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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b62173335183be65b5f41cc1779a5b84b3e2cbfb | [
"super(IQN, self).__init__()\nobs_shape, action_shape = (squeeze(obs_shape), squeeze(action_shape))\nif head_hidden_size is None:\n head_hidden_size = encoder_hidden_size_list[-1]\nif isinstance(obs_shape, int) or len(obs_shape) == 1:\n self.encoder = FCEncoder(obs_shape, encoder_hidden_size_list, activation=... | <|body_start_0|>
super(IQN, self).__init__()
obs_shape, action_shape = (squeeze(obs_shape), squeeze(action_shape))
if head_hidden_size is None:
head_hidden_size = encoder_hidden_size_list[-1]
if isinstance(obs_shape, int) or len(obs_shape) == 1:
self.encoder = FCE... | IQN | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IQN:
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], head_hidden_size: Optional[int]=None, head_layer_num: int=1, num_quantiles: int=32, quantile_embedding_size: int=128, activation: Optional[n... | stack_v2_sparse_classes_10k_train_000700 | 30,380 | permissive | [
{
"docstring": "Overview: Init the IQN Model according to input arguments. Arguments: - obs_shape (:obj:`Union[int, SequenceType]`): Observation space shape. - action_shape (:obj:`Union[int, SequenceType]`): Action space shape. - encoder_hidden_size_list (:obj:`SequenceType`): Collection of ``hidden_size`` to p... | 2 | null | Implement the Python class `IQN` described below.
Class description:
Implement the IQN class.
Method signatures and docstrings:
- def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], head_hidden_size: Optional[int]=None,... | Implement the Python class `IQN` described below.
Class description:
Implement the IQN class.
Method signatures and docstrings:
- def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], head_hidden_size: Optional[int]=None,... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class IQN:
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], head_hidden_size: Optional[int]=None, head_layer_num: int=1, num_quantiles: int=32, quantile_embedding_size: int=128, activation: Optional[n... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IQN:
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], head_hidden_size: Optional[int]=None, head_layer_num: int=1, num_quantiles: int=32, quantile_embedding_size: int=128, activation: Optional[nn.Module]=nn.R... | the_stack_v2_python_sparse | ding/model/template/q_learning.py | shengxuesun/DI-engine | train | 1 | |
d43b7ebba3c8d859469b2168efecb696a855bdf9 | [
"if not prices:\n return 0\nn = len(prices)\ndp, min_buy_stock_value = ([0] * n, prices[0])\nfor i in range(1, n):\n min_buy_stock_value = min(prices[i], min_buy_stock_value)\n dp[i] = max(prices[i] - min_buy_stock_value, dp[i - 1])\nreturn dp[n - 1]",
"if not prices:\n return 0\nn, min_buy_stock_valu... | <|body_start_0|>
if not prices:
return 0
n = len(prices)
dp, min_buy_stock_value = ([0] * n, prices[0])
for i in range(1, n):
min_buy_stock_value = min(prices[i], min_buy_stock_value)
dp[i] = max(prices[i] - min_buy_stock_value, dp[i - 1])
retu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: list) -> int:
"""动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])"""
<|body_0|>
def maxProfit_1(self, prices: list) -> int:
"""迭代"""
<|body_1|>
def ... | stack_v2_sparse_classes_10k_train_000701 | 3,964 | no_license | [
{
"docstring": "动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: list) -> int"
},
{
"docstring": "迭代",
"name": "maxProfit_1",
"signature": "def maxProfit_1... | 4 | stack_v2_sparse_classes_30k_train_006593 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: list) -> int: 动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])
- def maxProfit_1(s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: list) -> int: 动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])
- def maxProfit_1(s... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def maxProfit(self, prices: list) -> int:
"""动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])"""
<|body_0|>
def maxProfit_1(self, prices: list) -> int:
"""迭代"""
<|body_1|>
def ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices: list) -> int:
"""动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])"""
if not prices:
return 0
n = len(prices)
dp, min_buy_stock_value = ([0] * n, prices[0])
... | the_stack_v2_python_sparse | algorithm/leetcode/dp/08-买卖股票的最佳时机.py | lxconfig/UbuntuCode_bak | train | 0 | |
1b78c7d9d8a926db4786577ea8ebd650eecd1d3c | [
"super(LandmarkGeneratorMultipleHeatmap, self).__init__(dim, output_size, landmark_indizes, landmark_flip_pairs, data_format, pre_transformation, post_transformation)\nself.output_size_np = list(reversed(self.output_size))\nself.sigma = sigma\nself.scale_factor = scale_factor\nself.normalize_center = normalize_cent... | <|body_start_0|>
super(LandmarkGeneratorMultipleHeatmap, self).__init__(dim, output_size, landmark_indizes, landmark_flip_pairs, data_format, pre_transformation, post_transformation)
self.output_size_np = list(reversed(self.output_size))
self.sigma = sigma
self.scale_factor = scale_facto... | Generates heatmap images with multiple Gaussian peaks | LandmarkGeneratorMultipleHeatmap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LandmarkGeneratorMultipleHeatmap:
"""Generates heatmap images with multiple Gaussian peaks"""
def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first', pre_transformation=None, post_transformatio... | stack_v2_sparse_classes_10k_train_000702 | 16,690 | no_license | [
{
"docstring": "Initializer :param output_size: output image size :param sigma: Gaussian sigma :param scale_factor: heatmap scale factor, each value of the Gaussian will be multiplied with this value :param normalize_center: if True, the value on the center is set to scale_factor otherwise, the default gaussian... | 2 | stack_v2_sparse_classes_30k_train_002388 | Implement the Python class `LandmarkGeneratorMultipleHeatmap` described below.
Class description:
Generates heatmap images with multiple Gaussian peaks
Method signatures and docstrings:
- def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_... | Implement the Python class `LandmarkGeneratorMultipleHeatmap` described below.
Class description:
Generates heatmap images with multiple Gaussian peaks
Method signatures and docstrings:
- def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_... | ef6cee91264ba1fe6b40d9823a07647b95bcc2c4 | <|skeleton|>
class LandmarkGeneratorMultipleHeatmap:
"""Generates heatmap images with multiple Gaussian peaks"""
def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first', pre_transformation=None, post_transformatio... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LandmarkGeneratorMultipleHeatmap:
"""Generates heatmap images with multiple Gaussian peaks"""
def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first', pre_transformation=None, post_transformation=None):
... | the_stack_v2_python_sparse | generators/landmark_generator.py | XiaoweiXu/MedicalDataAugmentationTool | train | 1 |
9491a39cf700a2c335c03197b903861e6eaca755 | [
"head = ListNode(0)\nl3 = head\naddon = 0\nwhile l1 is not None or l2 is not None:\n if l1 is None:\n tmp = l2.val + addon * 1\n elif l2 is None:\n tmp = l1.val + addon * 1\n else:\n tmp = l1.val + l2.val + addon * 1\n addon = 0\n if tmp >= 10:\n l3.val = tmp - 10\n ... | <|body_start_0|>
head = ListNode(0)
l3 = head
addon = 0
while l1 is not None or l2 is not None:
if l1 is None:
tmp = l2.val + addon * 1
elif l2 is None:
tmp = l1.val + addon * 1
else:
tmp = l1.val + l2.va... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def addTwoNumbers(self, l1, l2) -> ListNode:
"""最直接的方法：遍历两个链表到最后，执行加操作 Q：l1，l2为空之后，继续执行增加一个节点，导致最后多一位0 A：加一个判断，都为空直接结束 Q：其中一个链表对应的数位数多一位 1 8 + 2 A：有一个不为空则继续加，只不过不加为空的那个链表的值，None.val报错， 遍历的时候也忽略为空的那个 Q：还有最后可能也有进位 5 + 5 A: 判断都为空的时候再判断进位标志位是否为1，是的话一个节点值为1"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_000703 | 3,769 | no_license | [
{
"docstring": "最直接的方法：遍历两个链表到最后，执行加操作 Q：l1，l2为空之后，继续执行增加一个节点，导致最后多一位0 A：加一个判断，都为空直接结束 Q：其中一个链表对应的数位数多一位 1 8 + 2 A：有一个不为空则继续加，只不过不加为空的那个链表的值，None.val报错， 遍历的时候也忽略为空的那个 Q：还有最后可能也有进位 5 + 5 A: 判断都为空的时候再判断进位标志位是否为1，是的话一个节点值为1",
"name": "addTwoNumbers",
"signature": "def addTwoNumbers(self, l1, l2) -> ListNod... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addTwoNumbers(self, l1, l2) -> ListNode: 最直接的方法：遍历两个链表到最后，执行加操作 Q：l1，l2为空之后，继续执行增加一个节点，导致最后多一位0 A：加一个判断，都为空直接结束 Q：其中一个链表对应的数位数多一位 1 8 + 2 A：有一个不为空则继续加，只不过不加为空的那个链表的值，None.val... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addTwoNumbers(self, l1, l2) -> ListNode: 最直接的方法：遍历两个链表到最后，执行加操作 Q：l1，l2为空之后，继续执行增加一个节点，导致最后多一位0 A：加一个判断，都为空直接结束 Q：其中一个链表对应的数位数多一位 1 8 + 2 A：有一个不为空则继续加，只不过不加为空的那个链表的值，None.val... | 95dddb78bccd169d9d219a473627361fe739ab5e | <|skeleton|>
class Solution:
def addTwoNumbers(self, l1, l2) -> ListNode:
"""最直接的方法：遍历两个链表到最后，执行加操作 Q：l1，l2为空之后，继续执行增加一个节点，导致最后多一位0 A：加一个判断，都为空直接结束 Q：其中一个链表对应的数位数多一位 1 8 + 2 A：有一个不为空则继续加，只不过不加为空的那个链表的值，None.val报错， 遍历的时候也忽略为空的那个 Q：还有最后可能也有进位 5 + 5 A: 判断都为空的时候再判断进位标志位是否为1，是的话一个节点值为1"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def addTwoNumbers(self, l1, l2) -> ListNode:
"""最直接的方法：遍历两个链表到最后，执行加操作 Q：l1，l2为空之后，继续执行增加一个节点，导致最后多一位0 A：加一个判断，都为空直接结束 Q：其中一个链表对应的数位数多一位 1 8 + 2 A：有一个不为空则继续加，只不过不加为空的那个链表的值，None.val报错， 遍历的时候也忽略为空的那个 Q：还有最后可能也有进位 5 + 5 A: 判断都为空的时候再判断进位标志位是否为1，是的话一个节点值为1"""
head = ListNode(0)
l... | the_stack_v2_python_sparse | LinkListOperation/addTwoNumbers.py | Philex5/codingPractice | train | 0 | |
e1693b454a5a36cbb1ef53743dbad728954c1078 | [
"team.trusted = trusted\nteam.save(update_fields=['trusted'])\nreturn Response({'detail': 'Mapping Team set as {}.'.format('trusted' if trusted else 'untrusted')}, status=status.HTTP_200_OK)",
"team = self.get_object()\nif team.trusted:\n return Response({'detail': 'Mapping team is already trusted.'}, status=s... | <|body_start_0|>
team.trusted = trusted
team.save(update_fields=['trusted'])
return Response({'detail': 'Mapping Team set as {}.'.format('trusted' if trusted else 'untrusted')}, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
team = self.get_object()
if team.trusted:
... | MappingTeamTrustingAPIView | [
"BSD-3-Clause",
"BSD-2-Clause",
"ISC",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MappingTeamTrustingAPIView:
def update_team(self, team, request, trusted):
"""Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 200 response"""
<|body_0|>
def set_trusted(self, request, pk):
"""Set a Mapping Team as trusted.... | stack_v2_sparse_classes_10k_train_000704 | 9,317 | permissive | [
{
"docstring": "Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 200 response",
"name": "update_team",
"signature": "def update_team(self, team, request, trusted)"
},
{
"docstring": "Set a Mapping Team as trusted. You don't need to send data, just make... | 3 | stack_v2_sparse_classes_30k_train_001405 | Implement the Python class `MappingTeamTrustingAPIView` described below.
Class description:
Implement the MappingTeamTrustingAPIView class.
Method signatures and docstrings:
- def update_team(self, team, request, trusted): Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 20... | Implement the Python class `MappingTeamTrustingAPIView` described below.
Class description:
Implement the MappingTeamTrustingAPIView class.
Method signatures and docstrings:
- def update_team(self, team, request, trusted): Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 20... | 603496dce834bf3ecf28cc949da619b837e2873c | <|skeleton|>
class MappingTeamTrustingAPIView:
def update_team(self, team, request, trusted):
"""Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 200 response"""
<|body_0|>
def set_trusted(self, request, pk):
"""Set a Mapping Team as trusted.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MappingTeamTrustingAPIView:
def update_team(self, team, request, trusted):
"""Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 200 response"""
team.trusted = trusted
team.save(update_fields=['trusted'])
return Response({'detail': 'Map... | the_stack_v2_python_sparse | Backend/osmchadjango/users/views.py | habi/srz-edi | train | 1 | |
dd9c6a80e3cdb9dad37839d2c6d98e65e3e248d4 | [
"if type(FocalPlaneInfo) == type(None):\n self.FocalPlaneInfo = [{'xpos': 0.0, 'ypos': 0.0, 'Pf': 0, 'Px': 0, 'Py': 0, 'Pc': 0, 'Pn': 0, 'Pa': 0, 'Pb': 0}]\nelse:\n self.FocalPlaneInfo = FocalPlaneInfo\nif type(ReceiverInfo) == type(None):\n self.ReceiverInfo = [{'sigma': 1.0, 'fknee': 1.0, 'SampRate': 100... | <|body_start_0|>
if type(FocalPlaneInfo) == type(None):
self.FocalPlaneInfo = [{'xpos': 0.0, 'ypos': 0.0, 'Pf': 0, 'Px': 0, 'Py': 0, 'Pc': 0, 'Pn': 0, 'Pa': 0, 'Pb': 0}]
else:
self.FocalPlaneInfo = FocalPlaneInfo
if type(ReceiverInfo) == type(None):
self.Recei... | Telescope | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Telescope:
def __init__(self, FocalPlaneInfo=None, ReceiverInfo=None, SkyMap=None, Healpix=False):
"""Simulated Telescope Arguments ObsInfo-- List of user defined observations KeyWord Arguments FocalPlaneInfo -- Information on focal positions of horns and TPoint values ReceiverInfo -- In... | stack_v2_sparse_classes_10k_train_000705 | 2,432 | no_license | [
{
"docstring": "Simulated Telescope Arguments ObsInfo-- List of user defined observations KeyWord Arguments FocalPlaneInfo -- Information on focal positions of horns and TPoint values ReceiverInfo -- Information of receiver noise and 1/f characteristics SkyMap -- Fits file containing image to be sampled",
"... | 2 | stack_v2_sparse_classes_30k_train_001511 | Implement the Python class `Telescope` described below.
Class description:
Implement the Telescope class.
Method signatures and docstrings:
- def __init__(self, FocalPlaneInfo=None, ReceiverInfo=None, SkyMap=None, Healpix=False): Simulated Telescope Arguments ObsInfo-- List of user defined observations KeyWord Argume... | Implement the Python class `Telescope` described below.
Class description:
Implement the Telescope class.
Method signatures and docstrings:
- def __init__(self, FocalPlaneInfo=None, ReceiverInfo=None, SkyMap=None, Healpix=False): Simulated Telescope Arguments ObsInfo-- List of user defined observations KeyWord Argume... | ef7caf1b05880a4a2f4c1c12ca439014f82dfe6b | <|skeleton|>
class Telescope:
def __init__(self, FocalPlaneInfo=None, ReceiverInfo=None, SkyMap=None, Healpix=False):
"""Simulated Telescope Arguments ObsInfo-- List of user defined observations KeyWord Arguments FocalPlaneInfo -- Information on focal positions of horns and TPoint values ReceiverInfo -- In... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Telescope:
def __init__(self, FocalPlaneInfo=None, ReceiverInfo=None, SkyMap=None, Healpix=False):
"""Simulated Telescope Arguments ObsInfo-- List of user defined observations KeyWord Arguments FocalPlaneInfo -- Information on focal positions of horns and TPoint values ReceiverInfo -- Information of r... | the_stack_v2_python_sparse | SIMTELE/Telescope.py | SharperJBCA/MFI-Pipeline | train | 0 | |
81af6202e57d9a4e0d3f5e47c160aeefcf7db447 | [
"address = u'local@domain'\nexpected = address.encode(config.charset)\nself.failUnlessEqual(mail.encodeAddress(address, self.charset), expected)",
"address = u'Phrase <local@domain>'\nphrase = str(Header(u'Phrase '.encode('utf-8'), self.charset))\nexpected = phrase + '<local@domain>'\nself.failUnlessEqual(mail.en... | <|body_start_0|>
address = u'local@domain'
expected = address.encode(config.charset)
self.failUnlessEqual(mail.encodeAddress(address, self.charset), expected)
<|end_body_0|>
<|body_start_1|>
address = u'Phrase <local@domain>'
phrase = str(Header(u'Phrase '.encode('utf-8'), self.... | Address encoding tests See http://www.faqs.org/rfcs/rfc2822.html section 3.4. Address Specification. mailbox = name-addr / addr-spec name-addr = [display-name] angle-addr angle-addr = [CFWS] "<" addr-spec ">" [CFWS] / obs-angle-addr | EncodeAddressTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncodeAddressTests:
"""Address encoding tests See http://www.faqs.org/rfcs/rfc2822.html section 3.4. Address Specification. mailbox = name-addr / addr-spec name-addr = [display-name] angle-addr angle-addr = [CFWS] "<" addr-spec ">" [CFWS] / obs-angle-addr"""
def testSimpleAddress(self):
... | stack_v2_sparse_classes_10k_train_000706 | 4,366 | no_license | [
{
"docstring": "util.mail: encode simple address: local@domain",
"name": "testSimpleAddress",
"signature": "def testSimpleAddress(self)"
},
{
"docstring": "util.mail: encode address: 'Phrase <local@domain>'",
"name": "testComposite",
"signature": "def testComposite(self)"
},
{
"d... | 6 | null | Implement the Python class `EncodeAddressTests` described below.
Class description:
Address encoding tests See http://www.faqs.org/rfcs/rfc2822.html section 3.4. Address Specification. mailbox = name-addr / addr-spec name-addr = [display-name] angle-addr angle-addr = [CFWS] "<" addr-spec ">" [CFWS] / obs-angle-addr
M... | Implement the Python class `EncodeAddressTests` described below.
Class description:
Address encoding tests See http://www.faqs.org/rfcs/rfc2822.html section 3.4. Address Specification. mailbox = name-addr / addr-spec name-addr = [display-name] angle-addr angle-addr = [CFWS] "<" addr-spec ">" [CFWS] / obs-angle-addr
M... | a17b987c5adaa13befb0fd74ac400c8edbe62ef5 | <|skeleton|>
class EncodeAddressTests:
"""Address encoding tests See http://www.faqs.org/rfcs/rfc2822.html section 3.4. Address Specification. mailbox = name-addr / addr-spec name-addr = [display-name] angle-addr angle-addr = [CFWS] "<" addr-spec ">" [CFWS] / obs-angle-addr"""
def testSimpleAddress(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncodeAddressTests:
"""Address encoding tests See http://www.faqs.org/rfcs/rfc2822.html section 3.4. Address Specification. mailbox = name-addr / addr-spec name-addr = [display-name] angle-addr angle-addr = [CFWS] "<" addr-spec ">" [CFWS] / obs-angle-addr"""
def testSimpleAddress(self):
"""util.m... | the_stack_v2_python_sparse | moin/lib/python2.4/site-packages/MoinMoin/_tests/test_util_mail.py | imosts/flume | train | 0 |
abba8f84e256d582a94f4ecf3ecd451f8bdadc25 | [
"out_x = u_x * scale_x - u_y * scale_y + shift_x\nout_y = u_x * scale_y + u_y * scale_x + shift_y\nreturn (out_x, out_y)",
"norm2 = self.get_square_norm(u)\neps = 1e-07\nout = ops.sqrt(norm2 + eps)\nreturn out",
"u_r, u_i = get_real_and_imag(u)\nout = u_r ** 2 + u_i ** 2\nreturn out"
] | <|body_start_0|>
out_x = u_x * scale_x - u_y * scale_y + shift_x
out_y = u_x * scale_y + u_y * scale_x + shift_y
return (out_x, out_y)
<|end_body_0|>
<|body_start_1|>
norm2 = self.get_square_norm(u)
eps = 1e-07
out = ops.sqrt(norm2 + eps)
return out
<|end_body_1|... | The implementor class of the Batch Normalization layer for complex numbers. Implements the functionality specific to complex numbers and needed by the 'BatchNorm' class. This includes: getting the norm of complex number, applying scaling and shift to a complex tensor, and updating the running mean and variance, which a... | _BatchNormImpl | [
"Apache-2.0",
"LicenseRef-scancode-proprietary-license",
"MPL-1.0",
"OpenSSL",
"LGPL-3.0-only",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-3-Clause-Open-MPI",
"MIT",
"MPL-2.0-no-copyleft-exception",
"NTP",
"BSD-3-Clause",
"GPL-1.0-or-later",
"0BSD",
"MPL-2.0",
"LicenseRef-scancode-f... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _BatchNormImpl:
"""The implementor class of the Batch Normalization layer for complex numbers. Implements the functionality specific to complex numbers and needed by the 'BatchNorm' class. This includes: getting the norm of complex number, applying scaling and shift to a complex tensor, and updat... | stack_v2_sparse_classes_10k_train_000707 | 7,025 | permissive | [
{
"docstring": "Applies complex scaling and shift to an input tensor. This function implements the operation as: .. math:: \\\\begin{align} \\\\text{Re(out)} = \\\\text{Re(inp)} * \\\\text{Re(scale)} - \\\\text{Im(inp)} * \\\\text{Im(scale)} + \\\\text{Re(shift)}\\\\\\\\ \\\\text{Im(out)} = \\\\text{Re(inp)} * ... | 3 | null | Implement the Python class `_BatchNormImpl` described below.
Class description:
The implementor class of the Batch Normalization layer for complex numbers. Implements the functionality specific to complex numbers and needed by the 'BatchNorm' class. This includes: getting the norm of complex number, applying scaling a... | Implement the Python class `_BatchNormImpl` described below.
Class description:
The implementor class of the Batch Normalization layer for complex numbers. Implements the functionality specific to complex numbers and needed by the 'BatchNorm' class. This includes: getting the norm of complex number, applying scaling a... | 54acb15d435533c815ee1bd9f6dc0b56b4d4cf83 | <|skeleton|>
class _BatchNormImpl:
"""The implementor class of the Batch Normalization layer for complex numbers. Implements the functionality specific to complex numbers and needed by the 'BatchNorm' class. This includes: getting the norm of complex number, applying scaling and shift to a complex tensor, and updat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _BatchNormImpl:
"""The implementor class of the Batch Normalization layer for complex numbers. Implements the functionality specific to complex numbers and needed by the 'BatchNorm' class. This includes: getting the norm of complex number, applying scaling and shift to a complex tensor, and updating the runni... | the_stack_v2_python_sparse | mindspore/python/mindspore/hypercomplex/complex/_complex_bn_impl.py | mindspore-ai/mindspore | train | 4,178 |
6dea838389ac83e4eab6519a632ccd1dff39842f | [
"if this is None:\n return copy.deepcopy(that)\nif that is None:\n return copy.deepcopy(this)\nresult = copy.deepcopy(this)\nresult_key_set = set(result.ids().keys())\nthat_key_set = set(that.ids().keys())\nresult._ids = {x: 1 for x in result_key_set.union(that_key_set)}\nreturn result",
"if this is None or... | <|body_start_0|>
if this is None:
return copy.deepcopy(that)
if that is None:
return copy.deepcopy(this)
result = copy.deepcopy(this)
result_key_set = set(result.ids().keys())
that_key_set = set(that.ids().keys())
result._ids = {x: 1 for x in resul... | Set operations for ExactSet. The methods below all accept an ExactMultiSet object and returning an ExactMultiSet object. | ExactSetOperator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExactSetOperator:
"""Set operations for ExactSet. The methods below all accept an ExactMultiSet object and returning an ExactMultiSet object."""
def union(cls, this, that):
"""Union operation for ExactSet."""
<|body_0|>
def intersection(cls, this, that):
"""Inter... | stack_v2_sparse_classes_10k_train_000708 | 19,268 | permissive | [
{
"docstring": "Union operation for ExactSet.",
"name": "union",
"signature": "def union(cls, this, that)"
},
{
"docstring": "Intersection operation for ExactSet.",
"name": "intersection",
"signature": "def intersection(cls, this, that)"
},
{
"docstring": "Difference operation fo... | 3 | stack_v2_sparse_classes_30k_val_000150 | Implement the Python class `ExactSetOperator` described below.
Class description:
Set operations for ExactSet. The methods below all accept an ExactMultiSet object and returning an ExactMultiSet object.
Method signatures and docstrings:
- def union(cls, this, that): Union operation for ExactSet.
- def intersection(cl... | Implement the Python class `ExactSetOperator` described below.
Class description:
Set operations for ExactSet. The methods below all accept an ExactMultiSet object and returning an ExactMultiSet object.
Method signatures and docstrings:
- def union(cls, this, that): Union operation for ExactSet.
- def intersection(cl... | 1727e9545a8f219b543c1b67da6b6653e36d931e | <|skeleton|>
class ExactSetOperator:
"""Set operations for ExactSet. The methods below all accept an ExactMultiSet object and returning an ExactMultiSet object."""
def union(cls, this, that):
"""Union operation for ExactSet."""
<|body_0|>
def intersection(cls, this, that):
"""Inter... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExactSetOperator:
"""Set operations for ExactSet. The methods below all accept an ExactMultiSet object and returning an ExactMultiSet object."""
def union(cls, this, that):
"""Union operation for ExactSet."""
if this is None:
return copy.deepcopy(that)
if that is None:... | the_stack_v2_python_sparse | src/estimators/stratified_sketch.py | world-federation-of-advertisers/cardinality_estimation_evaluation_framework | train | 21 |
9e72d71ab50682762f33ec8557006432fbb41843 | [
"self.d = collections.deque()\nself.sum = 0\nself.size = size",
"self.d.append(val)\nself.sum += val\nif len(self.d) > self.size:\n self.sum -= self.d.popleft()\nreturn self.sum / len(self.d)"
] | <|body_start_0|>
self.d = collections.deque()
self.sum = 0
self.size = size
<|end_body_0|>
<|body_start_1|>
self.d.append(val)
self.sum += val
if len(self.d) > self.size:
self.sum -= self.d.popleft()
return self.sum / len(self.d)
<|end_body_1|>
| 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.d = collections.deque()
... | stack_v2_sparse_classes_10k_train_000709 | 854 | 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_004900 | 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:
... | c27f19fac14b4acef8c631ad5569e1a5c29e9e1f | <|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.d = collections.deque()
self.sum = 0
self.size = size
def next(self, val):
""":type val: int :rtype: float"""
self.d.append(val)
self.sum += val... | the_stack_v2_python_sparse | leetcode/p0346 - Moving Average from Data Stream.py | liseyko/CtCI | train | 0 | |
649c00d62dfe4aa3e741000804b3b5daec97222a | [
"self._negate = False\nself.values = [v.strip() for v in value.split() if v.strip() != '']\nself._policy_files = policy_files\nself._ignoremissingpolicyfiles = ignoremissingpolicyfiles",
"if value.startswith('!'):\n return (value[1:], True)\nreturn (value, False)",
"current_dir = os.path.abspath(os.path.dirn... | <|body_start_0|>
self._negate = False
self.values = [v.strip() for v in value.split() if v.strip() != '']
self._policy_files = policy_files
self._ignoremissingpolicyfiles = ignoremissingpolicyfiles
<|end_body_0|>
<|body_start_1|>
if value.startswith('!'):
return (val... | A selector that selects files based on other criteria. It is similar to the Ant file selector objects in design. This one selects files based on whether the root-most Distribution.Policy.S60 file matches the given value. | DistributionPolicySelector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DistributionPolicySelector:
"""A selector that selects files based on other criteria. It is similar to the Ant file selector objects in design. This one selects files based on whether the root-most Distribution.Policy.S60 file matches the given value."""
def __init__(self, policy_files, valu... | stack_v2_sparse_classes_10k_train_000710 | 7,073 | no_license | [
{
"docstring": "Initialization.",
"name": "__init__",
"signature": "def __init__(self, policy_files, value, ignoremissingpolicyfiles=False)"
},
{
"docstring": "get value and negate it",
"name": "get_value_and_negate",
"signature": "def get_value_and_negate(self, value)"
},
{
"doc... | 3 | stack_v2_sparse_classes_30k_train_001910 | Implement the Python class `DistributionPolicySelector` described below.
Class description:
A selector that selects files based on other criteria. It is similar to the Ant file selector objects in design. This one selects files based on whether the root-most Distribution.Policy.S60 file matches the given value.
Metho... | Implement the Python class `DistributionPolicySelector` described below.
