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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3df4e1858e26fe7e014b54b644efe469609bcf35 | [
"result = {}\nup_off_station = format_result2one(StudentLineSeat().get_one_bus_station(login_user_id))\nbus_station_list = format_result(StudentLineSeat().get_all_bus_station(login_user_id))\nif up_off_station and bus_station_list:\n result['up_off_station'] = up_off_station\n result['bus_station_list'] = bus... | <|body_start_0|>
result = {}
up_off_station = format_result2one(StudentLineSeat().get_one_bus_station(login_user_id))
bus_station_list = format_result(StudentLineSeat().get_all_bus_station(login_user_id))
if up_off_station and bus_station_list:
result['up_off_station'] = up_o... | BusStationService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BusStationService:
def get_bus_station(self, login_user_id):
"""获取校车列表"""
<|body_0|>
def update_bus_station(self, login_user_id, info):
"""修改上下车站点 :param login_user_id: :param info: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = {... | stack_v2_sparse_classes_36k_train_020900 | 2,478 | no_license | [
{
"docstring": "获取校车列表",
"name": "get_bus_station",
"signature": "def get_bus_station(self, login_user_id)"
},
{
"docstring": "修改上下车站点 :param login_user_id: :param info: :return:",
"name": "update_bus_station",
"signature": "def update_bus_station(self, login_user_id, info)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001292 | Implement the Python class `BusStationService` described below.
Class description:
Implement the BusStationService class.
Method signatures and docstrings:
- def get_bus_station(self, login_user_id): 获取校车列表
- def update_bus_station(self, login_user_id, info): 修改上下车站点 :param login_user_id: :param info: :return: | Implement the Python class `BusStationService` described below.
Class description:
Implement the BusStationService class.
Method signatures and docstrings:
- def get_bus_station(self, login_user_id): 获取校车列表
- def update_bus_station(self, login_user_id, info): 修改上下车站点 :param login_user_id: :param info: :return:
<|ske... | a7cf5a0b6daa372ed860dc43d92c55fcde764eb9 | <|skeleton|>
class BusStationService:
def get_bus_station(self, login_user_id):
"""获取校车列表"""
<|body_0|>
def update_bus_station(self, login_user_id, info):
"""修改上下车站点 :param login_user_id: :param info: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BusStationService:
def get_bus_station(self, login_user_id):
"""获取校车列表"""
result = {}
up_off_station = format_result2one(StudentLineSeat().get_one_bus_station(login_user_id))
bus_station_list = format_result(StudentLineSeat().get_all_bus_station(login_user_id))
if up_of... | the_stack_v2_python_sparse | python_project/smart_schoolBus_project/app/schoolbus_situation/services/bus_station_service.py | malqch/aibus | train | 0 | |
ee67d5cd5b790a807698b12233d15949a1caa381 | [
"for i in range(1, len(s), 1):\n if len(s) % i == 0:\n t = s[0:i]\n if self.isit(s, t):\n return True\nreturn False",
"for i in range(0, len(s), len(t)):\n if s[i:i + len(t)] != t:\n return False\nreturn True"
] | <|body_start_0|>
for i in range(1, len(s), 1):
if len(s) % i == 0:
t = s[0:i]
if self.isit(s, t):
return True
return False
<|end_body_0|>
<|body_start_1|>
for i in range(0, len(s), len(t)):
if s[i:i + len(t)] != t:
... | 静态类 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""静态类"""
def repeatedSubstringPattern(self, s: str) -> bool:
"""题目要求 :param s: :return:"""
<|body_0|>
def isit(self, s: str, t: str) -> bool:
"""判断t是否是S的循环子串 :param s: 大串 :param t: 小串 :return: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_020901 | 891 | no_license | [
{
"docstring": "题目要求 :param s: :return:",
"name": "repeatedSubstringPattern",
"signature": "def repeatedSubstringPattern(self, s: str) -> bool"
},
{
"docstring": "判断t是否是S的循环子串 :param s: 大串 :param t: 小串 :return: bool",
"name": "isit",
"signature": "def isit(self, s: str, t: str) -> bool"
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
静态类
Method signatures and docstrings:
- def repeatedSubstringPattern(self, s: str) -> bool: 题目要求 :param s: :return:
- def isit(self, s: str, t: str) -> bool: 判断t是否是S的循环子串 :param s: 大串 :param t: 小串 :return: bool | Implement the Python class `Solution` described below.
Class description:
静态类
Method signatures and docstrings:
- def repeatedSubstringPattern(self, s: str) -> bool: 题目要求 :param s: :return:
- def isit(self, s: str, t: str) -> bool: 判断t是否是S的循环子串 :param s: 大串 :param t: 小串 :return: bool
<|skeleton|>
class Solution:
... | c7becb56e207ee2de6dbf662c98db7eb5b9471ff | <|skeleton|>
class Solution:
"""静态类"""
def repeatedSubstringPattern(self, s: str) -> bool:
"""题目要求 :param s: :return:"""
<|body_0|>
def isit(self, s: str, t: str) -> bool:
"""判断t是否是S的循环子串 :param s: 大串 :param t: 小串 :return: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""静态类"""
def repeatedSubstringPattern(self, s: str) -> bool:
"""题目要求 :param s: :return:"""
for i in range(1, len(s), 1):
if len(s) % i == 0:
t = s[0:i]
if self.isit(s, t):
return True
return False
def ... | the_stack_v2_python_sparse | problemset/459. 重复的子字符串/solution.py | KevenGe/LeetCode-Solutions | train | 1 |
24cd457259d79a1d81d4a951c9c228a1402cf834 | [
"if isinstance(key, int):\n return RouterAlert(key)\nif key not in RouterAlert._member_map_:\n extend_enum(RouterAlert, key, default)\nreturn RouterAlert[key]",
"if not (isinstance(value, int) and 0 <= value <= 65535):\n raise ValueError('%r is not a valid %s' % (value, cls.__name__))\nif 66 <= value <= ... | <|body_start_0|>
if isinstance(key, int):
return RouterAlert(key)
if key not in RouterAlert._member_map_:
extend_enum(RouterAlert, key, default)
return RouterAlert[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and 0 <= value <= 65535):
... | Enumeration class for RouterAlert. | RouterAlert | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RouterAlert:
"""Enumeration class for RouterAlert."""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_36k_train_020902 | 7,255 | no_license | [
{
"docstring": "Backport support for original codes.",
"name": "get",
"signature": "def get(key, default=-1)"
},
{
"docstring": "Lookup function used when value is not found.",
"name": "_missing_",
"signature": "def _missing_(cls, value)"
}
] | 2 | null | Implement the Python class `RouterAlert` described below.
Class description:
Enumeration class for RouterAlert.
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found. | Implement the Python class `RouterAlert` described below.
Class description:
Enumeration class for RouterAlert.
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found.
<|skeleton|>
class RouterAlert:... | fd43ccca1d032f8f230c4467dcb5df757669ef13 | <|skeleton|>
class RouterAlert:
"""Enumeration class for RouterAlert."""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RouterAlert:
"""Enumeration class for RouterAlert."""
def get(key, default=-1):
"""Backport support for original codes."""
if isinstance(key, int):
return RouterAlert(key)
if key not in RouterAlert._member_map_:
extend_enum(RouterAlert, key, default)
... | the_stack_v2_python_sparse | venv/lib/python3.6/site-packages/pcapkit/const/ipv4/router_alert.py | IvanLetteri/MLfeaturesExtractor | train | 0 |
f86f7cfb1d1410c499eb26df1a33f74c37600c25 | [
"if hook_name in ('startup', 'shutdown') and controller is not None:\n raise TGConfigError('Startup and Shutdown hooks cannot be registered on controllers')\nif hook_name == 'controller_wrapper':\n raise TGConfigError('tg.hooks.wrap_controller must be used to register wrappers')\nif controller is None:\n c... | <|body_start_0|>
if hook_name in ('startup', 'shutdown') and controller is not None:
raise TGConfigError('Startup and Shutdown hooks cannot be registered on controllers')
if hook_name == 'controller_wrapper':
raise TGConfigError('tg.hooks.wrap_controller must be used to register ... | Manages hooks registrations and notifications | _TGHooks | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _TGHooks:
"""Manages hooks registrations and notifications"""
def register(self, hook_name, func, controller=None):
"""Registers a TurboGears hook. Given an hook name and a function it registers the provided function for that role. For a complete list of hooks provided by default hav... | stack_v2_sparse_classes_36k_train_020903 | 7,031 | no_license | [
{
"docstring": "Registers a TurboGears hook. Given an hook name and a function it registers the provided function for that role. For a complete list of hooks provided by default have a look at :ref:`hooks_and_events`. It permits to register hooks both application wide or for specific controllers:: tg.hooks.regi... | 4 | stack_v2_sparse_classes_30k_train_000859 | Implement the Python class `_TGHooks` described below.
Class description:
Manages hooks registrations and notifications
Method signatures and docstrings:
- def register(self, hook_name, func, controller=None): Registers a TurboGears hook. Given an hook name and a function it registers the provided function for that r... | Implement the Python class `_TGHooks` described below.
Class description:
Manages hooks registrations and notifications
Method signatures and docstrings:
- def register(self, hook_name, func, controller=None): Registers a TurboGears hook. Given an hook name and a function it registers the provided function for that r... | fcf1955cafc34c25986a14b841a9f05d11dd86d0 | <|skeleton|>
class _TGHooks:
"""Manages hooks registrations and notifications"""
def register(self, hook_name, func, controller=None):
"""Registers a TurboGears hook. Given an hook name and a function it registers the provided function for that role. For a complete list of hooks provided by default hav... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _TGHooks:
"""Manages hooks registrations and notifications"""
def register(self, hook_name, func, controller=None):
"""Registers a TurboGears hook. Given an hook name and a function it registers the provided function for that role. For a complete list of hooks provided by default have a look at :... | the_stack_v2_python_sparse | tgenv/lib/python2.6/site-packages/tg/configuration/hooks.py | garrettmc/TGWikiTutorial | train | 1 |
4b6d1a60fde46b36f10518a8b0683bbfab40a08f | [
"if n < 1 or m < 1:\n return -1\nremainIndex = 0\nfor i in range(1, n + 1):\n remainIndex = (remainIndex + m) % i\nreturn remainIndex",
"if n < 1 or m < 1:\n return -1\nnode = head = LinkNode(0)\nfor i in range(1, n):\n head.next = LinkNode(i)\n head = head.next\nhead.next = node\ncount = 1\nwhile ... | <|body_start_0|>
if n < 1 or m < 1:
return -1
remainIndex = 0
for i in range(1, n + 1):
remainIndex = (remainIndex + m) % i
return remainIndex
<|end_body_0|>
<|body_start_1|>
if n < 1 or m < 1:
return -1
node = head = LinkNode(0)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def LastRemaining_Solution(self, n, m):
"""数学解法"""
<|body_0|>
def LastRemaining(self, n, m):
"""链表解法, 0, 1, 2, 3, 4... 报数分别是1, 2, 3"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n < 1 or m < 1:
return -1
remainInde... | stack_v2_sparse_classes_36k_train_020904 | 4,311 | no_license | [
{
"docstring": "数学解法",
"name": "LastRemaining_Solution",
"signature": "def LastRemaining_Solution(self, n, m)"
},
{
"docstring": "链表解法, 0, 1, 2, 3, 4... 报数分别是1, 2, 3",
"name": "LastRemaining",
"signature": "def LastRemaining(self, n, m)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def LastRemaining_Solution(self, n, m): 数学解法
- def LastRemaining(self, n, m): 链表解法, 0, 1, 2, 3, 4... 报数分别是1, 2, 3 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def LastRemaining_Solution(self, n, m): 数学解法
- def LastRemaining(self, n, m): 链表解法, 0, 1, 2, 3, 4... 报数分别是1, 2, 3
<|skeleton|>
class Solution:
def LastRemaining_Solution(se... | 8c0c2a8bcd51825e6902e4d03dabbaf6f303ba83 | <|skeleton|>
class Solution:
def LastRemaining_Solution(self, n, m):
"""数学解法"""
<|body_0|>
def LastRemaining(self, n, m):
"""链表解法, 0, 1, 2, 3, 4... 报数分别是1, 2, 3"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def LastRemaining_Solution(self, n, m):
"""数学解法"""
if n < 1 or m < 1:
return -1
remainIndex = 0
for i in range(1, n + 1):
remainIndex = (remainIndex + m) % i
return remainIndex
def LastRemaining(self, n, m):
"""链表解法, 0, 1, ... | the_stack_v2_python_sparse | python_fundemental/45_Joseph_Game.py | Deanwinger/python_project | train | 0 | |
e05fa7d75fe7e6999ff70beb79c92004f036a7f5 | [
"env = management.env['sale.order']\ndate_begin = date_bx + ' 05:00:00'\ndate_end_dt = datetime.datetime.strptime(date_ex, _DATE_FORMAT) + datetime.timedelta(hours=24) + datetime.timedelta(hours=5, minutes=0)\ndate_end = date_end_dt.strftime(_DATE_HOUR_FORMAT)\nimplementor = OdooDbImpl(env, date_begin, date_end, do... | <|body_start_0|>
env = management.env['sale.order']
date_begin = date_bx + ' 05:00:00'
date_end_dt = datetime.datetime.strptime(date_ex, _DATE_FORMAT) + datetime.timedelta(hours=24) + datetime.timedelta(hours=5, minutes=0)
date_end = date_end_dt.strftime(_DATE_HOUR_FORMAT)
implem... | ManagementDb | ManagementDb | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManagementDb:
"""ManagementDb"""
def get_orders_filter_by_doctor(management, date_bx, date_ex, doctor):
"""Provides sales between begin date and end date. Filters: by Doctor. Used by - Management"""
<|body_0|>
def get_orders_filter(management, date_bx, date_ex, state_arr... | stack_v2_sparse_classes_36k_train_020905 | 6,978 | no_license | [
{
"docstring": "Provides sales between begin date and end date. Filters: by Doctor. Used by - Management",
"name": "get_orders_filter_by_doctor",
"signature": "def get_orders_filter_by_doctor(management, date_bx, date_ex, doctor)"
},
{
"docstring": "Used by Management",
"name": "get_orders_f... | 4 | null | Implement the Python class `ManagementDb` described below.
Class description:
ManagementDb
Method signatures and docstrings:
- def get_orders_filter_by_doctor(management, date_bx, date_ex, doctor): Provides sales between begin date and end date. Filters: by Doctor. Used by - Management
- def get_orders_filter(managem... | Implement the Python class `ManagementDb` described below.
Class description:
ManagementDb
Method signatures and docstrings:
- def get_orders_filter_by_doctor(management, date_bx, date_ex, doctor): Provides sales between begin date and end date. Filters: by Doctor. Used by - Management
- def get_orders_filter(managem... | c15f8b146392d47a9040404a4ac8e45a1b062198 | <|skeleton|>
class ManagementDb:
"""ManagementDb"""
def get_orders_filter_by_doctor(management, date_bx, date_ex, doctor):
"""Provides sales between begin date and end date. Filters: by Doctor. Used by - Management"""
<|body_0|>
def get_orders_filter(management, date_bx, date_ex, state_arr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ManagementDb:
"""ManagementDb"""
def get_orders_filter_by_doctor(management, date_bx, date_ex, doctor):
"""Provides sales between begin date and end date. Filters: by Doctor. Used by - Management"""
env = management.env['sale.order']
date_begin = date_bx + ' 05:00:00'
date... | the_stack_v2_python_sparse | models/management/management_db.py | gibil5/openhealth | train | 1 |
32c54e1bbd090701fa95ef6740b368281cb9ef20 | [
"QMainWindow.__init__(self, parent)\nui_path = os.path.join(os.path.dirname(__file__), 'gui/import.ui')\nself.ui = load_ui(ui_path, baseinstance=self)\nself._myParent = parent\nself._myProjectName = ''\nself._myIPTS = None\nself._currRowIndex = -1\nself._numRows = 0\nself.ui.pushButton_selectAll.clicked.connect(sel... | <|body_start_0|>
QMainWindow.__init__(self, parent)
ui_path = os.path.join(os.path.dirname(__file__), 'gui/import.ui')
self.ui = load_ui(ui_path, baseinstance=self)
self._myParent = parent
self._myProjectName = ''
self._myIPTS = None
self._currRowIndex = -1
... | GUI (sub) for select run to reduce as final decision before reduction | FinalSelectRunToReduceDialog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FinalSelectRunToReduceDialog:
"""GUI (sub) for select run to reduce as final decision before reduction"""
def __init__(self, parent):
"""Set up main window"""
<|body_0|>
def doClearAllSelection(self):
"""Clear all selected runs for not reduction"""
<|body... | stack_v2_sparse_classes_36k_train_020906 | 5,669 | no_license | [
{
"docstring": "Set up main window",
"name": "__init__",
"signature": "def __init__(self, parent)"
},
{
"docstring": "Clear all selected runs for not reduction",
"name": "doClearAllSelection",
"signature": "def doClearAllSelection(self)"
},
{
"docstring": "Select all runs to redu... | 6 | stack_v2_sparse_classes_30k_train_010108 | Implement the Python class `FinalSelectRunToReduceDialog` described below.
Class description:
GUI (sub) for select run to reduce as final decision before reduction
Method signatures and docstrings:
- def __init__(self, parent): Set up main window
- def doClearAllSelection(self): Clear all selected runs for not reduct... | Implement the Python class `FinalSelectRunToReduceDialog` described below.
Class description:
GUI (sub) for select run to reduce as final decision before reduction
Method signatures and docstrings:
- def __init__(self, parent): Set up main window
- def doClearAllSelection(self): Clear all selected runs for not reduct... | 875a5b99a7a6f51129844bf8052fc6f231497d71 | <|skeleton|>
class FinalSelectRunToReduceDialog:
"""GUI (sub) for select run to reduce as final decision before reduction"""
def __init__(self, parent):
"""Set up main window"""
<|body_0|>
def doClearAllSelection(self):
"""Clear all selected runs for not reduction"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FinalSelectRunToReduceDialog:
"""GUI (sub) for select run to reduce as final decision before reduction"""
def __init__(self, parent):
"""Set up main window"""
QMainWindow.__init__(self, parent)
ui_path = os.path.join(os.path.dirname(__file__), 'gui/import.ui')
self.ui = lo... | the_stack_v2_python_sparse | pyvdrive/interface/Dialog_FinalSelectRunToReduce.py | neutrons/PyVDrive | train | 2 |
a32042b9b4e4880db0f7f2b220bcd15349d90c89 | [
"GroupFactory(type_id='area')\nurl = reverse('ietf.secr.areas.views.list_areas')\nself.client.login(username='secretary', password='secretary+password')\nresponse = self.client.get(url)\nself.assertEqual(response.status_code, 200)",
"area = GroupEventFactory(type='started', group__type_id='area').group\nurl = rev... | <|body_start_0|>
GroupFactory(type_id='area')
url = reverse('ietf.secr.areas.views.list_areas')
self.client.login(username='secretary', password='secretary+password')
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
<|end_body_0|>
<|body_start_1|>
... | SecrAreasTestCase | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecrAreasTestCase:
def test_main(self):
"""Main Test"""
<|body_0|>
def test_view(self):
"""View Test"""
<|body_1|>
def test_add(self):
"""Add Test"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
GroupFactory(type_id='area')
... | stack_v2_sparse_classes_36k_train_020907 | 1,934 | permissive | [
{
"docstring": "Main Test",
"name": "test_main",
"signature": "def test_main(self)"
},
{
"docstring": "View Test",
"name": "test_view",
"signature": "def test_view(self)"
},
{
"docstring": "Add Test",
"name": "test_add",
"signature": "def test_add(self)"
}
] | 3 | stack_v2_sparse_classes_30k_train_006754 | Implement the Python class `SecrAreasTestCase` described below.
Class description:
Implement the SecrAreasTestCase class.
Method signatures and docstrings:
- def test_main(self): Main Test
- def test_view(self): View Test
- def test_add(self): Add Test | Implement the Python class `SecrAreasTestCase` described below.
Class description:
Implement the SecrAreasTestCase class.
Method signatures and docstrings:
- def test_main(self): Main Test
- def test_view(self): View Test
- def test_add(self): Add Test
<|skeleton|>
class SecrAreasTestCase:
def test_main(self):
... | aeaae292fbd55aca1b6043227ec105e67d73367f | <|skeleton|>
class SecrAreasTestCase:
def test_main(self):
"""Main Test"""
<|body_0|>
def test_view(self):
"""View Test"""
<|body_1|>
def test_add(self):
"""Add Test"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SecrAreasTestCase:
def test_main(self):
"""Main Test"""
GroupFactory(type_id='area')
url = reverse('ietf.secr.areas.views.list_areas')
self.client.login(username='secretary', password='secretary+password')
response = self.client.get(url)
self.assertEqual(respons... | the_stack_v2_python_sparse | ietf/secr/areas/tests.py | omunroe-com/ietfdb2 | train | 2 | |
b5827e0479028da039e67738a0081c76486a77d6 | [
"if not inorder or not postorder:\n return None\nroot_v = postorder.pop()\nroot = TreeNode(root_v)\nroot_index = inorder.index(root_v)\nleft_inorder, right_inorder = (inorder[:root_index], inorder[root_index + 1:])\nleft_postorder, right_postorder = (postorder[:len(left_inorder)], postorder[len(left_inorder):])\... | <|body_start_0|>
if not inorder or not postorder:
return None
root_v = postorder.pop()
root = TreeNode(root_v)
root_index = inorder.index(root_v)
left_inorder, right_inorder = (inorder[:root_index], inorder[root_index + 1:])
left_postorder, right_postorder = (... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def buildTree(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTree1(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
<|bod... | stack_v2_sparse_classes_36k_train_020908 | 2,184 | no_license | [
{
"docstring": ":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode",
"name": "buildTree",
"signature": "def buildTree(self, inorder, postorder)"
},
{
"docstring": ":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode",
"name": "buildTree1",
"signature": ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, inorder, postorder): :type inorder: List[int] :type postorder: List[int] :rtype: TreeNode
- def buildTree1(self, inorder, postorder): :type inorder: List[int]... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, inorder, postorder): :type inorder: List[int] :type postorder: List[int] :rtype: TreeNode
- def buildTree1(self, inorder, postorder): :type inorder: List[int]... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def buildTree(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTree1(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def buildTree(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
if not inorder or not postorder:
return None
root_v = postorder.pop()
root = TreeNode(root_v)
root_index = inorder.index(root_v)
... | the_stack_v2_python_sparse | 106.从中序与后序遍历序列构造二叉树.py | yangyuxiang1996/leetcode | train | 0 | |
f1714e047dd62af8cda94e7f0f065c0b02983926 | [
"res = []\nif num // 100 != 0:\n res.append(self.dict[num // 100])\n res.append('Hundred')\n num %= 100\nif num != 0:\n if num < 21:\n res.append(self.dict[num])\n else:\n res.append(self.dict[num // 10 * 10])\n if num % 10 != 0:\n res.append(self.dict[num % 10])\nretu... | <|body_start_0|>
res = []
if num // 100 != 0:
res.append(self.dict[num // 100])
res.append('Hundred')
num %= 100
if num != 0:
if num < 21:
res.append(self.dict[num])
else:
res.append(self.dict[num // 10 *... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _convensionWithinThousand(self, num):
"""convert to words for number within one thousand"""
<|body_0|>
def numberToWords(self, num):
""":type num: int :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
if num ... | stack_v2_sparse_classes_36k_train_020909 | 2,195 | no_license | [
{
"docstring": "convert to words for number within one thousand",
"name": "_convensionWithinThousand",
"signature": "def _convensionWithinThousand(self, num)"
},
{
"docstring": ":type num: int :rtype: str",
"name": "numberToWords",
"signature": "def numberToWords(self, num)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _convensionWithinThousand(self, num): convert to words for number within one thousand
- def numberToWords(self, num): :type num: int :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _convensionWithinThousand(self, num): convert to words for number within one thousand
- def numberToWords(self, num): :type num: int :rtype: str
<|skeleton|>
class Solution:... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def _convensionWithinThousand(self, num):
"""convert to words for number within one thousand"""
<|body_0|>
def numberToWords(self, num):
""":type num: int :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _convensionWithinThousand(self, num):
"""convert to words for number within one thousand"""
res = []
if num // 100 != 0:
res.append(self.dict[num // 100])
res.append('Hundred')
num %= 100
if num != 0:
if num < 21:
... | the_stack_v2_python_sparse | code273IntegerToEnglishWords.py | cybelewang/leetcode-python | train | 0 | |
b41ac4610f28f45088ba8ce584e8c2d8b10393f1 | [
"try:\n if 'created' in kwargs:\n extra = TYPE_FIXES.get(self.translator.provider_instance.driver.type, {})\n self.translator.provider_instance.driver.create_zone(domain=self.name, type=self.type, ttl=self.ttl, extra=extra)\n else:\n LOGGER.warning('libcloud Zone updating not implemented'... | <|body_start_0|>
try:
if 'created' in kwargs:
extra = TYPE_FIXES.get(self.translator.provider_instance.driver.type, {})
self.translator.provider_instance.driver.create_zone(domain=self.name, type=self.type, ttl=self.ttl, extra=extra)
else:
... | LCloud intermediate Zone object | LCloudZoneObject | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LCloudZoneObject:
"""LCloud intermediate Zone object"""
def save(self, **kwargs) -> ProviderResult:
"""Save this instance"""
<|body_0|>
def delete(self, **kwargs) -> ProviderResult:
"""Delete this instance"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_020910 | 2,645 | permissive | [
{
"docstring": "Save this instance",
"name": "save",
"signature": "def save(self, **kwargs) -> ProviderResult"
},
{
"docstring": "Delete this instance",
"name": "delete",
"signature": "def delete(self, **kwargs) -> ProviderResult"
}
] | 2 | stack_v2_sparse_classes_30k_train_005000 | Implement the Python class `LCloudZoneObject` described below.
Class description:
LCloud intermediate Zone object
Method signatures and docstrings:
- def save(self, **kwargs) -> ProviderResult: Save this instance
- def delete(self, **kwargs) -> ProviderResult: Delete this instance | Implement the Python class `LCloudZoneObject` described below.
Class description:
LCloud intermediate Zone object
Method signatures and docstrings:
- def save(self, **kwargs) -> ProviderResult: Save this instance
- def delete(self, **kwargs) -> ProviderResult: Delete this instance
<|skeleton|>
class LCloudZoneObject... | 2305b1e27abb0bfe9fcee93b79e012c62cba712e | <|skeleton|>
class LCloudZoneObject:
"""LCloud intermediate Zone object"""
def save(self, **kwargs) -> ProviderResult:
"""Save this instance"""
<|body_0|>
def delete(self, **kwargs) -> ProviderResult:
"""Delete this instance"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LCloudZoneObject:
"""LCloud intermediate Zone object"""
def save(self, **kwargs) -> ProviderResult:
"""Save this instance"""
try:
if 'created' in kwargs:
extra = TYPE_FIXES.get(self.translator.provider_instance.driver.type, {})
self.translator.p... | the_stack_v2_python_sparse | supervisr/provider/libcloud/providers/translators/zone.py | BeryJu/supervisr | train | 1 |
49bea5216e02a8c891f34824e163cd961e813ca2 | [
"self.string = pageinfo\nself.isvalid = True\nself.begin = bsl\nself.endloc = 0\nself.discount = self.find(self.string, gds, end, cb=True)\nself.price = self.find(self.string, gps, end)\nself.ogprice = self.find(self.string, gops, end)\nself.name = self.find(self.string, gns, end, cwe=True)",
"try:\n startloc ... | <|body_start_0|>
self.string = pageinfo
self.isvalid = True
self.begin = bsl
self.endloc = 0
self.discount = self.find(self.string, gds, end, cb=True)
self.price = self.find(self.string, gps, end)
self.ogprice = self.find(self.string, gops, end)
self.name ... | game | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class game:
def __init__(self, pageinfo, bsl: int, gns, gds, gps, gops, end):
"""Arguments: bsl is the beginning search location. It should be an integer pageinfo is the html of a website converted to a string gns is the 'game's name start'; it is what to look for directly before a game's name... | stack_v2_sparse_classes_36k_train_020911 | 4,903 | permissive | [
{
"docstring": "Arguments: bsl is the beginning search location. It should be an integer pageinfo is the html of a website converted to a string gns is the 'game's name start'; it is what to look for directly before a game's name gds is the 'game's discount start'; it is what to look for directly before a game'... | 2 | null | Implement the Python class `game` described below.
Class description:
Implement the game class.
Method signatures and docstrings:
- def __init__(self, pageinfo, bsl: int, gns, gds, gps, gops, end): Arguments: bsl is the beginning search location. It should be an integer pageinfo is the html of a website converted to ... | Implement the Python class `game` described below.
Class description:
Implement the game class.
Method signatures and docstrings:
- def __init__(self, pageinfo, bsl: int, gns, gds, gps, gops, end): Arguments: bsl is the beginning search location. It should be an integer pageinfo is the html of a website converted to ... | 8648e42feb610228021b42646c1c4c8b929e745a | <|skeleton|>
class game:
def __init__(self, pageinfo, bsl: int, gns, gds, gps, gops, end):
"""Arguments: bsl is the beginning search location. It should be an integer pageinfo is the html of a website converted to a string gns is the 'game's name start'; it is what to look for directly before a game's name... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class game:
def __init__(self, pageinfo, bsl: int, gns, gds, gps, gops, end):
"""Arguments: bsl is the beginning search location. It should be an integer pageinfo is the html of a website converted to a string gns is the 'game's name start'; it is what to look for directly before a game's name gds is the 'g... | the_stack_v2_python_sparse | 3_advanced/chapter20/solutions/txt_write_practice.py | thestrawberryqueen/python | train | 0 | |
dc3eb246d561af1c0ff95b3feed58fb6b9e1ba5b | [
"def func_recursion(node, lower=float('-inf'), upper=float('inf')):\n if not node:\n return True\n val = node.val\n if val <= lower or val >= upper:\n return False\n if not func_recursion(node.left, lower, val):\n return False\n if not func_recursion(node.right, val, upper):\n ... | <|body_start_0|>
def func_recursion(node, lower=float('-inf'), upper=float('inf')):
if not node:
return True
val = node.val
if val <= lower or val >= upper:
return False
if not func_recursion(node.left, lower, val):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValidBST(self, root):
"""递归法判定给出的二叉树是否为BST。 复杂度分析 时间复杂度 : O(N)。每个结点访问一次。 空间复杂度 : O(N)。跟进了整棵树。 :param root: :return:"""
<|body_0|>
def isValidBST_iteration(self, root):
"""迭代法判断二叉树是否为BST 复杂度分析 时间复杂度 : O(N)O(N)。每个结点访问一次。 空间复杂度 : O(N)O(N)。我们跟进了整棵树。 :para... | stack_v2_sparse_classes_36k_train_020912 | 3,189 | no_license | [
{
"docstring": "递归法判定给出的二叉树是否为BST。 复杂度分析 时间复杂度 : O(N)。每个结点访问一次。 空间复杂度 : O(N)。跟进了整棵树。 :param root: :return:",
"name": "isValidBST",
"signature": "def isValidBST(self, root)"
},
{
"docstring": "迭代法判断二叉树是否为BST 复杂度分析 时间复杂度 : O(N)O(N)。每个结点访问一次。 空间复杂度 : O(N)O(N)。我们跟进了整棵树。 :param root: :return:",
"... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST(self, root): 递归法判定给出的二叉树是否为BST。 复杂度分析 时间复杂度 : O(N)。每个结点访问一次。 空间复杂度 : O(N)。跟进了整棵树。 :param root: :return:
- def isValidBST_iteration(self, root): 迭代法判断二叉树是否为BST 复杂度分... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST(self, root): 递归法判定给出的二叉树是否为BST。 复杂度分析 时间复杂度 : O(N)。每个结点访问一次。 空间复杂度 : O(N)。跟进了整棵树。 :param root: :return:
- def isValidBST_iteration(self, root): 迭代法判断二叉树是否为BST 复杂度分... | 62ad010a992c031e8c0fe4d1a9b6f9364f96ed4c | <|skeleton|>
class Solution:
def isValidBST(self, root):
"""递归法判定给出的二叉树是否为BST。 复杂度分析 时间复杂度 : O(N)。每个结点访问一次。 空间复杂度 : O(N)。跟进了整棵树。 :param root: :return:"""
<|body_0|>
def isValidBST_iteration(self, root):
"""迭代法判断二叉树是否为BST 复杂度分析 时间复杂度 : O(N)O(N)。每个结点访问一次。 空间复杂度 : O(N)O(N)。我们跟进了整棵树。 :para... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isValidBST(self, root):
"""递归法判定给出的二叉树是否为BST。 复杂度分析 时间复杂度 : O(N)。每个结点访问一次。 空间复杂度 : O(N)。跟进了整棵树。 :param root: :return:"""
def func_recursion(node, lower=float('-inf'), upper=float('inf')):
if not node:
return True
val = node.val
... | the_stack_v2_python_sparse | leetcode/solved/098_.py | usnnu/python_foundation | train | 0 | |
1cec0651b533ca798a85d01220d1c25bdee42354 | [
"CalendarHelper = calendar_helpers.CalendarHelper\nnumber_of_participants = len(participants)\ndates_of_month = CalendarHelper.get_days_of_month(year, month)\nlist_of_saturdays = CalendarHelper.get_day_list_of_month(year, month, SATURDAY)\nlist_invalid_saturdays = []\nfor index, is_valid_sat in enumerate(saturday_l... | <|body_start_0|>
CalendarHelper = calendar_helpers.CalendarHelper
number_of_participants = len(participants)
dates_of_month = CalendarHelper.get_days_of_month(year, month)
list_of_saturdays = CalendarHelper.get_day_list_of_month(year, month, SATURDAY)
list_invalid_saturdays = []
... | Class containing helper methods to create Roster. | CreateRosterHelper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateRosterHelper:
"""Class containing helper methods to create Roster."""
def prepare_roster(self, participants: List[model_init_service.ModelService.get_participant_model_class], holiday_list: List[datetime.date], saturday_list: List[bool], is_sunday_included: bool, session_list: List[str... | stack_v2_sparse_classes_36k_train_020913 | 4,575 | permissive | [
{
"docstring": "Method to get the list containig number of sessions for each participants and the remaining days to be catered. The return value would be as follows<br>",
"name": "prepare_roster",
"signature": "def prepare_roster(self, participants: List[model_init_service.ModelService.get_participant_m... | 2 | stack_v2_sparse_classes_30k_val_001104 | Implement the Python class `CreateRosterHelper` described below.
