Create customer. Automatically logins.",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
},
{
"docstring": "Update customer fields. 404 if not logged in. If want to set password, old password has to be provided in 'password_old' parameter.",
"name": "p... | 2 | stack_v2_sparse_classes_30k_train_019267 | Implement the Python class `CustomerView` described below.
Class description:
Implement the CustomerView class.
Method signatures and docstrings:
- def post(self, request, *args, **kwargs): Create customer. Automatically logins.
- def put(self, request, *args, **kwargs): Update customer fields. 404 if not logged in. ... | Implement the Python class `CustomerView` described below.
Class description:
Implement the CustomerView class.
Method signatures and docstrings:
- def post(self, request, *args, **kwargs): Create customer. Automatically logins.
- def put(self, request, *args, **kwargs): Update customer fields. 404 if not logged in. ... | 038834c0f544d6997613d61d593a7d5abf673c70 | <|skeleton|>
class CustomerView:
def post(self, request, *args, **kwargs):
"""Create customer. Automatically logins."""
<|body_0|>
def put(self, request, *args, **kwargs):
"""Update customer fields. 404 if not logged in. If want to set password, old password has to be provided in 'pass... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomerView:
def post(self, request, *args, **kwargs):
"""Create customer. Automatically logins."""
customer_data = self.parse_request()
customer = Customer.objects.create(**customer_data)
session.auth.set_data(self.request, customer)
return http.HttpResponse()
de... | the_stack_v2_python_sparse | sites/hermanmiller/shop/views.py | alexgula/django_sites | train | 0 | |
bf6acef6187502b2b91651b537b15cbcfaf5c6cf | [
"tokens = []\nself.space, tokens = (len(tokens), tokens + [' '])\ntokens.extend(chars)\nif apostrophe:\n tokens.append(\"'\")\nif punct:\n if non_default_punct_list is not None:\n self.PUNCT_LIST = non_default_punct_list\n tokens.extend(self.PUNCT_LIST)\nsuper().__init__(tokens, add_blank_at=add_bla... | <|body_start_0|>
tokens = []
self.space, tokens = (len(tokens), tokens + [' '])
tokens.extend(chars)
if apostrophe:
tokens.append("'")
if punct:
if non_default_punct_list is not None:
self.PUNCT_LIST = non_default_punct_list
tok... | BaseCharsTokenizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseCharsTokenizer:
def __init__(self, chars, punct=True, apostrophe=True, add_blank_at=None, pad_with_space=False, non_default_punct_list=None, text_preprocessing_func=lambda x: x):
"""Base class for char-based tokenizer. Args: chars: string that represents all possible characters. punc... | stack_v2_sparse_classes_36k_train_029111 | 13,991 | permissive | [
{
"docstring": "Base class for char-based tokenizer. Args: chars: string that represents all possible characters. punct: Whether to reserve grapheme for basic punctuation or not. apostrophe: Whether to use apostrophe or not. add_blank_at: Add blank to labels in the specified order (\"last\") or after tokens (an... | 2 | null | Implement the Python class `BaseCharsTokenizer` described below.
Class description:
Implement the BaseCharsTokenizer class.
Method signatures and docstrings:
- def __init__(self, chars, punct=True, apostrophe=True, add_blank_at=None, pad_with_space=False, non_default_punct_list=None, text_preprocessing_func=lambda x:... | Implement the Python class `BaseCharsTokenizer` described below.
Class description:
Implement the BaseCharsTokenizer class.
Method signatures and docstrings:
- def __init__(self, chars, punct=True, apostrophe=True, add_blank_at=None, pad_with_space=False, non_default_punct_list=None, text_preprocessing_func=lambda x:... | 866cc3f66fab3a796a6b74ef7a9e362c2282a976 | <|skeleton|>
class BaseCharsTokenizer:
def __init__(self, chars, punct=True, apostrophe=True, add_blank_at=None, pad_with_space=False, non_default_punct_list=None, text_preprocessing_func=lambda x: x):
"""Base class for char-based tokenizer. Args: chars: string that represents all possible characters. punc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseCharsTokenizer:
def __init__(self, chars, punct=True, apostrophe=True, add_blank_at=None, pad_with_space=False, non_default_punct_list=None, text_preprocessing_func=lambda x: x):
"""Base class for char-based tokenizer. Args: chars: string that represents all possible characters. punct: Whether to ... | the_stack_v2_python_sparse | nemo/collections/tts/torch/tts_tokenizers.py | VahidooX/NeMo | train | 1 | |
5cd1afffcc6c59497a995a07aa6bc7b297311a8f | [
"super().define(spec)\nspec.input('num_val', valid_type=orm.Int, required=True, serializer=orm.to_aiida_type, help='Number of valence WFs.')\nspec.input('rotate_unk', valid_type=orm.Bool, default=lambda: orm.Bool(False), serializer=orm.to_aiida_type, help='Number of valence WFs.')\nspec.inputs['metadata']['options'... | <|body_start_0|>
super().define(spec)
spec.input('num_val', valid_type=orm.Int, required=True, serializer=orm.to_aiida_type, help='Number of valence WFs.')
spec.input('rotate_unk', valid_type=orm.Bool, default=lambda: orm.Bool(False), serializer=orm.to_aiida_type, help='Number of valence WFs.')
... | AiiDA calculation plugin wrapping the split AMN/MMN/EIG script. | Wannier90SplitCalculation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Wannier90SplitCalculation:
"""AiiDA calculation plugin wrapping the split AMN/MMN/EIG script."""
def define(cls, spec):
"""Define inputs and outputs of the calculation."""
<|body_0|>
def prepare_for_submission(self, folder):
"""Create input files. :param folder: ... | stack_v2_sparse_classes_36k_train_029112 | 5,395 | permissive | [
{
"docstring": "Define inputs and outputs of the calculation.",
"name": "define",
"signature": "def define(cls, spec)"
},
{
"docstring": "Create input files. :param folder: an `aiida.common.folders.Folder` where the plugin should temporarily place all files needed by the calculation. :return: `a... | 2 | stack_v2_sparse_classes_30k_val_001116 | Implement the Python class `Wannier90SplitCalculation` described below.
Class description:
AiiDA calculation plugin wrapping the split AMN/MMN/EIG script.
Method signatures and docstrings:
- def define(cls, spec): Define inputs and outputs of the calculation.
- def prepare_for_submission(self, folder): Create input f... | Implement the Python class `Wannier90SplitCalculation` described below.
Class description:
AiiDA calculation plugin wrapping the split AMN/MMN/EIG script.
Method signatures and docstrings:
- def define(cls, spec): Define inputs and outputs of the calculation.
- def prepare_for_submission(self, folder): Create input f... | aeceb3519ffd1cd071d5b98f81888052fff58163 | <|skeleton|>
class Wannier90SplitCalculation:
"""AiiDA calculation plugin wrapping the split AMN/MMN/EIG script."""
def define(cls, spec):
"""Define inputs and outputs of the calculation."""
<|body_0|>
def prepare_for_submission(self, folder):
"""Create input files. :param folder: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Wannier90SplitCalculation:
"""AiiDA calculation plugin wrapping the split AMN/MMN/EIG script."""
def define(cls, spec):
"""Define inputs and outputs of the calculation."""
super().define(spec)
spec.input('num_val', valid_type=orm.Int, required=True, serializer=orm.to_aiida_type, h... | the_stack_v2_python_sparse | src/aiida_wannier90_workflows/calculations/split.py | aiidateam/aiida-wannier90-workflows | train | 5 |
ffc27843d222e28dec61943da71cf3dd35b75133 | [
"install_cache_path = os.path.join(sublime.cache_path(), 'Rainmeter', 'install', 'last_entered_folder.cache')\nif os.path.exists(install_cache_path) and os.path.isfile(install_cache_path):\n with open(install_cache_path, 'r') as cache_handler:\n cache_content = cache_handler.read()\n default_path =... | <|body_start_0|>
install_cache_path = os.path.join(sublime.cache_path(), 'Rainmeter', 'install', 'last_entered_folder.cache')
if os.path.exists(install_cache_path) and os.path.isfile(install_cache_path):
with open(install_cache_path, 'r') as cache_handler:
cache_content = cac... | Command to install skin from a folder. Command String is rainmeter_install_skin_from_folder_command. | RainmeterInstallSkinFromFolderCommand | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RainmeterInstallSkinFromFolderCommand:
"""Command to install skin from a folder. Command String is rainmeter_install_skin_from_folder_command."""
def run(self):
"""Automatically executed upon calling this command."""
<|body_0|>
def __on_folder_path_entered(cls, path):
... | stack_v2_sparse_classes_36k_train_029113 | 11,700 | permissive | [
{
"docstring": "Automatically executed upon calling this command.",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "Executed after a path is entered. Checks the given user input to verify some basic requirements like that it is a directory.",
"name": "__on_folder_path_entered"... | 2 | stack_v2_sparse_classes_30k_train_000668 | Implement the Python class `RainmeterInstallSkinFromFolderCommand` described below.
Class description:
Command to install skin from a folder. Command String is rainmeter_install_skin_from_folder_command.
Method signatures and docstrings:
- def run(self): Automatically executed upon calling this command.
- def __on_fo... | Implement the Python class `RainmeterInstallSkinFromFolderCommand` described below.
Class description:
Command to install skin from a folder. Command String is rainmeter_install_skin_from_folder_command.
Method signatures and docstrings:
- def run(self): Automatically executed upon calling this command.
- def __on_fo... | 89d67adfd0ef196360785aa2aedecb693f71e965 | <|skeleton|>
class RainmeterInstallSkinFromFolderCommand:
"""Command to install skin from a folder. Command String is rainmeter_install_skin_from_folder_command."""
def run(self):
"""Automatically executed upon calling this command."""
<|body_0|>
def __on_folder_path_entered(cls, path):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RainmeterInstallSkinFromFolderCommand:
"""Command to install skin from a folder. Command String is rainmeter_install_skin_from_folder_command."""
def run(self):
"""Automatically executed upon calling this command."""
install_cache_path = os.path.join(sublime.cache_path(), 'Rainmeter', 'in... | the_stack_v2_python_sparse | install_skin.py | thatsIch/sublime-rainmeter | train | 62 |
c7f289f030458cc4a3f694f93b361fc691f606ff | [
"tofAxis = timeHistogram.axisFromName('tof')\ntofVector = tofAxis.storage()\nenergyAxis = energyHistogram.axisFromName('energy')\nenergyVector = energyAxis.storage()\nself._calcor(pixelDist, tofVector, energyVector)\nreturn",
"from reduction.vectorCompat.EBinCalcor import EBinCalcor\nself._calcor = EBinCalcor(dat... | <|body_start_0|>
tofAxis = timeHistogram.axisFromName('tof')
tofVector = tofAxis.storage()
energyAxis = energyHistogram.axisFromName('energy')
energyVector = energyAxis.storage()
self._calcor(pixelDist, tofVector, energyVector)
return
<|end_body_0|>
<|body_start_1|>
... | energy bin calculator calculate energy bins out of tof bins | EBinCalcor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EBinCalcor:
"""energy bin calculator calculate energy bins out of tof bins"""
def __call__(self, pixelDist, timeHistogram, energyHistogram):
"""ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin boundaries for histogram with energy axis given pixel dist... | stack_v2_sparse_classes_36k_train_029114 | 2,138 | no_license | [
{
"docstring": "ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin boundaries for histogram with energy axis given pixel distance and histogram with tof axis. inputs: pixelDist: distance from sample to pixel (float) timeHistogram (instance of Histogram with axis \"tof\") energyHis... | 2 | stack_v2_sparse_classes_30k_train_008736 | Implement the Python class `EBinCalcor` described below.
Class description:
energy bin calculator calculate energy bins out of tof bins
Method signatures and docstrings:
- def __call__(self, pixelDist, timeHistogram, energyHistogram): ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin b... | Implement the Python class `EBinCalcor` described below.
Class description:
energy bin calculator calculate energy bins out of tof bins
Method signatures and docstrings:
- def __call__(self, pixelDist, timeHistogram, energyHistogram): ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin b... | 7ba4ce07a5a4645942192b4b81f7afcae505db90 | <|skeleton|>
class EBinCalcor:
"""energy bin calculator calculate energy bins out of tof bins"""
def __call__(self, pixelDist, timeHistogram, energyHistogram):
"""ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin boundaries for histogram with energy axis given pixel dist... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EBinCalcor:
"""energy bin calculator calculate energy bins out of tof bins"""
def __call__(self, pixelDist, timeHistogram, energyHistogram):
"""ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin boundaries for histogram with energy axis given pixel distance and hist... | the_stack_v2_python_sparse | histogrammode/reduction/histCompat/EBinCalcor.py | danse-inelastic/DrChops | train | 0 |
5ebaf98990f1723ed520236535b543888dfc7e95 | [
"if type(data) != np.ndarray or len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nd, n = (data.shape[0], data.shape[1])\nif n < 2:\n raise ValueError('data must contain multiple data points')\nself.mean = np.mean(data, axis=1, keepdims=True)\nself.cov = np.matmul(data - self.mean, da... | <|body_start_0|>
if type(data) != np.ndarray or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
d, n = (data.shape[0], data.shape[1])
if n < 2:
raise ValueError('data must contain multiple data points')
self.mean = np.mean(data, axis=1, ke... | represents multinormal random variable | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""represents multinormal random variable"""
def __init__(self, data):
"""creates multinormal instance"""
<|body_0|>
def pdf(self, x):
"""calculates the pdf at a data point x: np.ndarray (d, 1) containing a data point d: number of dimensions"""
... | stack_v2_sparse_classes_36k_train_029115 | 1,446 | no_license | [
{
"docstring": "creates multinormal instance",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "calculates the pdf at a data point x: np.ndarray (d, 1) containing a data point d: number of dimensions",
"name": "pdf",
"signature": "def pdf(self, x)"
}
] | 2 | null | Implement the Python class `MultiNormal` described below.
Class description:
represents multinormal random variable
Method signatures and docstrings:
- def __init__(self, data): creates multinormal instance
- def pdf(self, x): calculates the pdf at a data point x: np.ndarray (d, 1) containing a data point d: number o... | Implement the Python class `MultiNormal` described below.
Class description:
represents multinormal random variable
Method signatures and docstrings:
- def __init__(self, data): creates multinormal instance
- def pdf(self, x): calculates the pdf at a data point x: np.ndarray (d, 1) containing a data point d: number o... | d86b0e0cae2dd07c761f84a493abc895007873ee | <|skeleton|>
class MultiNormal:
"""represents multinormal random variable"""
def __init__(self, data):
"""creates multinormal instance"""
<|body_0|>
def pdf(self, x):
"""calculates the pdf at a data point x: np.ndarray (d, 1) containing a data point d: number of dimensions"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""represents multinormal random variable"""
def __init__(self, data):
"""creates multinormal instance"""
if type(data) != np.ndarray or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
d, n = (data.shape[0], data.shape[1])
... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | mag389/holbertonschool-machine_learning | train | 2 |
410804580eedfb7a0f337e7c4304c6047c1b85c2 | [
"components = []\n\ndef dfs(node):\n if node is None:\n components.append('')\n else:\n components.append(str(node.val))\n dfs(node.left)\n dfs(node.right)\ndfs(root)\nreturn ','.join(components) + ','",
"if data == ',':\n return None\nself.index = 0\n\ndef dfs():\n if data... | <|body_start_0|>
components = []
def dfs(node):
if node is None:
components.append('')
else:
components.append(str(node.val))
dfs(node.left)
dfs(node.right)
dfs(root)
return ','.join(components) + ',... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_029116 | 1,917 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_016867 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 488d93280d45ea686d30b0928e96aa5ed5498e6b | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
components = []
def dfs(node):
if node is None:
components.append('')
else:
components.append(str(node.val))
... | the_stack_v2_python_sparse | leetcode/lc297.py | JasonXJ/algorithms | train | 1 | |
0c1b699d18933ca76dcc0358803abd2a50a8c082 | [
"mix = mix.to(self.device)\nmix_w = self.modules.encoder(mix)\nest_mask = self.modules.masknet(mix_w)\nmix_w = torch.stack([mix_w] * self.hparams.num_spks)\nsep_h = mix_w * est_mask\nest_source = torch.cat([self.modules.decoder(sep_h[i]).unsqueeze(-1) for i in range(self.hparams.num_spks)], dim=-1)\nT_origin = mix.... | <|body_start_0|>
mix = mix.to(self.device)
mix_w = self.modules.encoder(mix)
est_mask = self.modules.masknet(mix_w)
mix_w = torch.stack([mix_w] * self.hparams.num_spks)
sep_h = mix_w * est_mask
est_source = torch.cat([self.modules.decoder(sep_h[i]).unsqueeze(-1) for i in ... | A "ready-to-use" speech separation model. Uses Sepformer architecture. Example ------- >>> tmpdir = getfixture("tmpdir") >>> model = SepformerSeparation.from_hparams( ... source="speechbrain/sepformer-wsj02mix", ... savedir=tmpdir) >>> mix = torch.randn(1, 400) >>> est_sources = model.separate_batch(mix) >>> print(est_... | SepformerSeparation | [
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference",
"GPL-1.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SepformerSeparation:
"""A "ready-to-use" speech separation model. Uses Sepformer architecture. Example ------- >>> tmpdir = getfixture("tmpdir") >>> model = SepformerSeparation.from_hparams( ... source="speechbrain/sepformer-wsj02mix", ... savedir=tmpdir) >>> mix = torch.randn(1, 400) >>> est_sou... | stack_v2_sparse_classes_36k_train_029117 | 35,100 | permissive | [
{
"docstring": "Run source separation on batch of audio. Arguments --------- mix : torch.tensor The mixture of sources. Returns ------- tensor Separated sources",
"name": "separate_batch",
"signature": "def separate_batch(self, mix)"
},
{
"docstring": "Separate sources from file. Arguments -----... | 2 | stack_v2_sparse_classes_30k_train_018613 | Implement the Python class `SepformerSeparation` described below.
Class description:
A "ready-to-use" speech separation model. Uses Sepformer architecture. Example ------- >>> tmpdir = getfixture("tmpdir") >>> model = SepformerSeparation.from_hparams( ... source="speechbrain/sepformer-wsj02mix", ... savedir=tmpdir) >>... | Implement the Python class `SepformerSeparation` described below.
Class description:
A "ready-to-use" speech separation model. Uses Sepformer architecture. Example ------- >>> tmpdir = getfixture("tmpdir") >>> model = SepformerSeparation.from_hparams( ... source="speechbrain/sepformer-wsj02mix", ... savedir=tmpdir) >>... | 92acc188d3a0f634de58463b6676e70df83ef808 | <|skeleton|>
class SepformerSeparation:
"""A "ready-to-use" speech separation model. Uses Sepformer architecture. Example ------- >>> tmpdir = getfixture("tmpdir") >>> model = SepformerSeparation.from_hparams( ... source="speechbrain/sepformer-wsj02mix", ... savedir=tmpdir) >>> mix = torch.randn(1, 400) >>> est_sou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SepformerSeparation:
"""A "ready-to-use" speech separation model. Uses Sepformer architecture. Example ------- >>> tmpdir = getfixture("tmpdir") >>> model = SepformerSeparation.from_hparams( ... source="speechbrain/sepformer-wsj02mix", ... savedir=tmpdir) >>> mix = torch.randn(1, 400) >>> est_sources = model.... | the_stack_v2_python_sparse | ACL_PyTorch/contrib/audio/tdnn/interfaces.py | Ascend/ModelZoo-PyTorch | train | 23 |
77c744cfa3caf1023aeb65602c56b7492b12bf52 | [
"super(MultiHeadAttention, self).__init__()\nself.h = h\nself.dm = dm\nself.depth = int(dm / h)\nself.Wq = tf.keras.layers.Dense(units=dm)\nself.Wk = tf.keras.layers.Dense(units=dm)\nself.Wv = tf.keras.layers.Dense(units=dm)\nself.linear = tf.keras.layers.Dense(units=dm)",
"batch, seq_len_q, dk = Q.shape\n_, seq_... | <|body_start_0|>
super(MultiHeadAttention, self).__init__()
self.h = h
self.dm = dm
self.depth = int(dm / h)
self.Wq = tf.keras.layers.Dense(units=dm)
self.Wk = tf.keras.layers.Dense(units=dm)
self.Wv = tf.keras.layers.Dense(units=dm)
self.linear = tf.kera... | Class MultiHeadAttention | MultiHeadAttention | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadAttention:
"""Class MultiHeadAttention"""
def __init__(self, dm, h):
"""Constructor dm is an integer representing the dimensionality of the model h is an integer representing the number of heads dm is divisible by h Sets the following public instance attributes: h - the numb... | stack_v2_sparse_classes_36k_train_029118 | 4,328 | permissive | [
{
"docstring": "Constructor dm is an integer representing the dimensionality of the model h is an integer representing the number of heads dm is divisible by h Sets the following public instance attributes: h - the number of heads dm - the dimensionality of the model depth - the depth of each attention head Wq ... | 2 | null | Implement the Python class `MultiHeadAttention` described below.
Class description:
Class MultiHeadAttention
Method signatures and docstrings:
- def __init__(self, dm, h): Constructor dm is an integer representing the dimensionality of the model h is an integer representing the number of heads dm is divisible by h Se... | Implement the Python class `MultiHeadAttention` described below.
Class description:
Class MultiHeadAttention
Method signatures and docstrings:
- def __init__(self, dm, h): Constructor dm is an integer representing the dimensionality of the model h is an integer representing the number of heads dm is divisible by h Se... | eaf23423ec0f412f103f5931d6610fdd67bcc5be | <|skeleton|>
class MultiHeadAttention:
"""Class MultiHeadAttention"""
def __init__(self, dm, h):
"""Constructor dm is an integer representing the dimensionality of the model h is an integer representing the number of heads dm is divisible by h Sets the following public instance attributes: h - the numb... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiHeadAttention:
"""Class MultiHeadAttention"""
def __init__(self, dm, h):
"""Constructor dm is an integer representing the dimensionality of the model h is an integer representing the number of heads dm is divisible by h Sets the following public instance attributes: h - the number of heads d... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/6-multihead_attention.py | ledbagholberton/holbertonschool-machine_learning | train | 1 |
13b59db3f2968efaadf006a57e566787a23a11d2 | [
"title = getattr(self, 'page_title', None)\nlanguages = getattr(self, 'page_languages', None)\nif not title:\n languages = languages or [settings.LANGUAGE_CODE]\n title = {language: factory.Faker('catch_phrase').evaluate(None, None, {'locale': language}) for language in languages}\nreturn create_i18n_page(tit... | <|body_start_0|>
title = getattr(self, 'page_title', None)
languages = getattr(self, 'page_languages', None)
if not title:
languages = languages or [settings.LANGUAGE_CODE]
title = {language: factory.Faker('catch_phrase').evaluate(None, None, {'locale': language}) for lan... | Factories for page extensions have in common that: - they must create a related page with a title, - the related page may have to be placed below a "parent" page, - we may want to test the related page in several languages. All this is mutualized by inheriting from the present class. | PageExtensionDjangoModelFactory | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PageExtensionDjangoModelFactory:
"""Factories for page extensions have in common that: - they must create a related page with a title, - the related page may have to be placed below a "parent" page, - we may want to test the related page in several languages. All this is mutualized by inheriting ... | stack_v2_sparse_classes_36k_train_029119 | 11,346 | permissive | [
{
"docstring": "Automatically create a related page with the title (or random title if None) in all the requested languages",
"name": "extended_object",
"signature": "def extended_object(self)"
},
{
"docstring": "This hook method is called last when generating an instance from a factory. The sup... | 3 | null | Implement the Python class `PageExtensionDjangoModelFactory` described below.
Class description:
Factories for page extensions have in common that: - they must create a related page with a title, - the related page may have to be placed below a "parent" page, - we may want to test the related page in several languages... | Implement the Python class `PageExtensionDjangoModelFactory` described below.
Class description:
Factories for page extensions have in common that: - they must create a related page with a title, - the related page may have to be placed below a "parent" page, - we may want to test the related page in several languages... | f2d46fc46b271eb3b4d565039a29c15ba15f027c | <|skeleton|>
class PageExtensionDjangoModelFactory:
"""Factories for page extensions have in common that: - they must create a related page with a title, - the related page may have to be placed below a "parent" page, - we may want to test the related page in several languages. All this is mutualized by inheriting ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PageExtensionDjangoModelFactory:
"""Factories for page extensions have in common that: - they must create a related page with a title, - the related page may have to be placed below a "parent" page, - we may want to test the related page in several languages. All this is mutualized by inheriting from the pres... | the_stack_v2_python_sparse | src/richie/apps/core/factories.py | openfun/richie | train | 238 |
409ebe1d510a2644b274fbf98e60ac84f1bf76eb | [
"wx.Frame.__init__(self, None, title='Crosshair', style=wx.NO_BORDER)\nself.height_half = crosshair_height // 2\nself.width_half = crosshair_width // 2\nself.screenheight_half = screen_height // 2\nself.screenwidth_half = screen_width // 2\nself.thickness = thickness\nself.SetBackgroundColour(background_color)\nsel... | <|body_start_0|>
wx.Frame.__init__(self, None, title='Crosshair', style=wx.NO_BORDER)
self.height_half = crosshair_height // 2
self.width_half = crosshair_width // 2
self.screenheight_half = screen_height // 2
self.screenwidth_half = screen_width // 2
self.thickness = thi... | Crosshair | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Crosshair:
def __init__(self, x_pos=-1920, y_pos=0, screen_width=1920, screen_height=1080, title='Crosshair', background_color='#686868', crosshair_height=60, crosshair_width=60, thickness=7, hide_cursor=True):
"""A wxpython Crosshair that can flash red. :param x_pos: x position (default... | stack_v2_sparse_classes_36k_train_029120 | 2,843 | no_license | [
{
"docstring": "A wxpython Crosshair that can flash red. :param x_pos: x position (defaults to 1920 pixels left of main screen) :param y_pos: y position (defaults to 0) :param screen_width: size of screen in pixels :param screen_height: height of screen in pixels :param title: Not displayed externally. Defaults... | 3 | stack_v2_sparse_classes_30k_train_021553 | Implement the Python class `Crosshair` described below.
Class description:
Implement the Crosshair class.
Method signatures and docstrings:
- def __init__(self, x_pos=-1920, y_pos=0, screen_width=1920, screen_height=1080, title='Crosshair', background_color='#686868', crosshair_height=60, crosshair_width=60, thicknes... | Implement the Python class `Crosshair` described below.
Class description:
Implement the Crosshair class.