Class description:
A selector that selects files based on other criteria. It is similar to the Ant file selector objects in design. This one selects files based on whether the root-most Distribution.Policy.S60 file matches the given value.
Metho... | f458a4ce83f74d603362fe6b71eaa647ccc62fee | <|skeleton|>
class DistributionPolicySelector:
"""A selector that selects files based on other criteria. It is similar to the Ant file selector objects in design. This one selects files based on whether the root-most Distribution.Policy.S60 file matches the given value."""
def __init__(self, policy_files, valu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DistributionPolicySelector:
"""A selector that selects files based on other criteria. It is similar to the Ant file selector objects in design. This one selects files based on whether the root-most Distribution.Policy.S60 file matches the given value."""
def __init__(self, policy_files, value, ignoremiss... | the_stack_v2_python_sparse | buildframework/helium/sf/python/pythoncore/lib/archive/selectors.py | anagovitsyn/oss.FCL.sftools.dev.build | train | 0 |
5dbcada26174abe15d3fab2e2fa678c1c8888d83 | [
"super().__init__(*args, **kwargs)\nself.data_type = data_type\nself.processor = processor or (lambda x: x)\nself.allow_fallback = allow_fallback",
"if isinstance(value, self.data_type):\n return self.processor(value)\ntry:\n return self.processor(self.data_type(value))\nexcept ValueError:\n if not self.... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.data_type = data_type
self.processor = processor or (lambda x: x)
self.allow_fallback = allow_fallback
<|end_body_0|>
<|body_start_1|>
if isinstance(value, self.data_type):
return self.processor(value)
t... | Basic property to handle int, Decimal and other basic types. | Basic | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Basic:
"""Basic property to handle int, Decimal and other basic types."""
def __init__(self, *args: str, data_type: typing.Type, processor: typing.Optional[typing.Callable[[T], T]]=None, allow_fallback: bool=False, **kwargs):
"""Init method."""
<|body_0|>
def handle(self... | stack_v2_sparse_classes_10k_train_000711 | 4,580 | permissive | [
{
"docstring": "Init method.",
"name": "__init__",
"signature": "def __init__(self, *args: str, data_type: typing.Type, processor: typing.Optional[typing.Callable[[T], T]]=None, allow_fallback: bool=False, **kwargs)"
},
{
"docstring": "Handle value.",
"name": "handle",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_003274 | Implement the Python class `Basic` described below.
Class description:
Basic property to handle int, Decimal and other basic types.
Method signatures and docstrings:
- def __init__(self, *args: str, data_type: typing.Type, processor: typing.Optional[typing.Callable[[T], T]]=None, allow_fallback: bool=False, **kwargs)... | Implement the Python class `Basic` described below.
Class description:
Basic property to handle int, Decimal and other basic types.
Method signatures and docstrings:
- def __init__(self, *args: str, data_type: typing.Type, processor: typing.Optional[typing.Callable[[T], T]]=None, allow_fallback: bool=False, **kwargs)... | 00909d2c47d158bfeac300e1d7477c4f87c52096 | <|skeleton|>
class Basic:
"""Basic property to handle int, Decimal and other basic types."""
def __init__(self, *args: str, data_type: typing.Type, processor: typing.Optional[typing.Callable[[T], T]]=None, allow_fallback: bool=False, **kwargs):
"""Init method."""
<|body_0|>
def handle(self... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Basic:
"""Basic property to handle int, Decimal and other basic types."""
def __init__(self, *args: str, data_type: typing.Type, processor: typing.Optional[typing.Callable[[T], T]]=None, allow_fallback: bool=False, **kwargs):
"""Init method."""
super().__init__(*args, **kwargs)
se... | the_stack_v2_python_sparse | knowit/properties/general.py | ratoaq2/knowit | train | 27 |
0d15a41e684c9ef3b962b106f147bbdf02c38bd6 | [
"prev = None\ncur = head\nwhile cur:\n tmp = cur.next\n cur.next = prev\n prev = cur\n cur = tmp\nreturn prev",
"fast = slow = head\nwhile fast and fast.next:\n slow = slow.next\n fast = fast.next.next\nslow = self.reverseList(slow)\ncur = head\nslow_cur = slow\nwhile slow_cur:\n if slow_cur.... | <|body_start_0|>
prev = None
cur = head
while cur:
tmp = cur.next
cur.next = prev
prev = cur
cur = tmp
return prev
<|end_body_0|>
<|body_start_1|>
fast = slow = head
while fast and fast.next:
slow = slow.next
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reorderList(self, head):
""":type head: ListNode :rtype: void Do not return anything, modify head in-place instead."""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_10k_train_000712 | 1,163 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList",
"signature": "def reverseList(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: void Do not return anything, modify head in-place instead.",
"name": "reorderList",
"signature": "def reorderList(self... | 2 | stack_v2_sparse_classes_30k_train_002670 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def reorderList(self, head): :type head: ListNode :rtype: void Do not return anything, modify head in-place i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def reorderList(self, head): :type head: ListNode :rtype: void Do not return anything, modify head in-place i... | 9bd2d706f014ce84356ba38fc7801da0285a91d3 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reorderList(self, head):
""":type head: ListNode :rtype: void Do not return anything, modify head in-place instead."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
prev = None
cur = head
while cur:
tmp = cur.next
cur.next = prev
prev = cur
cur = tmp
return prev
def reorderList(self, head):
... | the_stack_v2_python_sparse | leetcode/reorderList-143.py | pittcat/Algorithm_Practice | train | 0 | |
4d078befe570d6124c37f52c6aed5d2cc561fab6 | [
"wordsets = set(words)\nfor word in words:\n for i in range(1, len(word) + 1):\n if word[i:] in wordsets:\n wordsets.remove(word[i:])\nLens = sum([len(word) + 1 for word in wordsets])\nreturn Lens",
"root = TrieNode(0)\nfor word in words:\n node = root\n for w in word[::-1]:\n if... | <|body_start_0|>
wordsets = set(words)
for word in words:
for i in range(1, len(word) + 1):
if word[i:] in wordsets:
wordsets.remove(word[i:])
Lens = sum([len(word) + 1 for word in wordsets])
return Lens
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minimumLengthEncoding(self, words) -> int:
"""查找，没有后缀的单词 :param list[str] words: :return:"""
<|body_0|>
def minimumLengthEncoding2(self, words) -> int:
"""字典树，Trie :param list[str] words: :return:"""
<|body_1|>
def minimumLengthEncoding3(se... | stack_v2_sparse_classes_10k_train_000713 | 3,061 | no_license | [
{
"docstring": "查找，没有后缀的单词 :param list[str] words: :return:",
"name": "minimumLengthEncoding",
"signature": "def minimumLengthEncoding(self, words) -> int"
},
{
"docstring": "字典树，Trie :param list[str] words: :return:",
"name": "minimumLengthEncoding2",
"signature": "def minimumLengthEnco... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumLengthEncoding(self, words) -> int: 查找，没有后缀的单词 :param list[str] words: :return:
- def minimumLengthEncoding2(self, words) -> int: 字典树，Trie :param list[str] words: :ret... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumLengthEncoding(self, words) -> int: 查找，没有后缀的单词 :param list[str] words: :return:
- def minimumLengthEncoding2(self, words) -> int: 字典树，Trie :param list[str] words: :ret... | 837957ea22aa07ce28a6c23ea0419bd2011e1f88 | <|skeleton|>
class Solution:
def minimumLengthEncoding(self, words) -> int:
"""查找，没有后缀的单词 :param list[str] words: :return:"""
<|body_0|>
def minimumLengthEncoding2(self, words) -> int:
"""字典树，Trie :param list[str] words: :return:"""
<|body_1|>
def minimumLengthEncoding3(se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def minimumLengthEncoding(self, words) -> int:
"""查找，没有后缀的单词 :param list[str] words: :return:"""
wordsets = set(words)
for word in words:
for i in range(1, len(word) + 1):
if word[i:] in wordsets:
wordsets.remove(word[i:])
... | the_stack_v2_python_sparse | 华为题库/单词压缩编码.py | 2226171237/Algorithmpractice | train | 0 | |
b00f119c871ab01134e58d807bf7c121968b0076 | [
"parser = MagicCommandParser(prog='compress', description='display the content of a repository (GIT or SVN)')\nparser.add_argument('dest', type=str, help='destination, the extension defines the compression format, zip, gzip 7z')\nparser.add_argument('files', type=str, nargs='?', help='files to compress or a python ... | <|body_start_0|>
parser = MagicCommandParser(prog='compress', description='display the content of a repository (GIT or SVN)')
parser.add_argument('dest', type=str, help='destination, the extension defines the compression format, zip, gzip 7z')
parser.add_argument('files', type=str, nargs='?', he... | Defines magic commands to compress files. | MagicCompress | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MagicCompress:
"""Defines magic commands to compress files."""
def compress_parser():
"""defines the way to parse the magic command ``%compress``"""
<|body_0|>
def compress(self, line):
""".. nbref:: :title: %compress It compresses a list of files, it returns the... | stack_v2_sparse_classes_10k_train_000714 | 2,650 | permissive | [
{
"docstring": "defines the way to parse the magic command ``%compress``",
"name": "compress_parser",
"signature": "def compress_parser()"
},
{
"docstring": ".. nbref:: :title: %compress It compresses a list of files, it returns the number of compressed files:: from pyquickhelper import zip_file... | 2 | null | Implement the Python class `MagicCompress` described below.
Class description:
Defines magic commands to compress files.
Method signatures and docstrings:
- def compress_parser(): defines the way to parse the magic command ``%compress``
- def compress(self, line): .. nbref:: :title: %compress It compresses a list of ... | Implement the Python class `MagicCompress` described below.
Class description:
Defines magic commands to compress files.
Method signatures and docstrings:
- def compress_parser(): defines the way to parse the magic command ``%compress``
- def compress(self, line): .. nbref:: :title: %compress It compresses a list of ... | 860ec5b9a53bae4fc616076c0b52dbe2a1153d30 | <|skeleton|>
class MagicCompress:
"""Defines magic commands to compress files."""
def compress_parser():
"""defines the way to parse the magic command ``%compress``"""
<|body_0|>
def compress(self, line):
""".. nbref:: :title: %compress It compresses a list of files, it returns the... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MagicCompress:
"""Defines magic commands to compress files."""
def compress_parser():
"""defines the way to parse the magic command ``%compress``"""
parser = MagicCommandParser(prog='compress', description='display the content of a repository (GIT or SVN)')
parser.add_argument('de... | the_stack_v2_python_sparse | src/pyquickhelper/ipythonhelper/magic_class_compress.py | Pandinosaurus/pyquickhelper | train | 0 |
0d9d0fcb29341f051b4b31640a98976da53f2422 | [
"for id, op in vars(cls).items():\n if isinstance(op, IOperation) and op.is_valid(operator, left, right):\n if isinstance(op, BinaryOperation):\n return op.build(left, right)\n else:\n from boa3.model.type.type import Type\n operand = right if left is Type.none else... | <|body_start_0|>
for id, op in vars(cls).items():
if isinstance(op, IOperation) and op.is_valid(operator, left, right):
if isinstance(op, BinaryOperation):
return op.build(left, right)
else:
from boa3.model.type.type import Type... | BinaryOp | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryOp:
def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]:
"""Gets a binary operation given the operator and the operands types. :param operator: binary operator :param left: type of the left operand :param right: type of the right opera... | stack_v2_sparse_classes_10k_train_000715 | 4,052 | permissive | [
{
"docstring": "Gets a binary operation given the operator and the operands types. :param operator: binary operator :param left: type of the left operand :param right: type of the right operand :return: The operation if exists. None otherwise; :rtype: BinaryOperation or None",
"name": "validate_type",
"... | 3 | stack_v2_sparse_classes_30k_train_006494 | Implement the Python class `BinaryOp` described below.
Class description:
Implement the BinaryOp class.
Method signatures and docstrings:
- def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]: Gets a binary operation given the operator and the operands types. :param oper... | Implement the Python class `BinaryOp` described below.
Class description:
Implement the BinaryOp class.
Method signatures and docstrings:
- def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]: Gets a binary operation given the operator and the operands types. :param oper... | e4ef340744b5bd25ade26f847eac50789b97f3e9 | <|skeleton|>
class BinaryOp:
def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]:
"""Gets a binary operation given the operator and the operands types. :param operator: binary operator :param left: type of the left operand :param right: type of the right opera... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BinaryOp:
def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]:
"""Gets a binary operation given the operator and the operands types. :param operator: binary operator :param left: type of the left operand :param right: type of the right operand :return: Th... | the_stack_v2_python_sparse | boa3/model/operation/binaryop.py | DanPopa46/neo3-boa | train | 0 | |
1c7371fa786f45b30039391075b7c6b4a990bdf8 | [
"self.prefix = list(w)\nfor i in range(1, len(w)):\n self.prefix[i] = self.prefix[i - 1] + w[i]",
"target = random.randint(0, self.prefix[-1] - 1)\nleft, right = (0, len(self.prefix) - 1)\nwhile left < right:\n mid = left + (right - left) // 2\n if self.prefix[mid] <= target:\n left = mid + 1\n ... | <|body_start_0|>
self.prefix = list(w)
for i in range(1, len(w)):
self.prefix[i] = self.prefix[i - 1] + w[i]
<|end_body_0|>
<|body_start_1|>
target = random.randint(0, self.prefix[-1] - 1)
left, right = (0, len(self.prefix) - 1)
while left < right:
mid = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.prefix = list(w)
for i in range(1, len(w)):
self.prefix[i] = self.prefi... | stack_v2_sparse_classes_10k_train_000716 | 841 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | 5b14b6f42baf59b04cbcc8e115df4272029b64c8 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.prefix = list(w)
for i in range(1, len(w)):
self.prefix[i] = self.prefix[i - 1] + w[i]
def pickIndex(self):
""":rtype: int"""
target = random.randint(0, self.prefix[-1] - 1)
left, ri... | the_stack_v2_python_sparse | LeetCode/0528.Random-Pick-With-Weight/Random-Pick-With-Weight.py | htingwang/HandsOnAlgoDS | train | 12 | |
5a9daab4114da3539b8233b71115e085b5a9a4fe | [
"paginated = Paginator(models.SiteInvite.objects.filter(user=request.user).order_by('-created_date'), PAGE_LENGTH)\npage = paginated.get_page(request.GET.get('page'))\ndata = {'invites': page, 'page_range': paginated.get_elided_page_range(page.number, on_each_side=2, on_ends=1), 'form': forms.CreateInviteForm()}\nr... | <|body_start_0|>
paginated = Paginator(models.SiteInvite.objects.filter(user=request.user).order_by('-created_date'), PAGE_LENGTH)
page = paginated.get_page(request.GET.get('page'))
data = {'invites': page, 'page_range': paginated.get_elided_page_range(page.number, on_each_side=2, on_ends=1), 'f... | create invites | ManageInvites | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageInvites:
"""create invites"""
def get(self, request):
"""invite management page"""
<|body_0|>
def post(self, request):
"""creates an invite database entry"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
paginated = Paginator(models.SiteInv... | stack_v2_sparse_classes_10k_train_000717 | 6,414 | no_license | [
{
"docstring": "invite management page",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "creates an invite database entry",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | null | Implement the Python class `ManageInvites` described below.
Class description:
create invites
Method signatures and docstrings:
- def get(self, request): invite management page
- def post(self, request): creates an invite database entry | Implement the Python class `ManageInvites` described below.
Class description:
create invites
Method signatures and docstrings:
- def get(self, request): invite management page
- def post(self, request): creates an invite database entry
<|skeleton|>
class ManageInvites:
"""create invites"""
def get(self, re... | 0f8da5b738047f3c34d60d93f59bdedd8f797224 | <|skeleton|>
class ManageInvites:
"""create invites"""
def get(self, request):
"""invite management page"""
<|body_0|>
def post(self, request):
"""creates an invite database entry"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ManageInvites:
"""create invites"""
def get(self, request):
"""invite management page"""
paginated = Paginator(models.SiteInvite.objects.filter(user=request.user).order_by('-created_date'), PAGE_LENGTH)
page = paginated.get_page(request.GET.get('page'))
data = {'invites': ... | the_stack_v2_python_sparse | bookwyrm/views/admin/invite.py | bookwyrm-social/bookwyrm | train | 1,398 |
e5e327f31990ba02267e9b8dffa25f2fe1269096 | [
"self.name = name\nself.owner = owner\nself.tag = tag\nself.state = state\nself.countr = countr",
"if self.tag is not None:\n query = '\\n { repository(name: \"%s\", owner: \"%s\") {\\n pullRequests(states: %s, last: %i, orderBy: {field: CREATED_AT, direction: ASC},labels:\"... | <|body_start_0|>
self.name = name
self.owner = owner
self.tag = tag
self.state = state
self.countr = countr
<|end_body_0|>
<|body_start_1|>
if self.tag is not None:
query = '\n { repository(name: "%s", owner: "%s") {\n pull... | The Queries class defines an object that represents a pull request query | Queries | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Queries:
"""The Queries class defines an object that represents a pull request query"""
def __init__(self, owner, name, state, tag=None, countr=30):
"""initialize query object with state, name, owner, tag and counter."""
<|body_0|>
def pulls(self):
"""this functi... | stack_v2_sparse_classes_10k_train_000718 | 2,463 | permissive | [
{
"docstring": "initialize query object with state, name, owner, tag and counter.",
"name": "__init__",
"signature": "def __init__(self, owner, name, state, tag=None, countr=30)"
},
{
"docstring": "this function returns pull request query",
"name": "pulls",
"signature": "def pulls(self)"... | 2 | null | Implement the Python class `Queries` described below.
Class description:
The Queries class defines an object that represents a pull request query
Method signatures and docstrings:
- def __init__(self, owner, name, state, tag=None, countr=30): initialize query object with state, name, owner, tag and counter.
- def pul... | Implement the Python class `Queries` described below.
Class description:
The Queries class defines an object that represents a pull request query
Method signatures and docstrings:
- def __init__(self, owner, name, state, tag=None, countr=30): initialize query object with state, name, owner, tag and counter.
- def pul... | 31fd3fb1233f39ea2252a7a44160ff8a2140f7bd | <|skeleton|>
class Queries:
"""The Queries class defines an object that represents a pull request query"""
def __init__(self, owner, name, state, tag=None, countr=30):
"""initialize query object with state, name, owner, tag and counter."""
<|body_0|>
def pulls(self):
"""this functi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Queries:
"""The Queries class defines an object that represents a pull request query"""
def __init__(self, owner, name, state, tag=None, countr=30):
"""initialize query object with state, name, owner, tag and counter."""
self.name = name
self.owner = owner
self.tag = tag
... | the_stack_v2_python_sparse | Python/PR_Workflow/src/graphqlapi.py | HarshCasper/Rotten-Scripts | train | 1,474 |
8b085fff21261152e2cd43b3d0704ed56eb23550 | [
"blackTypeDict = self.getDictBykey(self.__getBlacklistConfig().json(), 'name', blackType)\nself.url = '/mgr/park/parkBlacklist/save.do'\ndata = {'specialCarTypeConfigId': blackTypeDict['id'], 'carLicenseNumber': carNum, 'owner': 'apipytest', 'reason': 'pytest', 'remark1': 'pytest', 'blacklistForeverFlag': 'CLOSE', ... | <|body_start_0|>
blackTypeDict = self.getDictBykey(self.__getBlacklistConfig().json(), 'name', blackType)
self.url = '/mgr/park/parkBlacklist/save.do'
data = {'specialCarTypeConfigId': blackTypeDict['id'], 'carLicenseNumber': carNum, 'owner': 'apipytest', 'reason': 'pytest', 'remark1': 'pytest',... | 黑名单录入 | ParkBlacklist | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParkBlacklist:
"""黑名单录入"""
def addBlacklist(self, blackType, carNum):
"""新建黑名单车辆"""
<|body_0|>
def __getBlacklistConfig(self):
"""获取黑名单配置"""
<|body_1|>
def delBlacklist(self, parkName, carNum):
"""删除黑名单"""
<|body_2|>
def getBlack... | stack_v2_sparse_classes_10k_train_000719 | 13,467 | no_license | [
{
"docstring": "新建黑名单车辆",
"name": "addBlacklist",
"signature": "def addBlacklist(self, blackType, carNum)"
},
{
"docstring": "获取黑名单配置",
"name": "__getBlacklistConfig",
"signature": "def __getBlacklistConfig(self)"
},
{
"docstring": "删除黑名单",
"name": "delBlacklist",
"signat... | 4 | stack_v2_sparse_classes_30k_train_002272 | Implement the Python class `ParkBlacklist` described below.
Class description:
黑名单录入
Method signatures and docstrings:
- def addBlacklist(self, blackType, carNum): 新建黑名单车辆
- def __getBlacklistConfig(self): 获取黑名单配置
- def delBlacklist(self, parkName, carNum): 删除黑名单
- def getBlacklist(self, parkName): 获取黑名单列表 | Implement the Python class `ParkBlacklist` described below.
Class description:
黑名单录入
Method signatures and docstrings:
- def addBlacklist(self, blackType, carNum): 新建黑名单车辆
- def __getBlacklistConfig(self): 获取黑名单配置
- def delBlacklist(self, parkName, carNum): 删除黑名单
- def getBlacklist(self, parkName): 获取黑名单列表
<|skeleto... | 34c368c109867da26d9256bca85f872b0fac2ea7 | <|skeleton|>
class ParkBlacklist:
"""黑名单录入"""
def addBlacklist(self, blackType, carNum):
"""新建黑名单车辆"""
<|body_0|>
def __getBlacklistConfig(self):
"""获取黑名单配置"""
<|body_1|>
def delBlacklist(self, parkName, carNum):
"""删除黑名单"""
<|body_2|>
def getBlack... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ParkBlacklist:
"""黑名单录入"""
def addBlacklist(self, blackType, carNum):
"""新建黑名单车辆"""
blackTypeDict = self.getDictBykey(self.__getBlacklistConfig().json(), 'name', blackType)
self.url = '/mgr/park/parkBlacklist/save.do'
data = {'specialCarTypeConfigId': blackTypeDict['id'], ... | the_stack_v2_python_sparse | Api/parkingManage_service/carTypeManage_service/carTypeConfig.py | oyebino/pomp_api | train | 1 |
aff8e4a8bc7571ae75464bb5a38286570ff77ea2 | [
"super().__init__()\nself.encoder = Encoder(N, dm, h, hidden, input_vocab, max_seq_input, drop_rate)\nself.decoder = Decoder(N, dm, h, hidden, target_vocab, max_seq_target, drop_rate)\nself.linear = tf.keras.layers.Dense(target_vocab)",
"enc_output = self.encoder(inputs, training, encoder_mask)\ndec_output = self... | <|body_start_0|>
super().__init__()
self.encoder = Encoder(N, dm, h, hidden, input_vocab, max_seq_input, drop_rate)
self.decoder = Decoder(N, dm, h, hidden, target_vocab, max_seq_target, drop_rate)
self.linear = tf.keras.layers.Dense(target_vocab)
<|end_body_0|>
<|body_start_1|>
... | class Transform | Transformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transformer:
"""class Transform"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""Sets the following public instance attributes: * encoder - the encoder layer * decoder - the decoder layer * linear - a final Dense lay... | stack_v2_sparse_classes_10k_train_000720 | 1,535 | no_license | [
{
"docstring": "Sets the following public instance attributes: * encoder - the encoder layer * decoder - the decoder layer * linear - a final Dense layer with target_vocab units",
"name": "__init__",
"signature": "def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_tar... | 2 | stack_v2_sparse_classes_30k_train_003720 | Implement the Python class `Transformer` described below.
Class description:
class Transform
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1): Sets the following public instance attributes: * encoder - the encoder layer *... | Implement the Python class `Transformer` described below.
Class description:
class Transform
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1): Sets the following public instance attributes: * encoder - the encoder layer *... | 9ff78818c132d1233c11b8fc8fd469878b23b14e | <|skeleton|>
class Transformer:
"""class Transform"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""Sets the following public instance attributes: * encoder - the encoder layer * decoder - the decoder layer * linear - a final Dense lay... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Transformer:
"""class Transform"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""Sets the following public instance attributes: * encoder - the encoder layer * decoder - the decoder layer * linear - a final Dense layer with targe... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/11-transformer.py | Nzparra/holbertonschool-machine_learning | train | 0 |
8417dc42f77c4855434f754f63be1bfa4d47bf15 | [
"super().__init__()\nlogger.debug('Create PaddleTextConnectionHandler to process the text request')\nself.text_engine = text_engine\nself.task = self.text_engine.executor.task\nself.model = self.text_engine.executor.model\nself.tokenizer = self.text_engine.executor.tokenizer\nself._punc_list = self.text_engine.exec... | <|body_start_0|>
super().__init__()
logger.debug('Create PaddleTextConnectionHandler to process the text request')
self.text_engine = text_engine
self.task = self.text_engine.executor.task
self.model = self.text_engine.executor.model
self.tokenizer = self.text_engine.exec... | PaddleTextConnectionHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PaddleTextConnectionHandler:
def __init__(self, text_engine):
"""The PaddleSpeech Text Server Connection Handler This connection process every server request Args: text_engine (TextEngine): The Text engine"""
<|body_0|>
def run(self, text):
"""The connection process ... | stack_v2_sparse_classes_10k_train_000721 | 6,419 | permissive | [
{
"docstring": "The PaddleSpeech Text Server Connection Handler This connection process every server request Args: text_engine (TextEngine): The Text engine",
"name": "__init__",
"signature": "def __init__(self, text_engine)"
},
{
"docstring": "The connection process the request text Args: text ... | 5 | null | Implement the Python class `PaddleTextConnectionHandler` described below.
Class description:
Implement the PaddleTextConnectionHandler class.
Method signatures and docstrings:
- def __init__(self, text_engine): The PaddleSpeech Text Server Connection Handler This connection process every server request Args: text_eng... | Implement the Python class `PaddleTextConnectionHandler` described below.
Class description:
Implement the PaddleTextConnectionHandler class.
Method signatures and docstrings:
- def __init__(self, text_engine): The PaddleSpeech Text Server Connection Handler This connection process every server request Args: text_eng... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class PaddleTextConnectionHandler:
def __init__(self, text_engine):
"""The PaddleSpeech Text Server Connection Handler This connection process every server request Args: text_engine (TextEngine): The Text engine"""
<|body_0|>
def run(self, text):
"""The connection process ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PaddleTextConnectionHandler:
def __init__(self, text_engine):
"""The PaddleSpeech Text Server Connection Handler This connection process every server request Args: text_engine (TextEngine): The Text engine"""
super().__init__()
logger.debug('Create PaddleTextConnectionHandler to proces... | the_stack_v2_python_sparse | paddlespeech/server/engine/text/python/text_engine.py | anniyanvr/DeepSpeech-1 | train | 0 | |
5e03adcad67aef73b6801d5bf8aad51652f4b4eb | [
"bin1, bin2, w2 = self._calc_bin(logits, target)\nw1 = 1 - w2\nnlp = -F.log_softmax(logits, dim=-1)\nB = _get_indexer(logits.shape[:-1])\nloss = w1 * nlp[B + (bin1,)] + w2 * nlp[B + (bin2,)]\nneg_entropy = w1.xlogy(w1) + w2.xlogy(w2)\nreturn (loss + neg_entropy).relu()",
"support = self._calc_support(logits.shape... | <|body_start_0|>
bin1, bin2, w2 = self._calc_bin(logits, target)
w1 = 1 - w2
nlp = -F.log_softmax(logits, dim=-1)
B = _get_indexer(logits.shape[:-1])
loss = w1 * nlp[B + (bin1,)] + w2 * nlp[B + (bin2,)]
neg_entropy = w1.xlogy(w1) + w2.xlogy(w2)
return (loss + neg_... | A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being one of the ``n`` values. If a target value y is not an integer, it is treated as having prabability mass of :math:... | DiscreteRegressionLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiscreteRegressionLoss:
"""A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being one of the ``n`` values. If a target value y is not an integer, ... | stack_v2_sparse_classes_10k_train_000722 | 31,133 | permissive | [
{
"docstring": "Caculate the loss. Args: logits: shape is [B, n] target: the shape is [B] Returns: loss with the same shape as target",
"name": "__call__",
"signature": "def __call__(self, logits: torch.Tensor, target: torch.Tensor)"
},
{
"docstring": "Calculate the expected predition in the unt... | 3 | stack_v2_sparse_classes_30k_train_000082 | Implement the Python class `DiscreteRegressionLoss` described below.
Class description:
A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being one of the ``n`` values. ... | Implement the Python class `DiscreteRegressionLoss` described below.