Class description:
Class containing helper methods to create Roster.
Method signatures and docstrings:
- def prepare_roster(self, participants: List[model_init_service.ModelService.get_participant_model_class], holiday_list: List[datetime.date], saturda... | Implement the Python class `CreateRosterHelper` described below.
Class description:
Class containing helper methods to create Roster.
Method signatures and docstrings:
- def prepare_roster(self, participants: List[model_init_service.ModelService.get_participant_model_class], holiday_list: List[datetime.date], saturda... | 23131aff6e0c20497bde632ed32aadcad0947e56 | <|skeleton|>
class CreateRosterHelper:
"""Class containing helper methods to create Roster."""
def prepare_roster(self, participants: List[model_init_service.ModelService.get_participant_model_class], holiday_list: List[datetime.date], saturday_list: List[bool], is_sunday_included: bool, session_list: List[str... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateRosterHelper:
"""Class containing helper methods to create Roster."""
def prepare_roster(self, participants: List[model_init_service.ModelService.get_participant_model_class], holiday_list: List[datetime.date], saturday_list: List[bool], is_sunday_included: bool, session_list: List[str], year: int,... | the_stack_v2_python_sparse | roster-backend/roster_project/roster_api/utils/helpers/business_helpers/create_roster_helper.py | akhilanil/roster | train | 0 |
005f3a262959acbc5d028dbf38c3b7335056a283 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | A set of methods for managing Organization users. | UserServiceServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserServiceServicer:
"""A set of methods for managing Organization users."""
def ListMembers(self, request, context):
"""List organization active members."""
<|body_0|>
def DeleteMembership(self, request, context):
"""Delete user membership."""
<|body_1|>... | stack_v2_sparse_classes_36k_train_020914 | 4,946 | permissive | [
{
"docstring": "List organization active members.",
"name": "ListMembers",
"signature": "def ListMembers(self, request, context)"
},
{
"docstring": "Delete user membership.",
"name": "DeleteMembership",
"signature": "def DeleteMembership(self, request, context)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006564 | Implement the Python class `UserServiceServicer` described below.
Class description:
A set of methods for managing Organization users.
Method signatures and docstrings:
- def ListMembers(self, request, context): List organization active members.
- def DeleteMembership(self, request, context): Delete user membership. | Implement the Python class `UserServiceServicer` described below.
Class description:
A set of methods for managing Organization users.
Method signatures and docstrings:
- def ListMembers(self, request, context): List organization active members.
- def DeleteMembership(self, request, context): Delete user membership.
... | b906a014dd893e2697864e1e48e814a8d9fbc48c | <|skeleton|>
class UserServiceServicer:
"""A set of methods for managing Organization users."""
def ListMembers(self, request, context):
"""List organization active members."""
<|body_0|>
def DeleteMembership(self, request, context):
"""Delete user membership."""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserServiceServicer:
"""A set of methods for managing Organization users."""
def ListMembers(self, request, context):
"""List organization active members."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplemented... | the_stack_v2_python_sparse | yandex/cloud/organizationmanager/v1/user_service_pb2_grpc.py | yandex-cloud/python-sdk | train | 63 |
50e49557d9f115fb046b3b381dee29d439bf8d1f | [
"values = {'class_path': None, 'enabled': True, 'in_progress_behavior': None, 'name': name, 'locked': False, 'profile': None, 'protected': False, 'region': None, 'required_by': None, 'requires': None, 'stack_name': None, 'stack_policy_path': None, 'tags': None, 'template_path': None, 'termination_protection': False... | <|body_start_0|>
values = {'class_path': None, 'enabled': True, 'in_progress_behavior': None, 'name': name, 'locked': False, 'profile': None, 'protected': False, 'region': None, 'required_by': None, 'requires': None, 'stack_name': None, 'stack_policy_path': None, 'tags': None, 'template_path': None, 'terminatio... | Stack definition for use in hooks to avoid cyclic imports. | HookStackDefinition | [
"Apache-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HookStackDefinition:
"""Stack definition for use in hooks to avoid cyclic imports."""
def __init__(self, name, **kwargs):
"""Instantiate class."""
<|body_0|>
def __getattr__(self, key):
"""Implement dot notation."""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_020915 | 9,661 | permissive | [
{
"docstring": "Instantiate class.",
"name": "__init__",
"signature": "def __init__(self, name, **kwargs)"
},
{
"docstring": "Implement dot notation.",
"name": "__getattr__",
"signature": "def __getattr__(self, key)"
}
] | 2 | null | Implement the Python class `HookStackDefinition` described below.
Class description:
Stack definition for use in hooks to avoid cyclic imports.
Method signatures and docstrings:
- def __init__(self, name, **kwargs): Instantiate class.
- def __getattr__(self, key): Implement dot notation. | Implement the Python class `HookStackDefinition` described below.
Class description:
Stack definition for use in hooks to avoid cyclic imports.
Method signatures and docstrings:
- def __init__(self, name, **kwargs): Instantiate class.
- def __getattr__(self, key): Implement dot notation.
<|skeleton|>
class HookStack... | 94aebff4f83b294653192a1b74111f6a9f114de2 | <|skeleton|>
class HookStackDefinition:
"""Stack definition for use in hooks to avoid cyclic imports."""
def __init__(self, name, **kwargs):
"""Instantiate class."""
<|body_0|>
def __getattr__(self, key):
"""Implement dot notation."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HookStackDefinition:
"""Stack definition for use in hooks to avoid cyclic imports."""
def __init__(self, name, **kwargs):
"""Instantiate class."""
values = {'class_path': None, 'enabled': True, 'in_progress_behavior': None, 'name': name, 'locked': False, 'profile': None, 'protected': Fals... | the_stack_v2_python_sparse | runway/cfngin/hooks/base.py | edgarpoce/runway | train | 1 |
7d48359e5b9532ada9a0bf6ce0859bfacef18e85 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AppliedConditionalAccessPolicy()",
"from .applied_conditional_access_policy_result import AppliedConditionalAccessPolicyResult\nfrom .applied_conditional_access_policy_result import AppliedConditionalAccessPolicyResult\nfields: Dict[st... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AppliedConditionalAccessPolicy()
<|end_body_0|>
<|body_start_1|>
from .applied_conditional_access_policy_result import AppliedConditionalAccessPolicyResult
from .applied_conditional_acce... | AppliedConditionalAccessPolicy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AppliedConditionalAccessPolicy:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppliedConditionalAccessPolicy:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator v... | stack_v2_sparse_classes_36k_train_020916 | 4,450 | 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: AppliedConditionalAccessPolicy",
"name": "create_from_discriminator_value",
"signature": "def create_from_di... | 3 | stack_v2_sparse_classes_30k_train_017444 | Implement the Python class `AppliedConditionalAccessPolicy` described below.
Class description:
Implement the AppliedConditionalAccessPolicy class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppliedConditionalAccessPolicy: Creates a new instance of... | Implement the Python class `AppliedConditionalAccessPolicy` described below.
Class description:
Implement the AppliedConditionalAccessPolicy class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppliedConditionalAccessPolicy: Creates a new instance of... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AppliedConditionalAccessPolicy:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppliedConditionalAccessPolicy:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator v... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AppliedConditionalAccessPolicy:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppliedConditionalAccessPolicy:
"""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 creat... | the_stack_v2_python_sparse | msgraph/generated/models/applied_conditional_access_policy.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e091d03d3ea5ec4d503bd736aafba91aba0ab645 | [
"test_obj = Furniture(1, 2, 3, 4, 5, 6)\nself.assertEqual(test_obj.product_code, 1)\nself.assertEqual(test_obj.description, 2)\nself.assertEqual(test_obj.market_price, 3)\nself.assertEqual(test_obj.rental_price, 4)\nself.assertEqual(test_obj.material, 5)\nself.assertEqual(test_obj.size, 6)",
"test_obj = Furniture... | <|body_start_0|>
test_obj = Furniture(1, 2, 3, 4, 5, 6)
self.assertEqual(test_obj.product_code, 1)
self.assertEqual(test_obj.description, 2)
self.assertEqual(test_obj.market_price, 3)
self.assertEqual(test_obj.rental_price, 4)
self.assertEqual(test_obj.material, 5)
... | Test Furniture class | FurnitureTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FurnitureTest:
"""Test Furniture class"""
def test_init(self):
"""Test init"""
<|body_0|>
def test_return_dict(self):
"""Test return as dict func"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
test_obj = Furniture(1, 2, 3, 4, 5, 6)
self... | stack_v2_sparse_classes_36k_train_020917 | 4,928 | no_license | [
{
"docstring": "Test init",
"name": "test_init",
"signature": "def test_init(self)"
},
{
"docstring": "Test return as dict func",
"name": "test_return_dict",
"signature": "def test_return_dict(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010702 | Implement the Python class `FurnitureTest` described below.
Class description:
Test Furniture class
Method signatures and docstrings:
- def test_init(self): Test init
- def test_return_dict(self): Test return as dict func | Implement the Python class `FurnitureTest` described below.
Class description:
Test Furniture class
Method signatures and docstrings:
- def test_init(self): Test init
- def test_return_dict(self): Test return as dict func
<|skeleton|>
class FurnitureTest:
"""Test Furniture class"""
def test_init(self):
... | 6ffd7b4ab8346076d3b6cc02ca1ebca3bf028697 | <|skeleton|>
class FurnitureTest:
"""Test Furniture class"""
def test_init(self):
"""Test init"""
<|body_0|>
def test_return_dict(self):
"""Test return as dict func"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FurnitureTest:
"""Test Furniture class"""
def test_init(self):
"""Test init"""
test_obj = Furniture(1, 2, 3, 4, 5, 6)
self.assertEqual(test_obj.product_code, 1)
self.assertEqual(test_obj.description, 2)
self.assertEqual(test_obj.market_price, 3)
self.assert... | the_stack_v2_python_sparse | students/JasneetChandok/lesson01/assignment/test_unit.py | UWPCE-PythonCert-ClassRepos/220-Advanced-Summer-2019 | train | 4 |
43014415d4e4b7c3a2ca6aa1907409479c864587 | [
"self.item = item\nself.key = key\nself.left = left\nself.right = right\nself._size = 1",
"if self.key == key:\n self.item = item\nelif self.key < key:\n if self.right:\n self.right.insert(item, key)\n else:\n self.right = BSTreeNode(item, key)\nelif self.left:\n self.left.insert(item, k... | <|body_start_0|>
self.item = item
self.key = key
self.left = left
self.right = right
self._size = 1
<|end_body_0|>
<|body_start_1|>
if self.key == key:
self.item = item
elif self.key < key:
if self.right:
self.right.insert(... | Binary search tree node (subtree) | BSTreeNode | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTreeNode:
"""Binary search tree node (subtree)"""
def __init__(self, item, key, left=None, right=None):
"""Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) :param right (BSTreeNode): right child (subtree)"""
... | stack_v2_sparse_classes_36k_train_020918 | 3,986 | no_license | [
{
"docstring": "Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) :param right (BSTreeNode): right child (subtree)",
"name": "__init__",
"signature": "def __init__(self, item, key, left=None, right=None)"
},
{
"docstring": "Assi... | 6 | stack_v2_sparse_classes_30k_train_019148 | Implement the Python class `BSTreeNode` described below.
Class description:
Binary search tree node (subtree)
Method signatures and docstrings:
- def __init__(self, item, key, left=None, right=None): Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) ... | Implement the Python class `BSTreeNode` described below.
Class description:
Binary search tree node (subtree)
Method signatures and docstrings:
- def __init__(self, item, key, left=None, right=None): Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) ... | 61746b48482eb0701f5c7211b153a3726c24f355 | <|skeleton|>
class BSTreeNode:
"""Binary search tree node (subtree)"""
def __init__(self, item, key, left=None, right=None):
"""Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) :param right (BSTreeNode): right child (subtree)"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BSTreeNode:
"""Binary search tree node (subtree)"""
def __init__(self, item, key, left=None, right=None):
"""Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) :param right (BSTreeNode): right child (subtree)"""
self.item ... | the_stack_v2_python_sparse | mpiaa/search/bstree_node.py | sergey-suslov/mpiaa-sem3 | train | 0 |
0282584d3a0d651c43310be13a3b14766b2cdf18 | [
"def direct_drop(layer, prob):\n \"\"\" Build a condition node if we are in train_phase. thus we can use the\n is_training_ placeholder to switch.\n Build a prob*layer node when we're not in train_phase.\n Returns the correct node\"\"\"\n if train_phase:\n layer = tf.co... | <|body_start_0|>
def direct_drop(layer, prob):
""" Build a condition node if we are in train_phase. thus we can use the
is_training_ placeholder to switch.
Build a prob*layer node when we're not in train_phase.
Returns the correct node"""
... | Build a LeNet-like network with direct dropout layers | LeNetDirectDropout | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LeNetDirectDropout:
"""Build a LeNet-like network with direct dropout layers"""
def _inference(self, images, num_classes, is_training_, train_phase=False, l2_penalty=0.0):
"""Build the LeNet-like network. Args: images: Images returned from distorted_inputs() or inputs(). num_classes:... | stack_v2_sparse_classes_36k_train_020919 | 5,471 | no_license | [
{
"docstring": "Build the LeNet-like network. Args: images: Images returned from distorted_inputs() or inputs(). num_classes: Number of classes to predict is_training_: enable/disable training ops at run time train_phase: Boolean to enable/disable training ops at build time l2_penalty: float value, weight decay... | 3 | null | Implement the Python class `LeNetDirectDropout` described below.
Class description:
Build a LeNet-like network with direct dropout layers
Method signatures and docstrings:
- def _inference(self, images, num_classes, is_training_, train_phase=False, l2_penalty=0.0): Build the LeNet-like network. Args: images: Images r... | Implement the Python class `LeNetDirectDropout` described below.
Class description:
Build a LeNet-like network with direct dropout layers
Method signatures and docstrings:
- def _inference(self, images, num_classes, is_training_, train_phase=False, l2_penalty=0.0): Build the LeNet-like network. Args: images: Images r... | d494b3041069d377d6a7a9c296a14334f2fa5acc | <|skeleton|>
class LeNetDirectDropout:
"""Build a LeNet-like network with direct dropout layers"""
def _inference(self, images, num_classes, is_training_, train_phase=False, l2_penalty=0.0):
"""Build the LeNet-like network. Args: images: Images returned from distorted_inputs() or inputs(). num_classes:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LeNetDirectDropout:
"""Build a LeNet-like network with direct dropout layers"""
def _inference(self, images, num_classes, is_training_, train_phase=False, l2_penalty=0.0):
"""Build the LeNet-like network. Args: images: Images returned from distorted_inputs() or inputs(). num_classes: Number of cl... | the_stack_v2_python_sparse | python/galeone_dynamic-training-bench/dynamic-training-bench-master/models/LeNetDirectDropout.py | LiuFang816/SALSTM_py_data | train | 10 |
e312b1d5d6279ab5fa4cae313f044f9ed3b4a023 | [
"actual = clean_text('check out this link: https://cyphon.io')\nexpected = 'check out this link'\nself.assertEqual(actual, expected)",
"actual = clean_text('@foobar hey there')\nexpected = 'hey there'\nself.assertEqual(actual, expected)",
"actual = clean_text('#foobar hey there')\nexpected = 'foobar hey there'\... | <|body_start_0|>
actual = clean_text('check out this link: https://cyphon.io')
expected = 'check out this link'
self.assertEqual(actual, expected)
<|end_body_0|>
<|body_start_1|>
actual = clean_text('@foobar hey there')
expected = 'hey there'
self.assertEqual(actual, exp... | Tests the clean_text() function. | CleanTextTestCase | [
"LicenseRef-scancode-proprietary-license",
"GPL-3.0-only",
"LicenseRef-scancode-unknown-license-reference",
"GPL-1.0-or-later",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-copyleft",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CleanTextTestCase:
"""Tests the clean_text() function."""
def test_clean_url(self):
"""Tests the clean_text() function for text containing a URL."""
<|body_0|>
def test_clean_at(self):
"""Tests the clean_text() function for text containing an @ symbol."""
... | stack_v2_sparse_classes_36k_train_020920 | 4,456 | permissive | [
{
"docstring": "Tests the clean_text() function for text containing a URL.",
"name": "test_clean_url",
"signature": "def test_clean_url(self)"
},
{
"docstring": "Tests the clean_text() function for text containing an @ symbol.",
"name": "test_clean_at",
"signature": "def test_clean_at(se... | 3 | stack_v2_sparse_classes_30k_train_008482 | Implement the Python class `CleanTextTestCase` described below.
Class description:
Tests the clean_text() function.
Method signatures and docstrings:
- def test_clean_url(self): Tests the clean_text() function for text containing a URL.
- def test_clean_at(self): Tests the clean_text() function for text containing an... | Implement the Python class `CleanTextTestCase` described below.
Class description:
Tests the clean_text() function.
Method signatures and docstrings:
- def test_clean_url(self): Tests the clean_text() function for text containing a URL.
- def test_clean_at(self): Tests the clean_text() function for text containing an... | a379a134c0c5af14df4ed2afa066c1626506b754 | <|skeleton|>
class CleanTextTestCase:
"""Tests the clean_text() function."""
def test_clean_url(self):
"""Tests the clean_text() function for text containing a URL."""
<|body_0|>
def test_clean_at(self):
"""Tests the clean_text() function for text containing an @ symbol."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CleanTextTestCase:
"""Tests the clean_text() function."""
def test_clean_url(self):
"""Tests the clean_text() function for text containing a URL."""
actual = clean_text('check out this link: https://cyphon.io')
expected = 'check out this link'
self.assertEqual(actual, expe... | the_stack_v2_python_sparse | Incident-Response/Tools/cyphon/cyphon/lab/sentiment/test_sentiment.py | foss2cyber/Incident-Playbook | train | 1 |
2752037d02a31f81e926fa7be34b3c4bfc67e1d5 | [
"re = cloudparking_service().mockCarInOut(send_data['carNum'], 0, send_data['inClientID'])\nresult = re\nAssertions().assert_in_text(result, expect['screen'])\nAssertions().assert_in_text(result, expect['voice'])",
"re = Information(userLogin).getPresentCar(send_data['parkName'], send_data['carNum'])\nresult = re... | <|body_start_0|>
re = cloudparking_service().mockCarInOut(send_data['carNum'], 0, send_data['inClientID'])
result = re
Assertions().assert_in_text(result, expect['screen'])
Assertions().assert_in_text(result, expect['voice'])
<|end_body_0|>
<|body_start_1|>
re = Information(user... | 白名单宽进宽出 | TestWhitelistWideInOutProcess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestWhitelistWideInOutProcess:
"""白名单宽进宽出"""
def test_mockCarIn(self, send_data, expect):
"""模拟车辆进场"""
<|body_0|>
def test_presentCar(self, userLogin, send_data, expect):
"""查看在场记录"""
<|body_1|>
def test_mockCarOut(self, send_data, expect):
"... | stack_v2_sparse_classes_36k_train_020921 | 1,988 | no_license | [
{
"docstring": "模拟车辆进场",
"name": "test_mockCarIn",
"signature": "def test_mockCarIn(self, send_data, expect)"
},
{
"docstring": "查看在场记录",
"name": "test_presentCar",
"signature": "def test_presentCar(self, userLogin, send_data, expect)"
},
{
"docstring": "模拟车辆离场",
"name": "tes... | 4 | null | Implement the Python class `TestWhitelistWideInOutProcess` described below.
Class description:
白名单宽进宽出
Method signatures and docstrings:
- def test_mockCarIn(self, send_data, expect): 模拟车辆进场
- def test_presentCar(self, userLogin, send_data, expect): 查看在场记录
- def test_mockCarOut(self, send_data, expect): 模拟车辆离场
- def ... | Implement the Python class `TestWhitelistWideInOutProcess` described below.
Class description:
白名单宽进宽出
Method signatures and docstrings:
- def test_mockCarIn(self, send_data, expect): 模拟车辆进场
- def test_presentCar(self, userLogin, send_data, expect): 查看在场记录
- def test_mockCarOut(self, send_data, expect): 模拟车辆离场
- def ... | 34c368c109867da26d9256bca85f872b0fac2ea7 | <|skeleton|>
class TestWhitelistWideInOutProcess:
"""白名单宽进宽出"""
def test_mockCarIn(self, send_data, expect):
"""模拟车辆进场"""
<|body_0|>
def test_presentCar(self, userLogin, send_data, expect):
"""查看在场记录"""
<|body_1|>
def test_mockCarOut(self, send_data, expect):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestWhitelistWideInOutProcess:
"""白名单宽进宽出"""
def test_mockCarIn(self, send_data, expect):
"""模拟车辆进场"""
re = cloudparking_service().mockCarInOut(send_data['carNum'], 0, send_data['inClientID'])
result = re
Assertions().assert_in_text(result, expect['screen'])
Assert... | the_stack_v2_python_sparse | test_suite/parkingConfig/useParking/lightRuleChannel/test_whitelistWideInOutProcess.py | oyebino/pomp_api | train | 1 |
963dbd77e8c2e6756dc99c775be29740019f072f | [
"dictionary = self.formatDict(results)\nfinal = {}\nfor entry in dictionary:\n final[entry['jobid']] = entry['task']\nreturn final",
"if isinstance(jobID, list):\n if len(jobID) == 0:\n return {}\n binds = []\n for ID in jobID:\n binds.append({'jobid': int(ID)})\nelif isinstance(jobID, i... | <|body_start_0|>
dictionary = self.formatDict(results)
final = {}
for entry in dictionary:
final[entry['jobid']] = entry['task']
return final
<|end_body_0|>
<|body_start_1|>
if isinstance(jobID, list):
if len(jobID) == 0:
return {}
... | GetTask | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetTask:
def format(self, results):
"""Should create one dictionary of the form {'jobid':'taskName'}"""
<|body_0|>
def execute(self, jobID, conn=None, transaction=False):
"""Should handle bulk and regular attempts to find the task"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_020922 | 1,509 | permissive | [
{
"docstring": "Should create one dictionary of the form {'jobid':'taskName'}",
"name": "format",
"signature": "def format(self, results)"
},
{
"docstring": "Should handle bulk and regular attempts to find the task",
"name": "execute",
"signature": "def execute(self, jobID, conn=None, tr... | 2 | null | Implement the Python class `GetTask` described below.
Class description:
Implement the GetTask class.
Method signatures and docstrings:
- def format(self, results): Should create one dictionary of the form {'jobid':'taskName'}
- def execute(self, jobID, conn=None, transaction=False): Should handle bulk and regular at... | Implement the Python class `GetTask` described below.
Class description:
Implement the GetTask class.
Method signatures and docstrings:
- def format(self, results): Should create one dictionary of the form {'jobid':'taskName'}
- def execute(self, jobID, conn=None, transaction=False): Should handle bulk and regular at... | de110ccf6fc63ef5589b4e871ef4d51d5bce7a25 | <|skeleton|>
class GetTask:
def format(self, results):
"""Should create one dictionary of the form {'jobid':'taskName'}"""
<|body_0|>
def execute(self, jobID, conn=None, transaction=False):
"""Should handle bulk and regular attempts to find the task"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetTask:
def format(self, results):
"""Should create one dictionary of the form {'jobid':'taskName'}"""
dictionary = self.formatDict(results)
final = {}
for entry in dictionary:
final[entry['jobid']] = entry['task']
return final
def execute(self, jobID,... | the_stack_v2_python_sparse | src/python/WMCore/WMBS/MySQL/Jobs/GetTask.py | vkuznet/WMCore | train | 0 | |
d4997c678a24d2f08149fa26c65e0f2736d0ec95 | [
"super().__init__()\nself._ui = Ui_CpfcDialog()\nself._ui.setupUi(self)\nself._ui.new_pfc_line_edit.setValidator(QDoubleValidator())\nwith open('.steelcase_pfc', 'a+') as file:\n self.current_pfc = file.read()\nself._ui.current_pfc_line_edit.setText(self.current_pfc)\nself.move(QDesktopWidget().availableGeometry... | <|body_start_0|>
super().__init__()
self._ui = Ui_CpfcDialog()
self._ui.setupUi(self)
self._ui.new_pfc_line_edit.setValidator(QDoubleValidator())
with open('.steelcase_pfc', 'a+') as file:
self.current_pfc = file.read()
self._ui.current_pfc_line_edit.setText(s... | QDialog class containing methods to change the pass/fail criteria. | CpfcDialog | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CpfcDialog:
"""QDialog class containing methods to change the pass/fail criteria."""
def __init__(self):
"""Start_steelcase init method."""
<|body_0|>
def accept(self):
"""Overiding of QDialog accept method."""
<|body_1|>
def _check_input(self, obj):... | stack_v2_sparse_classes_36k_train_020923 | 2,474 | permissive | [
{
"docstring": "Start_steelcase init method.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Overiding of QDialog accept method.",
"name": "accept",
"signature": "def accept(self)"
},
{
"docstring": "Method to create input for the zero condition.",
... | 3 | stack_v2_sparse_classes_30k_val_000197 | Implement the Python class `CpfcDialog` described below.
Class description:
QDialog class containing methods to change the pass/fail criteria.
Method signatures and docstrings:
- def __init__(self): Start_steelcase init method.
- def accept(self): Overiding of QDialog accept method.
- def _check_input(self, obj): Met... | Implement the Python class `CpfcDialog` described below.
Class description:
QDialog class containing methods to change the pass/fail criteria.
Method signatures and docstrings:
- def __init__(self): Start_steelcase init method.
- def accept(self): Overiding of QDialog accept method.
- def _check_input(self, obj): Met... | 024def3d5654e772e6ac598b6555cdcdd8a26287 | <|skeleton|>
class CpfcDialog:
"""QDialog class containing methods to change the pass/fail criteria."""
def __init__(self):
"""Start_steelcase init method."""
<|body_0|>
def accept(self):
"""Overiding of QDialog accept method."""
<|body_1|>
def _check_input(self, obj):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CpfcDialog:
"""QDialog class containing methods to change the pass/fail criteria."""
def __init__(self):
"""Start_steelcase init method."""
super().__init__()
self._ui = Ui_CpfcDialog()
self._ui.setupUi(self)
self._ui.new_pfc_line_edit.setValidator(QDoubleValidator... | the_stack_v2_python_sparse | src/cpfc_dialog.py | lawrencend/steelcase | train | 0 |
ad43de3c5a81158d7d4c73d6f0fd37f197c70c2f | [
"df = df.reset_index(drop=True)\nfor i in range(len(df)):\n feature = df.loc[i, 'column_name']\n df.loc[i, 'original_name'] = '_'.join(str(feature).split('_')[:-1])\n df.loc[i, 'binning_method'] = 'ChiMerge' if 'ChiMerge' in feature.split('_')[-1] else 'DecisionTree'\n df.loc[i, 'binning_number'] = feat... | <|body_start_0|>
df = df.reset_index(drop=True)
for i in range(len(df)):
feature = df.loc[i, 'column_name']
df.loc[i, 'original_name'] = '_'.join(str(feature).split('_')[:-1])
df.loc[i, 'binning_method'] = 'ChiMerge' if 'ChiMerge' in feature.split('_')[-1] else 'Decis... | 功能：整理评分卡应用的特征单调性筛选输入数据 输入：整理的分箱编码数据集 df 控制：保留特征列表 keep_columns_list 输出：过滤后特征数据集 | FeatureSelectionByMonotonicityRule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureSelectionByMonotonicityRule:
"""功能：整理评分卡应用的特征单调性筛选输入数据 输入：整理的分箱编码数据集 df 控制：保留特征列表 keep_columns_list 输出：过滤后特征数据集"""
def _filter_data(self, df):
"""保留具有单调性的变量 :param df: 带单调性判断的编码规则 :return: 具有单调性的编码规则"""
<|body_0|>
def fit(self, df):
"""单调性判断服务 :param df: 单... | stack_v2_sparse_classes_36k_train_020924 | 32,082 | no_license | [
{
"docstring": "保留具有单调性的变量 :param df: 带单调性判断的编码规则 :return: 具有单调性的编码规则",
"name": "_filter_data",
"signature": "def _filter_data(self, df)"
},
{
"docstring": "单调性判断服务 :param df: 单调性判断输入数据 :return: 具有单调性的编码规则",
"name": "fit",
"signature": "def fit(self, df)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000224 | Implement the Python class `FeatureSelectionByMonotonicityRule` described below.
Class description:
功能：整理评分卡应用的特征单调性筛选输入数据 输入：整理的分箱编码数据集 df 控制：保留特征列表 keep_columns_list 输出：过滤后特征数据集
Method signatures and docstrings:
- def _filter_data(self, df): 保留具有单调性的变量 :param df: 带单调性判断的编码规则 :return: 具有单调性的编码规则
- def fit(self, df):... | Implement the Python class `FeatureSelectionByMonotonicityRule` described below.
Class description:
功能：整理评分卡应用的特征单调性筛选输入数据 输入：整理的分箱编码数据集 df 控制：保留特征列表 keep_columns_list 输出：过滤后特征数据集
Method signatures and docstrings:
- def _filter_data(self, df): 保留具有单调性的变量 :param df: 带单调性判断的编码规则 :return: 具有单调性的编码规则
- def fit(self, df):... | 47c95814d2bfcaf1f30cb892db0d09c8c88901e7 | <|skeleton|>
class FeatureSelectionByMonotonicityRule:
"""功能：整理评分卡应用的特征单调性筛选输入数据 输入：整理的分箱编码数据集 df 控制：保留特征列表 keep_columns_list 输出：过滤后特征数据集"""
def _filter_data(self, df):
"""保留具有单调性的变量 :param df: 带单调性判断的编码规则 :return: 具有单调性的编码规则"""
<|body_0|>
def fit(self, df):
"""单调性判断服务 :param df: 单... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeatureSelectionByMonotonicityRule:
"""功能：整理评分卡应用的特征单调性筛选输入数据 输入：整理的分箱编码数据集 df 控制：保留特征列表 keep_columns_list 输出：过滤后特征数据集"""
def _filter_data(self, df):
"""保留具有单调性的变量 :param df: 带单调性判断的编码规则 :return: 具有单调性的编码规则"""
df = df.reset_index(drop=True)
for i in range(len(df)):
fea... | the_stack_v2_python_sparse | mldesigntoolkit/mldesigntoolkit/modules/feature_engineering/_feature_select.py | Stormzqz/py | train | 0 |
77fe400c5078ab9f6cdd076d6c73ef6d561029ef | [
"if isinstance(key, int):\n return MPTCPOption(key)\nif key not in MPTCPOption._member_map_:\n return extend_enum(MPTCPOption, key, default)\nreturn MPTCPOption[key]",
"if not (isinstance(value, int) and 0 <= value <= 255):\n raise ValueError('%r is not a valid %s' % (value, cls.__name__))\nif 9 <= value... | <|body_start_0|>
if isinstance(key, int):
return MPTCPOption(key)
if key not in MPTCPOption._member_map_:
return extend_enum(MPTCPOption, key, default)
return MPTCPOption[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and 0 <= value <= 255):
... | [MPTCPOption] Multipath TCP options [:rfc:`6824`] | MPTCPOption | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MPTCPOption:
"""[MPTCPOption] Multipath TCP options [:rfc:`6824`]"""
def get(key: 'int | str', default: 'int'=-1) -> 'MPTCPOption':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_020925 | 2,275 | permissive | [
{
"docstring": "Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:",
"name": "get",
"signature": "def get(key: 'int | str', default: 'int'=-1) -> 'MPTCPOption'"
},
{
"docstring": "Lookup function used when value is not found.... | 2 | null | Implement the Python class `MPTCPOption` described below.
