blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
85e097bf77eb7059717f5b98b090a6f8797cb239 | [
"if user is None or user.is_active is False:\n raise ValueError('{\"detail\":\"' + str(_('In order to perform this operation, your account must be active')) + '\"}')\nif user.is_staff:\n images = accounts_models.PublicFeed.objects.all()\nelse:\n images = accounts_models.PublicFeed.objects.filter(user_id=us... | <|body_start_0|>
if user is None or user.is_active is False:
raise ValueError('{"detail":"' + str(_('In order to perform this operation, your account must be active')) + '"}')
if user.is_staff:
images = accounts_models.PublicFeed.objects.all()
else:
images = a... | this class contain a crud for the image upload to public feed 420 | UploadImagePublicProfileService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadImagePublicProfileService:
"""this class contain a crud for the image upload to public feed 420"""
def list(self, user: accounts_models.User) -> accounts_models.PublicFeed:
"""Get all images upload to public feed 420. if user is admin o staff the can see all images upload for a... | stack_v2_sparse_classes_10k_train_004900 | 42,606 | no_license | [
{
"docstring": "Get all images upload to public feed 420. if user is admin o staff the can see all images upload for any user in weedmtach. :param user: user weedmatch :type user: Model User :return: Model PublicFeed :raise: ValueError",
"name": "list",
"signature": "def list(self, user: accounts_models... | 5 | stack_v2_sparse_classes_30k_train_003117 | Implement the Python class `UploadImagePublicProfileService` described below.
Class description:
this class contain a crud for the image upload to public feed 420
Method signatures and docstrings:
- def list(self, user: accounts_models.User) -> accounts_models.PublicFeed: Get all images upload to public feed 420. if ... | Implement the Python class `UploadImagePublicProfileService` described below.
Class description:
this class contain a crud for the image upload to public feed 420
Method signatures and docstrings:
- def list(self, user: accounts_models.User) -> accounts_models.PublicFeed: Get all images upload to public feed 420. if ... | 497b8724d6e02582f28bc9c5a19f93ec21db84d8 | <|skeleton|>
class UploadImagePublicProfileService:
"""this class contain a crud for the image upload to public feed 420"""
def list(self, user: accounts_models.User) -> accounts_models.PublicFeed:
"""Get all images upload to public feed 420. if user is admin o staff the can see all images upload for a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UploadImagePublicProfileService:
"""this class contain a crud for the image upload to public feed 420"""
def list(self, user: accounts_models.User) -> accounts_models.PublicFeed:
"""Get all images upload to public feed 420. if user is admin o staff the can see all images upload for any user in we... | the_stack_v2_python_sparse | accounts/services.py | carlos-o/weedmatchheroku | train | 0 |
008acc477c6de384db81166439581d21a3140acd | [
"if not root:\n return '[]'\nres = [root.val]\nq = collections.deque([root])\nwhile q:\n front = q.popleft()\n if front.left:\n q.append(front.left)\n if front.right:\n q.append(front.right)\n res.append(front.left.val if front.left else 'null')\n res.append(front.right.val if front.... | <|body_start_0|>
if not root:
return '[]'
res = [root.val]
q = collections.deque([root])
while q:
front = q.popleft()
if front.left:
q.append(front.left)
if front.right:
q.append(front.right)
res.... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_004901 | 17,936 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 035ef08434fa1ca781a6fb2f9eed3538b7d20c02 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return '[]'
res = [root.val]
q = collections.deque([root])
while q:
front = q.popleft()
if front.left:
... | the_stack_v2_python_sparse | leetcode_python/Tree/serialize-and-deserialize-binary-tree.py | yennanliu/CS_basics | train | 64 | |
801a861f2d8fab540fb6225be46064eb4f81564a | [
"self.driver.get(detail_url)\nsleep(2)\nself.driver.execute_script('window.scrollTo(0, 1300)')\nreport_title = self.driver.find_element(CarDetail_Locator.REPORT_TITLE).text\ntt_check.assertEqual('检测报告', report_title, '检测报告tab的title，期望是检测报告，实际是%s' % report_title)",
"self.driver.get(detail_url)\nsleep(2)\nself.driv... | <|body_start_0|>
self.driver.get(detail_url)
sleep(2)
self.driver.execute_script('window.scrollTo(0, 1300)')
report_title = self.driver.find_element(CarDetail_Locator.REPORT_TITLE).text
tt_check.assertEqual('检测报告', report_title, '检测报告tab的title，期望是检测报告，实际是%s' % report_title)
<|end... | Report | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Report:
def test_report_title(self):
"""测试检测报告title显示的是否正确@author:zhangyanli"""
<|body_0|>
def test_report_type(self):
"""测试检测报告各类型显示的是否正确@author:zhangyanli"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.driver.get(detail_url)
sleep(2)... | stack_v2_sparse_classes_10k_train_004902 | 1,735 | no_license | [
{
"docstring": "测试检测报告title显示的是否正确@author:zhangyanli",
"name": "test_report_title",
"signature": "def test_report_title(self)"
},
{
"docstring": "测试检测报告各类型显示的是否正确@author:zhangyanli",
"name": "test_report_type",
"signature": "def test_report_type(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000097 | Implement the Python class `Report` described below.
Class description:
Implement the Report class.
Method signatures and docstrings:
- def test_report_title(self): 测试检测报告title显示的是否正确@author:zhangyanli
- def test_report_type(self): 测试检测报告各类型显示的是否正确@author:zhangyanli | Implement the Python class `Report` described below.
Class description:
Implement the Report class.
Method signatures and docstrings:
- def test_report_title(self): 测试检测报告title显示的是否正确@author:zhangyanli
- def test_report_type(self): 测试检测报告各类型显示的是否正确@author:zhangyanli
<|skeleton|>
class Report:
def test_report_ti... | a73e4ed1dc02f05e93f11788591efe68109fd277 | <|skeleton|>
class Report:
def test_report_title(self):
"""测试检测报告title显示的是否正确@author:zhangyanli"""
<|body_0|>
def test_report_type(self):
"""测试检测报告各类型显示的是否正确@author:zhangyanli"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Report:
def test_report_title(self):
"""测试检测报告title显示的是否正确@author:zhangyanli"""
self.driver.get(detail_url)
sleep(2)
self.driver.execute_script('window.scrollTo(0, 1300)')
report_title = self.driver.find_element(CarDetail_Locator.REPORT_TITLE).text
tt_check.asse... | the_stack_v2_python_sparse | taocheM/test_detail/test_carreport.py | zhangyanli616/TaoCheAuto | train | 0 | |
980de806b394bb46849606d7e27fdf360354e87e | [
"super().setUpTestData()\ncompanies = [Company(name=f'Company {idx}', description='Some company') for idx in range(3)]\nCompany.objects.bulk_create(companies)\ncontacts = []\nfor cmp in Company.objects.all():\n contacts += [Contact(company=cmp, name=f'My name {idx}') for idx in range(3)]\nContact.objects.bulk_cr... | <|body_start_0|>
super().setUpTestData()
companies = [Company(name=f'Company {idx}', description='Some company') for idx in range(3)]
Company.objects.bulk_create(companies)
contacts = []
for cmp in Company.objects.all():
contacts += [Contact(company=cmp, name=f'My nam... | Tests for the Contact models | ContactTest | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContactTest:
"""Tests for the Contact models"""
def setUpTestData(cls):
"""Perform init for this test class"""
<|body_0|>
def test_list(self):
"""Test company list API endpoint"""
<|body_1|>
def test_create(self):
"""Test that we can create a... | stack_v2_sparse_classes_10k_train_004903 | 19,439 | permissive | [
{
"docstring": "Perform init for this test class",
"name": "setUpTestData",
"signature": "def setUpTestData(cls)"
},
{
"docstring": "Test company list API endpoint",
"name": "test_list",
"signature": "def test_list(self)"
},
{
"docstring": "Test that we can create a new Contact o... | 5 | stack_v2_sparse_classes_30k_train_001309 | Implement the Python class `ContactTest` described below.
Class description:
Tests for the Contact models
Method signatures and docstrings:
- def setUpTestData(cls): Perform init for this test class
- def test_list(self): Test company list API endpoint
- def test_create(self): Test that we can create a new Contact ob... | Implement the Python class `ContactTest` described below.
Class description:
Tests for the Contact models
Method signatures and docstrings:
- def setUpTestData(cls): Perform init for this test class
- def test_list(self): Test company list API endpoint
- def test_create(self): Test that we can create a new Contact ob... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class ContactTest:
"""Tests for the Contact models"""
def setUpTestData(cls):
"""Perform init for this test class"""
<|body_0|>
def test_list(self):
"""Test company list API endpoint"""
<|body_1|>
def test_create(self):
"""Test that we can create a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ContactTest:
"""Tests for the Contact models"""
def setUpTestData(cls):
"""Perform init for this test class"""
super().setUpTestData()
companies = [Company(name=f'Company {idx}', description='Some company') for idx in range(3)]
Company.objects.bulk_create(companies)
... | the_stack_v2_python_sparse | InvenTree/company/test_api.py | inventree/InvenTree | train | 3,077 |
f8bb3e91da6541b197aad0efae6ec0c9126fb60f | [
"self.pr_state = pr_state\nself._default_min = 0.8 * self.pr_state.d_max\nself._default_max = 1.2 * self.pr_state.d_max",
"if dmin is None:\n dmin = self._default_min\nif dmax is None:\n dmax = self._default_max\nresults = Results()\nfor i in range(npts):\n d = dmin + i * (dmax - dmin) / (npts - 1.0)\n ... | <|body_start_0|>
self.pr_state = pr_state
self._default_min = 0.8 * self.pr_state.d_max
self._default_max = 1.2 * self.pr_state.d_max
<|end_body_0|>
<|body_start_1|>
if dmin is None:
dmin = self._default_min
if dmax is None:
dmax = self._default_max
... | The explorer class | DistExplorer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DistExplorer:
"""The explorer class"""
def __init__(self, pr_state):
"""Initialization. :param pr_state: sas.sascalc.pr.invertor.Invertor object"""
<|body_0|>
def __call__(self, dmin=None, dmax=None, npts=10):
"""Compute the outputs as a function of D_max. :param... | stack_v2_sparse_classes_10k_train_004904 | 3,307 | permissive | [
{
"docstring": "Initialization. :param pr_state: sas.sascalc.pr.invertor.Invertor object",
"name": "__init__",
"signature": "def __init__(self, pr_state)"
},
{
"docstring": "Compute the outputs as a function of D_max. :param dmin: minimum value for D_max :param dmax: maximum value for D_max :par... | 2 | stack_v2_sparse_classes_30k_train_007108 | Implement the Python class `DistExplorer` described below.
Class description:
The explorer class
Method signatures and docstrings:
- def __init__(self, pr_state): Initialization. :param pr_state: sas.sascalc.pr.invertor.Invertor object
- def __call__(self, dmin=None, dmax=None, npts=10): Compute the outputs as a func... | Implement the Python class `DistExplorer` described below.
Class description:
The explorer class
Method signatures and docstrings:
- def __init__(self, pr_state): Initialization. :param pr_state: sas.sascalc.pr.invertor.Invertor object
- def __call__(self, dmin=None, dmax=None, npts=10): Compute the outputs as a func... | 55b1e9f6db58e33729f2a93b7dd1d8bf255b46f7 | <|skeleton|>
class DistExplorer:
"""The explorer class"""
def __init__(self, pr_state):
"""Initialization. :param pr_state: sas.sascalc.pr.invertor.Invertor object"""
<|body_0|>
def __call__(self, dmin=None, dmax=None, npts=10):
"""Compute the outputs as a function of D_max. :param... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DistExplorer:
"""The explorer class"""
def __init__(self, pr_state):
"""Initialization. :param pr_state: sas.sascalc.pr.invertor.Invertor object"""
self.pr_state = pr_state
self._default_min = 0.8 * self.pr_state.d_max
self._default_max = 1.2 * self.pr_state.d_max
def... | the_stack_v2_python_sparse | src/sas/sascalc/pr/distance_explorer.py | SasView/sasview | train | 48 |
e2837251d0e687836465e0cb1a86cf825cfccb92 | [
"date_time_string = self._FormatDateTime(output_mediator, event, event_data, event_data_stream)\ntimestamp_description = event.timestamp_desc or 'UNKNOWN'\nmessage = self._FormatMessage(output_mediator, event, event_data, event_data_stream)\nmessage = message.replace(self._DESCRIPTION_FIELD_DELIMITER, ' ')\nreturn ... | <|body_start_0|>
date_time_string = self._FormatDateTime(output_mediator, event, event_data, event_data_stream)
timestamp_description = event.timestamp_desc or 'UNKNOWN'
message = self._FormatMessage(output_mediator, event, event_data, event_data_stream)
message = message.replace(self._D... | TLN output module field formatting helper. | TLNFieldFormattingHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TLNFieldFormattingHelper:
"""TLN output module field formatting helper."""
def _FormatDescription(self, output_mediator, event, event_data, event_data_stream):
"""Formats a description field. Args: output_mediator (OutputMediator): mediates interactions between output modules and oth... | stack_v2_sparse_classes_10k_train_004905 | 5,497 | permissive | [
{
"docstring": "Formats a description field. Args: output_mediator (OutputMediator): mediates interactions between output modules and other components, such as storage and dfVFS. event (EventObject): event. event_data (EventData): event data. event_data_stream (EventDataStream): event data stream. Returns: str:... | 3 | stack_v2_sparse_classes_30k_train_003146 | Implement the Python class `TLNFieldFormattingHelper` described below.
Class description:
TLN output module field formatting helper.
Method signatures and docstrings:
- def _FormatDescription(self, output_mediator, event, event_data, event_data_stream): Formats a description field. Args: output_mediator (OutputMediat... | Implement the Python class `TLNFieldFormattingHelper` described below.
Class description:
TLN output module field formatting helper.
Method signatures and docstrings:
- def _FormatDescription(self, output_mediator, event, event_data, event_data_stream): Formats a description field. Args: output_mediator (OutputMediat... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class TLNFieldFormattingHelper:
"""TLN output module field formatting helper."""
def _FormatDescription(self, output_mediator, event, event_data, event_data_stream):
"""Formats a description field. Args: output_mediator (OutputMediator): mediates interactions between output modules and oth... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TLNFieldFormattingHelper:
"""TLN output module field formatting helper."""
def _FormatDescription(self, output_mediator, event, event_data, event_data_stream):
"""Formats a description field. Args: output_mediator (OutputMediator): mediates interactions between output modules and other components... | the_stack_v2_python_sparse | plaso/output/tln.py | log2timeline/plaso | train | 1,506 |
371f7250db3db5a1ed091f2cfa2d49854ae3ca24 | [
"dict = {}\nfor each in nums:\n if each not in dict:\n dict[each] = 1\n else:\n dict[each] += 1\nres = []\nfor each in dict.keys():\n if dict[each] == 2:\n res.append(each)\nreturn res",
"a = []\nb = set()\nfor each in nums:\n if each in b:\n a.append(each)\n else:\n ... | <|body_start_0|>
dict = {}
for each in nums:
if each not in dict:
dict[each] = 1
else:
dict[each] += 1
res = []
for each in dict.keys():
if dict[each] == 2:
res.append(each)
return res
<|end_body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicates(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findDuplicates2(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dict = {}
for each... | stack_v2_sparse_classes_10k_train_004906 | 724 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findDuplicates",
"signature": "def findDuplicates(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findDuplicates2",
"signature": "def findDuplicates2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicates(self, nums): :type nums: List[int] :rtype: List[int]
- def findDuplicates2(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicates(self, nums): :type nums: List[int] :rtype: List[int]
- def findDuplicates2(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
class Solution:
... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def findDuplicates(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findDuplicates2(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicates(self, nums):
""":type nums: List[int] :rtype: List[int]"""
dict = {}
for each in nums:
if each not in dict:
dict[each] = 1
else:
dict[each] += 1
res = []
for each in dict.keys():
... | the_stack_v2_python_sparse | findDuplicates.py | NeilWangziyu/Leetcode_py | train | 2 | |
78eac0d7ab32ee63c9542b0a7e7ed12ea5fe9fcf | [
"super(HonourAutoCombat, self).start()\nfor char in self.characters.values():\n character = char['char']\n character.start_auto_combat_skill()",
"for char in self.characters.values():\n character = char['char']\n character.stop_auto_combat_skill()\nawait super(HonourAutoCombat, self).finish()"
] | <|body_start_0|>
super(HonourAutoCombat, self).start()
for char in self.characters.values():
character = char['char']
character.start_auto_combat_skill()
<|end_body_0|>
<|body_start_1|>
for char in self.characters.values():
character = char['char']
... | This implements the honour combat handler. | HonourAutoCombat | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HonourAutoCombat:
"""This implements the honour combat handler."""
def start(self):
"""Start a combat, make all NPCs to cast skills automatically."""
<|body_0|>
async def finish(self):
"""Finish a combat. Send results to players, and kill all failed characters.""... | stack_v2_sparse_classes_10k_train_004907 | 856 | permissive | [
{
"docstring": "Start a combat, make all NPCs to cast skills automatically.",
"name": "start",
"signature": "def start(self)"
},
{
"docstring": "Finish a combat. Send results to players, and kill all failed characters.",
"name": "finish",
"signature": "async def finish(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000698 | Implement the Python class `HonourAutoCombat` described below.
Class description:
This implements the honour combat handler.
Method signatures and docstrings:
- def start(self): Start a combat, make all NPCs to cast skills automatically.
- async def finish(self): Finish a combat. Send results to players, and kill all... | Implement the Python class `HonourAutoCombat` described below.
Class description:
This implements the honour combat handler.
Method signatures and docstrings:
- def start(self): Start a combat, make all NPCs to cast skills automatically.
- async def finish(self): Finish a combat. Send results to players, and kill all... | 5fa06b29bf800646dc4da5851fdf7a1f299f15a7 | <|skeleton|>
class HonourAutoCombat:
"""This implements the honour combat handler."""
def start(self):
"""Start a combat, make all NPCs to cast skills automatically."""
<|body_0|>
async def finish(self):
"""Finish a combat. Send results to players, and kill all failed characters.""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HonourAutoCombat:
"""This implements the honour combat handler."""
def start(self):
"""Start a combat, make all NPCs to cast skills automatically."""
super(HonourAutoCombat, self).start()
for char in self.characters.values():
character = char['char']
charac... | the_stack_v2_python_sparse | muddery/server/combat/combat_runner/honour_auto_combat.py | muddery/muddery | train | 139 |
b1a650b937b507391196567a83dec206663e2280 | [
"self._helper = helper.ImportHelper()\nwith tempfile.NamedTemporaryFile('w', suffix='.yaml') as fw:\n fw.write(MOCK_CONFIG)\n fw.seek(0)\n self._helper.add_config(fw.name)",
"streamer = MockStreamer()\nself._helper.configure_streamer(streamer, data_type='foo:no')\nself.assertEqual(streamer.format_string,... | <|body_start_0|>
self._helper = helper.ImportHelper()
with tempfile.NamedTemporaryFile('w', suffix='.yaml') as fw:
fw.write(MOCK_CONFIG)
fw.seek(0)
self._helper.add_config(fw.name)
<|end_body_0|>
<|body_start_1|>
streamer = MockStreamer()
self._helper... | Test Timesketch import helper. | TimesketchHelperTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimesketchHelperTest:
"""Test Timesketch import helper."""
def setUp(self):
"""Set up the test."""
<|body_0|>
def test_not_config(self):
"""Test a helper that does not match."""
<|body_1|>
def test_sub_column(self):
"""Test a helper that matc... | stack_v2_sparse_classes_10k_train_004908 | 4,792 | permissive | [
{
"docstring": "Set up the test.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test a helper that does not match.",
"name": "test_not_config",
"signature": "def test_not_config(self)"
},
{
"docstring": "Test a helper that matches on sub columns.",
"name... | 5 | null | Implement the Python class `TimesketchHelperTest` described below.
Class description:
Test Timesketch import helper.
Method signatures and docstrings:
- def setUp(self): Set up the test.
- def test_not_config(self): Test a helper that does not match.
- def test_sub_column(self): Test a helper that matches on sub colu... | Implement the Python class `TimesketchHelperTest` described below.
Class description:
Test Timesketch import helper.
Method signatures and docstrings:
- def setUp(self): Set up the test.
- def test_not_config(self): Test a helper that does not match.
- def test_sub_column(self): Test a helper that matches on sub colu... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class TimesketchHelperTest:
"""Test Timesketch import helper."""
def setUp(self):
"""Set up the test."""
<|body_0|>
def test_not_config(self):
"""Test a helper that does not match."""
<|body_1|>
def test_sub_column(self):
"""Test a helper that matc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TimesketchHelperTest:
"""Test Timesketch import helper."""
def setUp(self):
"""Set up the test."""
self._helper = helper.ImportHelper()
with tempfile.NamedTemporaryFile('w', suffix='.yaml') as fw:
fw.write(MOCK_CONFIG)
fw.seek(0)
self._helper.ad... | the_stack_v2_python_sparse | importer_client/python/timesketch_import_client/helper_test.py | google/timesketch | train | 2,263 |
84c7b4672491ecd3605e73296a97ef10b2a7eeac | [
"if self.end and self.start and (self.start >= self.end):\n self.not_valid('Start date after end date?', 'Consistency error', self.start)\nif not self.end and (not self.duration):\n self.not_valid('Either end or a duration must be specified', 'Consistency Error', self.end)\nif self.end is not None:\n self.... | <|body_start_0|>
if self.end and self.start and (self.start >= self.end):
self.not_valid('Start date after end date?', 'Consistency error', self.start)
if not self.end and (not self.duration):
self.not_valid('Either end or a duration must be specified', 'Consistency Error', self.... | Command to create a new Sprint | CreateSprintCommand | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateSprintCommand:
"""Command to create a new Sprint"""
def consistency_validation(self, env):
"""Validate the consistency of dates and duration together, the individual parameter format validation has already occurred, now we check the relation between them, in particular: start <... | stack_v2_sparse_classes_10k_train_004909 | 46,751 | no_license | [
{
"docstring": "Validate the consistency of dates and duration together, the individual parameter format validation has already occurred, now we check the relation between them, in particular: start < end if end is not present, duration must be if duration is not present, end must be",
"name": "consistency_... | 3 | null | Implement the Python class `CreateSprintCommand` described below.
Class description:
Command to create a new Sprint
Method signatures and docstrings:
- def consistency_validation(self, env): Validate the consistency of dates and duration together, the individual parameter format validation has already occurred, now w... | Implement the Python class `CreateSprintCommand` described below.
Class description:
Command to create a new Sprint
Method signatures and docstrings:
- def consistency_validation(self, env): Validate the consistency of dates and duration together, the individual parameter format validation has already occurred, now w... | 1059b76554363004887b2a60953957f413b80bb0 | <|skeleton|>
class CreateSprintCommand:
"""Command to create a new Sprint"""
def consistency_validation(self, env):
"""Validate the consistency of dates and duration together, the individual parameter format validation has already occurred, now we check the relation between them, in particular: start <... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CreateSprintCommand:
"""Command to create a new Sprint"""
def consistency_validation(self, env):
"""Validate the consistency of dates and duration together, the individual parameter format validation has already occurred, now we check the relation between them, in particular: start < end if end i... | the_stack_v2_python_sparse | agilo/scrum/sprint/controller.py | djangsters/agilo | train | 0 |
39ec904b209ac1263abcd6a99fb489bc874cdea1 | [
"if handler_config is None:\n raise CSVFileToSQLHandlerError('None passed as handler config.')\nself.name = handler_config[CONFIG_NAME]\nself.source = handler_config[CONFIG_SOURCE]\nself.exitonfailure = handler_config[CONFIG_EXITONFAILURE]\nself.recursive = handler_config[CONFIG_RECURSIVE]\nself.delete_source = ... | <|body_start_0|>
if handler_config is None:
raise CSVFileToSQLHandlerError('None passed as handler config.')
self.name = handler_config[CONFIG_NAME]
self.source = handler_config[CONFIG_SOURCE]
self.exitonfailure = handler_config[CONFIG_EXITONFAILURE]
self.recursive = ... | Import CSV file to MySQL database. Read in CSV file and insert/update rows within a given MySQL database/table. If no key attribute is specified then the rows are inserted otherwise updated. Attributes: name : Name of handler object source: Directory to watch for files recursive: Boolean == true perform recursive file ... | CSVFileToSQLHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSVFileToSQLHandler:
"""Import CSV file to MySQL database. Read in CSV file and insert/update rows within a given MySQL database/table. If no key attribute is specified then the rows are inserted otherwise updated. Attributes: name : Name of handler object source: Directory to watch for files rec... | stack_v2_sparse_classes_10k_train_004910 | 5,607 | permissive | [
{
"docstring": "Initialise handler attributes. Args: handler_config (ConfigDict): Handler configuration. Raises: CSVFileToSQLHandlerError: None passed as handler configuration.",
"name": "__init__",
"signature": "def __init__(self, handler_config: ConfigDict) -> None"
},
{
"docstring": "Import C... | 2 | stack_v2_sparse_classes_30k_train_000935 | Implement the Python class `CSVFileToSQLHandler` described below.
Class description:
Import CSV file to MySQL database. Read in CSV file and insert/update rows within a given MySQL database/table. If no key attribute is specified then the rows are inserted otherwise updated. Attributes: name : Name of handler object s... | Implement the Python class `CSVFileToSQLHandler` described below.
Class description:
Import CSV file to MySQL database. Read in CSV file and insert/update rows within a given MySQL database/table. If no key attribute is specified then the rows are inserted otherwise updated. Attributes: name : Name of handler object s... | abbd95b0ddd9da577b6cad69708f2e31db694d94 | <|skeleton|>
class CSVFileToSQLHandler:
"""Import CSV file to MySQL database. Read in CSV file and insert/update rows within a given MySQL database/table. If no key attribute is specified then the rows are inserted otherwise updated. Attributes: name : Name of handler object source: Directory to watch for files rec... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CSVFileToSQLHandler:
"""Import CSV file to MySQL database. Read in CSV file and insert/update rows within a given MySQL database/table. If no key attribute is specified then the rows are inserted otherwise updated. Attributes: name : Name of handler object source: Directory to watch for files recursive: Boole... | the_stack_v2_python_sparse | FPE/builtin/csvfile_to_sql_handler.py | clockworkengineer/Constrictor | train | 1 |
54b3e82178d6d185c5df7325c906c948b1d10ad5 | [
"words.sort()\nwords += ['z']\nstack = []\nret = ''\nlength_ret = 0\nfor i in range(len(words)):\n s = words[i]\n length_s = len(s)\n if length_s == 1:\n if stack and len(stack[-1]) > length_ret:\n ret = stack[-1]\n length_ret = len(ret)\n stack = [words[i]]\n else:\n... | <|body_start_0|>
words.sort()
words += ['z']
stack = []
ret = ''
length_ret = 0
for i in range(len(words)):
s = words[i]
length_s = len(s)
if length_s == 1:
if stack and len(stack[-1]) > length_ret:
r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestWord(self, words):
""":type words: List[str] :rtype: str"""
<|body_0|>
def longestWord2(self, words):
""":type words: List[str] :rtype: str"""
<|body_1|>
def longestWord1(self, words):
""":type words: List[str] :rtype: str"""... | stack_v2_sparse_classes_10k_train_004911 | 2,692 | no_license | [
{
"docstring": ":type words: List[str] :rtype: str",
"name": "longestWord",
"signature": "def longestWord(self, words)"
},
{
"docstring": ":type words: List[str] :rtype: str",
"name": "longestWord2",
"signature": "def longestWord2(self, words)"
},
{
"docstring": ":type words: Lis... | 3 | stack_v2_sparse_classes_30k_train_000747 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestWord(self, words): :type words: List[str] :rtype: str
- def longestWord2(self, words): :type words: List[str] :rtype: str
- def longestWord1(self, words): :type words:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestWord(self, words): :type words: List[str] :rtype: str
- def longestWord2(self, words): :type words: List[str] :rtype: str
- def longestWord1(self, words): :type words:... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def longestWord(self, words):
""":type words: List[str] :rtype: str"""
<|body_0|>
def longestWord2(self, words):
""":type words: List[str] :rtype: str"""
<|body_1|>
def longestWord1(self, words):
""":type words: List[str] :rtype: str"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def longestWord(self, words):
""":type words: List[str] :rtype: str"""
words.sort()
words += ['z']
stack = []
ret = ''
length_ret = 0
for i in range(len(words)):
s = words[i]
length_s = len(s)
if length_s == ... | the_stack_v2_python_sparse | python/leetcode_bak/720_Longest_Word_in_Dictionary.py | bobcaoge/my-code | train | 0 | |
3ea752b496dd506b0ef584709aefc59c05417052 | [
"if not root:\n return json.dumps([])\narr = []\nqueue = [[root, -1]]\nwhile queue:\n tmp = queue.pop(0)\n cur, parentIdx = (tmp[0], tmp[1])\n arr.append([cur.val, parentIdx])\n if cur.left:\n queue.append([cur.left, len(arr) - 1])\n if cur.right:\n queue.append([cur.right, len(arr) ... | <|body_start_0|>
if not root:
return json.dumps([])
arr = []
queue = [[root, -1]]
while queue:
tmp = queue.pop(0)
cur, parentIdx = (tmp[0], tmp[1])
arr.append([cur.val, parentIdx])
if cur.left:
queue.append([cur.... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_10k_train_004912 | 1,317 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_007175 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 6c716ee37fcb82387f050422f578daa142926101 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
if not root:
return json.dumps([])
arr = []
queue = [[root, -1]]
while queue:
tmp = queue.pop(0)
cur, parentIdx = (tmp[0], tmp[1])
... | the_stack_v2_python_sparse | src/449.py | yibwu/leetcode | train | 0 | |
305fee1943e236aa1338f3a083890bf0053eaec6 | [
"if self.dialog is None:\n self.dialog = TextureBakerDlg()\nreturn self.dialog.Open(dlgtype=c4d.DLG_TYPE_ASYNC, pluginid=PLUGIN_ID, defaultw=250, defaulth=50)",
"if self.dialog is None:\n self.dialog = TextureBakerDlg()\nreturn self.dialog.Restore(pluginid=PLUGIN_ID, secret=sec_ref)"
] | <|body_start_0|>
if self.dialog is None:
self.dialog = TextureBakerDlg()
return self.dialog.Open(dlgtype=c4d.DLG_TYPE_ASYNC, pluginid=PLUGIN_ID, defaultw=250, defaulth=50)
<|end_body_0|>
<|body_start_1|>
if self.dialog is None:
self.dialog = TextureBakerDlg()
ret... | Command Data class that holds the TextureBakerDlg instance. | TextureBakerData | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextureBakerData:
"""Command Data class that holds the TextureBakerDlg instance."""
def Execute(self, doc):
"""Called when the user Execute the command (CallCommand or a clicks on the Command from the plugin menu) Args: doc (c4d.documents.BaseDocument): the current active document Re... | stack_v2_sparse_classes_10k_train_004913 | 10,936 | permissive | [
{
"docstring": "Called when the user Execute the command (CallCommand or a clicks on the Command from the plugin menu) Args: doc (c4d.documents.BaseDocument): the current active document Returns: bool: True if the command success",
"name": "Execute",
"signature": "def Execute(self, doc)"
},
{
"d... | 2 | null | Implement the Python class `TextureBakerData` described below.