Class description:
A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being one of the ``n`` values. ... | b00ff2fa5e660de31020338ba340263183fbeaa4 | <|skeleton|>
class DiscreteRegressionLoss:
"""A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being one of the ``n`` values. If a target value y is not an integer, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DiscreteRegressionLoss:
"""A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being one of the ``n`` values. If a target value y is not an integer, it is treated... | the_stack_v2_python_sparse | alf/utils/losses.py | HorizonRobotics/alf | train | 288 |
a8c90bd1f109a271af58a5767da9b95bbcf07318 | [
"super(SharedAdam, self).__init__(params, lr=lr, betas=betas, eps=eps, weight_decay=weight_decay, amsgrad=amsgrad)\nfor group in self.param_groups:\n for p in group['params']:\n state = self.state[p]\n state['step'] = 0\n state['shared_step'] = torch.zeros(1).share_memory_()\n state['... | <|body_start_0|>
super(SharedAdam, self).__init__(params, lr=lr, betas=betas, eps=eps, weight_decay=weight_decay, amsgrad=amsgrad)
for group in self.param_groups:
for p in group['params']:
state = self.state[p]
state['step'] = 0
state['shared_s... | SharedAdam | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SharedAdam:
def __init__(self, params, lr=0.001, betas=(0.9, 0.999), eps=1e-08, weight_decay=0, amsgrad=False):
"""arguments are all default arguments of torch.optim.Adam. Params are weights of neural network. Betas are coefficients for gradient averages, eps is numerical stability term ... | stack_v2_sparse_classes_10k_train_000723 | 23,572 | no_license | [
{
"docstring": "arguments are all default arguments of torch.optim.Adam. Params are weights of neural network. Betas are coefficients for gradient averages, eps is numerical stability term to denominator, weight_decay is L2 penalty, and amsgrad is boolean weather to use AMSGrad. Adam is subclass of torch.optim.... | 2 | stack_v2_sparse_classes_30k_train_005961 | Implement the Python class `SharedAdam` described below.
Class description:
Implement the SharedAdam class.
Method signatures and docstrings:
- def __init__(self, params, lr=0.001, betas=(0.9, 0.999), eps=1e-08, weight_decay=0, amsgrad=False): arguments are all default arguments of torch.optim.Adam. Params are weight... | Implement the Python class `SharedAdam` described below.
Class description:
Implement the SharedAdam class.
Method signatures and docstrings:
- def __init__(self, params, lr=0.001, betas=(0.9, 0.999), eps=1e-08, weight_decay=0, amsgrad=False): arguments are all default arguments of torch.optim.Adam. Params are weight... | 6f38cfd121c504e78ecd4b7762e86f4825bb596d | <|skeleton|>
class SharedAdam:
def __init__(self, params, lr=0.001, betas=(0.9, 0.999), eps=1e-08, weight_decay=0, amsgrad=False):
"""arguments are all default arguments of torch.optim.Adam. Params are weights of neural network. Betas are coefficients for gradient averages, eps is numerical stability term ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SharedAdam:
def __init__(self, params, lr=0.001, betas=(0.9, 0.999), eps=1e-08, weight_decay=0, amsgrad=False):
"""arguments are all default arguments of torch.optim.Adam. Params are weights of neural network. Betas are coefficients for gradient averages, eps is numerical stability term to denominator... | the_stack_v2_python_sparse | algorithm/a3c_breakout.py | corot/reinforcement-learning | train | 0 | |
bbb127e8589cb421126a51c11224c730e89465e3 | [
"try:\n return Gateway.objects.get(reservoir=self, task=task)\nexcept Gateway.DoesNotExist:\n return None",
"gateway = self.get_gateway(task)\nif gateway and gateway.pipe:\n return gateway.pipe\nelse:\n return None"
] | <|body_start_0|>
try:
return Gateway.objects.get(reservoir=self, task=task)
except Gateway.DoesNotExist:
return None
<|end_body_0|>
<|body_start_1|>
gateway = self.get_gateway(task)
if gateway and gateway.pipe:
return gateway.pipe
else:
... | Determines whether a platform is enabled for use. The platform corresponds to a subpackage in the Platforms package. A Reservoir's primary key is the name of the subpackage associated with the Reservoir (e.g., 'twitter'). | Reservoir | [
"MIT",
"LicenseRef-scancode-proprietary-license",
"GPL-3.0-only",
"LicenseRef-scancode-unknown-license-reference",
"GPL-1.0-or-later",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-copyleft"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reservoir:
"""Determines whether a platform is enabled for use. The platform corresponds to a subpackage in the Platforms package. A Reservoir's primary key is the name of the subpackage associated with the Reservoir (e.g., 'twitter')."""
def get_gateway(self, task):
"""Returns the g... | stack_v2_sparse_classes_10k_train_000724 | 3,199 | permissive | [
{
"docstring": "Returns the gateway for a given task, or None if the gateway doesn't exist.",
"name": "get_gateway",
"signature": "def get_gateway(self, task)"
},
{
"docstring": "Takes the primary key (name) of a SearchTask and returns the Pipe for that task, if one exists. Otherwise, returns No... | 2 | stack_v2_sparse_classes_30k_train_005478 | Implement the Python class `Reservoir` described below.
Class description:
Determines whether a platform is enabled for use. The platform corresponds to a subpackage in the Platforms package. A Reservoir's primary key is the name of the subpackage associated with the Reservoir (e.g., 'twitter').
Method signatures and... | Implement the Python class `Reservoir` described below.
Class description:
Determines whether a platform is enabled for use. The platform corresponds to a subpackage in the Platforms package. A Reservoir's primary key is the name of the subpackage associated with the Reservoir (e.g., 'twitter').
Method signatures and... | a379a134c0c5af14df4ed2afa066c1626506b754 | <|skeleton|>
class Reservoir:
"""Determines whether a platform is enabled for use. The platform corresponds to a subpackage in the Platforms package. A Reservoir's primary key is the name of the subpackage associated with the Reservoir (e.g., 'twitter')."""
def get_gateway(self, task):
"""Returns the g... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Reservoir:
"""Determines whether a platform is enabled for use. The platform corresponds to a subpackage in the Platforms package. A Reservoir's primary key is the name of the subpackage associated with the Reservoir (e.g., 'twitter')."""
def get_gateway(self, task):
"""Returns the gateway for a ... | the_stack_v2_python_sparse | Incident-Response/Tools/cyphon/cyphon/aggregator/reservoirs/models.py | foss2cyber/Incident-Playbook | train | 1 |
e70c1d480265b0ad4ea553ce9a2f1cd0d0bd4a43 | [
"lower_bound = float('-inf')\nstack = []\nfor val in preorder:\n if val < lower_bound:\n return False\n while stack and val > stack[-1]:\n lower_bound = stack.pop()\n stack.append(val)\nreturn True",
"lower_bound = float('-inf')\ni = 0\nfor val in preorder:\n if val < lower_bound:\n ... | <|body_start_0|>
lower_bound = float('-inf')
stack = []
for val in preorder:
if val < lower_bound:
return False
while stack and val > stack[-1]:
lower_bound = stack.pop()
stack.append(val)
return True
<|end_body_0|>
<|b... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def verifyPreorder(self, preorder: List[int]) -> bool:
"""In BST, node.left.val < node.val < node.right.val, and the preorder traversal will visit left child all the way to the leaf before visiting any right child. This traversal order will reflect in the preorder array as a de... | stack_v2_sparse_classes_10k_train_000725 | 2,035 | no_license | [
{
"docstring": "In BST, node.left.val < node.val < node.right.val, and the preorder traversal will visit left child all the way to the leaf before visiting any right child. This traversal order will reflect in the preorder array as a decreasing val subseq. If we see a val that's greater than its preceeding val ... | 2 | stack_v2_sparse_classes_30k_train_006300 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def verifyPreorder(self, preorder: List[int]) -> bool: In BST, node.left.val < node.val < node.right.val, and the preorder traversal will visit left child all the way to the leaf... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def verifyPreorder(self, preorder: List[int]) -> bool: In BST, node.left.val < node.val < node.right.val, and the preorder traversal will visit left child all the way to the leaf... | 6ff1941ff213a843013100ac7033e2d4f90fbd6a | <|skeleton|>
class Solution:
def verifyPreorder(self, preorder: List[int]) -> bool:
"""In BST, node.left.val < node.val < node.right.val, and the preorder traversal will visit left child all the way to the leaf before visiting any right child. This traversal order will reflect in the preorder array as a de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def verifyPreorder(self, preorder: List[int]) -> bool:
"""In BST, node.left.val < node.val < node.right.val, and the preorder traversal will visit left child all the way to the leaf before visiting any right child. This traversal order will reflect in the preorder array as a decreasing val s... | the_stack_v2_python_sparse | Leetcode 0255. Verify Preorder Sequence in Binary Search Tree.py | Chaoran-sjsu/leetcode | train | 0 | |
e1d712db8bdc8619ba3de8b15c107fd1ec058cc1 | [
"super().__init__()\nself.W = tf.keras.layers.Dense(units=units)\nself.U = tf.keras.layers.Dense(units=units)\nself.V = tf.keras.layers.Dense(units=1)",
"s_expanded = tf.expand_dims(input=s_prev, axis=1)\nfirst = self.W(s_expanded)\nsecond = self.U(hidden_states)\nscore = self.V(tf.nn.tanh(first + second))\natten... | <|body_start_0|>
super().__init__()
self.W = tf.keras.layers.Dense(units=units)
self.U = tf.keras.layers.Dense(units=units)
self.V = tf.keras.layers.Dense(units=1)
<|end_body_0|>
<|body_start_1|>
s_expanded = tf.expand_dims(input=s_prev, axis=1)
first = self.W(s_expanded... | class SelfAttention | SelfAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAttention:
"""class SelfAttention"""
def __init__(self, units):
"""* units is an integer representing the number of hidden units in the alignment model * Sets the following public instance attributes: * W - a Dense layer with units units, to be applied to the previous decoder hid... | stack_v2_sparse_classes_10k_train_000726 | 1,978 | no_license | [
{
"docstring": "* units is an integer representing the number of hidden units in the alignment model * Sets the following public instance attributes: * W - a Dense layer with units units, to be applied to the previous decoder hidden state * U - a Dense layer with units units, to be applied to the encoder hidden... | 2 | stack_v2_sparse_classes_30k_train_003294 | Implement the Python class `SelfAttention` described below.
Class description:
class SelfAttention
Method signatures and docstrings:
- def __init__(self, units): * units is an integer representing the number of hidden units in the alignment model * Sets the following public instance attributes: * W - a Dense layer wi... | Implement the Python class `SelfAttention` described below.
Class description:
class SelfAttention
Method signatures and docstrings:
- def __init__(self, units): * units is an integer representing the number of hidden units in the alignment model * Sets the following public instance attributes: * W - a Dense layer wi... | 8ad4c2594ff78b345dbd92e9d54d2a143ac4071a | <|skeleton|>
class SelfAttention:
"""class SelfAttention"""
def __init__(self, units):
"""* units is an integer representing the number of hidden units in the alignment model * Sets the following public instance attributes: * W - a Dense layer with units units, to be applied to the previous decoder hid... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SelfAttention:
"""class SelfAttention"""
def __init__(self, units):
"""* units is an integer representing the number of hidden units in the alignment model * Sets the following public instance attributes: * W - a Dense layer with units units, to be applied to the previous decoder hidden state * U... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/1-self_attention.py | jorgezafra94/holbertonschool-machine_learning | train | 1 |
662423ab416d826e04f11ca0e33e718f6e0c9e1a | [
"self.sum = w[0:]\nif len(w) <= 0:\n return\nfor i in range(1, len(w)):\n self.sum[i] = self.sum[i - 1] + w[i]\nprint(self.sum)",
"import numpy as np\nrnd = np.random.randint(0, self.sum[-1])\nlow = 0\nhigh = len(self.sum) - 1\nwhile low < high:\n mid = low + (high - low) / 2\n if self.sum[mid] <= rnd... | <|body_start_0|>
self.sum = w[0:]
if len(w) <= 0:
return
for i in range(1, len(w)):
self.sum[i] = self.sum[i - 1] + w[i]
print(self.sum)
<|end_body_0|>
<|body_start_1|>
import numpy as np
rnd = np.random.randint(0, self.sum[-1])
low = 0
... | Solution1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.sum = w[0:]
if len(w) <= 0:
return
for i in range(1, len(w)):
... | stack_v2_sparse_classes_10k_train_000727 | 1,927 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | null | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution1:
def __init__(self, w):
""":type w: List[int]"""
... | 176cc1db3291843fb068f06d0180766dd8c3122c | <|skeleton|>
class Solution1:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution1:
def __init__(self, w):
""":type w: List[int]"""
self.sum = w[0:]
if len(w) <= 0:
return
for i in range(1, len(w)):
self.sum[i] = self.sum[i - 1] + w[i]
print(self.sum)
def pickIndex(self):
""":rtype: int"""
import ... | the_stack_v2_python_sparse | 2019/sampling/random_pick_with_weight_528.py | yehongyu/acode | train | 0 | |
6cbb073eefcb2371ff40183a96f348d5313c11f0 | [
"n = len(s)\ndp = [[0] * n for _ in range(n)]\nres = 0\nfor i in range(n - 1, -1, -1):\n for j in range(i, n):\n if s[i] == s[j]:\n if j - i < 3 or dp[i + 1][j - 1] == 1:\n dp[i][j] = 1\n res += 1\nreturn res",
"def helper(s, left, right):\n res = 0\n while... | <|body_start_0|>
n = len(s)
dp = [[0] * n for _ in range(n)]
res = 0
for i in range(n - 1, -1, -1):
for j in range(i, n):
if s[i] == s[j]:
if j - i < 3 or dp[i + 1][j - 1] == 1:
dp[i][j] = 1
r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countSubstrings0(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def countSubstrings(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(s)
dp = [[0] * n for _ in range(n)]
... | stack_v2_sparse_classes_10k_train_000728 | 1,490 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "countSubstrings0",
"signature": "def countSubstrings0(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "countSubstrings",
"signature": "def countSubstrings(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001400 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubstrings0(self, s): :type s: str :rtype: int
- def countSubstrings(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubstrings0(self, s): :type s: str :rtype: int
- def countSubstrings(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def countSubstrings0(self, s):... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def countSubstrings0(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def countSubstrings(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def countSubstrings0(self, s):
""":type s: str :rtype: int"""
n = len(s)
dp = [[0] * n for _ in range(n)]
res = 0
for i in range(n - 1, -1, -1):
for j in range(i, n):
if s[i] == s[j]:
if j - i < 3 or dp[i + 1][j ... | the_stack_v2_python_sparse | 剑指 Offer II 020. 回文子字符串的个数.py | yangyuxiang1996/leetcode | train | 0 | |
b7e27af93232c5796fac5c6476a8b4a654a90240 | [
"repo_ref = registry_model.lookup_repository(namespace_name, repository_name)\nif repo_ref is None:\n raise NotFound()\nmanifest = registry_model.lookup_manifest_by_digest(repo_ref, manifestref)\nif manifest is None:\n raise NotFound()\nlabel = registry_model.get_manifest_label(manifest, labelid)\nif label is... | <|body_start_0|>
repo_ref = registry_model.lookup_repository(namespace_name, repository_name)
if repo_ref is None:
raise NotFound()
manifest = registry_model.lookup_manifest_by_digest(repo_ref, manifestref)
if manifest is None:
raise NotFound()
label = reg... | Resource for managing the labels on a specific repository manifest. | ManageRepositoryManifestLabel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageRepositoryManifestLabel:
"""Resource for managing the labels on a specific repository manifest."""
def get(self, namespace_name, repository_name, manifestref, labelid):
"""Retrieves the label with the specific ID under the manifest."""
<|body_0|>
def delete(self, n... | stack_v2_sparse_classes_10k_train_000729 | 10,731 | permissive | [
{
"docstring": "Retrieves the label with the specific ID under the manifest.",
"name": "get",
"signature": "def get(self, namespace_name, repository_name, manifestref, labelid)"
},
{
"docstring": "Deletes an existing label from a manifest.",
"name": "delete",
"signature": "def delete(sel... | 2 | stack_v2_sparse_classes_30k_train_002866 | Implement the Python class `ManageRepositoryManifestLabel` described below.
Class description:
Resource for managing the labels on a specific repository manifest.
Method signatures and docstrings:
- def get(self, namespace_name, repository_name, manifestref, labelid): Retrieves the label with the specific ID under th... | Implement the Python class `ManageRepositoryManifestLabel` described below.
Class description:
Resource for managing the labels on a specific repository manifest.
Method signatures and docstrings:
- def get(self, namespace_name, repository_name, manifestref, labelid): Retrieves the label with the specific ID under th... | e400a0c22c5f89dd35d571654b13d262b1f6e3b3 | <|skeleton|>
class ManageRepositoryManifestLabel:
"""Resource for managing the labels on a specific repository manifest."""
def get(self, namespace_name, repository_name, manifestref, labelid):
"""Retrieves the label with the specific ID under the manifest."""
<|body_0|>
def delete(self, n... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ManageRepositoryManifestLabel:
"""Resource for managing the labels on a specific repository manifest."""
def get(self, namespace_name, repository_name, manifestref, labelid):
"""Retrieves the label with the specific ID under the manifest."""
repo_ref = registry_model.lookup_repository(nam... | the_stack_v2_python_sparse | endpoints/api/manifest.py | quay/quay | train | 2,363 |
c7cca67e7cc2d5a5ded317040857073e9293f2a8 | [
"maxArea = 0\nhist = []\ni = 0\nwhile i < len(heights):\n if not hist or heights[hist[-1]] <= heights[i]:\n hist.append(i)\n i += 1\n else:\n h = heights[hist.pop()]\n if not hist:\n w = i\n else:\n w = i - 1 - hist[-1]\n maxArea = max(h * w, max... | <|body_start_0|>
maxArea = 0
hist = []
i = 0
while i < len(heights):
if not hist or heights[hist[-1]] <= heights[i]:
hist.append(i)
i += 1
else:
h = heights[hist.pop()]
if not hist:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
<|body_0|>
def maximalRectangle(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
maxArea = 0
... | stack_v2_sparse_classes_10k_train_000730 | 2,261 | no_license | [
{
"docstring": ":type heights: List[int] :rtype: int",
"name": "largestRectangleArea",
"signature": "def largestRectangleArea(self, heights)"
},
{
"docstring": ":type matrix: List[List[str]] :rtype: int",
"name": "maximalRectangle",
"signature": "def maximalRectangle(self, matrix)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): :type heights: List[int] :rtype: int
- def maximalRectangle(self, matrix): :type matrix: List[List[str]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): :type heights: List[int] :rtype: int
- def maximalRectangle(self, matrix): :type matrix: List[List[str]] :rtype: int
<|skeleton|>
class ... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
<|body_0|>
def maximalRectangle(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
maxArea = 0
hist = []
i = 0
while i < len(heights):
if not hist or heights[hist[-1]] <= heights[i]:
hist.append(i)
i += 1
... | the_stack_v2_python_sparse | code85MaximalRectangle.py | cybelewang/leetcode-python | train | 0 | |
2ef5a697b1f5d3a1870f107696efcbf58e5e0c73 | [
"try:\n courses = (yield Course.get_courses_from_ids(self.handler.room.courses))\n ids = {c['user_id'] for c in courses}\n names = (yield {id_: User.get_name(id_) for id_ in ids})\n for course in courses:\n course['owner'] = names[course['user_id']]\n del course['user_id']\n self.pub_su... | <|body_start_0|>
try:
courses = (yield Course.get_courses_from_ids(self.handler.room.courses))
ids = {c['user_id'] for c in courses}
names = (yield {id_: User.get_name(id_) for id_ in ids})
for course in courses:
course['owner'] = names[course['use... | CoursesWSC | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoursesWSC:
def send_room_courses(self, message):
"""Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of each course is replaced by the ``owner`` field. The ``owner`` field contains the name of the user, ... | stack_v2_sparse_classes_10k_train_000731 | 2,550 | no_license | [
{
"docstring": "Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of each course is replaced by the ``owner`` field. The ``owner`` field contains the name of the user, instead of it's ID. :param dict message: The client's message... | 2 | stack_v2_sparse_classes_30k_train_002484 | Implement the Python class `CoursesWSC` described below.
Class description:
Implement the CoursesWSC class.
Method signatures and docstrings:
- def send_room_courses(self, message): Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of ... | Implement the Python class `CoursesWSC` described below.
Class description:
Implement the CoursesWSC class.
Method signatures and docstrings:
- def send_room_courses(self, message): Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of ... | bc3870f809ad43feb78fbc39e7a4cead62207b27 | <|skeleton|>
class CoursesWSC:
def send_room_courses(self, message):
"""Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of each course is replaced by the ``owner`` field. The ``owner`` field contains the name of the user, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CoursesWSC:
def send_room_courses(self, message):
"""Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of each course is replaced by the ``owner`` field. The ``owner`` field contains the name of the user, instead of it'... | the_stack_v2_python_sparse | backend_modules/courses/wsclass.py | pipegreyback/artificialAlan | train | 1 | |
0253a1abeaa438a51e1fdcc8141b1615475d9bd1 | [
"if isinstance(models, dict):\n included_models = {model: val for model, val in models.items() if model in included_model_types}\n missing_models = set(included_model_types) - set(included_models.keys())\nelif isinstance(models, list):\n included_models = [model for model in models if model in included_mod... | <|body_start_0|>
if isinstance(models, dict):
included_models = {model: val for model, val in models.items() if model in included_model_types}
missing_models = set(included_model_types) - set(included_models.keys())
elif isinstance(models, list):
included_models = [mo... | Class to filter models given user requirements | ModelFilter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelFilter:
"""Class to filter models given user requirements"""
def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]:
"""Only include models specified in `included_model_types`, other models will be remove... | stack_v2_sparse_classes_10k_train_000732 | 4,609 | permissive | [
{
"docstring": "Only include models specified in `included_model_types`, other models will be removed If model specified in `included_model_types` doesn't present in `models`, will warn users and ignore Parameters ---------- models: Union[Dict[str, Any], List[str]] A dictionary containing models and their hyper... | 3 | null | Implement the Python class `ModelFilter` described below.
Class description:
Class to filter models given user requirements
Method signatures and docstrings:
- def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]: Only include models specifi... | Implement the Python class `ModelFilter` described below.
Class description:
Class to filter models given user requirements
Method signatures and docstrings:
- def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]: Only include models specifi... | 6af92e149491f6e5062495d87306b3625d12d992 | <|skeleton|>
class ModelFilter:
"""Class to filter models given user requirements"""
def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]:
"""Only include models specified in `included_model_types`, other models will be remove... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ModelFilter:
"""Class to filter models given user requirements"""
def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]:
"""Only include models specified in `included_model_types`, other models will be removed If model sp... | the_stack_v2_python_sparse | common/src/autogluon/common/model_filter/_model_filter.py | stjordanis/autogluon | train | 0 |
da07c5ea03b747c7333afc677373ed9bbf657aac | [
"res = []\n\ndef dfs(root):\n if root is None:\n res.append('N')\n return\n res.append(str(root.val))\n dfs(root.left)\n dfs(root.right)\ndfs(root)\nres = ','.join(res)\nreturn res",
"data = data.split(',')\nself.idx = 0\n\ndef dfs():\n if data[self.idx] == 'N':\n self.idx += 1... | <|body_start_0|>
res = []
def dfs(root):
if root is None:
res.append('N')
return
res.append(str(root.val))
dfs(root.left)
dfs(root.right)
dfs(root)
res = ','.join(res)
return res
<|end_body_0|>
<|bo... | 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_000733 | 1,410 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_003736 | 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:... | 86875d7436a78420591a60b716acd2780287b4a8 | <|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"""
res = []
def dfs(root):
if root is None:
res.append('N')
return
res.append(str(root.val))
dfs(root.left)
... | the_stack_v2_python_sparse | leetcode/LeetCode-150/Trees/297-Serialize-and-Deserialize-Binary-Tree.py | hrishikeshtak/Coding_Practises_Solutions | train | 0 | |
3e889150e6eb1ea1efac6e168fe3e5e0dde6c8bf | [
"self.player1 = player1\nself.player2 = player2\nself.game = game\nself.display = display",
"players = [self.player1, self.player1, self.player1]\ncurPlayer = 1\nboard = self.game.getInitBoard_fix_sonet(sonete, sequences, nround)\nit = 0\nwhile self.game.getGameEnded(board, curPlayer) == 0:\n it += 1\n if v... | <|body_start_0|>
self.player1 = player1
self.player2 = player2
self.game = game
self.display = display
<|end_body_0|>
<|body_start_1|>
players = [self.player1, self.player1, self.player1]
curPlayer = 1
board = self.game.getInitBoard_fix_sonet(sonete, sequences, n... | An Arena class where any 2 agents can be pit against each other. | Arena | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Arena:
"""An Arena class where any 2 agents can be pit against each other."""
def __init__(self, player1, player2, game, display=None):
"""Input: player 1,2: two functions that takes board as input, return action game: Game object display: a function that takes board as input and pri... | stack_v2_sparse_classes_10k_train_000734 | 3,337 | permissive | [
{
"docstring": "Input: player 1,2: two functions that takes board as input, return action game: Game object display: a function that takes board as input and prints it (e.g. display in othello/OthelloGame). Is necessary for verbose mode. see othello/OthelloPlayers.py for an example. See pit.py for pitting human... | 3 | stack_v2_sparse_classes_30k_val_000000 | Implement the Python class `Arena` described below.
Class description:
An Arena class where any 2 agents can be pit against each other.
Method signatures and docstrings:
- def __init__(self, player1, player2, game, display=None): Input: player 1,2: two functions that takes board as input, return action game: Game obj... | Implement the Python class `Arena` described below.
Class description:
An Arena class where any 2 agents can be pit against each other.
Method signatures and docstrings:
- def __init__(self, player1, player2, game, display=None): Input: player 1,2: two functions that takes board as input, return action game: Game obj... | 2ba6f153e428227fcf6f27080bdd0183d395ef64 | <|skeleton|>
class Arena:
"""An Arena class where any 2 agents can be pit against each other."""
def __init__(self, player1, player2, game, display=None):
"""Input: player 1,2: two functions that takes board as input, return action game: Game object display: a function that takes board as input and pri... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Arena:
"""An Arena class where any 2 agents can be pit against each other."""
def __init__(self, player1, player2, game, display=None):
"""Input: player 1,2: two functions that takes board as input, return action game: Game object display: a function that takes board as input and prints it (e.g. ... | the_stack_v2_python_sparse | alpha-zero-general_one_step/Arena_2.py | rubenrtorrado/NLP | train | 0 |
a462a969e0eec08f456f34f64f849b88965c4688 | [
"self.index = 0\nself.counter = 0\nself.amount = ''\nself.cs = compressedString\nself.leng = len(compressedString)\nself.char = ''\ni = self.index\nwhile i < self.leng:\n self.char = compressedString[i]\n stringnum = ''\n i += 1\n while not compressedString[i].isalpha():\n stringnum += compressed... | <|body_start_0|>
self.index = 0
self.counter = 0
self.amount = ''
self.cs = compressedString
self.leng = len(compressedString)
self.char = ''
i = self.index
while i < self.leng:
self.char = compressedString[i]
stringnum = ''
... | StringIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringIterator:
def __init__(self, compressedString):
""":type compressedString: str"""
<|body_0|>
def next(self):
""":rtype: str"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_10k_train_000735 | 2,237 | no_license | [
{
"docstring": ":type compressedString: str",
"name": "__init__",
"signature": "def __init__(self, compressedString)"
},
{
"docstring": ":rtype: str",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",
"signature": "def hasN... | 3 | null | Implement the Python class `StringIterator` described below.
Class description:
Implement the StringIterator class.
Method signatures and docstrings:
- def __init__(self, compressedString): :type compressedString: str
- def next(self): :rtype: str
- def hasNext(self): :rtype: bool | Implement the Python class `StringIterator` described below.
Class description:
Implement the StringIterator class.
Method signatures and docstrings:
- def __init__(self, compressedString): :type compressedString: str
- def next(self): :rtype: str
- def hasNext(self): :rtype: bool
<|skeleton|>
class StringIterator:
... | 05d49ca91ac2a4d414dbb38b01266962ce68f34a | <|skeleton|>
class StringIterator:
def __init__(self, compressedString):
""":type compressedString: str"""
<|body_0|>
def next(self):
""":rtype: str"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StringIterator:
def __init__(self, compressedString):
""":type compressedString: str"""
self.index = 0
self.counter = 0
self.amount = ''
self.cs = compressedString
self.leng = len(compressedString)
self.char = ''
i = self.index
while i < ... | the_stack_v2_python_sparse | leetcode/contest/2017/june10/604.py | jonathantsang/CompetitiveProgramming | train | 2 | |
55abbed335856edce14fdfad7a592c34b81a6378 | [
"if isinstance(self.id, str):\n self.id = [self.id]\nif 'entit' in self.data_type.value and 'instance' not in self.data_type.value:\n for id in self.id:\n if '_' not in id:\n print(f'WARNING: {id} not valid for {self.data_type.value}.')\nelif 'instance' in self.data_type.value:\n for id i... | <|body_start_0|>
if isinstance(self.id, str):
self.id = [self.id]
if 'entit' in self.data_type.value and 'instance' not in self.data_type.value:
for id in self.id:
if '_' not in id:
print(f'WARNING: {id} not valid for {self.data_type.value}.')