Class description:
[MPTCPOption] Multipath TCP options [:rfc:`6824`]
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'MPTCPOption': Backport support for original codes. Args: key: Key to get enum item. default: Default value... | Implement the Python class `MPTCPOption` described below.
Class description:
[MPTCPOption] Multipath TCP options [:rfc:`6824`]
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'MPTCPOption': Backport support for original codes. Args: key: Key to get enum item. default: Default value... | a6fe49ec58f09e105bec5a00fb66d9b3f22730d9 | <|skeleton|>
class MPTCPOption:
"""[MPTCPOption] Multipath TCP options [:rfc:`6824`]"""
def get(key: 'int | str', default: 'int'=-1) -> 'MPTCPOption':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MPTCPOption:
"""[MPTCPOption] Multipath TCP options [:rfc:`6824`]"""
def get(key: 'int | str', default: 'int'=-1) -> 'MPTCPOption':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
if isinstance(key, int):
... | the_stack_v2_python_sparse | pcapkit/const/tcp/mp_tcp_option.py | JarryShaw/PyPCAPKit | train | 204 |
ad9e716393b8df9ef1396fb0b04c3bcb39c6b415 | [
"if isinstance(queue_rq, STRING_TYPES):\n jobqueue = JobQueue.query.filter_by(name=queue_rq).first()\nelse:\n jobqueue = JobQueue.query.filter_by(id=queue_rq).first()\nif not jobqueue:\n return (jsonify(error='Requested job queue %r not found' % queue_rq), NOT_FOUND)\nreturn (jsonify(jobqueue.to_dict()), O... | <|body_start_0|>
if isinstance(queue_rq, STRING_TYPES):
jobqueue = JobQueue.query.filter_by(name=queue_rq).first()
else:
jobqueue = JobQueue.query.filter_by(id=queue_rq).first()
if not jobqueue:
return (jsonify(error='Requested job queue %r not found' % queue_... | SingleJobQueueAPI | [
"BSD-3-Clause",
"Apache-2.0",
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleJobQueueAPI:
def get(self, queue_rq):
"""A ``GET`` to this endpoint will return the requested job queue .. http:get:: /api/v1/jobqueues/[<str:name>|<int:id>] HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/jobqueues/Test%20Queue HTTP/1.1 Accept: application/json **Response** ... | stack_v2_sparse_classes_36k_train_020926 | 11,392 | permissive | [
{
"docstring": "A ``GET`` to this endpoint will return the requested job queue .. http:get:: /api/v1/jobqueues/[<str:name>|<int:id>] HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/jobqueues/Test%20Queue HTTP/1.1 Accept: application/json **Response** .. sourcecode:: http HTTP/1.1 200 OK Content-Type: appl... | 3 | stack_v2_sparse_classes_30k_train_000618 | Implement the Python class `SingleJobQueueAPI` described below.
Class description:
Implement the SingleJobQueueAPI class.
Method signatures and docstrings:
- def get(self, queue_rq): A ``GET`` to this endpoint will return the requested job queue .. http:get:: /api/v1/jobqueues/[<str:name>|<int:id>] HTTP/1.1 **Request... | Implement the Python class `SingleJobQueueAPI` described below.
Class description:
Implement the SingleJobQueueAPI class.
Method signatures and docstrings:
- def get(self, queue_rq): A ``GET`` to this endpoint will return the requested job queue .. http:get:: /api/v1/jobqueues/[<str:name>|<int:id>] HTTP/1.1 **Request... | ea04bbcb807eb669415c569417b4b1b68e75d29d | <|skeleton|>
class SingleJobQueueAPI:
def get(self, queue_rq):
"""A ``GET`` to this endpoint will return the requested job queue .. http:get:: /api/v1/jobqueues/[<str:name>|<int:id>] HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/jobqueues/Test%20Queue HTTP/1.1 Accept: application/json **Response** ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SingleJobQueueAPI:
def get(self, queue_rq):
"""A ``GET`` to this endpoint will return the requested job queue .. http:get:: /api/v1/jobqueues/[<str:name>|<int:id>] HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/jobqueues/Test%20Queue HTTP/1.1 Accept: application/json **Response** .. sourcecode:... | the_stack_v2_python_sparse | pyfarm/master/api/jobqueues.py | pyfarm/pyfarm-master | train | 2 | |
98a313f2c66063b91b0ebb911eda2c0709d19f57 | [
"if head == None or head.next == None:\n return head\nnewHead = None\nwhile head != None:\n temp = head.next\n head.next = newHead\n newHead = head\n head = temp\nreturn newHead",
"cur, prev = (head, None)\nwhile cur:\n cur.next, prev, cur = (prev, cur, cur.next)\nreturn prev"
] | <|body_start_0|>
if head == None or head.next == None:
return head
newHead = None
while head != None:
temp = head.next
head.next = newHead
newHead = head
head = temp
return newHead
<|end_body_0|>
<|body_start_1|>
cur, p... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseList1(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if head == None or head.next == None... | stack_v2_sparse_classes_36k_train_020927 | 2,178 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList",
"signature": "def reverseList(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList1",
"signature": "def reverseList1(self, head)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def reverseList1(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def reverseList1(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
def re... | 1379a6dc2400751ecf79ccd6ed401a1fb0d78046 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseList1(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
if head == None or head.next == None:
return head
newHead = None
while head != None:
temp = head.next
head.next = newHead
newHead = head
... | the_stack_v2_python_sparse | Python3.6/206-Py3-E-Reverse Linked List.py | Hidenver2016/Leetcode | train | 1 | |
3be89f3d288f881ea6ccf1fe7a8ed0060398c25b | [
"with open(path, encoding='cp437') as f:\n raw_data = f.read().splitlines()\n self.detectors = raw_data[detector_row].split('\\t')[data_columns]\n self.bias = np.array(raw_data[bias_row].split('\\t')[data_columns]).astype(float)\n self.calibration = np.array(raw_data[calibration_row].split('\\t')[data_c... | <|body_start_0|>
with open(path, encoding='cp437') as f:
raw_data = f.read().splitlines()
self.detectors = raw_data[detector_row].split('\t')[data_columns]
self.bias = np.array(raw_data[bias_row].split('\t')[data_columns]).astype(float)
self.calibration = np.array... | Load a file from a Sun Nuclear Profiler device. This accepts .prs files. | SNCProfiler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SNCProfiler:
"""Load a file from a Sun Nuclear Profiler device. This accepts .prs files."""
def __init__(self, path: str, gain_row: int=20, detector_row: int=106, bias_row: int=107, calibration_row: int=108, data_row: int=-1, data_columns: slice=slice(5, 259)):
"""Parameters --------... | stack_v2_sparse_classes_36k_train_020928 | 9,453 | permissive | [
{
"docstring": "Parameters ---------- path : str Path to the .prs file. detector_row bias_row calibration_row data_row data_columns The range of columns that the data is in. Usually, there are some columns before and after the real data.",
"name": "__init__",
"signature": "def __init__(self, path: str, ... | 2 | stack_v2_sparse_classes_30k_train_020437 | Implement the Python class `SNCProfiler` described below.
Class description:
Load a file from a Sun Nuclear Profiler device. This accepts .prs files.
Method signatures and docstrings:
- def __init__(self, path: str, gain_row: int=20, detector_row: int=106, bias_row: int=107, calibration_row: int=108, data_row: int=-1... | Implement the Python class `SNCProfiler` described below.
Class description:
Load a file from a Sun Nuclear Profiler device. This accepts .prs files.
Method signatures and docstrings:
- def __init__(self, path: str, gain_row: int=20, detector_row: int=106, bias_row: int=107, calibration_row: int=108, data_row: int=-1... | 5c2cfe971f2f6a8d27b0d81159e0f1bacba007b8 | <|skeleton|>
class SNCProfiler:
"""Load a file from a Sun Nuclear Profiler device. This accepts .prs files."""
def __init__(self, path: str, gain_row: int=20, detector_row: int=106, bias_row: int=107, calibration_row: int=108, data_row: int=-1, data_columns: slice=slice(5, 259)):
"""Parameters --------... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SNCProfiler:
"""Load a file from a Sun Nuclear Profiler device. This accepts .prs files."""
def __init__(self, path: str, gain_row: int=20, detector_row: int=106, bias_row: int=107, calibration_row: int=108, data_row: int=-1, data_columns: slice=slice(5, 259)):
"""Parameters ---------- path : str... | the_stack_v2_python_sparse | pylinac/core/io.py | jrkerns/pylinac | train | 129 |
2cd423217af03d8b8edbc873ca1d4edf26eac669 | [
"self.name = name\nself.description = description\nself.statement_descriptor = statement_descriptor\nself.items = items\nself.shippable = shippable\nself.payment_methods = payment_methods\nself.installments = installments\nself.currency = currency\nself.interval = interval\nself.interval_count = interval_count\nsel... | <|body_start_0|>
self.name = name
self.description = description
self.statement_descriptor = statement_descriptor
self.items = items
self.shippable = shippable
self.payment_methods = payment_methods
self.installments = installments
self.currency = currency... | Implementation of the 'CreatePlanRequest' model. Request for creating a plan Attributes: name (string): Plan's name description (string): Description statement_descriptor (string): Text that will be printed on the credit card's statement items (list of CreatePlanItemRequest): Plan items shippable (bool): Indicates if t... | CreatePlanRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreatePlanRequest:
"""Implementation of the 'CreatePlanRequest' model. Request for creating a plan Attributes: name (string): Plan's name description (string): Description statement_descriptor (string): Text that will be printed on the credit card's statement items (list of CreatePlanItemRequest)... | stack_v2_sparse_classes_36k_train_020929 | 6,468 | permissive | [
{
"docstring": "Constructor for the CreatePlanRequest class",
"name": "__init__",
"signature": "def __init__(self, name=None, description=None, statement_descriptor=None, items=None, shippable=None, payment_methods=None, installments=None, currency=None, interval=None, interval_count=None, billing_days=... | 2 | null | Implement the Python class `CreatePlanRequest` described below.
Class description:
Implementation of the 'CreatePlanRequest' model. Request for creating a plan Attributes: name (string): Plan's name description (string): Description statement_descriptor (string): Text that will be printed on the credit card's statemen... | Implement the Python class `CreatePlanRequest` described below.
Class description:
Implementation of the 'CreatePlanRequest' model. Request for creating a plan Attributes: name (string): Plan's name description (string): Description statement_descriptor (string): Text that will be printed on the credit card's statemen... | 95c80c35dd57bb2a238faeaf30d1e3b4544d2298 | <|skeleton|>
class CreatePlanRequest:
"""Implementation of the 'CreatePlanRequest' model. Request for creating a plan Attributes: name (string): Plan's name description (string): Description statement_descriptor (string): Text that will be printed on the credit card's statement items (list of CreatePlanItemRequest)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreatePlanRequest:
"""Implementation of the 'CreatePlanRequest' model. Request for creating a plan Attributes: name (string): Plan's name description (string): Description statement_descriptor (string): Text that will be printed on the credit card's statement items (list of CreatePlanItemRequest): Plan items ... | the_stack_v2_python_sparse | mundiapi/models/create_plan_request.py | mundipagg/MundiAPI-PYTHON | train | 10 |
5a1813cb35ad501e5e775fd3f6742d4995fcecf8 | [
"super(SkipGram, self).__init__()\nself.vocab_size = vocab_size\nself.emb_dimension = emb_dimension\nself.c_emb = nn.Embedding(vocab_size, emb_dimension, embedding_table=Uniform(0.5 / emb_dimension))\nself.n_emb = nn.Embedding(vocab_size, emb_dimension, embedding_table=Uniform(0))\nself.mul = ops.Mul()\nself.sum = ... | <|body_start_0|>
super(SkipGram, self).__init__()
self.vocab_size = vocab_size
self.emb_dimension = emb_dimension
self.c_emb = nn.Embedding(vocab_size, emb_dimension, embedding_table=Uniform(0.5 / emb_dimension))
self.n_emb = nn.Embedding(vocab_size, emb_dimension, embedding_tabl... | Skip gram model of word2vec. Attributes: vocab_size: Vocabulary size. emb_dimension: Embedding dimension. c_emb: Embedding for center word. n_emb: Embedding for neighbor word. | SkipGram | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SkipGram:
"""Skip gram model of word2vec. Attributes: vocab_size: Vocabulary size. emb_dimension: Embedding dimension. c_emb: Embedding for center word. n_emb: Embedding for neighbor word."""
def __init__(self, vocab_size, emb_dimension):
"""Initialize model parameters. Apply for two... | stack_v2_sparse_classes_36k_train_020930 | 3,900 | permissive | [
{
"docstring": "Initialize model parameters. Apply for two embedding layers. Initialize layer weight. Args: vocab_size: Vocabulary size. emb_dimension: Embedding dimension. Returns: None",
"name": "__init__",
"signature": "def __init__(self, vocab_size, emb_dimension)"
},
{
"docstring": "Forward... | 3 | stack_v2_sparse_classes_30k_train_009627 | Implement the Python class `SkipGram` described below.
Class description:
Skip gram model of word2vec. Attributes: vocab_size: Vocabulary size. emb_dimension: Embedding dimension. c_emb: Embedding for center word. n_emb: Embedding for neighbor word.
Method signatures and docstrings:
- def __init__(self, vocab_size, e... | Implement the Python class `SkipGram` described below.
Class description:
Skip gram model of word2vec. Attributes: vocab_size: Vocabulary size. emb_dimension: Embedding dimension. c_emb: Embedding for center word. n_emb: Embedding for neighbor word.
Method signatures and docstrings:
- def __init__(self, vocab_size, e... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class SkipGram:
"""Skip gram model of word2vec. Attributes: vocab_size: Vocabulary size. emb_dimension: Embedding dimension. c_emb: Embedding for center word. n_emb: Embedding for neighbor word."""
def __init__(self, vocab_size, emb_dimension):
"""Initialize model parameters. Apply for two... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SkipGram:
"""Skip gram model of word2vec. Attributes: vocab_size: Vocabulary size. emb_dimension: Embedding dimension. c_emb: Embedding for center word. n_emb: Embedding for neighbor word."""
def __init__(self, vocab_size, emb_dimension):
"""Initialize model parameters. Apply for two embedding la... | the_stack_v2_python_sparse | research/nlp/skipgram/src/skipgram.py | mindspore-ai/models | train | 301 |
393ef2139f74724982f8e72afb06fedb139bc048 | [
"queryset = queryset.annotate(parts_manufactured=SubqueryCount('manufactured_parts'))\nqueryset = queryset.annotate(parts_supplied=SubqueryCount('supplied_parts'))\nreturn queryset",
"super().save()\ncompany = self.instance\nremote_img = getattr(self, 'remote_image_file', None)\nif remote_img and company:\n fm... | <|body_start_0|>
queryset = queryset.annotate(parts_manufactured=SubqueryCount('manufactured_parts'))
queryset = queryset.annotate(parts_supplied=SubqueryCount('supplied_parts'))
return queryset
<|end_body_0|>
<|body_start_1|>
super().save()
company = self.instance
remot... | Serializer for Company object (full detail) | CompanySerializer | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompanySerializer:
"""Serializer for Company object (full detail)"""
def annotate_queryset(queryset):
"""Annoate the supplied queryset with aggregated information"""
<|body_0|>
def save(self):
"""Save the Company instance"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_020931 | 11,419 | permissive | [
{
"docstring": "Annoate the supplied queryset with aggregated information",
"name": "annotate_queryset",
"signature": "def annotate_queryset(queryset)"
},
{
"docstring": "Save the Company instance",
"name": "save",
"signature": "def save(self)"
}
] | 2 | null | Implement the Python class `CompanySerializer` described below.
Class description:
Serializer for Company object (full detail)
Method signatures and docstrings:
- def annotate_queryset(queryset): Annoate the supplied queryset with aggregated information
- def save(self): Save the Company instance | Implement the Python class `CompanySerializer` described below.
Class description:
Serializer for Company object (full detail)
Method signatures and docstrings:
- def annotate_queryset(queryset): Annoate the supplied queryset with aggregated information
- def save(self): Save the Company instance
<|skeleton|>
class ... | 5a08ef908dd5344b4433436a4679d122f7f99e41 | <|skeleton|>
class CompanySerializer:
"""Serializer for Company object (full detail)"""
def annotate_queryset(queryset):
"""Annoate the supplied queryset with aggregated information"""
<|body_0|>
def save(self):
"""Save the Company instance"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompanySerializer:
"""Serializer for Company object (full detail)"""
def annotate_queryset(queryset):
"""Annoate the supplied queryset with aggregated information"""
queryset = queryset.annotate(parts_manufactured=SubqueryCount('manufactured_parts'))
queryset = queryset.annotate(p... | the_stack_v2_python_sparse | InvenTree/company/serializers.py | onurtatli/InvenTree | train | 0 |
c76dc4f3c93d23a5a734b0ddd74ea7bc57b7cb59 | [
"subsets = self.subsets(nums)\nresult = []\nfor subset in subsets:\n sorted_subset = sorted(subset)\n if sorted_subset not in result:\n result.append(sorted_subset)\nreturn result",
"length_of_nums = len(nums)\nnumber_of_subarrays = 2 ** length_of_nums\nresult = []\nfor i in range(0, number_of_subarr... | <|body_start_0|>
subsets = self.subsets(nums)
result = []
for subset in subsets:
sorted_subset = sorted(subset)
if sorted_subset not in result:
result.append(sorted_subset)
return result
<|end_body_0|>
<|body_start_1|>
length_of_nums = len... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subsetsWithDup(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
subsets = self.subsets... | stack_v2_sparse_classes_36k_train_020932 | 1,223 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsetsWithDup",
"signature": "def subsetsWithDup(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsets",
"signature": "def subsets(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013155 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsetsWithDup(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def subsets(self, nums): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsetsWithDup(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def subsets(self, nums): :type nums: List[int] :rtype: List[List[int]]
<|skeleton|>
class Solutio... | fcf6c3d5d60d13706950247d8a2327adc5faf17e | <|skeleton|>
class Solution:
def subsetsWithDup(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def subsetsWithDup(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
subsets = self.subsets(nums)
result = []
for subset in subsets:
sorted_subset = sorted(subset)
if sorted_subset not in result:
result.append(sor... | the_stack_v2_python_sparse | Medium/Subsets2.py | mangalagb/Leetcode | train | 0 | |
e17b2b5f2d3f9991b3e1554ed00acdc34006f18c | [
"body = self.data['body']\nraw = striptags(body)\nif len(raw) < ContentForm.BODY_LENGTH_MIN:\n raise forms_.ValidationError(_('Your text must be at least {} characters long.').format(ContentForm.BODY_LENGTH_MIN))\nreturn body",
"title = self.data['title']\nif len(title) < ContentForm.TITLE_LENGTH_MIN:\n rai... | <|body_start_0|>
body = self.data['body']
raw = striptags(body)
if len(raw) < ContentForm.BODY_LENGTH_MIN:
raise forms_.ValidationError(_('Your text must be at least {} characters long.').format(ContentForm.BODY_LENGTH_MIN))
return body
<|end_body_0|>
<|body_start_1|>
... | Formulaire de contenu | ContentForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContentForm:
"""Formulaire de contenu"""
def clean_body(self):
"""Valider et traiter le champ de texte"""
<|body_0|>
def clean_title(self):
"""Valider et traiter le champ de titre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
body = self.data[... | stack_v2_sparse_classes_36k_train_020933 | 2,989 | no_license | [
{
"docstring": "Valider et traiter le champ de texte",
"name": "clean_body",
"signature": "def clean_body(self)"
},
{
"docstring": "Valider et traiter le champ de titre",
"name": "clean_title",
"signature": "def clean_title(self)"
}
] | 2 | null | Implement the Python class `ContentForm` described below.
Class description:
Formulaire de contenu
Method signatures and docstrings:
- def clean_body(self): Valider et traiter le champ de texte
- def clean_title(self): Valider et traiter le champ de titre | Implement the Python class `ContentForm` described below.
Class description:
Formulaire de contenu
Method signatures and docstrings:
- def clean_body(self): Valider et traiter le champ de texte
- def clean_title(self): Valider et traiter le champ de titre
<|skeleton|>
class ContentForm:
"""Formulaire de contenu"... | 8cef6f6e89c1990e2b25f83e54e0c3481d83b6d7 | <|skeleton|>
class ContentForm:
"""Formulaire de contenu"""
def clean_body(self):
"""Valider et traiter le champ de texte"""
<|body_0|>
def clean_title(self):
"""Valider et traiter le champ de titre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContentForm:
"""Formulaire de contenu"""
def clean_body(self):
"""Valider et traiter le champ de texte"""
body = self.data['body']
raw = striptags(body)
if len(raw) < ContentForm.BODY_LENGTH_MIN:
raise forms_.ValidationError(_('Your text must be at least {} cha... | the_stack_v2_python_sparse | scoop/content/forms/content.py | artscoop/scoop | train | 0 |
aa5a5b6e36d631cbac9d42a7014a4ed874f2af52 | [
"self.D = 2\nself.gamma = gamma\nself.kT = kT\nself.diffusion = kT / gamma\nself.sqrt_2diffusion = np.sqrt(2 * self.diffusion)\nself.sigma = np.sqrt(2 * gamma * kT)\nself.lattice0type = lattice0type\nself.N_width = N_width\nself.N_height = N_height\nself.M_width = M_width\nself.M_height = M_height\nself.M_link1 = i... | <|body_start_0|>
self.D = 2
self.gamma = gamma
self.kT = kT
self.diffusion = kT / gamma
self.sqrt_2diffusion = np.sqrt(2 * self.diffusion)
self.sigma = np.sqrt(2 * gamma * kT)
self.lattice0type = lattice0type
self.N_width = N_width
self.N_height = ... | a thermal chain of bonded particles that has identical brownian particles inputs: N - #particles gamma - drag coefficient kT - temprature Larc0 - initial arc length chain0type - choose from: -straight_stretched -triangle_stretched -circle -random zigzag | SquareLattice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SquareLattice:
"""a thermal chain of bonded particles that has identical brownian particles inputs: N - #particles gamma - drag coefficient kT - temprature Larc0 - initial arc length chain0type - choose from: -straight_stretched -triangle_stretched -circle -random zigzag"""
def __init__(self... | stack_v2_sparse_classes_36k_train_020934 | 11,175 | no_license | [
{
"docstring": "consider the lattice as a square lattice of L shapes the hanging particles at the top and right are not used to calculate anything M is inside unit cell N is number of unit cells note that this lattice has a redundancy the linking particles are listed two times in self.r and self.f this is to en... | 2 | stack_v2_sparse_classes_30k_train_014168 | Implement the Python class `SquareLattice` described below.
Class description:
a thermal chain of bonded particles that has identical brownian particles inputs: N - #particles gamma - drag coefficient kT - temprature Larc0 - initial arc length chain0type - choose from: -straight_stretched -triangle_stretched -circle -... | Implement the Python class `SquareLattice` described below.
Class description:
a thermal chain of bonded particles that has identical brownian particles inputs: N - #particles gamma - drag coefficient kT - temprature Larc0 - initial arc length chain0type - choose from: -straight_stretched -triangle_stretched -circle -... | 855b502fea8dd93971f3073944388999c27859db | <|skeleton|>
class SquareLattice:
"""a thermal chain of bonded particles that has identical brownian particles inputs: N - #particles gamma - drag coefficient kT - temprature Larc0 - initial arc length chain0type - choose from: -straight_stretched -triangle_stretched -circle -random zigzag"""
def __init__(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SquareLattice:
"""a thermal chain of bonded particles that has identical brownian particles inputs: N - #particles gamma - drag coefficient kT - temprature Larc0 - initial arc length chain0type - choose from: -straight_stretched -triangle_stretched -circle -random zigzag"""
def __init__(self, N_width, N_... | the_stack_v2_python_sparse | 2d_md_simulator/Lattice.py | SimonStuij/MDsimulator_python | train | 0 |
0dacc7baba55b27ec3e2f9c84838f7ecdcfbbffc | [
"if host is None:\n try:\n self.host = socket.gethostbyname(socket.gethostname())\n except:\n self.host = '127.0.0.1'\nelse:\n self.host = host\nself.port = port\nself.site_path = site_path\nthreading.Thread.__init__(self)\nself.daemon = True",
"os.chdir(self.site_path)\nself.server = TestS... | <|body_start_0|>
if host is None:
try:
self.host = socket.gethostbyname(socket.gethostname())
except:
self.host = '127.0.0.1'
else:
self.host = host
self.port = port
self.site_path = site_path
threading.Thread.__... | WebServer | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WebServer:
def __init__(self, site_path, host=None, port=8880):
"""A single threaded SimpleHTTPServer This creates a daemon thread that sits and listens for web requests the thread stays alive untill the parent thread dies. By default we listen at localhost:8080"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_020935 | 2,111 | permissive | [
{
"docstring": "A single threaded SimpleHTTPServer This creates a daemon thread that sits and listens for web requests the thread stays alive untill the parent thread dies. By default we listen at localhost:8080",
"name": "__init__",
"signature": "def __init__(self, site_path, host=None, port=8880)"
}... | 2 | stack_v2_sparse_classes_30k_train_017292 | Implement the Python class `WebServer` described below.
Class description:
Implement the WebServer class.
Method signatures and docstrings:
- def __init__(self, site_path, host=None, port=8880): A single threaded SimpleHTTPServer This creates a daemon thread that sits and listens for web requests the thread stays ali... | Implement the Python class `WebServer` described below.
Class description:
Implement the WebServer class.
Method signatures and docstrings:
- def __init__(self, site_path, host=None, port=8880): A single threaded SimpleHTTPServer This creates a daemon thread that sits and listens for web requests the thread stays ali... | 09b962a7316e142ff917be47502cbfac4aed7ed6 | <|skeleton|>
class WebServer:
def __init__(self, site_path, host=None, port=8880):
"""A single threaded SimpleHTTPServer This creates a daemon thread that sits and listens for web requests the thread stays alive untill the parent thread dies. By default we listen at localhost:8080"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WebServer:
def __init__(self, site_path, host=None, port=8880):
"""A single threaded SimpleHTTPServer This creates a daemon thread that sits and listens for web requests the thread stays alive untill the parent thread dies. By default we listen at localhost:8080"""
if host is None:
... | the_stack_v2_python_sparse | staticpy/web_server.py | toddsifleet/staticpy | train | 1 | |
aef0ca8c96df3298026a946d01d61c1f80312bdf | [
"if event is None:\n event = np.ones(np.shape(time))\ntime, event = validate_samples(time, event, n_dim=1, equal_lengths=True)\nif any((t <= 0 for t in time)):\n raise ValueError(\"Entries of parameter 'time' must be positive.\")\nif any((x not in (0, 1) for x in event)):\n raise ValueError(\"Entries of pa... | <|body_start_0|>
if event is None:
event = np.ones(np.shape(time))
time, event = validate_samples(time, event, n_dim=1, equal_lengths=True)
if any((t <= 0 for t in time)):
raise ValueError("Entries of parameter 'time' must be positive.")
if any((x not in (0, 1) fo... | Non-parametric survival function estimator for right-censored data. Properties ---------- time : numpy.ndarray Vector of observed event times. event : numpy.ndarray Failure indicator (0=right-censored, 1=failure). survival : numpy.ndarray Estimate of the survival function at each observed failure time. | KaplanMeier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KaplanMeier:
"""Non-parametric survival function estimator for right-censored data. Properties ---------- time : numpy.ndarray Vector of observed event times. event : numpy.ndarray Failure indicator (0=right-censored, 1=failure). survival : numpy.ndarray Estimate of the survival function at each ... | stack_v2_sparse_classes_36k_train_020936 | 5,387 | permissive | [
{
"docstring": "Fit the Kaplan-Meier estimator using Efron's \"redistribution to the right\" algorithm. Parameters ---------- time : array-like, of shape (n,) Vector of observed event times. event : array-like, of shape (n,) Vector of 0's and 1's, 0 indicating a right-censored event, 1 indicating a failure. Ret... | 2 | stack_v2_sparse_classes_30k_val_001034 | Implement the Python class `KaplanMeier` described below.
Class description:
Non-parametric survival function estimator for right-censored data. Properties ---------- time : numpy.ndarray Vector of observed event times. event : numpy.ndarray Failure indicator (0=right-censored, 1=failure). survival : numpy.ndarray Est... | Implement the Python class `KaplanMeier` described below.
Class description:
Non-parametric survival function estimator for right-censored data. Properties ---------- time : numpy.ndarray Vector of observed event times. event : numpy.ndarray Failure indicator (0=right-censored, 1=failure). survival : numpy.ndarray Est... | 04525b5d6777be3ccdc6ad44e4cbfe24a8875933 | <|skeleton|>
class KaplanMeier:
"""Non-parametric survival function estimator for right-censored data. Properties ---------- time : numpy.ndarray Vector of observed event times. event : numpy.ndarray Failure indicator (0=right-censored, 1=failure). survival : numpy.ndarray Estimate of the survival function at each ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KaplanMeier:
"""Non-parametric survival function estimator for right-censored data. Properties ---------- time : numpy.ndarray Vector of observed event times. event : numpy.ndarray Failure indicator (0=right-censored, 1=failure). survival : numpy.ndarray Estimate of the survival function at each observed fail... | the_stack_v2_python_sparse | stattools/survival/kaplan_meier.py | roarkemc/StatTools | train | 0 |
2da750b4b196d236e289d467d04796659b218130 | [
"base_directory_glob = f'{self.multihost_base_directory}-*'\nbase_directories = tf.io.gfile.glob(base_directory_glob)\nif self.base_directory not in base_directories:\n return None\ncheckpoints = {}\nfor base_directory in base_directories:\n checkpoint_manager = tf.train.CheckpointManager(tf.train.Checkpoint(... | <|body_start_0|>
base_directory_glob = f'{self.multihost_base_directory}-*'
base_directories = tf.io.gfile.glob(base_directory_glob)
if self.base_directory not in base_directories:
return None
checkpoints = {}
for base_directory in base_directories:
checkp... | An subclass of `Checkpoint` that synchronizes between multiple JAX hosts. | QueryMultihostCheckpoint | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueryMultihostCheckpoint:
"""An subclass of `Checkpoint` that synchronizes between multiple JAX hosts."""
def get_all_checkpoints_to_restore_from(self):
"""Returns the latest checkpoint available on all hosts."""
<|body_0|>
def restore_from_path(self, state: T, path: str... | stack_v2_sparse_classes_36k_train_020937 | 7,517 | permissive | [
{
"docstring": "Returns the latest checkpoint available on all hosts.",
"name": "get_all_checkpoints_to_restore_from",
"signature": "def get_all_checkpoints_to_restore_from(self)"
},
{
"docstring": "Restores from a given checkpoint path. Args: state : A flax checkpoint to be stored or to serve a... | 2 | stack_v2_sparse_classes_30k_train_011134 | Implement the Python class `QueryMultihostCheckpoint` described below.
Class description:
An subclass of `Checkpoint` that synchronizes between multiple JAX hosts.
Method signatures and docstrings:
- def get_all_checkpoints_to_restore_from(self): Returns the latest checkpoint available on all hosts.
- def restore_fro... | Implement the Python class `QueryMultihostCheckpoint` described below.
Class description:
An subclass of `Checkpoint` that synchronizes between multiple JAX hosts.
Method signatures and docstrings:
- def get_all_checkpoints_to_restore_from(self): Returns the latest checkpoint available on all hosts.