Class description:
Command Data class that holds the TextureBakerDlg instance.
Method signatures and docstrings:
- def Execute(self, doc): Called when the user Execute the command (CallCommand or a clicks on the Command from the plugin menu) Args: doc (c4... | Implement the Python class `TextureBakerData` described below.
Class description:
Command Data class that holds the TextureBakerDlg instance.
Method signatures and docstrings:
- def Execute(self, doc): Called when the user Execute the command (CallCommand or a clicks on the Command from the plugin menu) Args: doc (c4... | b1ea3fce533df34094bc3d0bd6460dfb84306e53 | <|skeleton|>
class TextureBakerData:
"""Command Data class that holds the TextureBakerDlg instance."""
def Execute(self, doc):
"""Called when the user Execute the command (CallCommand or a clicks on the Command from the plugin menu) Args: doc (c4d.documents.BaseDocument): the current active document Re... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TextureBakerData:
"""Command Data class that holds the TextureBakerDlg instance."""
def Execute(self, doc):
"""Called when the user Execute the command (CallCommand or a clicks on the Command from the plugin menu) Args: doc (c4d.documents.BaseDocument): the current active document Returns: bool: ... | the_stack_v2_python_sparse | plugins/py-texture_baker_r18/py-texture_baker_r18.pyp | PluginCafe/cinema4d_py_sdk_extended | train | 112 |
b552b57e885cc03f71d154a606903e93c7d561f0 | [
"self.signatures = signature_dict\nself.ssgsea_kwds = ssgsea_kwds\nself.all_ids = reduce(lambda x, y: x.union(y), self.signatures.values(), set())",
"series_in = False\nif isinstance(sample_data, pd.Series):\n sample_data = pd.DataFrame(sample_data)\n series_in = True\nif sample_data.index.duplicated().any(... | <|body_start_0|>
self.signatures = signature_dict
self.ssgsea_kwds = ssgsea_kwds
self.all_ids = reduce(lambda x, y: x.union(y), self.signatures.values(), set())
<|end_body_0|>
<|body_start_1|>
series_in = False
if isinstance(sample_data, pd.Series):
sample_data = pd.... | Basic classifier that uses pre-defined signatures to score samples and assess classification. | ssGSEAClassifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ssGSEAClassifier:
"""Basic classifier that uses pre-defined signatures to score samples and assess classification."""
def __init__(self, signature_dict, **ssgsea_kwds):
""":param signature_dict: Dictionary. Keys are the class name, values are iterables of genes / probes or any other ... | stack_v2_sparse_classes_10k_train_004914 | 3,530 | no_license | [
{
"docstring": ":param signature_dict: Dictionary. Keys are the class name, values are iterables of genes / probes or any other row index :param ssgsea_kwds: Any additional kwargs are passed directly to the ssgsea algorithm.",
"name": "__init__",
"signature": "def __init__(self, signature_dict, **ssgsea... | 2 | stack_v2_sparse_classes_30k_train_006283 | Implement the Python class `ssGSEAClassifier` described below.
Class description:
Basic classifier that uses pre-defined signatures to score samples and assess classification.
Method signatures and docstrings:
- def __init__(self, signature_dict, **ssgsea_kwds): :param signature_dict: Dictionary. Keys are the class n... | Implement the Python class `ssGSEAClassifier` described below.
Class description:
Basic classifier that uses pre-defined signatures to score samples and assess classification.
Method signatures and docstrings:
- def __init__(self, signature_dict, **ssgsea_kwds): :param signature_dict: Dictionary. Keys are the class n... | 3cb6fa0e763ddc0a375fcd99a55eab5f9df26fe3 | <|skeleton|>
class ssGSEAClassifier:
"""Basic classifier that uses pre-defined signatures to score samples and assess classification."""
def __init__(self, signature_dict, **ssgsea_kwds):
""":param signature_dict: Dictionary. Keys are the class name, values are iterables of genes / probes or any other ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ssGSEAClassifier:
"""Basic classifier that uses pre-defined signatures to score samples and assess classification."""
def __init__(self, signature_dict, **ssgsea_kwds):
""":param signature_dict: Dictionary. Keys are the class name, values are iterables of genes / probes or any other row index :pa... | the_stack_v2_python_sparse | classification/signature.py | gaberosser/qmul-bioinf | train | 3 |
be76ad3d413e402df7e6ac137d0d26a444ef98f9 | [
"super().__init__(2, 1, seed)\nself.stamp_size = stamp_size\nself.max_shift = max_shift if max_shift is not None else self.stamp_size / 10.0\nself.mag_name = mag_name\nself.bright_cut = bright_cut\nself.dim_cut = dim_cut",
"if self.mag_name not in table.colnames:\n raise ValueError(f\"Catalog must have '{self.... | <|body_start_0|>
super().__init__(2, 1, seed)
self.stamp_size = stamp_size
self.max_shift = max_shift if max_shift is not None else self.stamp_size / 10.0
self.mag_name = mag_name
self.bright_cut = bright_cut
self.dim_cut = dim_cut
<|end_body_0|>
<|body_start_1|>
... | Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cut` and the dim galaxy is chosen with magnitude cut larger than `bright_cut` and... | PairSampling | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PairSampling:
"""Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cut` and the dim galaxy is chosen with ma... | stack_v2_sparse_classes_10k_train_004915 | 12,943 | permissive | [
{
"docstring": "Initializes the PairSampling function. Args: stamp_size: Size of the desired stamp (in arcseconds). max_shift: Maximum value of shift from center. If None then its set as one-tenth the stamp size (in arcseconds). mag_name: Name of the magnitude column in the catalog to be used. seed: See parent ... | 2 | stack_v2_sparse_classes_30k_train_005535 | Implement the Python class `PairSampling` described below.
Class description:
Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cu... | Implement the Python class `PairSampling` described below.
Class description:
Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cu... | f5b716a373f130238100db8980aa0d282822983a | <|skeleton|>
class PairSampling:
"""Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cut` and the dim galaxy is chosen with ma... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PairSampling:
"""Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cut` and the dim galaxy is chosen with magnitude cut l... | the_stack_v2_python_sparse | btk/sampling_functions.py | LSSTDESC/BlendingToolKit | train | 22 |
2e1fd26f62781ba9df41587ee8cbae5e72f487e1 | [
"if t == MOUSE:\n return [(m, p, 3 - t) for p in graph[c] if p != 0]\nelif t == CAT:\n return [(p, c, 3 - t) for p in graph[m] if p != 0]",
"childrenCount = {}\nfor m in range(len(graph)):\n for c in range(len(graph)):\n childrenCount[m, c, MOUSE] = len(graph[m])\n childrenCount[m, c, CAT] ... | <|body_start_0|>
if t == MOUSE:
return [(m, p, 3 - t) for p in graph[c] if p != 0]
elif t == CAT:
return [(p, c, 3 - t) for p in graph[m] if p != 0]
<|end_body_0|>
<|body_start_1|>
childrenCount = {}
for m in range(len(graph)):
for c in range(len(grap... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getParents(self, graph, m, c, t):
"""get parent states of (m, c, t)"""
<|body_0|>
def catMouseGame(self, graph):
"""Let (m,c,t) be the state of the game. m is the mouse location, c is cat location, t is 1 means it's mouse's turn, t is 2 means it's cat' ... | stack_v2_sparse_classes_10k_train_004916 | 4,078 | no_license | [
{
"docstring": "get parent states of (m, c, t)",
"name": "getParents",
"signature": "def getParents(self, graph, m, c, t)"
},
{
"docstring": "Let (m,c,t) be the state of the game. m is the mouse location, c is cat location, t is 1 means it's mouse's turn, t is 2 means it's cat' turn. Then the al... | 2 | stack_v2_sparse_classes_30k_train_006139 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getParents(self, graph, m, c, t): get parent states of (m, c, t)
- def catMouseGame(self, graph): Let (m,c,t) be the state of the game. m is the mouse location, c is cat loca... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getParents(self, graph, m, c, t): get parent states of (m, c, t)
- def catMouseGame(self, graph): Let (m,c,t) be the state of the game. m is the mouse location, c is cat loca... | ad2f5bd0aec3d2c2c77b7c18627c1dd8fe8c0653 | <|skeleton|>
class Solution:
def getParents(self, graph, m, c, t):
"""get parent states of (m, c, t)"""
<|body_0|>
def catMouseGame(self, graph):
"""Let (m,c,t) be the state of the game. m is the mouse location, c is cat location, t is 1 means it's mouse's turn, t is 2 means it's cat' ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def getParents(self, graph, m, c, t):
"""get parent states of (m, c, t)"""
if t == MOUSE:
return [(m, p, 3 - t) for p in graph[c] if p != 0]
elif t == CAT:
return [(p, c, 3 - t) for p in graph[m] if p != 0]
def catMouseGame(self, graph):
"... | the_stack_v2_python_sparse | 913 Cat and Mouse.py | jz33/LeetCodeSolutions | train | 8 | |
35aba2df40eeff2793ccfa02505ad40fda7e51a3 | [
"n = len(regular)\nOFFSET = 2 * n\nadjMap = defaultdict(lambda: defaultdict(lambda: INF))\nfor pre, cur in pairwise(range(n + 1)):\n adjMap[pre][cur] = regular[pre]\n adjMap[pre][pre + OFFSET] = expressCost\n adjMap[pre + OFFSET][pre] = 0\n adjMap[pre + OFFSET][cur + OFFSET] = express[pre]\ndist = defau... | <|body_start_0|>
n = len(regular)
OFFSET = 2 * n
adjMap = defaultdict(lambda: defaultdict(lambda: INF))
for pre, cur in pairwise(range(n + 1)):
adjMap[pre][cur] = regular[pre]
adjMap[pre][pre + OFFSET] = expressCost
adjMap[pre + OFFSET][pre] = 0
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minimumCosts(self, regular: List[int], express: List[int], expressCost: int) -> List[int]:
"""注意到原图有环，所以通用的方法是 dijkstra 求最短路"""
<|body_0|>
def minimumCosts2(self, A: List[int], B: List[int], C: int) -> List[int]:
"""将每个车站视为一个点(缩点),那么转移就是拓扑序dp了"""
... | stack_v2_sparse_classes_10k_train_004917 | 2,105 | no_license | [
{
"docstring": "注意到原图有环，所以通用的方法是 dijkstra 求最短路",
"name": "minimumCosts",
"signature": "def minimumCosts(self, regular: List[int], express: List[int], expressCost: int) -> List[int]"
},
{
"docstring": "将每个车站视为一个点(缩点),那么转移就是拓扑序dp了",
"name": "minimumCosts2",
"signature": "def minimumCosts2(... | 2 | stack_v2_sparse_classes_30k_train_007006 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumCosts(self, regular: List[int], express: List[int], expressCost: int) -> List[int]: 注意到原图有环，所以通用的方法是 dijkstra 求最短路
- def minimumCosts2(self, A: List[int], B: List[int]... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumCosts(self, regular: List[int], express: List[int], expressCost: int) -> List[int]: 注意到原图有环，所以通用的方法是 dijkstra 求最短路
- def minimumCosts2(self, A: List[int], B: List[int]... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def minimumCosts(self, regular: List[int], express: List[int], expressCost: int) -> List[int]:
"""注意到原图有环，所以通用的方法是 dijkstra 求最短路"""
<|body_0|>
def minimumCosts2(self, A: List[int], B: List[int], C: int) -> List[int]:
"""将每个车站视为一个点(缩点),那么转移就是拓扑序dp了"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def minimumCosts(self, regular: List[int], express: List[int], expressCost: int) -> List[int]:
"""注意到原图有环，所以通用的方法是 dijkstra 求最短路"""
n = len(regular)
OFFSET = 2 * n
adjMap = defaultdict(lambda: defaultdict(lambda: INF))
for pre, cur in pairwise(range(n + 1)):
... | the_stack_v2_python_sparse | 11_动态规划/dp分类/线性dp/2361. Minimum Costs Using the Train Line-火车站问题.py | 981377660LMT/algorithm-study | train | 225 | |
5b82728ecdb8af261742df9cdf47c4237b1d2a6e | [
"assert cluster\nosh = ObjectStateHolder('mscluster')\nosh.setAttribute('data_name', cluster.name)\nmodeling.setAppSystemVendor(osh)\nif cluster.version:\n osh.setAttribute('version', cluster.version)\ndetails = cluster.details\nif details:\n if details.defaultNetworkRole:\n osh.setAttribute('defaultNe... | <|body_start_0|>
assert cluster
osh = ObjectStateHolder('mscluster')
osh.setAttribute('data_name', cluster.name)
modeling.setAppSystemVendor(osh)
if cluster.version:
osh.setAttribute('version', cluster.version)
details = cluster.details
if details:
... | Builder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Builder:
def buildCluster(self, cluster):
"""@types: Cluster -> ObjectStateHolder"""
<|body_0|>
def buildClusterPdo(self, pdo):
"""@types: Builder.Pdo -> ObjectStateHolder"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
assert cluster
osh = ... | stack_v2_sparse_classes_10k_train_004918 | 15,554 | no_license | [
{
"docstring": "@types: Cluster -> ObjectStateHolder",
"name": "buildCluster",
"signature": "def buildCluster(self, cluster)"
},
{
"docstring": "@types: Builder.Pdo -> ObjectStateHolder",
"name": "buildClusterPdo",
"signature": "def buildClusterPdo(self, pdo)"
}
] | 2 | null | Implement the Python class `Builder` described below.
Class description:
Implement the Builder class.
Method signatures and docstrings:
- def buildCluster(self, cluster): @types: Cluster -> ObjectStateHolder
- def buildClusterPdo(self, pdo): @types: Builder.Pdo -> ObjectStateHolder | Implement the Python class `Builder` described below.
Class description:
Implement the Builder class.
Method signatures and docstrings:
- def buildCluster(self, cluster): @types: Cluster -> ObjectStateHolder
- def buildClusterPdo(self, pdo): @types: Builder.Pdo -> ObjectStateHolder
<|skeleton|>
class Builder:
d... | c431e809e8d0f82e1bca7e3429dd0245560b5680 | <|skeleton|>
class Builder:
def buildCluster(self, cluster):
"""@types: Cluster -> ObjectStateHolder"""
<|body_0|>
def buildClusterPdo(self, pdo):
"""@types: Builder.Pdo -> ObjectStateHolder"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Builder:
def buildCluster(self, cluster):
"""@types: Cluster -> ObjectStateHolder"""
assert cluster
osh = ObjectStateHolder('mscluster')
osh.setAttribute('data_name', cluster.name)
modeling.setAppSystemVendor(osh)
if cluster.version:
osh.setAttribute... | the_stack_v2_python_sparse | reference/ucmdb/discovery/ms_cluster.py | madmonkyang/cda-record | train | 0 | |
e98c17b010c1258e3c9b144718ae074979299732 | [
"if self.op.mode in (constants.IALLOCATOR_MODE_ALLOC, constants.IALLOCATOR_MODE_MULTI_ALLOC):\n self.inst_uuid, iname = self.cfg.ExpandInstanceName(self.op.name)\n if iname is not None:\n raise errors.OpPrereqError(\"Instance '%s' already in the cluster\" % iname, errors.ECODE_EXISTS)\n for row in s... | <|body_start_0|>
if self.op.mode in (constants.IALLOCATOR_MODE_ALLOC, constants.IALLOCATOR_MODE_MULTI_ALLOC):
self.inst_uuid, iname = self.cfg.ExpandInstanceName(self.op.name)
if iname is not None:
raise errors.OpPrereqError("Instance '%s' already in the cluster" % iname,... | Run allocator tests. This LU runs the allocator tests | LUTestAllocator | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LUTestAllocator:
"""Run allocator tests. This LU runs the allocator tests"""
def CheckPrereq(self):
"""Check prerequisites. This checks the opcode parameters depending on the director and mode test."""
<|body_0|>
def Exec(self, feedback_fn):
"""Run the allocator ... | stack_v2_sparse_classes_10k_train_004919 | 16,228 | permissive | [
{
"docstring": "Check prerequisites. This checks the opcode parameters depending on the director and mode test.",
"name": "CheckPrereq",
"signature": "def CheckPrereq(self)"
},
{
"docstring": "Run the allocator test.",
"name": "Exec",
"signature": "def Exec(self, feedback_fn)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005379 | Implement the Python class `LUTestAllocator` described below.
Class description:
Run allocator tests. This LU runs the allocator tests
Method signatures and docstrings:
- def CheckPrereq(self): Check prerequisites. This checks the opcode parameters depending on the director and mode test.
- def Exec(self, feedback_fn... | Implement the Python class `LUTestAllocator` described below.
Class description:
Run allocator tests. This LU runs the allocator tests
Method signatures and docstrings:
- def CheckPrereq(self): Check prerequisites. This checks the opcode parameters depending on the director and mode test.
- def Exec(self, feedback_fn... | 456ea285a7583183c2c8e5bcffe9006ec8a9d658 | <|skeleton|>
class LUTestAllocator:
"""Run allocator tests. This LU runs the allocator tests"""
def CheckPrereq(self):
"""Check prerequisites. This checks the opcode parameters depending on the director and mode test."""
<|body_0|>
def Exec(self, feedback_fn):
"""Run the allocator ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LUTestAllocator:
"""Run allocator tests. This LU runs the allocator tests"""
def CheckPrereq(self):
"""Check prerequisites. This checks the opcode parameters depending on the director and mode test."""
if self.op.mode in (constants.IALLOCATOR_MODE_ALLOC, constants.IALLOCATOR_MODE_MULTI_AL... | the_stack_v2_python_sparse | lib/cmdlib/test.py | ganeti/ganeti | train | 465 |
28d8ca8fe401e5e77888d61cdb98f6e9f49fae94 | [
"super().__init__()\nself.filename = filename\nself.line_format = '[{0:20s}]\\t\\t[Requested: {1} -- Data: {2}]\\n'",
"f = open(self.filename, 'a')\nfor key in data:\n f.write(self.line_format.format(datetime.now().__str__(), key, data[key]))\nf.close()"
] | <|body_start_0|>
super().__init__()
self.filename = filename
self.line_format = '[{0:20s}]\t\t[Requested: {1} -- Data: {2}]\n'
<|end_body_0|>
<|body_start_1|>
f = open(self.filename, 'a')
for key in data:
f.write(self.line_format.format(datetime.now().__str__(), key,... | Implements an interface to write data to file. | FileWriter | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileWriter:
"""Implements an interface to write data to file."""
def __init__(self, filename):
"""FileWriter implementation of broadcaster. Keyword Arguments: filename -- the name of the file to read/write to."""
<|body_0|>
def publish_dictionary(self, data):
"""... | stack_v2_sparse_classes_10k_train_004920 | 2,907 | permissive | [
{
"docstring": "FileWriter implementation of broadcaster. Keyword Arguments: filename -- the name of the file to read/write to.",
"name": "__init__",
"signature": "def __init__(self, filename)"
},
{
"docstring": "Writes a formated dictionary update to file. Keyword Arguments: data -- The data di... | 2 | stack_v2_sparse_classes_30k_train_003716 | Implement the Python class `FileWriter` described below.
Class description:
Implements an interface to write data to file.
Method signatures and docstrings:
- def __init__(self, filename): FileWriter implementation of broadcaster. Keyword Arguments: filename -- the name of the file to read/write to.
- def publish_dic... | Implement the Python class `FileWriter` described below.
Class description:
Implements an interface to write data to file.
Method signatures and docstrings:
- def __init__(self, filename): FileWriter implementation of broadcaster. Keyword Arguments: filename -- the name of the file to read/write to.
- def publish_dic... | b5d75cb82e4bc3e9c4e428a288c6ac98a4aa2c52 | <|skeleton|>
class FileWriter:
"""Implements an interface to write data to file."""
def __init__(self, filename):
"""FileWriter implementation of broadcaster. Keyword Arguments: filename -- the name of the file to read/write to."""
<|body_0|>
def publish_dictionary(self, data):
"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FileWriter:
"""Implements an interface to write data to file."""
def __init__(self, filename):
"""FileWriter implementation of broadcaster. Keyword Arguments: filename -- the name of the file to read/write to."""
super().__init__()
self.filename = filename
self.line_format... | the_stack_v2_python_sparse | src/broadcaster/broadcaster.py | vt-sailbot/sailbot-21 | train | 5 |
023776c9402f0f5915c2378c604e27879993da21 | [
"self.description = description\nself.domain = domain\nself.name = name\nself.nfs_access = nfs_access\nself.nfs_squash = nfs_squash",
"if dictionary is None:\n return None\ndescription = dictionary.get('description')\ndomain = dictionary.get('domain')\nname = dictionary.get('name')\nnfs_access = dictionary.get... | <|body_start_0|>
self.description = description
self.domain = domain
self.name = name
self.nfs_access = nfs_access
self.nfs_squash = nfs_squash
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
description = dictionary.get('descriptio... | Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_access (NfsAccessEnum): Specifies whether clients from this netgroup can mount ... | NisNetgroup | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NisNetgroup:
"""Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_access (NfsAccessEnum): Specifies whethe... | stack_v2_sparse_classes_10k_train_004921 | 2,471 | permissive | [
{
"docstring": "Constructor for the NisNetgroup class",
"name": "__init__",
"signature": "def __init__(self, description=None, domain=None, name=None, nfs_access=None, nfs_squash=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictio... | 2 | null | Implement the Python class `NisNetgroup` described below.
Class description:
Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_a... | Implement the Python class `NisNetgroup` described below.
Class description:
Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_a... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class NisNetgroup:
"""Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_access (NfsAccessEnum): Specifies whethe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NisNetgroup:
"""Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_access (NfsAccessEnum): Specifies whether clients fro... | the_stack_v2_python_sparse | cohesity_management_sdk/models/nis_netgroup.py | cohesity/management-sdk-python | train | 24 |
87368b51c1f1784b15294fe42a4709ef0866ee44 | [
"self.verbose = set_or_default(verbose, VERBOSE)\n'If ``True`` return verbose results.'\nself.fatal = set_or_default(fatal, FATAL)\n'If ``True``, die on test failure'\nself.passing = set_or_default(passing, PASSING)\n'If ``True`` attempt to return passing test cases.'\nself.results = {}\n'Dict that represents the r... | <|body_start_0|>
self.verbose = set_or_default(verbose, VERBOSE)
'If ``True`` return verbose results.'
self.fatal = set_or_default(fatal, FATAL)
'If ``True``, die on test failure'
self.passing = set_or_default(passing, PASSING)
'If ``True`` attempt to return passing test ... | DtfResults | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DtfResults:
def __init__(self, verbose=None, fatal=None, passing=None):
"""An interface to capture and report results from DtfCases."""
<|body_0|>
def add(self, name, result, msg):
""":param string name: The name of the test. :param bool result: ``True`` if the test ... | stack_v2_sparse_classes_10k_train_004922 | 4,828 | permissive | [
{
"docstring": "An interface to capture and report results from DtfCases.",
"name": "__init__",
"signature": "def __init__(self, verbose=None, fatal=None, passing=None)"
},
{
"docstring": ":param string name: The name of the test. :param bool result: ``True`` if the test passed, and ``False`` if... | 6 | stack_v2_sparse_classes_30k_train_000204 | Implement the Python class `DtfResults` described below.
Class description:
Implement the DtfResults class.
Method signatures and docstrings:
- def __init__(self, verbose=None, fatal=None, passing=None): An interface to capture and report results from DtfCases.
- def add(self, name, result, msg): :param string name: ... | Implement the Python class `DtfResults` described below.
Class description:
Implement the DtfResults class.
Method signatures and docstrings:
- def __init__(self, verbose=None, fatal=None, passing=None): An interface to capture and report results from DtfCases.
- def add(self, name, result, msg): :param string name: ... | 34bb5b5e0fcc986e923bd20102faeddf96437508 | <|skeleton|>
class DtfResults:
def __init__(self, verbose=None, fatal=None, passing=None):
"""An interface to capture and report results from DtfCases."""
<|body_0|>
def add(self, name, result, msg):
""":param string name: The name of the test. :param bool result: ``True`` if the test ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DtfResults:
def __init__(self, verbose=None, fatal=None, passing=None):
"""An interface to capture and report results from DtfCases."""
self.verbose = set_or_default(verbose, VERBOSE)
'If ``True`` return verbose results.'
self.fatal = set_or_default(fatal, FATAL)
'If ``... | the_stack_v2_python_sparse | dtf/results.py | tychoish/dtf | train | 0 | |
7d36c52ee93cdceb413da17b691a813df91ae5c7 | [
"self.settings = ai_game.settings\nfilname = 'highscore.txt'\nwith open(filname, 'r') as objects:\n num = objects.read()\nself.high_score = int(num)\nself.reset_stats()\nself.game_active = False",
"self.ship_left = self.settings.ship_limit\nself.score = 0\nself.level = 1"
] | <|body_start_0|>
self.settings = ai_game.settings
filname = 'highscore.txt'
with open(filname, 'r') as objects:
num = objects.read()
self.high_score = int(num)
self.reset_stats()
self.game_active = False
<|end_body_0|>
<|body_start_1|>
self.ship_left ... | Track statistics for Alien Invasion. | GameStats | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameStats:
"""Track statistics for Alien Invasion."""
def __init__(self, ai_game):
"""Initilaze statistics."""
<|body_0|>
def reset_stats(self):
"""Initilize stastics that can change during the game."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_004923 | 690 | no_license | [
{
"docstring": "Initilaze statistics.",
"name": "__init__",
"signature": "def __init__(self, ai_game)"
},
{
"docstring": "Initilize stastics that can change during the game.",
"name": "reset_stats",
"signature": "def reset_stats(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003693 | Implement the Python class `GameStats` described below.
Class description:
Track statistics for Alien Invasion.
Method signatures and docstrings:
- def __init__(self, ai_game): Initilaze statistics.
- def reset_stats(self): Initilize stastics that can change during the game. | Implement the Python class `GameStats` described below.
Class description:
Track statistics for Alien Invasion.
Method signatures and docstrings:
- def __init__(self, ai_game): Initilaze statistics.
- def reset_stats(self): Initilize stastics that can change during the game.
<|skeleton|>
class GameStats:
"""Trac... | eb40f515564fe781eaaf5202165e06be6b22b34d | <|skeleton|>
class GameStats:
"""Track statistics for Alien Invasion."""
def __init__(self, ai_game):
"""Initilaze statistics."""
<|body_0|>
def reset_stats(self):
"""Initilize stastics that can change during the game."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GameStats:
"""Track statistics for Alien Invasion."""
def __init__(self, ai_game):
"""Initilaze statistics."""
self.settings = ai_game.settings
filname = 'highscore.txt'
with open(filname, 'r') as objects:
num = objects.read()
self.high_score = int(num)... | the_stack_v2_python_sparse | SidewaysShooter/game_stats.py | noshah/Python_Practice | train | 0 |
01937a48602655b93701941497a9605e4d6d02e1 | [
"fsm = cls.FSM[operator_type]\nnext_state_info = fsm.get((current_status, event), None)\nreturn next_state_info",
"if current_status is None:\n current_status = shop.status if shop.status else cls.STATUS_INIT\nnext_state = cls.get_next_state(operator_type, current_status, event)\nnext_status = next_state['next... | <|body_start_0|>
fsm = cls.FSM[operator_type]
next_state_info = fsm.get((current_status, event), None)
return next_state_info
<|end_body_0|>
<|body_start_1|>
if current_status is None:
current_status = shop.status if shop.status else cls.STATUS_INIT
next_state = cls.... | 商户有限状态机 | ShopFSM | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShopFSM:
"""商户有限状态机"""
def get_next_state(cls, operator_type, current_status, event):
"""获取下一状态 :param operator_type: 'OUTSIDE'/'FE_INSIDE' :param current_status: 当前状态 :param event: 条件 :return: 如果返回None表示错误状态或条件"""
<|body_0|>
def update_status(cls, operator_type, shop, e... | stack_v2_sparse_classes_10k_train_004924 | 6,677 | permissive | [
{
"docstring": "获取下一状态 :param operator_type: 'OUTSIDE'/'FE_INSIDE' :param current_status: 当前状态 :param event: 条件 :return: 如果返回None表示错误状态或条件",
"name": "get_next_state",
"signature": "def get_next_state(cls, operator_type, current_status, event)"
},
{
"docstring": "更新对象的状态 :param operator_type: 'OU... | 2 | null | Implement the Python class `ShopFSM` described below.
Class description:
商户有限状态机
Method signatures and docstrings:
- def get_next_state(cls, operator_type, current_status, event): 获取下一状态 :param operator_type: 'OUTSIDE'/'FE_INSIDE' :param current_status: 当前状态 :param event: 条件 :return: 如果返回None表示错误状态或条件
- def update_st... | Implement the Python class `ShopFSM` described below.