... | General class that will host various data types, as detailed above. | DataFetcher | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataFetcher:
"""General class that will host various data types, as detailed above."""
def __post_init__(self):
"""Check types of IDs given, format accordingly."""
<|body_0|>
def add_property(self, property):
"""Add property to the list of data to fetch from the ... | stack_v2_sparse_classes_10k_train_000736 | 6,236 | permissive | [
{
"docstring": "Check types of IDs given, format accordingly.",
"name": "__post_init__",
"signature": "def __post_init__(self)"
},
{
"docstring": "Add property to the list of data to fetch from the PDB. property is a python dict, with keys as properties, and values as subproperties. e.g.: {\"cel... | 5 | stack_v2_sparse_classes_30k_train_003966 | Implement the Python class `DataFetcher` described below.
Class description:
General class that will host various data types, as detailed above.
Method signatures and docstrings:
- def __post_init__(self): Check types of IDs given, format accordingly.
- def add_property(self, property): Add property to the list of da... | Implement the Python class `DataFetcher` described below.
Class description:
General class that will host various data types, as detailed above.
Method signatures and docstrings:
- def __post_init__(self): Check types of IDs given, format accordingly.
- def add_property(self, property): Add property to the list of da... | 386359f91c5e064c0b51966a007c5475403e37a0 | <|skeleton|>
class DataFetcher:
"""General class that will host various data types, as detailed above."""
def __post_init__(self):
"""Check types of IDs given, format accordingly."""
<|body_0|>
def add_property(self, property):
"""Add property to the list of data to fetch from the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DataFetcher:
"""General class that will host various data types, as detailed above."""
def __post_init__(self):
"""Check types of IDs given, format accordingly."""
if isinstance(self.id, str):
self.id = [self.id]
if 'entit' in self.data_type.value and 'instance' not in... | the_stack_v2_python_sparse | pypdb/clients/data/data_types.py | williamgilpin/pypdb | train | 268 |
8413b45f0f4d872fe6755e67ff45a7e0316747ae | [
"self.nums = []\nself.values = []\nfor i in range(0, len(A), 2):\n self.nums.append(A[i])\n self.values.append(A[i + 1])\nself.off = 0\nfor i in range(1, len(self.nums)):\n self.nums[i] += self.nums[i - 1]\nself.lo = 0",
"if self.off > self.nums[-1]:\n return -1\nself.off += n\nif self.off > self.nums... | <|body_start_0|>
self.nums = []
self.values = []
for i in range(0, len(A), 2):
self.nums.append(A[i])
self.values.append(A[i + 1])
self.off = 0
for i in range(1, len(self.nums)):
self.nums[i] += self.nums[i - 1]
self.lo = 0
<|end_body_0... | RLEIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.nums = []
self.values = []
for i in range(0, len(A), 2):
... | stack_v2_sparse_classes_10k_train_000737 | 827 | no_license | [
{
"docstring": ":type A: List[int]",
"name": "__init__",
"signature": "def __init__(self, A)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "next",
"signature": "def next(self, n)"
}
] | 2 | null | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int
<|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: Lis... | c026f2969c784827fac702b34b07a9268b70b62a | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
self.nums = []
self.values = []
for i in range(0, len(A), 2):
self.nums.append(A[i])
self.values.append(A[i + 1])
self.off = 0
for i in range(1, len(self.nums)):
sel... | the_stack_v2_python_sparse | codes/contest/leetcode/rle-iterator.py | jiluhu/dirtysalt.github.io | train | 0 | |
46cf3286b9b2c65c1cb301a0f2abdc6bb683ae6c | [
"assert batch_size is not None and max_len is not None\nself.src_dataset = src_dataset\nself.src_vocab = src_vocab\nself.tgt_dataset = tgt_dataset\nself.tgt_vocab = tgt_vocab\nself.batch_size = batch_size\nself.max_len = max_len",
"src_tgt_dataset = tf.data.Dataset.zip((self.src_dataset, self.tgt_dataset))\nif sh... | <|body_start_0|>
assert batch_size is not None and max_len is not None
self.src_dataset = src_dataset
self.src_vocab = src_vocab
self.tgt_dataset = tgt_dataset
self.tgt_vocab = tgt_vocab
self.batch_size = batch_size
self.max_len = max_len
<|end_body_0|>
<|body_st... | Iterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Iterator:
def __init__(self, src_dataset, src_vocab, tgt_dataset=None, tgt_vocab=None, batch_size=None, max_len=None):
"""Constructs and Iterator for the given Model Note: batch size and datasets can be placeholders"""
<|body_0|>
def create_iterator(self, shuffle=True, reshu... | stack_v2_sparse_classes_10k_train_000738 | 6,517 | no_license | [
{
"docstring": "Constructs and Iterator for the given Model Note: batch size and datasets can be placeholders",
"name": "__init__",
"signature": "def __init__(self, src_dataset, src_vocab, tgt_dataset=None, tgt_vocab=None, batch_size=None, max_len=None)"
},
{
"docstring": "Constructs the Trainin... | 3 | stack_v2_sparse_classes_30k_val_000228 | Implement the Python class `Iterator` described below.
Class description:
Implement the Iterator class.
Method signatures and docstrings:
- def __init__(self, src_dataset, src_vocab, tgt_dataset=None, tgt_vocab=None, batch_size=None, max_len=None): Constructs and Iterator for the given Model Note: batch size and data... | Implement the Python class `Iterator` described below.
Class description:
Implement the Iterator class.
Method signatures and docstrings:
- def __init__(self, src_dataset, src_vocab, tgt_dataset=None, tgt_vocab=None, batch_size=None, max_len=None): Constructs and Iterator for the given Model Note: batch size and data... | 271955ab3a5543bdc38c57291d28f4736a5d067a | <|skeleton|>
class Iterator:
def __init__(self, src_dataset, src_vocab, tgt_dataset=None, tgt_vocab=None, batch_size=None, max_len=None):
"""Constructs and Iterator for the given Model Note: batch size and datasets can be placeholders"""
<|body_0|>
def create_iterator(self, shuffle=True, reshu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Iterator:
def __init__(self, src_dataset, src_vocab, tgt_dataset=None, tgt_vocab=None, batch_size=None, max_len=None):
"""Constructs and Iterator for the given Model Note: batch size and datasets can be placeholders"""
assert batch_size is not None and max_len is not None
self.src_data... | the_stack_v2_python_sparse | tf/nmt/utils/iterator_utils.py | oneTimePad/neural_networks | train | 1 | |
d1fb5f84538822f6219b18608e3ece32372eef08 | [
"super().__init__(max_n_sources)\nif use_band is None and (not use_mean):\n raise ValueError(\"Either set 'use_mean=True' OR indicate a 'use_band' index\")\nif use_band is not None and use_mean:\n raise ValueError(\"Only one of the parameters 'use_band' and 'use_mean' has to be set\")\nself.use_mean = use_mea... | <|body_start_0|>
super().__init__(max_n_sources)
if use_band is None and (not use_mean):
raise ValueError("Either set 'use_mean=True' OR indicate a 'use_band' index")
if use_band is not None and use_mean:
raise ValueError("Only one of the parameters 'use_band' and 'use_me... | Return detection, segmentation and deblending information running SEP on a single band. The function performs detection and deblending of the sources based on the provided band index. If `use_mean` feature is used, then we use the average of all the bands. For more details on SEP (Source-Extractor Python), see: https:/... | SepSingleBand | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SepSingleBand:
"""Return detection, segmentation and deblending information running SEP on a single band. The function performs detection and deblending of the sources based on the provided band index. If `use_mean` feature is used, then we use the average of all the bands. For more details on SE... | stack_v2_sparse_classes_10k_train_000739 | 24,907 | permissive | [
{
"docstring": "Initializes measurement class. Exactly one of 'use_mean' or 'use_band' must be specified. Args: max_n_sources: See parent class. thresh: Threshold pixel value for detection use in `sep.extract`. This is interpreted as a relative threshold: the absolute threshold at pixel (j, i) will be `thresh *... | 2 | stack_v2_sparse_classes_30k_train_002148 | Implement the Python class `SepSingleBand` described below.
Class description:
Return detection, segmentation and deblending information running SEP on a single band. The function performs detection and deblending of the sources based on the provided band index. If `use_mean` feature is used, then we use the average o... | Implement the Python class `SepSingleBand` described below.
Class description:
Return detection, segmentation and deblending information running SEP on a single band. The function performs detection and deblending of the sources based on the provided band index. If `use_mean` feature is used, then we use the average o... | f5b716a373f130238100db8980aa0d282822983a | <|skeleton|>
class SepSingleBand:
"""Return detection, segmentation and deblending information running SEP on a single band. The function performs detection and deblending of the sources based on the provided band index. If `use_mean` feature is used, then we use the average of all the bands. For more details on SE... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SepSingleBand:
"""Return detection, segmentation and deblending information running SEP on a single band. The function performs detection and deblending of the sources based on the provided band index. If `use_mean` feature is used, then we use the average of all the bands. For more details on SEP (Source-Ext... | the_stack_v2_python_sparse | btk/deblend.py | LSSTDESC/BlendingToolKit | train | 22 |
cdc578138d2b4d7413dcd6cdffb9d7717708b746 | [
"r = [str(len(strs))]\nfor s in strs:\n r.append(str(len(s)))\n r.append(s)\nreturn ' '.join(r)",
"q = 0\np = s.find(' ')\np = p if p > 0 else len(s)\nlistlen = int(s[q:p])\nstrs = []\nfor _ in xrange(listlen):\n q = p + 1\n p = s.find(' ', q)\n strlen = int(s[q:p])\n q = p + 1\n p = q + strl... | <|body_start_0|>
r = [str(len(strs))]
for s in strs:
r.append(str(len(s)))
r.append(s)
return ' '.join(r)
<|end_body_0|>
<|body_start_1|>
q = 0
p = s.find(' ')
p = p if p > 0 else len(s)
listlen = int(s[q:p])
strs = []
for ... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k_train_000740 | 877 | no_license | [
{
"docstring": "Encodes a list of strings to a single string. :type strs: List[str] :rtype: str",
"name": "encode",
"signature": "def encode(self, strs)"
},
{
"docstring": "Decodes a single string to a list of strings. :type s: str :rtype: List[str]",
"name": "decode",
"signature": "def ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | 20580185c6f72f3c09a725168af48893156161f5 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
r = [str(len(strs))]
for s in strs:
r.append(str(len(s)))
r.append(s)
return ' '.join(r)
def decode(self, s):
"""Decodes a s... | the_stack_v2_python_sparse | coding/00271-encode-decode-str/solution.py | misaka-10032/leetcode | train | 3 | |
e5d1fbd725e3dcfa1fa4c667e06a871641547634 | [
"user = User.objects.create_user(username='some_username', password='some_password', email='some_email@gmail.com')\nProfile.objects.create_player(username='some_username')\ndata = {'username': 'some_username', 'password': 'some_password'}\nresponse = self.client.post(self.url, data)\nself.assertEqual(response.statu... | <|body_start_0|>
user = User.objects.create_user(username='some_username', password='some_password', email='some_email@gmail.com')
Profile.objects.create_player(username='some_username')
data = {'username': 'some_username', 'password': 'some_password'}
response = self.client.post(self.ur... | UserAuthenticationTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserAuthenticationTests:
def test_valid_user_auth(self):
"""Ensure we get token in case of correct credentials"""
<|body_0|>
def test_invalid_user_auth(self):
"""Ensure we do not get token in case of wrong credentials"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_10k_train_000741 | 13,549 | permissive | [
{
"docstring": "Ensure we get token in case of correct credentials",
"name": "test_valid_user_auth",
"signature": "def test_valid_user_auth(self)"
},
{
"docstring": "Ensure we do not get token in case of wrong credentials",
"name": "test_invalid_user_auth",
"signature": "def test_invalid... | 2 | stack_v2_sparse_classes_30k_train_005866 | Implement the Python class `UserAuthenticationTests` described below.
Class description:
Implement the UserAuthenticationTests class.
Method signatures and docstrings:
- def test_valid_user_auth(self): Ensure we get token in case of correct credentials
- def test_invalid_user_auth(self): Ensure we do not get token in... | Implement the Python class `UserAuthenticationTests` described below.
Class description:
Implement the UserAuthenticationTests class.
Method signatures and docstrings:
- def test_valid_user_auth(self): Ensure we get token in case of correct credentials
- def test_invalid_user_auth(self): Ensure we do not get token in... | 9fa31e01c8fc3496f92540081a8c078474d59c0f | <|skeleton|>
class UserAuthenticationTests:
def test_valid_user_auth(self):
"""Ensure we get token in case of correct credentials"""
<|body_0|>
def test_invalid_user_auth(self):
"""Ensure we do not get token in case of wrong credentials"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserAuthenticationTests:
def test_valid_user_auth(self):
"""Ensure we get token in case of correct credentials"""
user = User.objects.create_user(username='some_username', password='some_password', email='some_email@gmail.com')
Profile.objects.create_player(username='some_username')
... | the_stack_v2_python_sparse | player/tests.py | apoorvaeternity/DirectMe | train | 1 | |
cbeccddb5d6c8d11f1e7abc36756e6213413386c | [
"self.first_register = False\ndecorator_name = ''.join(('@', Implement.__name__.lower()))\nself.decorator_name = decorator_name\nself.args = args\nself.kwargs = kwargs\nself.scope = CONTEXT.in_pycompss()\nself.core_element = None\nself.core_element_configured = False\nif self.scope:\n check_arguments(MANDATORY_A... | <|body_start_0|>
self.first_register = False
decorator_name = ''.join(('@', Implement.__name__.lower()))
self.decorator_name = decorator_name
self.args = args
self.kwargs = kwargs
self.scope = CONTEXT.in_pycompss()
self.core_element = None
self.core_elemen... | Implement decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on implementation task creation. | Implement | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Implement:
"""Implement decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on implementation task creation."""
def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
"""Store arguments passed to the decorat... | stack_v2_sparse_classes_10k_train_000742 | 6,895 | permissive | [
{
"docstring": "Store arguments passed to the decorator. self = itself. args = not used. kwargs = dictionary with the given implement parameters. :param args: Arguments. :param kwargs: Keyword arguments.",
"name": "__init__",
"signature": "def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> N... | 3 | stack_v2_sparse_classes_30k_train_006366 | Implement the Python class `Implement` described below.
Class description:
Implement decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on implementation task creation.
Method signatures and docstrings:
- def __init__(self, *args: typing.Any, **kwargs: t... | Implement the Python class `Implement` described below.
Class description:
Implement decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on implementation task creation.
Method signatures and docstrings:
- def __init__(self, *args: typing.Any, **kwargs: t... | 5f7a31436d0e6f5acbeb66fa36ab8aad18dc4092 | <|skeleton|>
class Implement:
"""Implement decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on implementation task creation."""
def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
"""Store arguments passed to the decorat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Implement:
"""Implement decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on implementation task creation."""
def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
"""Store arguments passed to the decorator. self = it... | the_stack_v2_python_sparse | compss/programming_model/bindings/python/src/pycompss/api/implement.py | bsc-wdc/compss | train | 39 |
2ae1bf7118a0e407bcfd215da6c9f87518f22f02 | [
"def build_string(root):\n if not root:\n return ['#']\n return [str(root.val)] + build_string(root.left) + build_string(root.right)\nreturn ','.join(build_string(root))",
"def build_tree(values):\n value = values.popleft()\n if value == '#':\n return None\n root = TreeNode(value)\n ... | <|body_start_0|>
def build_string(root):
if not root:
return ['#']
return [str(root.val)] + build_string(root.left) + build_string(root.right)
return ','.join(build_string(root))
<|end_body_0|>
<|body_start_1|>
def build_tree(values):
value = ... | 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_000743 | 1,884 | 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:... | 086b7c9b3651a0e70c5794f6c264eb975cc90363 | <|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"""
def build_string(root):
if not root:
return ['#']
return [str(root.val)] + build_string(root.left) + build_string(root.right)
return ','.j... | the_stack_v2_python_sparse | serialize_and_deserialize_binary_tree.py | chunweiliu/leetcode2 | train | 4 | |
52b95326eb5183ab8628d0a34c59b46b9fe72bec | [
"if len(inputFiles) == 0:\n self.inputFiles = glob.glob('z_ls-R_contents-*.txt')\nelse:\n self.inputFiles = list(inputFiles)\nself.process()",
"for i, inputFile in enumerate(self.inputFiles):\n seqInputFile = i + 1\n print(str(seqInputFile) + ' Processing ' + inputFile)\n newText = ''\n saveAppl... | <|body_start_0|>
if len(inputFiles) == 0:
self.inputFiles = glob.glob('z_ls-R_contents-*.txt')
else:
self.inputFiles = list(inputFiles)
self.process()
<|end_body_0|>
<|body_start_1|>
for i, inputFile in enumerate(self.inputFiles):
seqInputFile = i + 1... | FileSizeMinimizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileSizeMinimizer:
def __init__(self, inputFiles=[]):
""":param inputFiles:"""
<|body_0|>
def process(self):
""":return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(inputFiles) == 0:
self.inputFiles = glob.glob('z_ls-R_content... | stack_v2_sparse_classes_10k_train_000744 | 3,244 | no_license | [
{
"docstring": ":param inputFiles:",
"name": "__init__",
"signature": "def __init__(self, inputFiles=[])"
},
{
"docstring": ":return:",
"name": "process",
"signature": "def process(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003715 | Implement the Python class `FileSizeMinimizer` described below.
Class description:
Implement the FileSizeMinimizer class.
Method signatures and docstrings:
- def __init__(self, inputFiles=[]): :param inputFiles:
- def process(self): :return: | Implement the Python class `FileSizeMinimizer` described below.
Class description:
Implement the FileSizeMinimizer class.
Method signatures and docstrings:
- def __init__(self, inputFiles=[]): :param inputFiles:
- def process(self): :return:
<|skeleton|>
class FileSizeMinimizer:
def __init__(self, inputFiles=[]... | b4c5642c8d5843846d529630f8d93a7103676539 | <|skeleton|>
class FileSizeMinimizer:
def __init__(self, inputFiles=[]):
""":param inputFiles:"""
<|body_0|>
def process(self):
""":return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FileSizeMinimizer:
def __init__(self, inputFiles=[]):
""":param inputFiles:"""
if len(inputFiles) == 0:
self.inputFiles = glob.glob('z_ls-R_contents-*.txt')
else:
self.inputFiles = list(inputFiles)
self.process()
def process(self):
""":retur... | the_stack_v2_python_sparse | uTubeCompressContentsTxt.py | alclass/bin | train | 0 | |
2c94347df29165ac2a5109083de89f3ed8cec80b | [
"try:\n customer, _created = Customer.get_or_create(subscriber=subscriber_request_callback(self.request))\n serializer = SubscriptionSerializer(customer.subscription)\n return Response(serializer.data)\nexcept:\n return Response(status=status.HTTP_204_NO_CONTENT)",
"serializer = CreateSubscriptionSeri... | <|body_start_0|>
try:
customer, _created = Customer.get_or_create(subscriber=subscriber_request_callback(self.request))
serializer = SubscriptionSerializer(customer.subscription)
return Response(serializer.data)
except:
return Response(status=status.HTTP_2... | API Endpoints for the Subscription object. | SubscriptionRestView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubscriptionRestView:
"""API Endpoints for the Subscription object."""
def get(self, request, **kwargs):
"""Return the customer's valid subscriptions. Returns with status code 200."""
<|body_0|>
def post(self, request, **kwargs):
"""Create a new current subscript... | stack_v2_sparse_classes_10k_train_000745 | 4,950 | permissive | [
{
"docstring": "Return the customer's valid subscriptions. Returns with status code 200.",
"name": "get",
"signature": "def get(self, request, **kwargs)"
},
{
"docstring": "Create a new current subscription for the user. Returns with status code 201.",
"name": "post",
"signature": "def p... | 3 | stack_v2_sparse_classes_30k_train_000714 | Implement the Python class `SubscriptionRestView` described below.
Class description:
API Endpoints for the Subscription object.
Method signatures and docstrings:
- def get(self, request, **kwargs): Return the customer's valid subscriptions. Returns with status code 200.
- def post(self, request, **kwargs): Create a ... | Implement the Python class `SubscriptionRestView` described below.
Class description:
API Endpoints for the Subscription object.
Method signatures and docstrings:
- def get(self, request, **kwargs): Return the customer's valid subscriptions. Returns with status code 200.
- def post(self, request, **kwargs): Create a ... | 325cc11fbc28eee7507778e387714e9465880d68 | <|skeleton|>
class SubscriptionRestView:
"""API Endpoints for the Subscription object."""
def get(self, request, **kwargs):
"""Return the customer's valid subscriptions. Returns with status code 200."""
<|body_0|>
def post(self, request, **kwargs):
"""Create a new current subscript... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SubscriptionRestView:
"""API Endpoints for the Subscription object."""
def get(self, request, **kwargs):
"""Return the customer's valid subscriptions. Returns with status code 200."""
try:
customer, _created = Customer.get_or_create(subscriber=subscriber_request_callback(self.... | the_stack_v2_python_sparse | djstripe/contrib/rest_framework/views.py | talpor/dj-stripe | train | 1 |
bb0c5155111e0c6ad0be0dcc95af68e9fde7e24b | [
"response = self.client.get(reverse('education:demographic_detail', args=('XYZ',)))\nself.assertEqual(response.status_code, 200)\nself.assertEqual(response.context.get('json_rate_data'), None)\nself.assertNotEqual(response.context.get('message'), None)\nself.assertContains(response, 'Home')\nself.assertContains(res... | <|body_start_0|>
response = self.client.get(reverse('education:demographic_detail', args=('XYZ',)))
self.assertEqual(response.status_code, 200)
self.assertEqual(response.context.get('json_rate_data'), None)
self.assertNotEqual(response.context.get('message'), None)
self.assertCon... | EducationDemographicDetailsViewTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EducationDemographicDetailsViewTest:
def test_fake_group(self):
"""Make sure the page gives an error message if a group is specified that does not actually exist."""
<|body_0|>
def test_no_data(self):
"""Make sure all demographic pages render even when there is no da... | stack_v2_sparse_classes_10k_train_000746 | 9,266 | no_license | [
{
"docstring": "Make sure the page gives an error message if a group is specified that does not actually exist.",
"name": "test_fake_group",
"signature": "def test_fake_group(self)"
},
{
"docstring": "Make sure all demographic pages render even when there is no data in the database.",
"name"... | 3 | stack_v2_sparse_classes_30k_train_004881 | Implement the Python class `EducationDemographicDetailsViewTest` described below.
Class description:
Implement the EducationDemographicDetailsViewTest class.
Method signatures and docstrings:
- def test_fake_group(self): Make sure the page gives an error message if a group is specified that does not actually exist.
-... | Implement the Python class `EducationDemographicDetailsViewTest` described below.
Class description:
Implement the EducationDemographicDetailsViewTest class.
Method signatures and docstrings:
- def test_fake_group(self): Make sure the page gives an error message if a group is specified that does not actually exist.
-... | 2a8e2dc4e9b3cb92d4d437b37e61940a9486b81f | <|skeleton|>
class EducationDemographicDetailsViewTest:
def test_fake_group(self):
"""Make sure the page gives an error message if a group is specified that does not actually exist."""
<|body_0|>
def test_no_data(self):
"""Make sure all demographic pages render even when there is no da... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EducationDemographicDetailsViewTest:
def test_fake_group(self):
"""Make sure the page gives an error message if a group is specified that does not actually exist."""
response = self.client.get(reverse('education:demographic_detail', args=('XYZ',)))
self.assertEqual(response.status_code... | the_stack_v2_python_sparse | education/tests.py | smeds1/mysite | train | 1 | |
cab1175a1f05b916f942b1f7256aeebfa52af0fa | [
"super(IPAMAddressPool, self).__init__()\nself.schema_class = 'ipam_address_pool_schema.IPAMAddressPoolSchema'\nself.set_connection(vsm.get_connection())\nself.set_create_endpoint('/services/ipam/pools/scope/globalroot-0')\nself.set_read_endpoint('/services/ipam/pools')\nself.set_delete_endpoint('/services/ipam/poo... | <|body_start_0|>
super(IPAMAddressPool, self).__init__()
self.schema_class = 'ipam_address_pool_schema.IPAMAddressPoolSchema'
self.set_connection(vsm.get_connection())
self.set_create_endpoint('/services/ipam/pools/scope/globalroot-0')
self.set_read_endpoint('/services/ipam/pools... | IPAMAddressPool | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IPAMAddressPool:
def __init__(self, vsm):
"""Constructor to create IPAMAddressPool managed object @param vsm object on which IPAM address pool has to be configured"""
<|body_0|>
def delete(self, schema_object=None, url_parameters=None):
"""When delete ippool, the sch... | stack_v2_sparse_classes_10k_train_000747 | 2,254 | no_license | [
{
"docstring": "Constructor to create IPAMAddressPool managed object @param vsm object on which IPAM address pool has to be configured",
"name": "__init__",
"signature": "def __init__(self, vsm)"
},
{
"docstring": "When delete ippool, the scheam_obj should be set None.",
"name": "delete",
... | 2 | stack_v2_sparse_classes_30k_train_000692 | Implement the Python class `IPAMAddressPool` described below.
Class description:
Implement the IPAMAddressPool class.
Method signatures and docstrings:
- def __init__(self, vsm): Constructor to create IPAMAddressPool managed object @param vsm object on which IPAM address pool has to be configured
- def delete(self, s... | Implement the Python class `IPAMAddressPool` described below.
Class description:
Implement the IPAMAddressPool class.
Method signatures and docstrings:
- def __init__(self, vsm): Constructor to create IPAMAddressPool managed object @param vsm object on which IPAM address pool has to be configured
- def delete(self, s... | 5b55817c050b637e2747084290f6206d2e622938 | <|skeleton|>
class IPAMAddressPool:
def __init__(self, vsm):
"""Constructor to create IPAMAddressPool managed object @param vsm object on which IPAM address pool has to be configured"""
<|body_0|>
def delete(self, schema_object=None, url_parameters=None):
"""When delete ippool, the sch... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IPAMAddressPool:
def __init__(self, vsm):
"""Constructor to create IPAMAddressPool managed object @param vsm object on which IPAM address pool has to be configured"""
super(IPAMAddressPool, self).__init__()
self.schema_class = 'ipam_address_pool_schema.IPAMAddressPoolSchema'
se... | the_stack_v2_python_sparse | SystemTesting/pylib/nsx/vsm/ipam_address_pool/ipam_address_pool.py | Cloudxtreme/MyProject | train | 0 | |
7d7bdccc4bd70b6cf6830b6d0d9fafa1fdcbdc5b | [
"self.nc_file = nc_file\nxr_variables, global_attributes = self._readXarrayFile(var_ids, exclude_vars)\nsuper().__init__(xr_variables, global_attributes=global_attributes, na_items_to_override=na_items_to_override, only_return_file_names=only_return_file_names, requested_ffi=requested_ffi)",
"exclude_vars = exclu... | <|body_start_0|>
self.nc_file = nc_file
xr_variables, global_attributes = self._readXarrayFile(var_ids, exclude_vars)
super().__init__(xr_variables, global_attributes=global_attributes, na_items_to_override=na_items_to_override, only_return_file_names=only_return_file_names, requested_ffi=reques... | Converts a NetCDF file to one or more NASA Ames files. | NCToNA | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NCToNA:
"""Converts a NetCDF file to one or more NASA Ames files."""
def __init__(self, nc_file, var_ids=None, na_items_to_override=None, only_return_file_names=False, exclude_vars=None, requested_ffi=None):
"""Sets up instance variables. Typical usage is: >>> import nappy.nc_interfa... | stack_v2_sparse_classes_10k_train_000748 | 3,661 | permissive | [
{
"docstring": "Sets up instance variables. Typical usage is: >>> import nappy.nc_interface.nc_to_na as nc_to_na >>> c = nc_to_na.NCToNA(\"old_file.nc\") >>> c.convert() >>> c.writeNAFiles(\"new_file.na\", delimiter=\",\") OR: >>> c = nc_to_na.NCToNA(\"old_file.nc\") >>> file_names = c.constructNAFileNames()",
... | 2 | stack_v2_sparse_classes_30k_train_000723 | Implement the Python class `NCToNA` described below.
Class description:
Converts a NetCDF file to one or more NASA Ames files.
Method signatures and docstrings:
- def __init__(self, nc_file, var_ids=None, na_items_to_override=None, only_return_file_names=False, exclude_vars=None, requested_ffi=None): Sets up instance... | Implement the Python class `NCToNA` described below.
Class description:
Converts a NetCDF file to one or more NASA Ames files.