- def restore_fro... | 1ed54e21f889775cf9e78ff736f804472c9b4337 | <|skeleton|>
class QueryMultihostCheckpoint:
"""An subclass of `Checkpoint` that synchronizes between multiple JAX hosts."""
def get_all_checkpoints_to_restore_from(self):
"""Returns the latest checkpoint available on all hosts."""
<|body_0|>
def restore_from_path(self, state: T, path: str... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueryMultihostCheckpoint:
"""An subclass of `Checkpoint` that synchronizes between multiple JAX hosts."""
def get_all_checkpoints_to_restore_from(self):
"""Returns the latest checkpoint available on all hosts."""
base_directory_glob = f'{self.multihost_base_directory}-*'
base_dire... | the_stack_v2_python_sparse | xmcgan/utils/task_manager.py | jiny419/xmcgan_image_generation | train | 0 |
5641100448b83aa4f90dad9abb3732bc7bbdf896 | [
"data = request.data\nserializer = self.serializer_class(data=data)\nserializer.is_valid(raise_exception=True)\nuser = serializer.validated_data['user']\ntoken = AuthToken.objects.create(user)\nlogin(request, user)\nprefixes = prefix_service.find(user=user).all()\nif len(prefixes) == 1:\n user.profile.product_ac... | <|body_start_0|>
data = request.data
serializer = self.serializer_class(data=data)
serializer.is_valid(raise_exception=True)
user = serializer.validated_data['user']
token = AuthToken.objects.create(user)
login(request, user)
prefixes = prefix_service.find(user=us... | UserLoginView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserLoginView:
def post(self, request, *args, **kwargs):
"""logs in the user"""
<|body_0|>
def get(self, request):
"""validates if user is still logged in, in which case returns app token"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = reques... | stack_v2_sparse_classes_36k_train_020938 | 11,433 | no_license | [
{
"docstring": "logs in the user",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
},
{
"docstring": "validates if user is still logged in, in which case returns app token",
"name": "get",
"signature": "def get(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018848 | Implement the Python class `UserLoginView` described below.
Class description:
Implement the UserLoginView class.
Method signatures and docstrings:
- def post(self, request, *args, **kwargs): logs in the user
- def get(self, request): validates if user is still logged in, in which case returns app token | Implement the Python class `UserLoginView` described below.
Class description:
Implement the UserLoginView class.
Method signatures and docstrings:
- def post(self, request, *args, **kwargs): logs in the user
- def get(self, request): validates if user is still logged in, in which case returns app token
<|skeleton|>... | 338fd6396dbdce971bc542718fbb9608bdcfc2a7 | <|skeleton|>
class UserLoginView:
def post(self, request, *args, **kwargs):
"""logs in the user"""
<|body_0|>
def get(self, request):
"""validates if user is still logged in, in which case returns app token"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserLoginView:
def post(self, request, *args, **kwargs):
"""logs in the user"""
data = request.data
serializer = self.serializer_class(data=data)
serializer.is_valid(raise_exception=True)
user = serializer.validated_data['user']
token = AuthToken.objects.create(... | the_stack_v2_python_sparse | api/views/account_views.py | sai9912/mypyton | train | 0 | |
7176962bd8c5f25a42cdb36b4a53f027e1259760 | [
"db.session.add(self)\nif commit is True:\n db.session.commit()",
"try:\n code = kwargs['code']\nexcept KeyError:\n code = uuid.uuid4()\nobj = VerificationCodes(verified_user=kwargs['user'], code=code, types=kwargs['types'], status=kwargs['status'], created_by=str(kwargs['user'].id))\ndb.session.add(obj)... | <|body_start_0|>
db.session.add(self)
if commit is True:
db.session.commit()
<|end_body_0|>
<|body_start_1|>
try:
code = kwargs['code']
except KeyError:
code = uuid.uuid4()
obj = VerificationCodes(verified_user=kwargs['user'], code=code, types... | verification codes model | VerificationCodes | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VerificationCodes:
"""verification codes model"""
def save(self, commit=True):
"""VerificationCodes save method"""
<|body_0|>
def save_verification_code(**kwargs):
"""save verification code to db"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
d... | stack_v2_sparse_classes_36k_train_020939 | 2,150 | no_license | [
{
"docstring": "VerificationCodes save method",
"name": "save",
"signature": "def save(self, commit=True)"
},
{
"docstring": "save verification code to db",
"name": "save_verification_code",
"signature": "def save_verification_code(**kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005953 | Implement the Python class `VerificationCodes` described below.
Class description:
verification codes model
Method signatures and docstrings:
- def save(self, commit=True): VerificationCodes save method
- def save_verification_code(**kwargs): save verification code to db | Implement the Python class `VerificationCodes` described below.
Class description:
verification codes model
Method signatures and docstrings:
- def save(self, commit=True): VerificationCodes save method
- def save_verification_code(**kwargs): save verification code to db
<|skeleton|>
class VerificationCodes:
"""... | 4dc5f5e816e3c461b8a60c5f61c7eafc08050579 | <|skeleton|>
class VerificationCodes:
"""verification codes model"""
def save(self, commit=True):
"""VerificationCodes save method"""
<|body_0|>
def save_verification_code(**kwargs):
"""save verification code to db"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VerificationCodes:
"""verification codes model"""
def save(self, commit=True):
"""VerificationCodes save method"""
db.session.add(self)
if commit is True:
db.session.commit()
def save_verification_code(**kwargs):
"""save verification code to db"""
... | the_stack_v2_python_sparse | app/models/verification_codes.py | ekramulmostafa/ms-auth | train | 0 |
2bdd5a02f1774029c2134f6488806c0edff5bba9 | [
"self.hass = hass\nself.speech = None\nself.card = None\nself.reprompt = None\nself.session_attributes = {}\nself.should_end_session = True\nif intent is not None and 'slots' in intent:\n self.variables = {key: value['value'] for key, value in intent['slots'].items() if 'value' in value}\nelse:\n self.variabl... | <|body_start_0|>
self.hass = hass
self.speech = None
self.card = None
self.reprompt = None
self.session_attributes = {}
self.should_end_session = True
if intent is not None and 'slots' in intent:
self.variables = {key: value['value'] for key, value in ... | Help generating the response for Alexa. | AlexaResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlexaResponse:
"""Help generating the response for Alexa."""
def __init__(self, hass, intent=None):
"""Initialize the response."""
<|body_0|>
def add_card(self, card_type, title, content):
"""Add a card to the response."""
<|body_1|>
def add_speech(s... | stack_v2_sparse_classes_36k_train_020940 | 6,645 | permissive | [
{
"docstring": "Initialize the response.",
"name": "__init__",
"signature": "def __init__(self, hass, intent=None)"
},
{
"docstring": "Add a card to the response.",
"name": "add_card",
"signature": "def add_card(self, card_type, title, content)"
},
{
"docstring": "Add speech to t... | 5 | null | Implement the Python class `AlexaResponse` described below.
Class description:
Help generating the response for Alexa.
Method signatures and docstrings:
- def __init__(self, hass, intent=None): Initialize the response.
- def add_card(self, card_type, title, content): Add a card to the response.
- def add_speech(self,... | Implement the Python class `AlexaResponse` described below.
Class description:
Help generating the response for Alexa.
Method signatures and docstrings:
- def __init__(self, hass, intent=None): Initialize the response.
- def add_card(self, card_type, title, content): Add a card to the response.
- def add_speech(self,... | ca0e92aba83de2fd6cb1cc4d14f3b4471f17cf3d | <|skeleton|>
class AlexaResponse:
"""Help generating the response for Alexa."""
def __init__(self, hass, intent=None):
"""Initialize the response."""
<|body_0|>
def add_card(self, card_type, title, content):
"""Add a card to the response."""
<|body_1|>
def add_speech(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlexaResponse:
"""Help generating the response for Alexa."""
def __init__(self, hass, intent=None):
"""Initialize the response."""
self.hass = hass
self.speech = None
self.card = None
self.reprompt = None
self.session_attributes = {}
self.should_end... | the_stack_v2_python_sparse | homeassistant/components/alexa.py | Smart-Torvy/torvy-home-assistant | train | 2 |
df88988a47b2ecf8fc7e57e0f507b9bc2d8d86ba | [
"N = len(Profits)\n\ndef dfs(i, k, c):\n if k == 0 or i == N:\n return c\n ret = [dfs(i + 1, k, c)]\n if Capital[i] <= c:\n ret.append(dfs(i + 1, k - 1, c + Profits[i]))\n return max(ret)\nreturn dfs(0, k, W)",
"N = len(Profits)\nmemo = {k: W}\ncp = list(sorted(zip(Capital, Profits)))\nf... | <|body_start_0|>
N = len(Profits)
def dfs(i, k, c):
if k == 0 or i == N:
return c
ret = [dfs(i + 1, k, c)]
if Capital[i] <= c:
ret.append(dfs(i + 1, k - 1, c + Profits[i]))
return max(ret)
return dfs(0, k, W)
<|end_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMaximizedCapital(self, k: int, W: int, Profits: List[int], Capital: List[int]) -> int:
"""Nov 01, 2020 12:26"""
<|body_0|>
def findMaximizedCapital(self, k: int, W: int, Profits: List[int], Capital: List[int]) -> int:
"""Nov 01, 2020 13:05"""
... | stack_v2_sparse_classes_36k_train_020941 | 12,781 | no_license | [
{
"docstring": "Nov 01, 2020 12:26",
"name": "findMaximizedCapital",
"signature": "def findMaximizedCapital(self, k: int, W: int, Profits: List[int], Capital: List[int]) -> int"
},
{
"docstring": "Nov 01, 2020 13:05",
"name": "findMaximizedCapital",
"signature": "def findMaximizedCapital... | 4 | stack_v2_sparse_classes_30k_train_010827 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaximizedCapital(self, k: int, W: int, Profits: List[int], Capital: List[int]) -> int: Nov 01, 2020 12:26
- def findMaximizedCapital(self, k: int, W: int, Profits: List[i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaximizedCapital(self, k: int, W: int, Profits: List[int], Capital: List[int]) -> int: Nov 01, 2020 12:26
- def findMaximizedCapital(self, k: int, W: int, Profits: List[i... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def findMaximizedCapital(self, k: int, W: int, Profits: List[int], Capital: List[int]) -> int:
"""Nov 01, 2020 12:26"""
<|body_0|>
def findMaximizedCapital(self, k: int, W: int, Profits: List[int], Capital: List[int]) -> int:
"""Nov 01, 2020 13:05"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMaximizedCapital(self, k: int, W: int, Profits: List[int], Capital: List[int]) -> int:
"""Nov 01, 2020 12:26"""
N = len(Profits)
def dfs(i, k, c):
if k == 0 or i == N:
return c
ret = [dfs(i + 1, k, c)]
if Capital[i]... | the_stack_v2_python_sparse | leetcode/solved/502_IPO/solution.py | sungminoh/algorithms | train | 0 | |
467b62c5c6dbd3ff8834c49ebb91a6b8b0e504c7 | [
"for k in range(len(self.mset) + 1):\n for comb in Combinations_setk(self.mset, k):\n yield comb",
"k = 0\nn = len(self.mset)\nb = binomial(n, k)\nwhile r >= b:\n r -= b\n k += 1\n b = binomial(n, k)\nreturn [self.mset[i] for i in from_rank(r, n, k)]",
"x = [self.mset.index(_) for _ in x]\nr ... | <|body_start_0|>
for k in range(len(self.mset) + 1):
for comb in Combinations_setk(self.mset, k):
yield comb
<|end_body_0|>
<|body_start_1|>
k = 0
n = len(self.mset)
b = binomial(n, k)
while r >= b:
r -= b
k += 1
b ... | Combinations_set | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Combinations_set:
def __iter__(self):
"""EXAMPLES:: sage: Combinations([1,2,3]).list() #indirect doctest [[], [1], [2], [3], [1, 2], [1, 3], [2, 3], [1, 2, 3]]"""
<|body_0|>
def unrank(self, r):
"""EXAMPLES:: sage: c = Combinations([1,2,3]) sage: c.list() == map(c.un... | stack_v2_sparse_classes_36k_train_020942 | 16,000 | no_license | [
{
"docstring": "EXAMPLES:: sage: Combinations([1,2,3]).list() #indirect doctest [[], [1], [2], [3], [1, 2], [1, 3], [2, 3], [1, 2, 3]]",
"name": "__iter__",
"signature": "def __iter__(self)"
},
{
"docstring": "EXAMPLES:: sage: c = Combinations([1,2,3]) sage: c.list() == map(c.unrank, range(c.car... | 3 | stack_v2_sparse_classes_30k_train_004987 | Implement the Python class `Combinations_set` described below.
Class description:
Implement the Combinations_set class.
Method signatures and docstrings:
- def __iter__(self): EXAMPLES:: sage: Combinations([1,2,3]).list() #indirect doctest [[], [1], [2], [3], [1, 2], [1, 3], [2, 3], [1, 2, 3]]
- def unrank(self, r): ... | Implement the Python class `Combinations_set` described below.
Class description:
Implement the Combinations_set class.
Method signatures and docstrings:
- def __iter__(self): EXAMPLES:: sage: Combinations([1,2,3]).list() #indirect doctest [[], [1], [2], [3], [1, 2], [1, 3], [2, 3], [1, 2, 3]]
- def unrank(self, r): ... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class Combinations_set:
def __iter__(self):
"""EXAMPLES:: sage: Combinations([1,2,3]).list() #indirect doctest [[], [1], [2], [3], [1, 2], [1, 3], [2, 3], [1, 2, 3]]"""
<|body_0|>
def unrank(self, r):
"""EXAMPLES:: sage: c = Combinations([1,2,3]) sage: c.list() == map(c.un... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Combinations_set:
def __iter__(self):
"""EXAMPLES:: sage: Combinations([1,2,3]).list() #indirect doctest [[], [1], [2], [3], [1, 2], [1, 3], [2, 3], [1, 2, 3]]"""
for k in range(len(self.mset) + 1):
for comb in Combinations_setk(self.mset, k):
yield comb
def un... | the_stack_v2_python_sparse | sage/src/sage/combinat/combination.py | bopopescu/geosci | train | 0 | |
0341adbcc9667e041ccd24776d3d8b1a0d8eb714 | [
"super().__init__(**kwargs)\nself.alpha = alpha\nself.gamma = gamma\nself.label_smoothing = label_smoothing",
"normalizer, y_true = y\nalpha = tf.convert_to_tensor(self.alpha, dtype=y_pred.dtype)\ngamma = tf.convert_to_tensor(self.gamma, dtype=y_pred.dtype)\npred_prob = tf.sigmoid(y_pred)\np_t = y_true * pred_pro... | <|body_start_0|>
super().__init__(**kwargs)
self.alpha = alpha
self.gamma = gamma
self.label_smoothing = label_smoothing
<|end_body_0|>
<|body_start_1|>
normalizer, y_true = y
alpha = tf.convert_to_tensor(self.alpha, dtype=y_pred.dtype)
gamma = tf.convert_to_tens... | Compute the focal loss between `logits` and the golden `target` values. Focal loss = -(1-pt)^gamma * log(pt) where pt is the probability of being classified to the true class. | FocalLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FocalLoss:
"""Compute the focal loss between `logits` and the golden `target` values. Focal loss = -(1-pt)^gamma * log(pt) where pt is the probability of being classified to the true class."""
def __init__(self, alpha, gamma, label_smoothing=0.0, **kwargs):
"""Initialize focal loss. ... | stack_v2_sparse_classes_36k_train_020943 | 17,443 | permissive | [
{
"docstring": "Initialize focal loss. Args: alpha: A float32 scalar multiplying alpha to the loss from positive examples and (1-alpha) to the loss from negative examples. gamma: A float32 scalar modulating loss from hard and easy examples. label_smoothing: Float in [0, 1]. If > `0` then smooth the labels. **kw... | 2 | stack_v2_sparse_classes_30k_train_014787 | Implement the Python class `FocalLoss` described below.
Class description:
Compute the focal loss between `logits` and the golden `target` values. Focal loss = -(1-pt)^gamma * log(pt) where pt is the probability of being classified to the true class.
Method signatures and docstrings:
- def __init__(self, alpha, gamma... | Implement the Python class `FocalLoss` described below.
Class description:
Compute the focal loss between `logits` and the golden `target` values. Focal loss = -(1-pt)^gamma * log(pt) where pt is the probability of being classified to the true class.
Method signatures and docstrings:
- def __init__(self, alpha, gamma... | a5388a45f71a949639b35cc5b990bd130d2d8164 | <|skeleton|>
class FocalLoss:
"""Compute the focal loss between `logits` and the golden `target` values. Focal loss = -(1-pt)^gamma * log(pt) where pt is the probability of being classified to the true class."""
def __init__(self, alpha, gamma, label_smoothing=0.0, **kwargs):
"""Initialize focal loss. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FocalLoss:
"""Compute the focal loss between `logits` and the golden `target` values. Focal loss = -(1-pt)^gamma * log(pt) where pt is the probability of being classified to the true class."""
def __init__(self, alpha, gamma, label_smoothing=0.0, **kwargs):
"""Initialize focal loss. Args: alpha: ... | the_stack_v2_python_sparse | TensorFlow2/Detection/Efficientdet/utils/train_lib.py | NVIDIA/DeepLearningExamples | train | 11,838 |
12403df832b5bec19b75176bf1a3d032d8b6564e | [
"if not re.match('\\\\w+@\\\\w+.\\\\w+', email):\n raise serializers.ValidationError('邮箱格式不正确')\nreturn email",
"bind_token = attrs['bind_token']\nopenid = OAuthBase.check_save_user_token(bind_token)\nif not openid:\n raise serializers.ValidationError('无效的bind_token')\nattrs['openid'] = openid\nreal_email_c... | <|body_start_0|>
if not re.match('\\w+@\\w+.\\w+', email):
raise serializers.ValidationError('邮箱格式不正确')
return email
<|end_body_0|>
<|body_start_1|>
bind_token = attrs['bind_token']
openid = OAuthBase.check_save_user_token(bind_token)
if not openid:
raise... | 第三方账户绑定的序列化器 | OAuthSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OAuthSerializer:
"""第三方账户绑定的序列化器"""
def validate_email(self, email):
"""验证邮箱格式 :param value: :return:"""
<|body_0|>
def validate(self, attrs):
"""验证access_token :param attrs: :return:"""
<|body_1|>
def create(self, validated_data):
"""保存用户 :p... | stack_v2_sparse_classes_36k_train_020944 | 4,280 | no_license | [
{
"docstring": "验证邮箱格式 :param value: :return:",
"name": "validate_email",
"signature": "def validate_email(self, email)"
},
{
"docstring": "验证access_token :param attrs: :return:",
"name": "validate",
"signature": "def validate(self, attrs)"
},
{
"docstring": "保存用户 :param validate... | 3 | stack_v2_sparse_classes_30k_train_015260 | Implement the Python class `OAuthSerializer` described below.
Class description:
第三方账户绑定的序列化器
Method signatures and docstrings:
- def validate_email(self, email): 验证邮箱格式 :param value: :return:
- def validate(self, attrs): 验证access_token :param attrs: :return:
- def create(self, validated_data): 保存用户 :param validated_... | Implement the Python class `OAuthSerializer` described below.
Class description:
第三方账户绑定的序列化器
Method signatures and docstrings:
- def validate_email(self, email): 验证邮箱格式 :param value: :return:
- def validate(self, attrs): 验证access_token :param attrs: :return:
- def create(self, validated_data): 保存用户 :param validated_... | 952453482f5eb25bf642a132382801423f35b80c | <|skeleton|>
class OAuthSerializer:
"""第三方账户绑定的序列化器"""
def validate_email(self, email):
"""验证邮箱格式 :param value: :return:"""
<|body_0|>
def validate(self, attrs):
"""验证access_token :param attrs: :return:"""
<|body_1|>
def create(self, validated_data):
"""保存用户 :p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OAuthSerializer:
"""第三方账户绑定的序列化器"""
def validate_email(self, email):
"""验证邮箱格式 :param value: :return:"""
if not re.match('\\w+@\\w+.\\w+', email):
raise serializers.ValidationError('邮箱格式不正确')
return email
def validate(self, attrs):
"""验证access_token :param... | the_stack_v2_python_sparse | meiduo_mall/oauth/serializers.py | juehuan182/MeiduoShopping | train | 0 |
dbb50fd1ea93ee7b5d369d25c3eb98016d8c1d5b | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn CalendarSharingMessageAction()",
"from .calendar_sharing_action import CalendarSharingAction\nfrom .calendar_sharing_action_importance import CalendarSharingActionImportance\nfrom .calendar_sharing_action_type import CalendarSharingAct... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return CalendarSharingMessageAction()
<|end_body_0|>
<|body_start_1|>
from .calendar_sharing_action import CalendarSharingAction
from .calendar_sharing_action_importance import CalendarSharingA... | CalendarSharingMessageAction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalendarSharingMessageAction:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction:
"""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... | stack_v2_sparse_classes_36k_train_020945 | 3,763 | 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: CalendarSharingMessageAction",
"name": "create_from_discriminator_value",
"signature": "def create_from_disc... | 3 | stack_v2_sparse_classes_30k_train_009072 | Implement the Python class `CalendarSharingMessageAction` described below.
Class description:
Implement the CalendarSharingMessageAction class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction: Creates a new instance of the a... | Implement the Python class `CalendarSharingMessageAction` described below.
Class description:
Implement the CalendarSharingMessageAction class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction: Creates a new instance of the a... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class CalendarSharingMessageAction:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction:
"""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... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CalendarSharingMessageAction:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction:
"""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 th... | the_stack_v2_python_sparse | msgraph/generated/models/calendar_sharing_message_action.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e89f669ef8fc4c950b6a3d70901a9dbfa4b24c0e | [
"dp = [[math.inf] * (N + 1) for _ in range(K + 1)]\nfor i in range(1, K + 1):\n dp[i][0] = 0\n dp[i][1] = 1\nfor j in range(1, N + 1):\n dp[1][j] = j\nfor i in range(2, K + 1):\n for j in range(2, N + 1):\n for k in range(1, j + 1):\n dp[i][j] = min(dp[i][j], 1 + max(dp[i - 1][k - 1], ... | <|body_start_0|>
dp = [[math.inf] * (N + 1) for _ in range(K + 1)]
for i in range(1, K + 1):
dp[i][0] = 0
dp[i][1] = 1
for j in range(1, N + 1):
dp[1][j] = j
for i in range(2, K + 1):
for j in range(2, N + 1):
for k in range... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def superEggDrop_solution_1_brute_force(self, K: int, N: int) -> int:
""":type K: int :type N: int :rtype: int"""
<|body_0|>
def superEggDrop_solution_2_optimization_one(self, K: int, N: int) -> int:
""":type K: int :type N: int :rtype: int"""
<|bod... | stack_v2_sparse_classes_36k_train_020946 | 7,392 | no_license | [
{
"docstring": ":type K: int :type N: int :rtype: int",
"name": "superEggDrop_solution_1_brute_force",
"signature": "def superEggDrop_solution_1_brute_force(self, K: int, N: int) -> int"
},
{
"docstring": ":type K: int :type N: int :rtype: int",
"name": "superEggDrop_solution_2_optimization_... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def superEggDrop_solution_1_brute_force(self, K: int, N: int) -> int: :type K: int :type N: int :rtype: int
- def superEggDrop_solution_2_optimization_one(self, K: int, N: int) -... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def superEggDrop_solution_1_brute_force(self, K: int, N: int) -> int: :type K: int :type N: int :rtype: int
- def superEggDrop_solution_2_optimization_one(self, K: int, N: int) -... | f2621cd76822a922c49b60f32931f26cce1c571d | <|skeleton|>
class Solution:
def superEggDrop_solution_1_brute_force(self, K: int, N: int) -> int:
""":type K: int :type N: int :rtype: int"""
<|body_0|>
def superEggDrop_solution_2_optimization_one(self, K: int, N: int) -> int:
""":type K: int :type N: int :rtype: int"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def superEggDrop_solution_1_brute_force(self, K: int, N: int) -> int:
""":type K: int :type N: int :rtype: int"""
dp = [[math.inf] * (N + 1) for _ in range(K + 1)]
for i in range(1, K + 1):
dp[i][0] = 0
dp[i][1] = 1
for j in range(1, N + 1):
... | the_stack_v2_python_sparse | Dynamic_Programming/019_leetcode_P_887_SuperEggDrop/Solution.py | Keshav1506/competitive_programming | train | 0 | |
258fa2d7c5873801c63264e09d57e339eeaa4b37 | [
"super().__init__()\nself.in_chans = in_chans\nself.out_chans = out_chans\nself.chans = chans\nself.num_pool_layers = num_pool_layers\nself.drop_prob = drop_prob\nself.down_sample_layers = nn.ModuleList([ConvBlock(in_chans, chans, drop_prob)])\nch = chans\nfor i in range(num_pool_layers - 1):\n self.down_sample_... | <|body_start_0|>
super().__init__()
self.in_chans = in_chans
self.out_chans = out_chans
self.chans = chans
self.num_pool_layers = num_pool_layers
self.drop_prob = drop_prob
self.down_sample_layers = nn.ModuleList([ConvBlock(in_chans, chans, drop_prob)])
ch... | PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention, pages 234–241. Springer, 2015. | UnetModelTakeEverywhereWithIntermediate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnetModelTakeEverywhereWithIntermediate:
"""PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted ... | stack_v2_sparse_classes_36k_train_020947 | 30,521 | no_license | [
{
"docstring": "Args: in_chans (int): Number of channels in the input to the U-Net model. out_chans (int): Number of channels in the output to the U-Net model. chans (int): Number of output channels of the first convolution layer. num_pool_layers (int): Number of down-sampling and up-sampling layers. drop_prob ... | 2 | stack_v2_sparse_classes_30k_train_002394 | Implement the Python class `UnetModelTakeEverywhereWithIntermediate` described below.
Class description:
PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical... | Implement the Python class `UnetModelTakeEverywhereWithIntermediate` described below.
Class description:
PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical... | 219652c8a08c4f2f682acd9f95a4e1b3fd36b70b | <|skeleton|>
class UnetModelTakeEverywhereWithIntermediate:
"""PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UnetModelTakeEverywhereWithIntermediate:
"""PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention,... | the_stack_v2_python_sparse | lemawarersn_t1assist/models.py | Bala93/Holistic-MRI-Reconstruction | train | 1 |
e51492f2dd2cad288eff1ca0cc612c448c94d74c | [
"l = [0 for i in range(32)]\nindex = 31\nwhile n != 0:\n l[index] = n % 2\n n = n // 2\n index -= 1\nnumber = 0\nfor i in range(len(l)):\n number += l[i] * 2 ** i\nreturn number",
"num = bin(n)[2:]\nnum = str((32 - len(num)) * '0' + num)[::-1]\nreturn int(num, 2)"
] | <|body_start_0|>
l = [0 for i in range(32)]
index = 31
while n != 0:
l[index] = n % 2
n = n // 2
index -= 1
number = 0
for i in range(len(l)):
number += l[i] * 2 ** i
return number
<|end_body_0|>
<|body_start_1|>
nu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse_bits(self, n):
"""Generic Style"""
<|body_0|>
def reverse_bits2(self, n):
"""Python Style"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
l = [0 for i in range(32)]
index = 31
while n != 0:
l[index] ... | stack_v2_sparse_classes_36k_train_020948 | 845 | no_license | [
{
"docstring": "Generic Style",
"name": "reverse_bits",
"signature": "def reverse_bits(self, n)"
},
{
"docstring": "Python Style",
"name": "reverse_bits2",
"signature": "def reverse_bits2(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse_bits(self, n): Generic Style
- def reverse_bits2(self, n): Python Style | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse_bits(self, n): Generic Style
- def reverse_bits2(self, n): Python Style
<|skeleton|>
class Solution:
def reverse_bits(self, n):
"""Generic Style"""
... | b7e92f9a7c4d6652d4901b189f51063ce5520653 | <|skeleton|>
class Solution:
def reverse_bits(self, n):
"""Generic Style"""
<|body_0|>
def reverse_bits2(self, n):
"""Python Style"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverse_bits(self, n):
"""Generic Style"""
l = [0 for i in range(32)]
index = 31
while n != 0:
l[index] = n % 2
n = n // 2
index -= 1
number = 0
for i in range(len(l)):
number += l[i] * 2 ** i
... | the_stack_v2_python_sparse | leetcode/easy/reverse_bits.py | abkunal/Data-Structures-and-Algorithms | train | 2 | |
7c95171619985a7770772a094f52bad2824d330c | [
"super().__init__(name, entity_id, CATEGORY_SENSOR, *args, **kwargs)\nself._hass = hass\nself._entity_id = entity_id\nserv_humidity = add_preload_service(self, SERV_HUMIDITY_SENSOR)\nself.char_humidity = serv_humidity.get_characteristic(CHAR_CURRENT_HUMIDITY)\nself.char_humidity.value = 0",
"if new_state is None:... | <|body_start_0|>
super().__init__(name, entity_id, CATEGORY_SENSOR, *args, **kwargs)
self._hass = hass
self._entity_id = entity_id
serv_humidity = add_preload_service(self, SERV_HUMIDITY_SENSOR)
self.char_humidity = serv_humidity.get_characteristic(CHAR_CURRENT_HUMIDITY)
... | Generate a HumiditySensor accessory as humidity sensor. | HumiditySensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HumiditySensor:
"""Generate a HumiditySensor accessory as humidity sensor."""
def __init__(self, hass, entity_id, name, *args, **kwargs):
"""Initialize a HumiditySensor accessory object."""
<|body_0|>
def update_state(self, entity_id=None, old_state=None, new_state=None)... | stack_v2_sparse_classes_36k_train_020949 | 3,357 | permissive | [
{
"docstring": "Initialize a HumiditySensor accessory object.",
"name": "__init__",
"signature": "def __init__(self, hass, entity_id, name, *args, **kwargs)"
},
{
"docstring": "Update accessory after state change.",
"name": "update_state",
"signature": "def update_state(self, entity_id=N... | 2 | stack_v2_sparse_classes_30k_train_019989 | Implement the Python class `HumiditySensor` described below.
Class description:
Generate a HumiditySensor accessory as humidity sensor.
Method signatures and docstrings:
- def __init__(self, hass, entity_id, name, *args, **kwargs): Initialize a HumiditySensor accessory object.
- def update_state(self, entity_id=None,... | Implement the Python class `HumiditySensor` described below.
Class description:
Generate a HumiditySensor accessory as humidity sensor.
Method signatures and docstrings:
- def __init__(self, hass, entity_id, name, *args, **kwargs): Initialize a HumiditySensor accessory object.
- def update_state(self, entity_id=None,... | 5c4529d044463083bad73cdbf9d17d8cb2b29afa | <|skeleton|>
class HumiditySensor:
"""Generate a HumiditySensor accessory as humidity sensor."""
def __init__(self, hass, entity_id, name, *args, **kwargs):
"""Initialize a HumiditySensor accessory object."""