Class description:
商户有限状态机
Method signatures and docstrings:
- def get_next_state(cls, operator_type, current_status, event): 获取下一状态 :param operator_type: 'OUTSIDE'/'FE_INSIDE' :param current_status: 当前状态 :param event: 条件 :return: 如果返回None表示错误状态或条件
- def update_st... | a7c9567975b5372b2edabddb0fec8d73bc01c3dc | <|skeleton|>
class ShopFSM:
"""商户有限状态机"""
def get_next_state(cls, operator_type, current_status, event):
"""获取下一状态 :param operator_type: 'OUTSIDE'/'FE_INSIDE' :param current_status: 当前状态 :param event: 条件 :return: 如果返回None表示错误状态或条件"""
<|body_0|>
def update_status(cls, operator_type, shop, e... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ShopFSM:
"""商户有限状态机"""
def get_next_state(cls, operator_type, current_status, event):
"""获取下一状态 :param operator_type: 'OUTSIDE'/'FE_INSIDE' :param current_status: 当前状态 :param event: 条件 :return: 如果返回None表示错误状态或条件"""
fsm = cls.FSM[operator_type]
next_state_info = fsm.get((current_st... | the_stack_v2_python_sparse | Dispatcher/data_and_service/shop/model_logics/fsm.py | cash2one/Logistics | train | 0 |
243b4a17e32fcf653187c6bc45f397e5bf1a89e6 | [
"super(FlowData, self).__init__()\nself.filename_flow = 'trash can flow meter.xls'\nself.start_rowx = 2\nself.end_rowx = 17\nself.poly_order = 2\nself.trash_volume = 0.0776\nself.P = 100.0",
"worksheet = xlrd.open_workbook(filename=self.filename_flow).sheet_by_index(0)\nself.corrected_reading = np.array(worksheet... | <|body_start_0|>
super(FlowData, self).__init__()
self.filename_flow = 'trash can flow meter.xls'
self.start_rowx = 2
self.end_rowx = 17
self.poly_order = 2
self.trash_volume = 0.0776
self.P = 100.0
<|end_body_0|>
<|body_start_1|>
worksheet = xlrd.open_wo... | Class for handling flow rate and pressure drop data. | FlowData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlowData:
"""Class for handling flow rate and pressure drop data."""
def __init__(self):
"""Sets default file name, start row, and end row."""
<|body_0|>
def import_flow_data(self):
"""Imports data and stores it in numpy arrays."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_10k_train_004925 | 7,912 | no_license | [
{
"docstring": "Sets default file name, start row, and end row.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Imports data and stores it in numpy arrays.",
"name": "import_flow_data",
"signature": "def import_flow_data(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003387 | Implement the Python class `FlowData` described below.
Class description:
Class for handling flow rate and pressure drop data.
Method signatures and docstrings:
- def __init__(self): Sets default file name, start row, and end row.
- def import_flow_data(self): Imports data and stores it in numpy arrays. | Implement the Python class `FlowData` described below.
Class description:
Class for handling flow rate and pressure drop data.
Method signatures and docstrings:
- def __init__(self): Sets default file name, start row, and end row.
- def import_flow_data(self): Imports data and stores it in numpy arrays.
<|skeleton|>... | d619b66b1f16557e06c94eee1c16d4ee2a9e896a | <|skeleton|>
class FlowData:
"""Class for handling flow rate and pressure drop data."""
def __init__(self):
"""Sets default file name, start row, and end row."""
<|body_0|>
def import_flow_data(self):
"""Imports data and stores it in numpy arrays."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FlowData:
"""Class for handling flow rate and pressure drop data."""
def __init__(self):
"""Sets default file name, start row, and end row."""
super(FlowData, self).__init__()
self.filename_flow = 'trash can flow meter.xls'
self.start_rowx = 2
self.end_rowx = 17
... | the_stack_v2_python_sparse | exp_data.py | hfateh/TE_Model-1 | train | 0 |
4eca387528e53aa20835173db4bbc588aa27c96d | [
"super().__init__()\nself.attn = attn\nself.ffn = ffn\nself.skiplayers = clones(SkipLayer(ffn.d, drop), 2)\nself.d = ffn.d",
"x = self.skiplayers[0](x, lambda x: self.attn(x, x, x, mask))\nx = self.skiplayers[1](x, self.ffn)\nreturn x"
] | <|body_start_0|>
super().__init__()
self.attn = attn
self.ffn = ffn
self.skiplayers = clones(SkipLayer(ffn.d, drop), 2)
self.d = ffn.d
<|end_body_0|>
<|body_start_1|>
x = self.skiplayers[0](x, lambda x: self.attn(x, x, x, mask))
x = self.skiplayers[1](x, self.ffn... | EncoderLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderLayer:
def __init__(self, attn, ffn, drop):
"""attn:MultiAttentionLayer ffn:feed forward Layer drop:drop factor for skip connection"""
<|body_0|>
def forward(self, x, mask):
"""x:(N,T,D) mask:(N,1,T) return:(N,T,D)"""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_10k_train_004926 | 11,927 | no_license | [
{
"docstring": "attn:MultiAttentionLayer ffn:feed forward Layer drop:drop factor for skip connection",
"name": "__init__",
"signature": "def __init__(self, attn, ffn, drop)"
},
{
"docstring": "x:(N,T,D) mask:(N,1,T) return:(N,T,D)",
"name": "forward",
"signature": "def forward(self, x, m... | 2 | stack_v2_sparse_classes_30k_train_003220 | Implement the Python class `EncoderLayer` described below.
Class description:
Implement the EncoderLayer class.
Method signatures and docstrings:
- def __init__(self, attn, ffn, drop): attn:MultiAttentionLayer ffn:feed forward Layer drop:drop factor for skip connection
- def forward(self, x, mask): x:(N,T,D) mask:(N,... | Implement the Python class `EncoderLayer` described below.
Class description:
Implement the EncoderLayer class.
Method signatures and docstrings:
- def __init__(self, attn, ffn, drop): attn:MultiAttentionLayer ffn:feed forward Layer drop:drop factor for skip connection
- def forward(self, x, mask): x:(N,T,D) mask:(N,... | 24e60f24b6e442db22507adddd6bf3e2c343c013 | <|skeleton|>
class EncoderLayer:
def __init__(self, attn, ffn, drop):
"""attn:MultiAttentionLayer ffn:feed forward Layer drop:drop factor for skip connection"""
<|body_0|>
def forward(self, x, mask):
"""x:(N,T,D) mask:(N,1,T) return:(N,T,D)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncoderLayer:
def __init__(self, attn, ffn, drop):
"""attn:MultiAttentionLayer ffn:feed forward Layer drop:drop factor for skip connection"""
super().__init__()
self.attn = attn
self.ffn = ffn
self.skiplayers = clones(SkipLayer(ffn.d, drop), 2)
self.d = ffn.d
... | the_stack_v2_python_sparse | daily/8/pytorch_tutoral/nmt/model.py | mckjzhangxk/deepAI | train | 1 | |
04ab08ce29e6f248d90c5dd862be84a028191e39 | [
"try:\n return Vrf.objects.filter(id=id_vrf).uniqueResult()\nexcept ObjectDoesNotExist as e:\n raise VrfNotFoundError(u'Vrf id = %s does not exist.' % id_vrf)\nexcept OperationalError as e:\n cls.log.error(u'Lock wait timeout exceeded.')\n raise OperationalError(u'Lock wait timeout exceeded; try restart... | <|body_start_0|>
try:
return Vrf.objects.filter(id=id_vrf).uniqueResult()
except ObjectDoesNotExist as e:
raise VrfNotFoundError(u'Vrf id = %s does not exist.' % id_vrf)
except OperationalError as e:
cls.log.error(u'Lock wait timeout exceeded.')
ra... | Vrf | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vrf:
def get_by_pk(cls, id_vrf):
"""Get Vrf by id. @return: Vrf. @raise VrfNotFoundError: Vrf is not registered. @raise VrfError: Failed to search for the Vrf. @raise OperationalError: Lock wait timeout exceed"""
<|body_0|>
def create(self, authenticated_user):
"""In... | stack_v2_sparse_classes_10k_train_004927 | 5,338 | permissive | [
{
"docstring": "Get Vrf by id. @return: Vrf. @raise VrfNotFoundError: Vrf is not registered. @raise VrfError: Failed to search for the Vrf. @raise OperationalError: Lock wait timeout exceed",
"name": "get_by_pk",
"signature": "def get_by_pk(cls, id_vrf)"
},
{
"docstring": "Include new Vrf. @retu... | 4 | null | Implement the Python class `Vrf` described below.
Class description:
Implement the Vrf class.
Method signatures and docstrings:
- def get_by_pk(cls, id_vrf): Get Vrf by id. @return: Vrf. @raise VrfNotFoundError: Vrf is not registered. @raise VrfError: Failed to search for the Vrf. @raise OperationalError: Lock wait t... | Implement the Python class `Vrf` described below.
Class description:
Implement the Vrf class.
Method signatures and docstrings:
- def get_by_pk(cls, id_vrf): Get Vrf by id. @return: Vrf. @raise VrfNotFoundError: Vrf is not registered. @raise VrfError: Failed to search for the Vrf. @raise OperationalError: Lock wait t... | eb27e1d977a1c4bb1fee8fb51b8d8050c64696d9 | <|skeleton|>
class Vrf:
def get_by_pk(cls, id_vrf):
"""Get Vrf by id. @return: Vrf. @raise VrfNotFoundError: Vrf is not registered. @raise VrfError: Failed to search for the Vrf. @raise OperationalError: Lock wait timeout exceed"""
<|body_0|>
def create(self, authenticated_user):
"""In... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Vrf:
def get_by_pk(cls, id_vrf):
"""Get Vrf by id. @return: Vrf. @raise VrfNotFoundError: Vrf is not registered. @raise VrfError: Failed to search for the Vrf. @raise OperationalError: Lock wait timeout exceed"""
try:
return Vrf.objects.filter(id=id_vrf).uniqueResult()
exce... | the_stack_v2_python_sparse | networkapi/api_vrf/models.py | globocom/GloboNetworkAPI | train | 86 | |
bf2f829c85d143ecb2efc1d2f3c5bf88e7f54b82 | [
"self.instr = Instructions(reg, mem, alu)\nself.mem = mem\nself.reg = reg\nself.op_codes = {}\nself.op_codes[1] = self.instr.halt\nself.op_codes[32] = self.instr.add\nself.op_codes[33] = self.instr.lda\nself.op_codes[34] = self.instr.sta\nself.op_codes[35] = self.instr.jmp\nself.op_codes[36] = self.instr.sza\nself.... | <|body_start_0|>
self.instr = Instructions(reg, mem, alu)
self.mem = mem
self.reg = reg
self.op_codes = {}
self.op_codes[1] = self.instr.halt
self.op_codes[32] = self.instr.add
self.op_codes[33] = self.instr.lda
self.op_codes[34] = self.instr.sta
s... | Decode op codes into instructions. | Decoder | [
"Artistic-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""Decode op codes into instructions."""
def __init__(self, reg, mem, alu):
"""Create the op code instruction map."""
<|body_0|>
def fetch_execute(self):
"""The fetch execute cycle. Fetch the next instruction and the value of the address following it. Th... | stack_v2_sparse_classes_10k_train_004928 | 5,867 | permissive | [
{
"docstring": "Create the op code instruction map.",
"name": "__init__",
"signature": "def __init__(self, reg, mem, alu)"
},
{
"docstring": "The fetch execute cycle. Fetch the next instruction and the value of the address following it. That value, typically an address itself, is passed to the i... | 2 | stack_v2_sparse_classes_30k_train_006562 | Implement the Python class `Decoder` described below.
Class description:
Decode op codes into instructions.
Method signatures and docstrings:
- def __init__(self, reg, mem, alu): Create the op code instruction map.
- def fetch_execute(self): The fetch execute cycle. Fetch the next instruction and the value of the add... | Implement the Python class `Decoder` described below.
Class description:
Decode op codes into instructions.
Method signatures and docstrings:
- def __init__(self, reg, mem, alu): Create the op code instruction map.
- def fetch_execute(self): The fetch execute cycle. Fetch the next instruction and the value of the add... | 75997d72ceefdc35fd3c76fe50676626cb2be887 | <|skeleton|>
class Decoder:
"""Decode op codes into instructions."""
def __init__(self, reg, mem, alu):
"""Create the op code instruction map."""
<|body_0|>
def fetch_execute(self):
"""The fetch execute cycle. Fetch the next instruction and the value of the address following it. Th... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Decoder:
"""Decode op codes into instructions."""
def __init__(self, reg, mem, alu):
"""Create the op code instruction map."""
self.instr = Instructions(reg, mem, alu)
self.mem = mem
self.reg = reg
self.op_codes = {}
self.op_codes[1] = self.instr.halt
... | the_stack_v2_python_sparse | decoder.py | kmggh/python-simple-machine | train | 0 |
ca7b7dd63bafccdf224096b922a3730f1d50aa78 | [
"data = KlifsToKissimData.from_structure_klifs_id(structure_klifs_id, klifs_session)\nif data is None:\n logger.warning(f'{structure_klifs_id}: Empty fingerprint (data unaccessible).')\n fingerprint = None\nelse:\n fingerprint = cls.from_text(data.text, data.extension, data.residue_ids, data.residue_ixs, d... | <|body_start_0|>
data = KlifsToKissimData.from_structure_klifs_id(structure_klifs_id, klifs_session)
if data is None:
logger.warning(f'{structure_klifs_id}: Empty fingerprint (data unaccessible).')
fingerprint = None
else:
fingerprint = cls.from_text(data.text... | Fingerprint | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Fingerprint:
def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None):
"""Calculate fingerprint for a KLIFS structure (by structure KLIFS ID). Parameters ---------- structure_klifs_id : int Structure KLIFS ID. klifs_session : opencadd.databases.klifs.session.Session or No... | stack_v2_sparse_classes_10k_train_004929 | 5,476 | permissive | [
{
"docstring": "Calculate fingerprint for a KLIFS structure (by structure KLIFS ID). Parameters ---------- structure_klifs_id : int Structure KLIFS ID. klifs_session : opencadd.databases.klifs.session.Session or None Local or remote KLIFS session. If None (default), set up remote KLIFS session. Returns ------- ... | 4 | stack_v2_sparse_classes_30k_train_006088 | Implement the Python class `Fingerprint` described below.
Class description:
Implement the Fingerprint class.
Method signatures and docstrings:
- def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None): Calculate fingerprint for a KLIFS structure (by structure KLIFS ID). Parameters ---------- structu... | Implement the Python class `Fingerprint` described below.
Class description:
Implement the Fingerprint class.
Method signatures and docstrings:
- def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None): Calculate fingerprint for a KLIFS structure (by structure KLIFS ID). Parameters ---------- structu... | 8433bb64062ed785503b96b52f39bbdb02f66381 | <|skeleton|>
class Fingerprint:
def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None):
"""Calculate fingerprint for a KLIFS structure (by structure KLIFS ID). Parameters ---------- structure_klifs_id : int Structure KLIFS ID. klifs_session : opencadd.databases.klifs.session.Session or No... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Fingerprint:
def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None):
"""Calculate fingerprint for a KLIFS structure (by structure KLIFS ID). Parameters ---------- structure_klifs_id : int Structure KLIFS ID. klifs_session : opencadd.databases.klifs.session.Session or None Local or re... | the_stack_v2_python_sparse | kissim/encoding/fingerprint.py | volkamerlab/kissim | train | 26 | |
3911d2285a9a7b9710305824fe2e8f31e4dddad3 | [
"self._file: Path = file_path\nself._schema: vol.Schema = schema\nself._data: dict[str, Any] = _DEFAULT\nself.read_data()",
"try:\n self._data = self._schema(_DEFAULT)\nexcept vol.Invalid as ex:\n _LOGGER.error(\"Can't reset %s: %s\", self._file, humanize_error(self._data, ex))\nelse:\n self.save_data()"... | <|body_start_0|>
self._file: Path = file_path
self._schema: vol.Schema = schema
self._data: dict[str, Any] = _DEFAULT
self.read_data()
<|end_body_0|>
<|body_start_1|>
try:
self._data = self._schema(_DEFAULT)
except vol.Invalid as ex:
_LOGGER.error... | Baseclass for classes that uses configuration files, the files can be JSON/YAML. | FileConfiguration | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileConfiguration:
"""Baseclass for classes that uses configuration files, the files can be JSON/YAML."""
def __init__(self, file_path: Path, schema: vol.Schema):
"""Initialize hass object."""
<|body_0|>
def reset_data(self) -> None:
"""Reset configuration to def... | stack_v2_sparse_classes_10k_train_004930 | 3,335 | permissive | [
{
"docstring": "Initialize hass object.",
"name": "__init__",
"signature": "def __init__(self, file_path: Path, schema: vol.Schema)"
},
{
"docstring": "Reset configuration to default.",
"name": "reset_data",
"signature": "def reset_data(self) -> None"
},
{
"docstring": "Read conf... | 4 | stack_v2_sparse_classes_30k_train_001472 | Implement the Python class `FileConfiguration` described below.
Class description:
Baseclass for classes that uses configuration files, the files can be JSON/YAML.
Method signatures and docstrings:
- def __init__(self, file_path: Path, schema: vol.Schema): Initialize hass object.
- def reset_data(self) -> None: Reset... | Implement the Python class `FileConfiguration` described below.
Class description:
Baseclass for classes that uses configuration files, the files can be JSON/YAML.
Method signatures and docstrings:
- def __init__(self, file_path: Path, schema: vol.Schema): Initialize hass object.
- def reset_data(self) -> None: Reset... | 4838b280adafed0997f32e021274b531178386cd | <|skeleton|>
class FileConfiguration:
"""Baseclass for classes that uses configuration files, the files can be JSON/YAML."""
def __init__(self, file_path: Path, schema: vol.Schema):
"""Initialize hass object."""
<|body_0|>
def reset_data(self) -> None:
"""Reset configuration to def... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FileConfiguration:
"""Baseclass for classes that uses configuration files, the files can be JSON/YAML."""
def __init__(self, file_path: Path, schema: vol.Schema):
"""Initialize hass object."""
self._file: Path = file_path
self._schema: vol.Schema = schema
self._data: dict[... | the_stack_v2_python_sparse | supervisor/utils/common.py | home-assistant/supervisor | train | 928 |
dde40df29d623461c39f0e99caace39934694631 | [
"if nums is None or len(nums) <= 0:\n return 0\nl = len(nums)\nprev = 0\ncur = 0\nmax_value = -1 * 2 ** 31\nfor i in range(1, l + 1):\n for j in range(i, l + 1):\n if i == j:\n cur = nums[j - 1]\n prev = nums[j - 1]\n else:\n cur = prev + nums[j - 1]\n ... | <|body_start_0|>
if nums is None or len(nums) <= 0:
return 0
l = len(nums)
prev = 0
cur = 0
max_value = -1 * 2 ** 31
for i in range(1, l + 1):
for j in range(i, l + 1):
if i == j:
cur = nums[j - 1]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray_bak(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if nums is None or len(nums) <= 0:
... | stack_v2_sparse_classes_10k_train_004931 | 1,945 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray_bak",
"signature": "def maxSubArray_bak(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000927 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray_bak(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray_bak(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxSubA... | aa1d6677a89f15141a615d6d6151b09bcb825397 | <|skeleton|>
class Solution:
def maxSubArray_bak(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray_bak(self, nums):
""":type nums: List[int] :rtype: int"""
if nums is None or len(nums) <= 0:
return 0
l = len(nums)
prev = 0
cur = 0
max_value = -1 * 2 ** 31
for i in range(1, l + 1):
for j in range(i, l +... | the_stack_v2_python_sparse | leetcode/dp/max_subarray.py | shubham166/Competitive_Programming | train | 0 | |
76636a1200484ae7d2ef3113785f4f033cdaf370 | [
"links = response.xpath('//a[@class=\"product-title-link\"]/@href').extract()\nfor link in links:\n yield response.follow('https://www.labirint.ru' + link, callback=self.parse_item)\nnext_page = response.xpath('//a[@class=\"pagination-next__text\"]/@href').extract_first()\nif next_page:\n yield response.follo... | <|body_start_0|>
links = response.xpath('//a[@class="product-title-link"]/@href').extract()
for link in links:
yield response.follow('https://www.labirint.ru' + link, callback=self.parse_item)
next_page = response.xpath('//a[@class="pagination-next__text"]/@href').extract_first()
... | Labirint.ru spider. | LabirintruSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabirintruSpider:
"""Labirint.ru spider."""
def parse(self, response):
"""Novelty page parser."""
<|body_0|>
def parse_item(self, response: HtmlResponse):
"""Book item parser."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
links = response.xpat... | stack_v2_sparse_classes_10k_train_004932 | 1,756 | no_license | [
{
"docstring": "Novelty page parser.",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "Book item parser.",
"name": "parse_item",
"signature": "def parse_item(self, response: HtmlResponse)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005094 | Implement the Python class `LabirintruSpider` described below.
Class description:
Labirint.ru spider.
Method signatures and docstrings:
- def parse(self, response): Novelty page parser.
- def parse_item(self, response: HtmlResponse): Book item parser. | Implement the Python class `LabirintruSpider` described below.
Class description:
Labirint.ru spider.
Method signatures and docstrings:
- def parse(self, response): Novelty page parser.
- def parse_item(self, response: HtmlResponse): Book item parser.
<|skeleton|>
class LabirintruSpider:
"""Labirint.ru spider.""... | 69488f0e788578722bf4f1cf171508f1e5624145 | <|skeleton|>
class LabirintruSpider:
"""Labirint.ru spider."""
def parse(self, response):
"""Novelty page parser."""
<|body_0|>
def parse_item(self, response: HtmlResponse):
"""Book item parser."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LabirintruSpider:
"""Labirint.ru spider."""
def parse(self, response):
"""Novelty page parser."""
links = response.xpath('//a[@class="product-title-link"]/@href').extract()
for link in links:
yield response.follow('https://www.labirint.ru' + link, callback=self.parse_i... | the_stack_v2_python_sparse | lesson_6/bookparser/spiders/labirintru.py | IInvasion/collecting_and_processing_web_data | train | 0 |
3e5e6b59f567da9d7ac620a18efbb25eaa2b2054 | [
"len_nums = len(nums)\nif len_nums <= 1:\n return 0\np = 0\nstep = 0\nwhile p < len_nums:\n c_v = nums[p]\n temp_dict = dict()\n for i in range(1, c_v + 1):\n if p + i < len_nums:\n temp_dict[p + i + nums[p + i]] = p + i\n if p + i == len_nums - 1:\n return st... | <|body_start_0|>
len_nums = len(nums)
if len_nums <= 1:
return 0
p = 0
step = 0
while p < len_nums:
c_v = nums[p]
temp_dict = dict()
for i in range(1, c_v + 1):
if p + i < len_nums:
temp_dict[p + ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def jump(self, nums: List[int]) -> int:
"""贪心算法 :param nums: :return:"""
<|body_0|>
def jump2(self, nums: List[int]) -> int:
"""递归，遍历所有可能性 :param nums: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
len_nums = len(nums)
i... | stack_v2_sparse_classes_10k_train_004933 | 4,406 | no_license | [
{
"docstring": "贪心算法 :param nums: :return:",
"name": "jump",
"signature": "def jump(self, nums: List[int]) -> int"
},
{
"docstring": "递归，遍历所有可能性 :param nums: :return:",
"name": "jump2",
"signature": "def jump2(self, nums: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_val_000131 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums: List[int]) -> int: 贪心算法 :param nums: :return:
- def jump2(self, nums: List[int]) -> int: 递归，遍历所有可能性 :param nums: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums: List[int]) -> int: 贪心算法 :param nums: :return:
- def jump2(self, nums: List[int]) -> int: 递归，遍历所有可能性 :param nums: :return:
<|skeleton|>
class Solution:
... | bbcb7c3c9aa51141695d73b90bf8f04c794be131 | <|skeleton|>
class Solution:
def jump(self, nums: List[int]) -> int:
"""贪心算法 :param nums: :return:"""
<|body_0|>
def jump2(self, nums: List[int]) -> int:
"""递归，遍历所有可能性 :param nums: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def jump(self, nums: List[int]) -> int:
"""贪心算法 :param nums: :return:"""
len_nums = len(nums)
if len_nums <= 1:
return 0
p = 0
step = 0
while p < len_nums:
c_v = nums[p]
temp_dict = dict()
for i in range(... | the_stack_v2_python_sparse | 00001_00100/00045_跳跃游戏II.py | xiphodon/leetcode_studio | train | 1 | |
da9c15c98e48592ce33e686931d10fe18c2bd657 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UnifiedRoleManagementPolicyEnablementRule()",
"from .unified_role_management_policy_rule import UnifiedRoleManagementPolicyRule\nfrom .unified_role_management_policy_rule import UnifiedRoleManagementPolicyRule\nfields: Dict[str, Callab... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UnifiedRoleManagementPolicyEnablementRule()
<|end_body_0|>
<|body_start_1|>
from .unified_role_management_policy_rule import UnifiedRoleManagementPolicyRule
from .unified_role_management... | UnifiedRoleManagementPolicyEnablementRule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnifiedRoleManagementPolicyEnablementRule:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedRoleManagementPolicyEnablementRule:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to re... | stack_v2_sparse_classes_10k_train_004934 | 2,533 | 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: UnifiedRoleManagementPolicyEnablementRule",
"name": "create_from_discriminator_value",
"signature": "def cre... | 3 | null | Implement the Python class `UnifiedRoleManagementPolicyEnablementRule` described below.
Class description:
Implement the UnifiedRoleManagementPolicyEnablementRule class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedRoleManagementPolicyEnableme... | Implement the Python class `UnifiedRoleManagementPolicyEnablementRule` described below.
Class description:
Implement the UnifiedRoleManagementPolicyEnablementRule class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedRoleManagementPolicyEnableme... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UnifiedRoleManagementPolicyEnablementRule:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedRoleManagementPolicyEnablementRule:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to re... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UnifiedRoleManagementPolicyEnablementRule:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedRoleManagementPolicyEnablementRule:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discrim... | the_stack_v2_python_sparse | msgraph/generated/models/unified_role_management_policy_enablement_rule.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
1d0d0fc24cfca0022dbda83b86f6cb95ae3b2a78 | [
"self.message_handlers = [[] for i in range(self.NUMBER_OF_MESSAGE_TYPES)]\nself.lock = threading.Lock()\nself.logger = Logger().getLogger('backend.core.MessageBus')",
"if isinstance(message_handler, MessageHandler):\n for key in message_priority_list:\n rule = (message_priority_list[key], message_handl... | <|body_start_0|>
self.message_handlers = [[] for i in range(self.NUMBER_OF_MESSAGE_TYPES)]
self.lock = threading.Lock()
self.logger = Logger().getLogger('backend.core.MessageBus')
<|end_body_0|>
<|body_start_1|>
if isinstance(message_handler, MessageHandler):
for key in mess... | MessageBus is the heart of the backend messaging system. Almost all communication between components goes through this MessageBus. Components communicate with Messages, which are delivered to MessageHandlers via MessageBus. MessageBus knows which MessageHandlers are interested in which type of Messages. MessageBus is a... | MessageBus | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MessageBus:
"""MessageBus is the heart of the backend messaging system. Almost all communication between components goes through this MessageBus. Components communicate with Messages, which are delivered to MessageHandlers via MessageBus. MessageBus knows which MessageHandlers are interested in w... | stack_v2_sparse_classes_10k_train_004935 | 4,666 | no_license | [
{
"docstring": "Create a new MessageBus object.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Register a new MessageHandler to this MessageBus @param message_handler: MessageHandler object @param message_priority_list: Priority list for this MessageHandler",
"nam... | 4 | stack_v2_sparse_classes_30k_train_003797 | Implement the Python class `MessageBus` described below.
Class description:
MessageBus is the heart of the backend messaging system. Almost all communication between components goes through this MessageBus. Components communicate with Messages, which are delivered to MessageHandlers via MessageBus. MessageBus knows wh... | Implement the Python class `MessageBus` described below.
Class description:
MessageBus is the heart of the backend messaging system. Almost all communication between components goes through this MessageBus. Components communicate with Messages, which are delivered to MessageHandlers via MessageBus. MessageBus knows wh... | 945463032481c3afdef56d0ef9f5be102829eb35 | <|skeleton|>
class MessageBus:
"""MessageBus is the heart of the backend messaging system. Almost all communication between components goes through this MessageBus. Components communicate with Messages, which are delivered to MessageHandlers via MessageBus. MessageBus knows which MessageHandlers are interested in w... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MessageBus:
"""MessageBus is the heart of the backend messaging system. Almost all communication between components goes through this MessageBus. Components communicate with Messages, which are delivered to MessageHandlers via MessageBus. MessageBus knows which MessageHandlers are interested in which type of ... | the_stack_v2_python_sparse | entertainerlib/backend/core/message_bus.py | tiwilliam/entertainer | train | 0 |
10a2e03965397bb9d9cee9f675f7b95e49ece52e | [
"self.max_frames = max_frames\nself.sink = sink\nself.pipelines = pipelines\nself.name = name\nself.count = 0\nself.payload = b''",
"self.count += 1\nself.payload += data\ndebug('BufferedPipe count: {}, max frames: {}'.format(self.count, self.max_frames))\nif self.count == self.max_frames:\n debug('BufferedPip... | <|body_start_0|>
self.max_frames = max_frames
self.sink = sink
self.pipelines = pipelines
self.name = name
self.count = 0
self.payload = b''
<|end_body_0|>
<|body_start_1|>
self.count += 1
self.payload += data
debug('BufferedPipe count: {}, max fr... | BufferedPipe | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BufferedPipe:
def __init__(self, max_frames: int, sink, pipelines: list, name: str=None):
"""Create a buffer which will call the provided `sink` when full. It will call `sink` with the number of frames and the accumulated bytes when it reaches `max_buffer_size` frames. pass list of `pipe... | stack_v2_sparse_classes_10k_train_004936 | 1,348 | no_license | [
{
"docstring": "Create a buffer which will call the provided `sink` when full. It will call `sink` with the number of frames and the accumulated bytes when it reaches `max_buffer_size` frames. pass list of `pipelines` as arg to process this buffer using specified pipelines only (not all pipelines)",
"name":... | 3 | stack_v2_sparse_classes_30k_train_001165 | Implement the Python class `BufferedPipe` described below.
Class description:
Implement the BufferedPipe class.
Method signatures and docstrings:
- def __init__(self, max_frames: int, sink, pipelines: list, name: str=None): Create a buffer which will call the provided `sink` when full. It will call `sink` with the nu... | Implement the Python class `BufferedPipe` described below.
Class description:
Implement the BufferedPipe class.