Method signatures and docstrings:
- def __init__(self, x_pos=-1920, y_pos=0, screen_width=1920, screen_height=1080, title='Crosshair', background_color='#686868', crosshair_height=60, crosshair_width=60, thicknes... | 4eec0ea2eb3dc287d475f9ab4e0b75259c51b309 | <|skeleton|>
class Crosshair:
def __init__(self, x_pos=-1920, y_pos=0, screen_width=1920, screen_height=1080, title='Crosshair', background_color='#686868', crosshair_height=60, crosshair_width=60, thickness=7, hide_cursor=True):
"""A wxpython Crosshair that can flash red. :param x_pos: x position (default... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Crosshair:
def __init__(self, x_pos=-1920, y_pos=0, screen_width=1920, screen_height=1080, title='Crosshair', background_color='#686868', crosshair_height=60, crosshair_width=60, thickness=7, hide_cursor=True):
"""A wxpython Crosshair that can flash red. :param x_pos: x position (defaults to 1920 pixe... | the_stack_v2_python_sparse | Graphics/CursorTask/WxCrosshair.py | heathzhang35/CCDLUtil | train | 0 | |
7c57ae52609c14193963537895761dfe748b258b | [
"if numRows == 0:\n return []\nres = [[1]]\nfor r in range(1, numRows):\n pre_list = res[-1]\n cur_list = [1] * (len(pre_list) + 1)\n for i in range(len(pre_list) - 1):\n cur_list[i + 1] = pre_list[i] + pre_list[i + 1]\n res.append(cur_list)\nreturn res",
"if rowIndex == 0:\n return [1]\n... | <|body_start_0|>
if numRows == 0:
return []
res = [[1]]
for r in range(1, numRows):
pre_list = res[-1]
cur_list = [1] * (len(pre_list) + 1)
for i in range(len(pre_list) - 1):
cur_list[i + 1] = pre_list[i] + pre_list[i + 1]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generate(self, numRows: int) -> List[List[int]]:
"""118"""
<|body_0|>
def getRow(self, rowIndex: int) -> List[int]:
"""119"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if numRows == 0:
return []
res = [[1]]
... | stack_v2_sparse_classes_36k_train_029121 | 949 | no_license | [
{
"docstring": "118",
"name": "generate",
"signature": "def generate(self, numRows: int) -> List[List[int]]"
},
{
"docstring": "119",
"name": "getRow",
"signature": "def getRow(self, rowIndex: int) -> List[int]"
}
] | 2 | stack_v2_sparse_classes_30k_train_015103 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate(self, numRows: int) -> List[List[int]]: 118
- def getRow(self, rowIndex: int) -> List[int]: 119 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate(self, numRows: int) -> List[List[int]]: 118
- def getRow(self, rowIndex: int) -> List[int]: 119
<|skeleton|>
class Solution:
def generate(self, numRows: int) -... | 8290ad1c763d9f7c7f7bed63426b4769b34fd2fc | <|skeleton|>
class Solution:
def generate(self, numRows: int) -> List[List[int]]:
"""118"""
<|body_0|>
def getRow(self, rowIndex: int) -> List[int]:
"""119"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def generate(self, numRows: int) -> List[List[int]]:
"""118"""
if numRows == 0:
return []
res = [[1]]
for r in range(1, numRows):
pre_list = res[-1]
cur_list = [1] * (len(pre_list) + 1)
for i in range(len(pre_list) - 1):... | the_stack_v2_python_sparse | array_118_yanghuiTriangle.py | screnary/Algorithm_python | train | 0 | |
c84e92eb8e63816fa5058775f1be4baa582c6dce | [
"for i in range(len(nums)):\n for j in range(i + 1, len(nums)):\n if target == nums[i] + nums[j] and i != j:\n print(i, j)\n return (i, j)",
"sumdict = {}\nfor i, num in enumerate(nums):\n complement = target - num\n print(sumdict)\n print(complement, sumdict.keys())\n ... | <|body_start_0|>
for i in range(len(nums)):
for j in range(i + 1, len(nums)):
if target == nums[i] + nums[j] and i != j:
print(i, j)
return (i, j)
<|end_body_0|>
<|body_start_1|>
sumdict = {}
for i, num in enumerate(nums):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSumHash(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_36k_train_029122 | 1,465 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSumHash",
"signature": "def twoSumHash(self, nums, target... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def twoSumHash(self, nums, target): :type nums: List[int] :type target: int :rtype: Li... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def twoSumHash(self, nums, target): :type nums: List[int] :type target: int :rtype: Li... | 786075e0f9f61cf062703bc0b41cc3191d77f033 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSumHash(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
for i in range(len(nums)):
for j in range(i + 1, len(nums)):
if target == nums[i] + nums[j] and i != j:
print(i, j)
retu... | the_stack_v2_python_sparse | 1_TwoSum.py | Anirban2404/LeetCodePractice | train | 1 | |
f760ba04c172b5543705846b0de53713ebbab6bd | [
"self.dll = DLL()\nself.mapper = {}\nself.capacity = capacity\nself.count = 0",
"if key in self.mapper:\n node = self.mapper[key]\n self.dll.deleteNode(node)\n self.dll.addNode(node)\n return self.mapper[key].val[1]\nreturn -1",
"if key in self.mapper:\n node = self.mapper[key]\n self.dll.dele... | <|body_start_0|>
self.dll = DLL()
self.mapper = {}
self.capacity = capacity
self.count = 0
<|end_body_0|>
<|body_start_1|>
if key in self.mapper:
node = self.mapper[key]
self.dll.deleteNode(node)
self.dll.addNode(node)
return self.... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_029123 | 2,310 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: void",
"name": "pu... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void
<|sk... | 3bfee704adb1d94efc8e531b732cf06c4f8aef0f | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.dll = DLL()
self.mapper = {}
self.capacity = capacity
self.count = 0
def get(self, key):
""":type key: int :rtype: int"""
if key in self.mapper:
node = self.mapper[ke... | the_stack_v2_python_sparse | lru.py | zopepy/leetcode | train | 0 | |
38ee80688ed3024f5c27cfa9d508b466a2220937 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn IosCompliancePolicy()",
"from .device_compliance_policy import DeviceCompliancePolicy\nfrom .device_threat_protection_level import DeviceThreatProtectionLevel\nfrom .required_password_type import RequiredPasswordType\nfrom .device_comp... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return IosCompliancePolicy()
<|end_body_0|>
<|body_start_1|>
from .device_compliance_policy import DeviceCompliancePolicy
from .device_threat_protection_level import DeviceThreatProtectionLevel... | This class contains compliance settings for IOS. | IosCompliancePolicy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IosCompliancePolicy:
"""This class contains compliance settings for IOS."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosCompliancePolicy:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse no... | stack_v2_sparse_classes_36k_train_029124 | 7,140 | 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: IosCompliancePolicy",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator... | 3 | null | Implement the Python class `IosCompliancePolicy` described below.
Class description:
This class contains compliance settings for IOS.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosCompliancePolicy: Creates a new instance of the appropriate class ba... | Implement the Python class `IosCompliancePolicy` described below.
Class description:
This class contains compliance settings for IOS.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosCompliancePolicy: Creates a new instance of the appropriate class ba... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class IosCompliancePolicy:
"""This class contains compliance settings for IOS."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosCompliancePolicy:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse no... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IosCompliancePolicy:
"""This class contains compliance settings for IOS."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosCompliancePolicy:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to ... | the_stack_v2_python_sparse | msgraph/generated/models/ios_compliance_policy.py | microsoftgraph/msgraph-sdk-python | train | 135 |
18b112c31fd0e296ea4d961051746ba8d8a7e86f | [
"headers = []\nfor field in self.get_export_fields():\n field_model = AidProject._meta.get_field(field.column_name)\n headers.append(field_model.verbose_name)\nreturn headers",
"field_name = self.get_field_name(field)\nmethod = getattr(self, 'dehydrate_%s' % field_name, None)\nif method is not None:\n re... | <|body_start_0|>
headers = []
for field in self.get_export_fields():
field_model = AidProject._meta.get_field(field.column_name)
headers.append(field_model.verbose_name)
return headers
<|end_body_0|>
<|body_start_1|>
field_name = self.get_field_name(field)
... | Resource for Export AidProject. | AidProjectResource | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AidProjectResource:
"""Resource for Export AidProject."""
def get_export_headers(self):
"""override get_export_headers() to translate field names."""
<|body_0|>
def export_field(self, field, obj):
"""override export_field() to translate field values."""
<... | stack_v2_sparse_classes_36k_train_029125 | 13,586 | permissive | [
{
"docstring": "override get_export_headers() to translate field names.",
"name": "get_export_headers",
"signature": "def get_export_headers(self)"
},
{
"docstring": "override export_field() to translate field values.",
"name": "export_field",
"signature": "def export_field(self, field, ... | 2 | stack_v2_sparse_classes_30k_train_000645 | Implement the Python class `AidProjectResource` described below.
Class description:
Resource for Export AidProject.
Method signatures and docstrings:
- def get_export_headers(self): override get_export_headers() to translate field names.
- def export_field(self, field, obj): override export_field() to translate field... | Implement the Python class `AidProjectResource` described below.
Class description:
Resource for Export AidProject.
Method signatures and docstrings:
- def get_export_headers(self): override get_export_headers() to translate field names.
- def export_field(self, field, obj): override export_field() to translate field... | af9f6e6e8b1918363793fbf291f3518ef1454169 | <|skeleton|>
class AidProjectResource:
"""Resource for Export AidProject."""
def get_export_headers(self):
"""override get_export_headers() to translate field names."""
<|body_0|>
def export_field(self, field, obj):
"""override export_field() to translate field values."""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AidProjectResource:
"""Resource for Export AidProject."""
def get_export_headers(self):
"""override get_export_headers() to translate field names."""
headers = []
for field in self.get_export_fields():
field_model = AidProject._meta.get_field(field.column_name)
... | the_stack_v2_python_sparse | src/aids/resources.py | MTES-MCT/aides-territoires | train | 21 |
9b6aa1307c3a22123aa6636db3c8baa06c2773ca | [
"self.value = value\nself.description = description\nself.default = default",
"v = '\"%s\"' % self.value if type(self.value) is str else str(self.value)\nd = {'value': v}\nd['default'] = ' (Default)' if self.default else ''\nd['description'] = ' %s' % self.description if self.description != None else ''\nd['link'... | <|body_start_0|>
self.value = value
self.description = description
self.default = default
<|end_body_0|>
<|body_start_1|>
v = '"%s"' % self.value if type(self.value) is str else str(self.value)
d = {'value': v}
d['default'] = ' (Default)' if self.default else ''
... | Class representing a value for an Option. | OptionValue | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptionValue:
"""Class representing a value for an Option."""
def __init__(self, value, description=None, default=False):
"""Initialisation. @param value The value. @param description (str) A description for this value. @param default (bool) If this value is the default value."""
... | stack_v2_sparse_classes_36k_train_029126 | 11,864 | permissive | [
{
"docstring": "Initialisation. @param value The value. @param description (str) A description for this value. @param default (bool) If this value is the default value.",
"name": "__init__",
"signature": "def __init__(self, value, description=None, default=False)"
},
{
"docstring": "Render this ... | 2 | stack_v2_sparse_classes_30k_train_005563 | Implement the Python class `OptionValue` described below.
Class description:
Class representing a value for an Option.
Method signatures and docstrings:
- def __init__(self, value, description=None, default=False): Initialisation. @param value The value. @param description (str) A description for this value. @param d... | Implement the Python class `OptionValue` described below.
Class description:
Class representing a value for an Option.
Method signatures and docstrings:
- def __init__(self, value, description=None, default=False): Initialisation. @param value The value. @param description (str) A description for this value. @param d... | c20c06b85bc04902134ab37442763ef6660a35f5 | <|skeleton|>
class OptionValue:
"""Class representing a value for an Option."""
def __init__(self, value, description=None, default=False):
"""Initialisation. @param value The value. @param description (str) A description for this value. @param default (bool) If this value is the default value."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OptionValue:
"""Class representing a value for an Option."""
def __init__(self, value, description=None, default=False):
"""Initialisation. @param value The value. @param description (str) A description for this value. @param default (bool) If this value is the default value."""
self.valu... | the_stack_v2_python_sparse | olof/configuration.py | Roel/Gyrid-server | train | 0 |
e1652dc5737322ed873006c08e6653036affc57f | [
"if username is None and password is None:\n username = account.username\n password = decrypt_password(account.data['gerrit_http_password'])\nreturn super(GerritClient, self).get_http_credentials(account=account, username=username, password=password)",
"super(GerritClient, self).process_http_error(request, ... | <|body_start_0|>
if username is None and password is None:
username = account.username
password = decrypt_password(account.data['gerrit_http_password'])
return super(GerritClient, self).get_http_credentials(account=account, username=username, password=password)
<|end_body_0|>
<|... | The Gerrit hosting service API client. | GerritClient | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GerritClient:
"""The Gerrit hosting service API client."""
def get_http_credentials(self, account, username=None, password=None, **kwargs):
"""Return credentials used to authenticate with the service. Unless an explicit username and password is provided, this will use the ones stored... | stack_v2_sparse_classes_36k_train_029127 | 26,166 | permissive | [
{
"docstring": "Return credentials used to authenticate with the service. Unless an explicit username and password is provided, this will use the ones stored for the account. Args: account (reviewboard.hostingsvcs.models.HostingServiceAccount): The stored authentication data for the service. username (unicode, ... | 2 | stack_v2_sparse_classes_30k_train_011062 | Implement the Python class `GerritClient` described below.
Class description:
The Gerrit hosting service API client.
Method signatures and docstrings:
- def get_http_credentials(self, account, username=None, password=None, **kwargs): Return credentials used to authenticate with the service. Unless an explicit usernam... | Implement the Python class `GerritClient` described below.
Class description:
The Gerrit hosting service API client.
Method signatures and docstrings:
- def get_http_credentials(self, account, username=None, password=None, **kwargs): Return credentials used to authenticate with the service. Unless an explicit usernam... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class GerritClient:
"""The Gerrit hosting service API client."""
def get_http_credentials(self, account, username=None, password=None, **kwargs):
"""Return credentials used to authenticate with the service. Unless an explicit username and password is provided, this will use the ones stored... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GerritClient:
"""The Gerrit hosting service API client."""
def get_http_credentials(self, account, username=None, password=None, **kwargs):
"""Return credentials used to authenticate with the service. Unless an explicit username and password is provided, this will use the ones stored for the acco... | the_stack_v2_python_sparse | reviewboard/hostingsvcs/gerrit.py | reviewboard/reviewboard | train | 1,141 |
35b3e6750d559d2d5bf0f9e7e5c1abda5eb1a349 | [
"if root == None:\n return root\nout = self.dfs(root)\nprev = root\nif len(out) <= 1:\n return root\nelse:\n for e in out[1:]:\n prev.left = None\n prev.right = TreeNode(e)\n prev = prev.right",
"out_lst = [node.val]\nif node.left:\n out_lst += self.dfs(node.left)\nif node.right:\... | <|body_start_0|>
if root == None:
return root
out = self.dfs(root)
prev = root
if len(out) <= 1:
return root
else:
for e in out[1:]:
prev.left = None
prev.right = TreeNode(e)
prev = prev.right
<|e... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def flatten(self, root):
""":type root: TreeNode :rtype: None Do not return anything, modify root in-place instead."""
<|body_0|>
def dfs(self, node):
"""得到这个node下所有节点"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root == None:
... | stack_v2_sparse_classes_36k_train_029128 | 1,076 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: None Do not return anything, modify root in-place instead.",
"name": "flatten",
"signature": "def flatten(self, root)"
},
{
"docstring": "得到这个node下所有节点",
"name": "dfs",
"signature": "def dfs(self, node)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flatten(self, root): :type root: TreeNode :rtype: None Do not return anything, modify root in-place instead.
- def dfs(self, node): 得到这个node下所有节点 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flatten(self, root): :type root: TreeNode :rtype: None Do not return anything, modify root in-place instead.
- def dfs(self, node): 得到这个node下所有节点
<|skeleton|>
class Solution... | f1a3930c571a6d062208ee1c1aadfe93a5684c40 | <|skeleton|>
class Solution:
def flatten(self, root):
""":type root: TreeNode :rtype: None Do not return anything, modify root in-place instead."""
<|body_0|>
def dfs(self, node):
"""得到这个node下所有节点"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def flatten(self, root):
""":type root: TreeNode :rtype: None Do not return anything, modify root in-place instead."""
if root == None:
return root
out = self.dfs(root)
prev = root
if len(out) <= 1:
return root
else:
... | the_stack_v2_python_sparse | solution/problem 82.py | Fay321/leetcode-exercise | train | 0 | |
1baadf850299d55bf32988b389f9a27bb5b1e3b4 | [
"borders = np.arange(10)\n'when'\ntuples = get_buckets(borders)\n'then'\nself.assertEqual(str(tuples), str([(np.nan, 0.0), (0.0, 1.0), (1.0, 2.0), (2.0, 3.0), (3.0, 4.0), (4.0, 5.0), (5.0, 6.0), (6.0, 7.0), (7.0, 8.0), (8.0, 9.0), (9.0, np.nan)]))",
"b = CircularBuffer(10)\nb2 = CircularBuffer(10)\n'when'\nfor i ... | <|body_start_0|>
borders = np.arange(10)
'when'
tuples = get_buckets(borders)
'then'
self.assertEqual(str(tuples), str([(np.nan, 0.0), (0.0, 1.0), (1.0, 2.0), (2.0, 3.0), (3.0, 4.0), (4.0, 5.0), (5.0, 6.0), (6.0, 7.0), (7.0, 8.0), (8.0, 9.0), (9.0, np.nan)]))
<|end_body_0|>
<|bo... | TestNumpyUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestNumpyUtils:
def test_bucketing(self):
"""given"""
<|body_0|>
def test_circular_buffer(self):
"""given"""
<|body_1|>
def test_one_hot(self):
"""given integer numbers"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
borders = n... | stack_v2_sparse_classes_36k_train_029129 | 1,313 | permissive | [
{
"docstring": "given",
"name": "test_bucketing",
"signature": "def test_bucketing(self)"
},
{
"docstring": "given",
"name": "test_circular_buffer",
"signature": "def test_circular_buffer(self)"
},
{
"docstring": "given integer numbers",
"name": "test_one_hot",
"signature... | 3 | null | Implement the Python class `TestNumpyUtils` described below.
Class description:
Implement the TestNumpyUtils class.
Method signatures and docstrings:
- def test_bucketing(self): given
- def test_circular_buffer(self): given
- def test_one_hot(self): given integer numbers | Implement the Python class `TestNumpyUtils` described below.
Class description:
Implement the TestNumpyUtils class.
Method signatures and docstrings:
- def test_bucketing(self): given
- def test_circular_buffer(self): given
- def test_one_hot(self): given integer numbers
<|skeleton|>
class TestNumpyUtils:
def t... | 650a8e8f77bc4d71136518d1c7ee65c194a99cf0 | <|skeleton|>
class TestNumpyUtils:
def test_bucketing(self):
"""given"""
<|body_0|>
def test_circular_buffer(self):
"""given"""
<|body_1|>
def test_one_hot(self):
"""given integer numbers"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestNumpyUtils:
def test_bucketing(self):
"""given"""
borders = np.arange(10)
'when'
tuples = get_buckets(borders)
'then'
self.assertEqual(str(tuples), str([(np.nan, 0.0), (0.0, 1.0), (1.0, 2.0), (2.0, 3.0), (3.0, 4.0), (4.0, 5.0), (5.0, 6.0), (6.0, 7.0), (7.0, ... | the_stack_v2_python_sparse | pandas-ml-common/pandas_ml_common_test/unit/utils/test_numpy.py | jcoffi/pandas-ml-quant | train | 0 | |
dade4a359d421bd76494d53e10649ef2d7a32b09 | [
"super(QFlowWidgetItem, self).__init__(widget)\nself.data = data\nself._cached_hint = QSize()\nself._cached_max = QSize()\nself._cached_min = QSize()",
"if not self._cached_max.isValid():\n self._cached_max = super(QFlowWidgetItem, self).maximumSize()\nreturn self._cached_max",
"if not self._cached_min.isVal... | <|body_start_0|>
super(QFlowWidgetItem, self).__init__(widget)
self.data = data
self._cached_hint = QSize()
self._cached_max = QSize()
self._cached_min = QSize()
<|end_body_0|>
<|body_start_1|>
if not self._cached_max.isValid():
self._cached_max = super(QFlow... | A custom QWidgetItem for use with the QFlowLayout. | QFlowWidgetItem | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QFlowWidgetItem:
"""A custom QWidgetItem for use with the QFlowLayout."""
def __init__(self, widget, data):
"""Initialize a QFlowWidgetItem. Parameters ---------- widget : QWidget The widget to manage with this item. data : FlowLayoutData The layout data struct associated with this i... | stack_v2_sparse_classes_36k_train_029130 | 39,042 | permissive | [
{
"docstring": "Initialize a QFlowWidgetItem. Parameters ---------- widget : QWidget The widget to manage with this item. data : FlowLayoutData The layout data struct associated with this item.",
"name": "__init__",
"signature": "def __init__(self, widget, data)"
},
{
"docstring": "Reimplemented... | 6 | null | Implement the Python class `QFlowWidgetItem` described below.
Class description:
A custom QWidgetItem for use with the QFlowLayout.
Method signatures and docstrings:
- def __init__(self, widget, data): Initialize a QFlowWidgetItem. Parameters ---------- widget : QWidget The widget to manage with this item. data : Flo... | Implement the Python class `QFlowWidgetItem` described below.
Class description:
A custom QWidgetItem for use with the QFlowLayout.
Method signatures and docstrings:
- def __init__(self, widget, data): Initialize a QFlowWidgetItem. Parameters ---------- widget : QWidget The widget to manage with this item. data : Flo... | 1544e7fb371b8f941cfa2fde682795e479380284 | <|skeleton|>
class QFlowWidgetItem:
"""A custom QWidgetItem for use with the QFlowLayout."""
def __init__(self, widget, data):
"""Initialize a QFlowWidgetItem. Parameters ---------- widget : QWidget The widget to manage with this item. data : FlowLayoutData The layout data struct associated with this i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QFlowWidgetItem:
"""A custom QWidgetItem for use with the QFlowLayout."""
def __init__(self, widget, data):
"""Initialize a QFlowWidgetItem. Parameters ---------- widget : QWidget The widget to manage with this item. data : FlowLayoutData The layout data struct associated with this item."""
... | the_stack_v2_python_sparse | enaml/qt/q_flow_layout.py | MatthieuDartiailh/enaml | train | 26 |
9f61664d8d4b343d7e687880daf78b9d2bf28696 | [
"self.config_entry = entry\nself.client = Elgato(entry.data[CONF_HOST], port=entry.data[CONF_PORT], session=async_get_clientsession(hass))\nsuper().__init__(hass, LOGGER, name=f'{DOMAIN}_{entry.data[CONF_HOST]}', update_interval=SCAN_INTERVAL)",
"try:\n if self.has_battery is None:\n self.has_battery = ... | <|body_start_0|>
self.config_entry = entry
self.client = Elgato(entry.data[CONF_HOST], port=entry.data[CONF_PORT], session=async_get_clientsession(hass))
super().__init__(hass, LOGGER, name=f'{DOMAIN}_{entry.data[CONF_HOST]}', update_interval=SCAN_INTERVAL)
<|end_body_0|>
<|body_start_1|>
... | Class to manage fetching Elgato data. | ElgatoDataUpdateCoordinator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElgatoDataUpdateCoordinator:
"""Class to manage fetching Elgato data."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Initialize the coordinator."""
<|body_0|>
async def _async_update_data(self) -> ElgatoData:
"""Fetch data from the Elg... | stack_v2_sparse_classes_36k_train_029131 | 1,971 | permissive | [
{
"docstring": "Initialize the coordinator.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None"
},
{
"docstring": "Fetch data from the Elgato device.",
"name": "_async_update_data",
"signature": "async def _async_update_data(self) -> E... | 2 | stack_v2_sparse_classes_30k_train_002146 | Implement the Python class `ElgatoDataUpdateCoordinator` described below.
Class description:
Class to manage fetching Elgato data.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None: Initialize the coordinator.
- async def _async_update_data(self) -> ElgatoData: Fe... | Implement the Python class `ElgatoDataUpdateCoordinator` described below.
Class description:
Class to manage fetching Elgato data.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None: Initialize the coordinator.
- async def _async_update_data(self) -> ElgatoData: Fe... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ElgatoDataUpdateCoordinator:
"""Class to manage fetching Elgato data."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Initialize the coordinator."""
<|body_0|>
async def _async_update_data(self) -> ElgatoData:
"""Fetch data from the Elg... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElgatoDataUpdateCoordinator:
"""Class to manage fetching Elgato data."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Initialize the coordinator."""
self.config_entry = entry
self.client = Elgato(entry.data[CONF_HOST], port=entry.data[CONF_PORT], session... | the_stack_v2_python_sparse | homeassistant/components/elgato/coordinator.py | home-assistant/core | train | 35,501 |
e98c17b010c1258e3c9b144718ae074979299732 | [
"self.needed_locks = {}\nif self.op.duration <= 0:\n raise errors.OpPrereqError('Duration must be greater than zero')\nif not self.op.no_locks and (self.op.on_nodes or self.op.on_master):\n self.needed_locks[locking.LEVEL_NODE] = []\nself.op.on_node_uuids = []\nif self.op.on_nodes:\n self.op.on_node_uuids,... | <|body_start_0|>
self.needed_locks = {}
if self.op.duration <= 0:
raise errors.OpPrereqError('Duration must be greater than zero')
if not self.op.no_locks and (self.op.on_nodes or self.op.on_master):
self.needed_locks[locking.LEVEL_NODE] = []
self.op.on_node_uuids... | Sleep for a specified amount of time. This LU sleeps on the master and/or nodes for a specified amount of time. | LUTestDelay | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LUTestDelay:
"""Sleep for a specified amount of time. This LU sleeps on the master and/or nodes for a specified amount of time."""
def ExpandNames(self):
"""Expand names and set required locks. This expands the node list, if any."""
<|body_0|>
def _InterruptibleDelay(sel... | stack_v2_sparse_classes_36k_train_029132 | 16,228 | permissive | [
{
"docstring": "Expand names and set required locks. This expands the node list, if any.",
"name": "ExpandNames",
"signature": "def ExpandNames(self)"
},
{
"docstring": "Delays but provides the mechanisms necessary to interrupt the delay as needed.",
"name": "_InterruptibleDelay",
"signa... | 5 | stack_v2_sparse_classes_30k_val_000855 | Implement the Python class `LUTestDelay` described below.
Class description:
Sleep for a specified amount of time. This LU sleeps on the master and/or nodes for a specified amount of time.
Method signatures and docstrings:
- def ExpandNames(self): Expand names and set required locks. This expands the node list, if an... | Implement the Python class `LUTestDelay` described below.
Class description:
Sleep for a specified amount of time. This LU sleeps on the master and/or nodes for a specified amount of time.
Method signatures and docstrings:
- def ExpandNames(self): Expand names and set required locks. This expands the node list, if an... | 456ea285a7583183c2c8e5bcffe9006ec8a9d658 | <|skeleton|>
class LUTestDelay:
"""Sleep for a specified amount of time. This LU sleeps on the master and/or nodes for a specified amount of time."""
def ExpandNames(self):
"""Expand names and set required locks. This expands the node list, if any."""
<|body_0|>
def _InterruptibleDelay(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LUTestDelay:
"""Sleep for a specified amount of time. This LU sleeps on the master and/or nodes for a specified amount of time."""
def ExpandNames(self):
"""Expand names and set required locks. This expands the node list, if any."""
self.needed_locks = {}
if self.op.duration <= 0:... | the_stack_v2_python_sparse | lib/cmdlib/test.py | ganeti/ganeti | train | 465 |
c512c29e936921f2ad8fd937d3100dea310ce9eb | [
"response = await self.client(Operation(operation_type='RUNNER_READ', kwargs={'runner_id': runner_id}))\nself.set_header('Content-Type', 'application/json; charset=UTF-8')\nself.write(response)",
"response = await self.client(Operation(operation_type='RUNNER_DELETE', kwargs={'runner_id': runner_id, 'remove': True... | <|body_start_0|>
response = await self.client(Operation(operation_type='RUNNER_READ', kwargs={'runner_id': runner_id}))
self.set_header('Content-Type', 'application/json; charset=UTF-8')
self.write(response)
<|end_body_0|>
<|body_start_1|>
response = await self.client(Operation(operatio... | RunnerAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunnerAPI:
async def get(self, runner_id):
"""--- summary: Get a runner parameters: - name: runner_id in: path required: true description: The ID of the Runner type: string responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/4... | stack_v2_sparse_classes_36k_train_029133 | 6,146 | permissive | [
{
"docstring": "--- summary: Get a runner parameters: - name: runner_id in: path required: true description: The ID of the Runner type: string responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/404Error' 50x: $ref: '#/definitions/50xError' tags: - R... | 3 | stack_v2_sparse_classes_30k_train_002783 | Implement the Python class `RunnerAPI` described below.
Class description:
Implement the RunnerAPI class.
Method signatures and docstrings:
- async def get(self, runner_id): --- summary: Get a runner parameters: - name: runner_id in: path required: true description: The ID of the Runner type: string responses: 200: d... | Implement the Python class `RunnerAPI` described below.
Class description:
Implement the RunnerAPI class.