<|body_0|>
def update_state(self, entity_id=None, old_state=None, new_state=None)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HumiditySensor:
"""Generate a HumiditySensor accessory as humidity sensor."""
def __init__(self, hass, entity_id, name, *args, **kwargs):
"""Initialize a HumiditySensor accessory object."""
super().__init__(name, entity_id, CATEGORY_SENSOR, *args, **kwargs)
self._hass = hass
... | the_stack_v2_python_sparse | homeassistant/components/homekit/type_sensors.py | simpss/home-assistant | train | 1 |
c44e944c01e3bfd683202eb0be5df3168253293b | [
"l = len(nums1) + len(nums2)\nmid = l // 2\nif l % 2 == 1:\n return self.kth(nums1, nums2, mid)\nelse:\n return (self.kth(nums1, nums2, mid) + self.kth(nums1, nums2, mid - 1)) / 2",
"if len(A) > len(B):\n A, B = (B, A)\nif not A:\n return B[k]\nif k == len(A) + len(B) - 1:\n return max(A[-1], B[-1]... | <|body_start_0|>
l = len(nums1) + len(nums2)
mid = l // 2
if l % 2 == 1:
return self.kth(nums1, nums2, mid)
else:
return (self.kth(nums1, nums2, mid) + self.kth(nums1, nums2, mid - 1)) / 2
<|end_body_0|>
<|body_start_1|>
if len(A) > len(B):
A,... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2) -> float:
"""median of even len is at mid = even // 2 median of odd len is the average of (mid - 1) and mid elements"""
<|body_0|>
def kth(self, A, B, k):
"""find the kth element of two sorted array only for mi... | stack_v2_sparse_classes_36k_train_020950 | 1,620 | no_license | [
{
"docstring": "median of even len is at mid = even // 2 median of odd len is the average of (mid - 1) and mid elements",
"name": "findMedianSortedArrays",
"signature": "def findMedianSortedArrays(self, nums1, nums2) -> float"
},
{
"docstring": "find the kth element of two sorted array only for ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2) -> float: median of even len is at mid = even // 2 median of odd len is the average of (mid - 1) and mid elements
- def kth(self, A... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2) -> float: median of even len is at mid = even // 2 median of odd len is the average of (mid - 1) and mid elements
- def kth(self, A... | 3736bf8d082c8b5f92f88b09eef5060b3c6c46cb | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2) -> float:
"""median of even len is at mid = even // 2 median of odd len is the average of (mid - 1) and mid elements"""
<|body_0|>
def kth(self, A, B, k):
"""find the kth element of two sorted array only for mi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMedianSortedArrays(self, nums1, nums2) -> float:
"""median of even len is at mid = even // 2 median of odd len is the average of (mid - 1) and mid elements"""
l = len(nums1) + len(nums2)
mid = l // 2
if l % 2 == 1:
return self.kth(nums1, nums2, mid... | the_stack_v2_python_sparse | BinarySearch/MedianofTwoSortedArrays.py | JieFrye/leetcode | train | 1 | |
16281d1b69f59ea377fe24472bf6017853af13c8 | [
"super(_PyramidPoolingModule, self).__init__()\nself.features = []\nfor s in setting:\n self.features.append(nn.Sequential(nn.AdaptiveAvgPool2d(s), nn.Conv2d(in_dim, reduction_dim, kernel_size=1, bias=False), nn.BatchNorm2d(reduction_dim, momentum=0.95), nn.ReLU(inplace=True)))\nself.features = nn.ModuleList(sel... | <|body_start_0|>
super(_PyramidPoolingModule, self).__init__()
self.features = []
for s in setting:
self.features.append(nn.Sequential(nn.AdaptiveAvgPool2d(s), nn.Conv2d(in_dim, reduction_dim, kernel_size=1, bias=False), nn.BatchNorm2d(reduction_dim, momentum=0.95), nn.ReLU(inplace=T... | Creates a pyramid pooling module | _PyramidPoolingModule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _PyramidPoolingModule:
"""Creates a pyramid pooling module"""
def __init__(self, in_dim, reduction_dim, setting):
"""Initializes the pyramid pooling module"""
<|body_0|>
def forward(self, x):
"""Computes a forward pass through the network. Parameters ---------- x... | stack_v2_sparse_classes_36k_train_020951 | 4,011 | no_license | [
{
"docstring": "Initializes the pyramid pooling module",
"name": "__init__",
"signature": "def __init__(self, in_dim, reduction_dim, setting)"
},
{
"docstring": "Computes a forward pass through the network. Parameters ---------- x : torch.Tensor Input features Returns: torch.Tensor Output featur... | 2 | stack_v2_sparse_classes_30k_train_018806 | Implement the Python class `_PyramidPoolingModule` described below.
Class description:
Creates a pyramid pooling module
Method signatures and docstrings:
- def __init__(self, in_dim, reduction_dim, setting): Initializes the pyramid pooling module
- def forward(self, x): Computes a forward pass through the network. Pa... | Implement the Python class `_PyramidPoolingModule` described below.
Class description:
Creates a pyramid pooling module
Method signatures and docstrings:
- def __init__(self, in_dim, reduction_dim, setting): Initializes the pyramid pooling module
- def forward(self, x): Computes a forward pass through the network. Pa... | d833bc755cf10b16cc09038aae682387a1d1d936 | <|skeleton|>
class _PyramidPoolingModule:
"""Creates a pyramid pooling module"""
def __init__(self, in_dim, reduction_dim, setting):
"""Initializes the pyramid pooling module"""
<|body_0|>
def forward(self, x):
"""Computes a forward pass through the network. Parameters ---------- x... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _PyramidPoolingModule:
"""Creates a pyramid pooling module"""
def __init__(self, in_dim, reduction_dim, setting):
"""Initializes the pyramid pooling module"""
super(_PyramidPoolingModule, self).__init__()
self.features = []
for s in setting:
self.features.appen... | the_stack_v2_python_sparse | core/models/backbone/pspnet.py | mhashas/Temples-Classifier | train | 0 |
af99f48e1b0f91b83035567f88a474f33dc09e7b | [
"self.resource_name = str_id\nCDevice.__init__(self, self.resource_name)\nself.obj_parent = obj_device\nself.set_logger(self.obj_parent.obj_logger)\nself.set_rest_agent(self.obj_parent.obj_rest_agent)\nself.str_device_type = self.obj_parent.str_device_type\nself.uri = '{}/{}'.format(self.obj_parent.uri, self.resour... | <|body_start_0|>
self.resource_name = str_id
CDevice.__init__(self, self.resource_name)
self.obj_parent = obj_device
self.set_logger(self.obj_parent.obj_logger)
self.set_rest_agent(self.obj_parent.obj_rest_agent)
self.str_device_type = self.obj_parent.str_device_type
... | CSku | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSku:
def __init__(self, obj_device, str_id):
"""@param obj_device: Parent device that init this one @type obj_device: CDevice @param str_id: id of this SKU @type str_id: string"""
<|body_0|>
def update(self):
"""Update monorail data of self"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_020952 | 2,803 | no_license | [
{
"docstring": "@param obj_device: Parent device that init this one @type obj_device: CDevice @param str_id: id of this SKU @type str_id: string",
"name": "__init__",
"signature": "def __init__(self, obj_device, str_id)"
},
{
"docstring": "Update monorail data of self",
"name": "update",
... | 4 | stack_v2_sparse_classes_30k_train_002874 | Implement the Python class `CSku` described below.
Class description:
Implement the CSku class.
Method signatures and docstrings:
- def __init__(self, obj_device, str_id): @param obj_device: Parent device that init this one @type obj_device: CDevice @param str_id: id of this SKU @type str_id: string
- def update(self... | Implement the Python class `CSku` described below.
Class description:
Implement the CSku class.
Method signatures and docstrings:
- def __init__(self, obj_device, str_id): @param obj_device: Parent device that init this one @type obj_device: CDevice @param str_id: id of this SKU @type str_id: string
- def update(self... | 8290fc0ccbde0a6a7d8784aec04c88cc325cfa4c | <|skeleton|>
class CSku:
def __init__(self, obj_device, str_id):
"""@param obj_device: Parent device that init this one @type obj_device: CDevice @param str_id: id of this SKU @type str_id: string"""
<|body_0|>
def update(self):
"""Update monorail data of self"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CSku:
def __init__(self, obj_device, str_id):
"""@param obj_device: Parent device that init this one @type obj_device: CDevice @param str_id: id of this SKU @type str_id: string"""
self.resource_name = str_id
CDevice.__init__(self, self.resource_name)
self.obj_parent = obj_devi... | the_stack_v2_python_sparse | idic/monorail/Sku.py | InfraSIM/test | train | 1 | |
c3096c3c335acda40c457610d618589d73f8b90c | [
"l, r = (0, len(height) - 1)\nwater = 0\nwhile l < r:\n if height[l] < height[r]:\n i = l + 1\n while i < r and height[i] < height[l]:\n water += height[l] - height[i]\n i += 1\n l = i\n else:\n i = r - 1\n while i > l and height[i] < height[r]:\n ... | <|body_start_0|>
l, r = (0, len(height) - 1)
water = 0
while l < r:
if height[l] < height[r]:
i = l + 1
while i < r and height[i] < height[l]:
water += height[l] - height[i]
i += 1
l = i
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def trap1(self, height: List[int]) -> int:
"""greedy time: O(N) space: O(1)"""
<|body_0|>
def trap2(self, height: List[int]) -> int:
"""monotonic stack time: O(N) space: O(N)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
l, r = (0, len(h... | stack_v2_sparse_classes_36k_train_020953 | 1,641 | no_license | [
{
"docstring": "greedy time: O(N) space: O(1)",
"name": "trap1",
"signature": "def trap1(self, height: List[int]) -> int"
},
{
"docstring": "monotonic stack time: O(N) space: O(N)",
"name": "trap2",
"signature": "def trap2(self, height: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_016826 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap1(self, height: List[int]) -> int: greedy time: O(N) space: O(1)
- def trap2(self, height: List[int]) -> int: monotonic stack time: O(N) space: O(N) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap1(self, height: List[int]) -> int: greedy time: O(N) space: O(1)
- def trap2(self, height: List[int]) -> int: monotonic stack time: O(N) space: O(N)
<|skeleton|>
class S... | 6ff1941ff213a843013100ac7033e2d4f90fbd6a | <|skeleton|>
class Solution:
def trap1(self, height: List[int]) -> int:
"""greedy time: O(N) space: O(1)"""
<|body_0|>
def trap2(self, height: List[int]) -> int:
"""monotonic stack time: O(N) space: O(N)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def trap1(self, height: List[int]) -> int:
"""greedy time: O(N) space: O(1)"""
l, r = (0, len(height) - 1)
water = 0
while l < r:
if height[l] < height[r]:
i = l + 1
while i < r and height[i] < height[l]:
... | the_stack_v2_python_sparse | Leetcode 0042. Trapping Rain Water.py | Chaoran-sjsu/leetcode | train | 0 | |
911c1af33c13bebc987992cd258ae301ceabdb92 | [
"cmd_args = options.get('cmd_args', [''])\nexpected_substring = options.get('expected_substring', None)\ncall_task('pavelib.assets.update_assets', args=cmd_args)\nself.assertTrue(self._is_substring_in_list(self.task_messages, expected_substring), msg=f'{expected_substring} not found in messages')",
"for message i... | <|body_start_0|>
cmd_args = options.get('cmd_args', [''])
expected_substring = options.get('expected_substring', None)
call_task('pavelib.assets.update_assets', args=cmd_args)
self.assertTrue(self._is_substring_in_list(self.task_messages, expected_substring), msg=f'{expected_substring} n... | These are nearly end-to-end tests, because they observe output from the commandline request, but do not actually execute the commandline on the terminal/process | TestUpdateAssetsTask | [
"MIT",
"AGPL-3.0-only",
"AGPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestUpdateAssetsTask:
"""These are nearly end-to-end tests, because they observe output from the commandline request, but do not actually execute the commandline on the terminal/process"""
def test_update_assets_task_collectstatic_log_arg(self, options):
"""Scoped test that only look... | stack_v2_sparse_classes_36k_train_020954 | 14,737 | permissive | [
{
"docstring": "Scoped test that only looks at what is passed to the collecstatic options",
"name": "test_update_assets_task_collectstatic_log_arg",
"signature": "def test_update_assets_task_collectstatic_log_arg(self, options)"
},
{
"docstring": "Return true a given string is somewhere in a lis... | 2 | null | Implement the Python class `TestUpdateAssetsTask` described below.
Class description:
These are nearly end-to-end tests, because they observe output from the commandline request, but do not actually execute the commandline on the terminal/process
Method signatures and docstrings:
- def test_update_assets_task_collect... | Implement the Python class `TestUpdateAssetsTask` described below.
Class description:
These are nearly end-to-end tests, because they observe output from the commandline request, but do not actually execute the commandline on the terminal/process
Method signatures and docstrings:
- def test_update_assets_task_collect... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class TestUpdateAssetsTask:
"""These are nearly end-to-end tests, because they observe output from the commandline request, but do not actually execute the commandline on the terminal/process"""
def test_update_assets_task_collectstatic_log_arg(self, options):
"""Scoped test that only look... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestUpdateAssetsTask:
"""These are nearly end-to-end tests, because they observe output from the commandline request, but do not actually execute the commandline on the terminal/process"""
def test_update_assets_task_collectstatic_log_arg(self, options):
"""Scoped test that only looks at what is ... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/pavelib/paver_tests/test_assets.py | luque/better-ways-of-thinking-about-software | train | 3 |
51ba188f797c263aebb91c02b922df7478b794bd | [
"QMimeData.__init__(self)\nself._local_instance = p_data\nif p_data is not None:\n try:\n p_data = dumps(p_data)\n except Exception:\n return\n self.setData(self.MIME_TYPE, dumps(p_data.__class__) + p_data)",
"if self._local_instance is not None:\n return self._local_instance\nio = Strin... | <|body_start_0|>
QMimeData.__init__(self)
self._local_instance = p_data
if p_data is not None:
try:
p_data = dumps(p_data)
except Exception:
return
self.setData(self.MIME_TYPE, dumps(p_data.__class__) + p_data)
<|end_body_0|>
<... | The OrcMimeData wraps a Python instance as MIME data. | OrcMimeData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrcMimeData:
"""The OrcMimeData wraps a Python instance as MIME data."""
def __init__(self, p_data=None):
"""Initialise the instance."""
<|body_0|>
def instance(self):
"""Return the instance."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
QMime... | stack_v2_sparse_classes_36k_train_020955 | 13,946 | no_license | [
{
"docstring": "Initialise the instance.",
"name": "__init__",
"signature": "def __init__(self, p_data=None)"
},
{
"docstring": "Return the instance.",
"name": "instance",
"signature": "def instance(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017424 | Implement the Python class `OrcMimeData` described below.
Class description:
The OrcMimeData wraps a Python instance as MIME data.
Method signatures and docstrings:
- def __init__(self, p_data=None): Initialise the instance.
- def instance(self): Return the instance. | Implement the Python class `OrcMimeData` described below.
Class description:
The OrcMimeData wraps a Python instance as MIME data.
Method signatures and docstrings:
- def __init__(self, p_data=None): Initialise the instance.
- def instance(self): Return the instance.
<|skeleton|>
class OrcMimeData:
"""The OrcMim... | f3ccbbceaed4f4996f6907a2f4880c2fd3f82bbb | <|skeleton|>
class OrcMimeData:
"""The OrcMimeData wraps a Python instance as MIME data."""
def __init__(self, p_data=None):
"""Initialise the instance."""
<|body_0|>
def instance(self):
"""Return the instance."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrcMimeData:
"""The OrcMimeData wraps a Python instance as MIME data."""
def __init__(self, p_data=None):
"""Initialise the instance."""
QMimeData.__init__(self)
self._local_instance = p_data
if p_data is not None:
try:
p_data = dumps(p_data)
... | the_stack_v2_python_sparse | OrcView/Lib/LibTree.py | pubselenium/OrcTestToolsKit | train | 0 |
b427427086471f1f817c57521cb48782490d3351 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ContainerEvidence()",
"from .alert_evidence import AlertEvidence\nfrom .container_image_evidence import ContainerImageEvidence\nfrom .kubernetes_pod_evidence import KubernetesPodEvidence\nfrom .alert_evidence import AlertEvidence\nfrom... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ContainerEvidence()
<|end_body_0|>
<|body_start_1|>
from .alert_evidence import AlertEvidence
from .container_image_evidence import ContainerImageEvidence
from .kubernetes_pod_ev... | ContainerEvidence | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContainerEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ContainerEvidence:
"""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... | stack_v2_sparse_classes_36k_train_020956 | 3,852 | 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: ContainerEvidence",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_v... | 3 | null | Implement the Python class `ContainerEvidence` described below.
Class description:
Implement the ContainerEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ContainerEvidence: Creates a new instance of the appropriate class based on discrim... | Implement the Python class `ContainerEvidence` described below.
Class description:
Implement the ContainerEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ContainerEvidence: Creates a new instance of the appropriate class based on discrim... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ContainerEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ContainerEvidence:
"""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... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContainerEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ContainerEvidence:
"""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: Cont... | the_stack_v2_python_sparse | msgraph/generated/models/security/container_evidence.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
1fc0ee3f712f489f85e4c228e12e4d9da14da7a6 | [
"home = os.path.expanduser('~')\nif name == 'desktop':\n return os.path.join(home, 'Desktop')\nelif name == 'documents':\n return os.path.join(home, 'Documents')\nelif name == 'downloads':\n return os.path.join(home, 'Downloads')\nelif name == 'applications' or name == 'programs':\n return os.path.join(... | <|body_start_0|>
home = os.path.expanduser('~')
if name == 'desktop':
return os.path.join(home, 'Desktop')
elif name == 'documents':
return os.path.join(home, 'Documents')
elif name == 'downloads':
return os.path.join(home, 'Downloads')
elif na... | Exports | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exports:
def get_known_path(name: str, param: str='', approot=None):
"""特殊なフォルダ・ファイルの名前からパスを得る。"""
<|body_0|>
def start_file(path, operation=None):
"""デフォルトの方法でパスを開く。"""
<|body_1|>
def has_hidden_attribute(path):
"""隠し属性がついているファイルか。"""
<|... | stack_v2_sparse_classes_36k_train_020957 | 2,665 | permissive | [
{
"docstring": "特殊なフォルダ・ファイルの名前からパスを得る。",
"name": "get_known_path",
"signature": "def get_known_path(name: str, param: str='', approot=None)"
},
{
"docstring": "デフォルトの方法でパスを開く。",
"name": "start_file",
"signature": "def start_file(path, operation=None)"
},
{
"docstring": "隠し属性がついて... | 3 | stack_v2_sparse_classes_30k_train_018294 | Implement the Python class `Exports` described below.
Class description:
Implement the Exports class.
Method signatures and docstrings:
- def get_known_path(name: str, param: str='', approot=None): 特殊なフォルダ・ファイルの名前からパスを得る。
- def start_file(path, operation=None): デフォルトの方法でパスを開く。
- def has_hidden_attribute(path): 隠し属性がつ... | Implement the Python class `Exports` described below.
Class description:
Implement the Exports class.
Method signatures and docstrings:
- def get_known_path(name: str, param: str='', approot=None): 特殊なフォルダ・ファイルの名前からパスを得る。
- def start_file(path, operation=None): デフォルトの方法でパスを開く。
- def has_hidden_attribute(path): 隠し属性がつ... | f3d89b4449b04e5e587915f3b3623dfbe5ba01d8 | <|skeleton|>
class Exports:
def get_known_path(name: str, param: str='', approot=None):
"""特殊なフォルダ・ファイルの名前からパスを得る。"""
<|body_0|>
def start_file(path, operation=None):
"""デフォルトの方法でパスを開く。"""
<|body_1|>
def has_hidden_attribute(path):
"""隠し属性がついているファイルか。"""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Exports:
def get_known_path(name: str, param: str='', approot=None):
"""特殊なフォルダ・ファイルの名前からパスを得る。"""
home = os.path.expanduser('~')
if name == 'desktop':
return os.path.join(home, 'Desktop')
elif name == 'documents':
return os.path.join(home, 'Documents')
... | the_stack_v2_python_sparse | machaon/platforms/osx/path.py | betasewer/machaon | train | 4 | |
58de4c2654c6ab3c86707f74eb019eed82c0dfae | [
"g = [[] for _ in range(n)]\nfor a, b in edges:\n g[a].append(b)\n g[b].append(a)\nret = [0] * n\n\ndef dfs(a, p):\n counter = defaultdict(int)\n counter[labels[a]] += 1\n for b in g[a]:\n if b == p:\n continue\n for l, c in dfs(b, a).items():\n counter[l] += c\n ... | <|body_start_0|>
g = [[] for _ in range(n)]
for a, b in edges:
g[a].append(b)
g[b].append(a)
ret = [0] * n
def dfs(a, p):
counter = defaultdict(int)
counter[labels[a]] += 1
for b in g[a]:
if b == p:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> List[int]:
"""Mar 05, 2023 14:37"""
<|body_0|>
def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> List[int]:
"""Mar 05, 2023 14:39 Use one counter"""
<|body... | stack_v2_sparse_classes_36k_train_020958 | 3,712 | no_license | [
{
"docstring": "Mar 05, 2023 14:37",
"name": "countSubTrees",
"signature": "def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> List[int]"
},
{
"docstring": "Mar 05, 2023 14:39 Use one counter",
"name": "countSubTrees",
"signature": "def countSubTrees(self, n: int, ed... | 2 | stack_v2_sparse_classes_30k_train_003019 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> List[int]: Mar 05, 2023 14:37
- def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> Li... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> List[int]: Mar 05, 2023 14:37
- def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> Li... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> List[int]:
"""Mar 05, 2023 14:37"""
<|body_0|>
def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> List[int]:
"""Mar 05, 2023 14:39 Use one counter"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countSubTrees(self, n: int, edges: List[List[int]], labels: str) -> List[int]:
"""Mar 05, 2023 14:37"""
g = [[] for _ in range(n)]
for a, b in edges:
g[a].append(b)
g[b].append(a)
ret = [0] * n
def dfs(a, p):
counter = ... | the_stack_v2_python_sparse | leetcode/solved/1643_Number_of_Nodes_in_the_Sub-Tree_With_the_Same_Label/solution.py | sungminoh/algorithms | train | 0 | |
e091e0ffff07df32ce5f80bf0f0bf0b12bca1c8d | [
"TreatmentInfoView.validate_treatment_info_request(id_patient, id_treatment_cycle, id_treatment)\ntreatment_info = TreatmentService.treatment_info(id_treatment)\nreturn JsonResponse(treatment_info)",
"Utils.validate_uuid(id_patient)\nUtils.validate_uuid(id_treatment_cycle)\nUtils.validate_uuid(id_treatment)"
] | <|body_start_0|>
TreatmentInfoView.validate_treatment_info_request(id_patient, id_treatment_cycle, id_treatment)
treatment_info = TreatmentService.treatment_info(id_treatment)
return JsonResponse(treatment_info)
<|end_body_0|>
<|body_start_1|>
Utils.validate_uuid(id_patient)
Uti... | All endpoints related to treatment info actions | TreatmentInfoView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TreatmentInfoView:
"""All endpoints related to treatment info actions"""
def get(request, id_patient, id_treatment_cycle, id_treatment):
"""Action when calling the endpoint with GET"""
<|body_0|>
def validate_treatment_info_request(id_patient, id_treatment_cycle, id_trea... | stack_v2_sparse_classes_36k_train_020959 | 3,356 | no_license | [
{
"docstring": "Action when calling the endpoint with GET",
"name": "get",
"signature": "def get(request, id_patient, id_treatment_cycle, id_treatment)"
},
{
"docstring": "Validates the treatment information received in the request body :param id_patient: Id of the patient received :param id_tre... | 2 | stack_v2_sparse_classes_30k_train_018523 | Implement the Python class `TreatmentInfoView` described below.
Class description:
All endpoints related to treatment info actions
Method signatures and docstrings:
- def get(request, id_patient, id_treatment_cycle, id_treatment): Action when calling the endpoint with GET
- def validate_treatment_info_request(id_pati... | Implement the Python class `TreatmentInfoView` described below.
Class description:
All endpoints related to treatment info actions
Method signatures and docstrings:
- def get(request, id_patient, id_treatment_cycle, id_treatment): Action when calling the endpoint with GET
- def validate_treatment_info_request(id_pati... | 941e8b2870f8724db3d5103dda5157fd597cfcc7 | <|skeleton|>
class TreatmentInfoView:
"""All endpoints related to treatment info actions"""
def get(request, id_patient, id_treatment_cycle, id_treatment):
"""Action when calling the endpoint with GET"""
<|body_0|>
def validate_treatment_info_request(id_patient, id_treatment_cycle, id_trea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TreatmentInfoView:
"""All endpoints related to treatment info actions"""
def get(request, id_patient, id_treatment_cycle, id_treatment):
"""Action when calling the endpoint with GET"""
TreatmentInfoView.validate_treatment_info_request(id_patient, id_treatment_cycle, id_treatment)
... | the_stack_v2_python_sparse | backend/martin_helder/views/treatment_info_view.py | JoaoAlvaroFerreira/FEUP-LGP | train | 1 |
4e891eeb643036e61a3a120984403f3a7c9e7a96 | [
"self.generator = generator\nself.commons = pywikibot.Site('commons', 'commons')\nself.repo = pywikibot.Site().data_repository()",
"for itempage in self.generator:\n pywikibot.output(u'Working on %s' % (itempage.title(),))\n if not itempage.exists():\n pywikibot.output(u'Item does not exist, skipping... | <|body_start_0|>
self.generator = generator
self.commons = pywikibot.Site('commons', 'commons')
self.repo = pywikibot.Site().data_repository()
<|end_body_0|>
<|body_start_1|>
for itempage in self.generator:
pywikibot.output(u'Working on %s' % (itempage.title(),))
... | A bot to Commons Category sitelinks | MissingCommonsSitelinkBot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MissingCommonsSitelinkBot:
"""A bot to Commons Category sitelinks"""
def __init__(self, generator):
"""Arguments: * generator - A generator that yields ItemPage objects."""
<|body_0|>
def run(self):
"""Starts the robot."""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_020960 | 4,707 | no_license | [
{
"docstring": "Arguments: * generator - A generator that yields ItemPage objects.",
"name": "__init__",
"signature": "def __init__(self, generator)"
},
{
"docstring": "Starts the robot.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002475 | Implement the Python class `MissingCommonsSitelinkBot` described below.
Class description:
A bot to Commons Category sitelinks
Method signatures and docstrings:
- def __init__(self, generator): Arguments: * generator - A generator that yields ItemPage objects.
- def run(self): Starts the robot. | Implement the Python class `MissingCommonsSitelinkBot` described below.
Class description:
A bot to Commons Category sitelinks
Method signatures and docstrings:
- def __init__(self, generator): Arguments: * generator - A generator that yields ItemPage objects.
- def run(self): Starts the robot.
<|skeleton|>
class Mi... | 99a96e49cfe6b2d3151da7ad5469792d80171be3 | <|skeleton|>
class MissingCommonsSitelinkBot:
"""A bot to Commons Category sitelinks"""
def __init__(self, generator):
"""Arguments: * generator - A generator that yields ItemPage objects."""
<|body_0|>
def run(self):
"""Starts the robot."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MissingCommonsSitelinkBot:
"""A bot to Commons Category sitelinks"""
def __init__(self, generator):
"""Arguments: * generator - A generator that yields ItemPage objects."""
self.generator = generator
self.commons = pywikibot.Site('commons', 'commons')
self.repo = pywikibot... | the_stack_v2_python_sparse | bot/wikidata/commons_category_missing_sitelink.py | multichill/toollabs | train | 18 |
b31f4e139658a1ac6b3fbf3ff20beb012c45f11e | [
"super().__init__(config_entry, driver, info)\nself._target_value = self.get_zwave_value(TARGET_VALUE_PROPERTY)\nassert self.info.platform_data_template\nself._lookup_map = cast(dict[int, str], self.info.platform_data_template.static_data)\nself._attr_options = list(self._lookup_map.values())",
"if self.info.prim... | <|body_start_0|>
super().__init__(config_entry, driver, info)
self._target_value = self.get_zwave_value(TARGET_VALUE_PROPERTY)
assert self.info.platform_data_template
self._lookup_map = cast(dict[int, str], self.info.platform_data_template.static_data)
self._attr_options = list(s... | Representation of a Z-Wave Multilevel Switch CC select entity. | ZwaveMultilevelSwitchSelectEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZwaveMultilevelSwitchSelectEntity:
"""Representation of a Z-Wave Multilevel Switch CC select entity."""
def __init__(self, config_entry: ConfigEntry, driver: Driver, info: ZwaveDiscoveryInfo) -> None:
"""Initialize a ZwaveSelectEntity entity."""
<|body_0|>
def current_op... | stack_v2_sparse_classes_36k_train_020961 | 7,555 | permissive | [
{
"docstring": "Initialize a ZwaveSelectEntity entity.",
"name": "__init__",
"signature": "def __init__(self, config_entry: ConfigEntry, driver: Driver, info: ZwaveDiscoveryInfo) -> None"
},
{
"docstring": "Return the selected entity option to represent the entity state.",
"name": "current_o... | 3 | stack_v2_sparse_classes_30k_train_002199 | Implement the Python class `ZwaveMultilevelSwitchSelectEntity` described below.
Class description:
Representation of a Z-Wave Multilevel Switch CC select entity.
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry, driver: Driver, info: ZwaveDiscoveryInfo) -> None: Initialize a ZwaveSelec... | Implement the Python class `ZwaveMultilevelSwitchSelectEntity` described below.
Class description:
Representation of a Z-Wave Multilevel Switch CC select entity.
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry, driver: Driver, info: ZwaveDiscoveryInfo) -> None: Initialize a ZwaveSelec... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ZwaveMultilevelSwitchSelectEntity:
"""Representation of a Z-Wave Multilevel Switch CC select entity."""
def __init__(self, config_entry: ConfigEntry, driver: Driver, info: ZwaveDiscoveryInfo) -> None:
"""Initialize a ZwaveSelectEntity entity."""
<|body_0|>
def current_op... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZwaveMultilevelSwitchSelectEntity:
"""Representation of a Z-Wave Multilevel Switch CC select entity."""
def __init__(self, config_entry: ConfigEntry, driver: Driver, info: ZwaveDiscoveryInfo) -> None:
"""Initialize a ZwaveSelectEntity entity."""
super().__init__(config_entry, driver, info... | the_stack_v2_python_sparse | homeassistant/components/zwave_js/select.py | home-assistant/core | train | 35,501 |
123e088cafc8e624e4ddbb680a0f4ee775aad23e | [
"super().__init__()\nself.nf = nf\nw = torch.empty(nx, nf)\nnn.init.normal_(w, std=0.02)\nself.weight = nn.Parameter(w)\nself.bias = nn.Parameter(torch.zeros(nf))",
"size_out = x.size()[:-1] + (self.nf,)\nx = torch.addmm(self.bias, x.view(-1, x.size(-1)), self.weight)\nx = x.view(*size_out)\nreturn x"
] | <|body_start_0|>
super().__init__()
self.nf = nf
w = torch.empty(nx, nf)
nn.init.normal_(w, std=0.02)
self.weight = nn.Parameter(w)
self.bias = nn.Parameter(torch.zeros(nf))
<|end_body_0|>
<|body_start_1|>
size_out = x.size()[:-1] + (self.nf,)
x = torch.a... | 1D-convolutional layer (eqv to FCN) as defined by Radford et al. for OpenAI GPT (and also used in GPT-2). Basically works like a linear layer but the weights are transposed. Note: Code adopted from: https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_utils.py Args: nf (int): The number of ... | Conv1D | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Conv1D:
"""1D-convolutional layer (eqv to FCN) as defined by Radford et al. for OpenAI GPT (and also used in GPT-2). Basically works like a linear layer but the weights are transposed. Note: Code adopted from: https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_utils... | stack_v2_sparse_classes_36k_train_020962 | 2,885 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, nf: int, nx: int) -> None"
},
{
"docstring": "Forward pass Args: x (Tensor): [..., nx] input features Returns: Tensor: [..., nf] output features",
"name": "forward",
"signature": "def forward(self, x: Tens... | 2 | stack_v2_sparse_classes_30k_train_020787 | Implement the Python class `Conv1D` described below.
Class description:
1D-convolutional layer (eqv to FCN) as defined by Radford et al. for OpenAI GPT (and also used in GPT-2). Basically works like a linear layer but the weights are transposed. Note: Code adopted from: https://github.com/huggingface/transformers/blob... | Implement the Python class `Conv1D` described below.