Method signatures and docstrings:
- def __init__(self, nc_file, var_ids=None, na_items_to_override=None, only_return_file_names=False, exclude_vars=None, requested_ffi=None): Sets up instance... | 71e42a91112f52eef86183e35129b9ee2019e55b | <|skeleton|>
class NCToNA:
"""Converts a NetCDF file to one or more NASA Ames files."""
def __init__(self, nc_file, var_ids=None, na_items_to_override=None, only_return_file_names=False, exclude_vars=None, requested_ffi=None):
"""Sets up instance variables. Typical usage is: >>> import nappy.nc_interfa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NCToNA:
"""Converts a NetCDF file to one or more NASA Ames files."""
def __init__(self, nc_file, var_ids=None, na_items_to_override=None, only_return_file_names=False, exclude_vars=None, requested_ffi=None):
"""Sets up instance variables. Typical usage is: >>> import nappy.nc_interface.nc_to_na a... | the_stack_v2_python_sparse | nappy/nc_interface/nc_to_na.py | cedadev/nappy | train | 9 |
fb8278608e00a9762c37261d6e5d43f91f5995f1 | [
"if isinstance(rules, str):\n rules = re.split('\\\\s|,\\\\s*', rules)\npositive_rules = [rule for rule in rules if not rule.startswith('!') and (not rule.strip() == '')]\nnegative_rules = [rule[1:] for rule in rules if rule not in positive_rules]\nif len(positive_rules) == 0:\n positive_rules.append('*')\nma... | <|body_start_0|>
if isinstance(rules, str):
rules = re.split('\\s|,\\s*', rules)
positive_rules = [rule for rule in rules if not rule.startswith('!') and (not rule.strip() == '')]
negative_rules = [rule[1:] for rule in rules if rule not in positive_rules]
if len(positive_rule... | Device name matching against the devices specification in tuning profiles. The devices specification consists of multiple rules separated by spaces. The rules have a syntax of shell-style wildcards and are either positive or negative. The negative rules are prefixed with an exclamation mark. | DeviceMatcher | [
"GPL-2.0-or-later",
"CC-BY-SA-3.0",
"GPL-2.0-only",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceMatcher:
"""Device name matching against the devices specification in tuning profiles. The devices specification consists of multiple rules separated by spaces. The rules have a syntax of shell-style wildcards and are either positive or negative. The negative rules are prefixed with an excl... | stack_v2_sparse_classes_10k_train_000749 | 1,576 | permissive | [
{
"docstring": "Match a device against the specification in the profile. If there is no positive rule in the specification, implicit rule which matches all devices is added. The device matches if and only if it matches some positive rule, but no negative rule.",
"name": "match",
"signature": "def match(... | 2 | stack_v2_sparse_classes_30k_train_004666 | Implement the Python class `DeviceMatcher` described below.
Class description:
Device name matching against the devices specification in tuning profiles. The devices specification consists of multiple rules separated by spaces. The rules have a syntax of shell-style wildcards and are either positive or negative. The n... | Implement the Python class `DeviceMatcher` described below.
Class description:
Device name matching against the devices specification in tuning profiles. The devices specification consists of multiple rules separated by spaces. The rules have a syntax of shell-style wildcards and are either positive or negative. The n... | 6784795578ba558593cc9f620610bcf99fb26de5 | <|skeleton|>
class DeviceMatcher:
"""Device name matching against the devices specification in tuning profiles. The devices specification consists of multiple rules separated by spaces. The rules have a syntax of shell-style wildcards and are either positive or negative. The negative rules are prefixed with an excl... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeviceMatcher:
"""Device name matching against the devices specification in tuning profiles. The devices specification consists of multiple rules separated by spaces. The rules have a syntax of shell-style wildcards and are either positive or negative. The negative rules are prefixed with an exclamation mark.... | the_stack_v2_python_sparse | assets/tuned/daemon/tuned/hardware/device_matcher.py | openshift/cluster-node-tuning-operator | train | 90 |
71534e1658e74b28b9807e2dabc914c65f59002f | [
"self.aws_region = aws_region\nself.bucket_name = bucket_name\nself.key_prefix = key_prefix",
"if dictionary is None:\n return None\naws_region = dictionary.get('awsRegion')\nbucket_name = dictionary.get('bucketName')\nkey_prefix = dictionary.get('keyPrefix')\nreturn cls(aws_region, bucket_name, key_prefix)"
] | <|body_start_0|>
self.aws_region = aws_region
self.bucket_name = bucket_name
self.key_prefix = key_prefix
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
aws_region = dictionary.get('awsRegion')
bucket_name = dictionary.get('bucketName')
... | Implementation of the 'S3BucketInfo' model. TODO: type description here. Attributes: aws_region (string): AWS region of the S3 bucket. bucket_name (string): Name of the S3 bucket. key_prefix (string): Complete path of the sub folder in the s3 bucket. This job will create all keys within the given key prefix. | S3BucketInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class S3BucketInfo:
"""Implementation of the 'S3BucketInfo' model. TODO: type description here. Attributes: aws_region (string): AWS region of the S3 bucket. bucket_name (string): Name of the S3 bucket. key_prefix (string): Complete path of the sub folder in the s3 bucket. This job will create all keys... | stack_v2_sparse_classes_10k_train_000750 | 1,870 | permissive | [
{
"docstring": "Constructor for the S3BucketInfo class",
"name": "__init__",
"signature": "def __init__(self, aws_region=None, bucket_name=None, key_prefix=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of ... | 2 | null | Implement the Python class `S3BucketInfo` described below.
Class description:
Implementation of the 'S3BucketInfo' model. TODO: type description here. Attributes: aws_region (string): AWS region of the S3 bucket. bucket_name (string): Name of the S3 bucket. key_prefix (string): Complete path of the sub folder in the s... | Implement the Python class `S3BucketInfo` described below.
Class description:
Implementation of the 'S3BucketInfo' model. TODO: type description here. Attributes: aws_region (string): AWS region of the S3 bucket. bucket_name (string): Name of the S3 bucket. key_prefix (string): Complete path of the sub folder in the s... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class S3BucketInfo:
"""Implementation of the 'S3BucketInfo' model. TODO: type description here. Attributes: aws_region (string): AWS region of the S3 bucket. bucket_name (string): Name of the S3 bucket. key_prefix (string): Complete path of the sub folder in the s3 bucket. This job will create all keys... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class S3BucketInfo:
"""Implementation of the 'S3BucketInfo' model. TODO: type description here. Attributes: aws_region (string): AWS region of the S3 bucket. bucket_name (string): Name of the S3 bucket. key_prefix (string): Complete path of the sub folder in the s3 bucket. This job will create all keys within the g... | the_stack_v2_python_sparse | cohesity_management_sdk/models/s3_bucket_info.py | cohesity/management-sdk-python | train | 24 |
34efde1c8fe38fb5cfe4d603d1e1a693d1a02129 | [
"start = self.isodate_param(timezone.now())\nend = self.isodate_param(timezone.now() + datetime.timedelta(days=31))\nself.send_and_compare_request('getActivityStream', [start, end], None, [])\nself.send_and_compare_request('getActivityStream', [start, end], self.data['token1'], [])",
"_gen_activities(10)\nactivit... | <|body_start_0|>
start = self.isodate_param(timezone.now())
end = self.isodate_param(timezone.now() + datetime.timedelta(days=31))
self.send_and_compare_request('getActivityStream', [start, end], None, [])
self.send_and_compare_request('getActivityStream', [start, end], self.data['token1... | GetActivityStreamTest | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetActivityStreamTest:
def test_empty(self):
"""Test the getActivityStream() call without contents."""
<|body_0|>
def test_public(self):
"""Test the getActivityStream() call with public events."""
<|body_1|>
def test_private(self):
"""Test the ge... | stack_v2_sparse_classes_10k_train_000751 | 17,825 | permissive | [
{
"docstring": "Test the getActivityStream() call without contents.",
"name": "test_empty",
"signature": "def test_empty(self)"
},
{
"docstring": "Test the getActivityStream() call with public events.",
"name": "test_public",
"signature": "def test_public(self)"
},
{
"docstring":... | 4 | null | Implement the Python class `GetActivityStreamTest` described below.
Class description:
Implement the GetActivityStreamTest class.
Method signatures and docstrings:
- def test_empty(self): Test the getActivityStream() call without contents.
- def test_public(self): Test the getActivityStream() call with public events.... | Implement the Python class `GetActivityStreamTest` described below.
Class description:
Implement the GetActivityStreamTest class.
Method signatures and docstrings:
- def test_empty(self): Test the getActivityStream() call without contents.
- def test_public(self): Test the getActivityStream() call with public events.... | 5e46b82cab225b452eceffd4a5be6dadccceddd2 | <|skeleton|>
class GetActivityStreamTest:
def test_empty(self):
"""Test the getActivityStream() call without contents."""
<|body_0|>
def test_public(self):
"""Test the getActivityStream() call with public events."""
<|body_1|>
def test_private(self):
"""Test the ge... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GetActivityStreamTest:
def test_empty(self):
"""Test the getActivityStream() call without contents."""
start = self.isodate_param(timezone.now())
end = self.isodate_param(timezone.now() + datetime.timedelta(days=31))
self.send_and_compare_request('getActivityStream', [start, en... | the_stack_v2_python_sparse | amelie/api/test_activitystream.py | Inter-Actief/amelie | train | 11 | |
cd3d1bce5b87f875b31bd963f4a1f6bbccc68708 | [
"port = 8773\nconfig = [('ResNetBlockSpace2', {'block_mask': [0]})]\nrlnas = RLNAS(key='lstm', configs=config, server_addr=('', port), is_sync=False, controller_batch_size=1, lstm_num_layers=1, hidden_size=10, temperature=1.0, save_controller=False)\ninput = paddle.static.data(name='input', shape=[None, 3, 32, 32],... | <|body_start_0|>
port = 8773
config = [('ResNetBlockSpace2', {'block_mask': [0]})]
rlnas = RLNAS(key='lstm', configs=config, server_addr=('', port), is_sync=False, controller_batch_size=1, lstm_num_layers=1, hidden_size=10, temperature=1.0, save_controller=False)
input = paddle.static.da... | Test classpaddleslim.nas.RLNAS(key,...) | TestRLNAS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestRLNAS:
"""Test classpaddleslim.nas.RLNAS(key,...)"""
def test_RLNAS1(self):
"""classpaddleslim.nas.RLNAS(key, configs, use_gpu=False, server_addr=("", 8881), is_server=True, is_sync=False, save_controller=None, load_controller=None, **kwargs) :return:"""
<|body_0|>
d... | stack_v2_sparse_classes_10k_train_000752 | 3,697 | no_license | [
{
"docstring": "classpaddleslim.nas.RLNAS(key, configs, use_gpu=False, server_addr=(\"\", 8881), is_server=True, is_sync=False, save_controller=None, load_controller=None, **kwargs) :return:",
"name": "test_RLNAS1",
"signature": "def test_RLNAS1(self)"
},
{
"docstring": "is_server=False,is_sync=... | 3 | stack_v2_sparse_classes_30k_test_000095 | Implement the Python class `TestRLNAS` described below.
Class description:
Test classpaddleslim.nas.RLNAS(key,...)
Method signatures and docstrings:
- def test_RLNAS1(self): classpaddleslim.nas.RLNAS(key, configs, use_gpu=False, server_addr=("", 8881), is_server=True, is_sync=False, save_controller=None, load_control... | Implement the Python class `TestRLNAS` described below.
Class description:
Test classpaddleslim.nas.RLNAS(key,...)
Method signatures and docstrings:
- def test_RLNAS1(self): classpaddleslim.nas.RLNAS(key, configs, use_gpu=False, server_addr=("", 8881), is_server=True, is_sync=False, save_controller=None, load_control... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class TestRLNAS:
"""Test classpaddleslim.nas.RLNAS(key,...)"""
def test_RLNAS1(self):
"""classpaddleslim.nas.RLNAS(key, configs, use_gpu=False, server_addr=("", 8881), is_server=True, is_sync=False, save_controller=None, load_controller=None, **kwargs) :return:"""
<|body_0|>
d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestRLNAS:
"""Test classpaddleslim.nas.RLNAS(key,...)"""
def test_RLNAS1(self):
"""classpaddleslim.nas.RLNAS(key, configs, use_gpu=False, server_addr=("", 8881), is_server=True, is_sync=False, save_controller=None, load_controller=None, **kwargs) :return:"""
port = 8773
config = [... | the_stack_v2_python_sparse | models/PaddleSlim/CI/Slim_CI_all_case/p1_api_case_static/te_api_rl_nas.py | PaddlePaddle/PaddleTest | train | 42 |
20cc3b56e07bbaf04f98f1258f3b0c7e4eb37e44 | [
"if cls._driver is None:\n if browser_name == 'Chrome':\n cls._driver = webdriver.Chrome(driverPath['Chrome'])\n elif browser_name == 'Firefox':\n cls._driver = webdriver.Firefox(driverPath['Firefox'])\n cls._driver.maximize_window()\n cls._driver.get(URL)\n cls.__login()\n cls._driv... | <|body_start_0|>
if cls._driver is None:
if browser_name == 'Chrome':
cls._driver = webdriver.Chrome(driverPath['Chrome'])
elif browser_name == 'Firefox':
cls._driver = webdriver.Firefox(driverPath['Firefox'])
cls._driver.maximize_window()
... | 浏览器驱动工具类 | Driver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Driver:
"""浏览器驱动工具类"""
def get_driver(cls, browser_name='Chrome'):
"""获取浏览器驱动对象 :param browser_name: :return:"""
<|body_0|>
def __login(cls):
"""私有方法, 只能在类里边使用 类外部无法使用, 子类不能继承 解决登录问题 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if cl... | stack_v2_sparse_classes_10k_train_000753 | 2,453 | no_license | [
{
"docstring": "获取浏览器驱动对象 :param browser_name: :return:",
"name": "get_driver",
"signature": "def get_driver(cls, browser_name='Chrome')"
},
{
"docstring": "私有方法, 只能在类里边使用 类外部无法使用, 子类不能继承 解决登录问题 :return:",
"name": "__login",
"signature": "def __login(cls)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006107 | Implement the Python class `Driver` described below.
Class description:
浏览器驱动工具类
Method signatures and docstrings:
- def get_driver(cls, browser_name='Chrome'): 获取浏览器驱动对象 :param browser_name: :return:
- def __login(cls): 私有方法, 只能在类里边使用 类外部无法使用, 子类不能继承 解决登录问题 :return: | Implement the Python class `Driver` described below.
Class description:
浏览器驱动工具类
Method signatures and docstrings:
- def get_driver(cls, browser_name='Chrome'): 获取浏览器驱动对象 :param browser_name: :return:
- def __login(cls): 私有方法, 只能在类里边使用 类外部无法使用, 子类不能继承 解决登录问题 :return:
<|skeleton|>
class Driver:
"""浏览器驱动工具类"""
... | c777f2f8f532d58577e9f023db38a0d404c3a150 | <|skeleton|>
class Driver:
"""浏览器驱动工具类"""
def get_driver(cls, browser_name='Chrome'):
"""获取浏览器驱动对象 :param browser_name: :return:"""
<|body_0|>
def __login(cls):
"""私有方法, 只能在类里边使用 类外部无法使用, 子类不能继承 解决登录问题 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Driver:
"""浏览器驱动工具类"""
def get_driver(cls, browser_name='Chrome'):
"""获取浏览器驱动对象 :param browser_name: :return:"""
if cls._driver is None:
if browser_name == 'Chrome':
cls._driver = webdriver.Chrome(driverPath['Chrome'])
elif browser_name == 'Firefox'... | the_stack_v2_python_sparse | day6/day6作业.py | gongzuo666/pycharm.web | train | 0 |
ea8c39bc97a8e417a50e5e3755f7ac3f1c4180d4 | [
"self._logger = logging.getLogger('stone.compiler')\nself.api = api\nself.backend_module = backend_module\nself.backend_args = backend_args\nself.build_path = build_path\nif clean_build and os.path.exists(self.build_path):\n logging.info('Cleaning existing build directory %s...', self.build_path)\n shutil.rmt... | <|body_start_0|>
self._logger = logging.getLogger('stone.compiler')
self.api = api
self.backend_module = backend_module
self.backend_args = backend_args
self.build_path = build_path
if clean_build and os.path.exists(self.build_path):
logging.info('Cleaning exi... | Applies a collection of backends found in a single backend module to an API specification. | Compiler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Compiler:
"""Applies a collection of backends found in a single backend module to an API specification."""
def __init__(self, api, backend_module, backend_args, build_path, clean_build=False):
"""Creates a Compiler. :param stone.ir.Api api: A Stone description of the API. :param back... | stack_v2_sparse_classes_10k_train_000754 | 4,380 | permissive | [
{
"docstring": "Creates a Compiler. :param stone.ir.Api api: A Stone description of the API. :param backend_module: Python module that contains at least one top-level class definition that descends from a :class:`stone.backend.Backend`. :param list(str) backend_args: A list of command-line arguments to pass to ... | 5 | stack_v2_sparse_classes_30k_train_006581 | Implement the Python class `Compiler` described below.
Class description:
Applies a collection of backends found in a single backend module to an API specification.
Method signatures and docstrings:
- def __init__(self, api, backend_module, backend_args, build_path, clean_build=False): Creates a Compiler. :param ston... | Implement the Python class `Compiler` described below.
Class description:
Applies a collection of backends found in a single backend module to an API specification.
Method signatures and docstrings:
- def __init__(self, api, backend_module, backend_args, build_path, clean_build=False): Creates a Compiler. :param ston... | 0c9ceb748ac4dcdea5ff69c97704daccdcb7e60e | <|skeleton|>
class Compiler:
"""Applies a collection of backends found in a single backend module to an API specification."""
def __init__(self, api, backend_module, backend_args, build_path, clean_build=False):
"""Creates a Compiler. :param stone.ir.Api api: A Stone description of the API. :param back... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Compiler:
"""Applies a collection of backends found in a single backend module to an API specification."""
def __init__(self, api, backend_module, backend_args, build_path, clean_build=False):
"""Creates a Compiler. :param stone.ir.Api api: A Stone description of the API. :param backend_module: P... | the_stack_v2_python_sparse | stone/compiler.py | dropbox/stone | train | 440 |
4a2686406b220a6c21244889000fa0b7a858aa81 | [
"tests = ['test.1', 'test.2']\nexpected = 'test.1:test.2'\nself.assertEqual(test_apps.get_gtest_filter(tests), expected)",
"tests = ['test.1', 'test.2']\nexpected = '-test.1:test.2'\nself.assertEqual(test_apps.get_gtest_filter(tests, invert=True), expected)"
] | <|body_start_0|>
tests = ['test.1', 'test.2']
expected = 'test.1:test.2'
self.assertEqual(test_apps.get_gtest_filter(tests), expected)
<|end_body_0|>
<|body_start_1|>
tests = ['test.1', 'test.2']
expected = '-test.1:test.2'
self.assertEqual(test_apps.get_gtest_filter(tes... | Tests for test_runner.get_gtest_filter. | GetGTestFilterTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetGTestFilterTest:
"""Tests for test_runner.get_gtest_filter."""
def test_correct(self):
"""Ensures correctness of filter."""
<|body_0|>
def test_correct_inverted(self):
"""Ensures correctness of inverted filter."""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_10k_train_000755 | 1,492 | permissive | [
{
"docstring": "Ensures correctness of filter.",
"name": "test_correct",
"signature": "def test_correct(self)"
},
{
"docstring": "Ensures correctness of inverted filter.",
"name": "test_correct_inverted",
"signature": "def test_correct_inverted(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004818 | Implement the Python class `GetGTestFilterTest` described below.
Class description:
Tests for test_runner.get_gtest_filter.
Method signatures and docstrings:
- def test_correct(self): Ensures correctness of filter.
- def test_correct_inverted(self): Ensures correctness of inverted filter. | Implement the Python class `GetGTestFilterTest` described below.
Class description:
Tests for test_runner.get_gtest_filter.
Method signatures and docstrings:
- def test_correct(self): Ensures correctness of filter.
- def test_correct_inverted(self): Ensures correctness of inverted filter.
<|skeleton|>
class GetGTest... | 64bee65c921db7e78e25d08f1e98da2668b57be5 | <|skeleton|>
class GetGTestFilterTest:
"""Tests for test_runner.get_gtest_filter."""
def test_correct(self):
"""Ensures correctness of filter."""
<|body_0|>
def test_correct_inverted(self):
"""Ensures correctness of inverted filter."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GetGTestFilterTest:
"""Tests for test_runner.get_gtest_filter."""
def test_correct(self):
"""Ensures correctness of filter."""
tests = ['test.1', 'test.2']
expected = 'test.1:test.2'
self.assertEqual(test_apps.get_gtest_filter(tests), expected)
def test_correct_invert... | the_stack_v2_python_sparse | ios/build/bots/scripts/test_apps_test.py | otcshare/chromium-src | train | 18 |
8bc48e38b4d6a2bed4730d64e8552f6a8041451c | [
"self.output_raw = output_raw\nif isinstance(filter_spec, dict):\n self.output_raw = filter_spec.get('output-raw', output_raw)\n filter_spec = filter_spec.get('script', '.')\nif isinstance(filter_spec, list):\n filter_spec = '\\n'.join([str(line) for line in filter_spec])\nif not isinstance(filter_spec, st... | <|body_start_0|>
self.output_raw = output_raw
if isinstance(filter_spec, dict):
self.output_raw = filter_spec.get('output-raw', output_raw)
filter_spec = filter_spec.get('script', '.')
if isinstance(filter_spec, list):
filter_spec = '\n'.join([str(line) for li... | JQ JSON filter | JQFilter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JQFilter:
"""JQ JSON filter"""
def __init__(self, filter_spec='.', args={}, output_raw=False, groom=False):
"""Construct a filter. Arguments: filter_spec - The JQ script to be used for this filter. This may be any subclass of basestring, a list or a dict. Strings are interpreted dire... | stack_v2_sparse_classes_10k_train_000756 | 4,966 | permissive | [
{
"docstring": "Construct a filter. Arguments: filter_spec - The JQ script to be used for this filter. This may be any subclass of basestring, a list or a dict. Strings are interpreted directly, lists are stringified and joined with newlines (to make multi-line scripts readable in JSON) and dicts give their \"s... | 2 | null | Implement the Python class `JQFilter` described below.
Class description:
JQ JSON filter
Method signatures and docstrings:
- def __init__(self, filter_spec='.', args={}, output_raw=False, groom=False): Construct a filter. Arguments: filter_spec - The JQ script to be used for this filter. This may be any subclass of b... | Implement the Python class `JQFilter` described below.
Class description:
JQ JSON filter
Method signatures and docstrings:
- def __init__(self, filter_spec='.', args={}, output_raw=False, groom=False): Construct a filter. Arguments: filter_spec - The JQ script to be used for this filter. This may be any subclass of b... | f6d04c0455e5be4d490df16ec1acb377f9025d9f | <|skeleton|>
class JQFilter:
"""JQ JSON filter"""
def __init__(self, filter_spec='.', args={}, output_raw=False, groom=False):
"""Construct a filter. Arguments: filter_spec - The JQ script to be used for this filter. This may be any subclass of basestring, a list or a dict. Strings are interpreted dire... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class JQFilter:
"""JQ JSON filter"""
def __init__(self, filter_spec='.', args={}, output_raw=False, groom=False):
"""Construct a filter. Arguments: filter_spec - The JQ script to be used for this filter. This may be any subclass of basestring, a list or a dict. Strings are interpreted directly, lists a... | the_stack_v2_python_sparse | python-pscheduler/pscheduler/pscheduler/jqfilter.py | perfsonar/pscheduler | train | 53 |
cc7eba945a11325885ab4dd86da5078746bb3a0c | [
"delete_database()\ntest_import = import_data(self.folder_name, 'inventory.csv', 'customers.csv', 'rental.csv')\nself.assertEqual(test_import, ((7, 9, 7), (0, 0, 0)))\n'test import bad data'\ndelete_database()\ntest_import = import_data(self.folder_name, 'inventory1.csv', 'customers2.csv', 'rental3.csv')\nself.asse... | <|body_start_0|>
delete_database()
test_import = import_data(self.folder_name, 'inventory.csv', 'customers.csv', 'rental.csv')
self.assertEqual(test_import, ((7, 9, 7), (0, 0, 0)))
'test import bad data'
delete_database()
test_import = import_data(self.folder_name, 'inven... | "test for Mongo database.py | TestDatabase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDatabase:
""""test for Mongo database.py"""
def test_import_data(self):
"""test import all good data"""
<|body_0|>
def test_show_rentals(self):
"""test for show_rentals"""
<|body_1|>
def test_show_available_products(self):
"""rest for sho... | stack_v2_sparse_classes_10k_train_000757 | 3,154 | no_license | [
{
"docstring": "test import all good data",
"name": "test_import_data",
"signature": "def test_import_data(self)"
},
{
"docstring": "test for show_rentals",
"name": "test_show_rentals",
"signature": "def test_show_rentals(self)"
},
{
"docstring": "rest for show_available_products... | 4 | stack_v2_sparse_classes_30k_train_004314 | Implement the Python class `TestDatabase` described below.
Class description:
"test for Mongo database.py
Method signatures and docstrings:
- def test_import_data(self): test import all good data
- def test_show_rentals(self): test for show_rentals
- def test_show_available_products(self): rest for show_available_pro... | Implement the Python class `TestDatabase` described below.
Class description:
"test for Mongo database.py
Method signatures and docstrings:
- def test_import_data(self): test import all good data
- def test_show_rentals(self): test for show_rentals
- def test_show_available_products(self): rest for show_available_pro... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class TestDatabase:
""""test for Mongo database.py"""
def test_import_data(self):
"""test import all good data"""
<|body_0|>
def test_show_rentals(self):
"""test for show_rentals"""
<|body_1|>
def test_show_available_products(self):
"""rest for sho... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestDatabase:
""""test for Mongo database.py"""
def test_import_data(self):
"""test import all good data"""
delete_database()
test_import = import_data(self.folder_name, 'inventory.csv', 'customers.csv', 'rental.csv')
self.assertEqual(test_import, ((7, 9, 7), (0, 0, 0)))
... | the_stack_v2_python_sparse | students/ethan_nguyen/Lesson05/assignment/test_unit.py | JavaRod/SP_Python220B_2019 | train | 1 |
236e095119e026f3d122a24d26c154997b812528 | [
"super(Atom_Wise_Convolution, self).__init__()\nself.conv_weights = nn.Linear(input_feature, output_feature)\nself.batch_norm = nn.LayerNorm(output_feature)\nself.UseBN = UseBN\nself.activation = Shifted_softplus()\nself.dropout = nn.Dropout(p=dropout)",
"node_feats = self.conv_weights(node_feats)\nif self.UseBN:... | <|body_start_0|>
super(Atom_Wise_Convolution, self).__init__()
self.conv_weights = nn.Linear(input_feature, output_feature)
self.batch_norm = nn.LayerNorm(output_feature)
self.UseBN = UseBN
self.activation = Shifted_softplus()
self.dropout = nn.Dropout(p=dropout)
<|end_bo... | Performs self convolution to each node | Atom_Wise_Convolution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Atom_Wise_Convolution:
"""Performs self convolution to each node"""
def __init__(self, input_feature: int, output_feature: int, dropout: float=0.2, UseBN: bool=True):
"""Parameters ---------- input_feature: int Size of input feature size output_feature: int Size of output feature siz... | stack_v2_sparse_classes_10k_train_000758 | 18,579 | permissive | [
{
"docstring": "Parameters ---------- input_feature: int Size of input feature size output_feature: int Size of output feature size dropout: float, defult 0.2 p value for dropout between 0.0 to 1.0 UseBN: bool Setting it to True will perform Batch Normalisation",
"name": "__init__",
"signature": "def __... | 2 | stack_v2_sparse_classes_30k_train_002590 | Implement the Python class `Atom_Wise_Convolution` described below.
Class description:
Performs self convolution to each node
Method signatures and docstrings:
- def __init__(self, input_feature: int, output_feature: int, dropout: float=0.2, UseBN: bool=True): Parameters ---------- input_feature: int Size of input fe... | Implement the Python class `Atom_Wise_Convolution` described below.