Method signatures and docstrings:
- async def get(self, runner_id): --- summary: Get a runner parameters: - name: runner_id in: path required: true description: The ID of the Runner type: string responses: 200: d... | a5fd2dcc2444409e243d3fdaa43d86695e5cb142 | <|skeleton|>
class RunnerAPI:
async def get(self, runner_id):
"""--- summary: Get a runner parameters: - name: runner_id in: path required: true description: The ID of the Runner type: string responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/4... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RunnerAPI:
async def get(self, runner_id):
"""--- summary: Get a runner parameters: - name: runner_id in: path required: true description: The ID of the Runner type: string responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/404Error' 50x: ... | the_stack_v2_python_sparse | src/app/beer_garden/api/http/handlers/vbeta/runner.py | beer-garden/beer-garden | train | 254 | |
9f3c1acc7c1a14ab6efc85ddf6f00b4d87e0e44e | [
"if strs == []:\n return ''\ndict = {}\ncommon = len(strs[0])\nfor i, s in enumerate(strs):\n count = 0\n for j, c in enumerate(s):\n if count >= common:\n break\n if dict.get(j) == None:\n if i == 0:\n dict[j] = c\n count += 1\n ... | <|body_start_0|>
if strs == []:
return ''
dict = {}
common = len(strs[0])
for i, s in enumerate(strs):
count = 0
for j, c in enumerate(s):
if count >= common:
break
if dict.get(j) == None:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestCommonPrefix_myself(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_1|>
def longestCommonPrefix_heng(self, s1):
""":type strs... | stack_v2_sparse_classes_36k_train_029134 | 3,533 | no_license | [
{
"docstring": ":type strs: List[str] :rtype: str",
"name": "longestCommonPrefix_myself",
"signature": "def longestCommonPrefix_myself(self, strs)"
},
{
"docstring": ":type strs: List[str] :rtype: str",
"name": "longestCommonPrefix",
"signature": "def longestCommonPrefix(self, strs)"
}... | 3 | stack_v2_sparse_classes_30k_train_019416 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix_myself(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix_h... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix_myself(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix_h... | 93266095329e2e8e949a72371b88b07382a60e0d | <|skeleton|>
class Solution:
def longestCommonPrefix_myself(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_1|>
def longestCommonPrefix_heng(self, s1):
""":type strs... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestCommonPrefix_myself(self, strs):
""":type strs: List[str] :rtype: str"""
if strs == []:
return ''
dict = {}
common = len(strs[0])
for i, s in enumerate(strs):
count = 0
for j, c in enumerate(s):
if... | the_stack_v2_python_sparse | longestCommonPrefix.py | shivangi-prog/leetcode | train | 0 | |
47736eafa758724b7c78c98cb372047dad6c43f8 | [
"num_idx_map = {}\nfor idx, num in enumerate(nums):\n diff = target - num\n if diff in num_idx_map:\n return [num_idx_map[diff], idx]\n else:\n num_idx_map[num] = idx",
"pairs = [(num, i) for i, num in enumerate(nums)]\nnums = sorted(pairs)\nprint(nums)\nbeg, end = (0, len(nums) - 1)\nwhile... | <|body_start_0|>
num_idx_map = {}
for idx, num in enumerate(nums):
diff = target - num
if diff in num_idx_map:
return [num_idx_map[diff], idx]
else:
num_idx_map[num] = idx
<|end_body_0|>
<|body_start_1|>
pairs = [(num, i) for i... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
"""注意这题目 letcode 不是有序的，剑指offer 上的是有序的。一种方式是用 hash 来做 :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum1(self, nums, target):
"""注意这题目 letcode 不是有序的，剑指offer 上的是有序的。可以先排序来做。之后首位指针向中间归并 :type num... | stack_v2_sparse_classes_36k_train_029135 | 1,695 | permissive | [
{
"docstring": "注意这题目 letcode 不是有序的，剑指offer 上的是有序的。一种方式是用 hash 来做 :type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, nums, target)"
},
{
"docstring": "注意这题目 letcode 不是有序的，剑指offer 上的是有序的。可以先排序来做。之后首位指针向中间归并 :type nums: List[int] :type targ... | 2 | stack_v2_sparse_classes_30k_train_010226 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): 注意这题目 letcode 不是有序的，剑指offer 上的是有序的。一种方式是用 hash 来做 :type nums: List[int] :type target: int :rtype: List[int]
- def twoSum1(self, nums, target): 注意这... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): 注意这题目 letcode 不是有序的，剑指offer 上的是有序的。一种方式是用 hash 来做 :type nums: List[int] :type target: int :rtype: List[int]
- def twoSum1(self, nums, target): 注意这... | 3469a79c34b6c08ae52797c3974b49fbfa8cca51 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
"""注意这题目 letcode 不是有序的，剑指offer 上的是有序的。一种方式是用 hash 来做 :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum1(self, nums, target):
"""注意这题目 letcode 不是有序的，剑指offer 上的是有序的。可以先排序来做。之后首位指针向中间归并 :type num... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def twoSum(self, nums, target):
"""注意这题目 letcode 不是有序的，剑指offer 上的是有序的。一种方式是用 hash 来做 :type nums: List[int] :type target: int :rtype: List[int]"""
num_idx_map = {}
for idx, num in enumerate(nums):
diff = target - num
if diff in num_idx_map:
... | the_stack_v2_python_sparse | 剑指offer/41_1_TwoNumbersWithSum(和为s的两个数字VS和为s的连续正数序列).py | Mark24Code/python_data_structures_and_algorithms | train | 1 | |
a577d974c9da21494dcab37849ef72837c034fa8 | [
"db_start = time()\nprint('database start time is {}'.format(db_start))\ntry:\n user_profile = UserProfile.objects.get(pk=pk)\nexcept UserProfile.DoesNotExist:\n return Response({'message': 'The User Profile does not exist'}, status=status.HTTP_404_NOT_FOUND)\ndb_time = time() - db_start\nprint('database acce... | <|body_start_0|>
db_start = time()
print('database start time is {}'.format(db_start))
try:
user_profile = UserProfile.objects.get(pk=pk)
except UserProfile.DoesNotExist:
return Response({'message': 'The User Profile does not exist'}, status=status.HTTP_404_NOT_FO... | UserProfileView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserProfileView:
def get(self, request, pk, *args, **kwargs):
""":param request: :param pk: :param args: :param kwargs: :return:"""
<|body_0|>
def post(self, request, *args, **kwargs):
""":param request: :param pk: :param args: :param kwargs: :return:"""
<|bo... | stack_v2_sparse_classes_36k_train_029136 | 2,896 | no_license | [
{
"docstring": ":param request: :param pk: :param args: :param kwargs: :return:",
"name": "get",
"signature": "def get(self, request, pk, *args, **kwargs)"
},
{
"docstring": ":param request: :param pk: :param args: :param kwargs: :return:",
"name": "post",
"signature": "def post(self, re... | 4 | stack_v2_sparse_classes_30k_train_021236 | Implement the Python class `UserProfileView` described below.
Class description:
Implement the UserProfileView class.
Method signatures and docstrings:
- def get(self, request, pk, *args, **kwargs): :param request: :param pk: :param args: :param kwargs: :return:
- def post(self, request, *args, **kwargs): :param requ... | Implement the Python class `UserProfileView` described below.
Class description:
Implement the UserProfileView class.
Method signatures and docstrings:
- def get(self, request, pk, *args, **kwargs): :param request: :param pk: :param args: :param kwargs: :return:
- def post(self, request, *args, **kwargs): :param requ... | 1808c866a28ae1d9424d6d929890688b95cb7605 | <|skeleton|>
class UserProfileView:
def get(self, request, pk, *args, **kwargs):
""":param request: :param pk: :param args: :param kwargs: :return:"""
<|body_0|>
def post(self, request, *args, **kwargs):
""":param request: :param pk: :param args: :param kwargs: :return:"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserProfileView:
def get(self, request, pk, *args, **kwargs):
""":param request: :param pk: :param args: :param kwargs: :return:"""
db_start = time()
print('database start time is {}'.format(db_start))
try:
user_profile = UserProfile.objects.get(pk=pk)
excep... | the_stack_v2_python_sparse | assignment/promantus/views.py | kshitijParashar/PromantusApp | train | 0 | |
7f43f15cf9e55c8a9c3151392086d821effb23ff | [
"self.task.set_status(hd_fields.TaskStatus.Running)\nself.task.save()\ndriver = self._get_driver('node')\nif driver is None:\n self.task.set_status(hd_fields.TaskStatus.Complete)\n self.task.add_status_msg(msg='No node driver enabled, ending task.', error=True, ctx=str(self.task.get_id()), ctx_type='task')\n ... | <|body_start_0|>
self.task.set_status(hd_fields.TaskStatus.Running)
self.task.save()
driver = self._get_driver('node')
if driver is None:
self.task.set_status(hd_fields.TaskStatus.Complete)
self.task.add_status_msg(msg='No node driver enabled, ending task.', error... | Action to configure site wide/inter-node settings. | PrepareSite | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrepareSite:
"""Action to configure site wide/inter-node settings."""
def start(self):
"""Start executing this action in the context of the local task."""
<|body_0|>
def step_configureprovisioner(self, driver):
"""Run the ConfigureNodeProvisioner step of this act... | stack_v2_sparse_classes_36k_train_029137 | 47,038 | permissive | [
{
"docstring": "Start executing this action in the context of the local task.",
"name": "start",
"signature": "def start(self)"
},
{
"docstring": "Run the ConfigureNodeProvisioner step of this action. :param driver: The driver instance to use for execution.",
"name": "step_configureprovision... | 4 | null | Implement the Python class `PrepareSite` described below.
Class description:
Action to configure site wide/inter-node settings.
Method signatures and docstrings:
- def start(self): Start executing this action in the context of the local task.
- def step_configureprovisioner(self, driver): Run the ConfigureNodeProvisi... | Implement the Python class `PrepareSite` described below.
Class description:
Action to configure site wide/inter-node settings.
Method signatures and docstrings:
- def start(self): Start executing this action in the context of the local task.
- def step_configureprovisioner(self, driver): Run the ConfigureNodeProvisi... | f99abfa4337f8cbb591513aac404b11208d4187c | <|skeleton|>
class PrepareSite:
"""Action to configure site wide/inter-node settings."""
def start(self):
"""Start executing this action in the context of the local task."""
<|body_0|>
def step_configureprovisioner(self, driver):
"""Run the ConfigureNodeProvisioner step of this act... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrepareSite:
"""Action to configure site wide/inter-node settings."""
def start(self):
"""Start executing this action in the context of the local task."""
self.task.set_status(hd_fields.TaskStatus.Running)
self.task.save()
driver = self._get_driver('node')
if drive... | the_stack_v2_python_sparse | python/drydock_provisioner/orchestrator/actions/orchestrator.py | airshipit/drydock | train | 13 |
b62173335183be65b5f41cc1779a5b84b3e2cbfb | [
"super(RainbowDQN, self).__init__()\nobs_shape, action_shape = (squeeze(obs_shape), squeeze(action_shape))\nif head_hidden_size is None:\n head_hidden_size = encoder_hidden_size_list[-1]\nif isinstance(obs_shape, int) or len(obs_shape) == 1:\n self.encoder = FCEncoder(obs_shape, encoder_hidden_size_list, acti... | <|body_start_0|>
super(RainbowDQN, self).__init__()
obs_shape, action_shape = (squeeze(obs_shape), squeeze(action_shape))
if head_hidden_size is None:
head_hidden_size = encoder_hidden_size_list[-1]
if isinstance(obs_shape, int) or len(obs_shape) == 1:
self.encode... | Overview: RainbowDQN network (C51 + Dueling + Noisy Block) .. note:: RainbowDQN contains dueling architecture by default | RainbowDQN | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RainbowDQN:
"""Overview: RainbowDQN network (C51 + Dueling + Noisy Block) .. note:: RainbowDQN contains dueling architecture by default"""
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], he... | stack_v2_sparse_classes_36k_train_029138 | 30,380 | permissive | [
{
"docstring": "Overview: Init the Rainbow Model according to arguments. Arguments: - obs_shape (:obj:`Union[int, SequenceType]`): Observation space shape. - action_shape (:obj:`Union[int, SequenceType]`): Action space shape. - encoder_hidden_size_list (:obj:`SequenceType`): Collection of ``hidden_size`` to pas... | 2 | stack_v2_sparse_classes_30k_train_008113 | Implement the Python class `RainbowDQN` described below.
Class description:
Overview: RainbowDQN network (C51 + Dueling + Noisy Block) .. note:: RainbowDQN contains dueling architecture by default
Method signatures and docstrings:
- def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, Sequ... | Implement the Python class `RainbowDQN` described below.
Class description:
Overview: RainbowDQN network (C51 + Dueling + Noisy Block) .. note:: RainbowDQN contains dueling architecture by default
Method signatures and docstrings:
- def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, Sequ... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class RainbowDQN:
"""Overview: RainbowDQN network (C51 + Dueling + Noisy Block) .. note:: RainbowDQN contains dueling architecture by default"""
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], he... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RainbowDQN:
"""Overview: RainbowDQN network (C51 + Dueling + Noisy Block) .. note:: RainbowDQN contains dueling architecture by default"""
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], head_hidden_siz... | the_stack_v2_python_sparse | ding/model/template/q_learning.py | shengxuesun/DI-engine | train | 1 |
f1d83757e80d1b5229afb869b35ddbd8d9df6dad | [
"player_id = current_user.get('player_id')\nif player_id:\n ticket = flexmatch.get_player_ticket(player_id)\n if ticket and ticket['TicketId'] == ticket_id:\n ret = dict(ticket_id=ticket['TicketId'], ticket_status=ticket['Status'], configuration_name=ticket['ConfigurationName'], players=ticket['Players... | <|body_start_0|>
player_id = current_user.get('player_id')
if player_id:
ticket = flexmatch.get_player_ticket(player_id)
if ticket and ticket['TicketId'] == ticket_id:
ret = dict(ticket_id=ticket['TicketId'], ticket_status=ticket['Status'], configuration_name=tick... | RUD API for flexmatch tickets. | FlexMatchTicketAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlexMatchTicketAPI:
"""RUD API for flexmatch tickets."""
def get(ticket_id):
"""Return the stored ticket if the calling player is a member of the ticket, either solo or via party"""
<|body_0|>
def delete(ticket_id):
"""Delete and cancel 'ticket_id' if caller is a... | stack_v2_sparse_classes_36k_train_029139 | 11,779 | permissive | [
{
"docstring": "Return the stored ticket if the calling player is a member of the ticket, either solo or via party",
"name": "get",
"signature": "def get(ticket_id)"
},
{
"docstring": "Delete and cancel 'ticket_id' if caller is allowed to do so.",
"name": "delete",
"signature": "def dele... | 3 | stack_v2_sparse_classes_30k_train_008002 | Implement the Python class `FlexMatchTicketAPI` described below.
Class description:
RUD API for flexmatch tickets.
Method signatures and docstrings:
- def get(ticket_id): Return the stored ticket if the calling player is a member of the ticket, either solo or via party
- def delete(ticket_id): Delete and cancel 'tick... | Implement the Python class `FlexMatchTicketAPI` described below.
Class description:
RUD API for flexmatch tickets.
Method signatures and docstrings:
- def get(ticket_id): Return the stored ticket if the calling player is a member of the ticket, either solo or via party
- def delete(ticket_id): Delete and cancel 'tick... | 2771bb46db7fd331448f9db3cfb257fab7f89bcc | <|skeleton|>
class FlexMatchTicketAPI:
"""RUD API for flexmatch tickets."""
def get(ticket_id):
"""Return the stored ticket if the calling player is a member of the ticket, either solo or via party"""
<|body_0|>
def delete(ticket_id):
"""Delete and cancel 'ticket_id' if caller is a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlexMatchTicketAPI:
"""RUD API for flexmatch tickets."""
def get(ticket_id):
"""Return the stored ticket if the calling player is a member of the ticket, either solo or via party"""
player_id = current_user.get('player_id')
if player_id:
ticket = flexmatch.get_player_t... | the_stack_v2_python_sparse | driftbase/api/matchmakers/flexmatch.py | directivegames/drift-base | train | 1 |
0d321699c64a7e3af7180aacae9be4171af93cd7 | [
"X = _is_dataframe(X)\nself.variables = _find_numerical_variables(X, self.variables)\n_check_contains_na(X, self.variables)\nreturn X",
"check_is_fitted(self)\nX = _is_dataframe(X)\n_check_contains_na(X, self.variables)\n_check_input_matches_training_df(X, self.input_shape_[1])\nreturn X"
] | <|body_start_0|>
X = _is_dataframe(X)
self.variables = _find_numerical_variables(X, self.variables)
_check_contains_na(X, self.variables)
return X
<|end_body_0|>
<|body_start_1|>
check_is_fitted(self)
X = _is_dataframe(X)
_check_contains_na(X, self.variables)
... | BaseNumericalTransformer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseNumericalTransformer:
def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame:
"""Fits the transformation to the DataFrame. Args: X: Pandas DataFrame to fit the transformation y: This parameter exists only for compatibility with sklearn.pipeline.Pipeline. Defaults... | stack_v2_sparse_classes_36k_train_029140 | 2,119 | permissive | [
{
"docstring": "Fits the transformation to the DataFrame. Args: X: Pandas DataFrame to fit the transformation y: This parameter exists only for compatibility with sklearn.pipeline.Pipeline. Defaults to None. Alternatively takes Pandas Series. Returns: DataFrame with fitted transformation",
"name": "fit",
... | 2 | stack_v2_sparse_classes_30k_train_021667 | Implement the Python class `BaseNumericalTransformer` described below.
Class description:
Implement the BaseNumericalTransformer class.
Method signatures and docstrings:
- def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame: Fits the transformation to the DataFrame. Args: X: Pandas DataFrame t... | Implement the Python class `BaseNumericalTransformer` described below.
Class description:
Implement the BaseNumericalTransformer class.
Method signatures and docstrings:
- def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame: Fits the transformation to the DataFrame. Args: X: Pandas DataFrame t... | 74a2902c129452c96cc434df70127b7fa61b7f8a | <|skeleton|>
class BaseNumericalTransformer:
def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame:
"""Fits the transformation to the DataFrame. Args: X: Pandas DataFrame to fit the transformation y: This parameter exists only for compatibility with sklearn.pipeline.Pipeline. Defaults... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseNumericalTransformer:
def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame:
"""Fits the transformation to the DataFrame. Args: X: Pandas DataFrame to fit the transformation y: This parameter exists only for compatibility with sklearn.pipeline.Pipeline. Defaults to None. Alte... | the_stack_v2_python_sparse | feature_engine/base_transformers.py | mlaricobar/feature_engine | train | 0 | |
f6ae82440e44f59504edf5f3797ea1269b00cd32 | [
"super().__init__(ui_obj=ui_obj, vertex=vertex, scale_factor=scale_factor, movable=movable, selectable=selectable, r=r)\nself.pen = pen\nself.brush = brush\nself.selected_pen = QtGui.QPen(QtCore.Qt.darkCyan)\nself.selected_pen.setWidth(6)\nself.selected_brush = QtGui.QBrush(QtCore.Qt.darkCyan)\nself.set_style()",
... | <|body_start_0|>
super().__init__(ui_obj=ui_obj, vertex=vertex, scale_factor=scale_factor, movable=movable, selectable=selectable, r=r)
self.pen = pen
self.brush = brush
self.selected_pen = QtGui.QPen(QtCore.Qt.darkCyan)
self.selected_pen.setWidth(6)
self.selected_brush =... | InteractiveOverlayColumn | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InteractiveOverlayColumn:
def __init__(self, ui_obj=None, vertex=None, scale_factor=1, movable=True, selectable=True, r=16, pen=QtGui.QPen(QtCore.Qt.red), brush=QtGui.QBrush(QtCore.Qt.red)):
"""Initialize a positional interactive column. Inherits GUI_custom_components.InteractiveColumn. ... | stack_v2_sparse_classes_36k_train_029141 | 26,668 | no_license | [
{
"docstring": "Initialize a positional interactive column. Inherits GUI_custom_components.InteractiveColumn. Is used to highlight atomic positions.",
"name": "__init__",
"signature": "def __init__(self, ui_obj=None, vertex=None, scale_factor=1, movable=True, selectable=True, r=16, pen=QtGui.QPen(QtCore... | 2 | stack_v2_sparse_classes_30k_train_001849 | Implement the Python class `InteractiveOverlayColumn` described below.
Class description:
Implement the InteractiveOverlayColumn class.
Method signatures and docstrings:
- def __init__(self, ui_obj=None, vertex=None, scale_factor=1, movable=True, selectable=True, r=16, pen=QtGui.QPen(QtCore.Qt.red), brush=QtGui.QBrus... | Implement the Python class `InteractiveOverlayColumn` described below.
Class description:
Implement the InteractiveOverlayColumn class.
Method signatures and docstrings:
- def __init__(self, ui_obj=None, vertex=None, scale_factor=1, movable=True, selectable=True, r=16, pen=QtGui.QPen(QtCore.Qt.red), brush=QtGui.QBrus... | 7fed6e5121180981ce67b1397ddd5ef54246e5eb | <|skeleton|>
class InteractiveOverlayColumn:
def __init__(self, ui_obj=None, vertex=None, scale_factor=1, movable=True, selectable=True, r=16, pen=QtGui.QPen(QtCore.Qt.red), brush=QtGui.QBrush(QtCore.Qt.red)):
"""Initialize a positional interactive column. Inherits GUI_custom_components.InteractiveColumn. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InteractiveOverlayColumn:
def __init__(self, ui_obj=None, vertex=None, scale_factor=1, movable=True, selectable=True, r=16, pen=QtGui.QPen(QtCore.Qt.red), brush=QtGui.QBrush(QtCore.Qt.red)):
"""Initialize a positional interactive column. Inherits GUI_custom_components.InteractiveColumn. Is used to hig... | the_stack_v2_python_sparse | GUI_custom_components.py | Haawk666/AutomAl_6000_thesis_version | train | 0 | |
4109b0a3748f7d5d98c91fd5f9cadfed173c5270 | [
"self.batteries = {}\nfor section in cfg.sections():\n parts = section.split('.')\n if parts[0] == 'battery':\n name = parts[1]\n empty = cfg.getint(section, 'empty')\n full = cfg.getint(section, 'full')\n self.batteries[name] = Battery(empty, full)\nself.BATT_LOW = 30\nself.screen... | <|body_start_0|>
self.batteries = {}
for section in cfg.sections():
parts = section.split('.')
if parts[0] == 'battery':
name = parts[1]
empty = cfg.getint(section, 'empty')
full = cfg.getint(section, 'full')
self.ba... | Contains the important state and functions for this script. | BatteryMonitor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatteryMonitor:
"""Contains the important state and functions for this script."""
def __init__(self, screen, cfg):
"""Constructor. @param screen: a curses window object on which the battery levels will be drawn. @param cfg: a RawConfigParser object that contains the battery configura... | stack_v2_sparse_classes_36k_train_029142 | 5,209 | no_license | [
{
"docstring": "Constructor. @param screen: a curses window object on which the battery levels will be drawn. @param cfg: a RawConfigParser object that contains the battery configuration information.",
"name": "__init__",
"signature": "def __init__(self, screen, cfg)"
},
{
"docstring": "A callba... | 4 | null | Implement the Python class `BatteryMonitor` described below.
Class description:
Contains the important state and functions for this script.
Method signatures and docstrings:
- def __init__(self, screen, cfg): Constructor. @param screen: a curses window object on which the battery levels will be drawn. @param cfg: a R... | Implement the Python class `BatteryMonitor` described below.
Class description:
Contains the important state and functions for this script.
Method signatures and docstrings:
- def __init__(self, screen, cfg): Constructor. @param screen: a curses window object on which the battery levels will be drawn. @param cfg: a R... | 52bacd9f58524090e0ab421a47714629249ca273 | <|skeleton|>
class BatteryMonitor:
"""Contains the important state and functions for this script."""
def __init__(self, screen, cfg):
"""Constructor. @param screen: a curses window object on which the battery levels will be drawn. @param cfg: a RawConfigParser object that contains the battery configura... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BatteryMonitor:
"""Contains the important state and functions for this script."""
def __init__(self, screen, cfg):
"""Constructor. @param screen: a curses window object on which the battery levels will be drawn. @param cfg: a RawConfigParser object that contains the battery configuration informat... | the_stack_v2_python_sparse | src/09-10/ubc-tbird-ros-pkg/sb_util/scripts/battery_monitor.py | jpearkes/snowbots | train | 0 |
e998b49a3db66c22905d0c817517699f4fdd9e84 | [
"self.anneal = cfg.MODEL.LOSSES.SA.ANNEAL\nself.metric = cfg.MODEL.LOSSES.SA.METRIC\nself.num_id = cfg.SOLVER.IMS_PER_BATCH // cfg.DATALOADER.NUM_INSTANCE",
"embedding = F.normalize(embedding, dim=1)\nfeat_dim = embedding.size(1)\nif comm.get_world_size() > 1:\n all_embedding = concat_all_gather(embedding)\n ... | <|body_start_0|>
self.anneal = cfg.MODEL.LOSSES.SA.ANNEAL
self.metric = cfg.MODEL.LOSSES.SA.METRIC
self.num_id = cfg.SOLVER.IMS_PER_BATCH // cfg.DATALOADER.NUM_INSTANCE
<|end_body_0|>
<|body_start_1|>
embedding = F.normalize(embedding, dim=1)
feat_dim = embedding.size(1)
... | PyTorch implementation of the Smooth-AP loss. implementation of the Smooth-AP loss. Takes as input the mini-batch of CNN-produced feature embeddings and returns the value of the Smooth-AP loss. The mini-batch must be formed of a defined number of classes. Each class must have the same number of instances represented in... | SmoothAP | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmoothAP:
"""PyTorch implementation of the Smooth-AP loss. implementation of the Smooth-AP loss. Takes as input the mini-batch of CNN-produced feature embeddings and returns the value of the Smooth-AP loss. The mini-batch must be formed of a defined number of classes. Each class must have the sam... | stack_v2_sparse_classes_36k_train_029143 | 10,777 | permissive | [
{
"docstring": "Parameters ---------- cfg: (cfgNode) anneal : float the temperature of the sigmoid that is used to smooth the ranking function batch_size : int the batch size being used num_id : int the number of different classes that are represented in the batch feat_dims : int the dimension of the input feat... | 2 | stack_v2_sparse_classes_30k_train_013498 | Implement the Python class `SmoothAP` described below.
Class description:
PyTorch implementation of the Smooth-AP loss. implementation of the Smooth-AP loss. Takes as input the mini-batch of CNN-produced feature embeddings and returns the value of the Smooth-AP loss. The mini-batch must be formed of a defined number o... | Implement the Python class `SmoothAP` described below.
Class description:
PyTorch implementation of the Smooth-AP loss. implementation of the Smooth-AP loss. Takes as input the mini-batch of CNN-produced feature embeddings and returns the value of the Smooth-AP loss. The mini-batch must be formed of a defined number o... | d0eaee768e0be606417a27ce5ea2b3071b5a9bc2 | <|skeleton|>
class SmoothAP:
"""PyTorch implementation of the Smooth-AP loss. implementation of the Smooth-AP loss. Takes as input the mini-batch of CNN-produced feature embeddings and returns the value of the Smooth-AP loss. The mini-batch must be formed of a defined number of classes. Each class must have the sam... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SmoothAP:
"""PyTorch implementation of the Smooth-AP loss. implementation of the Smooth-AP loss. Takes as input the mini-batch of CNN-produced feature embeddings and returns the value of the Smooth-AP loss. The mini-batch must be formed of a defined number of classes. Each class must have the same number of i... | the_stack_v2_python_sparse | fastreid/modeling/losses/smooth_ap.py | SZLSP/reid2020NAIC | train | 2 |
6d3cfb37fc16d04de4b9d20cfe7d7cfc5535aece | [
"clear_test_collections()\nwith patch('database.__set_collection_names', return_value=TEST_DB_NAMES):\n incorrect_names = database.import_data('', 'Products .csv', 'Customers .csv', 'Rentals .csv')\nself.assertEqual([(0, 0, 0), (1, 1, 1)], incorrect_names)\nwith patch('database.__set_collection_names', return_va... | <|body_start_0|>
clear_test_collections()
with patch('database.__set_collection_names', return_value=TEST_DB_NAMES):
incorrect_names = database.import_data('', 'Products .csv', 'Customers .csv', 'Rentals .csv')
self.assertEqual([(0, 0, 0), (1, 1, 1)], incorrect_names)
with pa... | Class for unit tests for database.py | DatabaseUnitTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatabaseUnitTest:
"""Class for unit tests for database.py"""
def test_import_data(self):
"""Test that import_data imports csv into database"""
<|body_0|>
def test_show_available_products(self):
"""Tests show_available_products"""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k_train_029144 | 7,040 | no_license | [
{
"docstring": "Test that import_data imports csv into database",
"name": "test_import_data",
"signature": "def test_import_data(self)"
},
{
"docstring": "Tests show_available_products",
"name": "test_show_available_products",
"signature": "def test_show_available_products(self)"
},
... | 3 | null | Implement the Python class `DatabaseUnitTest` described below.
Class description:
Class for unit tests for database.py
Method signatures and docstrings:
- def test_import_data(self): Test that import_data imports csv into database
- def test_show_available_products(self): Tests show_available_products
- def test_show... | Implement the Python class `DatabaseUnitTest` described below.