Class description:
1D-convolutional layer (eqv to FCN) as defined by Radford et al. for OpenAI GPT (and also used in GPT-2). Basically works like a linear layer but the weights are transposed. Note: Code adopted from: https://github.com/huggingface/transformers/blob... | eb28d09957641cc594b3e5acf4ace2e4dc193584 | <|skeleton|>
class Conv1D:
"""1D-convolutional layer (eqv to FCN) as defined by Radford et al. for OpenAI GPT (and also used in GPT-2). Basically works like a linear layer but the weights are transposed. Note: Code adopted from: https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_utils... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Conv1D:
"""1D-convolutional layer (eqv to FCN) as defined by Radford et al. for OpenAI GPT (and also used in GPT-2). Basically works like a linear layer but the weights are transposed. Note: Code adopted from: https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_utils.py Args: nf ... | the_stack_v2_python_sparse | trphysx/transformer/utils.py | yus-nas/transformer-physx | train | 0 |
c6ca49cbd3f50b8bf68872607230bf358dc8c1ad | [
"inorderMap = {}\nfor idx, value in enumerate(inorder):\n inorderMap[value] = idx\nreturn self.buildTreeHelper(inorder, postorder, inorderMap)",
"if not inorder or not postorder:\n return None\nroot = TreeNode(postorder.pop())\nrootIdxFromInorder = inorder.index(root.val)\nroot.right = self.buildTreeHelper(... | <|body_start_0|>
inorderMap = {}
for idx, value in enumerate(inorder):
inorderMap[value] = idx
return self.buildTreeHelper(inorder, postorder, inorderMap)
<|end_body_0|>
<|body_start_1|>
if not inorder or not postorder:
return None
root = TreeNode(postord... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def buildTree(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTreeHelper(self, inorder, postorder, inorderMap):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode... | stack_v2_sparse_classes_36k_train_020963 | 1,895 | permissive | [
{
"docstring": ":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode",
"name": "buildTree",
"signature": "def buildTree(self, inorder, postorder)"
},
{
"docstring": ":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode",
"name": "buildTreeHelper",
"signatu... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, inorder, postorder): :type inorder: List[int] :type postorder: List[int] :rtype: TreeNode
- def buildTreeHelper(self, inorder, postorder, inorderMap): :type i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, inorder, postorder): :type inorder: List[int] :type postorder: List[int] :rtype: TreeNode
- def buildTreeHelper(self, inorder, postorder, inorderMap): :type i... | 20ae1a048eddbc9a32c819cf61258e2b57572f05 | <|skeleton|>
class Solution:
def buildTree(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTreeHelper(self, inorder, postorder, inorderMap):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def buildTree(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
inorderMap = {}
for idx, value in enumerate(inorder):
inorderMap[value] = idx
return self.buildTreeHelper(inorder, postorder, inorderMap)
... | the_stack_v2_python_sparse | leetcode.com/python/106_Construct_Binary_Tree_from_Inorder_and_Postorder_Traversal.py | partho-maple/coding-interview-gym | train | 862 | |
7f9be951db40216dbef352b4d1c8c1487bfcec29 | [
"self.threshold = threshold\nself.sampling_method = sampling_method\nself.eps = eps\nself.delta = delta\nself._store_every = store_every\nself.func_of_freq = func_of_freq\nself._inclusion_prob = [0.0]\nself.elements = set()",
"if not isinstance(sample, ThresholdSample):\n raise TypeError('Tried to create a pri... | <|body_start_0|>
self.threshold = threshold
self.sampling_method = sampling_method
self.eps = eps
self.delta = delta
self._store_every = store_every
self.func_of_freq = func_of_freq
self._inclusion_prob = [0.0]
self.elements = set()
<|end_body_0|>
<|body_... | Threshold sampling with differential privacy (returns sampled keys only). This class implements threshold sampling, and then performs subsampling to satisfy the differential privacy constraints. The private sample only includes keys (and no information about their frequencies). The sketch only supports aggregated data:... | PrivateThresholdSampleKeysOnly | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrivateThresholdSampleKeysOnly:
"""Threshold sampling with differential privacy (returns sampled keys only). This class implements threshold sampling, and then performs subsampling to satisfy the differential privacy constraints. The private sample only includes keys (and no information about the... | stack_v2_sparse_classes_36k_train_020964 | 32,453 | permissive | [
{
"docstring": "Initializes an empty sample. Args: threshold: The sampling threshold eps: The differential privacy parameter epsilon delta: The differential privacy parameter delta sampling_method: A class that provides functions to compute the score and inclusion probability according to the underlying non-pri... | 4 | stack_v2_sparse_classes_30k_train_018835 | Implement the Python class `PrivateThresholdSampleKeysOnly` described below.
Class description:
Threshold sampling with differential privacy (returns sampled keys only). This class implements threshold sampling, and then performs subsampling to satisfy the differential privacy constraints. The private sample only incl... | Implement the Python class `PrivateThresholdSampleKeysOnly` described below.
Class description:
Threshold sampling with differential privacy (returns sampled keys only). This class implements threshold sampling, and then performs subsampling to satisfy the differential privacy constraints. The private sample only incl... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class PrivateThresholdSampleKeysOnly:
"""Threshold sampling with differential privacy (returns sampled keys only). This class implements threshold sampling, and then performs subsampling to satisfy the differential privacy constraints. The private sample only includes keys (and no information about the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrivateThresholdSampleKeysOnly:
"""Threshold sampling with differential privacy (returns sampled keys only). This class implements threshold sampling, and then performs subsampling to satisfy the differential privacy constraints. The private sample only includes keys (and no information about their frequencie... | the_stack_v2_python_sparse | private_sampling/private_sampling.py | Jimmy-INL/google-research | train | 1 |
ce0e00663ad3f0a622b5112d516c0316df177f2f | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn PrincipalResourceMembershipsScope()",
"from .access_review_scope import AccessReviewScope\nfrom .access_review_scope import AccessReviewScope\nfields: Dict[str, Callable[[Any], None]] = {'principalScopes': lambda n: setattr(self, 'prin... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return PrincipalResourceMembershipsScope()
<|end_body_0|>
<|body_start_1|>
from .access_review_scope import AccessReviewScope
from .access_review_scope import AccessReviewScope
fields: ... | PrincipalResourceMembershipsScope | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrincipalResourceMembershipsScope:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrincipalResourceMembershipsScope:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discrimin... | stack_v2_sparse_classes_36k_train_020965 | 2,713 | 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: PrincipalResourceMembershipsScope",
"name": "create_from_discriminator_value",
"signature": "def create_from... | 3 | stack_v2_sparse_classes_30k_train_009261 | Implement the Python class `PrincipalResourceMembershipsScope` described below.
Class description:
Implement the PrincipalResourceMembershipsScope class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrincipalResourceMembershipsScope: Creates a new in... | Implement the Python class `PrincipalResourceMembershipsScope` described below.
Class description:
Implement the PrincipalResourceMembershipsScope class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrincipalResourceMembershipsScope: Creates a new in... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class PrincipalResourceMembershipsScope:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrincipalResourceMembershipsScope:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discrimin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrincipalResourceMembershipsScope:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrincipalResourceMembershipsScope:
"""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... | the_stack_v2_python_sparse | msgraph/generated/models/principal_resource_memberships_scope.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
cf58fcdc9b8992c75065587a53a9f5a42e6610bf | [
"well = WellService.get_by_well_id(well_id)\nif well is None:\n return self.format_failure(404, 'Well Not Found')\nreturn self.format_success(200, {'well': well})",
"well = WellService.get_by_well_id(well_id)\nif well is None:\n self.format_failure(404, 'Well Not Found')\nreturn self.format_success(200, {'w... | <|body_start_0|>
well = WellService.get_by_well_id(well_id)
if well is None:
return self.format_failure(404, 'Well Not Found')
return self.format_success(200, {'well': well})
<|end_body_0|>
<|body_start_1|>
well = WellService.get_by_well_id(well_id)
if well is None:
... | API Resource for /wells/<well_id>/hygiene | WellHygiene | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WellHygiene:
"""API Resource for /wells/<well_id>/hygiene"""
def get(self, well_id, **_):
"""GET /wells/<well_id>/hygiene"""
<|body_0|>
def post(self, well_id: str):
"""POST /wells/<well_id>/hygiene"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_020966 | 1,884 | no_license | [
{
"docstring": "GET /wells/<well_id>/hygiene",
"name": "get",
"signature": "def get(self, well_id, **_)"
},
{
"docstring": "POST /wells/<well_id>/hygiene",
"name": "post",
"signature": "def post(self, well_id: str)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016122 | Implement the Python class `WellHygiene` described below.
Class description:
API Resource for /wells/<well_id>/hygiene
Method signatures and docstrings:
- def get(self, well_id, **_): GET /wells/<well_id>/hygiene
- def post(self, well_id: str): POST /wells/<well_id>/hygiene | Implement the Python class `WellHygiene` described below.
Class description:
API Resource for /wells/<well_id>/hygiene
Method signatures and docstrings:
- def get(self, well_id, **_): GET /wells/<well_id>/hygiene
- def post(self, well_id: str): POST /wells/<well_id>/hygiene
<|skeleton|>
class WellHygiene:
"""API... | 8ab4034413262ff2271740d73df72b3d83ce5918 | <|skeleton|>
class WellHygiene:
"""API Resource for /wells/<well_id>/hygiene"""
def get(self, well_id, **_):
"""GET /wells/<well_id>/hygiene"""
<|body_0|>
def post(self, well_id: str):
"""POST /wells/<well_id>/hygiene"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WellHygiene:
"""API Resource for /wells/<well_id>/hygiene"""
def get(self, well_id, **_):
"""GET /wells/<well_id>/hygiene"""
well = WellService.get_by_well_id(well_id)
if well is None:
return self.format_failure(404, 'Well Not Found')
return self.format_success... | the_stack_v2_python_sparse | app/main/controllers/wells/well_hygiene_controller.py | Malawi-Water-Wells-project/malawi-auth-api | train | 1 |
7f21dcf95b011292844fa197982adee16c80fead | [
"super().__init__()\nt = int(abs(math.log(in_channels, 2) + beta) / gamma)\nkernel_size = max(t if t % 2 else t + 1, 3)\npadding = (kernel_size - 1) // 2\nself.conv = nn.Conv1d(1, 1, kernel_size=kernel_size, padding=padding, bias=False)\nself.gate = Activation(gate_activation)",
"B = x.shape[0]\ny = x.mean((2, 3)... | <|body_start_0|>
super().__init__()
t = int(abs(math.log(in_channels, 2) + beta) / gamma)
kernel_size = max(t if t % 2 else t + 1, 3)
padding = (kernel_size - 1) // 2
self.conv = nn.Conv1d(1, 1, kernel_size=kernel_size, padding=padding, bias=False)
self.gate = Activation(... | ECA | [
"MIT",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ECA:
def __init__(self, in_channels: int, beta: int=1, gamma: int=2, gate_activation: str='sigmoid', **kwargs) -> None:
"""Efficient Channel Attention (ECA). https://arxiv.org/abs/1910.03151 Parameters ---------- in_channels : int Number of input channels. beta : int, default=1 Coefficie... | stack_v2_sparse_classes_36k_train_020967 | 11,576 | permissive | [
{
"docstring": "Efficient Channel Attention (ECA). https://arxiv.org/abs/1910.03151 Parameters ---------- in_channels : int Number of input channels. beta : int, default=1 Coefficient used to compute the kernel size adaptively. gamma : int, default=2 Coefficient used to compute the kernel size adaptively. gate_... | 2 | null | Implement the Python class `ECA` described below.
Class description:
Implement the ECA class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, beta: int=1, gamma: int=2, gate_activation: str='sigmoid', **kwargs) -> None: Efficient Channel Attention (ECA). https://arxiv.org/abs/1910.03151 Param... | Implement the Python class `ECA` described below.
Class description:
Implement the ECA class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, beta: int=1, gamma: int=2, gate_activation: str='sigmoid', **kwargs) -> None: Efficient Channel Attention (ECA). https://arxiv.org/abs/1910.03151 Param... | 7f79405012eb934b419bbdba8de23f35e840ca85 | <|skeleton|>
class ECA:
def __init__(self, in_channels: int, beta: int=1, gamma: int=2, gate_activation: str='sigmoid', **kwargs) -> None:
"""Efficient Channel Attention (ECA). https://arxiv.org/abs/1910.03151 Parameters ---------- in_channels : int Number of input channels. beta : int, default=1 Coefficie... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ECA:
def __init__(self, in_channels: int, beta: int=1, gamma: int=2, gate_activation: str='sigmoid', **kwargs) -> None:
"""Efficient Channel Attention (ECA). https://arxiv.org/abs/1910.03151 Parameters ---------- in_channels : int Number of input channels. beta : int, default=1 Coefficient used to com... | the_stack_v2_python_sparse | cellseg_models_pytorch/modules/attention_modules.py | okunator/cellseg_models.pytorch | train | 43 | |
8301df83c054ad3e6341b3c5da1b8d9c9f5c7868 | [
"self.drone_connection.disconnect()\nif self.groundcam is not None:\n self.groundcam._close()",
"if self.use_wifi:\n return False\ncommand_tuple, enum_tuple = self.command_parser.get_command_tuple_with_enum('minidrone', 'UsbAccessory', 'GunControl', 'FIRE')\nreturn self.drone_connection.send_enum_command_pa... | <|body_start_0|>
self.drone_connection.disconnect()
if self.groundcam is not None:
self.groundcam._close()
<|end_body_0|>
<|body_start_1|>
if self.use_wifi:
return False
command_tuple, enum_tuple = self.command_parser.get_command_tuple_with_enum('minidrone', 'Usb... | Mambo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mambo:
def disconnect(self):
"""Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void"""
<|body_0|>
def fire_gun(self):
"""Fire the gun (assumes it is attached) - note not supposed under wifi since the camera... | stack_v2_sparse_classes_36k_train_020968 | 31,062 | permissive | [
{
"docstring": "Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void",
"name": "disconnect",
"signature": "def disconnect(self)"
},
{
"docstring": "Fire the gun (assumes it is attached) - note not supposed under wifi since the camera ta... | 2 | stack_v2_sparse_classes_30k_train_010717 | Implement the Python class `Mambo` described below.
Class description:
Implement the Mambo class.
Method signatures and docstrings:
- def disconnect(self): Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void
- def fire_gun(self): Fire the gun (assumes it is... | Implement the Python class `Mambo` described below.
Class description:
Implement the Mambo class.
Method signatures and docstrings:
- def disconnect(self): Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void
- def fire_gun(self): Fire the gun (assumes it is... | 99ab19f7896bc30cf059244962a7da318d4672bf | <|skeleton|>
class Mambo:
def disconnect(self):
"""Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void"""
<|body_0|>
def fire_gun(self):
"""Fire the gun (assumes it is attached) - note not supposed under wifi since the camera... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Mambo:
def disconnect(self):
"""Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void"""
self.drone_connection.disconnect()
if self.groundcam is not None:
self.groundcam._close()
def fire_gun(self):
"""... | the_stack_v2_python_sparse | Madrid/July2022/ProfessorX-BCI/src/drone/vendor/Minidrone.py | SaturdaysAI/Projects | train | 35 | |
621e71db710ee9f6e39d0e640f56cf368ecde545 | [
"Parametre.__init__(self, 'liste', 'list')\nself.groupe = 'administrateur'\nself.aide_courte = 'liste les questeurs existants'\nself.aide_longue = 'Cette commande liste les questeurs existants.'",
"questeurs = list(importeur.commerce.questeurs.values())\nquesteurs = [q for q in questeurs if q.salle]\nquesteurs = ... | <|body_start_0|>
Parametre.__init__(self, 'liste', 'list')
self.groupe = 'administrateur'
self.aide_courte = 'liste les questeurs existants'
self.aide_longue = 'Cette commande liste les questeurs existants.'
<|end_body_0|>
<|body_start_1|>
questeurs = list(importeur.commerce.que... | Commande 'questeur liste'. | PrmListe | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmListe:
"""Commande 'questeur liste'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Parametre.__... | stack_v2_sparse_classes_36k_train_020969 | 2,892 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | null | Implement the Python class `PrmListe` described below.
Class description:
Commande 'questeur liste'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre | Implement the Python class `PrmListe` described below.
Class description:
Commande 'questeur liste'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre
<|skeleton|>
class PrmListe:
"""Commande 'questeur l... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmListe:
"""Commande 'questeur liste'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrmListe:
"""Commande 'questeur liste'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'liste', 'list')
self.groupe = 'administrateur'
self.aide_courte = 'liste les questeurs existants'
self.aide_longue = 'Cette commande liste les q... | the_stack_v2_python_sparse | src/primaires/commerce/commandes/questeur/liste.py | vincent-lg/tsunami | train | 5 |
f1b274c77f585ce8990e5626afbd35304c4bc976 | [
"tasks_file = tfds.core.tfds_path(_TASKS_FNAME)\ntasks = tasks_file.read_text().splitlines()\nreturn self.dataset_info_from_configs(features=tfds.features.FeaturesDict({'num_nodes': tfds.features.Tensor(shape=(None,), dtype=np.int64), 'node_feat': tfds.features.Tensor(shape=(None, 9), dtype=np.float32), 'num_edges'... | <|body_start_0|>
tasks_file = tfds.core.tfds_path(_TASKS_FNAME)
tasks = tasks_file.read_text().splitlines()
return self.dataset_info_from_configs(features=tfds.features.FeaturesDict({'num_nodes': tfds.features.Tensor(shape=(None,), dtype=np.int64), 'node_feat': tfds.features.Tensor(shape=(None, ... | DatasetBuilder for ogbg_molpcba dataset. | Builder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Builder:
"""DatasetBuilder for ogbg_molpcba dataset."""
def _info(self) -> tfds.core.DatasetInfo:
"""Returns the dataset metadata."""
<|body_0|>
def _split_generators(self, dl_manager: tfds.download.DownloadManager):
"""Returns SplitGenerators."""
<|body_... | stack_v2_sparse_classes_36k_train_020970 | 6,334 | permissive | [
{
"docstring": "Returns the dataset metadata.",
"name": "_info",
"signature": "def _info(self) -> tfds.core.DatasetInfo"
},
{
"docstring": "Returns SplitGenerators.",
"name": "_split_generators",
"signature": "def _split_generators(self, dl_manager: tfds.download.DownloadManager)"
},
... | 3 | null | Implement the Python class `Builder` described below.
Class description:
DatasetBuilder for ogbg_molpcba dataset.
Method signatures and docstrings:
- def _info(self) -> tfds.core.DatasetInfo: Returns the dataset metadata.
- def _split_generators(self, dl_manager: tfds.download.DownloadManager): Returns SplitGenerator... | Implement the Python class `Builder` described below.
Class description:
DatasetBuilder for ogbg_molpcba dataset.
Method signatures and docstrings:
- def _info(self) -> tfds.core.DatasetInfo: Returns the dataset metadata.
- def _split_generators(self, dl_manager: tfds.download.DownloadManager): Returns SplitGenerator... | 41ae3cf1439711ed2f50f99caa0e6702082e6d37 | <|skeleton|>
class Builder:
"""DatasetBuilder for ogbg_molpcba dataset."""
def _info(self) -> tfds.core.DatasetInfo:
"""Returns the dataset metadata."""
<|body_0|>
def _split_generators(self, dl_manager: tfds.download.DownloadManager):
"""Returns SplitGenerators."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Builder:
"""DatasetBuilder for ogbg_molpcba dataset."""
def _info(self) -> tfds.core.DatasetInfo:
"""Returns the dataset metadata."""
tasks_file = tfds.core.tfds_path(_TASKS_FNAME)
tasks = tasks_file.read_text().splitlines()
return self.dataset_info_from_configs(features=t... | the_stack_v2_python_sparse | tensorflow_datasets/datasets/ogbg_molpcba/ogbg_molpcba_dataset_builder.py | tensorflow/datasets | train | 4,224 |
7e726f2026339d9021aa190e9cba07901a977eb5 | [
"startBin = start >> Binner.binFirstShift\nendBin = end - 1 >> Binner.binFirstShift\nfor binOff in offsets:\n if startBin == endBin:\n return baseOffset + binOff + startBin\n startBin >>= Binner.binNextShift\n endBin >>= Binner.binNextShift\nraise Exception(\"can't compute bin: start %d, end %d out ... | <|body_start_0|>
startBin = start >> Binner.binFirstShift
endBin = end - 1 >> Binner.binFirstShift
for binOff in offsets:
if startBin == endBin:
return baseOffset + binOff + startBin
startBin >>= Binner.binNextShift
endBin >>= Binner.binNextShi... | functions to translate ranges to bin numbers | Binner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Binner:
"""functions to translate ranges to bin numbers"""
def __calcBinForOffsets(start, end, baseOffset, offsets):
"""get the bin for a range"""
<|body_0|>
def calcBin(start, end):
"""get the bin for a range"""
<|body_1|>
def __getOverlappingBinsFo... | stack_v2_sparse_classes_36k_train_020971 | 10,668 | permissive | [
{
"docstring": "get the bin for a range",
"name": "__calcBinForOffsets",
"signature": "def __calcBinForOffsets(start, end, baseOffset, offsets)"
},
{
"docstring": "get the bin for a range",
"name": "calcBin",
"signature": "def calcBin(start, end)"
},
{
"docstring": "generate bins... | 5 | stack_v2_sparse_classes_30k_train_014326 | Implement the Python class `Binner` described below.
Class description:
functions to translate ranges to bin numbers
Method signatures and docstrings:
- def __calcBinForOffsets(start, end, baseOffset, offsets): get the bin for a range
- def calcBin(start, end): get the bin for a range
- def __getOverlappingBinsForOff... | Implement the Python class `Binner` described below.
Class description:
functions to translate ranges to bin numbers
Method signatures and docstrings:
- def __calcBinForOffsets(start, end, baseOffset, offsets): get the bin for a range
- def calcBin(start, end): get the bin for a range
- def __getOverlappingBinsForOff... | 5889b03380d92455b909c1ca0535fd590abbbe54 | <|skeleton|>
class Binner:
"""functions to translate ranges to bin numbers"""
def __calcBinForOffsets(start, end, baseOffset, offsets):
"""get the bin for a range"""
<|body_0|>
def calcBin(start, end):
"""get the bin for a range"""
<|body_1|>
def __getOverlappingBinsFo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Binner:
"""functions to translate ranges to bin numbers"""
def __calcBinForOffsets(start, end, baseOffset, offsets):
"""get the bin for a range"""
startBin = start >> Binner.binFirstShift
endBin = end - 1 >> Binner.binFirstShift
for binOff in offsets:
if startB... | the_stack_v2_python_sparse | tools/rangeFinder.py | ComparativeGenomicsToolkit/Comparative-Annotation-Toolkit | train | 144 |
7c459991652686190842ef83ace793a4e4560cd2 | [
"self.nwalkers = nwalkers\nself.ndim = ndim\nself.nelec = nelec\nself.init_domain = init\nself.pos = None\nself.status = None\nself.cuda = cuda\nif cuda:\n self.device = torch.device('cuda')\nelse:\n self.device = torch.device('cpu')",
"if self.cuda:\n self.device = torch.device('cuda')\nif pos is not No... | <|body_start_0|>
self.nwalkers = nwalkers
self.ndim = ndim
self.nelec = nelec
self.init_domain = init
self.pos = None
self.status = None
self.cuda = cuda
if cuda:
self.device = torch.device('cuda')
else:
self.device = torch.... | Walkers | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Walkers:
def __init__(self, nwalkers: int=100, nelec: int=1, ndim: int=3, init: Union[Dict, None]=None, cuda: bool=False):
"""Creates Walkers for the sampler. Args: nwalkers (int, optional): Number of walkers. Defaults to 100. nelec (int, optional): number of electron. Defaults to 1. ndi... | stack_v2_sparse_classes_36k_train_020972 | 4,967 | permissive | [
{
"docstring": "Creates Walkers for the sampler. Args: nwalkers (int, optional): Number of walkers. Defaults to 100. nelec (int, optional): number of electron. Defaults to 1. ndim (int, optional): Number of dimensions. Defaults to 3. init (dict, optional): method to initialize the walkers. Defaults to None. (se... | 6 | null | Implement the Python class `Walkers` described below.
Class description:
Implement the Walkers class.
Method signatures and docstrings:
- def __init__(self, nwalkers: int=100, nelec: int=1, ndim: int=3, init: Union[Dict, None]=None, cuda: bool=False): Creates Walkers for the sampler. Args: nwalkers (int, optional): N... | Implement the Python class `Walkers` described below.
Class description:
Implement the Walkers class.
Method signatures and docstrings:
- def __init__(self, nwalkers: int=100, nelec: int=1, ndim: int=3, init: Union[Dict, None]=None, cuda: bool=False): Creates Walkers for the sampler. Args: nwalkers (int, optional): N... | 439a79e97ee63057e3032d28a1a5ebafd2d5b5e4 | <|skeleton|>
class Walkers:
def __init__(self, nwalkers: int=100, nelec: int=1, ndim: int=3, init: Union[Dict, None]=None, cuda: bool=False):
"""Creates Walkers for the sampler. Args: nwalkers (int, optional): Number of walkers. Defaults to 100. nelec (int, optional): number of electron. Defaults to 1. ndi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Walkers:
def __init__(self, nwalkers: int=100, nelec: int=1, ndim: int=3, init: Union[Dict, None]=None, cuda: bool=False):
"""Creates Walkers for the sampler. Args: nwalkers (int, optional): Number of walkers. Defaults to 100. nelec (int, optional): number of electron. Defaults to 1. ndim (int, option... | the_stack_v2_python_sparse | qmctorch/sampler/walkers.py | NLESC-JCER/QMCTorch | train | 22 | |
76a85141c7322572151b5e01e3b127e88c2fa269 | [
"jsonschema.Draft4Validator.check_schema(schema)\nself.validator = jsonschema.Draft4Validator(schema)\nassert isinstance(field_vals, dict)\nassert all((isinstance(val, list) for val in field_vals.values()))\nself.field_vals = {field: frozenset(vals) for field, vals in field_vals.items()}",
"issues = list(self.val... | <|body_start_0|>
jsonschema.Draft4Validator.check_schema(schema)
self.validator = jsonschema.Draft4Validator(schema)
assert isinstance(field_vals, dict)
assert all((isinstance(val, list) for val in field_vals.values()))
self.field_vals = {field: frozenset(vals) for field, vals in... | Validate a single question against the schema. | QValidator | [
"MIT",
"CC-BY-SA-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QValidator:
"""Validate a single question against the schema."""
def __init__(self, schema, field_vals={}):
"""Create a new QValidator with the given `schema` dict. :param dict(str, list(str)) field_vals: For each key present, ensure the corresponding key in a question maps to a subs... | stack_v2_sparse_classes_36k_train_020973 | 3,215 | permissive | [
{
"docstring": "Create a new QValidator with the given `schema` dict. :param dict(str, list(str)) field_vals: For each key present, ensure the corresponding key in a question maps to a subset of the given value.",
"name": "__init__",
"signature": "def __init__(self, schema, field_vals={})"
},
{
... | 2 | null | Implement the Python class `QValidator` described below.
Class description:
Validate a single question against the schema.
Method signatures and docstrings:
- def __init__(self, schema, field_vals={}): Create a new QValidator with the given `schema` dict. :param dict(str, list(str)) field_vals: For each key present, ... | Implement the Python class `QValidator` described below.
Class description:
Validate a single question against the schema.
Method signatures and docstrings:
- def __init__(self, schema, field_vals={}): Create a new QValidator with the given `schema` dict. :param dict(str, list(str)) field_vals: For each key present, ... | 2cb4b45dd14a230aa0e800042e893f8dfb23beda | <|skeleton|>
class QValidator:
"""Validate a single question against the schema."""
def __init__(self, schema, field_vals={}):
"""Create a new QValidator with the given `schema` dict. :param dict(str, list(str)) field_vals: For each key present, ensure the corresponding key in a question maps to a subs... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QValidator:
"""Validate a single question against the schema."""
def __init__(self, schema, field_vals={}):
"""Create a new QValidator with the given `schema` dict. :param dict(str, list(str)) field_vals: For each key present, ensure the corresponding key in a question maps to a subset of the giv... | the_stack_v2_python_sparse | _Job-Search/interview-questions-master/validate.py | bgoonz/UsefulResourceRepo2.0 | train | 10 |
3c5070507aac4c54dc51a619dced20d44993a80b | [
"prev = -1\nres = float('-inf')\nif seats[0] == 1:\n prev = 0\nfor i, seat in enumerate(seats):\n if i == 1:\n if prev == -1:\n res = max(res, i)\n else:\n res = max(res, (i - prev) // 2)\n prev = i\nif seat[-1] == 0:\n res = max(res, len(seats) - 1 - prev)\nretur... | <|body_start_0|>
prev = -1
res = float('-inf')
if seats[0] == 1:
prev = 0
for i, seat in enumerate(seats):
if i == 1:
if prev == -1:
res = max(res, i)
else:
res = max(res, (i - prev) // 2)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxDistToClosest2(self, seats):
""":type seats: List[int] :rtype: int"""
<|body_0|>
def maxDistToClosest(self, seats):
""":type seats: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
prev = -1
res = float(... | stack_v2_sparse_classes_36k_train_020974 | 1,617 | no_license | [
{
"docstring": ":type seats: List[int] :rtype: int",
"name": "maxDistToClosest2",
"signature": "def maxDistToClosest2(self, seats)"
},
{
"docstring": ":type seats: List[int] :rtype: int",
"name": "maxDistToClosest",
"signature": "def maxDistToClosest(self, seats)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021066 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDistToClosest2(self, seats): :type seats: List[int] :rtype: int
- def maxDistToClosest(self, seats): :type seats: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDistToClosest2(self, seats): :type seats: List[int] :rtype: int
- def maxDistToClosest(self, seats): :type seats: List[int] :rtype: int
<|skeleton|>
class Solution:
... | 1a3c1f4d6e9d3444039f087763b93241f4ba7892 | <|skeleton|>
class Solution:
def maxDistToClosest2(self, seats):
""":type seats: List[int] :rtype: int"""
<|body_0|>
def maxDistToClosest(self, seats):
""":type seats: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxDistToClosest2(self, seats):
""":type seats: List[int] :rtype: int"""
prev = -1
res = float('-inf')
if seats[0] == 1:
prev = 0
for i, seat in enumerate(seats):
if i == 1:
if prev == -1:
res = m... | the_stack_v2_python_sparse | Algorithm/849_Max_Distance_To_Closest_People.py | Gi1ia/TechNoteBook | train | 7 | |
53b4a1cbbf1dd4744a57e15fb25741cbbf2c088d | [
"time = timezone.now() + datetime.timedelta(days=10)\nq = Question(question_text='Are we in future??', pub_date=time)\nself.assertIs(q.was_published_recently(), False)",
"time = timezone.now() - datetime.timedelta(days=2)\nq = Question(question_text='Are we in future??', pub_date=time)\nself.assertIs(q.was_publis... | <|body_start_0|>
time = timezone.now() + datetime.timedelta(days=10)
q = Question(question_text='Are we in future??', pub_date=time)
self.assertIs(q.was_published_recently(), False)
<|end_body_0|>
<|body_start_1|>
time = timezone.now() - datetime.timedelta(days=2)
q = Question(q... | QuestionMethodTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionMethodTests:
def test_was_published_recently_with_future_question(self):
"""was_published_recently should return False if published date is in the future."""
<|body_0|>
def test_was_published_recently_with_old_question(self):
"""was_published_recently should ... | stack_v2_sparse_classes_36k_train_020975 | 4,246 | no_license | [
{
"docstring": "was_published_recently should return False if published date is in the future.",
"name": "test_was_published_recently_with_future_question",
"signature": "def test_was_published_recently_with_future_question(self)"
},
{
"docstring": "was_published_recently should return False if ... | 4 | null | Implement the Python class `QuestionMethodTests` described below.
Class description:
Implement the QuestionMethodTests class.
Method signatures and docstrings:
- def test_was_published_recently_with_future_question(self): was_published_recently should return False if published date is in the future.
- def test_was_pu... | Implement the Python class `QuestionMethodTests` described below.
Class description:
Implement the QuestionMethodTests class.
Method signatures and docstrings:
- def test_was_published_recently_with_future_question(self): was_published_recently should return False if published date is in the future.
- def test_was_pu... | acbb6d21a8182feabcb3329e17c76ac3af375255 | <|skeleton|>
class QuestionMethodTests:
def test_was_published_recently_with_future_question(self):
"""was_published_recently should return False if published date is in the future."""