Method signatures and docstrings:
- def __init__(self, max_frames: int, sink, pipelines: list, name: str=None): Create a buffer which will call the provided `sink` when full. It will call `sink` with the nu... | bc81942cf8fea5e4cb127117f9e76577910c1a3d | <|skeleton|>
class BufferedPipe:
def __init__(self, max_frames: int, sink, pipelines: list, name: str=None):
"""Create a buffer which will call the provided `sink` when full. It will call `sink` with the number of frames and the accumulated bytes when it reaches `max_buffer_size` frames. pass list of `pipe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BufferedPipe:
def __init__(self, max_frames: int, sink, pipelines: list, name: str=None):
"""Create a buffer which will call the provided `sink` when full. It will call `sink` with the number of frames and the accumulated bytes when it reaches `max_buffer_size` frames. pass list of `pipelines` as arg ... | the_stack_v2_python_sparse | lib/BufferedPipe.py | wzulfikar/py-phonic | train | 0 | |
d44b0d52e4cfa37e936664595b8a13b265f96a6a | [
"queue = deque([(n, 0)])\nvisited = set()\nwhile queue:\n num, step = queue.popleft()\n remains = [num - n * n for n in range(1, int(num ** 0.5) + 1)]\n for i in remains:\n if i == 0:\n return step + 1\n if i not in visited:\n queue.append((i, step + 1))\n vis... | <|body_start_0|>
queue = deque([(n, 0)])
visited = set()
while queue:
num, step = queue.popleft()
remains = [num - n * n for n in range(1, int(num ** 0.5) + 1)]
for i in remains:
if i == 0:
return step + 1
if... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def num_squares(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def num_squares_2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
queue = deque([(n, 0)])
visited = set()
while queue... | stack_v2_sparse_classes_10k_train_004937 | 1,571 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "num_squares",
"signature": "def num_squares(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "num_squares_2",
"signature": "def num_squares_2(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005789 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def num_squares(self, n): :type n: int :rtype: int
- def num_squares_2(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def num_squares(self, n): :type n: int :rtype: int
- def num_squares_2(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def num_squares(self, n):
"""... | cc7740026c3774be21ab924b99ae7596ef20d0e4 | <|skeleton|>
class Solution:
def num_squares(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def num_squares_2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def num_squares(self, n):
""":type n: int :rtype: int"""
queue = deque([(n, 0)])
visited = set()
while queue:
num, step = queue.popleft()
remains = [num - n * n for n in range(1, int(num ** 0.5) + 1)]
for i in remains:
... | the_stack_v2_python_sparse | data_structure/queues_and_stacks/279_num_squares.py | yangtao0304/hands-on-programming-exercise | train | 0 | |
cf0f1df8f532da2aefa06001d44d225cb74eaf3a | [
"region_spec = concepts.ResourceSpec('cloudbuild.projects.locations', resource_name='region', projectsId=concepts.DEFAULT_PROJECT_ATTRIBUTE_CONFIG, locationsId=resource_args.RegionAttributeConfig())\nconcept_parsers.ConceptParser.ForResource('--region', region_spec, 'Cloud region', required=True).AddToParser(parser... | <|body_start_0|>
region_spec = concepts.ResourceSpec('cloudbuild.projects.locations', resource_name='region', projectsId=concepts.DEFAULT_PROJECT_ATTRIBUTE_CONFIG, locationsId=resource_args.RegionAttributeConfig())
concept_parsers.ConceptParser.ForResource('--region', region_spec, 'Cloud region', requir... | Create a build trigger for a GCB v2 repository. | CreateRepository | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateRepository:
"""Create a build trigger for a GCB v2 repository."""
def Args(parser):
"""Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser."""
<|... | stack_v2_sparse_classes_10k_train_004938 | 7,136 | permissive | [
{
"docstring": "Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "Parses command line arguments int... | 3 | null | Implement the Python class `CreateRepository` described below.
Class description:
Create a build trigger for a GCB v2 repository.
Method signatures and docstrings:
- def Args(parser): Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some infor... | Implement the Python class `CreateRepository` described below.
Class description:
Create a build trigger for a GCB v2 repository.
Method signatures and docstrings:
- def Args(parser): Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some infor... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class CreateRepository:
"""Create a build trigger for a GCB v2 repository."""
def Args(parser):
"""Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser."""
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CreateRepository:
"""Create a build trigger for a GCB v2 repository."""
def Args(parser):
"""Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser."""
region_spec = c... | the_stack_v2_python_sparse | lib/surface/builds/triggers/create/repository.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
1738ed8d4580f1107dfbee9373698fe766ade0ac | [
"ENFORCER.enforce_call(action='identity:list_project_tags', build_target=_build_project_target_enforcement)\nref = PROVIDERS.resource_api.list_project_tags(project_id)\nreturn self.wrap_member(ref)",
"ENFORCER.enforce_call(action='identity:update_project_tags', build_target=_build_project_target_enforcement)\ntag... | <|body_start_0|>
ENFORCER.enforce_call(action='identity:list_project_tags', build_target=_build_project_target_enforcement)
ref = PROVIDERS.resource_api.list_project_tags(project_id)
return self.wrap_member(ref)
<|end_body_0|>
<|body_start_1|>
ENFORCER.enforce_call(action='identity:upda... | ProjectTagsResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectTagsResource:
def get(self, project_id):
"""List tags associated with a given project. GET /v3/projects/{project_id}/tags"""
<|body_0|>
def put(self, project_id):
"""Update all tags associated with a given project. PUT /v3/projects/{project_id}/tags"""
... | stack_v2_sparse_classes_10k_train_004939 | 22,149 | permissive | [
{
"docstring": "List tags associated with a given project. GET /v3/projects/{project_id}/tags",
"name": "get",
"signature": "def get(self, project_id)"
},
{
"docstring": "Update all tags associated with a given project. PUT /v3/projects/{project_id}/tags",
"name": "put",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_002411 | Implement the Python class `ProjectTagsResource` described below.
Class description:
Implement the ProjectTagsResource class.
Method signatures and docstrings:
- def get(self, project_id): List tags associated with a given project. GET /v3/projects/{project_id}/tags
- def put(self, project_id): Update all tags associ... | Implement the Python class `ProjectTagsResource` described below.
Class description:
Implement the ProjectTagsResource class.
Method signatures and docstrings:
- def get(self, project_id): List tags associated with a given project. GET /v3/projects/{project_id}/tags
- def put(self, project_id): Update all tags associ... | 03a0a8146a78682ede9eca12a5a7fdacde2035c8 | <|skeleton|>
class ProjectTagsResource:
def get(self, project_id):
"""List tags associated with a given project. GET /v3/projects/{project_id}/tags"""
<|body_0|>
def put(self, project_id):
"""Update all tags associated with a given project. PUT /v3/projects/{project_id}/tags"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProjectTagsResource:
def get(self, project_id):
"""List tags associated with a given project. GET /v3/projects/{project_id}/tags"""
ENFORCER.enforce_call(action='identity:list_project_tags', build_target=_build_project_target_enforcement)
ref = PROVIDERS.resource_api.list_project_tags(... | the_stack_v2_python_sparse | keystone/api/projects.py | sapcc/keystone | train | 0 | |
44ee63fa031f015a32b8a8d6083697416065d539 | [
"self.destination = destination\nself.from_user_id = from_user_id\nself.to_user_id = to_user_id\nself.project_id = project_id\nself.project_name = project_name\nself.auth_role = auth_role\nself.user_message = user_message\nself.share_user_ids = share_user_ids",
"item_id = self.get_existing_item_id(api)\nif not it... | <|body_start_0|>
self.destination = destination
self.from_user_id = from_user_id
self.to_user_id = to_user_id
self.project_id = project_id
self.project_name = project_name
self.auth_role = auth_role
self.user_message = user_message
self.share_user_ids = sh... | Contains data for processing either share or deliver. | D4S2Item | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class D4S2Item:
"""Contains data for processing either share or deliver."""
def __init__(self, destination, from_user_id, to_user_id, project_id, project_name, auth_role, user_message, share_user_ids):
"""Save data for use with send method. :param destination: str type of message we are se... | stack_v2_sparse_classes_10k_train_004940 | 21,979 | permissive | [
{
"docstring": "Save data for use with send method. :param destination: str type of message we are sending(SHARE_DESTINATION or DELIVER_DESTINATION) :param from_user_id: str uuid(duke-data-service) of the user who is sending the share/delivery :param to_user_id: str uuid(duke-data-service) of the user is receiv... | 4 | stack_v2_sparse_classes_30k_train_006759 | Implement the Python class `D4S2Item` described below.
Class description:
Contains data for processing either share or deliver.
Method signatures and docstrings:
- def __init__(self, destination, from_user_id, to_user_id, project_id, project_name, auth_role, user_message, share_user_ids): Save data for use with send ... | Implement the Python class `D4S2Item` described below.
Class description:
Contains data for processing either share or deliver.
Method signatures and docstrings:
- def __init__(self, destination, from_user_id, to_user_id, project_id, project_name, auth_role, user_message, share_user_ids): Save data for use with send ... | 0e9d058429de915b8da5afefb21186f6b69cc235 | <|skeleton|>
class D4S2Item:
"""Contains data for processing either share or deliver."""
def __init__(self, destination, from_user_id, to_user_id, project_id, project_name, auth_role, user_message, share_user_ids):
"""Save data for use with send method. :param destination: str type of message we are se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class D4S2Item:
"""Contains data for processing either share or deliver."""
def __init__(self, destination, from_user_id, to_user_id, project_id, project_name, auth_role, user_message, share_user_ids):
"""Save data for use with send method. :param destination: str type of message we are sending(SHARE_D... | the_stack_v2_python_sparse | ddsc/core/d4s2.py | Duke-GCB/DukeDSClient | train | 6 |
350be941f0720ac139c61e422e69aafca0aee117 | [
"self.__subscriptions = []\nself.__publisher = None\nself.drop_policy = 'ignore'",
"try:\n if isinstance(subscription, Subscription):\n sub = Subscribe(subscription, self.__pool, self.myAddress)\n self.send(self.__pool, sub)\nexcept Exception:\n handle_actor_system_fail()",
"try:\n if isi... | <|body_start_0|>
self.__subscriptions = []
self.__publisher = None
self.drop_policy = 'ignore'
<|end_body_0|>
<|body_start_1|>
try:
if isinstance(subscription, Subscription):
sub = Subscribe(subscription, self.__pool, self.myAddress)
self.send... | Publisher. Publishes messages to subscribers. | Publisher | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Publisher:
"""Publisher. Publishes messages to subscribers."""
def __init__(self):
"""Constructor :param router: The router to use. All extend PubSub which is default. :type router: PubSub"""
<|body_0|>
def subscribe(self, subscription):
"""Subscribe a subscripti... | stack_v2_sparse_classes_10k_train_004941 | 3,196 | permissive | [
{
"docstring": "Constructor :param router: The router to use. All extend PubSub which is default. :type router: PubSub",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Subscribe a subscription actor :param subscription: The subscription to use :type subscription: Subscr... | 6 | stack_v2_sparse_classes_30k_train_001363 | Implement the Python class `Publisher` described below.
Class description:
Publisher. Publishes messages to subscribers.
Method signatures and docstrings:
- def __init__(self): Constructor :param router: The router to use. All extend PubSub which is default. :type router: PubSub
- def subscribe(self, subscription): S... | Implement the Python class `Publisher` described below.
Class description:
Publisher. Publishes messages to subscribers.
Method signatures and docstrings:
- def __init__(self): Constructor :param router: The router to use. All extend PubSub which is default. :type router: PubSub
- def subscribe(self, subscription): S... | db93ea9acf58b0da12bcc78ab267e83f3c3c473b | <|skeleton|>
class Publisher:
"""Publisher. Publishes messages to subscribers."""
def __init__(self):
"""Constructor :param router: The router to use. All extend PubSub which is default. :type router: PubSub"""
<|body_0|>
def subscribe(self, subscription):
"""Subscribe a subscripti... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Publisher:
"""Publisher. Publishes messages to subscribers."""
def __init__(self):
"""Constructor :param router: The router to use. All extend PubSub which is default. :type router: PubSub"""
self.__subscriptions = []
self.__publisher = None
self.drop_policy = 'ignore'
... | the_stack_v2_python_sparse | reactive/streams/base_objects/publisher.py | xyicheng/ReactiveThespian | train | 0 |
54478c202509058514035cf7f88d25a00312b5bc | [
"Integrator.setup_integrator(self)\nself.setup_cl(context)\nself.cl_precision = self.particles.get_cl_precision()",
"self.context = context\nfor calc in self.calcs:\n calc.setup_cl(context)\nroot = get_pysph_root()\nsrc = cl_read(path.join(root, 'solver/integrator.cl'), self.particles.get_cl_precision())\nself... | <|body_start_0|>
Integrator.setup_integrator(self)
self.setup_cl(context)
self.cl_precision = self.particles.get_cl_precision()
<|end_body_0|>
<|body_start_1|>
self.context = context
for calc in self.calcs:
calc.setup_cl(context)
root = get_pysph_root()
... | CLIntegrator | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CLIntegrator:
def setup_integrator(self, context):
"""Setup the additional particle arrays for integration. Parameters: ----------- context -- the OpenCL context setup_cl on the calcs must be called when all particle properties on the particle array are created. This is important as all ... | stack_v2_sparse_classes_10k_train_004942 | 9,164 | permissive | [
{
"docstring": "Setup the additional particle arrays for integration. Parameters: ----------- context -- the OpenCL context setup_cl on the calcs must be called when all particle properties on the particle array are created. This is important as all device buffers will created.",
"name": "setup_integrator",... | 6 | stack_v2_sparse_classes_30k_train_003779 | Implement the Python class `CLIntegrator` described below.
Class description:
Implement the CLIntegrator class.
Method signatures and docstrings:
- def setup_integrator(self, context): Setup the additional particle arrays for integration. Parameters: ----------- context -- the OpenCL context setup_cl on the calcs mus... | Implement the Python class `CLIntegrator` described below.
Class description:
Implement the CLIntegrator class.
Method signatures and docstrings:
- def setup_integrator(self, context): Setup the additional particle arrays for integration. Parameters: ----------- context -- the OpenCL context setup_cl on the calcs mus... | 5bb1fc46a9c84aefd42758356a9986689db05454 | <|skeleton|>
class CLIntegrator:
def setup_integrator(self, context):
"""Setup the additional particle arrays for integration. Parameters: ----------- context -- the OpenCL context setup_cl on the calcs must be called when all particle properties on the particle array are created. This is important as all ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CLIntegrator:
def setup_integrator(self, context):
"""Setup the additional particle arrays for integration. Parameters: ----------- context -- the OpenCL context setup_cl on the calcs must be called when all particle properties on the particle array are created. This is important as all device buffers... | the_stack_v2_python_sparse | source/pysph/solver/cl_integrator.py | pankajp/pysph | train | 1 | |
0fc3a2ed33206875f71dde5dac974fd2acdbe63d | [
"@lru_cache(None)\ndef dfs(n):\n if n == 1:\n return 0\n ans = 0\n if n & 1:\n ans += 1 + min(dfs(n + 1), dfs(n - 1))\n else:\n ans += 1 + dfs(n // 2)\n return ans\nreturn dfs(n)",
"def dfs(n):\n if n in memo:\n return memo[n]\n ans = 0\n if n & 1:\n ans ... | <|body_start_0|>
@lru_cache(None)
def dfs(n):
if n == 1:
return 0
ans = 0
if n & 1:
ans += 1 + min(dfs(n + 1), dfs(n - 1))
else:
ans += 1 + dfs(n // 2)
return ans
return dfs(n)
<|end_body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def integerReplacement1(self, n: int) -> int:
"""思路：记忆化递归-标准库 @param n: @return:"""
<|body_0|>
def integerReplacement2(self, n: int) -> int:
"""思路：记忆化递归-备忘录 @param n: @return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
@lru_cache(None... | stack_v2_sparse_classes_10k_train_004943 | 1,555 | no_license | [
{
"docstring": "思路：记忆化递归-标准库 @param n: @return:",
"name": "integerReplacement1",
"signature": "def integerReplacement1(self, n: int) -> int"
},
{
"docstring": "思路：记忆化递归-备忘录 @param n: @return:",
"name": "integerReplacement2",
"signature": "def integerReplacement2(self, n: int) -> int"
}... | 2 | stack_v2_sparse_classes_30k_train_006007 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerReplacement1(self, n: int) -> int: 思路：记忆化递归-标准库 @param n: @return:
- def integerReplacement2(self, n: int) -> int: 思路：记忆化递归-备忘录 @param n: @return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerReplacement1(self, n: int) -> int: 思路：记忆化递归-标准库 @param n: @return:
- def integerReplacement2(self, n: int) -> int: 思路：记忆化递归-备忘录 @param n: @return:
<|skeleton|>
class ... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def integerReplacement1(self, n: int) -> int:
"""思路：记忆化递归-标准库 @param n: @return:"""
<|body_0|>
def integerReplacement2(self, n: int) -> int:
"""思路：记忆化递归-备忘录 @param n: @return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def integerReplacement1(self, n: int) -> int:
"""思路：记忆化递归-标准库 @param n: @return:"""
@lru_cache(None)
def dfs(n):
if n == 1:
return 0
ans = 0
if n & 1:
ans += 1 + min(dfs(n + 1), dfs(n - 1))
else:
... | the_stack_v2_python_sparse | LeetCode/记忆化/397. 整数替换.py | yiming1012/MyLeetCode | train | 2 | |
8e8882f1ef437e2cf4589b6cb9190bc70df1a60c | [
"if postorder:\n root = TreeNode(postorder.pop())\n ind = inorder.index(root.val)\n root.left = self.buildTree(inorder[:ind], postorder[:ind])\n root.right = self.buildTree(inorder[ind + 1:], postorder[ind:])\n return root\nreturn None",
"temp = []\nnodes = []\ncurrent = root\nwhile current:\n i... | <|body_start_0|>
if postorder:
root = TreeNode(postorder.pop())
ind = inorder.index(root.val)
root.left = self.buildTree(inorder[:ind], postorder[:ind])
root.right = self.buildTree(inorder[ind + 1:], postorder[ind:])
return root
return None
<|e... | 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 inorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_10k_train_004944 | 1,501 | no_license | [
{
"docstring": ":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode",
"name": "buildTree",
"signature": "def buildTree(self, inorder, postorder)"
},
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "inorderTraversal",
"signature": "def inorderTraversal(se... | 2 | stack_v2_sparse_classes_30k_train_002494 | 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 inorderTraversal(self, root): :type root: TreeNode :rtype: Lis... | 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 inorderTraversal(self, root): :type root: TreeNode :rtype: Lis... | 6e4129d7c092be933497da2156680d25f72e42a4 | <|skeleton|>
class Solution:
def buildTree(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
<|body_0|>
def inorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def buildTree(self, inorder, postorder):
""":type inorder: List[int] :type postorder: List[int] :rtype: TreeNode"""
if postorder:
root = TreeNode(postorder.pop())
ind = inorder.index(root.val)
root.left = self.buildTree(inorder[:ind], postorder[:in... | the_stack_v2_python_sparse | 106_construct-binary-tree-from-inorder-and-postorder-traversal.py | setu4993/LeetCode | train | 0 | |
2bec81149662312e79c4bf490537b81533701d67 | [
"def _commands_help(topic):\n com = obj.get('endroid.plugins.command')\n return com._help_main(topic, plugin=obj)\nif not 'commands' in obj._help_topics:\n setattr(obj, 'help_topics', {'commands': _commands_help})\nreturn obj._help_topics",
"topics = obj._help_topics.copy()\ntopics.update(value)\nobj._he... | <|body_start_0|>
def _commands_help(topic):
com = obj.get('endroid.plugins.command')
return com._help_main(topic, plugin=obj)
if not 'commands' in obj._help_topics:
setattr(obj, 'help_topics', {'commands': _commands_help})
return obj._help_topics
<|end_body_0|... | Descriptor to handle auto-updating of the help_topics. This is required if a plugin doesn't just define its help_topics at the class level, and instead sets it during its initialisation. This descriptor will update the help_topics instead of replacing them when set. | _Topics | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Topics:
"""Descriptor to handle auto-updating of the help_topics. This is required if a plugin doesn't just define its help_topics at the class level, and instead sets it during its initialisation. This descriptor will update the help_topics instead of replacing them when set."""
def __get_... | stack_v2_sparse_classes_10k_train_004945 | 13,347 | no_license | [
{
"docstring": "As well as fetching the help_topics (from the _help_topics field), this also injects the 'commands' entry into topics. It is done here, as this is the first point at which we have an instance of the plugin (needed to do the filtering later when displaying the help). Moral of the story: injecting... | 2 | stack_v2_sparse_classes_30k_train_003260 | Implement the Python class `_Topics` described below.
Class description:
Descriptor to handle auto-updating of the help_topics. This is required if a plugin doesn't just define its help_topics at the class level, and instead sets it during its initialisation. This descriptor will update the help_topics instead of repl... | Implement the Python class `_Topics` described below.
Class description:
Descriptor to handle auto-updating of the help_topics. This is required if a plugin doesn't just define its help_topics at the class level, and instead sets it during its initialisation. This descriptor will update the help_topics instead of repl... | 26e19a67551c0524186c096439c33eaa003c8f20 | <|skeleton|>
class _Topics:
"""Descriptor to handle auto-updating of the help_topics. This is required if a plugin doesn't just define its help_topics at the class level, and instead sets it during its initialisation. This descriptor will update the help_topics instead of replacing them when set."""
def __get_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _Topics:
"""Descriptor to handle auto-updating of the help_topics. This is required if a plugin doesn't just define its help_topics at the class level, and instead sets it during its initialisation. This descriptor will update the help_topics instead of replacing them when set."""
def __get__(self, obj, ... | the_stack_v2_python_sparse | src/endroid/plugins/command.py | ensoft/endroid | train | 0 |
c13c0c436c5e436f594253a29b25b05189225cb8 | [
"ressource_options = default_ressource_options(request, current_app)\nif rss_name:\n RssUtils.validate_rss_name(rss_name)\n spec = {'name': {'$regex': rss_name}}\nelse:\n spec = {}\nresults = current_app.mongo.finder(cursor=current_app.mongo.rss, spec=spec)\ndata = [document for document in results]\nretur... | <|body_start_0|>
ressource_options = default_ressource_options(request, current_app)
if rss_name:
RssUtils.validate_rss_name(rss_name)
spec = {'name': {'$regex': rss_name}}
else:
spec = {}
results = current_app.mongo.finder(cursor=current_app.mongo.rss... | docstrings | Rss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rss:
"""docstrings"""
def get(self, rss_name=None):
"""retrieve the list of a rss"""
<|body_0|>
def post(self):
"""add a new rss @post data: <name> <url>"""
<|body_1|>
def patch(self, rss_name):
"""patch a rss for the givent rss_name paramete... | stack_v2_sparse_classes_10k_train_004946 | 2,828 | permissive | [
{
"docstring": "retrieve the list of a rss",
"name": "get",
"signature": "def get(self, rss_name=None)"
},
{
"docstring": "add a new rss @post data: <name> <url>",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "patch a rss for the givent rss_name parameter @patc... | 3 | stack_v2_sparse_classes_30k_train_003600 | Implement the Python class `Rss` described below.
Class description:
docstrings
Method signatures and docstrings:
- def get(self, rss_name=None): retrieve the list of a rss
- def post(self): add a new rss @post data: <name> <url>
- def patch(self, rss_name): patch a rss for the givent rss_name parameter @patch data: ... | Implement the Python class `Rss` described below.
Class description:
docstrings
Method signatures and docstrings:
- def get(self, rss_name=None): retrieve the list of a rss
- def post(self): add a new rss @post data: <name> <url>
- def patch(self, rss_name): patch a rss for the givent rss_name parameter @patch data: ... | 657304c8b017a98935de9728fc695abe8be7cc4f | <|skeleton|>
class Rss:
"""docstrings"""
def get(self, rss_name=None):
"""retrieve the list of a rss"""
<|body_0|>
def post(self):
"""add a new rss @post data: <name> <url>"""
<|body_1|>
def patch(self, rss_name):
"""patch a rss for the givent rss_name paramete... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Rss:
"""docstrings"""
def get(self, rss_name=None):
"""retrieve the list of a rss"""
ressource_options = default_ressource_options(request, current_app)
if rss_name:
RssUtils.validate_rss_name(rss_name)
spec = {'name': {'$regex': rss_name}}
else:
... | the_stack_v2_python_sparse | Observer/api/resources/rss.py | Lujeni/old-projects | train | 0 |
43debd58cd0ea6ce7012740db86698eda79cfb55 | [
"if self.domain and self.suffix:\n return self.domain + '.' + self.suffix\nreturn ''",
"if self.domain and self.suffix:\n return '.'.join((i for i in self if i))\nreturn ''",
"if not (self.suffix or self.subdomain) and IP_RE.match(self.domain):\n return self.domain\nreturn ''"
] | <|body_start_0|>
if self.domain and self.suffix:
return self.domain + '.' + self.suffix
return ''
<|end_body_0|>
<|body_start_1|>
if self.domain and self.suffix:
return '.'.join((i for i in self if i))
return ''
<|end_body_1|>
<|body_start_2|>
if not (se... | namedtuple of a URL's subdomain, domain, and suffix. | ExtractResult | [
"GPL-3.0-only",
"Python-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtractResult:
"""namedtuple of a URL's subdomain, domain, and suffix."""
def registered_domain(self):
"""Joins the domain and suffix fields with a dot, if they're both set. >>> extract('http://forums.bbc.co.uk').registered_domain 'bbc.co.uk' >>> extract('http://localhost:8080').regi... | stack_v2_sparse_classes_10k_train_004947 | 7,568 | permissive | [
{
"docstring": "Joins the domain and suffix fields with a dot, if they're both set. >>> extract('http://forums.bbc.co.uk').registered_domain 'bbc.co.uk' >>> extract('http://localhost:8080').registered_domain ''",
"name": "registered_domain",
"signature": "def registered_domain(self)"
},
{
"docst... | 3 | null | Implement the Python class `ExtractResult` described below.
Class description:
namedtuple of a URL's subdomain, domain, and suffix.
Method signatures and docstrings:
- def registered_domain(self): Joins the domain and suffix fields with a dot, if they're both set. >>> extract('http://forums.bbc.co.uk').registered_dom... | Implement the Python class `ExtractResult` described below.
Class description:
namedtuple of a URL's subdomain, domain, and suffix.
Method signatures and docstrings:
- def registered_domain(self): Joins the domain and suffix fields with a dot, if they're both set. >>> extract('http://forums.bbc.co.uk').registered_dom... | b6edb06fc4e53a90c756459d7c03f8b33692b42b | <|skeleton|>
class ExtractResult:
"""namedtuple of a URL's subdomain, domain, and suffix."""
def registered_domain(self):
"""Joins the domain and suffix fields with a dot, if they're both set. >>> extract('http://forums.bbc.co.uk').registered_domain 'bbc.co.uk' >>> extract('http://localhost:8080').regi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExtractResult:
"""namedtuple of a URL's subdomain, domain, and suffix."""
def registered_domain(self):
"""Joins the domain and suffix fields with a dot, if they're both set. >>> extract('http://forums.bbc.co.uk').registered_domain 'bbc.co.uk' >>> extract('http://localhost:8080').registered_domain... | the_stack_v2_python_sparse | python/app/thirdparty/oneforall/common/tldextract.py | taomujian/linbing | train | 545 |
6f9caafc549beea5b3756706faed5ee5ee719966 | [
"self.ser = serial.Serial(port=serial_port, timeout=timeout, write_timeout=write_timeout)\nself._serial_port = serial_port\nself._attr_name = name\nself._attributes = {LAMP_HOURS: STATE_UNKNOWN, INPUT_SOURCE: STATE_UNKNOWN, ECO_MODE: STATE_UNKNOWN}",
"ret = ''\ntry:\n if not self.ser.is_open:\n self.ser... | <|body_start_0|>
self.ser = serial.Serial(port=serial_port, timeout=timeout, write_timeout=write_timeout)
self._serial_port = serial_port
self._attr_name = name
self._attributes = {LAMP_HOURS: STATE_UNKNOWN, INPUT_SOURCE: STATE_UNKNOWN, ECO_MODE: STATE_UNKNOWN}
<|end_body_0|>
<|body_sta... | Represents an Acer Projector as a switch. | AcerSwitch | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AcerSwitch:
"""Represents an Acer Projector as a switch."""
def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None:
"""Init of the Acer projector."""
<|body_0|>
def _write_read(self, msg: str) -> str:
"""Write to the projector a... | stack_v2_sparse_classes_10k_train_004948 | 4,527 | permissive | [
{
"docstring": "Init of the Acer projector.",
"name": "__init__",
"signature": "def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None"
},
{
"docstring": "Write to the projector and read the return.",
"name": "_write_read",
"signature": "def _write_read... | 6 | null | Implement the Python class `AcerSwitch` described below.
Class description:
Represents an Acer Projector as a switch.
Method signatures and docstrings:
- def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None: Init of the Acer projector.
- def _write_read(self, msg: str) -> str: Wri... | Implement the Python class `AcerSwitch` described below.
Class description:
Represents an Acer Projector as a switch.
Method signatures and docstrings:
- def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None: Init of the Acer projector.
- def _write_read(self, msg: str) -> str: Wri... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class AcerSwitch:
"""Represents an Acer Projector as a switch."""
def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None:
"""Init of the Acer projector."""