Class description:
Class for unit tests for database.py
Method signatures and docstrings:
- def test_import_data(self): Test that import_data imports csv into database
- def test_show_available_products(self): Tests show_available_products
- def test_show... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class DatabaseUnitTest:
"""Class for unit tests for database.py"""
def test_import_data(self):
"""Test that import_data imports csv into database"""
<|body_0|>
def test_show_available_products(self):
"""Tests show_available_products"""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatabaseUnitTest:
"""Class for unit tests for database.py"""
def test_import_data(self):
"""Test that import_data imports csv into database"""
clear_test_collections()
with patch('database.__set_collection_names', return_value=TEST_DB_NAMES):
incorrect_names = database... | the_stack_v2_python_sparse | students/kyle_lehning/Lesson05/assignment/test_database.py | JavaRod/SP_Python220B_2019 | train | 1 |
83f7383fd83041bf61bd3e0006237db867408471 | [
"super(TDNN, self).__init__()\nself.context_size = context_size\nself.stride = stride\nself.input_dim = input_dim\nself.output_dim = output_dim\nself.dilation = dilation\nself.dropout_p = dropout_p\nself.batch_norm = batch_norm\nself.kernel = nn.Linear(input_dim * context_size, output_dim)\nself.nonlinearity = nn.R... | <|body_start_0|>
super(TDNN, self).__init__()
self.context_size = context_size
self.stride = stride
self.input_dim = input_dim
self.output_dim = output_dim
self.dilation = dilation
self.dropout_p = dropout_p
self.batch_norm = batch_norm
self.kernel... | TDNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TDNN:
def __init__(self, input_dim=3, output_dim=3, context_size=3, dilation=1, stride=1, batch_norm=True, dropout_p=0.0):
"""TDNN as defined by https://www.danielpovey.com/files/2015_interspeech_multisplice.pdf Affine transformation not applied globally to all frames but smaller windows... | stack_v2_sparse_classes_36k_train_029145 | 4,369 | no_license | [
{
"docstring": "TDNN as defined by https://www.danielpovey.com/files/2015_interspeech_multisplice.pdf Affine transformation not applied globally to all frames but smaller windows with local context batch_norm: True to include batch normalisation after the non linearity Context size and dilation determine the fr... | 2 | stack_v2_sparse_classes_30k_train_011309 | Implement the Python class `TDNN` described below.
Class description:
Implement the TDNN class.
Method signatures and docstrings:
- def __init__(self, input_dim=3, output_dim=3, context_size=3, dilation=1, stride=1, batch_norm=True, dropout_p=0.0): TDNN as defined by https://www.danielpovey.com/files/2015_interspeech... | Implement the Python class `TDNN` described below.
Class description:
Implement the TDNN class.
Method signatures and docstrings:
- def __init__(self, input_dim=3, output_dim=3, context_size=3, dilation=1, stride=1, batch_norm=True, dropout_p=0.0): TDNN as defined by https://www.danielpovey.com/files/2015_interspeech... | d04244ed07401567c493171d3e4b7b37d107a68d | <|skeleton|>
class TDNN:
def __init__(self, input_dim=3, output_dim=3, context_size=3, dilation=1, stride=1, batch_norm=True, dropout_p=0.0):
"""TDNN as defined by https://www.danielpovey.com/files/2015_interspeech_multisplice.pdf Affine transformation not applied globally to all frames but smaller windows... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TDNN:
def __init__(self, input_dim=3, output_dim=3, context_size=3, dilation=1, stride=1, batch_norm=True, dropout_p=0.0):
"""TDNN as defined by https://www.danielpovey.com/files/2015_interspeech_multisplice.pdf Affine transformation not applied globally to all frames but smaller windows with local co... | the_stack_v2_python_sparse | 2-x-vector/tdnn.py | zcx-1997/My_speaker_recognition | train | 1 | |
0a34b4e70ba768e49d9059f8ff38047e599a854f | [
"super().__init__(**kwargs)\nself.min_prefix_len = min_prefix_len\nself.max_prefix_len = max_prefix_len",
"value = super()._validate(cfg, value)\ntry:\n net = IPv4Network(value)\nexcept ValueError as err:\n raise ValueError('value is not a valid IPv4 Network (CIDR)') from err\nif self.min_prefix_len and net... | <|body_start_0|>
super().__init__(**kwargs)
self.min_prefix_len = min_prefix_len
self.max_prefix_len = max_prefix_len
<|end_body_0|>
<|body_start_1|>
value = super()._validate(cfg, value)
try:
net = IPv4Network(value)
except ValueError as err:
rai... | IPv4 network field. This field accepts CIDR notation networks in the form of ``A.B.C.D/Z``. | IPv4NetworkField | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IPv4NetworkField:
"""IPv4 network field. This field accepts CIDR notation networks in the form of ``A.B.C.D/Z``."""
def __init__(self, min_prefix_len: Optional[int]=None, max_prefix_len: Optional[int]=None, **kwargs):
""":param min_prefix_len: minimum subnet prefix length (/X), in bi... | stack_v2_sparse_classes_36k_train_029146 | 4,387 | permissive | [
{
"docstring": ":param min_prefix_len: minimum subnet prefix length (/X), in bits :param max_prefix_len: maximum subnet prefix length (/X), in bits",
"name": "__init__",
"signature": "def __init__(self, min_prefix_len: Optional[int]=None, max_prefix_len: Optional[int]=None, **kwargs)"
},
{
"docs... | 2 | stack_v2_sparse_classes_30k_train_014029 | Implement the Python class `IPv4NetworkField` described below.
Class description:
IPv4 network field. This field accepts CIDR notation networks in the form of ``A.B.C.D/Z``.
Method signatures and docstrings:
- def __init__(self, min_prefix_len: Optional[int]=None, max_prefix_len: Optional[int]=None, **kwargs): :param... | Implement the Python class `IPv4NetworkField` described below.
Class description:
IPv4 network field. This field accepts CIDR notation networks in the form of ``A.B.C.D/Z``.
Method signatures and docstrings:
- def __init__(self, min_prefix_len: Optional[int]=None, max_prefix_len: Optional[int]=None, **kwargs): :param... | 1499ff8f00a43a592571a10666823e125d5fbc49 | <|skeleton|>
class IPv4NetworkField:
"""IPv4 network field. This field accepts CIDR notation networks in the form of ``A.B.C.D/Z``."""
def __init__(self, min_prefix_len: Optional[int]=None, max_prefix_len: Optional[int]=None, **kwargs):
""":param min_prefix_len: minimum subnet prefix length (/X), in bi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IPv4NetworkField:
"""IPv4 network field. This field accepts CIDR notation networks in the form of ``A.B.C.D/Z``."""
def __init__(self, min_prefix_len: Optional[int]=None, max_prefix_len: Optional[int]=None, **kwargs):
""":param min_prefix_len: minimum subnet prefix length (/X), in bits :param max... | the_stack_v2_python_sparse | cincoconfig/fields/net_field.py | ameily/cincoconfig | train | 6 |
0fdd2d2adc2923914bb1558939979dd0dfab7837 | [
"def batch_shaped(t):\n return graph_typecheck.assert_shape(t, [batch_size])\n\ndef batch_win_shaped(t):\n return graph_typecheck.assert_shape(t, [batch_size, window_size])\n\ndef batch_2win_shaped(t):\n return graph_typecheck.assert_shape(t, [batch_size, 2 * window_size])\n\ndef tile_to_2win(t):\n retu... | <|body_start_0|>
def batch_shaped(t):
return graph_typecheck.assert_shape(t, [batch_size])
def batch_win_shaped(t):
return graph_typecheck.assert_shape(t, [batch_size, window_size])
def batch_2win_shaped(t):
return graph_typecheck.assert_shape(t, [batch_size... | Helper for dealing with window-like raw features. In particular, this class generates concatenated "dflux_dt" values, and has a masking helper, which will probably be applied after doing some non-linear transformations to dflux_dt (or possibly raw self.dtime, self.dflux) values. | WindowFeatures | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WindowFeatures:
"""Helper for dealing with window-like raw features. In particular, this class generates concatenated "dflux_dt" values, and has a masking helper, which will probably be applied after doing some non-linear transformations to dflux_dt (or possibly raw self.dtime, self.dflux) values... | stack_v2_sparse_classes_36k_train_029147 | 11,936 | permissive | [
{
"docstring": "Initializes a windowed feature extractor. :param band_features: Band features, generated by raw_value_features. :param batch_size: Outer batch size. :param window_size: Number of points in 'before' and 'after' windows. :param band_time_diff: Maximum difference between requested time and actual t... | 3 | stack_v2_sparse_classes_30k_train_003189 | Implement the Python class `WindowFeatures` described below.
Class description:
Helper for dealing with window-like raw features. In particular, this class generates concatenated "dflux_dt" values, and has a masking helper, which will probably be applied after doing some non-linear transformations to dflux_dt (or poss... | Implement the Python class `WindowFeatures` described below.
Class description:
Helper for dealing with window-like raw features. In particular, this class generates concatenated "dflux_dt" values, and has a masking helper, which will probably be applied after doing some non-linear transformations to dflux_dt (or poss... | 2edcb471cd01d6659a498bcd0209cb5dae83375a | <|skeleton|>
class WindowFeatures:
"""Helper for dealing with window-like raw features. In particular, this class generates concatenated "dflux_dt" values, and has a masking helper, which will probably be applied after doing some non-linear transformations to dflux_dt (or possibly raw self.dtime, self.dflux) values... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WindowFeatures:
"""Helper for dealing with window-like raw features. In particular, this class generates concatenated "dflux_dt" values, and has a masking helper, which will probably be applied after doing some non-linear transformations to dflux_dt (or possibly raw self.dtime, self.dflux) values."""
def... | the_stack_v2_python_sparse | justice/features/dense_extracted_features.py | aimalz/justice | train | 1 |
631a1a02fbacdba3a7b45af19d3ce49c86d035b6 | [
"if not head or not head.next:\n return head\ndummy = ListNode(None)\nd = dummy\nh = head\nd.next = head\nwhile h and h.next:\n n1 = h.next\n n2 = h.next.next\n d.next = n1\n n1.next = h\n h.next = n2\n d = h\n h = n2\nreturn dummy.next",
"if not head or not head.next:\n return head\nne... | <|body_start_0|>
if not head or not head.next:
return head
dummy = ListNode(None)
d = dummy
h = head
d.next = head
while h and h.next:
n1 = h.next
n2 = h.next.next
d.next = n1
n1.next = h
h.next = n2
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseInPairs1(self, head):
"""input: ListNode head return: ListNode"""
<|body_0|>
def reverseInPairs2(self, head):
"""input: ListNode head return: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not head or not head.next:... | stack_v2_sparse_classes_36k_train_029148 | 1,535 | no_license | [
{
"docstring": "input: ListNode head return: ListNode",
"name": "reverseInPairs1",
"signature": "def reverseInPairs1(self, head)"
},
{
"docstring": "input: ListNode head return: ListNode",
"name": "reverseInPairs2",
"signature": "def reverseInPairs2(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012470 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseInPairs1(self, head): input: ListNode head return: ListNode
- def reverseInPairs2(self, head): input: ListNode head return: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseInPairs1(self, head): input: ListNode head return: ListNode
- def reverseInPairs2(self, head): input: ListNode head return: ListNode
<|skeleton|>
class Solution:
... | c34b55bb42dc44a9026a902f6afcc018b4154662 | <|skeleton|>
class Solution:
def reverseInPairs1(self, head):
"""input: ListNode head return: ListNode"""
<|body_0|>
def reverseInPairs2(self, head):
"""input: ListNode head return: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseInPairs1(self, head):
"""input: ListNode head return: ListNode"""
if not head or not head.next:
return head
dummy = ListNode(None)
d = dummy
h = head
d.next = head
while h and h.next:
n1 = h.next
n... | the_stack_v2_python_sparse | Algorithm/Reverse Linked List In Pairs - Lai.py | superpigBB/Happy-Coding | train | 0 | |
5cf53a8bdb3640698c1f305be5e6512b420fe8dd | [
"wx.Panel.__init__(self, parent, *args, **kwargs)\nself.layouts = {}\nself.bind_objects = {}\nself.setting = setting\nself.SetSizerAndFit(self.do_layout())",
"vsizer = wx.BoxSizer(wx.VERTICAL)\nlayout = LayoutDimensions(top=2, bottom=2, left=4, right=4, interior=2, widths=(100, 200), stretch_factor=(0, 1), height... | <|body_start_0|>
wx.Panel.__init__(self, parent, *args, **kwargs)
self.layouts = {}
self.bind_objects = {}
self.setting = setting
self.SetSizerAndFit(self.do_layout())
<|end_body_0|>
<|body_start_1|>
vsizer = wx.BoxSizer(wx.VERTICAL)
layout = LayoutDimensions(top... | Particular Figure Setting | FigureSettingPanel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FigureSettingPanel:
"""Particular Figure Setting"""
def __init__(self, parent, setting, *args, **kwargs):
""":param setting: :param args: :param kwargs: :return:"""
<|body_0|>
def do_layout(self):
"""Layout form :return:"""
<|body_1|>
def sync_data(s... | stack_v2_sparse_classes_36k_train_029149 | 8,601 | no_license | [
{
"docstring": ":param setting: :param args: :param kwargs: :return:",
"name": "__init__",
"signature": "def __init__(self, parent, setting, *args, **kwargs)"
},
{
"docstring": "Layout form :return:",
"name": "do_layout",
"signature": "def do_layout(self)"
},
{
"docstring": "Sync... | 3 | stack_v2_sparse_classes_30k_train_011182 | Implement the Python class `FigureSettingPanel` described below.
Class description:
Particular Figure Setting
Method signatures and docstrings:
- def __init__(self, parent, setting, *args, **kwargs): :param setting: :param args: :param kwargs: :return:
- def do_layout(self): Layout form :return:
- def sync_data(self)... | Implement the Python class `FigureSettingPanel` described below.
Class description:
Particular Figure Setting
Method signatures and docstrings:
- def __init__(self, parent, setting, *args, **kwargs): :param setting: :param args: :param kwargs: :return:
- def do_layout(self): Layout form :return:
- def sync_data(self)... | e78511f30935b006385b571472487bb081aa36d8 | <|skeleton|>
class FigureSettingPanel:
"""Particular Figure Setting"""
def __init__(self, parent, setting, *args, **kwargs):
""":param setting: :param args: :param kwargs: :return:"""
<|body_0|>
def do_layout(self):
"""Layout form :return:"""
<|body_1|>
def sync_data(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FigureSettingPanel:
"""Particular Figure Setting"""
def __init__(self, parent, setting, *args, **kwargs):
""":param setting: :param args: :param kwargs: :return:"""
wx.Panel.__init__(self, parent, *args, **kwargs)
self.layouts = {}
self.bind_objects = {}
self.setti... | the_stack_v2_python_sparse | boaui/chart/dlg.py | JoenyBui/boa-gui | train | 0 |
d3f0a3110e1363fcfe79a8d0d1312d4914e55cff | [
"if not name:\n name = model_load_name\nsuper().__init__(name=name, type='keras')\nself.model_load_name = model_load_name\nself.pop_last = pop_last",
"model = saveload.load_tf_model(self.model_load_name)\nif self.pop_last:\n model.pop()\nreturn model",
"try:\n model = self.get_model()\n y = model.pr... | <|body_start_0|>
if not name:
name = model_load_name
super().__init__(name=name, type='keras')
self.model_load_name = model_load_name
self.pop_last = pop_last
<|end_body_0|>
<|body_start_1|>
model = saveload.load_tf_model(self.model_load_name)
if self.pop_las... | KerasLoadsWhole | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KerasLoadsWhole:
def __init__(self, model_load_name, name=None, pop_last=False):
"""Wrap a saved Keras model. This subclass of ModelWrapper should be used with Keras models that have been saved using utils.saveload.save_tf_model. If only weights have been saved, KerasLoadsWeights (not im... | stack_v2_sparse_classes_36k_train_029150 | 5,167 | no_license | [
{
"docstring": "Wrap a saved Keras model. This subclass of ModelWrapper should be used with Keras models that have been saved using utils.saveload.save_tf_model. If only weights have been saved, KerasLoadsWeights (not implemented) should be used instead. Args: model_load_name (str): The name used when saving th... | 3 | null | Implement the Python class `KerasLoadsWhole` described below.
Class description:
Implement the KerasLoadsWhole class.
Method signatures and docstrings:
- def __init__(self, model_load_name, name=None, pop_last=False): Wrap a saved Keras model. This subclass of ModelWrapper should be used with Keras models that have b... | Implement the Python class `KerasLoadsWhole` described below.
Class description:
Implement the KerasLoadsWhole class.
Method signatures and docstrings:
- def __init__(self, model_load_name, name=None, pop_last=False): Wrap a saved Keras model. This subclass of ModelWrapper should be used with Keras models that have b... | d61d298b52c4338e07d7cd4a3fdc65f1de1bcbf1 | <|skeleton|>
class KerasLoadsWhole:
def __init__(self, model_load_name, name=None, pop_last=False):
"""Wrap a saved Keras model. This subclass of ModelWrapper should be used with Keras models that have been saved using utils.saveload.save_tf_model. If only weights have been saved, KerasLoadsWeights (not im... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KerasLoadsWhole:
def __init__(self, model_load_name, name=None, pop_last=False):
"""Wrap a saved Keras model. This subclass of ModelWrapper should be used with Keras models that have been saved using utils.saveload.save_tf_model. If only weights have been saved, KerasLoadsWeights (not implemented) sho... | the_stack_v2_python_sparse | code/models/ensemble.py | lennelov/endd-reproduce | train | 3 | |
9d1f5c96335c114405f718f133b7bb1bce7198d5 | [
"def bisearch(s, e):\n while s <= e:\n m = s + (e - s) // 2\n if nums[m] < target:\n s = m + 1\n elif nums[m] > target:\n e = m - 1\n else:\n return m\n return s\nreturn bisearch(0, len(nums) - 1)",
"l, r = (0, len(nums) - 1)\nwhile l <= r:\n m... | <|body_start_0|>
def bisearch(s, e):
while s <= e:
m = s + (e - s) // 2
if nums[m] < target:
s = m + 1
elif nums[m] > target:
e = m - 1
else:
return m
return s
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchInsert(self, nums: List[int], target: int) -> int:
"""Dec 03, 2021 13:53"""
<|body_0|>
def searchInsert(self, nums: List[int], target: int) -> int:
"""Mar 22, 2023 00:17"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def bisearc... | stack_v2_sparse_classes_36k_train_029151 | 1,819 | no_license | [
{
"docstring": "Dec 03, 2021 13:53",
"name": "searchInsert",
"signature": "def searchInsert(self, nums: List[int], target: int) -> int"
},
{
"docstring": "Mar 22, 2023 00:17",
"name": "searchInsert",
"signature": "def searchInsert(self, nums: List[int], target: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert(self, nums: List[int], target: int) -> int: Dec 03, 2021 13:53
- def searchInsert(self, nums: List[int], target: int) -> int: Mar 22, 2023 00:17 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert(self, nums: List[int], target: int) -> int: Dec 03, 2021 13:53
- def searchInsert(self, nums: List[int], target: int) -> int: Mar 22, 2023 00:17
<|skeleton|>
cl... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def searchInsert(self, nums: List[int], target: int) -> int:
"""Dec 03, 2021 13:53"""
<|body_0|>
def searchInsert(self, nums: List[int], target: int) -> int:
"""Mar 22, 2023 00:17"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def searchInsert(self, nums: List[int], target: int) -> int:
"""Dec 03, 2021 13:53"""
def bisearch(s, e):
while s <= e:
m = s + (e - s) // 2
if nums[m] < target:
s = m + 1
elif nums[m] > target:
... | the_stack_v2_python_sparse | leetcode/solved/35_Search_Insert_Position/solution.py | sungminoh/algorithms | train | 0 | |
2e115ed0c4c9b5e70866402d3dc3fb0e54610ea6 | [
"DirectFrame.__init__(self, parent=parent, pos=pos)\nself.createGuiObjects()\nself.hourCallback = hourCallback\nself.lastHour = -1\nself.lastMinute = -1",
"textScale = 0.075\ntimeFont = ToontownGlobals.getMinnieFont()\nself.hourLabel = DirectLabel(parent=self, pos=(-0.015, 0, 0), relief=None, text='', text_scale=... | <|body_start_0|>
DirectFrame.__init__(self, parent=parent, pos=pos)
self.createGuiObjects()
self.hourCallback = hourCallback
self.lastHour = -1
self.lastMinute = -1
<|end_body_0|>
<|body_start_1|>
textScale = 0.075
timeFont = ToontownGlobals.getMinnieFont()
... | A class to dislay the server time nicely. Do not put references to the shtiker page or book, so this class can be placed anywhere. | ServerTimeGui | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServerTimeGui:
"""A class to dislay the server time nicely. Do not put references to the shtiker page or book, so this class can be placed anywhere."""
def __init__(self, parent, pos=(0, 0, 0), hourCallback=None):
"""Construct ourself."""
<|body_0|>
def createGuiObjects(... | stack_v2_sparse_classes_36k_train_029152 | 3,512 | no_license | [
{
"docstring": "Construct ourself.",
"name": "__init__",
"signature": "def __init__(self, parent, pos=(0, 0, 0), hourCallback=None)"
},
{
"docstring": "Create all gui elements and tasks.",
"name": "createGuiObjects",
"signature": "def createGuiObjects(self)"
},
{
"docstring": "Do... | 4 | stack_v2_sparse_classes_30k_train_000881 | Implement the Python class `ServerTimeGui` described below.
Class description:
A class to dislay the server time nicely. Do not put references to the shtiker page or book, so this class can be placed anywhere.
Method signatures and docstrings:
- def __init__(self, parent, pos=(0, 0, 0), hourCallback=None): Construct ... | Implement the Python class `ServerTimeGui` described below.
Class description:
A class to dislay the server time nicely. Do not put references to the shtiker page or book, so this class can be placed anywhere.
Method signatures and docstrings:
- def __init__(self, parent, pos=(0, 0, 0), hourCallback=None): Construct ... | 0e7bfc1fe29fd595df0b982e40f94c30befb1ec7 | <|skeleton|>
class ServerTimeGui:
"""A class to dislay the server time nicely. Do not put references to the shtiker page or book, so this class can be placed anywhere."""
def __init__(self, parent, pos=(0, 0, 0), hourCallback=None):
"""Construct ourself."""
<|body_0|>
def createGuiObjects(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServerTimeGui:
"""A class to dislay the server time nicely. Do not put references to the shtiker page or book, so this class can be placed anywhere."""
def __init__(self, parent, pos=(0, 0, 0), hourCallback=None):
"""Construct ourself."""
DirectFrame.__init__(self, parent=parent, pos=pos)... | the_stack_v2_python_sparse | toontown/src/parties/ServerTimeGui.py | satire6/Anesidora | train | 89 |
893994880d83d79a34b358adfd017158a8e32282 | [
"self.id = id\nself.name = name\nself.number = number\nself.mtype = mtype\nself.aggregation_status_code = aggregation_status_code\nself.balance = balance\nself.balance_date = balance_date\nself.transactions = transactions\nself.additional_properties = additional_properties",
"if dictionary is None:\n return No... | <|body_start_0|>
self.id = id
self.name = name
self.number = number
self.mtype = mtype
self.aggregation_status_code = aggregation_status_code
self.balance = balance
self.balance_date = balance_date
self.transactions = transactions
self.additional_p... | Implementation of the 'Transactions Report Account' model. The fields used for the Transaction History Report (CRA products). Attributes: id (long|int): The Finicity account ID. name (string): The account name from the financial institution. number (string): The account number from the financial institution (obfuscated... | TransactionsReportAccount | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransactionsReportAccount:
"""Implementation of the 'Transactions Report Account' model. The fields used for the Transaction History Report (CRA products). Attributes: id (long|int): The Finicity account ID. name (string): The account name from the financial institution. number (string): The acco... | stack_v2_sparse_classes_36k_train_029153 | 4,249 | permissive | [
{
"docstring": "Constructor for the TransactionsReportAccount class",
"name": "__init__",
"signature": "def __init__(self, id=None, name=None, number=None, mtype=None, aggregation_status_code=None, balance=None, balance_date=None, transactions=None, additional_properties={})"
},
{
"docstring": "... | 2 | null | Implement the Python class `TransactionsReportAccount` described below.
Class description:
Implementation of the 'Transactions Report Account' model. The fields used for the Transaction History Report (CRA products). Attributes: id (long|int): The Finicity account ID. name (string): The account name from the financial... | Implement the Python class `TransactionsReportAccount` described below.
Class description:
Implementation of the 'Transactions Report Account' model. The fields used for the Transaction History Report (CRA products). Attributes: id (long|int): The Finicity account ID. name (string): The account name from the financial... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class TransactionsReportAccount:
"""Implementation of the 'Transactions Report Account' model. The fields used for the Transaction History Report (CRA products). Attributes: id (long|int): The Finicity account ID. name (string): The account name from the financial institution. number (string): The acco... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransactionsReportAccount:
"""Implementation of the 'Transactions Report Account' model. The fields used for the Transaction History Report (CRA products). Attributes: id (long|int): The Finicity account ID. name (string): The account name from the financial institution. number (string): The account number fr... | the_stack_v2_python_sparse | finicityapi/models/transactions_report_account.py | monarchmoney/finicity-python | train | 0 |
51423a8e76303794466b956e97c993d0f9003d90 | [
"batch_brw = self.env['batch'].browse(vals['batch_id'])\nbatch_start_date = batch_brw.start_date\nbatch_stop_date = batch_brw.end_date\nstart_date = vals['start_date']\nstop_date = vals['end_date']\nif start_date >= batch_start_date and start_date <= batch_stop_date and (stop_date >= batch_start_date) and (stop_dat... | <|body_start_0|>
batch_brw = self.env['batch'].browse(vals['batch_id'])
batch_start_date = batch_brw.start_date
batch_stop_date = batch_brw.end_date
start_date = vals['start_date']
stop_date = vals['end_date']
if start_date >= batch_start_date and start_date <= batch_stop... | acd_term | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class acd_term:
def create(self, vals):
"""------------------ :param vals: :return:"""
<|body_0|>
def write(self, vals):
"""----------------- :param vals: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
batch_brw = self.env['batch'].browse(vals['... | stack_v2_sparse_classes_36k_train_029154 | 3,521 | no_license | [
{
"docstring": "------------------ :param vals: :return:",
"name": "create",
"signature": "def create(self, vals)"
},
{
"docstring": "----------------- :param vals: :return:",
"name": "write",
"signature": "def write(self, vals)"
}
] | 2 | null | Implement the Python class `acd_term` described below.
Class description:
Implement the acd_term class.
Method signatures and docstrings:
- def create(self, vals): ------------------ :param vals: :return:
- def write(self, vals): ----------------- :param vals: :return: | Implement the Python class `acd_term` described below.
Class description:
Implement the acd_term class.
Method signatures and docstrings:
- def create(self, vals): ------------------ :param vals: :return:
- def write(self, vals): ----------------- :param vals: :return:
<|skeleton|>
class acd_term:
def create(se... | 0e65e5d937b029beb69563772197b9b050748407 | <|skeleton|>
class acd_term:
def create(self, vals):
"""------------------ :param vals: :return:"""
<|body_0|>
def write(self, vals):
"""----------------- :param vals: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class acd_term:
def create(self, vals):
"""------------------ :param vals: :return:"""
batch_brw = self.env['batch'].browse(vals['batch_id'])
batch_start_date = batch_brw.start_date
batch_stop_date = batch_brw.end_date
start_date = vals['start_date']
stop_date = vals[... | the_stack_v2_python_sparse | edsys_edu_masters/models/acd_term.py | probytesodoo/edsys_school_erp | train | 1 | |
7aeb04ca35c8e1b5c183596eca353461970a2dc0 | [
"queue = deque([root])\ns = ''\nwhile queue:\n node = queue.popleft()\n if node:\n s += str(node.val) + ','\n queue.append(node.left)\n queue.append(node.right)\n else:\n s += 'None' + ','\nreturn '[' + s[:-1] + ']'",
"data_split = data[1:-1].split(',')\nr = data_split[0]\nif ... | <|body_start_0|>
queue = deque([root])
s = ''
while queue:
node = queue.popleft()
if node:
s += str(node.val) + ','
queue.append(node.left)
queue.append(node.right)
else:
s += 'None' + ','
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_029155 | 1,696 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 9aed6e84fbe48090382744dd103843fec43ccce9 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
queue = deque([root])
s = ''
while queue:
node = queue.popleft()
if node:
s += str(node.val) + ','
queue.append(no... | the_stack_v2_python_sparse | python/297_codeC.py | LeonhardtWang/leetcode-train | train | 1 | |
df1d3f4f4ff2800213a045e5c8f45224dfbb726f | [
"key = cls.des_key\nlength = len(reqdata)\nif length < cls.block_size:\n add = cls.block_size - length\nelif length > cls.block_size:\n add = cls.block_size - length % cls.block_size\nelse:\n add = 8\nreqdata = reqdata + cls.pad_str[add - 1] * add\ndes = DES.new(key, DES.MODE_ECB)\nencrypt_data = des.encry... | <|body_start_0|>
key = cls.des_key
length = len(reqdata)
if length < cls.block_size:
add = cls.block_size - length
elif length > cls.block_size:
add = cls.block_size - length % cls.block_size
else:
add = 8
reqdata = reqdata + cls.pad_st... | 加密和解密工具类 | Crypt | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Crypt:
"""加密和解密工具类"""
def des_base64_encrypt(cls, reqdata):
"""基于DES和base64的加密算法 @:param reqdata 需要加密的请求数据"""
<|body_0|>
def des_base64_decrypt(cls, retdata):
"""DES解密 @:param retdata: lakala reponse retData"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_029156 | 1,265 | no_license | [
{
"docstring": "基于DES和base64的加密算法 @:param reqdata 需要加密的请求数据",
"name": "des_base64_encrypt",
"signature": "def des_base64_encrypt(cls, reqdata)"
},
{
"docstring": "DES解密 @:param retdata: lakala reponse retData",
"name": "des_base64_decrypt",
"signature": "def des_base64_decrypt(cls, retda... | 2 | stack_v2_sparse_classes_30k_train_011431 | Implement the Python class `Crypt` described below.