<|body_0|>
def test_was_published_recently_with_old_question(self):
"""was_published_recently should ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuestionMethodTests:
def test_was_published_recently_with_future_question(self):
"""was_published_recently should return False if published date is in the future."""
time = timezone.now() + datetime.timedelta(days=10)
q = Question(question_text='Are we in future??', pub_date=time)
... | the_stack_v2_python_sparse | pythonTutorial/django/mysite/polls/tests.py | rajatgirotra/study | train | 6 | |
2b2b3b8c712bc4e12329ec12fd1664201ac5fd9b | [
"if len(ransomNote) > len(magazine):\n return False\nd = dict()\nfor char in magazine:\n if char in d:\n d[char] = d[char] + 1\n else:\n d[char] = 1\nfor char in ransomNote:\n if char in d and d[char] > 0:\n d[char] = d[char] - 1\n else:\n return False\nreturn True",
"if... | <|body_start_0|>
if len(ransomNote) > len(magazine):
return False
d = dict()
for char in magazine:
if char in d:
d[char] = d[char] + 1
else:
d[char] = 1
for char in ransomNote:
if char in d and d[char] > 0:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canConstruct1(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_0|>
def canConstruct2(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_36k_train_020976 | 996 | permissive | [
{
"docstring": ":type ransomNote: str :type magazine: str :rtype: bool",
"name": "canConstruct1",
"signature": "def canConstruct1(self, ransomNote, magazine)"
},
{
"docstring": ":type ransomNote: str :type magazine: str :rtype: bool",
"name": "canConstruct2",
"signature": "def canConstru... | 2 | stack_v2_sparse_classes_30k_train_001975 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canConstruct1(self, ransomNote, magazine): :type ransomNote: str :type magazine: str :rtype: bool
- def canConstruct2(self, ransomNote, magazine): :type ransomNote: str :type... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canConstruct1(self, ransomNote, magazine): :type ransomNote: str :type magazine: str :rtype: bool
- def canConstruct2(self, ransomNote, magazine): :type ransomNote: str :type... | 03876232521a20d32f8fa4e7d6d19cf208739a79 | <|skeleton|>
class Solution:
def canConstruct1(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_0|>
def canConstruct2(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canConstruct1(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
if len(ransomNote) > len(magazine):
return False
d = dict()
for char in magazine:
if char in d:
d[char] = d[char] + 1
... | the_stack_v2_python_sparse | Python/ransom-note.py | coolryze/LeetCode | train | 4 | |
46fbc83852d00ff2a80b2b00ffcb099e9e96064f | [
"UVMSequenceItem.__init__(self, name)\nself.value: List[int] = [0]\nself.path = UVM_FRONTDOOR\nself.status = 0\nself.fname = ''\nself.lineno = 0\nself.bd_kind = ''\nself.prior = -1\nself.extension = None\nself.parent = None\nself.offset = 0\nself.kind = UVM_READ\nself.element = None\nself.element_kind = -1\nself.ma... | <|body_start_0|>
UVMSequenceItem.__init__(self, name)
self.value: List[int] = [0]
self.path = UVM_FRONTDOOR
self.status = 0
self.fname = ''
self.lineno = 0
self.bd_kind = ''
self.prior = -1
self.extension = None
self.parent = None
s... | CLASS: UVMRegItem Defines an abstract register transaction item. No bus-specific information is present, although a handle to a `UVMRegMap` is provided in case a user wishes to implement a custom address translation algorithm. | UVMRegItem | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UVMRegItem:
"""CLASS: UVMRegItem Defines an abstract register transaction item. No bus-specific information is present, although a handle to a `UVMRegMap` is provided in case a user wishes to implement a custom address translation algorithm."""
def __init__(self, name='') -> None:
""... | stack_v2_sparse_classes_36k_train_020977 | 9,874 | permissive | [
{
"docstring": "Create a new instance of this type, giving it the optional `name`. Args: name (str): Name of the instance",
"name": "__init__",
"signature": "def __init__(self, name='') -> None"
},
{
"docstring": "Function: convert2string Returns a string showing the contents of this transaction... | 3 | stack_v2_sparse_classes_30k_train_017314 | Implement the Python class `UVMRegItem` described below.
Class description:
CLASS: UVMRegItem Defines an abstract register transaction item. No bus-specific information is present, although a handle to a `UVMRegMap` is provided in case a user wishes to implement a custom address translation algorithm.
Method signatur... | Implement the Python class `UVMRegItem` described below.
Class description:
CLASS: UVMRegItem Defines an abstract register transaction item. No bus-specific information is present, although a handle to a `UVMRegMap` is provided in case a user wishes to implement a custom address translation algorithm.
Method signatur... | fc5f955701b2b56c1fddac195c70cb3ebb9139fe | <|skeleton|>
class UVMRegItem:
"""CLASS: UVMRegItem Defines an abstract register transaction item. No bus-specific information is present, although a handle to a `UVMRegMap` is provided in case a user wishes to implement a custom address translation algorithm."""
def __init__(self, name='') -> None:
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UVMRegItem:
"""CLASS: UVMRegItem Defines an abstract register transaction item. No bus-specific information is present, although a handle to a `UVMRegMap` is provided in case a user wishes to implement a custom address translation algorithm."""
def __init__(self, name='') -> None:
"""Create a new... | the_stack_v2_python_sparse | src/uvm/reg/uvm_reg_item.py | tpoikela/uvm-python | train | 199 |
c970759c31ed17d65566c66f589bc780431f8463 | [
"signature, key = read_fmt('4sH', fp)\ntry:\n key = ImageResourceID(key)\nexcept ValueError:\n if ImageResourceID.is_path_info(key):\n logger.debug('Undefined PATH_INFO found: %d' % key)\n elif ImageResourceID.is_plugin_resource(key):\n logger.debug('Undefined PLUGIN_RESOURCE found: %d' % key... | <|body_start_0|>
signature, key = read_fmt('4sH', fp)
try:
key = ImageResourceID(key)
except ValueError:
if ImageResourceID.is_path_info(key):
logger.debug('Undefined PATH_INFO found: %d' % key)
elif ImageResourceID.is_plugin_resource(key):
... | Image resource block. .. py:attribute:: signature Binary signature, always ``b'8BIM'``. .. py:attribute:: key Unique identifier for the resource. See :py:class:`~psd_tools.constants.ImageResourceID`. .. py:attribute:: name .. py:attribute:: data The resource data. | ImageResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageResource:
"""Image resource block. .. py:attribute:: signature Binary signature, always ``b'8BIM'``. .. py:attribute:: key Unique identifier for the resource. See :py:class:`~psd_tools.constants.ImageResourceID`. .. py:attribute:: name .. py:attribute:: data The resource data."""
def re... | stack_v2_sparse_classes_36k_train_020978 | 30,369 | permissive | [
{
"docstring": "Read the element from a file-like object. :param fp: file-like object :rtype: :py:class:`.ImageResource`",
"name": "read",
"signature": "def read(cls, fp, encoding='macroman')"
},
{
"docstring": "Write the element to a file-like object. :param fp: file-like object :rtype: int",
... | 2 | stack_v2_sparse_classes_30k_train_001573 | Implement the Python class `ImageResource` described below.
Class description:
Image resource block. .. py:attribute:: signature Binary signature, always ``b'8BIM'``. .. py:attribute:: key Unique identifier for the resource. See :py:class:`~psd_tools.constants.ImageResourceID`. .. py:attribute:: name .. py:attribute::... | Implement the Python class `ImageResource` described below.
Class description:
Image resource block. .. py:attribute:: signature Binary signature, always ``b'8BIM'``. .. py:attribute:: key Unique identifier for the resource. See :py:class:`~psd_tools.constants.ImageResourceID`. .. py:attribute:: name .. py:attribute::... | 0e3ac5b64061c7eb87c6eeacce4b9792d1f479b5 | <|skeleton|>
class ImageResource:
"""Image resource block. .. py:attribute:: signature Binary signature, always ``b'8BIM'``. .. py:attribute:: key Unique identifier for the resource. See :py:class:`~psd_tools.constants.ImageResourceID`. .. py:attribute:: name .. py:attribute:: data The resource data."""
def re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageResource:
"""Image resource block. .. py:attribute:: signature Binary signature, always ``b'8BIM'``. .. py:attribute:: key Unique identifier for the resource. See :py:class:`~psd_tools.constants.ImageResourceID`. .. py:attribute:: name .. py:attribute:: data The resource data."""
def read(cls, fp, e... | the_stack_v2_python_sparse | psd_tools/psd/image_resources.py | sfneal/psd-tools3 | train | 30 |
711d3d0969e312c9f467c2458b9d17def42666e8 | [
"super(BottleNeck, self).__init__()\nself.inp_bn = inp_bn\nadd_block = []\nif droprate > 0:\n add_block += [nn.Dropout(p=droprate)]\nadd_block += [nn.Linear(input_dim, num_bottleneck)]\nadd_block += [nn.BatchNorm1D(num_bottleneck)]\nadd_block += [nn.LeakyReLU(0.1)]\nadd_block = nn.Sequential(*add_block)\nself.ad... | <|body_start_0|>
super(BottleNeck, self).__init__()
self.inp_bn = inp_bn
add_block = []
if droprate > 0:
add_block += [nn.Dropout(p=droprate)]
add_block += [nn.Linear(input_dim, num_bottleneck)]
add_block += [nn.BatchNorm1D(num_bottleneck)]
add_block +... | bottleneck | BottleNeck | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BottleNeck:
"""bottleneck"""
def __init__(self, input_dim, num_bottleneck, droprate=0.5, inp_bn=False):
"""init"""
<|body_0|>
def forward(self, x):
"""forward"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(BottleNeck, self).__init__()
... | stack_v2_sparse_classes_36k_train_020979 | 994 | permissive | [
{
"docstring": "init",
"name": "__init__",
"signature": "def __init__(self, input_dim, num_bottleneck, droprate=0.5, inp_bn=False)"
},
{
"docstring": "forward",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015936 | Implement the Python class `BottleNeck` described below.
Class description:
bottleneck
Method signatures and docstrings:
- def __init__(self, input_dim, num_bottleneck, droprate=0.5, inp_bn=False): init
- def forward(self, x): forward | Implement the Python class `BottleNeck` described below.
Class description:
bottleneck
Method signatures and docstrings:
- def __init__(self, input_dim, num_bottleneck, droprate=0.5, inp_bn=False): init
- def forward(self, x): forward
<|skeleton|>
class BottleNeck:
"""bottleneck"""
def __init__(self, input_... | b8ec015fa9e16c0a879c619ee1f2aab8a393c7bd | <|skeleton|>
class BottleNeck:
"""bottleneck"""
def __init__(self, input_dim, num_bottleneck, droprate=0.5, inp_bn=False):
"""init"""
<|body_0|>
def forward(self, x):
"""forward"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BottleNeck:
"""bottleneck"""
def __init__(self, input_dim, num_bottleneck, droprate=0.5, inp_bn=False):
"""init"""
super(BottleNeck, self).__init__()
self.inp_bn = inp_bn
add_block = []
if droprate > 0:
add_block += [nn.Dropout(p=droprate)]
add_... | the_stack_v2_python_sparse | ST_DM/KDD2022-DuMapper/DME/arch/gears/neck.py | sserdoubleh/Research | train | 10 |
30bd1d1296bad3941e7174f1fc07a2e29b80ab5e | [
"self.num_points = num_points\nself.x_values = [init_coords[0]]\nself.y_values = [init_coords[1]]\nself.z_values = [init_coords[2]]\nself.theta_ = []\nself.phi_ = []\nself.theta = 0\nself.theta_.append(self.theta)\nself.phi = init_phi\nself.phi_.append(self.phi)\nself.deltaTheta = 0\nself.deltaPhi = 0",
"while le... | <|body_start_0|>
self.num_points = num_points
self.x_values = [init_coords[0]]
self.y_values = [init_coords[1]]
self.z_values = [init_coords[2]]
self.theta_ = []
self.phi_ = []
self.theta = 0
self.theta_.append(self.theta)
self.phi = init_phi
... | A class to generate random datas. | GenerateLine3D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenerateLine3D:
"""A class to generate random datas."""
def __init__(self, init_coords=[], init_theta=0, init_phi=0, num_points=5000):
"""Initialize attributes of a data."""
<|body_0|>
def fill_points(self):
"""Calculate all the points in the data."""
<|b... | stack_v2_sparse_classes_36k_train_020980 | 20,287 | no_license | [
{
"docstring": "Initialize attributes of a data.",
"name": "__init__",
"signature": "def __init__(self, init_coords=[], init_theta=0, init_phi=0, num_points=5000)"
},
{
"docstring": "Calculate all the points in the data.",
"name": "fill_points",
"signature": "def fill_points(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012986 | Implement the Python class `GenerateLine3D` described below.
Class description:
A class to generate random datas.
Method signatures and docstrings:
- def __init__(self, init_coords=[], init_theta=0, init_phi=0, num_points=5000): Initialize attributes of a data.
- def fill_points(self): Calculate all the points in the... | Implement the Python class `GenerateLine3D` described below.
Class description:
A class to generate random datas.
Method signatures and docstrings:
- def __init__(self, init_coords=[], init_theta=0, init_phi=0, num_points=5000): Initialize attributes of a data.
- def fill_points(self): Calculate all the points in the... | 6e7a278031ff0a1eb51e7810b326d66524d4aef3 | <|skeleton|>
class GenerateLine3D:
"""A class to generate random datas."""
def __init__(self, init_coords=[], init_theta=0, init_phi=0, num_points=5000):
"""Initialize attributes of a data."""
<|body_0|>
def fill_points(self):
"""Calculate all the points in the data."""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GenerateLine3D:
"""A class to generate random datas."""
def __init__(self, init_coords=[], init_theta=0, init_phi=0, num_points=5000):
"""Initialize attributes of a data."""
self.num_points = num_points
self.x_values = [init_coords[0]]
self.y_values = [init_coords[1]]
... | the_stack_v2_python_sparse | check_data/generate_data/generate_data.py | c-feng/Neuron-Tracking | train | 1 |
c1e287f1ad9aa7f3f2fffae267ba8339c549fb9f | [
"dl = DisplayList()\nam = IAddressManagement(self)\nfor address in am.getAddresses():\n dl.add(address.getId(), address.getName() + ' - ' + address.getAddress1())\nreturn dl",
"dl = DisplayList()\npm = IShippingManagement(self.getShop())\nfor shipping_method in pm.getShippingMethods():\n dl.add(shipping_met... | <|body_start_0|>
dl = DisplayList()
am = IAddressManagement(self)
for address in am.getAddresses():
dl.add(address.getId(), address.getName() + ' - ' + address.getAddress1())
return dl
<|end_body_0|>
<|body_start_1|>
dl = DisplayList()
pm = IShippingManagemen... | A customer can buy products from a shop. A customer has addresses and payment methods. A customer exists additionally to the members of Plone. Whenever a member wants to buy something a customer content object is added for this member. This is intended to be changed to use remember in future. | Customer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Customer:
"""A customer can buy products from a shop. A customer has addresses and payment methods. A customer exists additionally to the members of Plone. Whenever a member wants to buy something a customer content object is added for this member. This is intended to be changed to use remember i... | stack_v2_sparse_classes_36k_train_020981 | 4,537 | no_license | [
{
"docstring": "Returns all addresses as DisplayList.",
"name": "_getAddressesAsDL",
"signature": "def _getAddressesAsDL(self)"
},
{
"docstring": "Returns all shipping methods as DisplayList.",
"name": "_getShippingMethodsAsDL",
"signature": "def _getShippingMethodsAsDL(self)"
},
{
... | 3 | null | Implement the Python class `Customer` described below.
Class description:
A customer can buy products from a shop. A customer has addresses and payment methods. A customer exists additionally to the members of Plone. Whenever a member wants to buy something a customer content object is added for this member. This is i... | Implement the Python class `Customer` described below.
Class description:
A customer can buy products from a shop. A customer has addresses and payment methods. A customer exists additionally to the members of Plone. Whenever a member wants to buy something a customer content object is added for this member. This is i... | 26e9a40f8e25684a1c156ac1cea08e6796e4c2d7 | <|skeleton|>
class Customer:
"""A customer can buy products from a shop. A customer has addresses and payment methods. A customer exists additionally to the members of Plone. Whenever a member wants to buy something a customer content object is added for this member. This is intended to be changed to use remember i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Customer:
"""A customer can buy products from a shop. A customer has addresses and payment methods. A customer exists additionally to the members of Plone. Whenever a member wants to buy something a customer content object is added for this member. This is intended to be changed to use remember in future."""
... | the_stack_v2_python_sparse | Attic_from_svn_import/easyshop.customer/easyshop/customer/content/customer.py | Easyshop/Easyshop | train | 3 |
40ecb2662a9d3b74b1bfb38180ba8a4fe3e436db | [
"self.delay = delay\nself.ticks = ticks\nself.tick_count = 0\nself.timer = None\nself.done = False\nself.callback = callback",
"if not self.timer:\n self.timer = now\n self.callback(self.tick_count)\nelif not self.done and now - self.timer > self.delay:\n self.tick_count += 1\n self.timer = now\n i... | <|body_start_0|>
self.delay = delay
self.ticks = ticks
self.tick_count = 0
self.timer = None
self.done = False
self.callback = callback
<|end_body_0|>
<|body_start_1|>
if not self.timer:
self.timer = now
self.callback(self.tick_count)
... | Very simple timer. It does not take care about how late it checks tick. | Timer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Timer:
"""Very simple timer. It does not take care about how late it checks tick."""
def __init__(self, delay, callback, ticks=-1):
"""Delay is given in milliseconds; ticks is a number of ticks the timer will make before setting self.done to True. Pass a value -1 to bypass. callback ... | stack_v2_sparse_classes_36k_train_020982 | 4,928 | no_license | [
{
"docstring": "Delay is given in milliseconds; ticks is a number of ticks the timer will make before setting self.done to True. Pass a value -1 to bypass. callback specify function of one argument (tick count), that is called when 'delay' passed, but it is not called automaticly - check_tick must be called.",
... | 2 | stack_v2_sparse_classes_30k_train_013460 | Implement the Python class `Timer` described below.
Class description:
Very simple timer. It does not take care about how late it checks tick.
Method signatures and docstrings:
- def __init__(self, delay, callback, ticks=-1): Delay is given in milliseconds; ticks is a number of ticks the timer will make before settin... | Implement the Python class `Timer` described below.
Class description:
Very simple timer. It does not take care about how late it checks tick.
Method signatures and docstrings:
- def __init__(self, delay, callback, ticks=-1): Delay is given in milliseconds; ticks is a number of ticks the timer will make before settin... | 026ef53b5ed9683691b8f136ceae756fe6dd7f07 | <|skeleton|>
class Timer:
"""Very simple timer. It does not take care about how late it checks tick."""
def __init__(self, delay, callback, ticks=-1):
"""Delay is given in milliseconds; ticks is a number of ticks the timer will make before setting self.done to True. Pass a value -1 to bypass. callback ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Timer:
"""Very simple timer. It does not take care about how late it checks tick."""
def __init__(self, delay, callback, ticks=-1):
"""Delay is given in milliseconds; ticks is a number of ticks the timer will make before setting self.done to True. Pass a value -1 to bypass. callback specify funct... | the_stack_v2_python_sparse | data/tools.py | jpaulovic/Asteroids | train | 0 |
acb3b08a4bcde379f3affcc629e731e68fba24be | [
"review_id = label.review_id\nlast_review_id = label.last_review_id\ntext_id = label.text_id\nlast_text_id = label.last_text_id\nreview = label.review\ntext = label.text\nlabel_attrs = label.attributes\npred_attrs = pred.attributes\nattr_annotation_pairs = zip(label_attrs, pred_attrs)\nfor label_attr_annotation, pr... | <|body_start_0|>
review_id = label.review_id
last_review_id = label.last_review_id
text_id = label.text_id
last_text_id = label.last_text_id
review = label.review
text = label.text
label_attrs = label.attributes
pred_attrs = pred.attributes
attr_an... | 定量評価または、エラー分析に使いやすいようにフォーマットを定めたクラス Attributes: review_id (int): レビュー番号 last_review_id (int): 最後のレビュー番号 text_id (int): レビュー文中の文番号 last_text_id (int): レビュー文中の最後の文番号 review (str): レビュー本文 text (str): 評価対象の文 label (int): 正解ラベル pred (int): 属性抽出結果 label_attrs (Tuple[AttrAnnotation, ...]): 正解アノテーション pred_attrs (Tuple[AttrAnno... | DataForEvaluation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataForEvaluation:
"""定量評価または、エラー分析に使いやすいようにフォーマットを定めたクラス Attributes: review_id (int): レビュー番号 last_review_id (int): 最後のレビュー番号 text_id (int): レビュー文中の文番号 last_text_id (int): レビュー文中の最後の文番号 review (str): レビュー本文 text (str): 評価対象の文 label (int): 正解ラベル pred (int): 属性抽出結果 label_attrs (Tuple[AttrAnnotation... | stack_v2_sparse_classes_36k_train_020983 | 10,681 | no_license | [
{
"docstring": "正解データと属性抽出結果データからインスタンス化し、属性ごとにインスタンスを返すジェネレータ関数 Args: pred (TextWithAttrAnnotation): 属性抽出結果データ label (TextWithAttrAnnotation): 正解データ Returns: 属性とそれに対応するDataForEvaluationインスタンスのジェネレータ",
"name": "iterator_from_text_with_annotation_pair",
"signature": "def iterator_from_text_with_annotatio... | 2 | stack_v2_sparse_classes_30k_train_003905 | Implement the Python class `DataForEvaluation` described below.
Class description:
定量評価または、エラー分析に使いやすいようにフォーマットを定めたクラス Attributes: review_id (int): レビュー番号 last_review_id (int): 最後のレビュー番号 text_id (int): レビュー文中の文番号 last_text_id (int): レビュー文中の最後の文番号 review (str): レビュー本文 text (str): 評価対象の文 label (int): 正解ラベル pred (int): 属... | Implement the Python class `DataForEvaluation` described below.
Class description:
定量評価または、エラー分析に使いやすいようにフォーマットを定めたクラス Attributes: review_id (int): レビュー番号 last_review_id (int): 最後のレビュー番号 text_id (int): レビュー文中の文番号 last_text_id (int): レビュー文中の最後の文番号 review (str): レビュー本文 text (str): 評価対象の文 label (int): 正解ラベル pred (int): 属... | a4c6334b779a94814b7798a0fbfe9a148bf18d3a | <|skeleton|>
class DataForEvaluation:
"""定量評価または、エラー分析に使いやすいようにフォーマットを定めたクラス Attributes: review_id (int): レビュー番号 last_review_id (int): 最後のレビュー番号 text_id (int): レビュー文中の文番号 last_text_id (int): レビュー文中の最後の文番号 review (str): レビュー本文 text (str): 評価対象の文 label (int): 正解ラベル pred (int): 属性抽出結果 label_attrs (Tuple[AttrAnnotation... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataForEvaluation:
"""定量評価または、エラー分析に使いやすいようにフォーマットを定めたクラス Attributes: review_id (int): レビュー番号 last_review_id (int): 最後のレビュー番号 text_id (int): レビュー文中の文番号 last_text_id (int): レビュー文中の最後の文番号 review (str): レビュー本文 text (str): 評価対象の文 label (int): 正解ラベル pred (int): 属性抽出結果 label_attrs (Tuple[AttrAnnotation, ...]): 正解アノ... | the_stack_v2_python_sparse | src/review_research/evaluation/attr_extraction_evaluater.py | S38knt-ks/ReviewResearch | train | 0 |
12345da3ad71cbbda7c47bc19e76481739bfc0da | [
"with open(filepath) as fp:\n self.data = fp.read().splitlines()\nself.width = len(self.data[0])\nself.x = 0\nself.y = 0\nself.placement = (0, 0)",
"_x = (self.placement[0] + self.x) % self.width\n_y = (self.placement[0] + self.y) % self.width\nself.placement = (_x, _y)",
"self.x = x\nself.y = y\nself.placem... | <|body_start_0|>
with open(filepath) as fp:
self.data = fp.read().splitlines()
self.width = len(self.data[0])
self.x = 0
self.y = 0
self.placement = (0, 0)
<|end_body_0|>
<|body_start_1|>
_x = (self.placement[0] + self.x) % self.width
_y = (self.place... | Generic Sled class | Sled | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sled:
"""Generic Sled class"""
def __init__(self, filepath):
"""init"""
<|body_0|>
def _new_position(self):
"""calc new position"""
<|body_1|>
def find_trees(self, x, y):
"""find the trees in the way based on slope"""
<|body_2|>
<|en... | stack_v2_sparse_classes_36k_train_020984 | 1,345 | permissive | [
{
"docstring": "init",
"name": "__init__",
"signature": "def __init__(self, filepath)"
},
{
"docstring": "calc new position",
"name": "_new_position",
"signature": "def _new_position(self)"
},
{
"docstring": "find the trees in the way based on slope",
"name": "find_trees",
... | 3 | stack_v2_sparse_classes_30k_train_004596 | Implement the Python class `Sled` described below.
Class description:
Generic Sled class
Method signatures and docstrings:
- def __init__(self, filepath): init
- def _new_position(self): calc new position
- def find_trees(self, x, y): find the trees in the way based on slope | Implement the Python class `Sled` described below.
Class description:
Generic Sled class
Method signatures and docstrings:
- def __init__(self, filepath): init
- def _new_position(self): calc new position
- def find_trees(self, x, y): find the trees in the way based on slope
<|skeleton|>
class Sled:
"""Generic S... | 9481e4b518eacb86beb42f83906872dcc871c3f7 | <|skeleton|>
class Sled:
"""Generic Sled class"""
def __init__(self, filepath):
"""init"""
<|body_0|>
def _new_position(self):
"""calc new position"""
<|body_1|>
def find_trees(self, x, y):
"""find the trees in the way based on slope"""
<|body_2|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sled:
"""Generic Sled class"""
def __init__(self, filepath):
"""init"""
with open(filepath) as fp:
self.data = fp.read().splitlines()
self.width = len(self.data[0])
self.x = 0
self.y = 0
self.placement = (0, 0)
def _new_position(self):
... | the_stack_v2_python_sparse | day3/run.py | layertwo/adventofcode2020 | train | 0 |
707aef503547fc51c6b2fb2e8bff1d3cb6419ff3 | [
"super().__init__(hass=hass, logger=_LOGGER, name=name, update_interval=timedelta(minutes=5))\nself.api = api\nself.name = name\nself.latitude = int(latitude)\nself.longitude = int(longitude)\nself.threshold = int(threshold)",
"try:\n return await self.api.get_forecast_data(self.longitude, self.latitude)\nexce... | <|body_start_0|>
super().__init__(hass=hass, logger=_LOGGER, name=name, update_interval=timedelta(minutes=5))
self.api = api
self.name = name
self.latitude = int(latitude)
self.longitude = int(longitude)
self.threshold = int(threshold)
<|end_body_0|>
<|body_start_1|>
... | Class to manage fetching data from the NOAA Aurora API. | AuroraDataUpdateCoordinator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuroraDataUpdateCoordinator:
"""Class to manage fetching data from the NOAA Aurora API."""
def __init__(self, hass: HomeAssistant, name: str, api: AuroraForecast, latitude: float, longitude: float, threshold: float) -> None:
"""Initialize the data updater."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_020985 | 1,334 | permissive | [
{
"docstring": "Initialize the data updater.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, name: str, api: AuroraForecast, latitude: float, longitude: float, threshold: float) -> None"
},
{
"docstring": "Fetch the data from the NOAA Aurora Forecast.",
"name": "_... | 2 | null | Implement the Python class `AuroraDataUpdateCoordinator` described below.
Class description:
Class to manage fetching data from the NOAA Aurora API.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, name: str, api: AuroraForecast, latitude: float, longitude: float, threshold: float) -> None:... | Implement the Python class `AuroraDataUpdateCoordinator` described below.
Class description:
Class to manage fetching data from the NOAA Aurora API.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, name: str, api: AuroraForecast, latitude: float, longitude: float, threshold: float) -> None:... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class AuroraDataUpdateCoordinator:
"""Class to manage fetching data from the NOAA Aurora API."""
def __init__(self, hass: HomeAssistant, name: str, api: AuroraForecast, latitude: float, longitude: float, threshold: float) -> None:
"""Initialize the data updater."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuroraDataUpdateCoordinator:
"""Class to manage fetching data from the NOAA Aurora API."""
def __init__(self, hass: HomeAssistant, name: str, api: AuroraForecast, latitude: float, longitude: float, threshold: float) -> None:
"""Initialize the data updater."""
super().__init__(hass=hass, l... | the_stack_v2_python_sparse | homeassistant/components/aurora/coordinator.py | home-assistant/core | train | 35,501 |
afda35c857caf037e0b4e2803a1860c2a1f9fce2 | [
"self.client = None\nself.channel = None\nself.delimiter = delimiter",
"start = time()\nclient = paramiko.SSHClient()\nclient.set_missing_host_key_policy(paramiko.AutoAddPolicy())\nclient.connect(node['host'], username=node['honeycomb']['user'], password=node['honeycomb']['passwd'], pkey=None, port=node['honeycom... | <|body_start_0|>
self.client = None
self.channel = None
self.delimiter = delimiter
<|end_body_0|>
<|body_start_1|>
start = time()
client = paramiko.SSHClient()
client.set_missing_host_key_policy(paramiko.AutoAddPolicy())
client.connect(node['host'], username=node... | Implements methods for creating and managing Netconf sessions. | Netconf | [
"CC-BY-4.0",
"Apache-2.0",
"LicenseRef-scancode-dco-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Netconf:
"""Implements methods for creating and managing Netconf sessions."""
def __init__(self, delimiter=']]>]]>'):
"""Initializer. Note: Passing the channel object as a robotframework argument closes the channel. Class variables are used instead, to persist the connection channel ... | stack_v2_sparse_classes_36k_train_020986 | 5,637 | permissive | [
{
"docstring": "Initializer. Note: Passing the channel object as a robotframework argument closes the channel. Class variables are used instead, to persist the connection channel throughout test cases.",
"name": "__init__",
"signature": "def __init__(self, delimiter=']]>]]>')"
},
{
"docstring": ... | 5 | stack_v2_sparse_classes_30k_val_000016 | Implement the Python class `Netconf` described below.
Class description:
Implements methods for creating and managing Netconf sessions.
Method signatures and docstrings:
- def __init__(self, delimiter=']]>]]>'): Initializer. Note: Passing the channel object as a robotframework argument closes the channel. Class varia... | Implement the Python class `Netconf` described below.
Class description:
Implements methods for creating and managing Netconf sessions.
Method signatures and docstrings:
- def __init__(self, delimiter=']]>]]>'): Initializer. Note: Passing the channel object as a robotframework argument closes the channel. Class varia... | 3151c98618c78e3782e48bbe4d9c8f906c126f69 | <|skeleton|>
class Netconf:
"""Implements methods for creating and managing Netconf sessions."""
def __init__(self, delimiter=']]>]]>'):
"""Initializer. Note: Passing the channel object as a robotframework argument closes the channel. Class variables are used instead, to persist the connection channel ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Netconf:
"""Implements methods for creating and managing Netconf sessions."""
def __init__(self, delimiter=']]>]]>'):
"""Initializer. Note: Passing the channel object as a robotframework argument closes the channel. Class variables are used instead, to persist the connection channel throughout te... | the_stack_v2_python_sparse | resources/libraries/python/honeycomb/Netconf.py | preym17/csit | train | 0 |
51268626e17402dd27ff8f3f689c3fbf1e94cad0 | [
"m_bin = bin(m)[2:]\ndiff = n - m\nans = 0\nfor i in range(len(m_bin)):\n if m_bin[-1 - i] == '1':\n cur = int(m_bin[-1 - i:], 2)\n moves_to_change = (1 << i + 1) - cur\n if moves_to_change > diff:\n ans |= 1 << i\nreturn ans",
"digit = 1\nwhile m != n:\n digit <<= 1\n m >... | <|body_start_0|>
m_bin = bin(m)[2:]
diff = n - m
ans = 0
for i in range(len(m_bin)):
if m_bin[-1 - i] == '1':
cur = int(m_bin[-1 - i:], 2)
moves_to_change = (1 << i + 1) - cur
if moves_to_change > diff:
ans |... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rangeBitwiseAnd(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_0|>
def rangeBitwiseAnd2(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
m_bin = bin(m)[2:]
d... | stack_v2_sparse_classes_36k_train_020987 | 853 | no_license | [
{
"docstring": ":type m: int :type n: int :rtype: int",
"name": "rangeBitwiseAnd",
"signature": "def rangeBitwiseAnd(self, m, n)"
},
{
"docstring": ":type m: int :type n: int :rtype: int",
"name": "rangeBitwiseAnd2",
"signature": "def rangeBitwiseAnd2(self, m, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rangeBitwiseAnd(self, m, n): :type m: int :type n: int :rtype: int
- def rangeBitwiseAnd2(self, m, n): :type m: int :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rangeBitwiseAnd(self, m, n): :type m: int :type n: int :rtype: int
- def rangeBitwiseAnd2(self, m, n): :type m: int :type n: int :rtype: int
<|skeleton|>
class Solution:
... | 0da45559271d3dba687858b8945b3e361ecc813c | <|skeleton|>
class Solution:
def rangeBitwiseAnd(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_0|>
def rangeBitwiseAnd2(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rangeBitwiseAnd(self, m, n):
""":type m: int :type n: int :rtype: int"""
m_bin = bin(m)[2:]
diff = n - m
ans = 0
for i in range(len(m_bin)):
if m_bin[-1 - i] == '1':
cur = int(m_bin[-1 - i:], 2)
moves_to_change =... | the_stack_v2_python_sparse | 201-bitwise-and-numbers-range/solution.py | katryo/leetcode | train | 0 | |
510f2305a55ad99d420bdc20b0c73551a0b56a18 | [
"super(softCrossEntropy, self).__init__()\nself.alpha = alpha\nreturn",
"KD_loss = self.alpha\nKD_loss *= nn.KLDivLoss(size_average=False)(fcnal.log_softmax(inputs, dim=1), fcnal.softmax(target, dim=1))\nKD_loss += (1 - self.alpha) * fcnal.cross_entropy(inputs, true_labels)\nreturn KD_loss"
] | <|body_start_0|>
super(softCrossEntropy, self).__init__()
self.alpha = alpha
return
<|end_body_0|>
<|body_start_1|>
KD_loss = self.alpha
KD_loss *= nn.KLDivLoss(size_average=False)(fcnal.log_softmax(inputs, dim=1), fcnal.softmax(target, dim=1))
KD_loss += (1 - self.alpha... | softCrossEntropy | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class softCrossEntropy:
def __init__(self, alpha=0.95):
""":param alpha: Strength (0-1) of influence from soft labels in training"""
<|body_0|>
def forward(self, inputs, target, true_labels):
""":param inputs: predictions :param target: target (soft) labels :param true_lab... | stack_v2_sparse_classes_36k_train_020988 | 15,691 | permissive | [
{
"docstring": ":param alpha: Strength (0-1) of influence from soft labels in training",
"name": "__init__",
"signature": "def __init__(self, alpha=0.95)"
},
{
"docstring": ":param inputs: predictions :param target: target (soft) labels :param true_labels: true (hard) labels :return: loss",
... | 2 | stack_v2_sparse_classes_30k_train_008487 | Implement the Python class `softCrossEntropy` described below.