Class description:
Performs self convolution to each node
Method signatures and docstrings:
- def __init__(self, input_feature: int, output_feature: int, dropout: float=0.2, UseBN: bool=True): Parameters ---------- input_feature: int Size of input fe... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class Atom_Wise_Convolution:
"""Performs self convolution to each node"""
def __init__(self, input_feature: int, output_feature: int, dropout: float=0.2, UseBN: bool=True):
"""Parameters ---------- input_feature: int Size of input feature size output_feature: int Size of output feature siz... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Atom_Wise_Convolution:
"""Performs self convolution to each node"""
def __init__(self, input_feature: int, output_feature: int, dropout: float=0.2, UseBN: bool=True):
"""Parameters ---------- input_feature: int Size of input feature size output_feature: int Size of output feature size dropout: fl... | the_stack_v2_python_sparse | deepchem/models/torch_models/lcnn.py | deepchem/deepchem | train | 4,876 |
3207b24b55371b1f12e102101a7bc8a2abad83d4 | [
"res = []\nif not root:\n return []\n\ndef _recur_func(node, level):\n if len(res) == level:\n res.append([])\n res[level].append(node.val)\n if node.left:\n _recur_func(node.left, level + 1)\n if node.right:\n _recur_func(node.right, level + 1)\n_recur_func(root, 0)\nreturn res"... | <|body_start_0|>
res = []
if not root:
return []
def _recur_func(node, level):
if len(res) == level:
res.append([])
res[level].append(node.val)
if node.left:
_recur_func(node.left, level + 1)
if node.rig... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder_recursion(self, root: TreeNode):
"""递归实现层次遍历二叉树，并逐层返回该层的值列表。 :param root: :return: list"""
<|body_0|>
def levelOrder_iteration_t(self, root: TreeNode):
"""迭代实现层次遍历二叉树，并逐层返回该层的值列表。 :param root: :return: res"""
<|body_1|>
def level... | stack_v2_sparse_classes_10k_train_000759 | 3,953 | no_license | [
{
"docstring": "递归实现层次遍历二叉树，并逐层返回该层的值列表。 :param root: :return: list",
"name": "levelOrder_recursion",
"signature": "def levelOrder_recursion(self, root: TreeNode)"
},
{
"docstring": "迭代实现层次遍历二叉树，并逐层返回该层的值列表。 :param root: :return: res",
"name": "levelOrder_iteration_t",
"signature": "def ... | 3 | stack_v2_sparse_classes_30k_val_000300 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder_recursion(self, root: TreeNode): 递归实现层次遍历二叉树，并逐层返回该层的值列表。 :param root: :return: list
- def levelOrder_iteration_t(self, root: TreeNode): 迭代实现层次遍历二叉树，并逐层返回该层的值列表。 :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder_recursion(self, root: TreeNode): 递归实现层次遍历二叉树，并逐层返回该层的值列表。 :param root: :return: list
- def levelOrder_iteration_t(self, root: TreeNode): 迭代实现层次遍历二叉树，并逐层返回该层的值列表。 :... | 62ad010a992c031e8c0fe4d1a9b6f9364f96ed4c | <|skeleton|>
class Solution:
def levelOrder_recursion(self, root: TreeNode):
"""递归实现层次遍历二叉树，并逐层返回该层的值列表。 :param root: :return: list"""
<|body_0|>
def levelOrder_iteration_t(self, root: TreeNode):
"""迭代实现层次遍历二叉树，并逐层返回该层的值列表。 :param root: :return: res"""
<|body_1|>
def level... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder_recursion(self, root: TreeNode):
"""递归实现层次遍历二叉树，并逐层返回该层的值列表。 :param root: :return: list"""
res = []
if not root:
return []
def _recur_func(node, level):
if len(res) == level:
res.append([])
res[level]... | the_stack_v2_python_sparse | leetcode/solved/102_.py | usnnu/python_foundation | train | 0 | |
e07e35976407d5147f6c4b3c88d7e9014483afa4 | [
"self._d = d\nself._seed = seed\nself._inv_transform = inv_transform\nif inv_transform:\n sobol_dim = d\nelse:\n sobol_dim = 2 * math.ceil(d / 2)\nself._sobol_engine = SobolEngine(dimension=sobol_dim, scramble=True, seed=seed)",
"samples = self._sobol_engine.draw(n, dtype=dtype)\nif self._inv_transform:\n ... | <|body_start_0|>
self._d = d
self._seed = seed
self._inv_transform = inv_transform
if inv_transform:
sobol_dim = d
else:
sobol_dim = 2 * math.ceil(d / 2)
self._sobol_engine = SobolEngine(dimension=sobol_dim, scramble=True, seed=seed)
<|end_body_0|>... | Engine for qMC sampling from a Multivariate Normal `N(0, I_d)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=True`. Example: >>> engine = NormalQMCEngine(3) >>> samples = engine.draw(16) | NormalQMCEngine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NormalQMCEngine:
"""Engine for qMC sampling from a Multivariate Normal `N(0, I_d)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=True`. Example: >>> engine = NormalQMCEn... | stack_v2_sparse_classes_10k_train_000760 | 6,555 | permissive | [
{
"docstring": "Engine for drawing qMC samples from a multivariate normal `N(0, I_d)`. Args: d: The dimension of the samples. seed: The seed with which to seed the random number generator of the underlying SobolEngine. inv_transform: If True, use inverse transform instead of Box-Muller.",
"name": "__init__"... | 2 | stack_v2_sparse_classes_30k_train_001870 | Implement the Python class `NormalQMCEngine` described below.
Class description:
Engine for qMC sampling from a Multivariate Normal `N(0, I_d)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=T... | Implement the Python class `NormalQMCEngine` described below.
Class description:
Engine for qMC sampling from a Multivariate Normal `N(0, I_d)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=T... | 4cc5ed59b2e8a9c780f786830c548e05cc74d53c | <|skeleton|>
class NormalQMCEngine:
"""Engine for qMC sampling from a Multivariate Normal `N(0, I_d)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=True`. Example: >>> engine = NormalQMCEn... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NormalQMCEngine:
"""Engine for qMC sampling from a Multivariate Normal `N(0, I_d)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=True`. Example: >>> engine = NormalQMCEngine(3) >>> s... | the_stack_v2_python_sparse | botorch/sampling/qmc.py | pytorch/botorch | train | 2,891 |
bff211b69b352fbe9174ecaa7060f6d379c6c711 | [
"self.control_points = Vec3.list(control_points)\nself.degree = degree\nself.closed = closed",
"if self.closed:\n spline = closed_uniform_bspline(self.control_points, order=self.degree + 1)\nelse:\n spline = BSpline(self.control_points, order=self.degree + 1)\nvertices = spline.approximate(segments)\nif ucs... | <|body_start_0|>
self.control_points = Vec3.list(control_points)
self.degree = degree
self.closed = closed
<|end_body_0|>
<|body_start_1|>
if self.closed:
spline = closed_uniform_bspline(self.control_points, order=self.degree + 1)
else:
spline = BSpline(s... | DXF R12 supports 2D B-splines, but Autodesk do not document the usage in the DXF Reference. The base entity for splines in DXF R12 is the POLYLINE entity. The spline itself is always in a plane, but as any 2D entity, the spline can be transformed into the 3D object by elevation and extrusion (:ref:`OCS`, :ref:`UCS`). T... | R12Spline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class R12Spline:
"""DXF R12 supports 2D B-splines, but Autodesk do not document the usage in the DXF Reference. The base entity for splines in DXF R12 is the POLYLINE entity. The spline itself is always in a plane, but as any 2D entity, the spline can be transformed into the 3D object by elevation and ... | stack_v2_sparse_classes_10k_train_000761 | 7,650 | permissive | [
{
"docstring": "Args: control_points: B-spline control frame vertices degree: degree of B-spline, only 2 and 3 is supported closed: ``True`` for closed curve",
"name": "__init__",
"signature": "def __init__(self, control_points: Iterable[UVec], degree: int=2, closed: bool=True)"
},
{
"docstring"... | 3 | null | Implement the Python class `R12Spline` described below.
Class description:
DXF R12 supports 2D B-splines, but Autodesk do not document the usage in the DXF Reference. The base entity for splines in DXF R12 is the POLYLINE entity. The spline itself is always in a plane, but as any 2D entity, the spline can be transform... | Implement the Python class `R12Spline` described below.
Class description:
DXF R12 supports 2D B-splines, but Autodesk do not document the usage in the DXF Reference. The base entity for splines in DXF R12 is the POLYLINE entity. The spline itself is always in a plane, but as any 2D entity, the spline can be transform... | ba6ab0264dcb6833173042a37b1b5ae878d75113 | <|skeleton|>
class R12Spline:
"""DXF R12 supports 2D B-splines, but Autodesk do not document the usage in the DXF Reference. The base entity for splines in DXF R12 is the POLYLINE entity. The spline itself is always in a plane, but as any 2D entity, the spline can be transformed into the 3D object by elevation and ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class R12Spline:
"""DXF R12 supports 2D B-splines, but Autodesk do not document the usage in the DXF Reference. The base entity for splines in DXF R12 is the POLYLINE entity. The spline itself is always in a plane, but as any 2D entity, the spline can be transformed into the 3D object by elevation and extrusion (:r... | the_stack_v2_python_sparse | src/ezdxf/render/r12spline.py | mozman/ezdxf | train | 750 |
957d1156ec560bbec583cde8a123231ef0151415 | [
"res = {}\nfor vehi in self.browse(cr, uid, ids, context=context):\n res[vehi['id']] = len(vehi.vehi_participants_ids)\nreturn res",
"if context is None:\n context = {}\nif context.get('name'):\n transport_obj = self.pool.get('student.transport')\n transport_data = transport_obj.browse(cr, uid, contex... | <|body_start_0|>
res = {}
for vehi in self.browse(cr, uid, ids, context=context):
res[vehi['id']] = len(vehi.vehi_participants_ids)
return res
<|end_body_0|>
<|body_start_1|>
if context is None:
context = {}
if context.get('name'):
transport_o... | transport_vehicle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class transport_vehicle:
def _participants(self, cr, uid, ids, name, vals, context=None):
"""This method calculate total participants @param self : Object Pointer @param cr : Database Cursor @param uid : Current Logged in User @param ids : Current Records @param name : Functional field's name ... | stack_v2_sparse_classes_10k_train_000762 | 21,327 | no_license | [
{
"docstring": "This method calculate total participants @param self : Object Pointer @param cr : Database Cursor @param uid : Current Logged in User @param ids : Current Records @param name : Functional field's name @param vals : Other arguments @param context : standard Dictionary @return : Dictionary having ... | 2 | null | Implement the Python class `transport_vehicle` described below.
Class description:
Implement the transport_vehicle class.
Method signatures and docstrings:
- def _participants(self, cr, uid, ids, name, vals, context=None): This method calculate total participants @param self : Object Pointer @param cr : Database Curs... | Implement the Python class `transport_vehicle` described below.
Class description:
Implement the transport_vehicle class.
Method signatures and docstrings:
- def _participants(self, cr, uid, ids, name, vals, context=None): This method calculate total participants @param self : Object Pointer @param cr : Database Curs... | c5a5678379649ccdf57a9d55b09b30436428b430 | <|skeleton|>
class transport_vehicle:
def _participants(self, cr, uid, ids, name, vals, context=None):
"""This method calculate total participants @param self : Object Pointer @param cr : Database Cursor @param uid : Current Logged in User @param ids : Current Records @param name : Functional field's name ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class transport_vehicle:
def _participants(self, cr, uid, ids, name, vals, context=None):
"""This method calculate total participants @param self : Object Pointer @param cr : Database Cursor @param uid : Current Logged in User @param ids : Current Records @param name : Functional field's name @param vals : ... | the_stack_v2_python_sparse | education/school_transport/transport.py | adahra/addons | train | 1 | |
1448e8715b7f0dd20ceed73ec4e74d2632c57585 | [
"self.directory = directory\nself.function_table = {}\nself.status = DataPackStatus.INACTIVE\nself.name = directory.split('/')[-1].split('\\\\')[-1]\nself.access = None\nself.description = ''",
"if self.status == DataPackStatus.SYSTEM_ERROR:\n return\ntry:\n if self.status in (DataPackStatus.ACTIVATED, Data... | <|body_start_0|>
self.directory = directory
self.function_table = {}
self.status = DataPackStatus.INACTIVE
self.name = directory.split('/')[-1].split('\\')[-1]
self.access = None
self.description = ''
<|end_body_0|>
<|body_start_1|>
if self.status == DataPackStat... | Class for a single data pack | DataPack | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataPack:
"""Class for a single data pack"""
def __init__(self, directory: str):
"""Will create a new DataPack-object :param directory: where the datapack is located"""
<|body_0|>
async def load(self):
"""Will load the data pack"""
<|body_1|>
def unl... | stack_v2_sparse_classes_10k_train_000763 | 10,029 | permissive | [
{
"docstring": "Will create a new DataPack-object :param directory: where the datapack is located",
"name": "__init__",
"signature": "def __init__(self, directory: str)"
},
{
"docstring": "Will load the data pack",
"name": "load",
"signature": "async def load(self)"
},
{
"docstri... | 4 | stack_v2_sparse_classes_30k_train_002945 | Implement the Python class `DataPack` described below.
Class description:
Class for a single data pack
Method signatures and docstrings:
- def __init__(self, directory: str): Will create a new DataPack-object :param directory: where the datapack is located
- async def load(self): Will load the data pack
- def unload(... | Implement the Python class `DataPack` described below.
Class description:
Class for a single data pack
Method signatures and docstrings:
- def __init__(self, directory: str): Will create a new DataPack-object :param directory: where the datapack is located
- async def load(self): Will load the data pack
- def unload(... | 644ef36a70c45a70820f6f6069b2f36545a187e5 | <|skeleton|>
class DataPack:
"""Class for a single data pack"""
def __init__(self, directory: str):
"""Will create a new DataPack-object :param directory: where the datapack is located"""
<|body_0|>
async def load(self):
"""Will load the data pack"""
<|body_1|>
def unl... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DataPack:
"""Class for a single data pack"""
def __init__(self, directory: str):
"""Will create a new DataPack-object :param directory: where the datapack is located"""
self.directory = directory
self.function_table = {}
self.status = DataPackStatus.INACTIVE
self.n... | the_stack_v2_python_sparse | mcpython/common/data/DataPacks.py | mcpython4-coding/core | train | 4 |
e6ef78007a4e0ed5904b72b50e2d0e941384de24 | [
"super().__init__()\nself.cost_class = cost_class\nself.cost_bbox = cost_bbox\nself.cost_giou = cost_giou\nassert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, 'all costs cant be 0'",
"bs, num_queries = outputs['pred_logits'].shape[:2]\nout_prob = outputs['pred_logits'].flatten(0, 1).softmax(-1)\nout_bbox ... | <|body_start_0|>
super().__init__()
self.cost_class = cost_class
self.cost_bbox = cost_bbox
self.cost_giou = cost_giou
assert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, 'all costs cant be 0'
<|end_body_0|>
<|body_start_1|>
bs, num_queries = outputs['pred_logits... | This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best predictions, while the others are un-matched (... | HungarianMatcher | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HungarianMatcher:
"""This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best pr... | stack_v2_sparse_classes_10k_train_000764 | 4,250 | permissive | [
{
"docstring": "Creates the matcher Params: cost_class: This is the relative weight of the classification error in the matching cost cost_bbox: This is the relative weight of the L1 error of the bounding box coordinates in the matching cost cost_giou: This is the relative weight of the giou loss of the bounding... | 2 | stack_v2_sparse_classes_30k_train_007346 | Implement the Python class `HungarianMatcher` described below.
Class description:
This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case,... | Implement the Python class `HungarianMatcher` described below.
Class description:
This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case,... | 3af9fa878e73b6894ce3596450a8d9b89d918ca9 | <|skeleton|>
class HungarianMatcher:
"""This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best pr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HungarianMatcher:
"""This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best predictions, wh... | the_stack_v2_python_sparse | models/matcher.py | facebookresearch/detr | train | 12,104 |
afb56ce2864fb14579beda356238f2d3c34d755d | [
"if root == None:\n return '[]'\nque = []\nque.append(root)\nres = []\nwhile any(que):\n next_level = []\n while len(que) > 0:\n cur = que.pop(0)\n if cur == None:\n res.append(None)\n next_level.append(None)\n next_level.append(None)\n else:\n ... | <|body_start_0|>
if root == None:
return '[]'
que = []
que.append(root)
res = []
while any(que):
next_level = []
while len(que) > 0:
cur = que.pop(0)
if cur == None:
res.append(None)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_000765 | 3,172 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_004524 | 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:... | 0d6f414e7610fedb2ec4818ecf88d51aa69e1355 | <|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 root == None:
return '[]'
que = []
que.append(root)
res = []
while any(que):
next_level = []
while len(que) > 0:
... | the_stack_v2_python_sparse | 0449_Serialize_and_Deserialize_BST.py | chien-wei/LeetCode | train | 0 | |
812248a8164863b123be84ff54d8eaf319a53f08 | [
"super().__init__(main_window)\nstacked_layout = QStackedLayout()\nmain_window.communication.item_selected.connect(stacked_layout.setCurrentIndex)\nself.setLayout(stacked_layout)\nself.showEvent = self._get_show_event(main_window)\nfor item in items:\n frame = AttributesFrame(main_window=main_window, item=item)\... | <|body_start_0|>
super().__init__(main_window)
stacked_layout = QStackedLayout()
main_window.communication.item_selected.connect(stacked_layout.setCurrentIndex)
self.setLayout(stacked_layout)
self.showEvent = self._get_show_event(main_window)
for item in items:
... | DataWidget | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataWidget:
def __init__(self, main_window, items):
"""Widget contains items with inputs."""
<|body_0|>
def _get_show_event(main_window):
"""Emit signal to hide ActionButton."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__(main_wind... | stack_v2_sparse_classes_10k_train_000766 | 946 | no_license | [
{
"docstring": "Widget contains items with inputs.",
"name": "__init__",
"signature": "def __init__(self, main_window, items)"
},
{
"docstring": "Emit signal to hide ActionButton.",
"name": "_get_show_event",
"signature": "def _get_show_event(main_window)"
}
] | 2 | null | Implement the Python class `DataWidget` described below.
Class description:
Implement the DataWidget class.
Method signatures and docstrings:
- def __init__(self, main_window, items): Widget contains items with inputs.
- def _get_show_event(main_window): Emit signal to hide ActionButton. | Implement the Python class `DataWidget` described below.
Class description:
Implement the DataWidget class.
Method signatures and docstrings:
- def __init__(self, main_window, items): Widget contains items with inputs.
- def _get_show_event(main_window): Emit signal to hide ActionButton.
<|skeleton|>
class DataWidge... | 606e188e88ee3a2b2e1daee60c71948c678228e1 | <|skeleton|>
class DataWidget:
def __init__(self, main_window, items):
"""Widget contains items with inputs."""
<|body_0|>
def _get_show_event(main_window):
"""Emit signal to hide ActionButton."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DataWidget:
def __init__(self, main_window, items):
"""Widget contains items with inputs."""
super().__init__(main_window)
stacked_layout = QStackedLayout()
main_window.communication.item_selected.connect(stacked_layout.setCurrentIndex)
self.setLayout(stacked_layout)
... | the_stack_v2_python_sparse | Hospital-Helper-2-master/app/gui/data_widget.py | JoaoBueno/estudos-python | train | 2 | |
49ce6e2a0ecf10003ba26fdd3def56ec42be51db | [
"mro = self.CustomError.mro()\nassert 'RuntimeError' == mro[1].__name__\nassert 'Exception' == mro[2].__name__\nassert 'BaseException' == mro[3].__name__",
"result = None\ntry:\n self.fail('Oops')\nexcept Exception as e:\n result = 'exception handled'\n e2 = e\nassert 'exception handled' == result\nasser... | <|body_start_0|>
mro = self.CustomError.mro()
assert 'RuntimeError' == mro[1].__name__
assert 'Exception' == mro[2].__name__
assert 'BaseException' == mro[3].__name__
<|end_body_0|>
<|body_start_1|>
result = None
try:
self.fail('Oops')
except Exceptio... | 파이썬으로 코딩을 할 때 피할 수는 있지만 피하기 어려운 것이 에러입니다. 파이썬에서는 이들을 예외 (Exception) 이라고 부릅니다. pyt 이번에는 파이썬의 예외 처리는 어떻게 하고 어떤 예외들이 있는지 등 보겠습니다. | PythonExceptions | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PythonExceptions:
"""파이썬으로 코딩을 할 때 피할 수는 있지만 피하기 어려운 것이 에러입니다. 파이썬에서는 이들을 예외 (Exception) 이라고 부릅니다. pyt 이번에는 파이썬의 예외 처리는 어떻게 하고 어떤 예외들이 있는지 등 보겠습니다."""
def test_about_exception_inheritance(self):
"""여기에서 나오는 `mro` 에 대해서는 자세히 아실 필요는 없습니다. 다만 해당 테스트를 통과하면서 어떤 것들이 나오는지 살펴보시면 될 것 같습니다. 직접... | stack_v2_sparse_classes_10k_train_000767 | 21,323 | no_license | [
{
"docstring": "여기에서 나오는 `mro` 에 대해서는 자세히 아실 필요는 없습니다. 다만 해당 테스트를 통과하면서 어떤 것들이 나오는지 살펴보시면 될 것 같습니다. 직접 파이썬으로 확인해 보시면서 테스트를 통과해주세요",
"name": "test_about_exception_inheritance",
"signature": "def test_about_exception_inheritance(self)"
},
{
"docstring": "try... except 는 파이썬에서 예외처리할 때 사용되는 매우 중요한 기... | 5 | stack_v2_sparse_classes_30k_train_006345 | Implement the Python class `PythonExceptions` described below.
Class description:
파이썬으로 코딩을 할 때 피할 수는 있지만 피하기 어려운 것이 에러입니다. 파이썬에서는 이들을 예외 (Exception) 이라고 부릅니다. pyt 이번에는 파이썬의 예외 처리는 어떻게 하고 어떤 예외들이 있는지 등 보겠습니다.
Method signatures and docstrings:
- def test_about_exception_inheritance(self): 여기에서 나오는 `mro` 에 대해서는 자세히 아실 ... | Implement the Python class `PythonExceptions` described below.
Class description:
파이썬으로 코딩을 할 때 피할 수는 있지만 피하기 어려운 것이 에러입니다. 파이썬에서는 이들을 예외 (Exception) 이라고 부릅니다. pyt 이번에는 파이썬의 예외 처리는 어떻게 하고 어떤 예외들이 있는지 등 보겠습니다.
Method signatures and docstrings:
- def test_about_exception_inheritance(self): 여기에서 나오는 `mro` 에 대해서는 자세히 아실 ... | 8dbd1eea6195df8b0dc1798d1ba2e27929c4eda7 | <|skeleton|>
class PythonExceptions:
"""파이썬으로 코딩을 할 때 피할 수는 있지만 피하기 어려운 것이 에러입니다. 파이썬에서는 이들을 예외 (Exception) 이라고 부릅니다. pyt 이번에는 파이썬의 예외 처리는 어떻게 하고 어떤 예외들이 있는지 등 보겠습니다."""
def test_about_exception_inheritance(self):
"""여기에서 나오는 `mro` 에 대해서는 자세히 아실 필요는 없습니다. 다만 해당 테스트를 통과하면서 어떤 것들이 나오는지 살펴보시면 될 것 같습니다. 직접... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PythonExceptions:
"""파이썬으로 코딩을 할 때 피할 수는 있지만 피하기 어려운 것이 에러입니다. 파이썬에서는 이들을 예외 (Exception) 이라고 부릅니다. pyt 이번에는 파이썬의 예외 처리는 어떻게 하고 어떤 예외들이 있는지 등 보겠습니다."""
def test_about_exception_inheritance(self):
"""여기에서 나오는 `mro` 에 대해서는 자세히 아실 필요는 없습니다. 다만 해당 테스트를 통과하면서 어떤 것들이 나오는지 살펴보시면 될 것 같습니다. 직접 파이썬으로 확인해 보시... | the_stack_v2_python_sparse | Python/src/Part_2.py | effection00/Study-Record | train | 0 |
7c7471a52f98172edc9172da3e1782b9bfa80fc9 | [
"if not root:\n return []\ndata = []\nqueue = deque()\nqueue.append(root)\nwhile queue:\n node = queue.popleft()\n if not node:\n data.append('#')\n continue\n data.append(node.val)\n queue.append(node.left)\n queue.append(node.right)\nwhile data[-1] == '#':\n data.pop()\nreturn d... | <|body_start_0|>
if not root:
return []
data = []
queue = deque()
queue.append(root)
while queue:
node = queue.popleft()
if not node:
data.append('#')
continue
data.append(node.val)
queue.... | 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_000768 | 1,914 | 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:... | b75b06fa1551f5e4d8a559ef64e1ac29db79c083 | <|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 []
data = []
queue = deque()
queue.append(root)
while queue:
node = queue.popleft()
if not node:
... | the_stack_v2_python_sparse | Python/297.py | arnabs542/Leetcode-38 | train | 0 | |
62da1c75cfc3b08a5c306e4bee070e1e3de30cf2 | [
"self.snake = [[0, 0]]\nself.food = food\nself.width = width\nself.height = height\nself.eat = 0",
"x, y = self.snake[0]\nif direction == 'U':\n x = x - 1\nelif direction == 'L':\n y = y - 1\nelif direction == 'R':\n y = y + 1\nelif direction == 'D':\n x = x + 1\nif 0 <= x < self.height and 0 <= y < s... | <|body_start_0|>
self.snake = [[0, 0]]
self.food = food
self.width = width
self.height = height
self.eat = 0
<|end_body_0|>
<|body_start_1|>
x, y = self.snake[0]
if direction == 'U':
x = x - 1
elif direction == 'L':
y = y - 1
... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], t... | stack_v2_sparse_classes_10k_train_000769 | 15,245 | no_license | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0].",
"name": "__init__",
"signature": "def __init__(self, widt... | 2 | null | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food: List[List[int]]): Initialize your data structure here. @param width - screen width @param height - screen height @param food -... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food: List[List[int]]): Initialize your data structure here. @param width - screen width @param height - screen height @param food -... | 035ef08434fa1ca781a6fb2f9eed3538b7d20c02 | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is a... | the_stack_v2_python_sparse | leetcode_python/Design/design-snake-game.py | yennanliu/CS_basics | train | 64 | |
af7701e084d96e61f35705798cf82747af601c85 | [
"n = len(nums) - 1\nleft, right = (1, n)\nwhile left < right:\n mid = left + (right - left) // 2\n count = 0\n for num in nums:\n if num <= mid:\n count += 1\n if count > mid:\n right = mid\n else:\n left = mid + 1\nreturn right",
"slow, fast = (nums[0], nums[nums[0]... | <|body_start_0|>
n = len(nums) - 1
left, right = (1, n)
while left < right:
mid = left + (right - left) // 2
count = 0
for num in nums:
if num <= mid:
count += 1
if count > mid:
right = mid
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicate1(self, nums: List[int]) -> int:
"""一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。"""
<|body_0|>
def findDuplicate2(self, nums: List[int]) -> int:
"""快慢指针，比较难理解，参考142题解"""
... | stack_v2_sparse_classes_10k_train_000770 | 2,089 | no_license | [
{
"docstring": "一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。",
"name": "findDuplicate1",
"signature": "def findDuplicate1(self, nums: List[int]) -> int"
},
{
"docstring": "快慢指针，比较难理解，参考142题解",
"name": "findDuplicate2",
"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate1(self, nums: List[int]) -> int: 一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。
- def findDupli... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate1(self, nums: List[int]) -> int: 一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。
- def findDupli... | 2bbb1640589aab34f2bc42489283033cc11fb885 | <|skeleton|>
class Solution:
def findDuplicate1(self, nums: List[int]) -> int:
"""一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。"""
<|body_0|>
def findDuplicate2(self, nums: List[int]) -> int:
"""快慢指针，比较难理解，参考142题解"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicate1(self, nums: List[int]) -> int:
"""一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。"""
n = len(nums) - 1
left, right = (1, n)
while left < right:
mid = left + (right - left) ... | the_stack_v2_python_sparse | 287_find-the-duplicate-number.py | helloocc/algorithm | train | 1 | |
910653a277a53b772235680a3a5f51295e1fc6ca | [
"try:\n params = request._serialize()\n headers = request.headers\n body = self.call('DescribeKBComponent', params, headers=headers)\n response = json.loads(body)\n model = models.DescribeKBComponentResponse()\n model._deserialize(response['Response'])\n return model\nexcept Exception as e:\n ... | <|body_start_0|>
try:
params = request._serialize()
headers = request.headers
body = self.call('DescribeKBComponent', params, headers=headers)
response = json.loads(body)
model = models.DescribeKBComponentResponse()
model._deserialize(respo... | BscaClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BscaClient:
def DescribeKBComponent(self, request):
"""本接口(DescribeKBComponent)用于在知识库中查询开源组件信息。本接口根据用户输入的PURL在知识库中寻找对应的开源组件，其中Name为必填字段。 :param request: Request instance for DescribeKBComponent. :type request: :class:`tencentcloud.bsca.v20210811.models.DescribeKBComponentRequest` :rtype:... | stack_v2_sparse_classes_10k_train_000771 | 5,975 | permissive | [
{
"docstring": "本接口(DescribeKBComponent)用于在知识库中查询开源组件信息。本接口根据用户输入的PURL在知识库中寻找对应的开源组件，其中Name为必填字段。 :param request: Request instance for DescribeKBComponent. :type request: :class:`tencentcloud.bsca.v20210811.models.DescribeKBComponentRequest` :rtype: :class:`tencentcloud.bsca.v20210811.models.DescribeKBComponent... | 5 | null | Implement the Python class `BscaClient` described below.
Class description:
Implement the BscaClient class.
Method signatures and docstrings:
- def DescribeKBComponent(self, request): 本接口(DescribeKBComponent)用于在知识库中查询开源组件信息。本接口根据用户输入的PURL在知识库中寻找对应的开源组件，其中Name为必填字段。 :param request: Request instance for DescribeKBCompo... | Implement the Python class `BscaClient` described below.