Class description:
加密和解密工具类
Method signatures and docstrings:
- def des_base64_encrypt(cls, reqdata): 基于DES和base64的加密算法 @:param reqdata 需要加密的请求数据
- def des_base64_decrypt(cls, retdata): DES解密 @:param retdata: lakala reponse retData | Implement the Python class `Crypt` described below.
Class description:
加密和解密工具类
Method signatures and docstrings:
- def des_base64_encrypt(cls, reqdata): 基于DES和base64的加密算法 @:param reqdata 需要加密的请求数据
- def des_base64_decrypt(cls, retdata): DES解密 @:param retdata: lakala reponse retData
<|skeleton|>
class Crypt:
"""... | 92358511e1de06d8bf93888128576c32f226a26b | <|skeleton|>
class Crypt:
"""加密和解密工具类"""
def des_base64_encrypt(cls, reqdata):
"""基于DES和base64的加密算法 @:param reqdata 需要加密的请求数据"""
<|body_0|>
def des_base64_decrypt(cls, retdata):
"""DES解密 @:param retdata: lakala reponse retData"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Crypt:
"""加密和解密工具类"""
def des_base64_encrypt(cls, reqdata):
"""基于DES和base64的加密算法 @:param reqdata 需要加密的请求数据"""
key = cls.des_key
length = len(reqdata)
if length < cls.block_size:
add = cls.block_size - length
elif length > cls.block_size:
add... | the_stack_v2_python_sparse | 加密隐藏/DES/des_ecb.py | KnowNo/CTF-LEARN | train | 0 |
934cc4adf4784cdbedeaa5bc022b4ec99423d927 | [
"if project == 'CMIP6':\n required = [{'short_name': 'o3'}, {'short_name': 'ps'}]\nelse:\n required = [{'short_name': 'tro3'}, {'short_name': 'ps'}]\nreturn required",
"tro3_cube = cubes.extract_cube(iris.Constraint(name='mole_fraction_of_ozone_in_air'))\nps_cube = cubes.extract_cube(iris.Constraint(name='s... | <|body_start_0|>
if project == 'CMIP6':
required = [{'short_name': 'o3'}, {'short_name': 'ps'}]
else:
required = [{'short_name': 'tro3'}, {'short_name': 'ps'}]
return required
<|end_body_0|>
<|body_start_1|>
tro3_cube = cubes.extract_cube(iris.Constraint(name='mo... | Derivation of variable `toz`. | DerivedVariable | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DerivedVariable:
"""Derivation of variable `toz`."""
def required(project):
"""Declare the variables needed for derivation."""
<|body_0|>
def calculate(cubes):
"""Compute total column ozone. Note ---- The surface pressure is used as a lower integration bound. A f... | stack_v2_sparse_classes_36k_train_029157 | 2,234 | permissive | [
{
"docstring": "Declare the variables needed for derivation.",
"name": "required",
"signature": "def required(project)"
},
{
"docstring": "Compute total column ozone. Note ---- The surface pressure is used as a lower integration bound. A fixed upper integration bound of 0 Pa is used.",
"name... | 2 | stack_v2_sparse_classes_30k_train_012006 | Implement the Python class `DerivedVariable` described below.
Class description:
Derivation of variable `toz`.
Method signatures and docstrings:
- def required(project): Declare the variables needed for derivation.
- def calculate(cubes): Compute total column ozone. Note ---- The surface pressure is used as a lower i... | Implement the Python class `DerivedVariable` described below.
Class description:
Derivation of variable `toz`.
Method signatures and docstrings:
- def required(project): Declare the variables needed for derivation.
- def calculate(cubes): Compute total column ozone. Note ---- The surface pressure is used as a lower i... | d5187438fea2928644cb53ecb26c6adb1e4cc947 | <|skeleton|>
class DerivedVariable:
"""Derivation of variable `toz`."""
def required(project):
"""Declare the variables needed for derivation."""
<|body_0|>
def calculate(cubes):
"""Compute total column ozone. Note ---- The surface pressure is used as a lower integration bound. A f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DerivedVariable:
"""Derivation of variable `toz`."""
def required(project):
"""Declare the variables needed for derivation."""
if project == 'CMIP6':
required = [{'short_name': 'o3'}, {'short_name': 'ps'}]
else:
required = [{'short_name': 'tro3'}, {'short_n... | the_stack_v2_python_sparse | esmvalcore/preprocessor/_derive/toz.py | ESMValGroup/ESMValCore | train | 41 |
379422795761c17158b780897250910eeb06333e | [
"self.pop_server = pop_server\nself.user = user\nself.password = passwd",
"try:\n self.reademail = poplib.POP3_SSL(self.pop_server)\n self.reademail.user(self.user)\n self.reademail.pass_(self.password)\n self.allemail = self.reademail.stat()\nexcept Exception as e:\n exit('读取邮件登录失败::%s' % str(e))"... | <|body_start_0|>
self.pop_server = pop_server
self.user = user
self.password = passwd
<|end_body_0|>
<|body_start_1|>
try:
self.reademail = poplib.POP3_SSL(self.pop_server)
self.reademail.user(self.user)
self.reademail.pass_(self.password)
... | My_Email_Rec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class My_Email_Rec:
def __init__(self, pop_server='pop.qq.com', user='964725349@qq.com', passwd='kxsxacdjdelsbejc', *args, **kwargs):
"""初始化接收邮件，获取第一封邮件标题字符的对象"""
<|body_0|>
def pop_connect(self):
"""连接pop服务器，收取邮件 :param self: :return:"""
<|body_1|>
def receiv... | stack_v2_sparse_classes_36k_train_029158 | 8,396 | no_license | [
{
"docstring": "初始化接收邮件，获取第一封邮件标题字符的对象",
"name": "__init__",
"signature": "def __init__(self, pop_server='pop.qq.com', user='964725349@qq.com', passwd='kxsxacdjdelsbejc', *args, **kwargs)"
},
{
"docstring": "连接pop服务器，收取邮件 :param self: :return:",
"name": "pop_connect",
"signature": "def p... | 3 | null | Implement the Python class `My_Email_Rec` described below.
Class description:
Implement the My_Email_Rec class.
Method signatures and docstrings:
- def __init__(self, pop_server='pop.qq.com', user='964725349@qq.com', passwd='kxsxacdjdelsbejc', *args, **kwargs): 初始化接收邮件，获取第一封邮件标题字符的对象
- def pop_connect(self): 连接pop服务器... | Implement the Python class `My_Email_Rec` described below.
Class description:
Implement the My_Email_Rec class.
Method signatures and docstrings:
- def __init__(self, pop_server='pop.qq.com', user='964725349@qq.com', passwd='kxsxacdjdelsbejc', *args, **kwargs): 初始化接收邮件，获取第一封邮件标题字符的对象
- def pop_connect(self): 连接pop服务器... | 8e4dfaaeae782a37f6baca4c024b1c2a1dc83cba | <|skeleton|>
class My_Email_Rec:
def __init__(self, pop_server='pop.qq.com', user='964725349@qq.com', passwd='kxsxacdjdelsbejc', *args, **kwargs):
"""初始化接收邮件，获取第一封邮件标题字符的对象"""
<|body_0|>
def pop_connect(self):
"""连接pop服务器，收取邮件 :param self: :return:"""
<|body_1|>
def receiv... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class My_Email_Rec:
def __init__(self, pop_server='pop.qq.com', user='964725349@qq.com', passwd='kxsxacdjdelsbejc', *args, **kwargs):
"""初始化接收邮件，获取第一封邮件标题字符的对象"""
self.pop_server = pop_server
self.user = user
self.password = passwd
def pop_connect(self):
"""连接pop服务器，收取邮件... | the_stack_v2_python_sparse | poweroff_by_email.py | PeterZhangxing/codewars | train | 0 | |
6cc07005984263fa6614700037e32de71fe39bb5 | [
"wait_for_nodes_1 = WaitForNodes(node_list, timeout=10.0)\nassert wait_for_nodes_1.wait()\nassert wait_for_nodes_1.get_nodes_not_found() == set()\nwait_for_nodes_1.shutdown()\nwith WaitForNodes(node_list, timeout=10.0) as wait_for_nodes_2:\n print('All nodes were found !')\n assert wait_for_nodes_2.get_nodes_... | <|body_start_0|>
wait_for_nodes_1 = WaitForNodes(node_list, timeout=10.0)
assert wait_for_nodes_1.wait()
assert wait_for_nodes_1.get_nodes_not_found() == set()
wait_for_nodes_1.shutdown()
with WaitForNodes(node_list, timeout=10.0) as wait_for_nodes_2:
print('All nodes... | CheckMultipleNodesLaunched | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckMultipleNodesLaunched:
def test_nodes_successful(self, node_list):
"""Check if all the nodes were launched correctly."""
<|body_0|>
def test_node_does_not_exist(self, node_list):
"""Insert a invalid node name that should not exist."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k_train_029159 | 4,984 | permissive | [
{
"docstring": "Check if all the nodes were launched correctly.",
"name": "test_nodes_successful",
"signature": "def test_nodes_successful(self, node_list)"
},
{
"docstring": "Insert a invalid node name that should not exist.",
"name": "test_node_does_not_exist",
"signature": "def test_n... | 2 | stack_v2_sparse_classes_30k_train_004200 | Implement the Python class `CheckMultipleNodesLaunched` described below.
Class description:
Implement the CheckMultipleNodesLaunched class.
Method signatures and docstrings:
- def test_nodes_successful(self, node_list): Check if all the nodes were launched correctly.
- def test_node_does_not_exist(self, node_list): I... | Implement the Python class `CheckMultipleNodesLaunched` described below.
Class description:
Implement the CheckMultipleNodesLaunched class.
Method signatures and docstrings:
- def test_nodes_successful(self, node_list): Check if all the nodes were launched correctly.
- def test_node_does_not_exist(self, node_list): I... | 1d97c4fc7445554f6f85f63305d424fc017212a0 | <|skeleton|>
class CheckMultipleNodesLaunched:
def test_nodes_successful(self, node_list):
"""Check if all the nodes were launched correctly."""
<|body_0|>
def test_node_does_not_exist(self, node_list):
"""Insert a invalid node name that should not exist."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckMultipleNodesLaunched:
def test_nodes_successful(self, node_list):
"""Check if all the nodes were launched correctly."""
wait_for_nodes_1 = WaitForNodes(node_list, timeout=10.0)
assert wait_for_nodes_1.wait()
assert wait_for_nodes_1.get_nodes_not_found() == set()
w... | the_stack_v2_python_sparse | launch_testing/launch_testing_examples/launch_testing_examples/check_multiple_nodes_launch_test.py | ros2/examples | train | 560 | |
d01e533c15be3ffa5d7717e6909ec649a258309c | [
"self.__ops = ops\nself.__nops = len(ops)\nfor iop in range(self.__nops):\n if not isinstance(self.__ops[iop], operator):\n raise Exception('Elements of ops list must be of type operator')\nif self.__nops != len(dims):\n raise Exception('Number of dimensions (%d) must equal number of operators (%d)' % ... | <|body_start_0|>
self.__ops = ops
self.__nops = len(ops)
for iop in range(self.__nops):
if not isinstance(self.__ops[iop], operator):
raise Exception('Elements of ops list must be of type operator')
if self.__nops != len(dims):
raise Exception('Num... | Row operator | rowop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class rowop:
"""Row operator"""
def __init__(self, ops, dims):
"""rowop constructor Parameters: ops - a list of operators used to form the row operator dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols... | stack_v2_sparse_classes_36k_train_029160 | 13,837 | no_license | [
{
"docstring": "rowop constructor Parameters: ops - a list of operators used to form the row operator dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols': 10},...] Note that the row operator will be formed in the order in wh... | 4 | stack_v2_sparse_classes_30k_train_001478 | Implement the Python class `rowop` described below.
Class description:
Row operator
Method signatures and docstrings:
- def __init__(self, ops, dims): rowop constructor Parameters: ops - a list of operators used to form the row operator dims - a list of dictionaries that contain the dimensions of the inputs and outpu... | Implement the Python class `rowop` described below.
Class description:
Row operator
Method signatures and docstrings:
- def __init__(self, ops, dims): rowop constructor Parameters: ops - a list of operators used to form the row operator dims - a list of dictionaries that contain the dimensions of the inputs and outpu... | 32a303eddd13385d8778b8bb3b4fbbfbe78bea51 | <|skeleton|>
class rowop:
"""Row operator"""
def __init__(self, ops, dims):
"""rowop constructor Parameters: ops - a list of operators used to form the row operator dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class rowop:
"""Row operator"""
def __init__(self, ops, dims):
"""rowop constructor Parameters: ops - a list of operators used to form the row operator dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols': 10},...] N... | the_stack_v2_python_sparse | opt/linopt/combops.py | ke0m/scaas | train | 2 |
26f2162ea2709a5275a8780d7415161efc420589 | [
"super(GRRHuntFileCollector, self).__init__(state, name=name, critical=critical)\nself.file_path_list = []\nself.max_file_size = 5 * 1024 * 1024 * 1024",
"self.GrrSetUp(reason, grr_server_url, grr_username, grr_password, approvers=approvers, verify=verify, message_callback=self.PublishMessage)\nself.file_path_lis... | <|body_start_0|>
super(GRRHuntFileCollector, self).__init__(state, name=name, critical=critical)
self.file_path_list = []
self.max_file_size = 5 * 1024 * 1024 * 1024
<|end_body_0|>
<|body_start_1|>
self.GrrSetUp(reason, grr_server_url, grr_username, grr_password, approvers=approvers, ve... | File collector for GRR hunts. Attributes: reason (str): justification for GRR access. approvers (str): comma-separated GRR approval recipients. file_path_list: comma-separated list of file paths. | GRRHuntFileCollector | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GRRHuntFileCollector:
"""File collector for GRR hunts. Attributes: reason (str): justification for GRR access. approvers (str): comma-separated GRR approval recipients. file_path_list: comma-separated list of file paths."""
def __init__(self, state: DFTimewolfState, name: Optional[str]=None,... | stack_v2_sparse_classes_36k_train_029161 | 27,645 | permissive | [
{
"docstring": "Initializes a GRR file collector hunt. Args: state (DFTimewolfState): recipe state. name (Optional[str]): The module's runtime name. critical (bool): True if the module is critical, which causes the entire recipe to fail if the module encounters an error.",
"name": "__init__",
"signature... | 4 | null | Implement the Python class `GRRHuntFileCollector` described below.
Class description:
File collector for GRR hunts. Attributes: reason (str): justification for GRR access. approvers (str): comma-separated GRR approval recipients. file_path_list: comma-separated list of file paths.
Method signatures and docstrings:
- ... | Implement the Python class `GRRHuntFileCollector` described below.
Class description:
File collector for GRR hunts. Attributes: reason (str): justification for GRR access. approvers (str): comma-separated GRR approval recipients. file_path_list: comma-separated list of file paths.
Method signatures and docstrings:
- ... | bcea85b1ce7a0feb2aa28b5be4fc6ae124e8ca3c | <|skeleton|>
class GRRHuntFileCollector:
"""File collector for GRR hunts. Attributes: reason (str): justification for GRR access. approvers (str): comma-separated GRR approval recipients. file_path_list: comma-separated list of file paths."""
def __init__(self, state: DFTimewolfState, name: Optional[str]=None,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GRRHuntFileCollector:
"""File collector for GRR hunts. Attributes: reason (str): justification for GRR access. approvers (str): comma-separated GRR approval recipients. file_path_list: comma-separated list of file paths."""
def __init__(self, state: DFTimewolfState, name: Optional[str]=None, critical: bo... | the_stack_v2_python_sparse | dftimewolf/lib/collectors/grr_hunt.py | log2timeline/dftimewolf | train | 248 |
11261b3cb6bbd2d41a11cdc6010d8c29c9d5e562 | [
"self._parent = parent\nself.scale = 0.01\nself.origin = self.scale * np.array([0, 0, 0])\nself.x_axis = self.scale * np.array([1, 0, 0])\nself.y_axis = self.scale * np.array([0, 1, 0])\nself.z_axis = self.scale * np.array([0, 0, 1])\nself.x_color = np.array([[1, 0, 0]])\nself.y_color = np.array([[0, 1, 0]])\nself.... | <|body_start_0|>
self._parent = parent
self.scale = 0.01
self.origin = self.scale * np.array([0, 0, 0])
self.x_axis = self.scale * np.array([1, 0, 0])
self.y_axis = self.scale * np.array([0, 1, 0])
self.z_axis = self.scale * np.array([0, 0, 1])
self.x_color = np.a... | classdocs | CoordinateSystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoordinateSystem:
"""classdocs"""
def __init__(self, parent=None):
"""Class constructor of VBO"""
<|body_0|>
def _create_VBO(self):
"""Function creates VBO of coordinate system"""
<|body_1|>
def _paintGL_VBO_CS(self):
"""Paint local coordinat... | stack_v2_sparse_classes_36k_train_029162 | 3,309 | no_license | [
{
"docstring": "Class constructor of VBO",
"name": "__init__",
"signature": "def __init__(self, parent=None)"
},
{
"docstring": "Function creates VBO of coordinate system",
"name": "_create_VBO",
"signature": "def _create_VBO(self)"
},
{
"docstring": "Paint local coordinate syste... | 3 | null | Implement the Python class `CoordinateSystem` described below.
Class description:
classdocs
Method signatures and docstrings:
- def __init__(self, parent=None): Class constructor of VBO
- def _create_VBO(self): Function creates VBO of coordinate system
- def _paintGL_VBO_CS(self): Paint local coordinate system VBO | Implement the Python class `CoordinateSystem` described below.
Class description:
classdocs
Method signatures and docstrings:
- def __init__(self, parent=None): Class constructor of VBO
- def _create_VBO(self): Function creates VBO of coordinate system
- def _paintGL_VBO_CS(self): Paint local coordinate system VBO
<... | 5e6a54dee662206664dde022ccca372f966b1789 | <|skeleton|>
class CoordinateSystem:
"""classdocs"""
def __init__(self, parent=None):
"""Class constructor of VBO"""
<|body_0|>
def _create_VBO(self):
"""Function creates VBO of coordinate system"""
<|body_1|>
def _paintGL_VBO_CS(self):
"""Paint local coordinat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoordinateSystem:
"""classdocs"""
def __init__(self, parent=None):
"""Class constructor of VBO"""
self._parent = parent
self.scale = 0.01
self.origin = self.scale * np.array([0, 0, 0])
self.x_axis = self.scale * np.array([1, 0, 0])
self.y_axis = self.scale ... | the_stack_v2_python_sparse | MBD_system/body/coordinate_system/coordinate_system.py | xupeiwust/DyS | train | 0 |
30e3ca8b72cc31243d061348299db2db33ef26de | [
"self._baseline_action_fn = baseline_action_fn\nself._comparator_fn = comparator_fn\nself._error_loss_fn = error_loss_fn\nself._margin = margin\nsuper(RelativeConstraint, self).__init__(time_step_spec, action_spec, constraint_network, error_loss_fn=self._error_loss_fn, name=name)",
"predicted_values, _ = self._co... | <|body_start_0|>
self._baseline_action_fn = baseline_action_fn
self._comparator_fn = comparator_fn
self._error_loss_fn = error_loss_fn
self._margin = margin
super(RelativeConstraint, self).__init__(time_step_spec, action_spec, constraint_network, error_loss_fn=self._error_loss_fn... | Class for representing a trainable relative constraint. This constraint class implements a relative constraint such as ``` expected_value(action) >= (1 - margin) * expected_value(baseline_action) ``` or ``` expected_value(action) <= (1 - margin) * expected_value(baseline_action) ``` | RelativeConstraint | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelativeConstraint:
"""Class for representing a trainable relative constraint. This constraint class implements a relative constraint such as ``` expected_value(action) >= (1 - margin) * expected_value(baseline_action) ``` or ``` expected_value(action) <= (1 - margin) * expected_value(baseline_ac... | stack_v2_sparse_classes_36k_train_029163 | 22,532 | permissive | [
{
"docstring": "Creates a trainable relative constraint using a neural network. Args: time_step_spec: A `TimeStep` spec of the expected time_steps. action_spec: A nest of `BoundedTensorSpec` representing the actions. constraint_network: An instance of `tf_agents.network.Network` used to provide estimates of act... | 2 | null | Implement the Python class `RelativeConstraint` described below.
Class description:
Class for representing a trainable relative constraint. This constraint class implements a relative constraint such as ``` expected_value(action) >= (1 - margin) * expected_value(baseline_action) ``` or ``` expected_value(action) <= (1... | Implement the Python class `RelativeConstraint` described below.
Class description:
Class for representing a trainable relative constraint. This constraint class implements a relative constraint such as ``` expected_value(action) >= (1 - margin) * expected_value(baseline_action) ``` or ``` expected_value(action) <= (1... | eca1093d3a047e538f17f6ab92ab4d8144284f23 | <|skeleton|>
class RelativeConstraint:
"""Class for representing a trainable relative constraint. This constraint class implements a relative constraint such as ``` expected_value(action) >= (1 - margin) * expected_value(baseline_action) ``` or ``` expected_value(action) <= (1 - margin) * expected_value(baseline_ac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RelativeConstraint:
"""Class for representing a trainable relative constraint. This constraint class implements a relative constraint such as ``` expected_value(action) >= (1 - margin) * expected_value(baseline_action) ``` or ``` expected_value(action) <= (1 - margin) * expected_value(baseline_action) ```"""
... | the_stack_v2_python_sparse | tf_agents/bandits/policies/constraints.py | tensorflow/agents | train | 2,755 |
971bd0c1781199c4c3585355cfefe61a4bc02c9a | [
"try:\n group = await get_data_from_req(self.request).groups.get(group_id)\nexcept ResourceNotFoundError:\n raise NotFound()\nreturn json_response(GroupResponse.parse_obj(group))",
"try:\n group = await get_data_from_req(self.request).groups.update(group_id, data)\nexcept ResourceNotFoundError:\n rais... | <|body_start_0|>
try:
group = await get_data_from_req(self.request).groups.get(group_id)
except ResourceNotFoundError:
raise NotFound()
return json_response(GroupResponse.parse_obj(group))
<|end_body_0|>
<|body_start_1|>
try:
group = await get_data_fr... | GroupView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupView:
async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]:
"""Get a group. Fetches the complete representation of a single user group including its permissions. Status Codes: 200: Successful operation 404: Group not found"""
<|body_0|>
async def pa... | stack_v2_sparse_classes_36k_train_029164 | 3,996 | permissive | [
{
"docstring": "Get a group. Fetches the complete representation of a single user group including its permissions. Status Codes: 200: Successful operation 404: Group not found",
"name": "get",
"signature": "async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_010501 | Implement the Python class `GroupView` described below.
Class description:
Implement the GroupView class.
Method signatures and docstrings:
- async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]: Get a group. Fetches the complete representation of a single user group including its permissions. St... | Implement the Python class `GroupView` described below.
Class description:
Implement the GroupView class.
Method signatures and docstrings:
- async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]: Get a group. Fetches the complete representation of a single user group including its permissions. St... | 1d17d2ba570cf5487e7514bec29250a5b368bb0a | <|skeleton|>
class GroupView:
async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]:
"""Get a group. Fetches the complete representation of a single user group including its permissions. Status Codes: 200: Successful operation 404: Group not found"""
<|body_0|>
async def pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupView:
async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]:
"""Get a group. Fetches the complete representation of a single user group including its permissions. Status Codes: 200: Successful operation 404: Group not found"""
try:
group = await get_data_fr... | the_stack_v2_python_sparse | virtool/groups/api.py | virtool/virtool | train | 45 | |
fd870f007d03036bafb3d1d54f73e97f37d00fa2 | [
"fields = super(IssueReportAdmin, self).get_fields(request, obj)\nif obj and obj.type != 'duplicate' and ('usecase_duplicate' in fields):\n fields.remove('usecase_duplicate')\nreturn fields",
"opts = self.model._meta\npk_value = obj._get_pk_val()\npreserved_filters = self.get_preserved_filters(request)\nredire... | <|body_start_0|>
fields = super(IssueReportAdmin, self).get_fields(request, obj)
if obj and obj.type != 'duplicate' and ('usecase_duplicate' in fields):
fields.remove('usecase_duplicate')
return fields
<|end_body_0|>
<|body_start_1|>
opts = self.model._meta
pk_value ... | IssueReportAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IssueReportAdmin:
def get_fields(self, request, obj=None):
"""Override to hide the 'usecase_duplicate' if type is not 'duplicate'"""
<|body_0|>
def response_change(self, request, obj, *args, **kwargs):
"""Override response_change method of admin/options.py to handle ... | stack_v2_sparse_classes_36k_train_029165 | 18,243 | no_license | [
{
"docstring": "Override to hide the 'usecase_duplicate' if type is not 'duplicate'",
"name": "get_fields",
"signature": "def get_fields(self, request, obj=None)"
},
{
"docstring": "Override response_change method of admin/options.py to handle the click of newly added buttons",
"name": "resp... | 2 | stack_v2_sparse_classes_30k_train_009320 | Implement the Python class `IssueReportAdmin` described below.
Class description:
Implement the IssueReportAdmin class.
Method signatures and docstrings:
- def get_fields(self, request, obj=None): Override to hide the 'usecase_duplicate' if type is not 'duplicate'
- def response_change(self, request, obj, *args, **kw... | Implement the Python class `IssueReportAdmin` described below.
Class description:
Implement the IssueReportAdmin class.
Method signatures and docstrings:
- def get_fields(self, request, obj=None): Override to hide the 'usecase_duplicate' if type is not 'duplicate'
- def response_change(self, request, obj, *args, **kw... | d9b330ef70b0d0985bfc8248612ba57ee46ff0f4 | <|skeleton|>
class IssueReportAdmin:
def get_fields(self, request, obj=None):
"""Override to hide the 'usecase_duplicate' if type is not 'duplicate'"""
<|body_0|>
def response_change(self, request, obj, *args, **kwargs):
"""Override response_change method of admin/options.py to handle ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IssueReportAdmin:
def get_fields(self, request, obj=None):
"""Override to hide the 'usecase_duplicate' if type is not 'duplicate'"""
fields = super(IssueReportAdmin, self).get_fields(request, obj)
if obj and obj.type != 'duplicate' and ('usecase_duplicate' in fields):
field... | the_stack_v2_python_sparse | Code/EnhanceCWE-master/muo/admin.py | happinesstaker/more-website | train | 0 | |
72fa32d825169a7a0c6418cfdb0c43c1b288462e | [
"if not last:\n t_cur = tuple(cur)\n if t_cur not in self.s:\n self.ret.append(cur)\n self.s.add(t_cur)\n return\nfor index, num in enumerate(last):\n self.buffer(cur + [num], last[:index] + last[index + 1:])",
"if not last:\n self.ret.append(cur)\n return\ns = set()\nfor index, nu... | <|body_start_0|>
if not last:
t_cur = tuple(cur)
if t_cur not in self.s:
self.ret.append(cur)
self.s.add(t_cur)
return
for index, num in enumerate(last):
self.buffer(cur + [num], last[:index] + last[index + 1:])
<|end_body_0... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def buffer1(self, cur, last):
""":type cur: list[int] :type last: list[int] :rtype :list[int]"""
<|body_0|>
def buffer(self, cur, last):
""":type cur: list[int] :type last: list[int] :rtype :list[int]"""
<|body_1|>
def permuteUnique(self, nums)... | stack_v2_sparse_classes_36k_train_029166 | 1,264 | no_license | [
{
"docstring": ":type cur: list[int] :type last: list[int] :rtype :list[int]",
"name": "buffer1",
"signature": "def buffer1(self, cur, last)"
},
{
"docstring": ":type cur: list[int] :type last: list[int] :rtype :list[int]",
"name": "buffer",
"signature": "def buffer(self, cur, last)"
}... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buffer1(self, cur, last): :type cur: list[int] :type last: list[int] :rtype :list[int]
- def buffer(self, cur, last): :type cur: list[int] :type last: list[int] :rtype :list[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buffer1(self, cur, last): :type cur: list[int] :type last: list[int] :rtype :list[int]
- def buffer(self, cur, last): :type cur: list[int] :type last: list[int] :rtype :list[... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def buffer1(self, cur, last):
""":type cur: list[int] :type last: list[int] :rtype :list[int]"""
<|body_0|>
def buffer(self, cur, last):
""":type cur: list[int] :type last: list[int] :rtype :list[int]"""
<|body_1|>
def permuteUnique(self, nums)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def buffer1(self, cur, last):
""":type cur: list[int] :type last: list[int] :rtype :list[int]"""
if not last:
t_cur = tuple(cur)
if t_cur not in self.s:
self.ret.append(cur)
self.s.add(t_cur)
return
for index... | the_stack_v2_python_sparse | python/leetcode/47_Permutations_II.py | bobcaoge/my-code | train | 0 | |
1104711a6ca608c8abb473799a3b9b50f368ba11 | [
"self.data = dict()\nself.total = 0\nself.rand = random.Random()",
"if val in self.data:\n return False\nself.data[val] = None\nself.total += 1\nreturn True",
"if val in self.data:\n self.data.pop(val)\n self.total -= 1\n return True\nreturn False",
"datas = list(self.data.keys())\npos = self.rand... | <|body_start_0|>
self.data = dict()
self.total = 0
self.rand = random.Random()
<|end_body_0|>
<|body_start_1|>
if val in self.data:
return False
self.data[val] = None
self.total += 1
return True
<|end_body_1|>
<|body_start_2|>
if val in self.... | RandomizedSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomizedSet:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, val: int) -> bool:
"""Inserts a value to the set. Returns true if the set did not already contain the specified element."""