Class description:
Implement the softCrossEntropy class.
Method signatures and docstrings:
- def __init__(self, alpha=0.95): :param alpha: Strength (0-1) of influence from soft labels in training
- def forward(self, inputs, target, true_labels): :param in... | Implement the Python class `softCrossEntropy` described below.
Class description:
Implement the softCrossEntropy class.
Method signatures and docstrings:
- def __init__(self, alpha=0.95): :param alpha: Strength (0-1) of influence from soft labels in training
- def forward(self, inputs, target, true_labels): :param in... | 5335672f84c0e4461744f9f5e43ae233179daf27 | <|skeleton|>
class softCrossEntropy:
def __init__(self, alpha=0.95):
""":param alpha: Strength (0-1) of influence from soft labels in training"""
<|body_0|>
def forward(self, inputs, target, true_labels):
""":param inputs: predictions :param target: target (soft) labels :param true_lab... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class softCrossEntropy:
def __init__(self, alpha=0.95):
""":param alpha: Strength (0-1) of influence from soft labels in training"""
super(softCrossEntropy, self).__init__()
self.alpha = alpha
return
def forward(self, inputs, target, true_labels):
""":param inputs: predi... | the_stack_v2_python_sparse | cyphercat/train.py | ninalopatina/cyphercat | train | 1 | |
9c6b7d5f36717db491a9ea6ce49dfba1a188c62b | [
"template = '%s.XXXXXX%s' % (prefix, suffix)\nargs = ['mktemp']\nif is_dir:\n args += ['-d']\nargs += ['--tmpdir' if dir is None else '--tmpdir=%s' % dir]\nargs += [template]\nreturn self._device.CheckOutput(args).strip()",
"path = self.mktemp(False, **kargs)\ntry:\n yield path\nfinally:\n self._device.C... | <|body_start_0|>
template = '%s.XXXXXX%s' % (prefix, suffix)
args = ['mktemp']
if is_dir:
args += ['-d']
args += ['--tmpdir' if dir is None else '--tmpdir=%s' % dir]
args += [template]
return self._device.CheckOutput(args).strip()
<|end_body_0|>
<|body_start_... | Provides access to temporary files and directories on DUT-based systems. Examples: temp_dir = self.dut.temp.mktemp(True, '.ext', 'mytmp') with self.dut.temp.TempFile() as tmp_path: self.dut.Call('echo test > %s' % tmp_path) with self.dut.temp.TempDirectory() as tmp_dir: self.dut.Call('gen_output -C %s' % tmp_dir) | TemporaryFiles | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemporaryFiles:
"""Provides access to temporary files and directories on DUT-based systems. Examples: temp_dir = self.dut.temp.mktemp(True, '.ext', 'mytmp') with self.dut.temp.TempFile() as tmp_path: self.dut.Call('echo test > %s' % tmp_path) with self.dut.temp.TempDirectory() as tmp_dir: self.du... | stack_v2_sparse_classes_36k_train_020989 | 3,493 | permissive | [
{
"docstring": "Creates a temporary file or directory on DUT.",
"name": "mktemp",
"signature": "def mktemp(self, is_dir, suffix='', prefix='cftmp', dir=None)"
},
{
"docstring": "Yields an unopened temporary file. The file is not opened, and it is deleted when the context manager is closed if it ... | 3 | null | Implement the Python class `TemporaryFiles` described below.
Class description:
Provides access to temporary files and directories on DUT-based systems. Examples: temp_dir = self.dut.temp.mktemp(True, '.ext', 'mytmp') with self.dut.temp.TempFile() as tmp_path: self.dut.Call('echo test > %s' % tmp_path) with self.dut.t... | Implement the Python class `TemporaryFiles` described below.
Class description:
Provides access to temporary files and directories on DUT-based systems. Examples: temp_dir = self.dut.temp.mktemp(True, '.ext', 'mytmp') with self.dut.temp.TempFile() as tmp_path: self.dut.Call('echo test > %s' % tmp_path) with self.dut.t... | a1b0fccd68987d8cd9c89710adc3c04b868347ec | <|skeleton|>
class TemporaryFiles:
"""Provides access to temporary files and directories on DUT-based systems. Examples: temp_dir = self.dut.temp.mktemp(True, '.ext', 'mytmp') with self.dut.temp.TempFile() as tmp_path: self.dut.Call('echo test > %s' % tmp_path) with self.dut.temp.TempDirectory() as tmp_dir: self.du... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TemporaryFiles:
"""Provides access to temporary files and directories on DUT-based systems. Examples: temp_dir = self.dut.temp.mktemp(True, '.ext', 'mytmp') with self.dut.temp.TempFile() as tmp_path: self.dut.Call('echo test > %s' % tmp_path) with self.dut.temp.TempDirectory() as tmp_dir: self.dut.Call('gen_o... | the_stack_v2_python_sparse | py/device/temp.py | bridder/factory | train | 0 |
2fa91fb56af0c6973bad27064aa87ea9d00b207f | [
"if OPER.imode_Efunc != 'Customize':\n self.freq = OPER.freq\n self.Vdc = OPER.Vdc\n self.Vrf = OPER.Vrf\n self.d_sh = OPER.d_sh\n if OPER.imode_Efunc == 'Dual':\n self.freq2 = OPER.freq2\n self.Vrf2 = OPER.Vrf2",
"E = np.zeros(3)\nE[1] = -self.Vdc / self.d_sh - self.Vrf / self.d_sh *... | <|body_start_0|>
if OPER.imode_Efunc != 'Customize':
self.freq = OPER.freq
self.Vdc = OPER.Vdc
self.Vrf = OPER.Vrf
self.d_sh = OPER.d_sh
if OPER.imode_Efunc == 'Dual':
self.freq2 = OPER.freq2
self.Vrf2 = OPER.Vrf2
<|end_... | Create EFUNC() object just for sheath model. | EFUNC | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EFUNC:
"""Create EFUNC() object just for sheath model."""
def load(self, OPER):
"""Load parameters from obj OPER. OPER: obj, contains all parameters."""
<|body_0|>
def sgl_freq(self, t):
"""E-field function of time with single frquency. The E-field is negative, o... | stack_v2_sparse_classes_36k_train_020990 | 2,007 | no_license | [
{
"docstring": "Load parameters from obj OPER. OPER: obj, contains all parameters.",
"name": "load",
"signature": "def load(self, OPER)"
},
{
"docstring": "E-field function of time with single frquency. The E-field is negative, only along z-axis. E: arr(3) of float, E-field",
"name": "sgl_fr... | 5 | stack_v2_sparse_classes_30k_train_010912 | Implement the Python class `EFUNC` described below.
Class description:
Create EFUNC() object just for sheath model.
Method signatures and docstrings:
- def load(self, OPER): Load parameters from obj OPER. OPER: obj, contains all parameters.
- def sgl_freq(self, t): E-field function of time with single frquency. The E... | Implement the Python class `EFUNC` described below.
Class description:
Create EFUNC() object just for sheath model.
Method signatures and docstrings:
- def load(self, OPER): Load parameters from obj OPER. OPER: obj, contains all parameters.
- def sgl_freq(self, t): E-field function of time with single frquency. The E... | 8a30014179d1c031b6cba2b7a34bac015b1e6ab5 | <|skeleton|>
class EFUNC:
"""Create EFUNC() object just for sheath model."""
def load(self, OPER):
"""Load parameters from obj OPER. OPER: obj, contains all parameters."""
<|body_0|>
def sgl_freq(self, t):
"""E-field function of time with single frquency. The E-field is negative, o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EFUNC:
"""Create EFUNC() object just for sheath model."""
def load(self, OPER):
"""Load parameters from obj OPER. OPER: obj, contains all parameters."""
if OPER.imode_Efunc != 'Customize':
self.freq = OPER.freq
self.Vdc = OPER.Vdc
self.Vrf = OPER.Vrf
... | the_stack_v2_python_sparse | run/Sheath2D/Efunc.py | buckees/Langmuir | train | 0 |
dceb2f2cb00d255e437826b574cbb22b31bf7de1 | [
"partinfo = dict(classes=[], features=[], samples=[])\nfor partname in datadict:\n partition = Partition(datadict[partname], f'{dataset}-{partname}')\n for attr in partinfo:\n partinfo[attr].append(getattr(partition, attr))\n setattr(self, partname.lower(), partition)\nself.classes = tuple(partinfo[... | <|body_start_0|>
partinfo = dict(classes=[], features=[], samples=[])
for partname in datadict:
partition = Partition(datadict[partname], f'{dataset}-{partname}')
for attr in partinfo:
partinfo[attr].append(getattr(partition, attr))
setattr(self, partn... | The Dataset class defines the main interfaces for datasets created with this repo. It instantiates Partition objects for each partition of the the dataset and defines methods for viewing metadata and partition information. :func:`__init__`: instantiates Dataset objects :func:`__repr__`: shows dataset metadata and infor... | Dataset | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataset:
"""The Dataset class defines the main interfaces for datasets created with this repo. It instantiates Partition objects for each partition of the the dataset and defines methods for viewing metadata and partition information. :func:`__init__`: instantiates Dataset objects :func:`__repr__... | stack_v2_sparse_classes_36k_train_020991 | 13,734 | permissive | [
{
"docstring": "This method instantiates a Dataset object with attributes to access the underlying data and labels (as Partition objects), as well as collects and saves partition information and metadata. :param datadict: the partitions to save :type datadict: dict of numpy ndarray objects :param dataset: name ... | 2 | stack_v2_sparse_classes_30k_train_011868 | Implement the Python class `Dataset` described below.
Class description:
The Dataset class defines the main interfaces for datasets created with this repo. It instantiates Partition objects for each partition of the the dataset and defines methods for viewing metadata and partition information. :func:`__init__`: insta... | Implement the Python class `Dataset` described below.
Class description:
The Dataset class defines the main interfaces for datasets created with this repo. It instantiates Partition objects for each partition of the the dataset and defines methods for viewing metadata and partition information. :func:`__init__`: insta... | 5a508b78cccc581b3b99ec2ba179ecb7fa31aafb | <|skeleton|>
class Dataset:
"""The Dataset class defines the main interfaces for datasets created with this repo. It instantiates Partition objects for each partition of the the dataset and defines methods for viewing metadata and partition information. :func:`__init__`: instantiates Dataset objects :func:`__repr__... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dataset:
"""The Dataset class defines the main interfaces for datasets created with this repo. It instantiates Partition objects for each partition of the the dataset and defines methods for viewing metadata and partition information. :func:`__init__`: instantiates Dataset objects :func:`__repr__`: shows data... | the_stack_v2_python_sparse | mlds/datasets.py | sheatsley/datasets | train | 13 |
9f7f6c8356ee33de22be64dbb5c9e4dc14f61a45 | [
"with tf.variable_scope(name):\n self._linear = tf.get_variable('linear', shape=[dim_summary, dim_summary], trainable=True, initializer=tf.initializers.orthogonal())\n self._bilinear = tf.get_variable('bilinear', shape=[dim_latent, dim_summary], trainable=True, initializer=tf.initializers.orthogonal())\nself.... | <|body_start_0|>
with tf.variable_scope(name):
self._linear = tf.get_variable('linear', shape=[dim_summary, dim_summary], trainable=True, initializer=tf.initializers.orthogonal())
self._bilinear = tf.get_variable('bilinear', shape=[dim_latent, dim_summary], trainable=True, initializer=tf... | DGI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DGI:
def __init__(self, dim_latent, dim_summary, name='DGI'):
"""Deep Graph Infomax"""
<|body_0|>
def score(self, graph, histories, states, observations, beliefs, lookaheads):
"""Args: histories: A 2-ary tuple: - global_histories: A (..., B, dH) Tensor. - local_histo... | stack_v2_sparse_classes_36k_train_020992 | 18,953 | no_license | [
{
"docstring": "Deep Graph Infomax",
"name": "__init__",
"signature": "def __init__(self, dim_latent, dim_summary, name='DGI')"
},
{
"docstring": "Args: histories: A 2-ary tuple: - global_histories: A (..., B, dH) Tensor. - local_histories: A (..., B, N, dH) Tensor. states: A 2-ary tuple: - glob... | 2 | stack_v2_sparse_classes_30k_train_015099 | Implement the Python class `DGI` described below.
Class description:
Implement the DGI class.
Method signatures and docstrings:
- def __init__(self, dim_latent, dim_summary, name='DGI'): Deep Graph Infomax
- def score(self, graph, histories, states, observations, beliefs, lookaheads): Args: histories: A 2-ary tuple: ... | Implement the Python class `DGI` described below.
Class description:
Implement the DGI class.
Method signatures and docstrings:
- def __init__(self, dim_latent, dim_summary, name='DGI'): Deep Graph Infomax
- def score(self, graph, histories, states, observations, beliefs, lookaheads): Args: histories: A 2-ary tuple: ... | 056c1578139ce9e342663f03aa208356f0c35fec | <|skeleton|>
class DGI:
def __init__(self, dim_latent, dim_summary, name='DGI'):
"""Deep Graph Infomax"""
<|body_0|>
def score(self, graph, histories, states, observations, beliefs, lookaheads):
"""Args: histories: A 2-ary tuple: - global_histories: A (..., B, dH) Tensor. - local_histo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DGI:
def __init__(self, dim_latent, dim_summary, name='DGI'):
"""Deep Graph Infomax"""
with tf.variable_scope(name):
self._linear = tf.get_variable('linear', shape=[dim_summary, dim_summary], trainable=True, initializer=tf.initializers.orthogonal())
self._bilinear = tf.... | the_stack_v2_python_sparse | auxiliary.py | fanyang01/relational-ssm | train | 4 | |
b66eba0f27ea4c4301190a7243ef02aa631504e7 | [
"self.sim = sim\nself.tokenizer = tokenizer if tokenizer else NGrams(n=6)\nself.minsize = minsize\nself.remove_duplicates = remove_duplicates",
"if not values:\n return list()\nblocks = self._get_blocks(values)\nfreq = values if isinstance(values, Counter) else ONE()\nclusters = defaultdict(Cluster)\nfor block... | <|body_start_0|>
self.sim = sim
self.tokenizer = tokenizer if tokenizer else NGrams(n=6)
self.minsize = minsize
self.remove_duplicates = remove_duplicates
<|end_body_0|>
<|body_start_1|>
if not values:
return list()
blocks = self._get_blocks(values)
f... | Nearest Neighbor clustering algorithm that is based on a hybrid clustring approach. The algorithm works by performing a first pass over the strings in order to group them into blocks of strings that share at least on token (e.g., n-gram). It then uses a given string similarity function to compute similarity between str... | kNNClusterer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class kNNClusterer:
"""Nearest Neighbor clustering algorithm that is based on a hybrid clustring approach. The algorithm works by performing a first pass over the strings in order to group them into blocks of strings that share at least on token (e.g., n-gram). It then uses a given string similarity fu... | stack_v2_sparse_classes_36k_train_020993 | 11,308 | permissive | [
{
"docstring": "Initialize the string tokenizer, the similarity constraint, and the minimal size for generated clusters. Parameters ---------- sim: openclean.function.similarity.base.SimilarityConstraint String similarity constraint for grouping strings in the generated blocks. tokenizer: openclean.function.tok... | 4 | null | Implement the Python class `kNNClusterer` described below.
Class description:
Nearest Neighbor clustering algorithm that is based on a hybrid clustring approach. The algorithm works by performing a first pass over the strings in order to group them into blocks of strings that share at least on token (e.g., n-gram). It... | Implement the Python class `kNNClusterer` described below.
Class description:
Nearest Neighbor clustering algorithm that is based on a hybrid clustring approach. The algorithm works by performing a first pass over the strings in order to group them into blocks of strings that share at least on token (e.g., n-gram). It... | e3d0e04f90468c49f29ca53edc2feb12465c24d5 | <|skeleton|>
class kNNClusterer:
"""Nearest Neighbor clustering algorithm that is based on a hybrid clustring approach. The algorithm works by performing a first pass over the strings in order to group them into blocks of strings that share at least on token (e.g., n-gram). It then uses a given string similarity fu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class kNNClusterer:
"""Nearest Neighbor clustering algorithm that is based on a hybrid clustring approach. The algorithm works by performing a first pass over the strings in order to group them into blocks of strings that share at least on token (e.g., n-gram). It then uses a given string similarity function to com... | the_stack_v2_python_sparse | openclean/cluster/knn.py | Denisfench/openclean-core | train | 0 |
b3bc4aa93366b2409f7bb0ccdc6ea3679dc0e94a | [
"if bundle.obj.latitude is None:\n return None\nreturn float(bundle.obj.latitude)",
"if bundle.obj.longitude is None:\n return None\nreturn float(bundle.obj.longitude)"
] | <|body_start_0|>
if bundle.obj.latitude is None:
return None
return float(bundle.obj.latitude)
<|end_body_0|>
<|body_start_1|>
if bundle.obj.longitude is None:
return None
return float(bundle.obj.longitude)
<|end_body_1|>
| LocationResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocationResource:
def dehydrate_latitude(self, bundle):
"""Overrides the default of strings as serialized DecimalField values"""
<|body_0|>
def dehydrate_longitude(self, bundle):
"""Overrides the default of strings as serialized DecimalField values"""
<|body_... | stack_v2_sparse_classes_36k_train_020994 | 5,945 | no_license | [
{
"docstring": "Overrides the default of strings as serialized DecimalField values",
"name": "dehydrate_latitude",
"signature": "def dehydrate_latitude(self, bundle)"
},
{
"docstring": "Overrides the default of strings as serialized DecimalField values",
"name": "dehydrate_longitude",
"s... | 2 | null | Implement the Python class `LocationResource` described below.
Class description:
Implement the LocationResource class.
Method signatures and docstrings:
- def dehydrate_latitude(self, bundle): Overrides the default of strings as serialized DecimalField values
- def dehydrate_longitude(self, bundle): Overrides the de... | Implement the Python class `LocationResource` described below.
Class description:
Implement the LocationResource class.
Method signatures and docstrings:
- def dehydrate_latitude(self, bundle): Overrides the default of strings as serialized DecimalField values
- def dehydrate_longitude(self, bundle): Overrides the de... | 3ed85e856a026001a1d91d09d31d944c64704824 | <|skeleton|>
class LocationResource:
def dehydrate_latitude(self, bundle):
"""Overrides the default of strings as serialized DecimalField values"""
<|body_0|>
def dehydrate_longitude(self, bundle):
"""Overrides the default of strings as serialized DecimalField values"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LocationResource:
def dehydrate_latitude(self, bundle):
"""Overrides the default of strings as serialized DecimalField values"""
if bundle.obj.latitude is None:
return None
return float(bundle.obj.latitude)
def dehydrate_longitude(self, bundle):
"""Overrides th... | the_stack_v2_python_sparse | scenable/places/api.py | gregarious/betasite | train | 0 | |
601034d873d29dac934b7c63ff0f0a33d36bb082 | [
"super(ContextOnlySoftDotAttention, self).__init__()\nif context_dim is None:\n context_dim = dim\nself.linear_in = nn.Linear(dim, context_dim, bias=False)\nself.sm = nn.Softmax(dim=1)",
"target = self.linear_in(h).unsqueeze(2)\nattn = torch.bmm(context, target).squeeze(2)\nif mask is not None:\n attn.data.... | <|body_start_0|>
super(ContextOnlySoftDotAttention, self).__init__()
if context_dim is None:
context_dim = dim
self.linear_in = nn.Linear(dim, context_dim, bias=False)
self.sm = nn.Softmax(dim=1)
<|end_body_0|>
<|body_start_1|>
target = self.linear_in(h).unsqueeze(2)... | Like SoftDot, but don't concatenat h or perform the non-linearity transform Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT. | ContextOnlySoftDotAttention | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContextOnlySoftDotAttention:
"""Like SoftDot, but don't concatenat h or perform the non-linearity transform Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT."""
def __init__(self, dim, context_dim=None):
"""Initialize layer."""
<|body_0|>
def f... | stack_v2_sparse_classes_36k_train_020995 | 22,228 | permissive | [
{
"docstring": "Initialize layer.",
"name": "__init__",
"signature": "def __init__(self, dim, context_dim=None)"
},
{
"docstring": "Propagate h through the network. h: batch x dim context: batch x seq_len x dim mask: batch x seq_len indices to be masked",
"name": "forward",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_010527 | Implement the Python class `ContextOnlySoftDotAttention` described below.
Class description:
Like SoftDot, but don't concatenat h or perform the non-linearity transform Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT.
Method signatures and docstrings:
- def __init__(self, dim, context_dim=... | Implement the Python class `ContextOnlySoftDotAttention` described below.
Class description:
Like SoftDot, but don't concatenat h or perform the non-linearity transform Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT.
Method signatures and docstrings:
- def __init__(self, dim, context_dim=... | 868fb53d6b7978bbb10439a59e65044c811ee5c2 | <|skeleton|>
class ContextOnlySoftDotAttention:
"""Like SoftDot, but don't concatenat h or perform the non-linearity transform Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT."""
def __init__(self, dim, context_dim=None):
"""Initialize layer."""
<|body_0|>
def f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContextOnlySoftDotAttention:
"""Like SoftDot, but don't concatenat h or perform the non-linearity transform Ref: http://www.aclweb.org/anthology/D15-1166 Adapted from PyTorch OPEN NMT."""
def __init__(self, dim, context_dim=None):
"""Initialize layer."""
super(ContextOnlySoftDotAttention,... | the_stack_v2_python_sparse | tasks/R2R/speaker/model.py | weituo12321/PREVALENT_R2R | train | 8 |
2f4782734481b8acafbdaa84869973fce7efc81b | [
"try:\n response = requests.get(rank_model_url, timeout=TIMEOUT)\n return StringIO(response.text)\nexcept Exception as ex:\n LOG.warning(ex)",
"try:\n return ConfigObj(stringio).dict()\nexcept Exception as ex:\n LOG.error(ex)",
"response = self.fetch_rank_model(rank_model_url)\nconfig = self.pars... | <|body_start_0|>
try:
response = requests.get(rank_model_url, timeout=TIMEOUT)
return StringIO(response.text)
except Exception as ex:
LOG.warning(ex)
<|end_body_0|>
<|body_start_1|>
try:
return ConfigObj(stringio).dict()
except Exception a... | RankModelHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RankModelHandler:
def fetch_rank_model(self, rank_model_url):
"""Send HTTP request to retrieve rank model config file Args: rank_model_url(str): URL to resource containing rank model configuration Returns: StringIO(response.text): A StringIO containing the content of the config file"""
... | stack_v2_sparse_classes_36k_train_020996 | 5,712 | permissive | [
{
"docstring": "Send HTTP request to retrieve rank model config file Args: rank_model_url(str): URL to resource containing rank model configuration Returns: StringIO(response.text): A StringIO containing the content of the config file",
"name": "fetch_rank_model",
"signature": "def fetch_rank_model(self... | 6 | null | Implement the Python class `RankModelHandler` described below.
Class description:
Implement the RankModelHandler class.
Method signatures and docstrings:
- def fetch_rank_model(self, rank_model_url): Send HTTP request to retrieve rank model config file Args: rank_model_url(str): URL to resource containing rank model ... | Implement the Python class `RankModelHandler` described below.
Class description:
Implement the RankModelHandler class.
Method signatures and docstrings:
- def fetch_rank_model(self, rank_model_url): Send HTTP request to retrieve rank model config file Args: rank_model_url(str): URL to resource containing rank model ... | 1e6a633ba0a83495047ee7b66db1ebf690ee465f | <|skeleton|>
class RankModelHandler:
def fetch_rank_model(self, rank_model_url):
"""Send HTTP request to retrieve rank model config file Args: rank_model_url(str): URL to resource containing rank model configuration Returns: StringIO(response.text): A StringIO containing the content of the config file"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RankModelHandler:
def fetch_rank_model(self, rank_model_url):
"""Send HTTP request to retrieve rank model config file Args: rank_model_url(str): URL to resource containing rank model configuration Returns: StringIO(response.text): A StringIO containing the content of the config file"""
try:
... | the_stack_v2_python_sparse | scout/adapter/mongo/rank_model.py | Clinical-Genomics/scout | train | 143 | |
18f3c4e9f1ec2dd0cde3e8094f3c21404dfb3a85 | [
"super().__init__()\nself._id = request_id\nself._project_name = project_name\nself._model_path = model_path\nself._input_precision = input_precision\nself._model_output_path = model_output_path\nself._output_precision = output_precision\nself._mode = mode\nself._workload_path = workload_path\nself._status = status... | <|body_start_0|>
super().__init__()
self._id = request_id
self._project_name = project_name
self._model_path = model_path
self._input_precision = input_precision
self._model_output_path = model_output_path
self._output_precision = output_precision
self._mo... | Create template for workload_list entity. | WorkloadInfo | [
"MIT",
"Intel",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkloadInfo:
"""Create template for workload_list entity."""
def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_output_path: Optional[str], output_precision: Optional[str], mode: Opt... | stack_v2_sparse_classes_36k_train_020997 | 12,851 | permissive | [
{
"docstring": "Initialize configuration WorkloadInfo class.",
"name": "__init__",
"signature": "def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_output_path: Optional[str], output_precision: O... | 3 | null | Implement the Python class `WorkloadInfo` described below.
Class description:
Create template for workload_list entity.
Method signatures and docstrings:
- def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_ou... | Implement the Python class `WorkloadInfo` described below.
Class description:
Create template for workload_list entity.
Method signatures and docstrings:
- def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_ou... | 3976edc4215398e69ce0213f87ec295f5dc96e0e | <|skeleton|>
class WorkloadInfo:
"""Create template for workload_list entity."""
def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_output_path: Optional[str], output_precision: Optional[str], mode: Opt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkloadInfo:
"""Create template for workload_list entity."""
def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_output_path: Optional[str], output_precision: Optional[str], mode: Optional[str], m... | the_stack_v2_python_sparse | neural_compressor/ux/utils/workload/workloads_list.py | Skp80/neural-compressor | train | 0 |
b7751561e1e48816b07c5a13e413056751e3f4b5 | [
"keywords = models.Goal.objects.values_list('keywords', flat=True)\nkeywords = [(kw, kw) for sublist in keywords for kw in sublist if kw]\nkeywords = sorted(set(keywords))\nreturn keywords",
"lookup = self.value()\nif lookup:\n queryset = queryset.filter(keywords__contains=[lookup])\nreturn queryset"
] | <|body_start_0|>
keywords = models.Goal.objects.values_list('keywords', flat=True)
keywords = [(kw, kw) for sublist in keywords for kw in sublist if kw]
keywords = sorted(set(keywords))
return keywords
<|end_body_0|>
<|body_start_1|>
lookup = self.value()
if lookup:
... | An admin list filter based on the values from a model's `keywords` ArrayField. For more info, see the django docs: https://docs.djangoproject.com/en/1.8/ref/contrib/admin/#django.contrib.admin.ModelAdmin.list_filter | ArrayFieldListFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArrayFieldListFilter:
"""An admin list filter based on the values from a model's `keywords` ArrayField. For more info, see the django docs: https://docs.djangoproject.com/en/1.8/ref/contrib/admin/#django.contrib.admin.ModelAdmin.list_filter"""
def lookups(self, request, model_admin):
... | stack_v2_sparse_classes_36k_train_020998 | 23,419 | permissive | [
{
"docstring": "Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The second element is the human-readable name for the option that will appear in the right sidebar.",
"name": "lookups",
"signature": "def lookups(self, request,... | 2 | null | Implement the Python class `ArrayFieldListFilter` described below.
Class description:
An admin list filter based on the values from a model's `keywords` ArrayField. For more info, see the django docs: https://docs.djangoproject.com/en/1.8/ref/contrib/admin/#django.contrib.admin.ModelAdmin.list_filter
Method signature... | Implement the Python class `ArrayFieldListFilter` described below.
Class description:
An admin list filter based on the values from a model's `keywords` ArrayField. For more info, see the django docs: https://docs.djangoproject.com/en/1.8/ref/contrib/admin/#django.contrib.admin.ModelAdmin.list_filter
Method signature... | 3d22179c581ab3da18900483930d5ecc0a5fca73 | <|skeleton|>
class ArrayFieldListFilter:
"""An admin list filter based on the values from a model's `keywords` ArrayField. For more info, see the django docs: https://docs.djangoproject.com/en/1.8/ref/contrib/admin/#django.contrib.admin.ModelAdmin.list_filter"""
def lookups(self, request, model_admin):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArrayFieldListFilter:
"""An admin list filter based on the values from a model's `keywords` ArrayField. For more info, see the django docs: https://docs.djangoproject.com/en/1.8/ref/contrib/admin/#django.contrib.admin.ModelAdmin.list_filter"""
def lookups(self, request, model_admin):
"""Returns a... | the_stack_v2_python_sparse | tndata_backend/goals/admin.py | tndatacommons/tndata_backend | train | 1 |
b2ab6448dc3ef24e707ee73cedaa18b3677d1f13 | [
"result = []\ncount = 1\nfor num in reversed(digits):\n if count == 1:\n sum = num + 1\n if sum > 9:\n result.insert(0, 0)\n else:\n result.insert(0, sum)\n count = 0\n else:\n result.insert(0, num)\nif count == 1:\n result.insert(0, 1)\nreturn r... | <|body_start_0|>
result = []
count = 1
for num in reversed(digits):
if count == 1:
sum = num + 1
if sum > 9:
result.insert(0, 0)
else:
result.insert(0, sum)
count = 0
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def plus_one(self, digits: List[int]) -> List[int]:
"""一个数组加1操作 Args: digits: 数组数字 Returns: 加1后结果"""
<|body_0|>
def plus_one2(self, digits: List[int]) -> List[int]:
"""一个数组加1操作 Args: digits: 数组数字 Returns: 加1后结果"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_020999 | 2,584 | permissive | [
{
"docstring": "一个数组加1操作 Args: digits: 数组数字 Returns: 加1后结果",
"name": "plus_one",
"signature": "def plus_one(self, digits: List[int]) -> List[int]"
},
{
"docstring": "一个数组加1操作 Args: digits: 数组数字 Returns: 加1后结果",
"name": "plus_one2",
"signature": "def plus_one2(self, digits: List[int]) -> ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plus_one(self, digits: List[int]) -> List[int]: 一个数组加1操作 Args: digits: 数组数字 Returns: 加1后结果
- def plus_one2(self, digits: List[int]) -> List[int]: 一个数组加1操作 Args: digits: 数组数字 ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plus_one(self, digits: List[int]) -> List[int]: 一个数组加1操作 Args: digits: 数组数字 Returns: 加1后结果
- def plus_one2(self, digits: List[int]) -> List[int]: 一个数组加1操作 Args: digits: 数组数字 ... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def plus_one(self, digits: List[int]) -> List[int]:
"""一个数组加1操作 Args: digits: 数组数字 Returns: 加1后结果"""
<|body_0|>
def plus_one2(self, digits: List[int]) -> List[int]:
"""一个数组加1操作 Args: digits: 数组数字 Returns: 加1后结果"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def plus_one(self, digits: List[int]) -> List[int]:
"""一个数组加1操作 Args: digits: 数组数字 Returns: 加1后结果"""
result = []
count = 1
for num in reversed(digits):
if count == 1:
sum = num + 1
if sum > 9:
result.inse... | the_stack_v2_python_sparse | src/leetcodepython/math/plus_one_66.py | zhangyu345293721/leetcode | train | 101 |
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