<|body_0|>
def _write_read(self, msg: str) -> str:
"""Write to the projector a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AcerSwitch:
"""Represents an Acer Projector as a switch."""
def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None:
"""Init of the Acer projector."""
self.ser = serial.Serial(port=serial_port, timeout=timeout, write_timeout=write_timeout)
self._s... | the_stack_v2_python_sparse | homeassistant/components/acer_projector/switch.py | home-assistant/core | train | 35,501 |
03cf94c6ce8ba1a25d1d14423071f393a949d212 | [
"if root:\n if root.left and root.right:\n return self.isSameTree(root.left, root.right)\n elif not root.left and (not root.right):\n return True\n else:\n return False\nelse:\n return True",
"if not (p and q or (not p and (not q))):\n return False\nif p:\n if p.val != q.val... | <|body_start_0|>
if root:
if root.left and root.right:
return self.isSameTree(root.left, root.right)
elif not root.left and (not root.right):
return True
else:
return False
else:
return True
<|end_body_0|>
<... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isSameTree(self, p, q):
""":type p: TreeNode :type q: TreeNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root:
if root.le... | stack_v2_sparse_classes_10k_train_004949 | 885 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isSymmetric",
"signature": "def isSymmetric(self, root)"
},
{
"docstring": ":type p: TreeNode :type q: TreeNode :rtype: bool",
"name": "isSameTree",
"signature": "def isSameTree(self, p, q)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000154 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isSymmetric(self, root): :type root: TreeNode :rtype: bool
- def isSameTree(self, p, q): :type p: TreeNode :type q: TreeNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isSymmetric(self, root): :type root: TreeNode :rtype: bool
- def isSameTree(self, p, q): :type p: TreeNode :type q: TreeNode :rtype: bool
<|skeleton|>
class Solution:
d... | 2711bc08f15266bec4ca135e8e3e629df46713eb | <|skeleton|>
class Solution:
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isSameTree(self, p, q):
""":type p: TreeNode :type q: TreeNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
if root:
if root.left and root.right:
return self.isSameTree(root.left, root.right)
elif not root.left and (not root.right):
return True
else:
... | the_stack_v2_python_sparse | 0.算法/101_Symmetric_Tree.py | unlimitediw/CheckCode | train | 0 | |
4d2f236e01d15de1940ea12c64551c74448a6743 | [
"self.d = dict()\nself.begin = Trie('')\nfor i, v in enumerate(sentences):\n self.begin.insert(v, v, times[i])\n self.d[v] = times[i]\nself.t = self.begin\nself.input_s = ''",
"ans = []\nif c == '#':\n self.d[self.input_s] = self.d.get(self.input_s, 0) + 1\n self.begin.insert(self.input_s, self.input_... | <|body_start_0|>
self.d = dict()
self.begin = Trie('')
for i, v in enumerate(sentences):
self.begin.insert(v, v, times[i])
self.d[v] = times[i]
self.t = self.begin
self.input_s = ''
<|end_body_0|>
<|body_start_1|>
ans = []
if c == '#':
... | AutocompleteSystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.d = dict()
... | stack_v2_sparse_classes_10k_train_004950 | 1,816 | no_license | [
{
"docstring": ":type sentences: List[str] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, sentences, times)"
},
{
"docstring": ":type c: str :rtype: List[str]",
"name": "input",
"signature": "def input(self, c)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004228 | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str] | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str]
<|skeleton|>
cla... | 9eb44afa4233fdedc2e5c72be0fdf54b25d1c45c | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
self.d = dict()
self.begin = Trie('')
for i, v in enumerate(sentences):
self.begin.insert(v, v, times[i])
self.d[v] = times[i]
self.... | the_stack_v2_python_sparse | Facebook/Pro642. Design Search Autocomplete System.py | YoyinZyc/Leetcode_Python | train | 0 | |
224b6a9b58d06e8efff273ed5952ca27e045022a | [
"for line in self:\n line.overdue_amount = 0\n if line.type == 'out_invoice':\n payments_obj = self.env['account.payment'].search([('partner_id', '=', line.partner_id.id), ('state', '=', 'posted'), ('bulk_payment_id.state', 'in', ['cheque_on_hand', 'deposited']), ('payment_type_name', '=', 'Cheque')])\... | <|body_start_0|>
for line in self:
line.overdue_amount = 0
if line.type == 'out_invoice':
payments_obj = self.env['account.payment'].search([('partner_id', '=', line.partner_id.id), ('state', '=', 'posted'), ('bulk_payment_id.state', 'in', ['cheque_on_hand', 'deposited'])... | AccountInvoiceInherit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountInvoiceInherit:
def _compute_overdue_amount(self):
"""Calculating Real outstanding by excluding all draft cheque payments"""
<|body_0|>
def _compute_stored_overdue_amount(self):
"""Calculating Real outstanding by excluding all draft cheque payments"""
... | stack_v2_sparse_classes_10k_train_004951 | 3,962 | no_license | [
{
"docstring": "Calculating Real outstanding by excluding all draft cheque payments",
"name": "_compute_overdue_amount",
"signature": "def _compute_overdue_amount(self)"
},
{
"docstring": "Calculating Real outstanding by excluding all draft cheque payments",
"name": "_compute_stored_overdue_... | 3 | stack_v2_sparse_classes_30k_train_007256 | Implement the Python class `AccountInvoiceInherit` described below.
Class description:
Implement the AccountInvoiceInherit class.
Method signatures and docstrings:
- def _compute_overdue_amount(self): Calculating Real outstanding by excluding all draft cheque payments
- def _compute_stored_overdue_amount(self): Calcu... | Implement the Python class `AccountInvoiceInherit` described below.
Class description:
Implement the AccountInvoiceInherit class.
Method signatures and docstrings:
- def _compute_overdue_amount(self): Calculating Real outstanding by excluding all draft cheque payments
- def _compute_stored_overdue_amount(self): Calcu... | b6b32366d966aa550af1de50fd4dd1f1e9daefd0 | <|skeleton|>
class AccountInvoiceInherit:
def _compute_overdue_amount(self):
"""Calculating Real outstanding by excluding all draft cheque payments"""
<|body_0|>
def _compute_stored_overdue_amount(self):
"""Calculating Real outstanding by excluding all draft cheque payments"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AccountInvoiceInherit:
def _compute_overdue_amount(self):
"""Calculating Real outstanding by excluding all draft cheque payments"""
for line in self:
line.overdue_amount = 0
if line.type == 'out_invoice':
payments_obj = self.env['account.payment'].search... | the_stack_v2_python_sparse | invoice_outstanding/models/account_invoice.py | EshangAllion/rts-payroll | train | 2 | |
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_10k_train_004952 | 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_004568 | 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_10k | 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 | |
2e7f6dac0b79271ba1d8184474af53820bae0490 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn TenantAppManagementPolicy()",
"from .app_management_configuration import AppManagementConfiguration\nfrom .policy_base import PolicyBase\nfrom .app_management_configuration import AppManagementConfiguration\nfrom .policy_base import Po... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return TenantAppManagementPolicy()
<|end_body_0|>
<|body_start_1|>
from .app_management_configuration import AppManagementConfiguration
from .policy_base import PolicyBase
from .app_man... | TenantAppManagementPolicy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TenantAppManagementPolicy:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TenantAppManagementPolicy:
"""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 c... | stack_v2_sparse_classes_10k_train_004953 | 3,160 | 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: TenantAppManagementPolicy",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrim... | 3 | stack_v2_sparse_classes_30k_train_006210 | Implement the Python class `TenantAppManagementPolicy` described below.
Class description:
Implement the TenantAppManagementPolicy class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TenantAppManagementPolicy: Creates a new instance of the appropriat... | Implement the Python class `TenantAppManagementPolicy` described below.
Class description:
Implement the TenantAppManagementPolicy class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TenantAppManagementPolicy: Creates a new instance of the appropriat... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class TenantAppManagementPolicy:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TenantAppManagementPolicy:
"""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 c... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TenantAppManagementPolicy:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TenantAppManagementPolicy:
"""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 obje... | the_stack_v2_python_sparse | msgraph/generated/models/tenant_app_management_policy.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e944924f06776adce205340fdb95884385004029 | [
"url = reverse('api-part-parameter-list')\nresponse = self.get(url)\nself.assertEqual(len(response.data), 7)\nresponse = self.get(url, {'part': 3})\nself.assertEqual(len(response.data), 3)\nresponse = self.get(url, {'template': 1})\nself.assertEqual(len(response.data), 4)",
"with self.assertRaises(django_exceptio... | <|body_start_0|>
url = reverse('api-part-parameter-list')
response = self.get(url)
self.assertEqual(len(response.data), 7)
response = self.get(url, {'part': 3})
self.assertEqual(len(response.data), 3)
response = self.get(url, {'template': 1})
self.assertEqual(len(... | Tests for the ParParameter API. | PartParameterTest | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PartParameterTest:
"""Tests for the ParParameter API."""
def test_list_params(self):
"""Test for listing part parameters."""
<|body_0|>
def test_param_template_validation(self):
"""Test that part parameter template validation routines work correctly."""
<... | stack_v2_sparse_classes_10k_train_004954 | 12,864 | permissive | [
{
"docstring": "Test for listing part parameters.",
"name": "test_list_params",
"signature": "def test_list_params(self)"
},
{
"docstring": "Test that part parameter template validation routines work correctly.",
"name": "test_param_template_validation",
"signature": "def test_param_temp... | 5 | stack_v2_sparse_classes_30k_test_000203 | Implement the Python class `PartParameterTest` described below.
Class description:
Tests for the ParParameter API.
Method signatures and docstrings:
- def test_list_params(self): Test for listing part parameters.
- def test_param_template_validation(self): Test that part parameter template validation routines work co... | Implement the Python class `PartParameterTest` described below.
Class description:
Tests for the ParParameter API.
Method signatures and docstrings:
- def test_list_params(self): Test for listing part parameters.
- def test_param_template_validation(self): Test that part parameter template validation routines work co... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class PartParameterTest:
"""Tests for the ParParameter API."""
def test_list_params(self):
"""Test for listing part parameters."""
<|body_0|>
def test_param_template_validation(self):
"""Test that part parameter template validation routines work correctly."""
<... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PartParameterTest:
"""Tests for the ParParameter API."""
def test_list_params(self):
"""Test for listing part parameters."""
url = reverse('api-part-parameter-list')
response = self.get(url)
self.assertEqual(len(response.data), 7)
response = self.get(url, {'part': ... | the_stack_v2_python_sparse | InvenTree/part/test_param.py | inventree/InvenTree | train | 3,077 |
4d9c5447d5c09557490f1a6f16236ecb19bf0b34 | [
"self.existing_tags_ids = [1, 2, 3, 4]\nself.content_id = 1\nself.tag_ids = [1, 5, 7]\nself.content = MagicMock(spec=Content, id=self.content_id, owner_id=21, tags=MagicMock(spec=Tag, all=MagicMock(return_value=MagicMock(values_list=MagicMock(return_value=self.existing_tags_ids)))))",
"mock_objects.get.return_val... | <|body_start_0|>
self.existing_tags_ids = [1, 2, 3, 4]
self.content_id = 1
self.tag_ids = [1, 5, 7]
self.content = MagicMock(spec=Content, id=self.content_id, owner_id=21, tags=MagicMock(spec=Tag, all=MagicMock(return_value=MagicMock(values_list=MagicMock(return_value=self.existing_tags_... | Test case for PushFeeds | TestStreamFeedsUtils | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestStreamFeedsUtils:
"""Test case for PushFeeds"""
def setUp(self):
"""SetUp method for test case"""
<|body_0|>
def test_update_content_tags_at_getsream(self, mock_objects, mock_delay, mock_parent_ids):
"""test case for testing the update_content_tags_at_getsrea... | stack_v2_sparse_classes_10k_train_004955 | 20,391 | no_license | [
{
"docstring": "SetUp method for test case",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "test case for testing the update_content_tags_at_getsream",
"name": "test_update_content_tags_at_getsream",
"signature": "def test_update_content_tags_at_getsream(self, mock_ob... | 2 | stack_v2_sparse_classes_30k_train_006473 | Implement the Python class `TestStreamFeedsUtils` described below.
Class description:
Test case for PushFeeds
Method signatures and docstrings:
- def setUp(self): SetUp method for test case
- def test_update_content_tags_at_getsream(self, mock_objects, mock_delay, mock_parent_ids): test case for testing the update_co... | Implement the Python class `TestStreamFeedsUtils` described below.
Class description:
Test case for PushFeeds
Method signatures and docstrings:
- def setUp(self): SetUp method for test case
- def test_update_content_tags_at_getsream(self, mock_objects, mock_delay, mock_parent_ids): test case for testing the update_co... | 248a7b406686c0c98e944319a6eca08485104f5d | <|skeleton|>
class TestStreamFeedsUtils:
"""Test case for PushFeeds"""
def setUp(self):
"""SetUp method for test case"""
<|body_0|>
def test_update_content_tags_at_getsream(self, mock_objects, mock_delay, mock_parent_ids):
"""test case for testing the update_content_tags_at_getsrea... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestStreamFeedsUtils:
"""Test case for PushFeeds"""
def setUp(self):
"""SetUp method for test case"""
self.existing_tags_ids = [1, 2, 3, 4]
self.content_id = 1
self.tag_ids = [1, 5, 7]
self.content = MagicMock(spec=Content, id=self.content_id, owner_id=21, tags=Mag... | the_stack_v2_python_sparse | common/feeds/tests.py | skshivammahajan/DRFChat | train | 0 |
7b982aa2d89c4863922a845486d87a8dd74a0055 | [
"res_list = []\nif root is None:\n return res_list\nres_list.append(root.val)\nres_left_list = self.preorderTraversal(root.left)\nres_list = res_list + res_left_list\nres_right_list = self.preorderTraversal(root.right)\nres_list = res_list + res_right_list\nreturn res_list",
"res_list = []\nif root is None:\n ... | <|body_start_0|>
res_list = []
if root is None:
return res_list
res_list.append(root.val)
res_left_list = self.preorderTraversal(root.left)
res_list = res_list + res_left_list
res_right_list = self.preorderTraversal(root.right)
res_list = res_list + re... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
"""递归 :type root: TreeNode :rtype: List[int]"""
<|body_0|>
def preorderTraversal2(self, root):
"""迭代，利用队列 :type root: TreeNode :rtype: List[int]"""
<|body_1|>
def preorderTraversal3(self, root):
"""迭代，... | stack_v2_sparse_classes_10k_train_004956 | 2,391 | no_license | [
{
"docstring": "递归 :type root: TreeNode :rtype: List[int]",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, root)"
},
{
"docstring": "迭代，利用队列 :type root: TreeNode :rtype: List[int]",
"name": "preorderTraversal2",
"signature": "def preorderTraversal2(self, root)"
... | 3 | stack_v2_sparse_classes_30k_train_004249 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): 递归 :type root: TreeNode :rtype: List[int]
- def preorderTraversal2(self, root): 迭代，利用队列 :type root: TreeNode :rtype: List[int]
- def preorderTr... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): 递归 :type root: TreeNode :rtype: List[int]
- def preorderTraversal2(self, root): 迭代，利用队列 :type root: TreeNode :rtype: List[int]
- def preorderTr... | f564806bd8e18831eeb20f2fd4bdd2d4aaa829ce | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
"""递归 :type root: TreeNode :rtype: List[int]"""
<|body_0|>
def preorderTraversal2(self, root):
"""迭代，利用队列 :type root: TreeNode :rtype: List[int]"""
<|body_1|>
def preorderTraversal3(self, root):
"""迭代，... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def preorderTraversal(self, root):
"""递归 :type root: TreeNode :rtype: List[int]"""
res_list = []
if root is None:
return res_list
res_list.append(root.val)
res_left_list = self.preorderTraversal(root.left)
res_list = res_list + res_left_lis... | the_stack_v2_python_sparse | Week 02/id_684/LeetCode_144_684.py | cboopen/algorithm004-04 | train | 2 | |
b5303726718e72dcbc078532a7ed19f0047f14e8 | [
"if obj.user_id:\n return self.get_user_member(obj['user'])\nelif obj.group_id:\n return self.get_group_member(obj['group'])",
"profile = user.get('profile', {})\nname = profile.get('full_name') or user.get('username') or _('Untitled')\ndescription = profile.get('affiliations') or ''\nfake_user_obj = Simple... | <|body_start_0|>
if obj.user_id:
return self.get_user_member(obj['user'])
elif obj.group_id:
return self.get_group_member(obj['group'])
<|end_body_0|>
<|body_start_1|>
profile = user.get('profile', {})
name = profile.get('full_name') or user.get('username') or _(... | Public Dump Schema. | PublicDumpSchema | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublicDumpSchema:
"""Public Dump Schema."""
def get_member(self, obj):
"""Get a member."""
<|body_0|>
def get_user_member(self, user):
"""Get a user member."""
<|body_1|>
def get_group_member(self, group):
"""Get a group member."""
<|... | stack_v2_sparse_classes_10k_train_004957 | 6,688 | permissive | [
{
"docstring": "Get a member.",
"name": "get_member",
"signature": "def get_member(self, obj)"
},
{
"docstring": "Get a user member.",
"name": "get_user_member",
"signature": "def get_user_member(self, user)"
},
{
"docstring": "Get a group member.",
"name": "get_group_member"... | 3 | stack_v2_sparse_classes_30k_train_002012 | Implement the Python class `PublicDumpSchema` described below.
Class description:
Public Dump Schema.
Method signatures and docstrings:
- def get_member(self, obj): Get a member.
- def get_user_member(self, user): Get a user member.
- def get_group_member(self, group): Get a group member. | Implement the Python class `PublicDumpSchema` described below.
Class description:
Public Dump Schema.
Method signatures and docstrings:
- def get_member(self, obj): Get a member.
- def get_user_member(self, user): Get a user member.
- def get_group_member(self, group): Get a group member.
<|skeleton|>
class PublicDu... | 9a17455c06bf606c19c6b1367e4e3d36bf017be9 | <|skeleton|>
class PublicDumpSchema:
"""Public Dump Schema."""
def get_member(self, obj):
"""Get a member."""
<|body_0|>
def get_user_member(self, user):
"""Get a user member."""
<|body_1|>
def get_group_member(self, group):
"""Get a group member."""
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PublicDumpSchema:
"""Public Dump Schema."""
def get_member(self, obj):
"""Get a member."""
if obj.user_id:
return self.get_user_member(obj['user'])
elif obj.group_id:
return self.get_group_member(obj['group'])
def get_user_member(self, user):
"... | the_stack_v2_python_sparse | invenio_communities/members/services/schemas.py | inveniosoftware/invenio-communities | train | 5 |
aa7029f71aa4f657ea5e28c5908cc715e9b77802 | [
"res = 0\nfor i in range(len(grid)):\n for j in range(len(grid[0])):\n if grid[i][j] == 1:\n self.step = 0\n self.dfs(grid, i, j)\n res = max(res, self.step)\nreturn res",
"if x < 0 or y < 0 or x > len(grid) - 1 or (y > len(grid[0]) - 1) or (grid[x][y] != 1):\n return... | <|body_start_0|>
res = 0
for i in range(len(grid)):
for j in range(len(grid[0])):
if grid[i][j] == 1:
self.step = 0
self.dfs(grid, i, j)
res = max(res, self.step)
return res
<|end_body_0|>
<|body_start_1|>
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxAreaOfIsland(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def dfs(self, grid, x, y):
""":type grid: List[list[int]] :type x: int :type y: int :rtype : None"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res... | stack_v2_sparse_classes_10k_train_004958 | 1,685 | permissive | [
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "maxAreaOfIsland",
"signature": "def maxAreaOfIsland(self, grid)"
},
{
"docstring": ":type grid: List[list[int]] :type x: int :type y: int :rtype : None",
"name": "dfs",
"signature": "def dfs(self, grid, x, y)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000347 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxAreaOfIsland(self, grid): :type grid: List[List[int]] :rtype: int
- def dfs(self, grid, x, y): :type grid: List[list[int]] :type x: int :type y: int :rtype : None | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxAreaOfIsland(self, grid): :type grid: List[List[int]] :rtype: int
- def dfs(self, grid, x, y): :type grid: List[list[int]] :type x: int :type y: int :rtype : None
<|skele... | 55c6c3e7890b596b709b50cafa415b9594c03edd | <|skeleton|>
class Solution:
def maxAreaOfIsland(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def dfs(self, grid, x, y):
""":type grid: List[list[int]] :type x: int :type y: int :rtype : None"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxAreaOfIsland(self, grid):
""":type grid: List[List[int]] :rtype: int"""
res = 0
for i in range(len(grid)):
for j in range(len(grid[0])):
if grid[i][j] == 1:
self.step = 0
self.dfs(grid, i, j)
... | the_stack_v2_python_sparse | max-area-of-island.py | summer-vacation/AlgoExec | train | 1 | |
741c6773ee9da987a6884ccf683917d9f868c4c8 | [
"kwargs = super(NewbobRelative, cls).load_initial_kwargs_from_config(config)\nkwargs.update({'relativeErrorThreshold': config.float('newbob_relative_error_threshold', -0.01), 'learningRateDecayFactor': config.float('newbob_learning_rate_decay', 0.5)})\nreturn kwargs",
"super(NewbobRelative, self).__init__(**kwarg... | <|body_start_0|>
kwargs = super(NewbobRelative, cls).load_initial_kwargs_from_config(config)
kwargs.update({'relativeErrorThreshold': config.float('newbob_relative_error_threshold', -0.01), 'learningRateDecayFactor': config.float('newbob_learning_rate_decay', 0.5)})
return kwargs
<|end_body_0|>
... | NewbobRelative | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewbobRelative:
def load_initial_kwargs_from_config(cls, config):
""":type config: Config.Config :rtype: dict[str]"""
<|body_0|>
def __init__(self, relativeErrorThreshold, learningRateDecayFactor, **kwargs):
""":param float defaultLearningRate: learning rate for epoc... | stack_v2_sparse_classes_10k_train_004959 | 19,323 | no_license | [
{
"docstring": ":type config: Config.Config :rtype: dict[str]",
"name": "load_initial_kwargs_from_config",
"signature": "def load_initial_kwargs_from_config(cls, config)"
},
{
"docstring": ":param float defaultLearningRate: learning rate for epoch 1+2 :type relativeErrorThreshold: float :type le... | 3 | null | Implement the Python class `NewbobRelative` described below.
Class description:
Implement the NewbobRelative class.
Method signatures and docstrings:
- def load_initial_kwargs_from_config(cls, config): :type config: Config.Config :rtype: dict[str]
- def __init__(self, relativeErrorThreshold, learningRateDecayFactor, ... | Implement the Python class `NewbobRelative` described below.
Class description:
Implement the NewbobRelative class.
Method signatures and docstrings:
- def load_initial_kwargs_from_config(cls, config): :type config: Config.Config :rtype: dict[str]
- def __init__(self, relativeErrorThreshold, learningRateDecayFactor, ... | d494b3041069d377d6a7a9c296a14334f2fa5acc | <|skeleton|>
class NewbobRelative:
def load_initial_kwargs_from_config(cls, config):
""":type config: Config.Config :rtype: dict[str]"""
<|body_0|>
def __init__(self, relativeErrorThreshold, learningRateDecayFactor, **kwargs):
""":param float defaultLearningRate: learning rate for epoc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NewbobRelative:
def load_initial_kwargs_from_config(cls, config):
""":type config: Config.Config :rtype: dict[str]"""
kwargs = super(NewbobRelative, cls).load_initial_kwargs_from_config(config)
kwargs.update({'relativeErrorThreshold': config.float('newbob_relative_error_threshold', -0.... | the_stack_v2_python_sparse | python/rwth-i6_returnn/returnn-master/LearningRateControl.py | LiuFang816/SALSTM_py_data | train | 10 | |
1a79384472c7b5858646db5c053721bf8dca7635 | [
"super(HonourAutoCombatHandler, self).start_combat()\nfor char in self.characters.values():\n character = char['char']\n character.start_auto_combat_skill()",
"for char in self.characters.values():\n character = char['char']\n character.stop_auto_combat_skill()\nsuper(HonourAutoCombatHandler, self).fi... | <|body_start_0|>
super(HonourAutoCombatHandler, self).start_combat()
for char in self.characters.values():
character = char['char']
character.start_auto_combat_skill()
<|end_body_0|>
<|body_start_1|>
for char in self.characters.values():
character = char['cha... | This implements the honour combat handler. | HonourAutoCombatHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HonourAutoCombatHandler:
"""This implements the honour combat handler."""
def start_combat(self):
"""Start a combat, make all NPCs to cast skills automatically."""
<|body_0|>
def finish(self):
"""Finish a combat. Send results to players, and kill all failed chara... | stack_v2_sparse_classes_10k_train_004960 | 887 | permissive | [
{
"docstring": "Start a combat, make all NPCs to cast skills automatically.",
"name": "start_combat",
"signature": "def start_combat(self)"
},
{
"docstring": "Finish a combat. Send results to players, and kill all failed characters.",
"name": "finish",
"signature": "def finish(self)"
}... | 2 | stack_v2_sparse_classes_30k_train_003699 | Implement the Python class `HonourAutoCombatHandler` described below.
Class description:
This implements the honour combat handler.
Method signatures and docstrings:
- def start_combat(self): Start a combat, make all NPCs to cast skills automatically.
- def finish(self): Finish a combat. Send results to players, and ... | Implement the Python class `HonourAutoCombatHandler` described below.
Class description:
This implements the honour combat handler.
Method signatures and docstrings:
- def start_combat(self): Start a combat, make all NPCs to cast skills automatically.
- def finish(self): Finish a combat. Send results to players, and ... | 4b4c6c0dc5cc237a5df012a05ed260fad1a793a7 | <|skeleton|>
class HonourAutoCombatHandler:
"""This implements the honour combat handler."""
def start_combat(self):
"""Start a combat, make all NPCs to cast skills automatically."""
<|body_0|>
def finish(self):
"""Finish a combat. Send results to players, and kill all failed chara... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HonourAutoCombatHandler:
"""This implements the honour combat handler."""
def start_combat(self):
"""Start a combat, make all NPCs to cast skills automatically."""
super(HonourAutoCombatHandler, self).start_combat()
for char in self.characters.values():
character = cha... | the_stack_v2_python_sparse | muddery/server/combat/honour_auto_combat_handler.py | nobodxbodon/muddery | train | 0 |
037d5658e5e85f09b18e9b0cab84902de5aed6fe | [
"super().__init__()\nassert use_masking != use_weighted_masking or not use_masking\nself.use_masking = use_masking\nself.use_weighted_masking = use_weighted_masking\nreduction = 'none' if self.use_weighted_masking else 'mean'\nself.l1_criterion = nn.L1Loss(reduction=reduction)\nself.mse_criterion = nn.MSELoss(reduc... | <|body_start_0|>
super().__init__()
assert use_masking != use_weighted_masking or not use_masking
self.use_masking = use_masking
self.use_weighted_masking = use_weighted_masking
reduction = 'none' if self.use_weighted_masking else 'mean'
self.l1_criterion = nn.L1Loss(redu... | Loss function module for Tacotron2. | Tacotron2Loss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tacotron2Loss:
"""Loss function module for Tacotron2."""
def __init__(self, use_masking=True, use_weighted_masking=False, bce_pos_weight=20.0):
"""Initialize Tactoron2 loss module. Args: use_masking (bool): Whether to apply masking for padded part in loss calculation. use_weighted_ma... | stack_v2_sparse_classes_10k_train_004961 | 46,210 | permissive | [
{
"docstring": "Initialize Tactoron2 loss module. Args: use_masking (bool): Whether to apply masking for padded part in loss calculation. use_weighted_masking (bool): Whether to apply weighted masking in loss calculation. bce_pos_weight (float): Weight of positive sample of stop token.",
"name": "__init__",... | 2 | stack_v2_sparse_classes_30k_train_000895 | Implement the Python class `Tacotron2Loss` described below.
Class description:
Loss function module for Tacotron2.
Method signatures and docstrings:
- def __init__(self, use_masking=True, use_weighted_masking=False, bce_pos_weight=20.0): Initialize Tactoron2 loss module. Args: use_masking (bool): Whether to apply mas... | Implement the Python class `Tacotron2Loss` described below.
Class description:
Loss function module for Tacotron2.
Method signatures and docstrings:
- def __init__(self, use_masking=True, use_weighted_masking=False, bce_pos_weight=20.0): Initialize Tactoron2 loss module. Args: use_masking (bool): Whether to apply mas... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class Tacotron2Loss:
"""Loss function module for Tacotron2."""
def __init__(self, use_masking=True, use_weighted_masking=False, bce_pos_weight=20.0):
"""Initialize Tactoron2 loss module. Args: use_masking (bool): Whether to apply masking for padded part in loss calculation. use_weighted_ma... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Tacotron2Loss:
"""Loss function module for Tacotron2."""
def __init__(self, use_masking=True, use_weighted_masking=False, bce_pos_weight=20.0):
"""Initialize Tactoron2 loss module. Args: use_masking (bool): Whether to apply masking for padded part in loss calculation. use_weighted_masking (bool):... | the_stack_v2_python_sparse | paddlespeech/t2s/modules/losses.py | anniyanvr/DeepSpeech-1 | train | 0 |
91201728441ca58c4e83f156ddb088b37387d498 | [
"self.SetStartDate(2013, 10, 7)\nself.SetEndDate(2013, 10, 11)\nself.SetCash(100000)\nself.symbols = [['SPY', SecurityType.Equity], ['EURUSD', SecurityType.Forex]]\nself.targets = []\nfor item in self.symbols:\n symbol = self.AddSecurity(item[1], item[0]).Symbol\n self.targets.append(PortfolioTarget(symbol, 0... | <|body_start_0|>
self.SetStartDate(2013, 10, 7)
self.SetEndDate(2013, 10, 11)
self.SetCash(100000)
self.symbols = [['SPY', SecurityType.Equity], ['EURUSD', SecurityType.Forex]]
self.targets = []
for item in self.symbols:
symbol = self.AddSecurity(item[1], item... | Collective2SignalExportDemonstrationAlgorithm | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Collective2SignalExportDemonstrationAlgorithm:
def Initialize(self):
"""Initialize the date and add all equity symbols present in list _symbols"""
<|body_0|>
def OnData(self, data):
"""Reduce the quantity of holdings for one security and increase the holdings to the ... | stack_v2_sparse_classes_10k_train_004962 | 4,637 | permissive | [
{
"docstring": "Initialize the date and add all equity symbols present in list _symbols",
"name": "Initialize",
"signature": "def Initialize(self)"
},
{
"docstring": "Reduce the quantity of holdings for one security and increase the holdings to the another one when the EMA's indicators crosses b... | 2 | null | Implement the Python class `Collective2SignalExportDemonstrationAlgorithm` described below.
Class description:
Implement the Collective2SignalExportDemonstrationAlgorithm class.
Method signatures and docstrings:
- def Initialize(self): Initialize the date and add all equity symbols present in list _symbols
- def OnDa... | Implement the Python class `Collective2SignalExportDemonstrationAlgorithm` described below.