<|body_1|>
def remove(se... | stack_v2_sparse_classes_36k_train_029167 | 1,584 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Inserts a value to the set. Returns true if the set did not already contain the specified element.",
"name": "insert",
"signature": "def insert(self, val: int) ... | 4 | stack_v2_sparse_classes_30k_train_011559 | Implement the Python class `RandomizedSet` described below.
Class description:
Implement the RandomizedSet class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, val: int) -> bool: Inserts a value to the set. Returns true if the set did not already conta... | Implement the Python class `RandomizedSet` described below.
Class description:
Implement the RandomizedSet class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, val: int) -> bool: Inserts a value to the set. Returns true if the set did not already conta... | 976090d52c77fc95ed7eb2eae3c60abc2a7f7106 | <|skeleton|>
class RandomizedSet:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, val: int) -> bool:
"""Inserts a value to the set. Returns true if the set did not already contain the specified element."""
<|body_1|>
def remove(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomizedSet:
def __init__(self):
"""Initialize your data structure here."""
self.data = dict()
self.total = 0
self.rand = random.Random()
def insert(self, val: int) -> bool:
"""Inserts a value to the set. Returns true if the set did not already contain the specif... | the_stack_v2_python_sparse | src/desgin/RandomizedSet.py | fanwucoder/leecode | train | 0 | |
ad1c389082b8c46fcc421eb4da67ec4cf18b358f | [
"tk.Toplevel.__init__(self)\nself.tid = scrolledtext.ScrolledText(self)\nself.tid.pack(fill=tk.BOTH, expand=1)\nself.Styles()\nself.Show()",
"for c in ['red', 'blue', 'magenta', 'yellow', 'green', 'red4', 'green4', 'blue4']:\n self.tid.tag_configure(c, foreground=c)\nself.tid.tag_config('underline', underline=... | <|body_start_0|>
tk.Toplevel.__init__(self)
self.tid = scrolledtext.ScrolledText(self)
self.tid.pack(fill=tk.BOTH, expand=1)
self.Styles()
self.Show()
<|end_body_0|>
<|body_start_1|>
for c in ['red', 'blue', 'magenta', 'yellow', 'green', 'red4', 'green4', 'blue4']:
... | Help window. | xbbtools_help | [
"BSD-3-Clause",
"LicenseRef-scancode-biopython"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class xbbtools_help:
"""Help window."""
def __init__(self, *args):
"""Make toplevel help window."""
<|body_0|>
def Styles(self):
"""Define text styles."""
<|body_1|>
def Show(self):
"""Display help text."""
<|body_2|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_029168 | 3,209 | permissive | [
{
"docstring": "Make toplevel help window.",
"name": "__init__",
"signature": "def __init__(self, *args)"
},
{
"docstring": "Define text styles.",
"name": "Styles",
"signature": "def Styles(self)"
},
{
"docstring": "Display help text.",
"name": "Show",
"signature": "def S... | 3 | stack_v2_sparse_classes_30k_val_000478 | Implement the Python class `xbbtools_help` described below.
Class description:
Help window.
Method signatures and docstrings:
- def __init__(self, *args): Make toplevel help window.
- def Styles(self): Define text styles.
- def Show(self): Display help text. | Implement the Python class `xbbtools_help` described below.
Class description:
Help window.
Method signatures and docstrings:
- def __init__(self, *args): Make toplevel help window.
- def Styles(self): Define text styles.
- def Show(self): Display help text.
<|skeleton|>
class xbbtools_help:
"""Help window."""
... | d416809344f1e345fbabbdaca4dd6dcf441e53bd | <|skeleton|>
class xbbtools_help:
"""Help window."""
def __init__(self, *args):
"""Make toplevel help window."""
<|body_0|>
def Styles(self):
"""Define text styles."""
<|body_1|>
def Show(self):
"""Display help text."""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class xbbtools_help:
"""Help window."""
def __init__(self, *args):
"""Make toplevel help window."""
tk.Toplevel.__init__(self)
self.tid = scrolledtext.ScrolledText(self)
self.tid.pack(fill=tk.BOTH, expand=1)
self.Styles()
self.Show()
def Styles(self):
... | the_stack_v2_python_sparse | Scripts/xbbtools/xbb_help.py | biopython/biopython | train | 3,669 |
b4910d9ce74079192a5ef828cdeafb5f4319323a | [
"res = super(ResConfigSettings, self).get_values()\nres['batch_num'] = int(self.env['ir.config_parameter'].sudo().get_param('funenc_wechat.batch_num', default=0))\nres['syn_thread_num'] = int(self.env['ir.config_parameter'].sudo().get_param('funenc_wechat.syn_thread_num', default=5))\nreturn res",
"self.env['ir.c... | <|body_start_0|>
res = super(ResConfigSettings, self).get_values()
res['batch_num'] = int(self.env['ir.config_parameter'].sudo().get_param('funenc_wechat.batch_num', default=0))
res['syn_thread_num'] = int(self.env['ir.config_parameter'].sudo().get_param('funenc_wechat.syn_thread_num', default=5... | 企业微信配置，批量处理 | ResConfigSettings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResConfigSettings:
"""企业微信配置，批量处理"""
def get_values(self):
"""取得配置 :return:"""
<|body_0|>
def set_values(self):
"""设置配置值 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = super(ResConfigSettings, self).get_values()
res['batc... | stack_v2_sparse_classes_36k_train_029169 | 1,184 | no_license | [
{
"docstring": "取得配置 :return:",
"name": "get_values",
"signature": "def get_values(self)"
},
{
"docstring": "设置配置值 :return:",
"name": "set_values",
"signature": "def set_values(self)"
}
] | 2 | null | Implement the Python class `ResConfigSettings` described below.
Class description:
企业微信配置，批量处理
Method signatures and docstrings:
- def get_values(self): 取得配置 :return:
- def set_values(self): 设置配置值 :return: | Implement the Python class `ResConfigSettings` described below.
Class description:
企业微信配置，批量处理
Method signatures and docstrings:
- def get_values(self): 取得配置 :return:
- def set_values(self): 设置配置值 :return:
<|skeleton|>
class ResConfigSettings:
"""企业微信配置，批量处理"""
def get_values(self):
"""取得配置 :return:... | 13b428a5c4ade6278e3e5e996ef10d9fb0fea4b9 | <|skeleton|>
class ResConfigSettings:
"""企业微信配置，批量处理"""
def get_values(self):
"""取得配置 :return:"""
<|body_0|>
def set_values(self):
"""设置配置值 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResConfigSettings:
"""企业微信配置，批量处理"""
def get_values(self):
"""取得配置 :return:"""
res = super(ResConfigSettings, self).get_values()
res['batch_num'] = int(self.env['ir.config_parameter'].sudo().get_param('funenc_wechat.batch_num', default=0))
res['syn_thread_num'] = int(self.... | the_stack_v2_python_sparse | mdias_addons/funenc_wechat/models/res_config_settings.py | rezaghanimi/main_mdias | train | 0 |
ca3e6c50ee6c12dfed3588318923f3633bf9dc9a | [
"try:\n verify_token(request.headers)\nexcept Exception as err:\n ns.abort(401, message=err)\noffset = request.args.get('offset', '0')\nlimit = request.args.get('limit', '10')\norder_by = request.args.get('order_by', 'id')\norder = request.args.get('order', 'ASC')\nper_page = request.args.get('per_page', '10'... | <|body_start_0|>
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
offset = request.args.get('offset', '0')
limit = request.args.get('limit', '10')
order_by = request.args.get('order_by', 'id')
order = request.a... | ObservacionCyTGList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObservacionCyTGList:
def get(self):
"""To fetch several observations (CyTG (resultados)). On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages"""
<|body_0|>
def post(self):
"""To create an observation (CyTG (resultados))."""
<|body_1... | stack_v2_sparse_classes_36k_train_029170 | 18,120 | no_license | [
{
"docstring": "To fetch several observations (CyTG (resultados)). On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "To create an observation (CyTG (resultados)).",
"name": "post",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_012379 | Implement the Python class `ObservacionCyTGList` described below.
Class description:
Implement the ObservacionCyTGList class.
Method signatures and docstrings:
- def get(self): To fetch several observations (CyTG (resultados)). On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages
- def post(... | Implement the Python class `ObservacionCyTGList` described below.
Class description:
Implement the ObservacionCyTGList class.
Method signatures and docstrings:
- def get(self): To fetch several observations (CyTG (resultados)). On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages
- def post(... | e00610fac26ef3ca078fd037c0649b70fa0e9a09 | <|skeleton|>
class ObservacionCyTGList:
def get(self):
"""To fetch several observations (CyTG (resultados)). On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages"""
<|body_0|>
def post(self):
"""To create an observation (CyTG (resultados))."""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObservacionCyTGList:
def get(self):
"""To fetch several observations (CyTG (resultados)). On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages"""
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
... | the_stack_v2_python_sparse | DOS/soa/service/genl/endpoints/observaciones_ires_cytg.py | Telematica/knight-rider | train | 1 | |
5d7f0d2b03d41c50ff6d837fc9d357219712a50e | [
"self.publisher = rospy.Publisher(output_heart_anomaly_topic, Classification2D, queue_size=10)\nrospy.Subscriber(input_ecg_topic, Float32MultiArray, self.callback)\nself.bridge = ROSBridge()\nself.channels = 1\nself.series_length = 9000\nif model == 'gru':\n self.learner = GatedRecurrentUnitLearner(in_channels=s... | <|body_start_0|>
self.publisher = rospy.Publisher(output_heart_anomaly_topic, Classification2D, queue_size=10)
rospy.Subscriber(input_ecg_topic, Float32MultiArray, self.callback)
self.bridge = ROSBridge()
self.channels = 1
self.series_length = 9000
if model == 'gru':
... | HeartAnomalyNode | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HeartAnomalyNode:
def __init__(self, input_ecg_topic='/ecg/ecg', output_heart_anomaly_topic='/opendr/heart_anomaly', device='cuda', model='anbof'):
"""Creates a ROS Node for heart anomaly (atrial fibrillation) detection from ecg data :param input_ecg_topic: Topic from which we are readin... | stack_v2_sparse_classes_36k_train_029171 | 4,848 | permissive | [
{
"docstring": "Creates a ROS Node for heart anomaly (atrial fibrillation) detection from ecg data :param input_ecg_topic: Topic from which we are reading the input array data :type input_ecg_topic: str :param output_heart_anomaly_topic: Topic to which we are publishing the predicted class :type output_heart_an... | 3 | null | Implement the Python class `HeartAnomalyNode` described below.
Class description:
Implement the HeartAnomalyNode class.
Method signatures and docstrings:
- def __init__(self, input_ecg_topic='/ecg/ecg', output_heart_anomaly_topic='/opendr/heart_anomaly', device='cuda', model='anbof'): Creates a ROS Node for heart ano... | Implement the Python class `HeartAnomalyNode` described below.
Class description:
Implement the HeartAnomalyNode class.
Method signatures and docstrings:
- def __init__(self, input_ecg_topic='/ecg/ecg', output_heart_anomaly_topic='/opendr/heart_anomaly', device='cuda', model='anbof'): Creates a ROS Node for heart ano... | b3d6ce670cdf63469fc5766630eb295d67b3d788 | <|skeleton|>
class HeartAnomalyNode:
def __init__(self, input_ecg_topic='/ecg/ecg', output_heart_anomaly_topic='/opendr/heart_anomaly', device='cuda', model='anbof'):
"""Creates a ROS Node for heart anomaly (atrial fibrillation) detection from ecg data :param input_ecg_topic: Topic from which we are readin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HeartAnomalyNode:
def __init__(self, input_ecg_topic='/ecg/ecg', output_heart_anomaly_topic='/opendr/heart_anomaly', device='cuda', model='anbof'):
"""Creates a ROS Node for heart anomaly (atrial fibrillation) detection from ecg data :param input_ecg_topic: Topic from which we are reading the input ar... | the_stack_v2_python_sparse | projects/opendr_ws/src/opendr_perception/scripts/heart_anomaly_detection_node.py | opendr-eu/opendr | train | 535 | |
2e7c3f9d920ad966b36810c939d667d1486a951b | [
"for page in range(1, self.settings.get('MAX_PAGE') + 1):\n url = self.base_url + str(page)\n yield Request(url=url, callback=self.parse, meta={'page': page}, dont_filter=True)",
"products = response.xpath(\"//*[@id='plist']/ul/li\")\nfor product in products:\n item = JdItem()\n item['title'] = produc... | <|body_start_0|>
for page in range(1, self.settings.get('MAX_PAGE') + 1):
url = self.base_url + str(page)
yield Request(url=url, callback=self.parse, meta={'page': page}, dont_filter=True)
<|end_body_0|>
<|body_start_1|>
products = response.xpath("//*[@id='plist']/ul/li")
... | LaptopSpider | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LaptopSpider:
def start_requests(self):
"""爬虫开始的地方，需要对页数进行处理"""
<|body_0|>
def parse(self, response):
"""对Selenium返回的页面进行解析"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for page in range(1, self.settings.get('MAX_PAGE') + 1):
url = se... | stack_v2_sparse_classes_36k_train_029172 | 1,308 | permissive | [
{
"docstring": "爬虫开始的地方，需要对页数进行处理",
"name": "start_requests",
"signature": "def start_requests(self)"
},
{
"docstring": "对Selenium返回的页面进行解析",
"name": "parse",
"signature": "def parse(self, response)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016210 | Implement the Python class `LaptopSpider` described below.
Class description:
Implement the LaptopSpider class.
Method signatures and docstrings:
- def start_requests(self): 爬虫开始的地方，需要对页数进行处理
- def parse(self, response): 对Selenium返回的页面进行解析 | Implement the Python class `LaptopSpider` described below.
Class description:
Implement the LaptopSpider class.
Method signatures and docstrings:
- def start_requests(self): 爬虫开始的地方，需要对页数进行处理
- def parse(self, response): 对Selenium返回的页面进行解析
<|skeleton|>
class LaptopSpider:
def start_requests(self):
"""爬虫... | e851524917b60e7308172bc235597b7c578882cc | <|skeleton|>
class LaptopSpider:
def start_requests(self):
"""爬虫开始的地方，需要对页数进行处理"""
<|body_0|>
def parse(self, response):
"""对Selenium返回的页面进行解析"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LaptopSpider:
def start_requests(self):
"""爬虫开始的地方，需要对页数进行处理"""
for page in range(1, self.settings.get('MAX_PAGE') + 1):
url = self.base_url + str(page)
yield Request(url=url, callback=self.parse, meta={'page': page}, dont_filter=True)
def parse(self, response):
... | the_stack_v2_python_sparse | 10th_week/homework/作业1/JD/JD/spiders/laptop.py | luhuadong/Python_Learning | train | 1 | |
82bb39dbb7391161dd61f37312a2e56b4923b0f9 | [
"perms = self.helper.get_all_permission_items()\nreq_keys = self.request.POST.keys()\nresponse = ''\nfor fieldname, email in self.request.POST.iteritems():\n if re.match(self.USER_PERMISSION_REGEX, fieldname):\n for perm in perms:\n key = '{0}-{1}'.format(email, perm)\n if key in req... | <|body_start_0|>
perms = self.helper.get_all_permission_items()
req_keys = self.request.POST.keys()
response = ''
for fieldname, email in self.request.POST.iteritems():
if re.match(self.USER_PERMISSION_REGEX, fieldname):
for perm in perms:
... | Class to handle requests to the /authorize page. | AuthorizePage | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthorizePage:
"""Class to handle requests to the /authorize page."""
def parse_update_user_permissions(self):
"""Update authorization matrix from form submission. Returns: A str with message to be displayed to the user."""
<|body_0|>
def post(self):
"""Handler f... | stack_v2_sparse_classes_36k_train_029173 | 37,207 | permissive | [
{
"docstring": "Update authorization matrix from form submission. Returns: A str with message to be displayed to the user.",
"name": "parse_update_user_permissions",
"signature": "def parse_update_user_permissions(self)"
},
{
"docstring": "Handler for POST requests.",
"name": "post",
"si... | 3 | stack_v2_sparse_classes_30k_train_008630 | Implement the Python class `AuthorizePage` described below.
Class description:
Class to handle requests to the /authorize page.
Method signatures and docstrings:
- def parse_update_user_permissions(self): Update authorization matrix from form submission. Returns: A str with message to be displayed to the user.
- def ... | Implement the Python class `AuthorizePage` described below.
Class description:
Class to handle requests to the /authorize page.
Method signatures and docstrings:
- def parse_update_user_permissions(self): Update authorization matrix from form submission. Returns: A str with message to be displayed to the user.
- def ... | aa36e8dfaa295d53bec616ed07f91ec8c02fa4e1 | <|skeleton|>
class AuthorizePage:
"""Class to handle requests to the /authorize page."""
def parse_update_user_permissions(self):
"""Update authorization matrix from form submission. Returns: A str with message to be displayed to the user."""
<|body_0|>
def post(self):
"""Handler f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthorizePage:
"""Class to handle requests to the /authorize page."""
def parse_update_user_permissions(self):
"""Update authorization matrix from form submission. Returns: A str with message to be displayed to the user."""
perms = self.helper.get_all_permission_items()
req_keys =... | the_stack_v2_python_sparse | AppDashboard/dashboard.py | shatterednirvana/appscale | train | 6 |
bb5ba0c6e69879dfc1292f329f4d60c4775aa4d5 | [
"self.data = data\nself.instruments = configuration.instruments\nself.exchanges = configuration.exchange_names\nself.exchange = self.exchanges[0]\nself.events = events\nself.short_window = short_window\nself.long_window = long_window\nself.trigger_window = trigger_window\nself.strategy_name = 'macd_crossover'\nself... | <|body_start_0|>
self.data = data
self.instruments = configuration.instruments
self.exchanges = configuration.exchange_names
self.exchange = self.exchanges[0]
self.events = events
self.short_window = short_window
self.long_window = long_window
self.trigger... | Carries out a basic MACD Strategy | MACDCrossover | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MACDCrossover:
"""Carries out a basic MACD Strategy"""
def __init__(self, data, events, configuration, long_window=52, short_window=24, trigger_window=18):
"""Initialises the Moving Average Cross Strategy. :param data: The DataHandler object that provides bar information. :param even... | stack_v2_sparse_classes_36k_train_029174 | 3,787 | no_license | [
{
"docstring": "Initialises the Moving Average Cross Strategy. :param data: The DataHandler object that provides bar information. :param events: The Event Queue object. :param short_window: The short moving average lookback. :param long_window: The long moving average lookback.",
"name": "__init__",
"si... | 3 | stack_v2_sparse_classes_30k_train_012824 | Implement the Python class `MACDCrossover` described below.
Class description:
Carries out a basic MACD Strategy
Method signatures and docstrings:
- def __init__(self, data, events, configuration, long_window=52, short_window=24, trigger_window=18): Initialises the Moving Average Cross Strategy. :param data: The Data... | Implement the Python class `MACDCrossover` described below.
Class description:
Carries out a basic MACD Strategy
Method signatures and docstrings:
- def __init__(self, data, events, configuration, long_window=52, short_window=24, trigger_window=18): Initialises the Moving Average Cross Strategy. :param data: The Data... | 39ad067fa9ea27002d06c98a9d06725ad886917b | <|skeleton|>
class MACDCrossover:
"""Carries out a basic MACD Strategy"""
def __init__(self, data, events, configuration, long_window=52, short_window=24, trigger_window=18):
"""Initialises the Moving Average Cross Strategy. :param data: The DataHandler object that provides bar information. :param even... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MACDCrossover:
"""Carries out a basic MACD Strategy"""
def __init__(self, data, events, configuration, long_window=52, short_window=24, trigger_window=18):
"""Initialises the Moving Average Cross Strategy. :param data: The DataHandler object that provides bar information. :param events: The Event... | the_stack_v2_python_sparse | strategies/crypto/macd_crossover.py | Dvisacker/backtrader | train | 2 |
a41d07f606937855b97dd9a7a565512634603b94 | [
"if n > 2:\n ans = self.climbStairs_rec(n - 1) + self.climbStairs_rec(n - 2)\nelse:\n ans = n\nreturn ans",
"if n > 2:\n ans = self.climbStairs_cacherec(n - 1) + self.climbStairs_cacherec(n - 2)\nelse:\n ans = n\nreturn ans",
"if n == 1:\n return 1\nif n == 2:\n return 2\ndp = [0] * n\ndp[0] =... | <|body_start_0|>
if n > 2:
ans = self.climbStairs_rec(n - 1) + self.climbStairs_rec(n - 2)
else:
ans = n
return ans
<|end_body_0|>
<|body_start_1|>
if n > 2:
ans = self.climbStairs_cacherec(n - 1) + self.climbStairs_cacherec(n - 2)
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs_rec(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs_cacherec(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def climbStairs_dp(self, n):
""":type n: int :rtype: int"""
<|body_2|>
def... | stack_v2_sparse_classes_36k_train_029175 | 2,932 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs_rec",
"signature": "def climbStairs_rec(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs_cacherec",
"signature": "def climbStairs_cacherec(self, n)"
},
{
"docstring": ":type n: int :rtype:... | 5 | stack_v2_sparse_classes_30k_train_001826 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs_rec(self, n): :type n: int :rtype: int
- def climbStairs_cacherec(self, n): :type n: int :rtype: int
- def climbStairs_dp(self, n): :type n: int :rtype: int
- def... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs_rec(self, n): :type n: int :rtype: int
- def climbStairs_cacherec(self, n): :type n: int :rtype: int
- def climbStairs_dp(self, n): :type n: int :rtype: int
- def... | 3f7b2ea959308eb80f4c65be35aaeed666570f80 | <|skeleton|>
class Solution:
def climbStairs_rec(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs_cacherec(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def climbStairs_dp(self, n):
""":type n: int :rtype: int"""
<|body_2|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs_rec(self, n):
""":type n: int :rtype: int"""
if n > 2:
ans = self.climbStairs_rec(n - 1) + self.climbStairs_rec(n - 2)
else:
ans = n
return ans
def climbStairs_cacherec(self, n):
""":type n: int :rtype: int"""
... | the_stack_v2_python_sparse | 70.爬楼梯.py | dxc19951001/Everyday_LeetCode | train | 1 | |
3a8b2f25b2ede5a50ac79f6478866acedd225294 | [
"self.model_statistics = model_statistics\nself.model_constraints = model_constraints\nself.model_data_statistics = model_data_statistics\nself.model_data_constraints = model_data_constraints\nself.bias = bias\nself.bias_pre_training = bias_pre_training\nself.bias_post_training = bias_post_training\nself.explainabi... | <|body_start_0|>
self.model_statistics = model_statistics
self.model_constraints = model_constraints
self.model_data_statistics = model_data_statistics
self.model_data_constraints = model_data_constraints
self.bias = bias
self.bias_pre_training = bias_pre_training
... | Accepts model metrics parameters for conversion to request dict. | ModelMetrics | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelMetrics:
"""Accepts model metrics parameters for conversion to request dict."""
def __init__(self, model_statistics: Optional['MetricsSource']=None, model_constraints: Optional['MetricsSource']=None, model_data_statistics: Optional['MetricsSource']=None, model_data_constraints: Optional... | stack_v2_sparse_classes_36k_train_029176 | 7,143 | permissive | [
{
"docstring": "Initialize a ``ModelMetrics`` instance and turn parameters into dict. Args: model_statistics (MetricsSource): A metric source object that represents model statistics (default: None). model_constraints (MetricsSource): A metric source object that represents model constraints (default: None). mode... | 2 | null | Implement the Python class `ModelMetrics` described below.
Class description:
Accepts model metrics parameters for conversion to request dict.
Method signatures and docstrings:
- def __init__(self, model_statistics: Optional['MetricsSource']=None, model_constraints: Optional['MetricsSource']=None, model_data_statisti... | Implement the Python class `ModelMetrics` described below.
Class description:
Accepts model metrics parameters for conversion to request dict.
Method signatures and docstrings:
- def __init__(self, model_statistics: Optional['MetricsSource']=None, model_constraints: Optional['MetricsSource']=None, model_data_statisti... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class ModelMetrics:
"""Accepts model metrics parameters for conversion to request dict."""
def __init__(self, model_statistics: Optional['MetricsSource']=None, model_constraints: Optional['MetricsSource']=None, model_data_statistics: Optional['MetricsSource']=None, model_data_constraints: Optional... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelMetrics:
"""Accepts model metrics parameters for conversion to request dict."""
def __init__(self, model_statistics: Optional['MetricsSource']=None, model_constraints: Optional['MetricsSource']=None, model_data_statistics: Optional['MetricsSource']=None, model_data_constraints: Optional['MetricsSour... | the_stack_v2_python_sparse | src/sagemaker/model_metrics.py | aws/sagemaker-python-sdk | train | 2,050 |
ed41bfc5515008d62eee2b4e11ec55f39c8710c4 | [
"query = request.GET.get('q')\nsort = request.GET.get('sort', 'name')\nform = PlatformForm()\nlist_platform = None\nif query:\n list_platform = Platform.objects.filter(Q(name_platform__icontains=query))\nelse:\n list_platform = Platform.objects.all()\noutput = {'form': form, 'list_platform': list_platform}\nr... | <|body_start_0|>
query = request.GET.get('q')
sort = request.GET.get('sort', 'name')
form = PlatformForm()
list_platform = None
if query:
list_platform = Platform.objects.filter(Q(name_platform__icontains=query))
else:
list_platform = Platform.obje... | Clase para agregar una plataforma | NewPlatformView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewPlatformView:
"""Clase para agregar una plataforma"""
def get(self, request, *args, **kwargs):
"""Método get"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Método post"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
query = reques... | stack_v2_sparse_classes_36k_train_029177 | 22,221 | no_license | [
{
"docstring": "Método get",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Método post",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005121 | Implement the Python class `NewPlatformView` described below.
Class description:
Clase para agregar una plataforma
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Método get
- def post(self, request, *args, **kwargs): Método post | Implement the Python class `NewPlatformView` described below.