Class description:
Implement the BscaClient class.
Method signatures and docstrings:
- def DescribeKBComponent(self, request): 本接口(DescribeKBComponent)用于在知识库中查询开源组件信息。本接口根据用户输入的PURL在知识库中寻找对应的开源组件，其中Name为必填字段。 :param request: Request instance for DescribeKBCompo... | 6baf00a5a56ba58b6a1123423e0a1422d17a0201 | <|skeleton|>
class BscaClient:
def DescribeKBComponent(self, request):
"""本接口(DescribeKBComponent)用于在知识库中查询开源组件信息。本接口根据用户输入的PURL在知识库中寻找对应的开源组件，其中Name为必填字段。 :param request: Request instance for DescribeKBComponent. :type request: :class:`tencentcloud.bsca.v20210811.models.DescribeKBComponentRequest` :rtype:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BscaClient:
def DescribeKBComponent(self, request):
"""本接口(DescribeKBComponent)用于在知识库中查询开源组件信息。本接口根据用户输入的PURL在知识库中寻找对应的开源组件，其中Name为必填字段。 :param request: Request instance for DescribeKBComponent. :type request: :class:`tencentcloud.bsca.v20210811.models.DescribeKBComponentRequest` :rtype: :class:`tence... | the_stack_v2_python_sparse | tencentcloud/bsca/v20210811/bsca_client.py | TencentCloud/tencentcloud-sdk-python | train | 594 | |
723c65584fffc4099c0923cb6e3f67b1090099fc | [
"date_time = None\ncreation_time = self._GetJSONValue(json_dict, 'CreationTime')\nif creation_time:\n try:\n date_time = dfdatetime_time_elements.TimeElements()\n date_time.CopyFromStringISO8601(creation_time)\n except ValueError as exception:\n parser_mediator.ProduceExtractionWarning('U... | <|body_start_0|>
date_time = None
creation_time = self._GetJSONValue(json_dict, 'CreationTime')
if creation_time:
try:
date_time = dfdatetime_time_elements.TimeElements()
date_time.CopyFromStringISO8601(creation_time)
except ValueError as e... | JSON-L parser plugin for Microsoft (Office) 365 audit log files. | Microsoft365AuditLogJSONLPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Microsoft365AuditLogJSONLPlugin:
"""JSON-L parser plugin for Microsoft (Office) 365 audit log files."""
def _ParseRecord(self, parser_mediator, json_dict):
"""Parses a Microsoft (Office) 365 audit log record. Args: parser_mediator (ParserMediator): mediates interactions between parse... | stack_v2_sparse_classes_10k_train_000772 | 4,708 | permissive | [
{
"docstring": "Parses a Microsoft (Office) 365 audit log record. Args: parser_mediator (ParserMediator): mediates interactions between parsers and other components, such as storage and dfVFS. json_dict (dict): JSON dictionary of the log record.",
"name": "_ParseRecord",
"signature": "def _ParseRecord(s... | 2 | null | Implement the Python class `Microsoft365AuditLogJSONLPlugin` described below.
Class description:
JSON-L parser plugin for Microsoft (Office) 365 audit log files.
Method signatures and docstrings:
- def _ParseRecord(self, parser_mediator, json_dict): Parses a Microsoft (Office) 365 audit log record. Args: parser_media... | Implement the Python class `Microsoft365AuditLogJSONLPlugin` described below.
Class description:
JSON-L parser plugin for Microsoft (Office) 365 audit log files.
Method signatures and docstrings:
- def _ParseRecord(self, parser_mediator, json_dict): Parses a Microsoft (Office) 365 audit log record. Args: parser_media... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class Microsoft365AuditLogJSONLPlugin:
"""JSON-L parser plugin for Microsoft (Office) 365 audit log files."""
def _ParseRecord(self, parser_mediator, json_dict):
"""Parses a Microsoft (Office) 365 audit log record. Args: parser_mediator (ParserMediator): mediates interactions between parse... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Microsoft365AuditLogJSONLPlugin:
"""JSON-L parser plugin for Microsoft (Office) 365 audit log files."""
def _ParseRecord(self, parser_mediator, json_dict):
"""Parses a Microsoft (Office) 365 audit log record. Args: parser_mediator (ParserMediator): mediates interactions between parsers and other ... | the_stack_v2_python_sparse | plaso/parsers/jsonl_plugins/microsoft365_audit_log.py | log2timeline/plaso | train | 1,506 |
fee352831935669d24c68eafbc5df41218c493d3 | [
"self.file_path = file_path\nself.current_row = 0\nself.workbook = ''\nself.sheet = ''\nself.load_workbook()",
"if os.path.exists(self.file_path):\n temp_workbook = xlrd.open_workbook(self.file_path)\n self.workbook = copy(temp_workbook)\nelse:\n self.workbook = xlwt.Workbook(encoding='utf-8')",
"try:\... | <|body_start_0|>
self.file_path = file_path
self.current_row = 0
self.workbook = ''
self.sheet = ''
self.load_workbook()
<|end_body_0|>
<|body_start_1|>
if os.path.exists(self.file_path):
temp_workbook = xlrd.open_workbook(self.file_path)
self.wor... | It is for printer discovery tests | Excel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Excel:
"""It is for printer discovery tests"""
def __init__(self, file_path):
"""Initialize workbook instance with sheet instance :param file_path: path of Excel file"""
<|body_0|>
def load_workbook(self):
"""Load a workbook :return:"""
<|body_1|>
de... | stack_v2_sparse_classes_10k_train_000773 | 4,409 | no_license | [
{
"docstring": "Initialize workbook instance with sheet instance :param file_path: path of Excel file",
"name": "__init__",
"signature": "def __init__(self, file_path)"
},
{
"docstring": "Load a workbook :return:",
"name": "load_workbook",
"signature": "def load_workbook(self)"
},
{
... | 6 | stack_v2_sparse_classes_30k_train_002666 | Implement the Python class `Excel` described below.
Class description:
It is for printer discovery tests
Method signatures and docstrings:
- def __init__(self, file_path): Initialize workbook instance with sheet instance :param file_path: path of Excel file
- def load_workbook(self): Load a workbook :return:
- def lo... | Implement the Python class `Excel` described below.
Class description:
It is for printer discovery tests
Method signatures and docstrings:
- def __init__(self, file_path): Initialize workbook instance with sheet instance :param file_path: path of Excel file
- def load_workbook(self): Load a workbook :return:
- def lo... | b5230c51d3bc7bb04b3448d1a1fe5a076d8898d5 | <|skeleton|>
class Excel:
"""It is for printer discovery tests"""
def __init__(self, file_path):
"""Initialize workbook instance with sheet instance :param file_path: path of Excel file"""
<|body_0|>
def load_workbook(self):
"""Load a workbook :return:"""
<|body_1|>
de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Excel:
"""It is for printer discovery tests"""
def __init__(self, file_path):
"""Initialize workbook instance with sheet instance :param file_path: path of Excel file"""
self.file_path = file_path
self.current_row = 0
self.workbook = ''
self.sheet = ''
self... | the_stack_v2_python_sparse | MobileApps/libs/ma_misc/excel.py | Amal548/QAMA | train | 0 |
d0076b53aa907cac14adbf074e95388152652485 | [
"super().__init__(z3_mask=z3_mask)\nself.edge_length = edge_length\nself.window_size = window_size",
"z3_mask, result = self._optimize()\nmask = np.zeros((self.edge_length, self.edge_length))\nnum_masks_along_row = math.ceil(self.edge_length / self.window_size)\nfor row in range(self.edge_length):\n for column... | <|body_start_0|>
super().__init__(z3_mask=z3_mask)
self.edge_length = edge_length
self.window_size = window_size
<|end_body_0|>
<|body_start_1|>
z3_mask, result = self._optimize()
mask = np.zeros((self.edge_length, self.edge_length))
num_masks_along_row = math.ceil(self.... | Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask. | ImageOptimizer | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageOptimizer:
"""Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask."""
def __init__(self, z3_mask, window_size, edge_length):
"""Initializer. Args: z... | stack_v2_sparse_classes_10k_train_000774 | 39,568 | permissive | [
{
"docstring": "Initializer. Args: z3_mask: list, contains mask bits as z3 vars. window_size: int, side length of the square mask. edge_length: int, side length of the 2D array (image) whose pixels are to be masked.",
"name": "__init__",
"signature": "def __init__(self, z3_mask, window_size, edge_length... | 2 | null | Implement the Python class `ImageOptimizer` described below.
Class description:
Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask.
Method signatures and docstrings:
- def __init__(self,... | Implement the Python class `ImageOptimizer` described below.
Class description:
Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask.
Method signatures and docstrings:
- def __init__(self,... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class ImageOptimizer:
"""Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask."""
def __init__(self, z3_mask, window_size, edge_length):
"""Initializer. Args: z... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ImageOptimizer:
"""Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask."""
def __init__(self, z3_mask, window_size, edge_length):
"""Initializer. Args: z3_mask: list,... | the_stack_v2_python_sparse | smug_saliency/utils.py | Jimmy-INL/google-research | train | 1 |
b20c07118efd6f48d1a54ef1f6ebb8eb150d7cac | [
"if cls.instance is None:\n cls.instance = super().__new__(cls)\nreturn cls.instance",
"if not MusicPlayer.init_flag:\n print('初始化音乐播放器')\n MusicPlayer.init_flag = True"
] | <|body_start_0|>
if cls.instance is None:
cls.instance = super().__new__(cls)
return cls.instance
<|end_body_0|>
<|body_start_1|>
if not MusicPlayer.init_flag:
print('初始化音乐播放器')
MusicPlayer.init_flag = True
<|end_body_1|>
| MusicPlayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MusicPlayer:
def __new__(cls, *args, **kwargs):
"""重写创建方法"""
<|body_0|>
def __init__(self):
"""重写初始化方法"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if cls.instance is None:
cls.instance = super().__new__(cls)
return cls.instan... | stack_v2_sparse_classes_10k_train_000775 | 2,738 | no_license | [
{
"docstring": "重写创建方法",
"name": "__new__",
"signature": "def __new__(cls, *args, **kwargs)"
},
{
"docstring": "重写初始化方法",
"name": "__init__",
"signature": "def __init__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002054 | Implement the Python class `MusicPlayer` described below.
Class description:
Implement the MusicPlayer class.
Method signatures and docstrings:
- def __new__(cls, *args, **kwargs): 重写创建方法
- def __init__(self): 重写初始化方法 | Implement the Python class `MusicPlayer` described below.
Class description:
Implement the MusicPlayer class.
Method signatures and docstrings:
- def __new__(cls, *args, **kwargs): 重写创建方法
- def __init__(self): 重写初始化方法
<|skeleton|>
class MusicPlayer:
def __new__(cls, *args, **kwargs):
"""重写创建方法"""
... | a4a1ae34daaa2764ee8d7005f414772c12d90c6a | <|skeleton|>
class MusicPlayer:
def __new__(cls, *args, **kwargs):
"""重写创建方法"""
<|body_0|>
def __init__(self):
"""重写初始化方法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MusicPlayer:
def __new__(cls, *args, **kwargs):
"""重写创建方法"""
if cls.instance is None:
cls.instance = super().__new__(cls)
return cls.instance
def __init__(self):
"""重写初始化方法"""
if not MusicPlayer.init_flag:
print('初始化音乐播放器')
Music... | the_stack_v2_python_sparse | 02_面向对象/py_09_单例模式.py | sunweiye12/python-BasicLearning | train | 0 | |
23050faaaaca4daad88eb1029b3ac34fd2f90920 | [
"attribution_key = metrics_for_slice_pb2.AttributionsKey()\nif self.name:\n attribution_key.name = self.name\nif self.model_name:\n attribution_key.model_name = self.model_name\nif self.output_name:\n attribution_key.output_name = self.output_name\nif self.sub_key:\n attribution_key.sub_key.CopyFrom(sel... | <|body_start_0|>
attribution_key = metrics_for_slice_pb2.AttributionsKey()
if self.name:
attribution_key.name = self.name
if self.model_name:
attribution_key.model_name = self.model_name
if self.output_name:
attribution_key.output_name = self.output_na... | An AttributionsKey is a metric key uniquely identifying attributions. | AttributionsKey | [
"BSD-3-Clause",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttributionsKey:
"""An AttributionsKey is a metric key uniquely identifying attributions."""
def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey:
"""Converts key to proto."""
<|body_0|>
def from_proto(pb: metrics_for_slice_pb2.AttributionsKey) -> 'AttributionsKey... | stack_v2_sparse_classes_10k_train_000776 | 44,385 | permissive | [
{
"docstring": "Converts key to proto.",
"name": "to_proto",
"signature": "def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey"
},
{
"docstring": "Configures class from proto.",
"name": "from_proto",
"signature": "def from_proto(pb: metrics_for_slice_pb2.AttributionsKey) -> 'Attr... | 2 | stack_v2_sparse_classes_30k_test_000082 | Implement the Python class `AttributionsKey` described below.
Class description:
An AttributionsKey is a metric key uniquely identifying attributions.
Method signatures and docstrings:
- def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey: Converts key to proto.
- def from_proto(pb: metrics_for_slice_pb2.Attr... | Implement the Python class `AttributionsKey` described below.
Class description:
An AttributionsKey is a metric key uniquely identifying attributions.
Method signatures and docstrings:
- def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey: Converts key to proto.
- def from_proto(pb: metrics_for_slice_pb2.Attr... | ee0d8eff562bfe068a3ffdc4da0472cc90adaf41 | <|skeleton|>
class AttributionsKey:
"""An AttributionsKey is a metric key uniquely identifying attributions."""
def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey:
"""Converts key to proto."""
<|body_0|>
def from_proto(pb: metrics_for_slice_pb2.AttributionsKey) -> 'AttributionsKey... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AttributionsKey:
"""An AttributionsKey is a metric key uniquely identifying attributions."""
def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey:
"""Converts key to proto."""
attribution_key = metrics_for_slice_pb2.AttributionsKey()
if self.name:
attribution_ke... | the_stack_v2_python_sparse | tensorflow_model_analysis/metrics/metric_types.py | tensorflow/model-analysis | train | 1,200 |
5fcbf9e26312bdeb82d6991a2b3d7997501675eb | [
"src_type, src_path = cls.identify_path_type(src)\ndest_type, dest_path = cls.identify_path_type(dest)\nformat_table = {'s3': cls.format_s3_path, 'local': cls.format_local_path}\nsrc_path = format_table[src_type](src_path)[0]\ndest_path, use_src_name = format_table[dest_type](dest_path)\nreturn {'dest': {'path': de... | <|body_start_0|>
src_type, src_path = cls.identify_path_type(src)
dest_type, dest_path = cls.identify_path_type(dest)
format_table = {'s3': cls.format_s3_path, 'local': cls.format_local_path}
src_path = format_table[src_type](src_path)[0]
dest_path, use_src_name = format_table[de... | Path format base class. | FormatPath | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FormatPath:
"""Path format base class."""
def format(cls, src: str, dest: str) -> FormatPathResult:
"""Format the source and destination for use in the file factory."""
<|body_0|>
def format_local_path(path: str, dir_op: bool=True) -> Tuple[str, bool]:
"""Format ... | stack_v2_sparse_classes_10k_train_000777 | 4,460 | permissive | [
{
"docstring": "Format the source and destination for use in the file factory.",
"name": "format",
"signature": "def format(cls, src: str, dest: str) -> FormatPathResult"
},
{
"docstring": "Format the path of local files. Returns whether the destination will keep its own name or take the source'... | 4 | null | Implement the Python class `FormatPath` described below.
Class description:
Path format base class.
Method signatures and docstrings:
- def format(cls, src: str, dest: str) -> FormatPathResult: Format the source and destination for use in the file factory.
- def format_local_path(path: str, dir_op: bool=True) -> Tupl... | Implement the Python class `FormatPath` described below.
Class description:
Path format base class.
Method signatures and docstrings:
- def format(cls, src: str, dest: str) -> FormatPathResult: Format the source and destination for use in the file factory.
- def format_local_path(path: str, dir_op: bool=True) -> Tupl... | 0763b06aee07d2cf3f037a49ca0cb81a048c5deb | <|skeleton|>
class FormatPath:
"""Path format base class."""
def format(cls, src: str, dest: str) -> FormatPathResult:
"""Format the source and destination for use in the file factory."""
<|body_0|>
def format_local_path(path: str, dir_op: bool=True) -> Tuple[str, bool]:
"""Format ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FormatPath:
"""Path format base class."""
def format(cls, src: str, dest: str) -> FormatPathResult:
"""Format the source and destination for use in the file factory."""
src_type, src_path = cls.identify_path_type(src)
dest_type, dest_path = cls.identify_path_type(dest)
for... | the_stack_v2_python_sparse | runway/core/providers/aws/s3/_helpers/format_path.py | onicagroup/runway | train | 156 |
52c9b76566500cea20db5a0f88432ef9581a160c | [
"super().__init__('DiseaseService')\nself.declare_parameter('model_file')\nself.declare_parameter('diseases')\nmodel_file = self.get_parameter('model_file').get_parameter_value().string_value\nself.get_logger().info('Loading Model %s' % model_file)\nself.model = tf.keras.models.load_model(model_file)\nself.bridge =... | <|body_start_0|>
super().__init__('DiseaseService')
self.declare_parameter('model_file')
self.declare_parameter('diseases')
model_file = self.get_parameter('model_file').get_parameter_value().string_value
self.get_logger().info('Loading Model %s' % model_file)
self.model ... | Specification of disease classification service node. Args: None Params: model_file (str): Pretrained TensorFlow model. | DiseaseService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiseaseService:
"""Specification of disease classification service node. Args: None Params: model_file (str): Pretrained TensorFlow model."""
def __init__(self):
"""Initialises the service by creating the cvBridge, loading the model from the given parameter and loading the list of va... | stack_v2_sparse_classes_10k_train_000778 | 4,255 | no_license | [
{
"docstring": "Initialises the service by creating the cvBridge, loading the model from the given parameter and loading the list of valid disease classes.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Callback for handeling incomeing requests. Basically updates dise... | 3 | stack_v2_sparse_classes_30k_train_004656 | Implement the Python class `DiseaseService` described below.
Class description:
Specification of disease classification service node. Args: None Params: model_file (str): Pretrained TensorFlow model.
Method signatures and docstrings:
- def __init__(self): Initialises the service by creating the cvBridge, loading the ... | Implement the Python class `DiseaseService` described below.
Class description:
Specification of disease classification service node. Args: None Params: model_file (str): Pretrained TensorFlow model.
Method signatures and docstrings:
- def __init__(self): Initialises the service by creating the cvBridge, loading the ... | d8d6c05c52673dc90ed7296235196c544461d940 | <|skeleton|>
class DiseaseService:
"""Specification of disease classification service node. Args: None Params: model_file (str): Pretrained TensorFlow model."""
def __init__(self):
"""Initialises the service by creating the cvBridge, loading the model from the given parameter and loading the list of va... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DiseaseService:
"""Specification of disease classification service node. Args: None Params: model_file (str): Pretrained TensorFlow model."""
def __init__(self):
"""Initialises the service by creating the cvBridge, loading the model from the given parameter and loading the list of valid disease c... | the_stack_v2_python_sparse | fruit_detection_component/scripts/disease_service.py | robmosys-tum/PapPercComp | train | 2 |
8bf0b83201a493179a273db5372f82e287190faa | [
"if not head:\n return True\nself.h = head\n\ndef travel(tail):\n if tail.next:\n t = travel(tail.next)\n self.h = self.h.next\n return t and self.h.val == tail.val\n else:\n return self.h.val == tail.val\nreturn travel(head)",
"if not head:\n return True\nr = []\nt = head\... | <|body_start_0|>
if not head:
return True
self.h = head
def travel(tail):
if tail.next:
t = travel(tail.next)
self.h = self.h.next
return t and self.h.val == tail.val
else:
return self.h.val == t... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome1(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not head:
return True
... | stack_v2_sparse_classes_10k_train_000779 | 1,213 | no_license | [
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "isPalindrome1",
"signature": "def isPalindrome1(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, head)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome1(self, head): :type head: ListNode :rtype: bool
- def isPalindrome(self, head): :type head: ListNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome1(self, head): :type head: ListNode :rtype: bool
- def isPalindrome(self, head): :type head: ListNode :rtype: bool
<|skeleton|>
class Solution:
def isPalind... | e5b018493bbd12edcdcd0434f35d9c358106d391 | <|skeleton|>
class Solution:
def isPalindrome1(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome1(self, head):
""":type head: ListNode :rtype: bool"""
if not head:
return True
self.h = head
def travel(tail):
if tail.next:
t = travel(tail.next)
self.h = self.h.next
return t a... | the_stack_v2_python_sparse | py/leetcode/234.py | wfeng1991/learnpy | train | 0 | |
c979fb8409696f1d1e25d2716c8f6b0404e5ad1f | [
"from .wrapper import NCNNWrapper\nif deploy_cfg:\n backend_config = get_backend_config(deploy_cfg)\n use_vulkan = backend_config.get('use_vulkan', False)\nelse:\n use_vulkan = False\nreturn NCNNWrapper(param_file=backend_files[0], bin_file=backend_files[1], output_names=output_names, use_vulkan=use_vulkan... | <|body_start_0|>
from .wrapper import NCNNWrapper
if deploy_cfg:
backend_config = get_backend_config(deploy_cfg)
use_vulkan = backend_config.get('use_vulkan', False)
else:
use_vulkan = False
return NCNNWrapper(param_file=backend_files[0], bin_file=back... | NCNNManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NCNNManager:
def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: Optional[Any]=None, **kwargs):
"""Build the wrapper for the backend model. Args: backend_files (Sequence... | stack_v2_sparse_classes_10k_train_000780 | 5,173 | permissive | [
{
"docstring": "Build the wrapper for the backend model. Args: backend_files (Sequence[str]): Backend files. device (str, optional): The device info. Defaults to 'cpu'. input_names (Optional[Sequence[str]], optional): input names. Defaults to None. output_names (Optional[Sequence[str]], optional): output names.... | 5 | stack_v2_sparse_classes_30k_train_005210 | Implement the Python class `NCNNManager` described below.
Class description:
Implement the NCNNManager class.
Method signatures and docstrings:
- def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: O... | Implement the Python class `NCNNManager` described below.
Class description:
Implement the NCNNManager class.
Method signatures and docstrings:
- def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: O... | 5479c8774f5b88d7ed9d399d4e305cb42cc2e73a | <|skeleton|>
class NCNNManager:
def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: Optional[Any]=None, **kwargs):
"""Build the wrapper for the backend model. Args: backend_files (Sequence... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NCNNManager:
def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: Optional[Any]=None, **kwargs):
"""Build the wrapper for the backend model. Args: backend_files (Sequence[str]): Backen... | the_stack_v2_python_sparse | mmdeploy/backend/ncnn/backend_manager.py | open-mmlab/mmdeploy | train | 2,164 | |
c0f3183c2e6059364952387a0aeea4b781730ee7 | [
"if len(intervals) == 0:\n return [newInterval]\nfor i in range(len(intervals)):\n if i == 0 and intervals[0].start >= newInterval.start:\n intervals.insert(0, newInterval)\n break\n if intervals[i].start <= newInterval.start:\n if intervals[i].end >= newInterval.start:\n in... | <|body_start_0|>
if len(intervals) == 0:
return [newInterval]
for i in range(len(intervals)):
if i == 0 and intervals[0].start >= newInterval.start:
intervals.insert(0, newInterval)
break
if intervals[i].start <= newInterval.start:
... | Ex57 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ex57:
def insert(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]"""
<|body_0|>
def merge(self, intervals):
""":type intervals: List[Interval] :rtype: List[Interval]"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_10k_train_000781 | 4,210 | no_license | [
{
"docstring": ":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]",
"name": "insert",
"signature": "def insert(self, intervals, newInterval)"
},
{
"docstring": ":type intervals: List[Interval] :rtype: List[Interval]",
"name": "merge",
"signature": "def me... | 2 | null | Implement the Python class `Ex57` described below.
Class description:
Implement the Ex57 class.
Method signatures and docstrings:
- def insert(self, intervals, newInterval): :type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]
- def merge(self, intervals): :type intervals: List[Interval]... | Implement the Python class `Ex57` described below.
Class description:
Implement the Ex57 class.
Method signatures and docstrings:
- def insert(self, intervals, newInterval): :type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]
- def merge(self, intervals): :type intervals: List[Interval]... | 8f9327a1879949f61b462cc6c82e00e7c27b8b07 | <|skeleton|>
class Ex57:
def insert(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]"""
<|body_0|>
def merge(self, intervals):
""":type intervals: List[Interval] :rtype: List[Interval]"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Ex57:
def insert(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]"""
if len(intervals) == 0:
return [newInterval]
for i in range(len(intervals)):
if i == 0 and intervals[0].start >= newInterval.... | the_stack_v2_python_sparse | LeetCode/Ex0/Ex57.py | JasonVann/CrackingCodingInterview | train | 0 | |
df4d3c58825ba83a47f08c1c2dac58d23b94e7aa | [
"n = len(nums)\n\n@lru_cache(None)\ndef dfs(total):\n if total > target:\n return 0\n if total == target:\n return 1\n result = 0\n for num in nums:\n result += dfs(total + num)\n return result\nreturn dfs(0)",
"dp = [0] * (target + 1)\ndp[0] = 1\nfor i in range(1, target + 1):... | <|body_start_0|>
n = len(nums)
@lru_cache(None)
def dfs(total):
if total > target:
return 0
if total == target:
return 1
result = 0
for num in nums:
result += dfs(total + num)
return resu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DFS"""
<|body_0|>
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DP, Time: O(n*target), Space: O(target)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_000782 | 980 | no_license | [
{
"docstring": "DFS",
"name": "combinationSum4",
"signature": "def combinationSum4(self, nums: List[int], target: int) -> int"
},
{
"docstring": "DP, Time: O(n*target), Space: O(target)",
"name": "combinationSum4",
"signature": "def combinationSum4(self, nums: List[int], target: int) -> ... | 2 | stack_v2_sparse_classes_30k_train_006090 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum4(self, nums: List[int], target: int) -> int: DFS
- def combinationSum4(self, nums: List[int], target: int) -> int: DP, Time: O(n*target), Space: O(target) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum4(self, nums: List[int], target: int) -> int: DFS
- def combinationSum4(self, nums: List[int], target: int) -> int: DP, Time: O(n*target), Space: O(target)
<|s... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DFS"""
<|body_0|>
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DP, Time: O(n*target), Space: O(target)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DFS"""
n = len(nums)
@lru_cache(None)
def dfs(total):
if total > target:
return 0
if total == target:
return 1
result = 0
... | the_stack_v2_python_sparse | python/377-Combination Sum IV.py | cwza/leetcode | train | 0 | |
a5b0584ea5548fdd57e313ef050bec4723fb3293 | [
"result = []\nfor c in range(C):\n for r in range(R):\n result.append([abs(r - r0), abs(c - c0)])\nreturn result",
"from collections import defaultdict\ndistance = defaultdict(list)\nfor r in range(R):\n for c in range(C):\n distance[abs(r - r0) + abs(c - c0)].append([r, c])\nresult = []\nfor ... | <|body_start_0|>
result = []
for c in range(C):
for r in range(R):
result.append([abs(r - r0), abs(c - c0)])
return result
<|end_body_0|>
<|body_start_1|>
from collections import defaultdict
distance = defaultdict(list)
for r in range(R):
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _allCellsDistOrder(self, R, C, r0, c0):
""":type R: int :type C: int :type r0: int :type c0: int :rtype: List[List[int]]"""
<|body_0|>
def allCellsDistOrder(self, R, C, r0, c0):
""":type R: int :type C: int :type r0: int :type c0: int :rtype: List[List[... | stack_v2_sparse_classes_10k_train_000783 | 2,764 | permissive | [
{
"docstring": ":type R: int :type C: int :type r0: int :type c0: int :rtype: List[List[int]]",
"name": "_allCellsDistOrder",
"signature": "def _allCellsDistOrder(self, R, C, r0, c0)"
},
{
"docstring": ":type R: int :type C: int :type r0: int :type c0: int :rtype: List[List[int]]",
"name": "... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _allCellsDistOrder(self, R, C, r0, c0): :type R: int :type C: int :type r0: int :type c0: int :rtype: List[List[int]]
- def allCellsDistOrder(self, R, C, r0, c0): :type R: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _allCellsDistOrder(self, R, C, r0, c0): :type R: int :type C: int :type r0: int :type c0: int :rtype: List[List[int]]
- def allCellsDistOrder(self, R, C, r0, c0): :type R: in... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _allCellsDistOrder(self, R, C, r0, c0):
""":type R: int :type C: int :type r0: int :type c0: int :rtype: List[List[int]]"""
<|body_0|>
def allCellsDistOrder(self, R, C, r0, c0):
""":type R: int :type C: int :type r0: int :type c0: int :rtype: List[List[... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def _allCellsDistOrder(self, R, C, r0, c0):
""":type R: int :type C: int :type r0: int :type c0: int :rtype: List[List[int]]"""
result = []
for c in range(C):
for r in range(R):
result.append([abs(r - r0), abs(c - c0)])
return result
d... | the_stack_v2_python_sparse | 1030.matrix-cells-in-distance-order.py | windard/leeeeee | train | 0 | |
6e6408893207a3ae9634aff5985f9527d690e142 | [
"button_list = [u'业务管理', u'投注卡管理', u'投注卡信息', u'展开']\nself.click_button_for_one(button_list[0])\nsleep(2)\nself.click_more_button_for_one(button_list[1:4])",
"if info_list[0] != u'':\n self.input_text_message_for_inside_text(u'请输入投注卡编号', info_list[0])\nif info_list[1] != u'':\n self.open_list_menu_by_inside_... | <|body_start_0|>
button_list = [u'业务管理', u'投注卡管理', u'投注卡信息', u'展开']
self.click_button_for_one(button_list[0])
sleep(2)
self.click_more_button_for_one(button_list[1:4])
<|end_body_0|>
<|body_start_1|>
if info_list[0] != u'':
self.input_text_message_for_inside_text(u'请... | 投注卡信息页面 | cardInformationPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class cardInformationPage:
"""投注卡信息页面"""
def open_card_information(self):
"""打开投注卡信息页面"""
<|body_0|>
def search_card_information(self, info_list):
"""投注卡信息查询"""
<|body_1|>
def switch_to_card_information(self):
"""切换至投注卡信息查页面"""
<|body_2|>
... | stack_v2_sparse_classes_10k_train_000784 | 1,510 | no_license | [
{
"docstring": "打开投注卡信息页面",
"name": "open_card_information",
"signature": "def open_card_information(self)"
},
{
"docstring": "投注卡信息查询",
"name": "search_card_information",
"signature": "def search_card_information(self, info_list)"
},
{
"docstring": "切换至投注卡信息查页面",
"name": "sw... | 3 | stack_v2_sparse_classes_30k_train_006217 | Implement the Python class `cardInformationPage` described below.