Class description:
Implement the Collective2SignalExportDemonstrationAlgorithm class.
Method signatures and docstrings:
- def Initialize(self): Initialize the date and add all equity symbols present in list _symbols
- def OnDa... | b33dd3bc140e14b883f39ecf848a793cf7292277 | <|skeleton|>
class Collective2SignalExportDemonstrationAlgorithm:
def Initialize(self):
"""Initialize the date and add all equity symbols present in list _symbols"""
<|body_0|>
def OnData(self, data):
"""Reduce the quantity of holdings for one security and increase the holdings to the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Collective2SignalExportDemonstrationAlgorithm:
def Initialize(self):
"""Initialize the date and add all equity symbols present in list _symbols"""
self.SetStartDate(2013, 10, 7)
self.SetEndDate(2013, 10, 11)
self.SetCash(100000)
self.symbols = [['SPY', SecurityType.Equi... | the_stack_v2_python_sparse | Algorithm.Python/Collective2SignalExportDemonstrationAlgorithm.py | Capnode/Algoloop | train | 87 | |
77f8713c7443fb029ded2cb01acaebe8d1d8a8fd | [
"super(SmoothL1Loss, self).__init__()\nself.beta = desc['beta'] if 'beta' in desc else 1.0\nself.reduction = desc['reduction'] if 'reduction' in desc else 'mean'\nself.loss_weight = desc['loss_weight'] if 'loss_weight' in desc else 1.0",
"reduction = reduction_override if reduction_override else self.reduction\ni... | <|body_start_0|>
super(SmoothL1Loss, self).__init__()
self.beta = desc['beta'] if 'beta' in desc else 1.0
self.reduction = desc['reduction'] if 'reduction' in desc else 'mean'
self.loss_weight = desc['loss_weight'] if 'loss_weight' in desc else 1.0
<|end_body_0|>
<|body_start_1|>
... | Smooth L1 Loss. | SmoothL1Loss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmoothL1Loss:
"""Smooth L1 Loss."""
def __init__(self, desc):
"""Init smooth l1 loss. :param desc: config dict"""
<|body_0|>
def forward(self, pred, target, weight=None, avg_factor=None, reduction_override=None, **kwargs):
"""Forward compute. :param pred: predict... | stack_v2_sparse_classes_10k_train_004963 | 2,297 | permissive | [
{
"docstring": "Init smooth l1 loss. :param desc: config dict",
"name": "__init__",
"signature": "def __init__(self, desc)"
},
{
"docstring": "Forward compute. :param pred: predict :param target: target :param weight: weight :param avg_factor: avg factor :param reduction_override: reduce overrid... | 2 | stack_v2_sparse_classes_30k_train_000315 | Implement the Python class `SmoothL1Loss` described below.
Class description:
Smooth L1 Loss.
Method signatures and docstrings:
- def __init__(self, desc): Init smooth l1 loss. :param desc: config dict
- def forward(self, pred, target, weight=None, avg_factor=None, reduction_override=None, **kwargs): Forward compute.... | Implement the Python class `SmoothL1Loss` described below.
Class description:
Smooth L1 Loss.
Method signatures and docstrings:
- def __init__(self, desc): Init smooth l1 loss. :param desc: config dict
- def forward(self, pred, target, weight=None, avg_factor=None, reduction_override=None, **kwargs): Forward compute.... | e4ef3a1c92d19d1d08c3ef0e2156b6fecefdbe04 | <|skeleton|>
class SmoothL1Loss:
"""Smooth L1 Loss."""
def __init__(self, desc):
"""Init smooth l1 loss. :param desc: config dict"""
<|body_0|>
def forward(self, pred, target, weight=None, avg_factor=None, reduction_override=None, **kwargs):
"""Forward compute. :param pred: predict... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SmoothL1Loss:
"""Smooth L1 Loss."""
def __init__(self, desc):
"""Init smooth l1 loss. :param desc: config dict"""
super(SmoothL1Loss, self).__init__()
self.beta = desc['beta'] if 'beta' in desc else 1.0
self.reduction = desc['reduction'] if 'reduction' in desc else 'mean'
... | the_stack_v2_python_sparse | zeus/networks/pytorch/losses/smooth_l1_loss.py | huawei-noah/xingtian | train | 308 |
3a853e31d9c343085a28a64cf7019df3b1142925 | [
"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 data of the Project resource. | ProjectDataServiceServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectDataServiceServicer:
"""A set of methods for managing data of the Project resource."""
def UploadFile(self, request_iterator, context):
"""Uploads a file to the specified project."""
<|body_0|>
def DownloadFile(self, request, context):
"""Downloads the spe... | stack_v2_sparse_classes_10k_train_004964 | 5,007 | permissive | [
{
"docstring": "Uploads a file to the specified project.",
"name": "UploadFile",
"signature": "def UploadFile(self, request_iterator, context)"
},
{
"docstring": "Downloads the specified file from the specified project.",
"name": "DownloadFile",
"signature": "def DownloadFile(self, reque... | 2 | stack_v2_sparse_classes_30k_train_004302 | Implement the Python class `ProjectDataServiceServicer` described below.
Class description:
A set of methods for managing data of the Project resource.
Method signatures and docstrings:
- def UploadFile(self, request_iterator, context): Uploads a file to the specified project.
- def DownloadFile(self, request, contex... | Implement the Python class `ProjectDataServiceServicer` described below.
Class description:
A set of methods for managing data of the Project resource.
Method signatures and docstrings:
- def UploadFile(self, request_iterator, context): Uploads a file to the specified project.
- def DownloadFile(self, request, contex... | b906a014dd893e2697864e1e48e814a8d9fbc48c | <|skeleton|>
class ProjectDataServiceServicer:
"""A set of methods for managing data of the Project resource."""
def UploadFile(self, request_iterator, context):
"""Uploads a file to the specified project."""
<|body_0|>
def DownloadFile(self, request, context):
"""Downloads the spe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProjectDataServiceServicer:
"""A set of methods for managing data of the Project resource."""
def UploadFile(self, request_iterator, context):
"""Uploads a file to the specified project."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented... | the_stack_v2_python_sparse | yandex/cloud/datasphere/v1/project_data_service_pb2_grpc.py | yandex-cloud/python-sdk | train | 63 |
f4925c088c1a78c3f5e5e35ebba5d6dc528e92d5 | [
"if order is None:\n raise ValueError('Polynomial order cannot be None')\nCenteredBasisFn.__init__(self, **kwargs)\nTimefnCollection.__init__(self)\nself.build(order=order, tau=tau, minorder=minorder)",
"for exp in range(minorder, order + 1):\n if exp == 0:\n fn = Constant(tmin=self.tmin, tmax=self.t... | <|body_start_0|>
if order is None:
raise ValueError('Polynomial order cannot be None')
CenteredBasisFn.__init__(self, **kwargs)
TimefnCollection.__init__(self)
self.build(order=order, tau=tau, minorder=minorder)
<|end_body_0|>
<|body_start_1|>
for exp in range(minord... | Collection of power objects to represent a polynomial. | Polynomial | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Polynomial:
"""Collection of power objects to represent a polynomial."""
def __init__(self, order=None, tau=1, minorder=0, **kwargs):
"""Constructor of a polynomial of specified order."""
<|body_0|>
def build(self, order=None, tau=1, minorder=0):
"""Build the pow... | stack_v2_sparse_classes_10k_train_004965 | 1,827 | permissive | [
{
"docstring": "Constructor of a polynomial of specified order.",
"name": "__init__",
"signature": "def __init__(self, order=None, tau=1, minorder=0, **kwargs)"
},
{
"docstring": "Build the power objects and add it to collection.",
"name": "build",
"signature": "def build(self, order=Non... | 2 | stack_v2_sparse_classes_30k_train_004392 | Implement the Python class `Polynomial` described below.
Class description:
Collection of power objects to represent a polynomial.
Method signatures and docstrings:
- def __init__(self, order=None, tau=1, minorder=0, **kwargs): Constructor of a polynomial of specified order.
- def build(self, order=None, tau=1, minor... | Implement the Python class `Polynomial` described below.
Class description:
Collection of power objects to represent a polynomial.
Method signatures and docstrings:
- def __init__(self, order=None, tau=1, minorder=0, **kwargs): Constructor of a polynomial of specified order.
- def build(self, order=None, tau=1, minor... | d53d6bc102dc4eb1b8d153fad80e10bd12f98029 | <|skeleton|>
class Polynomial:
"""Collection of power objects to represent a polynomial."""
def __init__(self, order=None, tau=1, minorder=0, **kwargs):
"""Constructor of a polynomial of specified order."""
<|body_0|>
def build(self, order=None, tau=1, minorder=0):
"""Build the pow... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Polynomial:
"""Collection of power objects to represent a polynomial."""
def __init__(self, order=None, tau=1, minorder=0, **kwargs):
"""Constructor of a polynomial of specified order."""
if order is None:
raise ValueError('Polynomial order cannot be None')
CenteredBas... | the_stack_v2_python_sparse | src/timefn/Polynomial.py | isce-framework/fringe | train | 74 |
1b8b79444ecbd7eab4216982a7028412f22af6c5 | [
"value = encode_value(value, flags)\nresponse = await self._write(key, value, flags=flags)\nreturn response.body is True",
"value = encode_value(value, flags)\nindex = extract_attr(index, keys=['ModifyIndex', 'Index'])\nresponse = await self._write(key, value, flags=flags, cas=index)\nreturn response.body is True... | <|body_start_0|>
value = encode_value(value, flags)
response = await self._write(key, value, flags=flags)
return response.body is True
<|end_body_0|>
<|body_start_1|>
value = encode_value(value, flags)
index = extract_attr(index, keys=['ModifyIndex', 'Index'])
response =... | WriteMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WriteMixin:
async def set(self, key, value, *, flags=None):
"""Sets the key to the given value. Parameters: key (str): Key to set value (Payload): Value to set, It will be encoded by flags flags (int): Flags to set with value Returns: bool: ``True`` on success"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_004966 | 19,443 | permissive | [
{
"docstring": "Sets the key to the given value. Parameters: key (str): Key to set value (Payload): Value to set, It will be encoded by flags flags (int): Flags to set with value Returns: bool: ``True`` on success",
"name": "set",
"signature": "async def set(self, key, value, *, flags=None)"
},
{
... | 5 | stack_v2_sparse_classes_30k_val_000063 | Implement the Python class `WriteMixin` described below.
Class description:
Implement the WriteMixin class.
Method signatures and docstrings:
- async def set(self, key, value, *, flags=None): Sets the key to the given value. Parameters: key (str): Key to set value (Payload): Value to set, It will be encoded by flags ... | Implement the Python class `WriteMixin` described below.
Class description:
Implement the WriteMixin class.
Method signatures and docstrings:
- async def set(self, key, value, *, flags=None): Sets the key to the given value. Parameters: key (str): Key to set value (Payload): Value to set, It will be encoded by flags ... | 02f7a529d7dc2e49bed942111067aa5faf320e90 | <|skeleton|>
class WriteMixin:
async def set(self, key, value, *, flags=None):
"""Sets the key to the given value. Parameters: key (str): Key to set value (Payload): Value to set, It will be encoded by flags flags (int): Flags to set with value Returns: bool: ``True`` on success"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WriteMixin:
async def set(self, key, value, *, flags=None):
"""Sets the key to the given value. Parameters: key (str): Key to set value (Payload): Value to set, It will be encoded by flags flags (int): Flags to set with value Returns: bool: ``True`` on success"""
value = encode_value(value, fl... | the_stack_v2_python_sparse | aioconsul/client/kv_endpoint.py | johnnoone/aioconsul | train | 8 | |
dad70f49e5a69177b94cefb3d0cfc6e04acf2f16 | [
"try:\n jd = jc.load_obj_json('{}')\n jd.config = 'Y'\n jd.nn_id = nnid\n netconf.update_network(jd)\n netconf.save_conf(nnid, request.body)\n netconf.set_on_net_conf(nnid)\n return_data = {'status': '200', 'result': nnid}\n return Response(json.dumps(return_data))\nexcept Exception as e:\n ... | <|body_start_0|>
try:
jd = jc.load_obj_json('{}')
jd.config = 'Y'
jd.nn_id = nnid
netconf.update_network(jd)
netconf.save_conf(nnid, request.body)
netconf.set_on_net_conf(nnid)
return_data = {'status': '200', 'result': nnid}
... | 1. Name : ConvNeuralNetConfig 2. Steps - CNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/nninfo/{nnid}/ - post /api/v1/type/imagedata/base/{baseid}/ - post /api/v1/type/imagedata/base/{baseid}/table/{tb}/ - post /api/v1/type/imagedata/base/{baseid}/table/{tb}/label/{label}/data/ - post /a... | ConvNeuralNetConfig | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvNeuralNetConfig:
"""1. Name : ConvNeuralNetConfig 2. Steps - CNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/nninfo/{nnid}/ - post /api/v1/type/imagedata/base/{baseid}/ - post /api/v1/type/imagedata/base/{baseid}/table/{tb}/ - post /api/v1/type/imagedata/base/{b... | stack_v2_sparse_classes_10k_train_004967 | 3,143 | no_license | [
{
"docstring": "- desc : insert cnn configuration data",
"name": "post",
"signature": "def post(self, request, nnid)"
},
{
"docstring": "- desc : get cnn configuration data",
"name": "get",
"signature": "def get(self, request, nnid)"
},
{
"docstring": "- desc ; update cnn configu... | 4 | stack_v2_sparse_classes_30k_train_004685 | Implement the Python class `ConvNeuralNetConfig` described below.
Class description:
1. Name : ConvNeuralNetConfig 2. Steps - CNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/nninfo/{nnid}/ - post /api/v1/type/imagedata/base/{baseid}/ - post /api/v1/type/imagedata/base/{baseid}/table/{tb}... | Implement the Python class `ConvNeuralNetConfig` described below.
Class description:
1. Name : ConvNeuralNetConfig 2. Steps - CNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/nninfo/{nnid}/ - post /api/v1/type/imagedata/base/{baseid}/ - post /api/v1/type/imagedata/base/{baseid}/table/{tb}... | ef058737f391de817c74398ef9a5d3a28f973c98 | <|skeleton|>
class ConvNeuralNetConfig:
"""1. Name : ConvNeuralNetConfig 2. Steps - CNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/nninfo/{nnid}/ - post /api/v1/type/imagedata/base/{baseid}/ - post /api/v1/type/imagedata/base/{baseid}/table/{tb}/ - post /api/v1/type/imagedata/base/{b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ConvNeuralNetConfig:
"""1. Name : ConvNeuralNetConfig 2. Steps - CNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/nninfo/{nnid}/ - post /api/v1/type/imagedata/base/{baseid}/ - post /api/v1/type/imagedata/base/{baseid}/table/{tb}/ - post /api/v1/type/imagedata/base/{baseid}/table/... | the_stack_v2_python_sparse | tfmsarest/views/cnn_config.py | TensorMSA/tensormsa_old | train | 6 |
c5afd837def6a6ec93ab77a5746a49b3d3ffd86d | [
"assert padding in ['SAME'], 'Error: unsupported padding for transposed conv'\nif isinstance(stride, int):\n stride = [1, stride, stride, 1]\nelse:\n assert len(stride) == 2, 'stride is either an int or a 2-tuple'\n stride = [1, stride[0], stride[1], 1]\nif isinstance(w, int):\n w = [w, w]\nself.padding... | <|body_start_0|>
assert padding in ['SAME'], 'Error: unsupported padding for transposed conv'
if isinstance(stride, int):
stride = [1, stride, stride, 1]
else:
assert len(stride) == 2, 'stride is either an int or a 2-tuple'
stride = [1, stride[0], stride[1], 1... | Convolution layer with support for equalized learning. | LayerTransposedConv | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerTransposedConv:
"""Convolution layer with support for equalized learning."""
def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0):
"""Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel... | stack_v2_sparse_classes_10k_train_004968 | 13,442 | permissive | [
{
"docstring": "Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. w: int or 2-tuple, width of the convolution kernel. n: 2-tuple int, [n_in_channels, n_out_channels] padding: string, the padding method {SAME, VALID, REFLECT}. use_scaling: bool, whether... | 2 | stack_v2_sparse_classes_30k_test_000090 | Implement the Python class `LayerTransposedConv` described below.
Class description:
Convolution layer with support for equalized learning.
Method signatures and docstrings:
- def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0): Layer constructor. Args: name: string, layer name. ... | Implement the Python class `LayerTransposedConv` described below.
Class description:
Convolution layer with support for equalized learning.
Method signatures and docstrings:
- def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0): Layer constructor. Args: name: string, layer name. ... | 091d6ae9e087cf5a6e18b00bce7d8f7ede9d9d08 | <|skeleton|>
class LayerTransposedConv:
"""Convolution layer with support for equalized learning."""
def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0):
"""Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LayerTransposedConv:
"""Convolution layer with support for equalized learning."""
def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0):
"""Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. w: int or 2... | the_stack_v2_python_sparse | layers.py | MoustafaMeshry/StEP | train | 6 |
4880c4ec6aedda01753fb907e133501d10badef7 | [
"if (d, f, target) in self.memo:\n return self.memo[d, f, target]\nmod = 10 ** 9 + 7\nif target < d or target > d * f:\n return 0\nif d == 0:\n return 1 if target == 0 else 0\nself.memo[d, f, target] = sum((self.numRollsToTarget(d - 1, f, target - x) for x in range(1, f + 1))) % mod\nreturn self.memo[d, f,... | <|body_start_0|>
if (d, f, target) in self.memo:
return self.memo[d, f, target]
mod = 10 ** 9 + 7
if target < d or target > d * f:
return 0
if d == 0:
return 1 if target == 0 else 0
self.memo[d, f, target] = sum((self.numRollsToTarget(d - 1, f,... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numRollsToTarget(self, d, f, target):
""":type d: int :type f: int :type target: int :rtype: int"""
<|body_0|>
def numRollsToTarget_1(self, d, f, target):
""":type d: int :type f: int :type target: int :rtype: int"""
<|body_1|>
def numRolls... | stack_v2_sparse_classes_10k_train_004969 | 4,009 | no_license | [
{
"docstring": ":type d: int :type f: int :type target: int :rtype: int",
"name": "numRollsToTarget",
"signature": "def numRollsToTarget(self, d, f, target)"
},
{
"docstring": ":type d: int :type f: int :type target: int :rtype: int",
"name": "numRollsToTarget_1",
"signature": "def numRo... | 3 | stack_v2_sparse_classes_30k_train_002563 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numRollsToTarget(self, d, f, target): :type d: int :type f: int :type target: int :rtype: int
- def numRollsToTarget_1(self, d, f, target): :type d: int :type f: int :type ta... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numRollsToTarget(self, d, f, target): :type d: int :type f: int :type target: int :rtype: int
- def numRollsToTarget_1(self, d, f, target): :type d: int :type f: int :type ta... | 3d9e0ad2f6ed92ec969556f75d97c51ea4854719 | <|skeleton|>
class Solution:
def numRollsToTarget(self, d, f, target):
""":type d: int :type f: int :type target: int :rtype: int"""
<|body_0|>
def numRollsToTarget_1(self, d, f, target):
""":type d: int :type f: int :type target: int :rtype: int"""
<|body_1|>
def numRolls... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def numRollsToTarget(self, d, f, target):
""":type d: int :type f: int :type target: int :rtype: int"""
if (d, f, target) in self.memo:
return self.memo[d, f, target]
mod = 10 ** 9 + 7
if target < d or target > d * f:
return 0
if d == 0... | the_stack_v2_python_sparse | Solutions/1155_numRollsToTarget.py | YoupengLi/leetcode-sorting | train | 3 | |
a52af499ea9b595160cdbfeee615c6064df45520 | [
"assert isinstance(cookie_jar, CookieJar)\ncookie_jar.__class__ = cls\nassert isinstance(cookie_jar, PickleableCookieJar)\nreturn cookie_jar",
"state = self.__dict__.copy()\nstate.pop('_cookies_lock')\nreturn state",
"self.__dict__.update(state)\nif '_cookies_lock' not in self.__dict__:\n self._cookies_lock ... | <|body_start_0|>
assert isinstance(cookie_jar, CookieJar)
cookie_jar.__class__ = cls
assert isinstance(cookie_jar, PickleableCookieJar)
return cookie_jar
<|end_body_0|>
<|body_start_1|>
state = self.__dict__.copy()
state.pop('_cookies_lock')
return state
<|end_bo... | A pickleable CookieJar class | PickleableCookieJar | [
"LicenseRef-scancode-warranty-disclaimer",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PickleableCookieJar:
"""A pickleable CookieJar class"""
def cast(cls, cookie_jar: CookieJar):
"""Make a kind of cast to convert the class from CookieJar to PickleableCookieJar"""
<|body_0|>
def __getstate__(self):
"""Unlike a normal CookieJar, this class is pickl... | stack_v2_sparse_classes_10k_train_004970 | 4,220 | permissive | [
{
"docstring": "Make a kind of cast to convert the class from CookieJar to PickleableCookieJar",
"name": "cast",
"signature": "def cast(cls, cookie_jar: CookieJar)"
},
{
"docstring": "Unlike a normal CookieJar, this class is pickleable.",
"name": "__getstate__",
"signature": "def __getst... | 3 | null | Implement the Python class `PickleableCookieJar` described below.
Class description:
A pickleable CookieJar class
Method signatures and docstrings:
- def cast(cls, cookie_jar: CookieJar): Make a kind of cast to convert the class from CookieJar to PickleableCookieJar
- def __getstate__(self): Unlike a normal CookieJar... | Implement the Python class `PickleableCookieJar` described below.
Class description:
A pickleable CookieJar class
Method signatures and docstrings:
- def cast(cls, cookie_jar: CookieJar): Make a kind of cast to convert the class from CookieJar to PickleableCookieJar
- def __getstate__(self): Unlike a normal CookieJar... | ece10d24449faaccd7d65a4093c6b5679ee0b383 | <|skeleton|>
class PickleableCookieJar:
"""A pickleable CookieJar class"""
def cast(cls, cookie_jar: CookieJar):
"""Make a kind of cast to convert the class from CookieJar to PickleableCookieJar"""
<|body_0|>
def __getstate__(self):
"""Unlike a normal CookieJar, this class is pickl... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PickleableCookieJar:
"""A pickleable CookieJar class"""
def cast(cls, cookie_jar: CookieJar):
"""Make a kind of cast to convert the class from CookieJar to PickleableCookieJar"""
assert isinstance(cookie_jar, CookieJar)
cookie_jar.__class__ = cls
assert isinstance(cookie_j... | the_stack_v2_python_sparse | resources/lib/utils/cookies.py | CastagnaIT/plugin.video.netflix | train | 2,019 |
00208201d290bf3ba95bb8f0797e723620c166e0 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AttackSimulationSimulationUserCoverage()",
"from .attack_simulation_user import AttackSimulationUser\nfrom .attack_simulation_user import AttackSimulationUser\nfields: Dict[str, Callable[[Any], None]] = {'attackSimulationUser': lambda ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AttackSimulationSimulationUserCoverage()
<|end_body_0|>
<|body_start_1|>
from .attack_simulation_user import AttackSimulationUser
from .attack_simulation_user import AttackSimulationUser... | AttackSimulationSimulationUserCoverage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttackSimulationSimulationUserCoverage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttackSimulationSimulationUserCoverage:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the... | stack_v2_sparse_classes_10k_train_004971 | 4,198 | 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: AttackSimulationSimulationUserCoverage",
"name": "create_from_discriminator_value",
"signature": "def create... | 3 | stack_v2_sparse_classes_30k_train_006465 | Implement the Python class `AttackSimulationSimulationUserCoverage` described below.
Class description:
Implement the AttackSimulationSimulationUserCoverage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttackSimulationSimulationUserCoverage: C... | Implement the Python class `AttackSimulationSimulationUserCoverage` described below.
Class description:
Implement the AttackSimulationSimulationUserCoverage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttackSimulationSimulationUserCoverage: C... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AttackSimulationSimulationUserCoverage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttackSimulationSimulationUserCoverage:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AttackSimulationSimulationUserCoverage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttackSimulationSimulationUserCoverage:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator... | the_stack_v2_python_sparse | msgraph/generated/models/attack_simulation_simulation_user_coverage.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
d40d60aa8544335a6ff99a90a85800a8a2f3e24d | [
"self.create_and_verify_stack('single/basic_api')\nfirst_dep_ids = self.get_stack_deployment_ids()\nself.assertEqual(len(first_dep_ids), 1)\nself.set_template_resource_property('MyApi', 'DefinitionUri', self.get_s3_uri('swagger2.json'))\nself.update_stack()\nsecond_dep_ids = self.get_stack_deployment_ids()\nself.as... | <|body_start_0|>
self.create_and_verify_stack('single/basic_api')
first_dep_ids = self.get_stack_deployment_ids()
self.assertEqual(len(first_dep_ids), 1)
self.set_template_resource_property('MyApi', 'DefinitionUri', self.get_s3_uri('swagger2.json'))
self.update_stack()
se... | Basic AWS::Serverless::Api tests | TestBasicApi | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestBasicApi:
"""Basic AWS::Serverless::Api tests"""
def test_basic_api(self):
"""Creates an API and updates its DefinitionUri"""
<|body_0|>
def test_basic_api_with_mode(self):
"""Creates an API and updates its DefinitionUri"""
<|body_1|>
def test_ba... | stack_v2_sparse_classes_10k_train_004972 | 5,166 | permissive | [
{
"docstring": "Creates an API and updates its DefinitionUri",
"name": "test_basic_api",
"signature": "def test_basic_api(self)"
},
{
"docstring": "Creates an API and updates its DefinitionUri",
"name": "test_basic_api_with_mode",
"signature": "def test_basic_api_with_mode(self)"
},
... | 6 | stack_v2_sparse_classes_30k_train_003316 | Implement the Python class `TestBasicApi` described below.
Class description:
Basic AWS::Serverless::Api tests
Method signatures and docstrings:
- def test_basic_api(self): Creates an API and updates its DefinitionUri
- def test_basic_api_with_mode(self): Creates an API and updates its DefinitionUri
- def test_basic_... | Implement the Python class `TestBasicApi` described below.
Class description:
Basic AWS::Serverless::Api tests
Method signatures and docstrings:
- def test_basic_api(self): Creates an API and updates its DefinitionUri
- def test_basic_api_with_mode(self): Creates an API and updates its DefinitionUri
- def test_basic_... | 0bb862ea715a4aafbb7984b407a81856b3ae19c4 | <|skeleton|>
class TestBasicApi:
"""Basic AWS::Serverless::Api tests"""
def test_basic_api(self):
"""Creates an API and updates its DefinitionUri"""
<|body_0|>
def test_basic_api_with_mode(self):
"""Creates an API and updates its DefinitionUri"""
<|body_1|>
def test_ba... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestBasicApi:
"""Basic AWS::Serverless::Api tests"""
def test_basic_api(self):
"""Creates an API and updates its DefinitionUri"""
self.create_and_verify_stack('single/basic_api')
first_dep_ids = self.get_stack_deployment_ids()
self.assertEqual(len(first_dep_ids), 1)
... | the_stack_v2_python_sparse | integration/single/test_basic_api.py | aws/serverless-application-model | train | 2,055 |
07e8cf1822f5f800afec874dc06db03440594b73 | [
"if len(nums) == 0:\n return None\nif len(nums) == 1:\n return nums[0]\nfor i in range(1, len(nums), 1):\n nums[i] = nums[i] + nums[i - 1]\nstart = 1\nmaxVal = nums[0]\nwhile start < len(nums):\n end = start\n s = nums[end]\n if s > maxVal:\n maxVal = s\n while end < len(nums):\n ... | <|body_start_0|>
if len(nums) == 0:
return None
if len(nums) == 1:
return nums[0]
for i in range(1, len(nums), 1):
nums[i] = nums[i] + nums[i - 1]
start = 1
maxVal = nums[0]
while start < len(nums):
end = start
s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(nums) == 0:
return None
... | stack_v2_sparse_classes_10k_train_004973 | 1,044 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray2",
"signature": "def maxSubArray2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxSubArra... | e836343be5185f8843bb77197fccff250e9a77e3 | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
if len(nums) == 0:
return None
if len(nums) == 1:
return nums[0]
for i in range(1, len(nums), 1):
nums[i] = nums[i] + nums[i - 1]
start = 1
maxVal ... | the_stack_v2_python_sparse | leetcode/max_subarray.py | rishabhranawat/challenge | train | 0 | |
037d5658e5e85f09b18e9b0cab84902de5aed6fe | [
"assert check_argument_types()\nsuper().__init__()\nassert use_masking != use_weighted_masking or not use_masking\nself.use_masking = use_masking\nself.use_weighted_masking = use_weighted_masking\nreduction = 'none' if self.use_weighted_masking else 'mean'\nself.mse_criterion = nn.MSELoss(reduction=reduction)\nself... | <|body_start_0|>
assert check_argument_types()
super().__init__()
assert use_masking != use_weighted_masking or not use_masking
self.use_masking = use_masking
self.use_weighted_masking = use_weighted_masking
reduction = 'none' if self.use_weighted_masking else 'mean'
... | VarianceLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VarianceLoss:
def __init__(self, use_masking: bool=True, use_weighted_masking: bool=False):
"""Initialize JETS variance loss module. Args: use_masking (bool): Whether to apply masking for padded part in loss calculation. use_weighted_masking (bool): Whether to weighted masking in loss ca... | stack_v2_sparse_classes_10k_train_004974 | 46,210 | permissive | [
{
"docstring": "Initialize JETS variance loss module. Args: use_masking (bool): Whether to apply masking for padded part in loss calculation. use_weighted_masking (bool): Whether to weighted masking in loss calculation.",
"name": "__init__",
"signature": "def __init__(self, use_masking: bool=True, use_w... | 2 | stack_v2_sparse_classes_30k_train_002021 | Implement the Python class `VarianceLoss` described below.
Class description:
Implement the VarianceLoss class.
Method signatures and docstrings:
- def __init__(self, use_masking: bool=True, use_weighted_masking: bool=False): Initialize JETS variance loss module. Args: use_masking (bool): Whether to apply masking for... | Implement the Python class `VarianceLoss` described below.
Class description:
Implement the VarianceLoss class.