Class description:
Clase para agregar una plataforma
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Método get
- def post(self, request, *args, **kwargs): Método post
<|skeleton|>
class NewPlatformView:
"""Clase para agre... | e28e2d968372609ad396c42fb572a00c2410a117 | <|skeleton|>
class NewPlatformView:
"""Clase para agregar una plataforma"""
def get(self, request, *args, **kwargs):
"""Método get"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Método post"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NewPlatformView:
"""Clase para agregar una plataforma"""
def get(self, request, *args, **kwargs):
"""Método get"""
query = request.GET.get('q')
sort = request.GET.get('sort', 'name')
form = PlatformForm()
list_platform = None
if query:
list_plat... | the_stack_v2_python_sparse | list/views.py | damaos/server_list2 | train | 0 |
caeab58fb0a79f61ec2fb79eade172ced2411470 | [
"self.prodLocation = prodLocation\nself.bingoAssetsFolder = AssetsFolder\nself.roomNumber = roomNumber\nself.gameName = os.path.split(self.prodLocation)[-1]\nself.runit = GeneralConversionCalls.intermediateFunctions(self.prodLocation, self.bingoAssetsFolder, self.roomNumber, False)\nself.GameFileNameSWF = self.game... | <|body_start_0|>
self.prodLocation = prodLocation
self.bingoAssetsFolder = AssetsFolder
self.roomNumber = roomNumber
self.gameName = os.path.split(self.prodLocation)[-1]
self.runit = GeneralConversionCalls.intermediateFunctions(self.prodLocation, self.bingoAssetsFolder, self.room... | Moves all the bingo art from one location to the correct final location with the correct naming convetnion | MoveBingo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MoveBingo:
"""Moves all the bingo art from one location to the correct final location with the correct naming convetnion"""
def __init__(self, prodLocation, AssetsFolder, roomNumber):
"""Set up the location of the origonal art. The final art location and naming of assets"""
<... | stack_v2_sparse_classes_36k_train_029178 | 2,578 | no_license | [
{
"docstring": "Set up the location of the origonal art. The final art location and naming of assets",
"name": "__init__",
"signature": "def __init__(self, prodLocation, AssetsFolder, roomNumber)"
},
{
"docstring": "Worker function call this if you want to move the art from one point to another"... | 2 | null | Implement the Python class `MoveBingo` described below.
Class description:
Moves all the bingo art from one location to the correct final location with the correct naming convetnion
Method signatures and docstrings:
- def __init__(self, prodLocation, AssetsFolder, roomNumber): Set up the location of the origonal art.... | Implement the Python class `MoveBingo` described below.
Class description:
Moves all the bingo art from one location to the correct final location with the correct naming convetnion
Method signatures and docstrings:
- def __init__(self, prodLocation, AssetsFolder, roomNumber): Set up the location of the origonal art.... | 06d179d6ddfebba8fa42c220ce017a52c6bd3377 | <|skeleton|>
class MoveBingo:
"""Moves all the bingo art from one location to the correct final location with the correct naming convetnion"""
def __init__(self, prodLocation, AssetsFolder, roomNumber):
"""Set up the location of the origonal art. The final art location and naming of assets"""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MoveBingo:
"""Moves all the bingo art from one location to the correct final location with the correct naming convetnion"""
def __init__(self, prodLocation, AssetsFolder, roomNumber):
"""Set up the location of the origonal art. The final art location and naming of assets"""
self.prodLocat... | the_stack_v2_python_sparse | FlashArtPipeline/art_pipeline/ExternalCalls/BingoConversion.py | underminerstudios/ScriptBackup | train | 2 |
d33f5928e4414fbed5d4a09ae32baa2c6f413c19 | [
"super(Variational, self).__init__()\nself.hidden_size = hidden_size\nself.latent_size = latent_size\nself.use_identity = use_identity\nif self.use_identity:\n self.hidden_to_mu = nn.Identity()\n self.hidden_to_tanh = nn.Linear(self.hidden_size, self.latent_size)\n self.act_tanh = nn.Tanh()\n self.than_... | <|body_start_0|>
super(Variational, self).__init__()
self.hidden_size = hidden_size
self.latent_size = latent_size
self.use_identity = use_identity
if self.use_identity:
self.hidden_to_mu = nn.Identity()
self.hidden_to_tanh = nn.Linear(self.hidden_size, se... | Variation Layer of Variational AutoEncoder | Variational | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Variational:
"""Variation Layer of Variational AutoEncoder"""
def __init__(self, hidden_size: int, latent_size: int, use_identity: bool=False):
"""Variational Args: hidden_size (int): number of features per time step (output from encoder) latent_size (int): what size the latent vecto... | stack_v2_sparse_classes_36k_train_029179 | 14,969 | permissive | [
{
"docstring": "Variational Args: hidden_size (int): number of features per time step (output from encoder) latent_size (int): what size the latent vector should be use_identity (bool, optional): if identity should be used. Defaults to False.",
"name": "__init__",
"signature": "def __init__(self, hidden... | 2 | stack_v2_sparse_classes_30k_train_018423 | Implement the Python class `Variational` described below.
Class description:
Variation Layer of Variational AutoEncoder
Method signatures and docstrings:
- def __init__(self, hidden_size: int, latent_size: int, use_identity: bool=False): Variational Args: hidden_size (int): number of features per time step (output fr... | Implement the Python class `Variational` described below.
Class description:
Variation Layer of Variational AutoEncoder
Method signatures and docstrings:
- def __init__(self, hidden_size: int, latent_size: int, use_identity: bool=False): Variational Args: hidden_size (int): number of features per time step (output fr... | 5b4a61b5dd0bc259ffe68223877949ef4ebfa5e3 | <|skeleton|>
class Variational:
"""Variation Layer of Variational AutoEncoder"""
def __init__(self, hidden_size: int, latent_size: int, use_identity: bool=False):
"""Variational Args: hidden_size (int): number of features per time step (output from encoder) latent_size (int): what size the latent vecto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Variational:
"""Variation Layer of Variational AutoEncoder"""
def __init__(self, hidden_size: int, latent_size: int, use_identity: bool=False):
"""Variational Args: hidden_size (int): number of features per time step (output from encoder) latent_size (int): what size the latent vector should be u... | the_stack_v2_python_sparse | src/models/anomalia/layers.py | maurony/ts-vrae | train | 1 |
6d7bd2ce2c1bbf766288a37830aa2857d5a1698b | [
"if balance < Decimal('0.00'):\n raise ValueError('Initial balance must be >= 0.00')\nself.name = name\nself.balance = balance",
"if amount < Decimal('0.00'):\n raise ValueError('Amount must be positive')\nself.balance += amount"
] | <|body_start_0|>
if balance < Decimal('0.00'):
raise ValueError('Initial balance must be >= 0.00')
self.name = name
self.balance = balance
<|end_body_0|>
<|body_start_1|>
if amount < Decimal('0.00'):
raise ValueError('Amount must be positive')
self.balanc... | Account class for maintaining a bank account balance | Account | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Account:
"""Account class for maintaining a bank account balance"""
def __init__(self, name, balance):
"""Initialize an Account Object"""
<|body_0|>
def deposit(self, amount):
"""Deposit money to the account"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_029180 | 622 | no_license | [
{
"docstring": "Initialize an Account Object",
"name": "__init__",
"signature": "def __init__(self, name, balance)"
},
{
"docstring": "Deposit money to the account",
"name": "deposit",
"signature": "def deposit(self, amount)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015594 | Implement the Python class `Account` described below.
Class description:
Account class for maintaining a bank account balance
Method signatures and docstrings:
- def __init__(self, name, balance): Initialize an Account Object
- def deposit(self, amount): Deposit money to the account | Implement the Python class `Account` described below.
Class description:
Account class for maintaining a bank account balance
Method signatures and docstrings:
- def __init__(self, name, balance): Initialize an Account Object
- def deposit(self, amount): Deposit money to the account
<|skeleton|>
class Account:
"... | a235a2635316248c8066fdb27074e92635603ee3 | <|skeleton|>
class Account:
"""Account class for maintaining a bank account balance"""
def __init__(self, name, balance):
"""Initialize an Account Object"""
<|body_0|>
def deposit(self, amount):
"""Deposit money to the account"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Account:
"""Account class for maintaining a bank account balance"""
def __init__(self, name, balance):
"""Initialize an Account Object"""
if balance < Decimal('0.00'):
raise ValueError('Initial balance must be >= 0.00')
self.name = name
self.balance = balance
... | the_stack_v2_python_sparse | Chap10_OOP/account.py | kevin-d-mcewan/ClassExamples | train | 0 |
da9bb410435d894fa4d5dfe710a387976b1c1818 | [
"self.preferences = preferences\nsuper(NewsLetterForm, self).__init__(*args, **kwargs)\nself.fields['newsletter_frequency'].initial = preferences.newsletter_frequency\nif preferences.paused_until and preferences.paused_until > now().date():\n self.fields['paused_until'].initial = preferences.paused_until",
"pr... | <|body_start_0|>
self.preferences = preferences
super(NewsLetterForm, self).__init__(*args, **kwargs)
self.fields['newsletter_frequency'].initial = preferences.newsletter_frequency
if preferences.paused_until and preferences.paused_until > now().date():
self.fields['paused_un... | The NewsLetterForm provides a form used to update the user's newsletter preferences | NewsLetterForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewsLetterForm:
"""The NewsLetterForm provides a form used to update the user's newsletter preferences"""
def __init__(self, preferences, *args, **kwargs):
"""Initializes a new instance of the ChangePasswordForm class."""
<|body_0|>
def save(self):
"""Applies the... | stack_v2_sparse_classes_36k_train_029181 | 5,957 | no_license | [
{
"docstring": "Initializes a new instance of the ChangePasswordForm class.",
"name": "__init__",
"signature": "def __init__(self, preferences, *args, **kwargs)"
},
{
"docstring": "Applies the new password to the user and saves it.",
"name": "save",
"signature": "def save(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015395 | Implement the Python class `NewsLetterForm` described below.
Class description:
The NewsLetterForm provides a form used to update the user's newsletter preferences
Method signatures and docstrings:
- def __init__(self, preferences, *args, **kwargs): Initializes a new instance of the ChangePasswordForm class.
- def sa... | Implement the Python class `NewsLetterForm` described below.
Class description:
The NewsLetterForm provides a form used to update the user's newsletter preferences
Method signatures and docstrings:
- def __init__(self, preferences, *args, **kwargs): Initializes a new instance of the ChangePasswordForm class.
- def sa... | b0702a8f7f60de6db9de7f712108e68d66f07f61 | <|skeleton|>
class NewsLetterForm:
"""The NewsLetterForm provides a form used to update the user's newsletter preferences"""
def __init__(self, preferences, *args, **kwargs):
"""Initializes a new instance of the ChangePasswordForm class."""
<|body_0|>
def save(self):
"""Applies the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NewsLetterForm:
"""The NewsLetterForm provides a form used to update the user's newsletter preferences"""
def __init__(self, preferences, *args, **kwargs):
"""Initializes a new instance of the ChangePasswordForm class."""
self.preferences = preferences
super(NewsLetterForm, self).... | the_stack_v2_python_sparse | getdeal/apps/profiles/forms.py | PankeshGupta/getdeal | train | 0 |
f2ef04603e0428e0e6daad5c0f93f1c4748f75ac | [
"res = {'version': __version__}\nres.update(v)\nreturn res",
"use_real_mongo = values.pop('use_real_mongo', None)\nif use_real_mongo is not None:\n warnings.warn(\"'use_real_mongo' is deprecated, please set the appropriate 'database_backend' instead.\", DeprecationWarning)\n if use_real_mongo:\n valu... | <|body_start_0|>
res = {'version': __version__}
res.update(v)
return res
<|end_body_0|>
<|body_start_1|>
use_real_mongo = values.pop('use_real_mongo', None)
if use_real_mongo is not None:
warnings.warn("'use_real_mongo' is deprecated, please set the appropriate 'data... | This class stores server config parameters in a way that can be easily extended for new config file types. | ServerConfig | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServerConfig:
"""This class stores server config parameters in a way that can be easily extended for new config file types."""
def set_implementation_version(cls, v):
"""Set defaults and modify bypassed value(s)"""
<|body_0|>
def use_real_mongo_override(cls, values):
... | stack_v2_sparse_classes_36k_train_029182 | 13,459 | permissive | [
{
"docstring": "Set defaults and modify bypassed value(s)",
"name": "set_implementation_version",
"signature": "def set_implementation_version(cls, v)"
},
{
"docstring": "Overrides the `database_backend` setting with MongoDB and raises a deprecation warning.",
"name": "use_real_mongo_overrid... | 2 | null | Implement the Python class `ServerConfig` described below.
Class description:
This class stores server config parameters in a way that can be easily extended for new config file types.
Method signatures and docstrings:
- def set_implementation_version(cls, v): Set defaults and modify bypassed value(s)
- def use_real_... | Implement the Python class `ServerConfig` described below.
Class description:
This class stores server config parameters in a way that can be easily extended for new config file types.
Method signatures and docstrings:
- def set_implementation_version(cls, v): Set defaults and modify bypassed value(s)
- def use_real_... | a9840269d11ca3f32e5b7d1547e5a49647656264 | <|skeleton|>
class ServerConfig:
"""This class stores server config parameters in a way that can be easily extended for new config file types."""
def set_implementation_version(cls, v):
"""Set defaults and modify bypassed value(s)"""
<|body_0|>
def use_real_mongo_override(cls, values):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServerConfig:
"""This class stores server config parameters in a way that can be easily extended for new config file types."""
def set_implementation_version(cls, v):
"""Set defaults and modify bypassed value(s)"""
res = {'version': __version__}
res.update(v)
return res
... | the_stack_v2_python_sparse | optimade/server/config.py | Materials-Consortia/optimade-python-tools | train | 54 |
1cd13fd81d7ee1ac2eafc5ab84bf218b3d90870c | [
"QtGui.QDialog.__init__(self, parent)\nself.data = data_for_plotting\nself.graph_name = bar_chart_name\nself.ordinate_name = ordinate_name\nself.figure = plt.figure()\nself.canvas = FigureCanvas(self.figure)\nself.toolbar = NavigationToolbar(self.canvas, self)\nlayout = QtGui.QVBoxLayout()\nlayout.addWidget(self.to... | <|body_start_0|>
QtGui.QDialog.__init__(self, parent)
self.data = data_for_plotting
self.graph_name = bar_chart_name
self.ordinate_name = ordinate_name
self.figure = plt.figure()
self.canvas = FigureCanvas(self.figure)
self.toolbar = NavigationToolbar(self.canvas,... | Implements mechanism for plotting of a bar chart for given data. | BarChart | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BarChart:
"""Implements mechanism for plotting of a bar chart for given data."""
def __init__(self, bar_chart_name, ordinate_name, data_for_plotting, parent=None):
"""Make a instance of BarChart class. Args: bar_chart_name (str): It is a name of a bar chart. ordinate_name (str): It i... | stack_v2_sparse_classes_36k_train_029183 | 2,458 | no_license | [
{
"docstring": "Make a instance of BarChart class. Args: bar_chart_name (str): It is a name of a bar chart. ordinate_name (str): It is a ordinate name of a bar chart. data_for_plotting (list): It is a data for plotting of a bar chart.",
"name": "__init__",
"signature": "def __init__(self, bar_chart_name... | 2 | stack_v2_sparse_classes_30k_train_017674 | Implement the Python class `BarChart` described below.
Class description:
Implements mechanism for plotting of a bar chart for given data.
Method signatures and docstrings:
- def __init__(self, bar_chart_name, ordinate_name, data_for_plotting, parent=None): Make a instance of BarChart class. Args: bar_chart_name (str... | Implement the Python class `BarChart` described below.
Class description:
Implements mechanism for plotting of a bar chart for given data.
Method signatures and docstrings:
- def __init__(self, bar_chart_name, ordinate_name, data_for_plotting, parent=None): Make a instance of BarChart class. Args: bar_chart_name (str... | 44d4b2977ee40564629e379f954dd54c68fa2c1a | <|skeleton|>
class BarChart:
"""Implements mechanism for plotting of a bar chart for given data."""
def __init__(self, bar_chart_name, ordinate_name, data_for_plotting, parent=None):
"""Make a instance of BarChart class. Args: bar_chart_name (str): It is a name of a bar chart. ordinate_name (str): It i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BarChart:
"""Implements mechanism for plotting of a bar chart for given data."""
def __init__(self, bar_chart_name, ordinate_name, data_for_plotting, parent=None):
"""Make a instance of BarChart class. Args: bar_chart_name (str): It is a name of a bar chart. ordinate_name (str): It is a ordinate ... | the_stack_v2_python_sparse | gui/BarChart.py | andrei-volkau/ground_station | train | 2 |
a97e4bcaa8292daec01217899686888da783db12 | [
"params = kwarg['params']\ncmd = 'df '\nreturn cmd",
"disk = []\nrecords = output.split('\\n')[1:]\nfor r in records:\n r = r.strip()\n if not r:\n continue\n tokens = r.split()\n filesystem = tokens.pop(0)\n size = int(tokens.pop(0))\n used = int(tokens.pop(0))\n available = int(token... | <|body_start_0|>
params = kwarg['params']
cmd = 'df '
return cmd
<|end_body_0|>
<|body_start_1|>
disk = []
records = output.split('\n')[1:]
for r in records:
r = r.strip()
if not r:
continue
tokens = r.split()
... | Disk free inforamtion | LinuxDiskFreeImpl | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinuxDiskFreeImpl:
"""Disk free inforamtion"""
def format_show(self, command, *argv, **kwarg):
"""> df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 603M 34% /mnt/onl/images /dev/sda1 123M 29M 89M 25% /mnt/o... | stack_v2_sparse_classes_36k_train_029184 | 2,420 | permissive | [
{
"docstring": "> df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 603M 34% /mnt/onl/images /dev/sda1 123M 29M 89M 25% /mnt/onl/boot /dev/sda2 120M 1.6M 110M 2% /mnt/onl/config tmpfs 3.9G 0 3.9G 0% /dev/shm tmpfs 3.9G 8.9M 3.9G 1% /run... | 2 | stack_v2_sparse_classes_30k_val_000769 | Implement the Python class `LinuxDiskFreeImpl` described below.
Class description:
Disk free inforamtion
Method signatures and docstrings:
- def format_show(self, command, *argv, **kwarg): > df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 6... | Implement the Python class `LinuxDiskFreeImpl` described below.
Class description:
Disk free inforamtion
Method signatures and docstrings:
- def format_show(self, command, *argv, **kwarg): > df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 6... | e4c8221e18cd94e7424c30e12eb0fb82f7767267 | <|skeleton|>
class LinuxDiskFreeImpl:
"""Disk free inforamtion"""
def format_show(self, command, *argv, **kwarg):
"""> df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 603M 34% /mnt/onl/images /dev/sda1 123M 29M 89M 25% /mnt/o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinuxDiskFreeImpl:
"""Disk free inforamtion"""
def format_show(self, command, *argv, **kwarg):
"""> df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 603M 34% /mnt/onl/images /dev/sda1 123M 29M 89M 25% /mnt/onl/boot /dev/... | the_stack_v2_python_sparse | Amazon_Framework/DentOsTestbedLib/src/dent_os_testbed/lib/os/linux/linux_disk_free_impl.py | tld3daniel/testing | train | 0 |
651f5aa5df5a0983bd999071d16c2b936ad25145 | [
"if not root:\n return '[]'\nqueue = deque()\nqueue.append(root)\nres = []\nwhile queue:\n node = queue.popleft()\n if node:\n res.append(str(node.val))\n queue.append(node.left)\n queue.append(node.right)\n else:\n res.append('null')\nreturn '[' + ','.join(res) + ']'",
"if... | <|body_start_0|>
if not root:
return '[]'
queue = deque()
queue.append(root)
res = []
while queue:
node = queue.popleft()
if node:
res.append(str(node.val))
queue.append(node.left)
queue.append(no... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_029185 | 1,786 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_018146 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 5cd8a6c99c463ce01f512379bcb265b7f0b99885 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return '[]'
queue = deque()
queue.append(root)
res = []
while queue:
node = queue.popleft()
if node:
... | the_stack_v2_python_sparse | jianzhi_offer/37.py | jingxiufenghua/algorithm_homework | train | 0 | |
5b5765a992c3941137c3b548ffe027dc0a1c19db | [
"super(SoftDotAttention, self).__init__()\ndim2 = dim2 if dim2 is not None else dim\nself.linear_in = nn.Linear(dim, dim2)\nself.sm = nn.Softmax(dim=1)\nself.linear_out = nn.Linear(dim + dim2, dim)\nself.mask = None",
"target = self.linear_in(input).unsqueeze(2)\nkey = context if key is None else key\nattn = torc... | <|body_start_0|>
super(SoftDotAttention, self).__init__()
dim2 = dim2 if dim2 is not None else dim
self.linear_in = nn.Linear(dim, dim2)
self.sm = nn.Softmax(dim=1)
self.linear_out = nn.Linear(dim + dim2, dim)
self.mask = None
<|end_body_0|>
<|body_start_1|>
targ... | Soft Dot Attention. Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT. | SoftDotAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SoftDotAttention:
"""Soft Dot Attention. Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT."""
def __init__(self, dim, dim2=None, heads=1):
"""Initialize layer."""
<|body_0|>
def forward(self, input, context, mask=None, attn_only=False, tok_leve... | stack_v2_sparse_classes_36k_train_029186 | 4,783 | no_license | [
{
"docstring": "Initialize layer.",
"name": "__init__",
"signature": "def __init__(self, dim, dim2=None, heads=1)"
},
{
"docstring": "Propogate input through the network. input: batch x dim context: batch x sourceL x dim",
"name": "forward",
"signature": "def forward(self, input, context... | 2 | stack_v2_sparse_classes_30k_train_021629 | Implement the Python class `SoftDotAttention` described below.
Class description:
Soft Dot Attention. Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT.
Method signatures and docstrings:
- def __init__(self, dim, dim2=None, heads=1): Initialize layer.
- def forward(self, input, context, mask... | Implement the Python class `SoftDotAttention` described below.
Class description:
Soft Dot Attention. Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT.
Method signatures and docstrings:
- def __init__(self, dim, dim2=None, heads=1): Initialize layer.
- def forward(self, input, context, mask... | 12c90a5cb3462afe47424c8608a7595c4db28e58 | <|skeleton|>
class SoftDotAttention:
"""Soft Dot Attention. Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT."""
def __init__(self, dim, dim2=None, heads=1):
"""Initialize layer."""
<|body_0|>
def forward(self, input, context, mask=None, attn_only=False, tok_leve... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SoftDotAttention:
"""Soft Dot Attention. Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT."""
def __init__(self, dim, dim2=None, heads=1):
"""Initialize layer."""
super(SoftDotAttention, self).__init__()
dim2 = dim2 if dim2 is not None else dim
s... | the_stack_v2_python_sparse | utilities/flow_lstm_util/models/lstm_attention.py | mrknight21/open_domain_interviewing_agent | train | 2 |
fe73898049aeb6bce9342b9ae04cba78be372394 | [
"self.gettext_domain = 'screen-resolution-extra'\ngettext.textdomain(self.gettext_domain)\nself.init_strings()",
"result = unicode(gettext.gettext(str), 'UTF-8')\nif convert_keybindings:\n result = self.convert_keybindings(result)\nreturn result",
"self.string_permission_text = self._('Monitor Resolution Set... | <|body_start_0|>
self.gettext_domain = 'screen-resolution-extra'
gettext.textdomain(self.gettext_domain)
self.init_strings()
<|end_body_0|>
<|body_start_1|>
result = unicode(gettext.gettext(str), 'UTF-8')
if convert_keybindings:
result = self.convert_keybindings(resu... | Abstract user interface. This encapsulates the entire program logic and all strings, but does not implement any concrete user interface. | AbstractUI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbstractUI:
"""Abstract user interface. This encapsulates the entire program logic and all strings, but does not implement any concrete user interface."""
def __init__(self):
"""Initialize system."""
<|body_0|>
def _(self, str, convert_keybindings=False):
"""Keyb... | stack_v2_sparse_classes_36k_train_029187 | 2,804 | no_license | [
{
"docstring": "Initialize system.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Keyboard accelerator aware gettext() wrapper. This optionally converts keyboard accelerators to the appropriate format for the frontend. All strings in the source code should use the '_'... | 3 | stack_v2_sparse_classes_30k_train_016074 | Implement the Python class `AbstractUI` described below.
Class description:
Abstract user interface. This encapsulates the entire program logic and all strings, but does not implement any concrete user interface.
Method signatures and docstrings:
- def __init__(self): Initialize system.
- def _(self, str, convert_key... | Implement the Python class `AbstractUI` described below.
Class description:
Abstract user interface. This encapsulates the entire program logic and all strings, but does not implement any concrete user interface.
Method signatures and docstrings:
- def __init__(self): Initialize system.
- def _(self, str, convert_key... | d08f7bf370a82b6970387bb9f165d374a9d9092b | <|skeleton|>
class AbstractUI:
"""Abstract user interface. This encapsulates the entire program logic and all strings, but does not implement any concrete user interface."""
def __init__(self):
"""Initialize system."""
<|body_0|>
def _(self, str, convert_keybindings=False):
"""Keyb... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AbstractUI:
"""Abstract user interface. This encapsulates the entire program logic and all strings, but does not implement any concrete user interface."""
def __init__(self):
"""Initialize system."""
self.gettext_domain = 'screen-resolution-extra'
gettext.textdomain(self.gettext_d... | the_stack_v2_python_sparse | usr/share/pyshared/ScreenResolution/ui.py | haniokasai/netwalker-rootfs | train | 2 |
b01b756a452aeb8a72bf22532397daf9d4c3037c | [
"count = 0\nfor i in range(len(dominoes) - 1):\n for j in range(i + 1, len(dominoes)):\n if dominoes[i][0] == dominoes[j][0] and dominoes[i][1] == dominoes[j][1] or (dominoes[i][1] == dominoes[j][0] and dominoes[i][0] == dominoes[j][1]):\n count += 1\nreturn count",
"data = {}\nfor domino in ... | <|body_start_0|>
count = 0
for i in range(len(dominoes) - 1):
for j in range(i + 1, len(dominoes)):
if dominoes[i][0] == dominoes[j][0] and dominoes[i][1] == dominoes[j][1] or (dominoes[i][1] == dominoes[j][0] and dominoes[i][0] == dominoes[j][1]):
count +... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _numEquivDominoPairs(self, dominoes):
""":type dominoes: List[List[int]] :rtype: int"""
<|body_0|>
def numEquivDominoPairs(self, dominoes):
""":type dominoes: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_029188 | 1,904 | permissive | [
{
"docstring": ":type dominoes: List[List[int]] :rtype: int",
"name": "_numEquivDominoPairs",
"signature": "def _numEquivDominoPairs(self, dominoes)"
},
{
"docstring": ":type dominoes: List[List[int]] :rtype: int",
"name": "numEquivDominoPairs",
"signature": "def numEquivDominoPairs(self... | 2 | stack_v2_sparse_classes_30k_val_000430 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _numEquivDominoPairs(self, dominoes): :type dominoes: List[List[int]] :rtype: int
- def numEquivDominoPairs(self, dominoes): :type dominoes: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _numEquivDominoPairs(self, dominoes): :type dominoes: List[List[int]] :rtype: int
- def numEquivDominoPairs(self, dominoes): :type dominoes: List[List[int]] :rtype: int
<|sk... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _numEquivDominoPairs(self, dominoes):
""":type dominoes: List[List[int]] :rtype: int"""
<|body_0|>
def numEquivDominoPairs(self, dominoes):
""":type dominoes: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _numEquivDominoPairs(self, dominoes):
""":type dominoes: List[List[int]] :rtype: int"""
count = 0
for i in range(len(dominoes) - 1):
for j in range(i + 1, len(dominoes)):
if dominoes[i][0] == dominoes[j][0] and dominoes[i][1] == dominoes[j][1] ... | the_stack_v2_python_sparse | 1128.number-of-equivalent-domino-pairs.py | windard/leeeeee | train | 0 | |
5b632ecf324ee12503ad2107bdcf75f72041b9a0 | [
"proof = 0\nwhile self.valid_proof(last_proof, proof) is False:\n proof += 1\nreturn proof",
"guess = f'{last_proof}{proof}'.encode()\nguess_hash = hashlib.sha256(guess).hexdigest()\nreturn guess_hash[:4] == '0000'"
] | <|body_start_0|>
proof = 0
while self.valid_proof(last_proof, proof) is False:
proof += 1
return proof
<|end_body_0|>
<|body_start_1|>
guess = f'{last_proof}{proof}'.encode()
guess_hash = hashlib.sha256(guess).hexdigest()
return guess_hash[:4] == '0000'
<|end... | Blockchain | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Blockchain:
def proof_of_work(self, last_proof):
"""Algoritmo Simple de Prueba de Trabajo: Buscar un número p' tal que hash(pp') contenga 4 ceros a la izquierda, donde p es la anterior p''. p es la prueba anterior, y p' es la nueva prueba :param last_proof: <int> :return: <int>"""
... | stack_v2_sparse_classes_36k_train_029189 | 11,891 | no_license | [
{
"docstring": "Algoritmo Simple de Prueba de Trabajo: Buscar un número p' tal que hash(pp') contenga 4 ceros a la izquierda, donde p es la anterior p''. p es la prueba anterior, y p' es la nueva prueba :param last_proof: <int> :return: <int>",
"name": "proof_of_work",
"signature": "def proof_of_work(se... | 2 | stack_v2_sparse_classes_30k_train_018640 | Implement the Python class `Blockchain` described below.
Class description:
Implement the Blockchain class.
Method signatures and docstrings:
- def proof_of_work(self, last_proof): Algoritmo Simple de Prueba de Trabajo: Buscar un número p' tal que hash(pp') contenga 4 ceros a la izquierda, donde p es la anterior p''.... | Implement the Python class `Blockchain` described below.