Method signatures and docstrings:
- def __init__(self, use_masking: bool=True, use_weighted_masking: bool=False): Initialize JETS variance loss module. Args: use_masking (bool): Whether to apply masking for... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class VarianceLoss:
def __init__(self, use_masking: bool=True, use_weighted_masking: bool=False):
"""Initialize JETS variance loss module. Args: use_masking (bool): Whether to apply masking for padded part in loss calculation. use_weighted_masking (bool): Whether to weighted masking in loss ca... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VarianceLoss:
def __init__(self, use_masking: bool=True, use_weighted_masking: bool=False):
"""Initialize JETS variance loss module. Args: use_masking (bool): Whether to apply masking for padded part in loss calculation. use_weighted_masking (bool): Whether to weighted masking in loss calculation."""
... | the_stack_v2_python_sparse | paddlespeech/t2s/modules/losses.py | anniyanvr/DeepSpeech-1 | train | 0 | |
1b35840c85755524de2b13c94d529569683f53cf | [
"tree_node_list = []\nfor i in range(len(tree_data)):\n if tree_data[i] != 'null':\n tree_node_list.append(TreeNode(tree_data[i]))\n else:\n tree_node_list.append(None)\nfor i in range(len(tree_data)):\n if tree_node_list[i]:\n if 2 * i + 2 < len(tree_data):\n tree_node_list... | <|body_start_0|>
tree_node_list = []
for i in range(len(tree_data)):
if tree_data[i] != 'null':
tree_node_list.append(TreeNode(tree_data[i]))
else:
tree_node_list.append(None)
for i in range(len(tree_data)):
if tree_node_list[i]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def buildTree(self, tree_data):
""":type tree_data: list :rtype: TreeNode"""
<|body_0|>
def maxDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
tree_node_list = []
for i in rang... | stack_v2_sparse_classes_10k_train_004975 | 1,354 | no_license | [
{
"docstring": ":type tree_data: list :rtype: TreeNode",
"name": "buildTree",
"signature": "def buildTree(self, tree_data)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "maxDepth",
"signature": "def maxDepth(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007304 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, tree_data): :type tree_data: list :rtype: TreeNode
- def maxDepth(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, tree_data): :type tree_data: list :rtype: TreeNode
- def maxDepth(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
def buildTr... | 37ece0a8e92a41ced2b4ce0f2d8dda3826b915ae | <|skeleton|>
class Solution:
def buildTree(self, tree_data):
""":type tree_data: list :rtype: TreeNode"""
<|body_0|>
def maxDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def buildTree(self, tree_data):
""":type tree_data: list :rtype: TreeNode"""
tree_node_list = []
for i in range(len(tree_data)):
if tree_data[i] != 'null':
tree_node_list.append(TreeNode(tree_data[i]))
else:
tree_node_li... | the_stack_v2_python_sparse | Q104MaximumDepthofBinaryTree.py | ShenTonyM/LeetCode-Learn | train | 0 | |
d305f1870b6c70dd447b39d202d420daeeb492dd | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn MainError()",
"from .error_details import ErrorDetails\nfrom .inner_error import InnerError\nfrom .error_details import ErrorDetails\nfrom .inner_error import InnerError\nfields: Dict[str, Callable[[Any], None]] = {'code': lambda n: se... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return MainError()
<|end_body_0|>
<|body_start_1|>
from .error_details import ErrorDetails
from .inner_error import InnerError
from .error_details import ErrorDetails
from .inne... | MainError | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainError:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MainError:
"""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: MainEr... | stack_v2_sparse_classes_10k_train_004976 | 3,350 | 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: MainError",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(par... | 3 | null | Implement the Python class `MainError` described below.
Class description:
Implement the MainError class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MainError: Creates a new instance of the appropriate class based on discriminator value Args: parse... | Implement the Python class `MainError` described below.
Class description:
Implement the MainError class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MainError: Creates a new instance of the appropriate class based on discriminator value Args: parse... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class MainError:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MainError:
"""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: MainEr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MainError:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MainError:
"""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: MainError"""
... | the_stack_v2_python_sparse | msgraph/generated/models/o_data_errors/main_error.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
85f47f0d3e6a9c0418d427d00de354e8fc2f4223 | [
"self.plugin = OrographicEnhancement()\nself.plugin.grid_spacing_km = 3.0\nself.point_orogenh = np.array([[4.1, 4.6, 5.6, 6.8, 5.5], [4.4, 4.6, 5.8, 6.2, 5.5], [5.2, 3.0, 3.4, 5.1, 3.3], [0.6, 2.0, 1.8, 4.2, 2.5], [0.0, 0.0, 0.2, 3.2, 1.8]])\nself.wind_speed = np.full((5, 5), 25.0, dtype=np.float32)\nsin_wind_dir =... | <|body_start_0|>
self.plugin = OrographicEnhancement()
self.plugin.grid_spacing_km = 3.0
self.point_orogenh = np.array([[4.1, 4.6, 5.6, 6.8, 5.5], [4.4, 4.6, 5.8, 6.2, 5.5], [5.2, 3.0, 3.4, 5.1, 3.3], [0.6, 2.0, 1.8, 4.2, 2.5], [0.0, 0.0, 0.2, 3.2, 1.8]])
self.wind_speed = np.full((5, 5)... | Test the _compute_weighted_values method | Test__compute_weighted_values | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test__compute_weighted_values:
"""Test the _compute_weighted_values method"""
def setUp(self):
"""Set up plugin and some inputs"""
<|body_0|>
def test_basic(self):
"""Test output is two arrays"""
<|body_1|>
def test_values(self):
"""Test valu... | stack_v2_sparse_classes_10k_train_004977 | 34,979 | permissive | [
{
"docstring": "Set up plugin and some inputs",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test output is two arrays",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "Test values are as expected",
"name": "test_values",
... | 3 | null | Implement the Python class `Test__compute_weighted_values` described below.
Class description:
Test the _compute_weighted_values method
Method signatures and docstrings:
- def setUp(self): Set up plugin and some inputs
- def test_basic(self): Test output is two arrays
- def test_values(self): Test values are as expec... | Implement the Python class `Test__compute_weighted_values` described below.
Class description:
Test the _compute_weighted_values method
Method signatures and docstrings:
- def setUp(self): Set up plugin and some inputs
- def test_basic(self): Test output is two arrays
- def test_values(self): Test values are as expec... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test__compute_weighted_values:
"""Test the _compute_weighted_values method"""
def setUp(self):
"""Set up plugin and some inputs"""
<|body_0|>
def test_basic(self):
"""Test output is two arrays"""
<|body_1|>
def test_values(self):
"""Test valu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test__compute_weighted_values:
"""Test the _compute_weighted_values method"""
def setUp(self):
"""Set up plugin and some inputs"""
self.plugin = OrographicEnhancement()
self.plugin.grid_spacing_km = 3.0
self.point_orogenh = np.array([[4.1, 4.6, 5.6, 6.8, 5.5], [4.4, 4.6, 5... | the_stack_v2_python_sparse | improver_tests/orographic_enhancement/test_OrographicEnhancement.py | metoppv/improver | train | 101 |
b652cd16ecd3e43b2865ffbc2505e7d68a8ca4ae | [
"self.total_count = total_count\nself.step = step\nself.cursor = 0",
"self.cursor += 1\nif self.cursor > 1 and eq(self.cursor % self.step, 0):\n print('%.1f%%' % (100.0 * self.cursor / self.total_count))"
] | <|body_start_0|>
self.total_count = total_count
self.step = step
self.cursor = 0
<|end_body_0|>
<|body_start_1|>
self.cursor += 1
if self.cursor > 1 and eq(self.cursor % self.step, 0):
print('%.1f%%' % (100.0 * self.cursor / self.total_count))
<|end_body_1|>
| ProcessPrint | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessPrint:
def __init__(self, total_count, step=50):
""":param total_count: 总量 :param step: 步长 :return:"""
<|body_0|>
def forward(self):
"""前进 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.total_count = total_count
self.st... | stack_v2_sparse_classes_10k_train_004978 | 3,299 | permissive | [
{
"docstring": ":param total_count: 总量 :param step: 步长 :return:",
"name": "__init__",
"signature": "def __init__(self, total_count, step=50)"
},
{
"docstring": "前进 :return:",
"name": "forward",
"signature": "def forward(self)"
}
] | 2 | null | Implement the Python class `ProcessPrint` described below.
Class description:
Implement the ProcessPrint class.
Method signatures and docstrings:
- def __init__(self, total_count, step=50): :param total_count: 总量 :param step: 步长 :return:
- def forward(self): 前进 :return: | Implement the Python class `ProcessPrint` described below.
Class description:
Implement the ProcessPrint class.
Method signatures and docstrings:
- def __init__(self, total_count, step=50): :param total_count: 总量 :param step: 步长 :return:
- def forward(self): 前进 :return:
<|skeleton|>
class ProcessPrint:
def __in... | a7c9567975b5372b2edabddb0fec8d73bc01c3dc | <|skeleton|>
class ProcessPrint:
def __init__(self, total_count, step=50):
""":param total_count: 总量 :param step: 步长 :return:"""
<|body_0|>
def forward(self):
"""前进 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProcessPrint:
def __init__(self, total_count, step=50):
""":param total_count: 总量 :param step: 步长 :return:"""
self.total_count = total_count
self.step = step
self.cursor = 0
def forward(self):
"""前进 :return:"""
self.cursor += 1
if self.cursor > 1 an... | the_stack_v2_python_sparse | Dispatcher/tools_lib/common_util/archived/utils.py | cash2one/Logistics | train | 0 | |
150526e2268e028666be9eed2338ff75ac2e6966 | [
"expected_obj = self.resize_prep_end_obj\nactual_json = json.dumps(self.instance_resize_prep_end_dict)\nactual_obj = InstanceResizePrepEnd.deserialize(actual_json, 'json')\nself.assertEqual(expected_obj, actual_obj)\nself.assertFalse(actual_obj.is_empty())",
"modified_dict = self.instance_resize_prep_end_dict.cop... | <|body_start_0|>
expected_obj = self.resize_prep_end_obj
actual_json = json.dumps(self.instance_resize_prep_end_dict)
actual_obj = InstanceResizePrepEnd.deserialize(actual_json, 'json')
self.assertEqual(expected_obj, actual_obj)
self.assertFalse(actual_obj.is_empty())
<|end_body_... | InstanceResizePrepEndTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceResizePrepEndTest:
def test_instance_resize_prep_end_valid_json(self):
"""Verify that the valid event deserialized correctly"""
<|body_0|>
def test_instance_resize_prep_end_missing_attribute_json(self):
"""Verify event missing expected attribute does not dese... | stack_v2_sparse_classes_10k_train_004979 | 5,720 | permissive | [
{
"docstring": "Verify that the valid event deserialized correctly",
"name": "test_instance_resize_prep_end_valid_json",
"signature": "def test_instance_resize_prep_end_valid_json(self)"
},
{
"docstring": "Verify event missing expected attribute does not deserialize",
"name": "test_instance_... | 3 | null | Implement the Python class `InstanceResizePrepEndTest` described below.
Class description:
Implement the InstanceResizePrepEndTest class.
Method signatures and docstrings:
- def test_instance_resize_prep_end_valid_json(self): Verify that the valid event deserialized correctly
- def test_instance_resize_prep_end_missi... | Implement the Python class `InstanceResizePrepEndTest` described below.
Class description:
Implement the InstanceResizePrepEndTest class.
Method signatures and docstrings:
- def test_instance_resize_prep_end_valid_json(self): Verify that the valid event deserialized correctly
- def test_instance_resize_prep_end_missi... | 7d49cf6bfd7e1a6e5b739e7de52f2e18e5ccf924 | <|skeleton|>
class InstanceResizePrepEndTest:
def test_instance_resize_prep_end_valid_json(self):
"""Verify that the valid event deserialized correctly"""
<|body_0|>
def test_instance_resize_prep_end_missing_attribute_json(self):
"""Verify event missing expected attribute does not dese... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InstanceResizePrepEndTest:
def test_instance_resize_prep_end_valid_json(self):
"""Verify that the valid event deserialized correctly"""
expected_obj = self.resize_prep_end_obj
actual_json = json.dumps(self.instance_resize_prep_end_dict)
actual_obj = InstanceResizePrepEnd.deseri... | the_stack_v2_python_sparse | metatests/events/models/compute/test_instance_resize_prep.py | kurhula/cloudcafe | train | 0 | |
31d527a544437cb4deac06a44ce603773282d238 | [
"hrd = pcs.Field('hrd', 16, default=1)\npro = pcs.Field('pro', 16, default=2048)\nhln = pcs.Field('hln', 8, default=6)\npln = pcs.Field('pln', 8, default=4)\nop = pcs.Field('op', 16)\nsha = pcs.StringField('sha', 48)\nspa = pcs.Field('spa', 32)\ntha = pcs.StringField('tha', 48)\ntpa = pcs.Field('tpa', 32)\npcs.Pack... | <|body_start_0|>
hrd = pcs.Field('hrd', 16, default=1)
pro = pcs.Field('pro', 16, default=2048)
hln = pcs.Field('hln', 8, default=6)
pln = pcs.Field('pln', 8, default=4)
op = pcs.Field('op', 16)
sha = pcs.StringField('sha', 48)
spa = pcs.Field('spa', 32)
t... | arp | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class arp:
def __init__(self, bytes=None):
"""initialize an ARP packet"""
<|body_0|>
def __str__(self):
"""return a human readable version of an ARP packet"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
hrd = pcs.Field('hrd', 16, default=1)
pro =... | stack_v2_sparse_classes_10k_train_004980 | 4,350 | no_license | [
{
"docstring": "initialize an ARP packet",
"name": "__init__",
"signature": "def __init__(self, bytes=None)"
},
{
"docstring": "return a human readable version of an ARP packet",
"name": "__str__",
"signature": "def __str__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000541 | Implement the Python class `arp` described below.
Class description:
Implement the arp class.
Method signatures and docstrings:
- def __init__(self, bytes=None): initialize an ARP packet
- def __str__(self): return a human readable version of an ARP packet | Implement the Python class `arp` described below.
Class description:
Implement the arp class.
Method signatures and docstrings:
- def __init__(self, bytes=None): initialize an ARP packet
- def __str__(self): return a human readable version of an ARP packet
<|skeleton|>
class arp:
def __init__(self, bytes=None):... | a070a39586b582fbeea72abf12bbfd812955ad81 | <|skeleton|>
class arp:
def __init__(self, bytes=None):
"""initialize an ARP packet"""
<|body_0|>
def __str__(self):
"""return a human readable version of an ARP packet"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class arp:
def __init__(self, bytes=None):
"""initialize an ARP packet"""
hrd = pcs.Field('hrd', 16, default=1)
pro = pcs.Field('pro', 16, default=2048)
hln = pcs.Field('hln', 8, default=6)
pln = pcs.Field('pln', 8, default=4)
op = pcs.Field('op', 16)
sha = pc... | the_stack_v2_python_sparse | src/pcs/packets/arp.py | bilouro/tcptest | train | 0 | |
ecfbb7619ad69652fba8c29608cadcb7db8389c8 | [
"super().__init__()\nself.resize_input = resize_input\nself.normalize_input = normalize_input\ninception = fid_inception_v3()\nself.features = nn.Sequential(inception.Conv2d_1a_3x3, inception.Conv2d_2a_3x3, inception.Conv2d_2b_3x3, nn.MaxPool2d(kernel_size=3, stride=2), inception.Conv2d_3b_1x1, inception.Conv2d_4a_... | <|body_start_0|>
super().__init__()
self.resize_input = resize_input
self.normalize_input = normalize_input
inception = fid_inception_v3()
self.features = nn.Sequential(inception.Conv2d_1a_3x3, inception.Conv2d_2a_3x3, inception.Conv2d_2b_3x3, nn.MaxPool2d(kernel_size=3, stride=2... | Pretrained InceptionV3 network returning feature maps | FIDInceptionV3 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FIDInceptionV3:
"""Pretrained InceptionV3 network returning feature maps"""
def __init__(self, resize_input=True, normalize_input=True, requires_grad=False):
"""Build pretrained InceptionV3 Parameters ---------- resize_input : bool If true, bilinearly resizes input to width and heigh... | stack_v2_sparse_classes_10k_train_004981 | 10,118 | permissive | [
{
"docstring": "Build pretrained InceptionV3 Parameters ---------- resize_input : bool If true, bilinearly resizes input to width and height 299 before feeding input to model. As the network without fully connected layers is fully convolutional, it should be able to handle inputs of arbitrary size, so resizing ... | 2 | stack_v2_sparse_classes_30k_train_001675 | Implement the Python class `FIDInceptionV3` described below.
Class description:
Pretrained InceptionV3 network returning feature maps
Method signatures and docstrings:
- def __init__(self, resize_input=True, normalize_input=True, requires_grad=False): Build pretrained InceptionV3 Parameters ---------- resize_input : ... | Implement the Python class `FIDInceptionV3` described below.
Class description:
Pretrained InceptionV3 network returning feature maps
Method signatures and docstrings:
- def __init__(self, resize_input=True, normalize_input=True, requires_grad=False): Build pretrained InceptionV3 Parameters ---------- resize_input : ... | f19abcbedd844a700b2e2596dd817ea80cbb6287 | <|skeleton|>
class FIDInceptionV3:
"""Pretrained InceptionV3 network returning feature maps"""
def __init__(self, resize_input=True, normalize_input=True, requires_grad=False):
"""Build pretrained InceptionV3 Parameters ---------- resize_input : bool If true, bilinearly resizes input to width and heigh... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FIDInceptionV3:
"""Pretrained InceptionV3 network returning feature maps"""
def __init__(self, resize_input=True, normalize_input=True, requires_grad=False):
"""Build pretrained InceptionV3 Parameters ---------- resize_input : bool If true, bilinearly resizes input to width and height 299 before ... | the_stack_v2_python_sparse | horch/legacy/gan/inception.py | sbl1996/pytorch-hrvvi-ext | train | 18 |
9f80b8fce268c87e43adbe8d3abc995e502b2d84 | [
"main.clear_collections()\nresult = main.import_data('./data/', 'products', 'customers', 'rentals')\nself.assertEqual(result[1], 1000)\nself.assertEqual(result[2], 0)\nself.assertEqual(result[3], 1000)\nself.assertGreater(result[4], 0)",
"function = main.show_available_products()\nproduct_1 = function['prd0018'][... | <|body_start_0|>
main.clear_collections()
result = main.import_data('./data/', 'products', 'customers', 'rentals')
self.assertEqual(result[1], 1000)
self.assertEqual(result[2], 0)
self.assertEqual(result[3], 1000)
self.assertGreater(result[4], 0)
<|end_body_0|>
<|body_st... | Class for testing HP Norton database | ModuleTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModuleTests:
"""Class for testing HP Norton database"""
def test_import_data(self):
"""Test CSV import and correct database insertion functionality"""
<|body_0|>
def test_show_available_products(self):
"""Test DB to show all available products as a Python diction... | stack_v2_sparse_classes_10k_train_004982 | 2,469 | no_license | [
{
"docstring": "Test CSV import and correct database insertion functionality",
"name": "test_import_data",
"signature": "def test_import_data(self)"
},
{
"docstring": "Test DB to show all available products as a Python dictionary",
"name": "test_show_available_products",
"signature": "de... | 3 | null | Implement the Python class `ModuleTests` described below.
Class description:
Class for testing HP Norton database
Method signatures and docstrings:
- def test_import_data(self): Test CSV import and correct database insertion functionality
- def test_show_available_products(self): Test DB to show all available product... | Implement the Python class `ModuleTests` described below.
Class description:
Class for testing HP Norton database
Method signatures and docstrings:
- def test_import_data(self): Test CSV import and correct database insertion functionality
- def test_show_available_products(self): Test DB to show all available product... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class ModuleTests:
"""Class for testing HP Norton database"""
def test_import_data(self):
"""Test CSV import and correct database insertion functionality"""
<|body_0|>
def test_show_available_products(self):
"""Test DB to show all available products as a Python diction... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ModuleTests:
"""Class for testing HP Norton database"""
def test_import_data(self):
"""Test CSV import and correct database insertion functionality"""
main.clear_collections()
result = main.import_data('./data/', 'products', 'customers', 'rentals')
self.assertEqual(result[... | the_stack_v2_python_sparse | students/stellie/lesson07/assignment/test_parallel.py | JavaRod/SP_Python220B_2019 | train | 1 |
14324f1ab1f78d59bc0d5d53883d0f1b311fcf5a | [
"self.new_object_name = new_object_name\nself.overwrite = overwrite\nself.restore_time_secs = restore_time_secs",
"if dictionary is None:\n return None\nnew_object_name = dictionary.get('newObjectName')\noverwrite = dictionary.get('overwrite')\nrestore_time_secs = dictionary.get('restoreTimeSecs')\nreturn cls(... | <|body_start_0|>
self.new_object_name = new_object_name
self.overwrite = overwrite
self.restore_time_secs = restore_time_secs
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
new_object_name = dictionary.get('newObjectName')
overwrite = dict... | Implementation of the 'UdaRestoreObjectParams' model. TODO: type description here. Attributes: new_object_name (string): The new name of the object, if it is going to be renamed. overwrite (bool): Whether to overwrite or keep the object if the object being recovered already exists in the destination. restore_time_secs ... | UdaRestoreObjectParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UdaRestoreObjectParams:
"""Implementation of the 'UdaRestoreObjectParams' model. TODO: type description here. Attributes: new_object_name (string): The new name of the object, if it is going to be renamed. overwrite (bool): Whether to overwrite or keep the object if the object being recovered alr... | stack_v2_sparse_classes_10k_train_004983 | 2,230 | permissive | [
{
"docstring": "Constructor for the UdaRestoreObjectParams class",
"name": "__init__",
"signature": "def __init__(self, new_object_name=None, overwrite=None, restore_time_secs=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionar... | 2 | stack_v2_sparse_classes_30k_train_001823 | Implement the Python class `UdaRestoreObjectParams` described below.
Class description:
Implementation of the 'UdaRestoreObjectParams' model. TODO: type description here. Attributes: new_object_name (string): The new name of the object, if it is going to be renamed. overwrite (bool): Whether to overwrite or keep the o... | Implement the Python class `UdaRestoreObjectParams` described below.
Class description:
Implementation of the 'UdaRestoreObjectParams' model. TODO: type description here. Attributes: new_object_name (string): The new name of the object, if it is going to be renamed. overwrite (bool): Whether to overwrite or keep the o... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class UdaRestoreObjectParams:
"""Implementation of the 'UdaRestoreObjectParams' model. TODO: type description here. Attributes: new_object_name (string): The new name of the object, if it is going to be renamed. overwrite (bool): Whether to overwrite or keep the object if the object being recovered alr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UdaRestoreObjectParams:
"""Implementation of the 'UdaRestoreObjectParams' model. TODO: type description here. Attributes: new_object_name (string): The new name of the object, if it is going to be renamed. overwrite (bool): Whether to overwrite or keep the object if the object being recovered already exists i... | the_stack_v2_python_sparse | cohesity_management_sdk/models/uda_restore_object_params.py | cohesity/management-sdk-python | train | 24 |
025193f000837a77cf88b95b37d345daddd2cfc4 | [
"S = S.upper()\nl = len(S)\ndicts = {char: [[], 0] for char in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'}\nfor i, char in enumerate(S):\n dicts[char][0].append(i)\nans = 0\nprint(dicts)\nfor i, char in enumerate(S):\n pos = dicts[char][1]\n if pos - 1 >= 0:\n left = dicts[char][0][pos - 1]\n else:\n le... | <|body_start_0|>
S = S.upper()
l = len(S)
dicts = {char: [[], 0] for char in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'}
for i, char in enumerate(S):
dicts[char][0].append(i)
ans = 0
print(dicts)
for i, char in enumerate(S):
pos = dicts[char][1]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniqueLetterString(self, S):
""":type S: str :rtype: int 517 ms"""
<|body_0|>
def uniqueLetterString_1(self, S):
"""136ms :param S: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
S = S.upper()
l = len(S)
dicts... | stack_v2_sparse_classes_10k_train_004984 | 2,560 | no_license | [
{
"docstring": ":type S: str :rtype: int 517 ms",
"name": "uniqueLetterString",
"signature": "def uniqueLetterString(self, S)"
},
{
"docstring": "136ms :param S: :return:",
"name": "uniqueLetterString_1",
"signature": "def uniqueLetterString_1(self, S)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003383 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniqueLetterString(self, S): :type S: str :rtype: int 517 ms
- def uniqueLetterString_1(self, S): 136ms :param S: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniqueLetterString(self, S): :type S: str :rtype: int 517 ms
- def uniqueLetterString_1(self, S): 136ms :param S: :return:
<|skeleton|>
class Solution:
def uniqueLetter... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def uniqueLetterString(self, S):
""":type S: str :rtype: int 517 ms"""
<|body_0|>
def uniqueLetterString_1(self, S):
"""136ms :param S: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def uniqueLetterString(self, S):
""":type S: str :rtype: int 517 ms"""
S = S.upper()
l = len(S)
dicts = {char: [[], 0] for char in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'}
for i, char in enumerate(S):
dicts[char][0].append(i)
ans = 0
print(dic... | the_stack_v2_python_sparse | UniqueLetterString_HARD_828.py | 953250587/leetcode-python | train | 2 | |
0a48e14b6b283b777b9041049549529b10dbbe1d | [
"if not quota_max_calls:\n use_rate_limiter = False\nself._groups = None\nself._members = None\nself._users = None\nsuper(AdminDirectoryRepositoryClient, self).__init__(API_NAME, versions=['directory_v1'], credentials=credentials, quota_max_calls=quota_max_calls, quota_period=quota_period, use_rate_limiter=use_r... | <|body_start_0|>
if not quota_max_calls:
use_rate_limiter = False
self._groups = None
self._members = None
self._users = None
super(AdminDirectoryRepositoryClient, self).__init__(API_NAME, versions=['directory_v1'], credentials=credentials, quota_max_calls=quota_max_c... | Admin Directory API Respository Client. | AdminDirectoryRepositoryClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdminDirectoryRepositoryClient:
"""Admin Directory API Respository Client."""
def __init__(self, credentials, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True):
"""Constructor. Args: credentials (object): An google.auth credentials object. The admin directory API needs a... | stack_v2_sparse_classes_10k_train_004985 | 9,750 | permissive | [
{
"docstring": "Constructor. Args: credentials (object): An google.auth credentials object. The admin directory API needs a service account credential with delegated super admin role. quota_max_calls (int): Allowed requests per <quota_period> for the API. quota_period (float): The time period to track requests ... | 4 | stack_v2_sparse_classes_30k_train_002210 | Implement the Python class `AdminDirectoryRepositoryClient` described below.
Class description:
Admin Directory API Respository Client.
Method signatures and docstrings:
- def __init__(self, credentials, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True): Constructor. Args: credentials (object): An google... | Implement the Python class `AdminDirectoryRepositoryClient` described below.
Class description:
Admin Directory API Respository Client.
Method signatures and docstrings:
- def __init__(self, credentials, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True): Constructor. Args: credentials (object): An google... | d4421afa50a17ed47cbebe942044ebab3720e0f5 | <|skeleton|>
class AdminDirectoryRepositoryClient:
"""Admin Directory API Respository Client."""
def __init__(self, credentials, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True):
"""Constructor. Args: credentials (object): An google.auth credentials object. The admin directory API needs a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AdminDirectoryRepositoryClient:
"""Admin Directory API Respository Client."""
def __init__(self, credentials, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True):
"""Constructor. Args: credentials (object): An google.auth credentials object. The admin directory API needs a service acco... | the_stack_v2_python_sparse | google/cloud/forseti/common/gcp_api/admin_directory.py | kevensen/forseti-security | train | 1 |
9e37b728d8045726aef7625fccc14111ecb0e1c8 | [
"self.size = size\nself.q = collections.deque()\nself.sum_ = 0",
"if len(self.q) == self.size:\n a = self.q.popleft()\n self.sum_ -= a\nself.q.append(val)\nself.sum_ += val\nreturn float(self.sum_) / len(self.q)"
] | <|body_start_0|>
self.size = size
self.q = collections.deque()
self.sum_ = 0
<|end_body_0|>
<|body_start_1|>
if len(self.q) == self.size:
a = self.q.popleft()
self.sum_ -= a
self.q.append(val)
self.sum_ += val
return float(self.sum_) / len... | MovingAverage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.size = size
self.q = col... | stack_v2_sparse_classes_10k_train_004986 | 826 | no_license | [
{
"docstring": "Initialize your data structure here. :type size: int",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": ":type val: int :rtype: float",
"name": "next",
"signature": "def next(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000122 | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float
<|skeleton|>
class MovingAverage:
... | e890bd480de93418ce10867085b52137be2caa7a | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
self.size = size
self.q = collections.deque()
self.sum_ = 0
def next(self, val):
""":type val: int :rtype: float"""
if len(self.q) == self.size:
... | the_stack_v2_python_sparse | python/346.py | LichAmnesia/LeetCode | train | 0 | |
83b027bbe9a384bab501f1ad937396ebf4515b3f | [
"logger.info('Checking Appfollow API connection...')\ntry:\n ext_id = config['ext_id']\n cid = config['cid']\n api_secret = config['api_secret']\n response = requests.get(f'https://api.appfollow.io/ratings?ext_id={ext_id}&cid={cid}', auth=HTTPBasicAuth(api_secret, api_secret))\n if response.status_co... | <|body_start_0|>
logger.info('Checking Appfollow API connection...')
try:
ext_id = config['ext_id']
cid = config['cid']
api_secret = config['api_secret']
response = requests.get(f'https://api.appfollow.io/ratings?ext_id={ext_id}&cid={cid}', auth=HTTPBasicA... | SourceAppfollow | [
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"Elastic-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceAppfollow:
def check_connection(self, logger, config) -> Tuple[bool, any]:
"""A connection check to validate that the user-provided config can be used to connect to the underlying API :param config: the user-input config object conforming to the connector's spec.yaml :param logger:... | stack_v2_sparse_classes_10k_train_004987 | 3,806 | permissive | [
{
"docstring": "A connection check to validate that the user-provided config can be used to connect to the underlying API :param config: the user-input config object conforming to the connector's spec.yaml :param logger: logger object :return Tuple[bool, any]: (True, None) if the input config can be used to con... | 2 | stack_v2_sparse_classes_30k_train_006111 | Implement the Python class `SourceAppfollow` described below.
Class description:
Implement the SourceAppfollow class.
Method signatures and docstrings:
- def check_connection(self, logger, config) -> Tuple[bool, any]: A connection check to validate that the user-provided config can be used to connect to the underlyin... | Implement the Python class `SourceAppfollow` described below.
Class description:
Implement the SourceAppfollow class.
Method signatures and docstrings:
- def check_connection(self, logger, config) -> Tuple[bool, any]: A connection check to validate that the user-provided config can be used to connect to the underlyin... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class SourceAppfollow:
def check_connection(self, logger, config) -> Tuple[bool, any]:
"""A connection check to validate that the user-provided config can be used to connect to the underlying API :param config: the user-input config object conforming to the connector's spec.yaml :param logger:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SourceAppfollow:
def check_connection(self, logger, config) -> Tuple[bool, any]:
"""A connection check to validate that the user-provided config can be used to connect to the underlying API :param config: the user-input config object conforming to the connector's spec.yaml :param logger: logger object... | the_stack_v2_python_sparse | dts/airbyte/airbyte-integrations/connectors/source-appfollow/source_appfollow/source.py | alldatacenter/alldata | train | 774 | |
58f65d75ad373949cf0198f5c14d8a296cf06d03 | [
"super().__init__(coordinator=coordinator, kind=kind, name=name, icon=icon, item_id=item_id, state_key=state_key)\nself._max_speed = int(coordinator.data[item_id].get('Max-Pump-Speed', 100))\nself._min_speed = int(coordinator.data[item_id].get('Min-Pump-Speed', 0))\nif 'Filter-Type' in coordinator.data[item_id]:\n ... | <|body_start_0|>
super().__init__(coordinator=coordinator, kind=kind, name=name, icon=icon, item_id=item_id, state_key=state_key)
self._max_speed = int(coordinator.data[item_id].get('Max-Pump-Speed', 100))
self._min_speed = int(coordinator.data[item_id].get('Min-Pump-Speed', 0))
if 'Filt... | Define the OmniLogic Pump Switch Entity. | OmniLogicPumpControl | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OmniLogicPumpControl:
"""Define the OmniLogic Pump Switch Entity."""
def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None:
"""Initialize entities."""
<|body_0|>
async def async_turn_on(self, ... | stack_v2_sparse_classes_10k_train_004988 | 8,137 | permissive | [
{
"docstring": "Initialize entities.",
"name": "__init__",
"signature": "def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None"
},
{
"docstring": "Turn on the pump.",
"name": "async_turn_on",
"signature": "asy... | 4 | null | Implement the Python class `OmniLogicPumpControl` described below.
Class description:
Define the OmniLogic Pump Switch Entity.
Method signatures and docstrings:
- def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None: Initialize entities.
... | Implement the Python class `OmniLogicPumpControl` described below.
Class description:
Define the OmniLogic Pump Switch Entity.
Method signatures and docstrings:
- def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None: Initialize entities.
... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class OmniLogicPumpControl:
"""Define the OmniLogic Pump Switch Entity."""
def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None:
"""Initialize entities."""
<|body_0|>
async def async_turn_on(self, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OmniLogicPumpControl:
"""Define the OmniLogic Pump Switch Entity."""
def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None:
"""Initialize entities."""
super().__init__(coordinator=coordinator, kind=kind, name=n... | the_stack_v2_python_sparse | homeassistant/components/omnilogic/switch.py | home-assistant/core | train | 35,501 |
e9eadedcbc1992bce435b1d3120e3e81bc3f46f3 | [
"for element in brain.getObject().objectValues():\n info = {'title': element.title or ''}\n if element.portal_type == 'PSCFileLink':\n info['url'] = element.externalURL\n else:\n info['url'] = element.absolute_url()\n yield info",
"sc = self.context\ncatalog = getToolByName(self.context,... | <|body_start_0|>
for element in brain.getObject().objectValues():
info = {'title': element.title or ''}
if element.portal_type == 'PSCFileLink':
info['url'] = element.externalURL
else:
info['url'] = element.absolute_url()
yield info... | view used for the main index page | PyPISimpleView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyPISimpleView:
"""view used for the main index page"""
def get_urls_and_titles(self, brain):
"""returns url and title"""
<|body_0|>
def get_files(self):
"""provides the simple view over the projects with links to the published files"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_10k_train_004989 | 1,303 | no_license | [
{
"docstring": "returns url and title",
"name": "get_urls_and_titles",
"signature": "def get_urls_and_titles(self, brain)"
},
{
"docstring": "provides the simple view over the projects with links to the published files",
"name": "get_files",
"signature": "def get_files(self)"
}
] | 2 | null | Implement the Python class `PyPISimpleView` described below.
Class description:
view used for the main index page
Method signatures and docstrings:
- def get_urls_and_titles(self, brain): returns url and title
- def get_files(self): provides the simple view over the projects with links to the published files | Implement the Python class `PyPISimpleView` described below.
Class description:
view used for the main index page
Method signatures and docstrings:
- def get_urls_and_titles(self, brain): returns url and title
- def get_files(self): provides the simple view over the projects with links to the published files
<|skele... | 8a7bdbdb98c3f9fc1073c6061cd2d3a0ec80caf5 | <|skeleton|>
class PyPISimpleView:
"""view used for the main index page"""
def get_urls_and_titles(self, brain):
"""returns url and title"""
<|body_0|>
def get_files(self):
"""provides the simple view over the projects with links to the published files"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PyPISimpleView:
"""view used for the main index page"""
def get_urls_and_titles(self, brain):
"""returns url and title"""
for element in brain.getObject().objectValues():
info = {'title': element.title or ''}
if element.portal_type == 'PSCFileLink':
... | the_stack_v2_python_sparse | buildout-cache/eggs/Products.PloneSoftwareCenter-1.5-py2.7.egg/Products/PloneSoftwareCenter/browser/pypisimple.py | renansfs/Plone_SP | train | 0 |
4b87ed0ed26a18fa2ef261ce8731e61c4b73eeea | [
"self.system = system\nself.cpu = cpu\nself.memory = memory\nself.gpu = gpu",
"system = platform.platform()\ngpu = GPU.from_host()\nmemory = Memory.from_host()\ncpu = CPU.from_host()\nreturn SystemInfo(system=system, cpu=cpu, gpu=gpu, memory=memory)"
] | <|body_start_0|>
self.system = system
self.cpu = cpu
self.memory = memory
self.gpu = gpu
<|end_body_0|>
<|body_start_1|>
system = platform.platform()
gpu = GPU.from_host()
memory = Memory.from_host()
cpu = CPU.from_host()
return SystemInfo(system=... | System Information data object | SystemInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SystemInfo:
"""System Information data object"""
def __init__(self, system: str, cpu: CPU, memory: Memory, gpu: GPU):
"""Args: system: name of operating system cpu: CPU info memory: Memory info gpu: GPU info"""
<|body_0|>
def from_host():
"""Create SystemInfo obj... | stack_v2_sparse_classes_10k_train_004990 | 9,744 | permissive | [
{
"docstring": "Args: system: name of operating system cpu: CPU info memory: Memory info gpu: GPU info",
"name": "__init__",
"signature": "def __init__(self, system: str, cpu: CPU, memory: Memory, gpu: GPU)"
},
{
"docstring": "Create SystemInfo object from host data Returns: SystemInfo object",
... | 2 | stack_v2_sparse_classes_30k_train_001583 | Implement the Python class `SystemInfo` described below.
Class description:
System Information data object
Method signatures and docstrings:
- def __init__(self, system: str, cpu: CPU, memory: Memory, gpu: GPU): Args: system: name of operating system cpu: CPU info memory: Memory info gpu: GPU info
- def from_host(): ... | Implement the Python class `SystemInfo` described below.
Class description:
System Information data object
Method signatures and docstrings:
- def __init__(self, system: str, cpu: CPU, memory: Memory, gpu: GPU): Args: system: name of operating system cpu: CPU info memory: Memory info gpu: GPU info
- def from_host(): ... | a5388a45f71a949639b35cc5b990bd130d2d8164 | <|skeleton|>
class SystemInfo:
"""System Information data object"""
def __init__(self, system: str, cpu: CPU, memory: Memory, gpu: GPU):
"""Args: system: name of operating system cpu: CPU info memory: Memory info gpu: GPU info"""
<|body_0|>
def from_host():
"""Create SystemInfo obj... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SystemInfo:
"""System Information data object"""
def __init__(self, system: str, cpu: CPU, memory: Memory, gpu: GPU):
"""Args: system: name of operating system cpu: CPU info memory: Memory info gpu: GPU info"""
self.system = system
self.cpu = cpu
self.memory = memory
... | the_stack_v2_python_sparse | PyTorch/LanguageModeling/BERT/triton/runner/task.py | NVIDIA/DeepLearningExamples | train | 11,838 |
4124c96e23e7b62944f93c83382e3889b63484a6 | [
"if not must_contain:\n return\nif isinstance(must_contain, str):\n must_contain = [must_contain]\nregexes = [re.compile(s) for s in must_contain]\nfor i, r in enumerate(regexes):\n match = r.search(output)\n if not match:\n self.fail(f\"Output of command: '{cmd}' contained no match for: '{must_c... | <|body_start_0|>
if not must_contain:
return
if isinstance(must_contain, str):
must_contain = [must_contain]
regexes = [re.compile(s) for s in must_contain]
for i, r in enumerate(regexes):
match = r.search(output)
if not match:
... | Utility Module for building tests that reliably check if a sub-process ran successfully. Commonly with an integration/system test you want to check a command can be run successfully and gives some expected output. How to use: 1. Make a test case in the normal way but inherit from test_util.SubProcessChecker instead of ... | SubProcessChecker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubProcessChecker:
"""Utility Module for building tests that reliably check if a sub-process ran successfully. Commonly with an integration/system test you want to check a command can be run successfully and gives some expected output. How to use: 1. Make a test case in the normal way but inherit... | stack_v2_sparse_classes_10k_train_004991 | 18,428 | permissive | [
{
"docstring": "Internal utility used by run_command(...) to check output (Should not need to call this directly from test cases).",
"name": "_check_output",
"signature": "def _check_output(self, cmd, output: str, must_contain: List[str])"
},
{
"docstring": "Run a command using subprocess, check... | 2 | null | Implement the Python class `SubProcessChecker` described below.
Class description:
Utility Module for building tests that reliably check if a sub-process ran successfully. Commonly with an integration/system test you want to check a command can be run successfully and gives some expected output. How to use: 1. Make a ... | Implement the Python class `SubProcessChecker` described below.
Class description:
Utility Module for building tests that reliably check if a sub-process ran successfully. Commonly with an integration/system test you want to check a command can be run successfully and gives some expected output. How to use: 1. Make a ... | e2f834dd60e7939672c1795b4ac62e89ad0bca49 | <|skeleton|>
class SubProcessChecker:
"""Utility Module for building tests that reliably check if a sub-process ran successfully. Commonly with an integration/system test you want to check a command can be run successfully and gives some expected output. How to use: 1. Make a test case in the normal way but inherit... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SubProcessChecker:
"""Utility Module for building tests that reliably check if a sub-process ran successfully. Commonly with an integration/system test you want to check a command can be run successfully and gives some expected output. How to use: 1. Make a test case in the normal way but inherit from test_ut... | the_stack_v2_python_sparse | utils/examples_tests/test_util.py | graphcore/examples | train | 311 |
74979e1e8793f43899afbb5ae6a5d64aeed8dd09 | [
"url = 'os-services'\nif params:\n url += '?%s' % urllib.urlencode(params)\nresp, body = self.get(url)\nbody = json.loads(body)\nschema = self.get_schema(self.schema_versions_info)\nself.validate_response(schema.list_services, resp, body)\nreturn rest_client.ResponseBody(resp, body)",
"put_body = json.dumps(kw... | <|body_start_0|>
url = 'os-services'
if params:
url += '?%s' % urllib.urlencode(params)
resp, body = self.get(url)
body = json.loads(body)
schema = self.get_schema(self.schema_versions_info)
self.validate_response(schema.list_services, resp, body)
retu... | Client class to send CRUD Volume Services API requests | ServicesClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServicesClient:
"""Client class to send CRUD Volume Services API requests"""
def list_services(self, **params):
"""List all Cinder services. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/block-storage/v3/#list-... | stack_v2_sparse_classes_10k_train_004992 | 4,477 | permissive | [
{
"docstring": "List all Cinder services. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/block-storage/v3/#list-all-cinder-services",
"name": "list_services",
"signature": "def list_services(self, **params)"
},
{
"docstring... | 6 | stack_v2_sparse_classes_30k_train_001126 | Implement the Python class `ServicesClient` described below.
Class description:
Client class to send CRUD Volume Services API requests
Method signatures and docstrings:
- def list_services(self, **params): List all Cinder services. For a full list of available parameters, please refer to the official API reference: h... | Implement the Python class `ServicesClient` described below.
Class description:
Client class to send CRUD Volume Services API requests
Method signatures and docstrings:
- def list_services(self, **params): List all Cinder services. For a full list of available parameters, please refer to the official API reference: h... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class ServicesClient:
"""Client class to send CRUD Volume Services API requests"""
def list_services(self, **params):
"""List all Cinder services. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/block-storage/v3/#list-... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ServicesClient:
"""Client class to send CRUD Volume Services API requests"""
def list_services(self, **params):
"""List all Cinder services. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/block-storage/v3/#list-all-cinder-se... | the_stack_v2_python_sparse | tempest/lib/services/volume/v3/services_client.py | openstack/tempest | train | 270 |
9512ac65ee120de771f37f2dc6182ea6f5e88231 | [
"similarity_calc = region_similarity_calculator.IouSimilarity()\nmatcher = argmax_matcher.ArgMaxMatcher(match_threshold, unmatched_threshold=match_threshold, negatives_lower_than_unmatched=True, force_match_for_each_row=True)\nbox_coder = faster_rcnn_box_coder.FasterRcnnBoxCoder()\nself._target_assigner = target_as... | <|body_start_0|>
similarity_calc = region_similarity_calculator.IouSimilarity()
matcher = argmax_matcher.ArgMaxMatcher(match_threshold, unmatched_threshold=match_threshold, negatives_lower_than_unmatched=True, force_match_for_each_row=True)
box_coder = faster_rcnn_box_coder.FasterRcnnBoxCoder()
... | Labeler for multiscale anchor boxes. | AnchorLabeler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnchorLabeler:
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.5):
"""Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num_classes: integer number representing number of classes i... | stack_v2_sparse_classes_10k_train_004993 | 10,735 | permissive | [
{
"docstring": "Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num_classes: integer number representing number of classes in the dataset. match_threshold: float number between 0 and 1 representing the threshold to assign positive labels for anchors.",
"na... | 3 | null | Implement the Python class `AnchorLabeler` described below.
Class description:
Labeler for multiscale anchor boxes.
Method signatures and docstrings:
- def __init__(self, anchors, num_classes, match_threshold=0.5): Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num... | Implement the Python class `AnchorLabeler` described below.
Class description:
Labeler for multiscale anchor boxes.
Method signatures and docstrings:
- def __init__(self, anchors, num_classes, match_threshold=0.5): Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num... | a5388a45f71a949639b35cc5b990bd130d2d8164 | <|skeleton|>
class AnchorLabeler:
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.5):
"""Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num_classes: integer number representing number of classes i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AnchorLabeler:
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.5):
"""Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num_classes: integer number representing number of classes in the dataset... | the_stack_v2_python_sparse | TensorFlow2/Detection/Efficientdet/model/anchors.py | NVIDIA/DeepLearningExamples | train | 11,838 |
98a0e702cc5df157fd32d387767acc8b2f588187 | [
"super(NRIModel, self).__init__()\nself.enc = AttENC(dim, n_hid, edge_type, do_prob)\nself.dec = RNNDEC(dim, edge_type, n_hid, n_hid, n_hid, do_prob, skip_first)\nself.gumbel_softmax = GumbelSoftmax()\nself.es = Tensor(es, dtype=ms.int32)\nself.size = size",
"logits = self.enc(states_enc, self.es)\nedges = self.g... | <|body_start_0|>
super(NRIModel, self).__init__()
self.enc = AttENC(dim, n_hid, edge_type, do_prob)
self.dec = RNNDEC(dim, edge_type, n_hid, n_hid, n_hid, do_prob, skip_first)
self.gumbel_softmax = GumbelSoftmax()
self.es = Tensor(es, dtype=ms.int32)
self.size = size
<|en... | Auto-encoder. | NRIModel | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NRIModel:
"""Auto-encoder."""
def __init__(self, dim, n_hid, edge_type, do_prob, skip_first, size, es):
"""Parameters ---------- encoder : nn.Cell an encoder inferring relations. decoder : nn.Cell an decoder predicting future states. es : Tensor edge list. size : int number of nodes.... | stack_v2_sparse_classes_10k_train_004994 | 12,491 | permissive | [
{
"docstring": "Parameters ---------- encoder : nn.Cell an encoder inferring relations. decoder : nn.Cell an decoder predicting future states. es : Tensor edge list. size : int number of nodes.",
"name": "__init__",
"signature": "def __init__(self, dim, n_hid, edge_type, do_prob, skip_first, size, es)"
... | 2 | null | Implement the Python class `NRIModel` described below.
Class description:
Auto-encoder.
Method signatures and docstrings:
- def __init__(self, dim, n_hid, edge_type, do_prob, skip_first, size, es): Parameters ---------- encoder : nn.Cell an encoder inferring relations. decoder : nn.Cell an decoder predicting future s... | Implement the Python class `NRIModel` described below.
Class description:
Auto-encoder.
Method signatures and docstrings:
- def __init__(self, dim, n_hid, edge_type, do_prob, skip_first, size, es): Parameters ---------- encoder : nn.Cell an encoder inferring relations. decoder : nn.Cell an decoder predicting future s... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class NRIModel:
"""Auto-encoder."""
def __init__(self, dim, n_hid, edge_type, do_prob, skip_first, size, es):
"""Parameters ---------- encoder : nn.Cell an encoder inferring relations. decoder : nn.Cell an decoder predicting future states. es : Tensor edge list. size : int number of nodes.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NRIModel:
"""Auto-encoder."""
def __init__(self, dim, n_hid, edge_type, do_prob, skip_first, size, es):
"""Parameters ---------- encoder : nn.Cell an encoder inferring relations. decoder : nn.Cell an decoder predicting future states. es : Tensor edge list. size : int number of nodes."""
s... | the_stack_v2_python_sparse | research/gnn/nri-mpm/models/nri.py | mindspore-ai/models | train | 301 |
8707cb81b2fdeea848921f87af2905db93c48710 | [
"predecessors = []\nfor idx in range(len(word)):\n predecessors.append(word[:idx] + word[idx + 1:])\nreturn predecessors",
"words.sort(key=lambda word: len(word))\nword_to_chain_length = {}\nmax_chain_length = 1\nfor word in words:\n word_to_chain_length[word] = 1\n predecessors = self.get_predecessors(w... | <|body_start_0|>
predecessors = []
for idx in range(len(word)):
predecessors.append(word[:idx] + word[idx + 1:])
return predecessors
<|end_body_0|>
<|body_start_1|>
words.sort(key=lambda word: len(word))
word_to_chain_length = {}
max_chain_length = 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def get_predecessors(self, word):
"""Return a list of words with 1 character removed from the provided word"""
<|body_0|>
def longestStrChain(self, words):
""":type words: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_004995 | 1,544 | no_license | [
{
"docstring": "Return a list of words with 1 character removed from the provided word",
"name": "get_predecessors",
"signature": "def get_predecessors(self, word)"
},
{
"docstring": ":type words: List[str] :rtype: int",
"name": "longestStrChain",
"signature": "def longestStrChain(self, ... | 2 | stack_v2_sparse_classes_30k_train_006488 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def get_predecessors(self, word): Return a list of words with 1 character removed from the provided word
- def longestStrChain(self, words): :type words: List[str] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def get_predecessors(self, word): Return a list of words with 1 character removed from the provided word
- def longestStrChain(self, words): :type words: List[str] :rtype: int
<... | 52d71a93de7f002ac887a82c947e1e32a3e7255f | <|skeleton|>
class Solution:
def get_predecessors(self, word):
"""Return a list of words with 1 character removed from the provided word"""
<|body_0|>
def longestStrChain(self, words):
""":type words: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def get_predecessors(self, word):
"""Return a list of words with 1 character removed from the provided word"""
predecessors = []
for idx in range(len(word)):
predecessors.append(word[:idx] + word[idx + 1:])
return predecessors
def longestStrChain(self... | the_stack_v2_python_sparse | template/solution.py | code-in-public/leetcode | train | 3 | |
c235f3fe930ecc07f178311983aad70f6f0706f1 | [
"super().__init__(name, instrument, **kwargs)\nself._reference = instrument.root_instrument.reference\nself._dll_get_function = partial(dll_get_function, self._reference)\nself._dll_set_function = partial(dll_set_function, self._reference)",
"if hasattr(self.instrument, 'channel_number'):\n instr = cast(Instru... | <|body_start_0|>
super().__init__(name, instrument, **kwargs)
self._reference = instrument.root_instrument.reference
self._dll_get_function = partial(dll_get_function, self._reference)
self._dll_set_function = partial(dll_set_function, self._reference)
<|end_body_0|>
<|body_start_1|>
... | LdaParameter | [
"GPL-2.0-only",
"GPL-2.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LdaParameter:
def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs):
"""Parameter associated with one channel of the LDA. Args: name: parameter name instrument: parent instrument, either LDA or LDA chann... | stack_v2_sparse_classes_10k_train_004996 | 12,103 | permissive | [
{
"docstring": "Parameter associated with one channel of the LDA. Args: name: parameter name instrument: parent instrument, either LDA or LDA channel dll_get_function: DLL function that gets the value dll_get_function: DLL function that sets the value",
"name": "__init__",
"signature": "def __init__(sel... | 4 | stack_v2_sparse_classes_30k_train_006445 | Implement the Python class `LdaParameter` described below.
Class description:
Implement the LdaParameter class.
Method signatures and docstrings:
- def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs): Parameter associated with one ... | Implement the Python class `LdaParameter` described below.
Class description:
Implement the LdaParameter class.
Method signatures and docstrings:
- def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs): Parameter associated with one ... | e07c9f23339ab00b0f4c4cc46711593d88f7fc84 | <|skeleton|>
class LdaParameter:
def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs):
"""Parameter associated with one channel of the LDA. Args: name: parameter name instrument: parent instrument, either LDA or LDA chann... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LdaParameter:
def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs):
"""Parameter associated with one channel of the LDA. Args: name: parameter name instrument: parent instrument, either LDA or LDA channel dll_get_fun... | the_stack_v2_python_sparse | qcodes_contrib_drivers/drivers/Vaunix/LDA.py | QCoDeS/Qcodes_contrib_drivers | train | 32 | |
f1620989ed61be9a21630c9afabc0867551b62e2 | [
"self.reporting = reporting\nself.github = GitHubService(ghName, ghToken)\nself.artifacts = ArtifactService()\nself.monitoring = MonitoringService()\nself.idle = True\nself.started = 0",
"s = os.statvfs(config.prbuildsRoot)\nfreeSpaceMB = s.f_frsize * s.f_bavail / 1000 / 1000\nhealth = {'has free space': freeSpac... | <|body_start_0|>
self.reporting = reporting
self.github = GitHubService(ghName, ghToken)
self.artifacts = ArtifactService()
self.monitoring = MonitoringService()
self.idle = True
self.started = 0
<|end_body_0|>
<|body_start_1|>
s = os.statvfs(config.prbuildsRoot)... | Trousers | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trousers:
def __init__(self, reporting, ghName, ghToken):
"""constructor"""
<|body_0|>
def is_healthy(self):
"""we are healthy under these conditions"""
<|body_1|>
def process(self, action, bucket, metricService):
"""process a message coming off ... | stack_v2_sparse_classes_10k_train_004997 | 3,641 | no_license | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self, reporting, ghName, ghToken)"
},
{
"docstring": "we are healthy under these conditions",
"name": "is_healthy",
"signature": "def is_healthy(self)"
},
{
"docstring": "process a message coming off the... | 4 | stack_v2_sparse_classes_30k_val_000193 | Implement the Python class `Trousers` described below.
Class description:
Implement the Trousers class.
Method signatures and docstrings:
- def __init__(self, reporting, ghName, ghToken): constructor
- def is_healthy(self): we are healthy under these conditions
- def process(self, action, bucket, metricService): proc... | Implement the Python class `Trousers` described below.
Class description:
Implement the Trousers class.
Method signatures and docstrings:
- def __init__(self, reporting, ghName, ghToken): constructor
- def is_healthy(self): we are healthy under these conditions
- def process(self, action, bucket, metricService): proc... | 1dd8f0959fec8a3bb5e06ee0c4acdd43c509765b | <|skeleton|>
class Trousers:
def __init__(self, reporting, ghName, ghToken):
"""constructor"""
<|body_0|>
def is_healthy(self):
"""we are healthy under these conditions"""
<|body_1|>
def process(self, action, bucket, metricService):
"""process a message coming off ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Trousers:
def __init__(self, reporting, ghName, ghToken):
"""constructor"""
self.reporting = reporting
self.github = GitHubService(ghName, ghToken)
self.artifacts = ArtifactService()
self.monitoring = MonitoringService()
self.idle = True
self.started = 0... | the_stack_v2_python_sparse | trousers/trouserlib/trousers.py | guardian/prbuilds | train | 6 | |
d6697b69f888aa83ef7cbd034c6a20d4dd7f0745 | [
"super(DeepLPFNet, self).__init__()\nself.backbonenet = unet.UNetModel()\nself.deeplpfnet = DeepLPFParameterPrediction()",
"feat = self.backbonenet(img)\nimg = self.deeplpfnet(feat)\nreturn img"
] | <|body_start_0|>
super(DeepLPFNet, self).__init__()
self.backbonenet = unet.UNetModel()
self.deeplpfnet = DeepLPFParameterPrediction()
<|end_body_0|>
<|body_start_1|>
feat = self.backbonenet(img)
img = self.deeplpfnet(feat)
return img
<|end_body_1|>
| DeepLPFNet | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepLPFNet:
def __init__(self):
"""Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A"""
<|body_0|>
def forward(self, img):
"""Neural network forward function :param img: forward the data img through the network :returns: residu... | stack_v2_sparse_classes_10k_train_004998 | 38,578 | permissive | [
{
"docstring": "Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Neural network forward function :param img: forward the data img through the network :returns: residual image :rtyp... | 2 | stack_v2_sparse_classes_30k_train_003840 | Implement the Python class `DeepLPFNet` described below.
Class description:
Implement the DeepLPFNet class.
Method signatures and docstrings:
- def __init__(self): Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A
- def forward(self, img): Neural network forward function :param... | Implement the Python class `DeepLPFNet` described below.
Class description:
Implement the DeepLPFNet class.
Method signatures and docstrings:
- def __init__(self): Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A
- def forward(self, img): Neural network forward function :param... | 82c49c36b76987a46dec8479793f7cf0150839c6 | <|skeleton|>
class DeepLPFNet:
def __init__(self):
"""Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A"""
<|body_0|>
def forward(self, img):
"""Neural network forward function :param img: forward the data img through the network :returns: residu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeepLPFNet:
def __init__(self):
"""Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A"""
super(DeepLPFNet, self).__init__()
self.backbonenet = unet.UNetModel()
self.deeplpfnet = DeepLPFParameterPrediction()
def forward(self, img):
... | the_stack_v2_python_sparse | DeepLPF/model.py | huawei-noah/noah-research | train | 816 | |
4a8f0e5e1d53827cd43c487ddf3b7f384c341376 | [
"if not isinstance(item, Area):\n raise TypeError(f'{item} is not an Area. Only Area objects can be inside Areas.')\nself.data.append(item)",
"containing = Areas()\nfor area in self:\n field = rgetattr(area, field_name)\n if field.value == field_value:\n containing.append(area)\nreturn containing"... | <|body_start_0|>
if not isinstance(item, Area):
raise TypeError(f'{item} is not an Area. Only Area objects can be inside Areas.')
self.data.append(item)
<|end_body_0|>
<|body_start_1|>
containing = Areas()
for area in self:
field = rgetattr(area, field_name)
... | Searchable collection of Areas. Behaves like a list. | Areas | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Areas:
"""Searchable collection of Areas. Behaves like a list."""
def append(self, item: Area) -> None:
"""Add a new Area to the container. Raises: TypeError: If a non-Area object is given."""
<|body_0|>
def containing(self, field_name: str, field_value: str):
""... | stack_v2_sparse_classes_10k_train_004999 | 3,005 | permissive | [
{
"docstring": "Add a new Area to the container. Raises: TypeError: If a non-Area object is given.",
"name": "append",
"signature": "def append(self, item: Area) -> None"
},
{
"docstring": "Search for Areas where the Field's value matches the expected value and then returns an Areas object with ... | 3 | stack_v2_sparse_classes_30k_train_004953 | Implement the Python class `Areas` described below.
Class description:
Searchable collection of Areas. Behaves like a list.
Method signatures and docstrings:
- def append(self, item: Area) -> None: Add a new Area to the container. Raises: TypeError: If a non-Area object is given.
- def containing(self, field_name: st... | Implement the Python class `Areas` described below.
Class description:
Searchable collection of Areas. Behaves like a list.
Method signatures and docstrings:
- def append(self, item: Area) -> None: Add a new Area to the container. Raises: TypeError: If a non-Area object is given.
- def containing(self, field_name: st... | c9864db2237d63055378c30652f43c84d20b3592 | <|skeleton|>
class Areas:
"""Searchable collection of Areas. Behaves like a list."""
def append(self, item: Area) -> None:
"""Add a new Area to the container. Raises: TypeError: If a non-Area object is given."""
<|body_0|>
def containing(self, field_name: str, field_value: str):
""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Areas:
"""Searchable collection of Areas. Behaves like a list."""
def append(self, item: Area) -> None:
"""Add a new Area to the container. Raises: TypeError: If a non-Area object is given."""
if not isinstance(item, Area):
raise TypeError(f'{item} is not an Area. Only Area ob... | the_stack_v2_python_sparse | stere/areas/areas.py | jsfehler/stere | train | 23 |
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