Class description:
Implement the Blockchain class.
Method signatures and docstrings:
- def proof_of_work(self, last_proof): Algoritmo Simple de Prueba de Trabajo: Buscar un número p' tal que hash(pp') contenga 4 ceros a la izquierda, donde p es la anterior p''.... | daba4247cca90c43a979e3e3f292cd7b8951b3d0 | <|skeleton|>
class Blockchain:
def proof_of_work(self, last_proof):
"""Algoritmo Simple de Prueba de Trabajo: Buscar un número p' tal que hash(pp') contenga 4 ceros a la izquierda, donde p es la anterior p''. p es la prueba anterior, y p' es la nueva prueba :param last_proof: <int> :return: <int>"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Blockchain:
def proof_of_work(self, last_proof):
"""Algoritmo Simple de Prueba de Trabajo: Buscar un número p' tal que hash(pp') contenga 4 ceros a la izquierda, donde p es la anterior p''. p es la prueba anterior, y p' es la nueva prueba :param last_proof: <int> :return: <int>"""
proof = 0
... | the_stack_v2_python_sparse | Blockchain/Blockchain1.py | mecomontes/Python | train | 1 | |
ad39751cc6ac7cc54e2738609dcdf25f520f1150 | [
"self.module = module\nself.model_parallel_group = model_parallel_group\nself.model_parallel_world_size = 1 if self.model_parallel_group is None else dist.get_world_size(self.model_parallel_group)\nself.parallelism = parallelism",
"dim1_size = self.module.weight.size(1)\nif self.parallelism == 'input':\n x = d... | <|body_start_0|>
self.module = module
self.model_parallel_group = model_parallel_group
self.model_parallel_world_size = 1 if self.model_parallel_group is None else dist.get_world_size(self.model_parallel_group)
self.parallelism = parallelism
<|end_body_0|>
<|body_start_1|>
dim1_... | ModuleHelper for GPTNeoX layers. | GPTNeoXLinearModuleHelper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GPTNeoXLinearModuleHelper:
"""ModuleHelper for GPTNeoX layers."""
def __init__(self, module: torch.nn.Module, model_parallel_group: dist.ProcessGroup | None, parallelism: Literal['input', 'output']):
"""Init ModuleHelper. Args: module (torch.nn.Module): module in model to wrap. model... | stack_v2_sparse_classes_36k_train_029190 | 2,162 | permissive | [
{
"docstring": "Init ModuleHelper. Args: module (torch.nn.Module): module in model to wrap. model_parallel_group (ProcessGroup): model parallel distributed process group this rank belongs to. If None, it is assumed model parallelism size is 1 (i.e., there is no model parallelism). parallelism (str): \"input\" i... | 3 | stack_v2_sparse_classes_30k_train_003584 | Implement the Python class `GPTNeoXLinearModuleHelper` described below.
Class description:
ModuleHelper for GPTNeoX layers.
Method signatures and docstrings:
- def __init__(self, module: torch.nn.Module, model_parallel_group: dist.ProcessGroup | None, parallelism: Literal['input', 'output']): Init ModuleHelper. Args:... | Implement the Python class `GPTNeoXLinearModuleHelper` described below.
Class description:
ModuleHelper for GPTNeoX layers.
Method signatures and docstrings:
- def __init__(self, module: torch.nn.Module, model_parallel_group: dist.ProcessGroup | None, parallelism: Literal['input', 'output']): Init ModuleHelper. Args:... | e2b0c7dd1b1534e53389e7af9c070164b50b5968 | <|skeleton|>
class GPTNeoXLinearModuleHelper:
"""ModuleHelper for GPTNeoX layers."""
def __init__(self, module: torch.nn.Module, model_parallel_group: dist.ProcessGroup | None, parallelism: Literal['input', 'output']):
"""Init ModuleHelper. Args: module (torch.nn.Module): module in model to wrap. model... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GPTNeoXLinearModuleHelper:
"""ModuleHelper for GPTNeoX layers."""
def __init__(self, module: torch.nn.Module, model_parallel_group: dist.ProcessGroup | None, parallelism: Literal['input', 'output']):
"""Init ModuleHelper. Args: module (torch.nn.Module): module in model to wrap. model_parallel_gro... | the_stack_v2_python_sparse | kfac/gpt_neox/modules.py | gpauloski/kfac-pytorch | train | 29 |
cd2f4524b8b0f1bf5869c7228957671d012236c2 | [
"super().__init__()\nassert (kernel_size - 1) % 2 == 0\nself.kernel_size = kernel_size\nself.pointwise_conv1 = torch.nn.Conv1d(channels, 2 * channels, kernel_size=1, stride=1, padding=0)\nif causal:\n self.lorder = kernel_size - 1\n padding = 0\nelse:\n self.lorder = 0\n padding = (kernel_size - 1) // 2... | <|body_start_0|>
super().__init__()
assert (kernel_size - 1) % 2 == 0
self.kernel_size = kernel_size
self.pointwise_conv1 = torch.nn.Conv1d(channels, 2 * channels, kernel_size=1, stride=1, padding=0)
if causal:
self.lorder = kernel_size - 1
padding = 0
... | ConformerConvolution module definition. Args: channels: The number of channels. kernel_size: Size of the convolving kernel. activation: Activation function. norm_args: Normalization module arguments. causal: Whether to use causal convolution (set to True if streaming). | ConformerConvolution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConformerConvolution:
"""ConformerConvolution module definition. Args: channels: The number of channels. kernel_size: Size of the convolving kernel. activation: Activation function. norm_args: Normalization module arguments. causal: Whether to use causal convolution (set to True if streaming)."""... | stack_v2_sparse_classes_36k_train_029191 | 7,416 | permissive | [
{
"docstring": "Construct an ConformerConvolution object.",
"name": "__init__",
"signature": "def __init__(self, channels: int, kernel_size: int, activation: torch.nn.Module=torch.nn.ReLU(), norm_args: Dict={}, causal: bool=False) -> None"
},
{
"docstring": "Compute convolution module. Args: x: ... | 2 | null | Implement the Python class `ConformerConvolution` described below.
Class description:
ConformerConvolution module definition. Args: channels: The number of channels. kernel_size: Size of the convolving kernel. activation: Activation function. norm_args: Normalization module arguments. causal: Whether to use causal con... | Implement the Python class `ConformerConvolution` described below.
Class description:
ConformerConvolution module definition. Args: channels: The number of channels. kernel_size: Size of the convolving kernel. activation: Activation function. norm_args: Normalization module arguments. causal: Whether to use causal con... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class ConformerConvolution:
"""ConformerConvolution module definition. Args: channels: The number of channels. kernel_size: Size of the convolving kernel. activation: Activation function. norm_args: Normalization module arguments. causal: Whether to use causal convolution (set to True if streaming)."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConformerConvolution:
"""ConformerConvolution module definition. Args: channels: The number of channels. kernel_size: Size of the convolving kernel. activation: Activation function. norm_args: Normalization module arguments. causal: Whether to use causal convolution (set to True if streaming)."""
def __i... | the_stack_v2_python_sparse | espnet2/asr_transducer/encoder/modules/convolution.py | espnet/espnet | train | 7,242 |
f54aeed44b551aa2eb2a75dd4d85bccd44a97262 | [
"result = '{key:s}{type:s}'.format(key=self.oauth_consumer_key, type=' [cs]' if self.consumer_site_id else ' [pl]' if self.playlist_id else '')\nif self.deleted:\n result = _('{:s}[deleted]').format(result)\nreturn result",
"if self.consumer_site and self.playlist:\n message = _('You should set either a Con... | <|body_start_0|>
result = '{key:s}{type:s}'.format(key=self.oauth_consumer_key, type=' [cs]' if self.consumer_site_id else ' [pl]' if self.playlist_id else '')
if self.deleted:
result = _('{:s}[deleted]').format(result)
return result
<|end_body_0|>
<|body_start_1|>
if self.c... | Model representing an LTI passport for LTI consumers to interact with Marsha. An LTI passport stores credentials that can be used by an LTI consumer to interact with Marsha acting as an LTI provider. A passport can be granted for: - a playlist: to be used when we trust an instructor. A playlist pre-exists in Marsha. Th... | LTIPassport | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LTIPassport:
"""Model representing an LTI passport for LTI consumers to interact with Marsha. An LTI passport stores credentials that can be used by an LTI consumer to interact with Marsha acting as an LTI provider. A passport can be granted for: - a playlist: to be used when we trust an instruct... | stack_v2_sparse_classes_36k_train_029192 | 20,635 | permissive | [
{
"docstring": "Get the string representation of an instance.",
"name": "__str__",
"signature": "def __str__(self)"
},
{
"docstring": "Clean instance fields before saving.",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Generate the oauth consumer key and sha... | 3 | stack_v2_sparse_classes_30k_train_015972 | Implement the Python class `LTIPassport` described below.
Class description:
Model representing an LTI passport for LTI consumers to interact with Marsha. An LTI passport stores credentials that can be used by an LTI consumer to interact with Marsha acting as an LTI provider. A passport can be granted for: - a playlis... | Implement the Python class `LTIPassport` described below.
Class description:
Model representing an LTI passport for LTI consumers to interact with Marsha. An LTI passport stores credentials that can be used by an LTI consumer to interact with Marsha acting as an LTI provider. A passport can be granted for: - a playlis... | f767f1bdc12c9712f26ea17cb8b19f536389f0ed | <|skeleton|>
class LTIPassport:
"""Model representing an LTI passport for LTI consumers to interact with Marsha. An LTI passport stores credentials that can be used by an LTI consumer to interact with Marsha acting as an LTI provider. A passport can be granted for: - a playlist: to be used when we trust an instruct... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LTIPassport:
"""Model representing an LTI passport for LTI consumers to interact with Marsha. An LTI passport stores credentials that can be used by an LTI consumer to interact with Marsha acting as an LTI provider. A passport can be granted for: - a playlist: to be used when we trust an instructor. A playlis... | the_stack_v2_python_sparse | src/backend/marsha/core/models/account.py | openfun/marsha | train | 92 |
13c028befe5a2a313429babf1c5f74bd7ca142b7 | [
"if self.storage_manager.state == 1:\n repseq_map_gen = self.find_rid_by_tid(ids, subs=subs, iterator=True)\n\n def acc_generator():\n \"\"\"\"\"\"\n for taxon_id, repseq_ids in repseq_map_gen:\n yield (taxon_id, self._retrieve_accs_by_id(repseq_ids))\n acc_gen = acc_generator()\n ... | <|body_start_0|>
if self.storage_manager.state == 1:
repseq_map_gen = self.find_rid_by_tid(ids, subs=subs, iterator=True)
def acc_generator():
""""""
for taxon_id, repseq_ids in repseq_map_gen:
yield (taxon_id, self._retrieve_accs_by_i... | Mixin class for handling accession numbers data. | DatabaseAccessionMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatabaseAccessionMixin:
"""Mixin class for handling accession numbers data."""
def get_accession_by_tid(self, ids: Optional[AnyGenericIdentifier]=None, subs: bool=False, iterator: bool=True) -> Union[Dict[GenericIdentifier, Dict[str, str]], Generator[Tuple[GenericIdentifier, Dict[str, str]],... | stack_v2_sparse_classes_36k_train_029193 | 3,852 | permissive | [
{
"docstring": "Get accession numbers from the database. Parameters ---------- ids Target :term:`tids`. Use None for all :term:`tids` subs If True :term:`subs` will be included. Default is False. iterator If True return a generator object. Default is True. Returns ------- If `iterator` is True Returns a :class:... | 3 | null | Implement the Python class `DatabaseAccessionMixin` described below.
Class description:
Mixin class for handling accession numbers data.
Method signatures and docstrings:
- def get_accession_by_tid(self, ids: Optional[AnyGenericIdentifier]=None, subs: bool=False, iterator: bool=True) -> Union[Dict[GenericIdentifier, ... | Implement the Python class `DatabaseAccessionMixin` described below.
Class description:
Mixin class for handling accession numbers data.
Method signatures and docstrings:
- def get_accession_by_tid(self, ids: Optional[AnyGenericIdentifier]=None, subs: bool=False, iterator: bool=True) -> Union[Dict[GenericIdentifier, ... | 028364e018f5f22a89aef9d4a86df9ba706747b5 | <|skeleton|>
class DatabaseAccessionMixin:
"""Mixin class for handling accession numbers data."""
def get_accession_by_tid(self, ids: Optional[AnyGenericIdentifier]=None, subs: bool=False, iterator: bool=True) -> Union[Dict[GenericIdentifier, Dict[str, str]], Generator[Tuple[GenericIdentifier, Dict[str, str]],... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatabaseAccessionMixin:
"""Mixin class for handling accession numbers data."""
def get_accession_by_tid(self, ids: Optional[AnyGenericIdentifier]=None, subs: bool=False, iterator: bool=True) -> Union[Dict[GenericIdentifier, Dict[str, str]], Generator[Tuple[GenericIdentifier, Dict[str, str]], None, None]]... | the_stack_v2_python_sparse | pmaf/database/_core/_acs_base.py | mmtechslv/PhyloMAF | train | 1 |
5b1951ca4052c764fabe5b2de4fc4aef32f6bd68 | [
"if n == 1:\n return '1'\nif n == 2:\n return '11'\nresult = '11'\nflag = 2\nwhile flag < n:\n result = self.count(result)\n flag += 1\nreturn result",
"index = []\ncount = []\nindex.append(input[0])\ncount.append(1)\nfor i in range(1, len(input)):\n if input[i] == input[i - 1]:\n count[-1] ... | <|body_start_0|>
if n == 1:
return '1'
if n == 2:
return '11'
result = '11'
flag = 2
while flag < n:
result = self.count(result)
flag += 1
return result
<|end_body_0|>
<|body_start_1|>
index = []
count = []
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countAndSay(self, n: int) -> str:
"""主函数，控制遍历描述函数的次数 :param n: :return:"""
<|body_0|>
def count(self, input):
"""对上一次结果描述的函数 :param input: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 1:
return '1'
... | stack_v2_sparse_classes_36k_train_029194 | 2,116 | no_license | [
{
"docstring": "主函数，控制遍历描述函数的次数 :param n: :return:",
"name": "countAndSay",
"signature": "def countAndSay(self, n: int) -> str"
},
{
"docstring": "对上一次结果描述的函数 :param input: :return:",
"name": "count",
"signature": "def count(self, input)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000558 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countAndSay(self, n: int) -> str: 主函数，控制遍历描述函数的次数 :param n: :return:
- def count(self, input): 对上一次结果描述的函数 :param input: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countAndSay(self, n: int) -> str: 主函数，控制遍历描述函数的次数 :param n: :return:
- def count(self, input): 对上一次结果描述的函数 :param input: :return:
<|skeleton|>
class Solution:
def count... | fa45cd44c3d4e7b0205833efcdc708d1638cbbe4 | <|skeleton|>
class Solution:
def countAndSay(self, n: int) -> str:
"""主函数，控制遍历描述函数的次数 :param n: :return:"""
<|body_0|>
def count(self, input):
"""对上一次结果描述的函数 :param input: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countAndSay(self, n: int) -> str:
"""主函数，控制遍历描述函数的次数 :param n: :return:"""
if n == 1:
return '1'
if n == 2:
return '11'
result = '11'
flag = 2
while flag < n:
result = self.count(result)
flag += 1
... | the_stack_v2_python_sparse | Python/t38.py | g-lyc/LeetCode | train | 15 | |
4530e501baae4bb0e5befc7809451034758d92c6 | [
"if loot_actions is None:\n return False\nloot_actions.apply_to_resolver(resolver)\nreturn True",
"loot_actions = CommonLootActionUtils.load_loot_actions_by_id(loot_actions_id)\nif loot_actions is None:\n return False\nloot_actions.apply_to_resolver(resolver)\nreturn True",
"has_applied_at_least_one = Fal... | <|body_start_0|>
if loot_actions is None:
return False
loot_actions.apply_to_resolver(resolver)
return True
<|end_body_0|>
<|body_start_1|>
loot_actions = CommonLootActionUtils.load_loot_actions_by_id(loot_actions_id)
if loot_actions is None:
return False... | Utilities for manipulating Loot Actions. | CommonLootActionUtils | [
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommonLootActionUtils:
"""Utilities for manipulating Loot Actions."""
def apply_loot_actions_using_resolver(loot_actions: LootActions, resolver: Resolver) -> bool:
"""apply_loot_actions_using_resolver(loot_actions, resolver) Apply loot actions using a resolver. :param loot_actions: T... | stack_v2_sparse_classes_36k_train_029195 | 4,906 | permissive | [
{
"docstring": "apply_loot_actions_using_resolver(loot_actions, resolver) Apply loot actions using a resolver. :param loot_actions: The loot actions to apply. :type loot_actions: LootActions :param resolver: A resolver used in various ways by loot actions. The resolver could be a SingleSimResolver, which will a... | 4 | null | Implement the Python class `CommonLootActionUtils` described below.
Class description:
Utilities for manipulating Loot Actions.
Method signatures and docstrings:
- def apply_loot_actions_using_resolver(loot_actions: LootActions, resolver: Resolver) -> bool: apply_loot_actions_using_resolver(loot_actions, resolver) Ap... | Implement the Python class `CommonLootActionUtils` described below.
Class description:
Utilities for manipulating Loot Actions.
Method signatures and docstrings:
- def apply_loot_actions_using_resolver(loot_actions: LootActions, resolver: Resolver) -> bool: apply_loot_actions_using_resolver(loot_actions, resolver) Ap... | 58e7beb30b9c818b294d35abd2436a0192cd3e82 | <|skeleton|>
class CommonLootActionUtils:
"""Utilities for manipulating Loot Actions."""
def apply_loot_actions_using_resolver(loot_actions: LootActions, resolver: Resolver) -> bool:
"""apply_loot_actions_using_resolver(loot_actions, resolver) Apply loot actions using a resolver. :param loot_actions: T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommonLootActionUtils:
"""Utilities for manipulating Loot Actions."""
def apply_loot_actions_using_resolver(loot_actions: LootActions, resolver: Resolver) -> bool:
"""apply_loot_actions_using_resolver(loot_actions, resolver) Apply loot actions using a resolver. :param loot_actions: The loot actio... | the_stack_v2_python_sparse | Scripts/sims4communitylib/utils/resources/common_loot_action_utils.py | ColonolNutty/Sims4CommunityLibrary | train | 183 |
14ae5040f647c5c2727a54de11be143983505526 | [
"if self.type_transformation is not None:\n self.type_transformation = self.type_transformation.upper()\n if self.type_transformation not in ['AA', 'AD', 'DA', 'DD']:\n raise ValueError(f\"Invalid type transformation: {self.type_transformation}\\nValid values are 'AA', 'AD', 'DA' and 'DD'.\")\nif self.... | <|body_start_0|>
if self.type_transformation is not None:
self.type_transformation = self.type_transformation.upper()
if self.type_transformation not in ['AA', 'AD', 'DA', 'DD']:
raise ValueError(f"Invalid type transformation: {self.type_transformation}\nValid values are ... | Describes the transformation of a signal. | SignalTransformation | [
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignalTransformation:
"""Describes the transformation of a signal."""
def __post_init__(self):
"""Perform some tests after construction."""
<|body_0|>
def _evaluate_function(self):
"""Evaluate the internal function."""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_029196 | 37,433 | permissive | [
{
"docstring": "Perform some tests after construction.",
"name": "__post_init__",
"signature": "def __post_init__(self)"
},
{
"docstring": "Evaluate the internal function.",
"name": "_evaluate_function",
"signature": "def _evaluate_function(self)"
}
] | 2 | null | Implement the Python class `SignalTransformation` described below.
Class description:
Describes the transformation of a signal.
Method signatures and docstrings:
- def __post_init__(self): Perform some tests after construction.
- def _evaluate_function(self): Evaluate the internal function. | Implement the Python class `SignalTransformation` described below.
Class description:
Describes the transformation of a signal.
Method signatures and docstrings:
- def __post_init__(self): Perform some tests after construction.
- def _evaluate_function(self): Evaluate the internal function.
<|skeleton|>
class Signal... | 7bc16a196ee669822f3663f3c7a08f6bbd0c76d5 | <|skeleton|>
class SignalTransformation:
"""Describes the transformation of a signal."""
def __post_init__(self):
"""Perform some tests after construction."""
<|body_0|>
def _evaluate_function(self):
"""Evaluate the internal function."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SignalTransformation:
"""Describes the transformation of a signal."""
def __post_init__(self):
"""Perform some tests after construction."""
if self.type_transformation is not None:
self.type_transformation = self.type_transformation.upper()
if self.type_transformat... | the_stack_v2_python_sparse | weldx/measurement.py | BAMWelDX/weldx | train | 20 |
473f84025c780a0448ab090db9cf15a8a5a84ed1 | [
"self.user_01 = get_user_model().objects.create_user(username='user_01', password='12345678')\nself.user_02 = get_user_model().objects.create_user(username='user_02', password='12345678')\nself.email_pref_01 = EmailPreference.objects.create(user_id=self.user_01.id)\nself.email_pref_02 = EmailPreference.objects.crea... | <|body_start_0|>
self.user_01 = get_user_model().objects.create_user(username='user_01', password='12345678')
self.user_02 = get_user_model().objects.create_user(username='user_02', password='12345678')
self.email_pref_01 = EmailPreference.objects.create(user_id=self.user_01.id)
self.ema... | Unsubscribe API test | UnsubscribeAPITest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnsubscribeAPITest:
"""Unsubscribe API test"""
def setUp(self):
"""Set up"""
<|body_0|>
def test_unsubscribe(self):
"""Test unsubscribe"""
<|body_1|>
def test_unsubscribe_invalid_username(self):
"""Test unsubscribe with invalid username"""
... | stack_v2_sparse_classes_36k_train_029197 | 17,449 | permissive | [
{
"docstring": "Set up",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test unsubscribe",
"name": "test_unsubscribe",
"signature": "def test_unsubscribe(self)"
},
{
"docstring": "Test unsubscribe with invalid username",
"name": "test_unsubscribe_invalid_u... | 6 | stack_v2_sparse_classes_30k_train_014112 | Implement the Python class `UnsubscribeAPITest` described below.
Class description:
Unsubscribe API test
Method signatures and docstrings:
- def setUp(self): Set up
- def test_unsubscribe(self): Test unsubscribe
- def test_unsubscribe_invalid_username(self): Test unsubscribe with invalid username
- def test_unsubscri... | Implement the Python class `UnsubscribeAPITest` described below.
Class description:
Unsubscribe API test
Method signatures and docstrings:
- def setUp(self): Set up
- def test_unsubscribe(self): Test unsubscribe
- def test_unsubscribe_invalid_username(self): Test unsubscribe with invalid username
- def test_unsubscri... | cf429f43251ad7e77c0d9bc9fe91bb030ca8bae8 | <|skeleton|>
class UnsubscribeAPITest:
"""Unsubscribe API test"""
def setUp(self):
"""Set up"""
<|body_0|>
def test_unsubscribe(self):
"""Test unsubscribe"""
<|body_1|>
def test_unsubscribe_invalid_username(self):
"""Test unsubscribe with invalid username"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UnsubscribeAPITest:
"""Unsubscribe API test"""
def setUp(self):
"""Set up"""
self.user_01 = get_user_model().objects.create_user(username='user_01', password='12345678')
self.user_02 = get_user_model().objects.create_user(username='user_02', password='12345678')
self.email... | the_stack_v2_python_sparse | user/tests.py | 810Teams/clubs-and-events-backend | train | 3 |
62cadba52319831c7d29cf0e345dad1244cba96d | [
"client = get_client_by_request(request)\ninfo = client.cmsi.get_msg_type()\nalls = info['data']\nfor app in alls:\n print(app['is_active'])\n print(app['label'])\n print(app['type'])\n print('*' * 30)\nreturn JsonResponse(info)",
"receiver = request.GET.get('receiver')\ntitle = request.GET.get('title... | <|body_start_0|>
client = get_client_by_request(request)
info = client.cmsi.get_msg_type()
alls = info['data']
for app in alls:
print(app['is_active'])
print(app['label'])
print(app['type'])
print('*' * 30)
return JsonResponse(info)... | PaasCmsi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PaasCmsi:
def get_msg_type(cls, request):
"""查询消息发送类型"""
<|body_0|>
def send_mail(cls, request):
"""发送邮件"""
<|body_1|>
def send_sms(cls, request):
"""发送短信"""
<|body_2|>
def send_weixin(cls, request):
"""发送微信"""
<|body... | stack_v2_sparse_classes_36k_train_029198 | 5,818 | no_license | [
{
"docstring": "查询消息发送类型",
"name": "get_msg_type",
"signature": "def get_msg_type(cls, request)"
},
{
"docstring": "发送邮件",
"name": "send_mail",
"signature": "def send_mail(cls, request)"
},
{
"docstring": "发送短信",
"name": "send_sms",
"signature": "def send_sms(cls, request... | 4 | null | Implement the Python class `PaasCmsi` described below.
Class description:
Implement the PaasCmsi class.
Method signatures and docstrings:
- def get_msg_type(cls, request): 查询消息发送类型
- def send_mail(cls, request): 发送邮件
- def send_sms(cls, request): 发送短信
- def send_weixin(cls, request): 发送微信 | Implement the Python class `PaasCmsi` described below.
Class description:
Implement the PaasCmsi class.
Method signatures and docstrings:
- def get_msg_type(cls, request): 查询消息发送类型
- def send_mail(cls, request): 发送邮件
- def send_sms(cls, request): 发送短信
- def send_weixin(cls, request): 发送微信
<|skeleton|>
class PaasCmsi... | 1911aadda75fc25c78f6fb37852111deb50052c0 | <|skeleton|>
class PaasCmsi:
def get_msg_type(cls, request):
"""查询消息发送类型"""
<|body_0|>
def send_mail(cls, request):
"""发送邮件"""
<|body_1|>
def send_sms(cls, request):
"""发送短信"""
<|body_2|>
def send_weixin(cls, request):
"""发送微信"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PaasCmsi:
def get_msg_type(cls, request):
"""查询消息发送类型"""
client = get_client_by_request(request)
info = client.cmsi.get_msg_type()
alls = info['data']
for app in alls:
print(app['is_active'])
print(app['label'])
print(app['type'])
... | the_stack_v2_python_sparse | BK/exam_api_test/home_application/api_views.py | Louis-King123/projects | train | 0 | |
59b06542a499b4a746f18f68ab1bb2b3ba8165d2 | [
"if model._meta.app_label in LABELS:\n return model._meta.app_label\nreturn None",
"if model._meta.app_label in LABELS:\n return model._meta.app_label\nreturn None",
"db_label1 = obj1._meta.app_label\ndb_label2 = obj2._meta.app_label\nif db_label1 and db_label2:\n if db_label1 == db_label2:\n re... | <|body_start_0|>
if model._meta.app_label in LABELS:
return model._meta.app_label
return None
<|end_body_0|>
<|body_start_1|>
if model._meta.app_label in LABELS:
return model._meta.app_label
return None
<|end_body_1|>
<|body_start_2|>
db_label1 = obj1._m... | A router to control all database operations on models for different databases. | DatabaseAppsRouter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatabaseAppsRouter:
"""A router to control all database operations on models for different databases."""
def db_for_read(self, model, **hints):
""""Point all read operations to the specific database."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Point ... | stack_v2_sparse_classes_36k_train_029199 | 1,746 | no_license | [
{
"docstring": "\"Point all read operations to the specific database.",
"name": "db_for_read",
"signature": "def db_for_read(self, model, **hints)"
},
{
"docstring": "Point all write operations to the specific database.",
"name": "db_for_write",
"signature": "def db_for_write(self, model... | 5 | stack_v2_sparse_classes_30k_train_005378 | Implement the Python class `DatabaseAppsRouter` described below.
Class description:
A router to control all database operations on models for different databases.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): "Point all read operations to the specific database.
- def db_for_write(self, mo... | Implement the Python class `DatabaseAppsRouter` described below.
Class description:
A router to control all database operations on models for different databases.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): "Point all read operations to the specific database.
- def db_for_write(self, mo... | 1b0e863ff3977471f5a94ef7d990796a9e9669c4 | <|skeleton|>
class DatabaseAppsRouter:
"""A router to control all database operations on models for different databases."""
def db_for_read(self, model, **hints):
""""Point all read operations to the specific database."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Point ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatabaseAppsRouter:
"""A router to control all database operations on models for different databases."""
def db_for_read(self, model, **hints):
""""Point all read operations to the specific database."""
if model._meta.app_label in LABELS:
return model._meta.app_label
r... | the_stack_v2_python_sparse | project/logchart/logchart/databaseRouter.py | P79N6A/project_code | train | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.