Class description:
投注卡信息页面
Method signatures and docstrings:
- def open_card_information(self): 打开投注卡信息页面
- def search_card_information(self, info_list): 投注卡信息查询
- def switch_to_card_information(self): 切换至投注卡信息查页面 | Implement the Python class `cardInformationPage` described below.
Class description:
投注卡信息页面
Method signatures and docstrings:
- def open_card_information(self): 打开投注卡信息页面
- def search_card_information(self, info_list): 投注卡信息查询
- def switch_to_card_information(self): 切换至投注卡信息查页面
<|skeleton|>
class cardInformationPag... | dcae68955b2857bbfe411145432865c57561c9ef | <|skeleton|>
class cardInformationPage:
"""投注卡信息页面"""
def open_card_information(self):
"""打开投注卡信息页面"""
<|body_0|>
def search_card_information(self, info_list):
"""投注卡信息查询"""
<|body_1|>
def switch_to_card_information(self):
"""切换至投注卡信息查页面"""
<|body_2|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class cardInformationPage:
"""投注卡信息页面"""
def open_card_information(self):
"""打开投注卡信息页面"""
button_list = [u'业务管理', u'投注卡管理', u'投注卡信息', u'展开']
self.click_button_for_one(button_list[0])
sleep(2)
self.click_more_button_for_one(button_list[1:4])
def search_card_informati... | the_stack_v2_python_sparse | genlot_vlt2/pages/Business_management/card_balance_page/card_manage_card_information_page.py | bbwdi/auto | train | 1 |
ed48c783fbe2f6dad6e5fa15eaf7e71a08a55584 | [
"config_settings = {}\nif os.path.isfile(config_path):\n with open(config_path, 'r') as clam_config:\n yaml_config = yaml.load(clam_config)\n if yaml_config['ocav_ops_files']:\n config_settings['ocav_ops_files'] = yaml_config['ocav_ops_files']\n if yaml_config['ocav_s3_bucket']:\n... | <|body_start_0|>
config_settings = {}
if os.path.isfile(config_path):
with open(config_path, 'r') as clam_config:
yaml_config = yaml.load(clam_config)
if yaml_config['ocav_ops_files']:
config_settings['ocav_ops_files'] = yaml_config['ocav_o... | Class to upload clam config files and databases to an S3 bucket. | UpdateBucket | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateBucket:
"""Class to upload clam config files and databases to an S3 bucket."""
def get_config(config_path):
"""Open and read config data from the variables file."""
<|body_0|>
def upload_files(bucket, file_list, aws_creds_file, timestamp):
"""Use the provid... | stack_v2_sparse_classes_10k_train_000785 | 3,647 | permissive | [
{
"docstring": "Open and read config data from the variables file.",
"name": "get_config",
"signature": "def get_config(config_path)"
},
{
"docstring": "Use the provided credentials to upload files to the specified bucket. Raises: A ValueError if the specified bucket can not be found.",
"nam... | 3 | null | Implement the Python class `UpdateBucket` described below.
Class description:
Class to upload clam config files and databases to an S3 bucket.
Method signatures and docstrings:
- def get_config(config_path): Open and read config data from the variables file.
- def upload_files(bucket, file_list, aws_creds_file, times... | Implement the Python class `UpdateBucket` described below.
Class description:
Class to upload clam config files and databases to an S3 bucket.
Method signatures and docstrings:
- def get_config(config_path): Open and read config data from the variables file.
- def upload_files(bucket, file_list, aws_creds_file, times... | e342f6659a4ef1a188ff403e2fc6b06ac6d119c7 | <|skeleton|>
class UpdateBucket:
"""Class to upload clam config files and databases to an S3 bucket."""
def get_config(config_path):
"""Open and read config data from the variables file."""
<|body_0|>
def upload_files(bucket, file_list, aws_creds_file, timestamp):
"""Use the provid... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UpdateBucket:
"""Class to upload clam config files and databases to an S3 bucket."""
def get_config(config_path):
"""Open and read config data from the variables file."""
config_settings = {}
if os.path.isfile(config_path):
with open(config_path, 'r') as clam_config:
... | the_stack_v2_python_sparse | scripts/clam-update/push_clam_signatures.py | openshift/openshift-tools | train | 170 |
b4643d057c94727aab206871daa05d033c2da29a | [
"self.vectors = vec2d\nself.list_index = 0\nself.element_index = 0",
"if self.hasNext():\n value = self.vectors[self.list_index][self.element_index]\n self.element_index += 1\n return value",
"while self.list_index < len(self.vectors):\n if self.element_index < len(self.vectors[self.list_index]):\n ... | <|body_start_0|>
self.vectors = vec2d
self.list_index = 0
self.element_index = 0
<|end_body_0|>
<|body_start_1|>
if self.hasNext():
value = self.vectors[self.list_index][self.element_index]
self.element_index += 1
return value
<|end_body_1|>
<|body_s... | Vector2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_10k_train_000786 | 1,316 | no_license | [
{
"docstring": "Initialize your data structure here. :type vec2d: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, vec2d)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",... | 3 | stack_v2_sparse_classes_30k_train_000760 | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool
<|skeleton|>
class V... | 086b7c9b3651a0e70c5794f6c264eb975cc90363 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
self.vectors = vec2d
self.list_index = 0
self.element_index = 0
def next(self):
""":rtype: int"""
if self.hasNext():
value = self.vector... | the_stack_v2_python_sparse | flatten_2d_vector.py | chunweiliu/leetcode2 | train | 4 | |
c75f973a3205155925e4538aa1611d10b3548397 | [
"self.client = Client()\nself.form_url = reverse('index')\nself.form_url_II = reverse('create')",
"response = self.client.get(self.form_url)\nself.assertEqual(response.status_code, 200)\nself.assertTemplateUsed(response, 'index.html')"
] | <|body_start_0|>
self.client = Client()
self.form_url = reverse('index')
self.form_url_II = reverse('create')
<|end_body_0|>
<|body_start_1|>
response = self.client.get(self.form_url)
self.assertEqual(response.status_code, 200)
self.assertTemplateUsed(response, 'index.ht... | Class with unittests for views. | TestViews | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestViews:
"""Class with unittests for views."""
def setUp(self):
"""Set up for tests."""
<|body_0|>
def test_GET_index(self):
"""GET method for index, tests."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.client = Client()
self.fo... | stack_v2_sparse_classes_10k_train_000787 | 709 | no_license | [
{
"docstring": "Set up for tests.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "GET method for index, tests.",
"name": "test_GET_index",
"signature": "def test_GET_index(self)"
}
] | 2 | null | Implement the Python class `TestViews` described below.
Class description:
Class with unittests for views.
Method signatures and docstrings:
- def setUp(self): Set up for tests.
- def test_GET_index(self): GET method for index, tests. | Implement the Python class `TestViews` described below.
Class description:
Class with unittests for views.
Method signatures and docstrings:
- def setUp(self): Set up for tests.
- def test_GET_index(self): GET method for index, tests.
<|skeleton|>
class TestViews:
"""Class with unittests for views."""
def s... | 3aa62ad36c3b06b2a3b05f1f8e2a9e21d68b371f | <|skeleton|>
class TestViews:
"""Class with unittests for views."""
def setUp(self):
"""Set up for tests."""
<|body_0|>
def test_GET_index(self):
"""GET method for index, tests."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestViews:
"""Class with unittests for views."""
def setUp(self):
"""Set up for tests."""
self.client = Client()
self.form_url = reverse('index')
self.form_url_II = reverse('create')
def test_GET_index(self):
"""GET method for index, tests."""
response... | the_stack_v2_python_sparse | Django/Django_three_projects/urlshortner/shortner/test_views.py | JakubKazimierski/PythonPortfolio | train | 9 |
54c4f3520d5d633aec41806b924b17ff1faf61a8 | [
"QtWidgets.QDialog.__init__(self)\nself.df = pandaTable\nself.layout = QtWidgets.QGridLayout(self)\nself.rankSelect = QtWidgets.QComboBox()\nself.rankSelect.addItems(self.df.columns.values)\nself.programSelect = QtWidgets.QComboBox()\nself.programSelect.addItems(self.df.columns.values)\nself.layout.addWidget(self.p... | <|body_start_0|>
QtWidgets.QDialog.__init__(self)
self.df = pandaTable
self.layout = QtWidgets.QGridLayout(self)
self.rankSelect = QtWidgets.QComboBox()
self.rankSelect.addItems(self.df.columns.values)
self.programSelect = QtWidgets.QComboBox()
self.programSelect.... | A dialog box to get the information required by the ranksbyPrograms function. | RanksByProgramsDialogBox | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RanksByProgramsDialogBox:
"""A dialog box to get the information required by the ranksbyPrograms function."""
def __init__(self, pandaTable, parent):
"""Initializes the UI and sets the two dropdowns to display column names of the active Panda."""
<|body_0|>
def getResult... | stack_v2_sparse_classes_10k_train_000788 | 29,548 | no_license | [
{
"docstring": "Initializes the UI and sets the two dropdowns to display column names of the active Panda.",
"name": "__init__",
"signature": "def __init__(self, pandaTable, parent)"
},
{
"docstring": "Returns the user's input",
"name": "getResults",
"signature": "def getResults(self, pa... | 2 | stack_v2_sparse_classes_30k_train_000425 | Implement the Python class `RanksByProgramsDialogBox` described below.
Class description:
A dialog box to get the information required by the ranksbyPrograms function.
Method signatures and docstrings:
- def __init__(self, pandaTable, parent): Initializes the UI and sets the two dropdowns to display column names of t... | Implement the Python class `RanksByProgramsDialogBox` described below.
Class description:
A dialog box to get the information required by the ranksbyPrograms function.
Method signatures and docstrings:
- def __init__(self, pandaTable, parent): Initializes the UI and sets the two dropdowns to display column names of t... | 1a3c5ad967472faf66236a311cc07a5128f5f911 | <|skeleton|>
class RanksByProgramsDialogBox:
"""A dialog box to get the information required by the ranksbyPrograms function."""
def __init__(self, pandaTable, parent):
"""Initializes the UI and sets the two dropdowns to display column names of the active Panda."""
<|body_0|>
def getResult... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RanksByProgramsDialogBox:
"""A dialog box to get the information required by the ranksbyPrograms function."""
def __init__(self, pandaTable, parent):
"""Initializes the UI and sets the two dropdowns to display column names of the active Panda."""
QtWidgets.QDialog.__init__(self)
s... | the_stack_v2_python_sparse | datatool/gui/Model.py | scottawalton/datatool | train | 0 |
9192d05768c17a08011946c8b55794d195f22761 | [
"self.root = Node()\nfor i, word in enumerate(words):\n longw = word + '#' + word\n for j in range(len(word)):\n cur = self.root\n cur.index = i\n for c in longw[j:]:\n cur = cur[c]\n cur.index = i",
"word = suffix + '#' + prefix\ncur = self.root\nfor c in word:\n ... | <|body_start_0|>
self.root = Node()
for i, word in enumerate(words):
longw = word + '#' + word
for j in range(len(word)):
cur = self.root
cur.index = i
for c in longw[j:]:
cur = cur[c]
cur.ind... | WordFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordFilter:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def f(self, prefix, suffix):
""":type prefix: str :type suffix: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.root = Node()
for i, word in ... | stack_v2_sparse_classes_10k_train_000789 | 2,614 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type prefix: str :type suffix: str :rtype: int",
"name": "f",
"signature": "def f(self, prefix, suffix)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002247 | Implement the Python class `WordFilter` described below.
Class description:
Implement the WordFilter class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def f(self, prefix, suffix): :type prefix: str :type suffix: str :rtype: int | Implement the Python class `WordFilter` described below.
Class description:
Implement the WordFilter class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def f(self, prefix, suffix): :type prefix: str :type suffix: str :rtype: int
<|skeleton|>
class WordFilter:
def __in... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class WordFilter:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def f(self, prefix, suffix):
""":type prefix: str :type suffix: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WordFilter:
def __init__(self, words):
""":type words: List[str]"""
self.root = Node()
for i, word in enumerate(words):
longw = word + '#' + word
for j in range(len(word)):
cur = self.root
cur.index = i
for c in lo... | the_stack_v2_python_sparse | P/PrefixandSuffixSearch.py | bssrdf/pyleet | train | 2 | |
4bcb3b48cba68dea3d255a9dd531c4f161fc1429 | [
"cnt1, cnt2 = (Counter(ransomNote), Counter(magazine))\nfor letter, v in cnt1.items():\n if v > cnt2.get(letter, 0):\n return False\nreturn True",
"cnt = Counter(ransomNote)\nfor letter, v in cnt.items():\n if v > magazine.count(letter):\n return False\nreturn True",
"pos = {}\nfor c in rans... | <|body_start_0|>
cnt1, cnt2 = (Counter(ransomNote), Counter(magazine))
for letter, v in cnt1.items():
if v > cnt2.get(letter, 0):
return False
return True
<|end_body_0|>
<|body_start_1|>
cnt = Counter(ransomNote)
for letter, v in cnt.items():
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canConstruct1(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_0|>
def canConstruct2(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_1|>
def ca... | stack_v2_sparse_classes_10k_train_000790 | 1,855 | no_license | [
{
"docstring": ":type ransomNote: str :type magazine: str :rtype: bool",
"name": "canConstruct1",
"signature": "def canConstruct1(self, ransomNote, magazine)"
},
{
"docstring": ":type ransomNote: str :type magazine: str :rtype: bool",
"name": "canConstruct2",
"signature": "def canConstru... | 3 | stack_v2_sparse_classes_30k_train_002691 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canConstruct1(self, ransomNote, magazine): :type ransomNote: str :type magazine: str :rtype: bool
- def canConstruct2(self, ransomNote, magazine): :type ransomNote: str :type... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canConstruct1(self, ransomNote, magazine): :type ransomNote: str :type magazine: str :rtype: bool
- def canConstruct2(self, ransomNote, magazine): :type ransomNote: str :type... | 4a1747b6497305f3821612d9c358a6795b1690da | <|skeleton|>
class Solution:
def canConstruct1(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_0|>
def canConstruct2(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_1|>
def ca... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def canConstruct1(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
cnt1, cnt2 = (Counter(ransomNote), Counter(magazine))
for letter, v in cnt1.items():
if v > cnt2.get(letter, 0):
return False
return... | the_stack_v2_python_sparse | String/q383_ransom_note.py | sevenhe716/LeetCode | train | 0 | |
aeda58e49a488dbebde457d4dc86fa231f11d5e2 | [
"self.warmup_epochs = warmup_epochs\nself.total_epochs = total_epochs\nself.warmup_start_lr = warmup_start_lr\nself.start_lr = start_lr\nself.end_lr = end_lr\nself.cycles = cycles\nsuper(WarmupCosineScheduler, self).__init__(learning_rate, last_epoch, verbose)",
"if self.last_epoch < self.warmup_epochs:\n val ... | <|body_start_0|>
self.warmup_epochs = warmup_epochs
self.total_epochs = total_epochs
self.warmup_start_lr = warmup_start_lr
self.start_lr = start_lr
self.end_lr = end_lr
self.cycles = cycles
super(WarmupCosineScheduler, self).__init__(learning_rate, last_epoch, ve... | Warmup Cosine Scheduler First apply linear warmup, then apply cosine decay schedule. Linearly increase learning rate from "warmup_start_lr" to "start_lr" over "warmup_epochs" Cosinely decrease learning rate from "start_lr" to "end_lr" over remaining "total_epochs - warmup_epochs" Attributes: learning_rate: the starting... | WarmupCosineScheduler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WarmupCosineScheduler:
"""Warmup Cosine Scheduler First apply linear warmup, then apply cosine decay schedule. Linearly increase learning rate from "warmup_start_lr" to "start_lr" over "warmup_epochs" Cosinely decrease learning rate from "start_lr" to "end_lr" over remaining "total_epochs - warmu... | stack_v2_sparse_classes_10k_train_000791 | 8,472 | permissive | [
{
"docstring": "init WarmupCosineScheduler",
"name": "__init__",
"signature": "def __init__(self, learning_rate, warmup_start_lr, start_lr, end_lr, warmup_epochs, total_epochs, cycles=0.5, last_epoch=-1, verbose=False)"
},
{
"docstring": "return lr value",
"name": "get_lr",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_006440 | Implement the Python class `WarmupCosineScheduler` described below.
Class description:
Warmup Cosine Scheduler First apply linear warmup, then apply cosine decay schedule. Linearly increase learning rate from "warmup_start_lr" to "start_lr" over "warmup_epochs" Cosinely decrease learning rate from "start_lr" to "end_l... | Implement the Python class `WarmupCosineScheduler` described below.
Class description:
Warmup Cosine Scheduler First apply linear warmup, then apply cosine decay schedule. Linearly increase learning rate from "warmup_start_lr" to "start_lr" over "warmup_epochs" Cosinely decrease learning rate from "start_lr" to "end_l... | c90a6c8dc3787e69cef3a37b9a260bd59eeff1f7 | <|skeleton|>
class WarmupCosineScheduler:
"""Warmup Cosine Scheduler First apply linear warmup, then apply cosine decay schedule. Linearly increase learning rate from "warmup_start_lr" to "start_lr" over "warmup_epochs" Cosinely decrease learning rate from "start_lr" to "end_lr" over remaining "total_epochs - warmu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WarmupCosineScheduler:
"""Warmup Cosine Scheduler First apply linear warmup, then apply cosine decay schedule. Linearly increase learning rate from "warmup_start_lr" to "start_lr" over "warmup_epochs" Cosinely decrease learning rate from "start_lr" to "end_lr" over remaining "total_epochs - warmup_epochs" Att... | the_stack_v2_python_sparse | object_detection/DETR/utils.py | Dongsheng-Bi/PaddleViT | train | 1 |
fe679d5f56871253bef8e90afee1deaa87381d75 | [
"res = super(create_quick_purchase, self)._onchange_product_id()\nproduct = self.product_id\nif product:\n if product.purchase_line_warn != 'no-message':\n res = {'warning': {'title': _('Warning for %s') % product.name, 'message': product.purchase_line_warn_msg}}\nreturn res",
"warning = {}\ntitle = Fal... | <|body_start_0|>
res = super(create_quick_purchase, self)._onchange_product_id()
product = self.product_id
if product:
if product.purchase_line_warn != 'no-message':
res = {'warning': {'title': _('Warning for %s') % product.name, 'message': product.purchase_line_warn_... | create_quick_purchase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class create_quick_purchase:
def _onchange_product_id(self):
"""Surcharge du onchange des produits du wizard de création rapide d'achat, lorsqu'on sélectionne un produit on vérifie s'il dispose ou non d'un warning et on l'affiche si c'est le cas."""
<|body_0|>
def _onchange_partne... | stack_v2_sparse_classes_10k_train_000792 | 1,707 | no_license | [
{
"docstring": "Surcharge du onchange des produits du wizard de création rapide d'achat, lorsqu'on sélectionne un produit on vérifie s'il dispose ou non d'un warning et on l'affiche si c'est le cas.",
"name": "_onchange_product_id",
"signature": "def _onchange_product_id(self)"
},
{
"docstring":... | 2 | stack_v2_sparse_classes_30k_train_006827 | Implement the Python class `create_quick_purchase` described below.
Class description:
Implement the create_quick_purchase class.
Method signatures and docstrings:
- def _onchange_product_id(self): Surcharge du onchange des produits du wizard de création rapide d'achat, lorsqu'on sélectionne un produit on vérifie s'i... | Implement the Python class `create_quick_purchase` described below.
Class description:
Implement the create_quick_purchase class.
Method signatures and docstrings:
- def _onchange_product_id(self): Surcharge du onchange des produits du wizard de création rapide d'achat, lorsqu'on sélectionne un produit on vérifie s'i... | eb394e1f79ba1995da2dcd81adfdd511c22caff9 | <|skeleton|>
class create_quick_purchase:
def _onchange_product_id(self):
"""Surcharge du onchange des produits du wizard de création rapide d'achat, lorsqu'on sélectionne un produit on vérifie s'il dispose ou non d'un warning et on l'affiche si c'est le cas."""
<|body_0|>
def _onchange_partne... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class create_quick_purchase:
def _onchange_product_id(self):
"""Surcharge du onchange des produits du wizard de création rapide d'achat, lorsqu'on sélectionne un produit on vérifie s'il dispose ou non d'un warning et on l'affiche si c'est le cas."""
res = super(create_quick_purchase, self)._onchange... | the_stack_v2_python_sparse | OpenPROD/openprod-addons/warning/wizard/create_quick_purchase.py | kazacube-mziouadi/ceci | train | 0 | |
44ca53d6280718d50d5b49a3c1a6f28f7f28fc63 | [
"super().__init__()\nself.mask_l2_weight = mask_l2_weight\nself.channel_weight = channel_weight\nself.spatial_weight = spatial_weight\nself.nonloacl_weight = nonloacl_weight\nself.loss_weight = loss_weight",
"losses = 0.0\ns_spatial_mask, s_channel_mask, s_channel_pool_adapt, s_spatial_pool_adapt, s_relation_adap... | <|body_start_0|>
super().__init__()
self.mask_l2_weight = mask_l2_weight
self.channel_weight = channel_weight
self.spatial_weight = spatial_weight
self.nonloacl_weight = nonloacl_weight
self.loss_weight = loss_weight
<|end_body_0|>
<|body_start_1|>
losses = 0.0
... | Loss For FBKD, which includs feat_loss, channel_loss, spatial_loss and nonlocal_loss. Source code: https://github.com/ArchipLab-LinfengZhang/Object-Detection-Knowledge- Distillation-ICLR2021 Args: mask_l2_weight (float): The weight of the mask l2 loss. Defaults to 7e-5, which is the default value in source code. channe... | FBKDLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FBKDLoss:
"""Loss For FBKD, which includs feat_loss, channel_loss, spatial_loss and nonlocal_loss. Source code: https://github.com/ArchipLab-LinfengZhang/Object-Detection-Knowledge- Distillation-ICLR2021 Args: mask_l2_weight (float): The weight of the mask l2 loss. Defaults to 7e-5, which is the ... | stack_v2_sparse_classes_10k_train_000793 | 4,435 | permissive | [
{
"docstring": "Inits FBKDLoss.",
"name": "__init__",
"signature": "def __init__(self, mask_l2_weight: float=7e-05, channel_weight: float=0.004, spatial_weight: float=0.004, nonloacl_weight: float=7e-05, loss_weight: float=1.0) -> None"
},
{
"docstring": "Forward function of FBKDLoss, including ... | 2 | null | Implement the Python class `FBKDLoss` described below.
Class description:
Loss For FBKD, which includs feat_loss, channel_loss, spatial_loss and nonlocal_loss. Source code: https://github.com/ArchipLab-LinfengZhang/Object-Detection-Knowledge- Distillation-ICLR2021 Args: mask_l2_weight (float): The weight of the mask l... | Implement the Python class `FBKDLoss` described below.
Class description:
Loss For FBKD, which includs feat_loss, channel_loss, spatial_loss and nonlocal_loss. Source code: https://github.com/ArchipLab-LinfengZhang/Object-Detection-Knowledge- Distillation-ICLR2021 Args: mask_l2_weight (float): The weight of the mask l... | 9d643e88946fc4a24f2d4d073c08b05ea693f4c5 | <|skeleton|>
class FBKDLoss:
"""Loss For FBKD, which includs feat_loss, channel_loss, spatial_loss and nonlocal_loss. Source code: https://github.com/ArchipLab-LinfengZhang/Object-Detection-Knowledge- Distillation-ICLR2021 Args: mask_l2_weight (float): The weight of the mask l2 loss. Defaults to 7e-5, which is the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FBKDLoss:
"""Loss For FBKD, which includs feat_loss, channel_loss, spatial_loss and nonlocal_loss. Source code: https://github.com/ArchipLab-LinfengZhang/Object-Detection-Knowledge- Distillation-ICLR2021 Args: mask_l2_weight (float): The weight of the mask l2 loss. Defaults to 7e-5, which is the default value... | the_stack_v2_python_sparse | cv/distiller/CWD/pytorch/mmrazor/mmrazor/models/losses/fbkd_loss.py | Deep-Spark/DeepSparkHub | train | 7 |
66284f5d00c672fdd26fd53213b47ab1fb673281 | [
"if request.user.has_perm(CHANGE_TASK):\n task = Task.objects.get(pk=request.data['id_task'])\n team = Team.objects.get(pk=request.data['id_team'])\n task.teams.add(team)\n return Response(status=status.HTTP_201_CREATED)\nreturn Response(status=status.HTTP_401_UNAUTHORIZED)",
"if request.user.has_perm... | <|body_start_0|>
if request.user.has_perm(CHANGE_TASK):
task = Task.objects.get(pk=request.data['id_task'])
team = Team.objects.get(pk=request.data['id_team'])
task.teams.add(team)
return Response(status=status.HTTP_201_CREATED)
return Response(status=stat... | \\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team from task If the user doesn't have the permissions, it will send HTTP 401. Both re... | AddTeamToTask | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddTeamToTask:
"""\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team from task If the user doesn't have the pe... | stack_v2_sparse_classes_10k_train_000794 | 21,722 | permissive | [
{
"docstring": "Assign a team to a task.",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "Remove a team from a task.",
"name": "put",
"signature": "def put(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007113 | Implement the Python class `AddTeamToTask` described below.
Class description:
\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team fr... | Implement the Python class `AddTeamToTask` described below.
Class description:
\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team fr... | 56511ebac83a5dc1fb8768a98bc675e88530a447 | <|skeleton|>
class AddTeamToTask:
"""\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team from task If the user doesn't have the pe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AddTeamToTask:
"""\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team from task If the user doesn't have the permissions, it... | the_stack_v2_python_sparse | maintenancemanagement/views/views_task.py | Open-CMMS/openCMMS_backend | train | 4 |
dbbf5d183f25689802b0dad86796eca5b1bca4bd | [
"self.count = count\nself.environment = environment\nself.size = size",
"if dictionary is None:\n return None\ncount = dictionary.get('count')\nenvironment = dictionary.get('environment')\nsize = dictionary.get('size')\nreturn cls(count, environment, size)"
] | <|body_start_0|>
self.count = count
self.environment = environment
self.size = size
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
count = dictionary.get('count')
environment = dictionary.get('environment')
size = dictionary.get('s... | Implementation of the 'VaultProviderStatsByEnv' model. Specifies the Vault stats by environments. Attributes: count (long|int): Specifies the count of the objects of the specified environment. environment (EnvironmentVaultProviderStatsByEnvEnum): Specifies the environment type. size (long|int): Specifies the size of th... | VaultProviderStatsByEnv | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VaultProviderStatsByEnv:
"""Implementation of the 'VaultProviderStatsByEnv' model. Specifies the Vault stats by environments. Attributes: count (long|int): Specifies the count of the objects of the specified environment. environment (EnvironmentVaultProviderStatsByEnvEnum): Specifies the environm... | stack_v2_sparse_classes_10k_train_000795 | 1,885 | permissive | [
{
"docstring": "Constructor for the VaultProviderStatsByEnv class",
"name": "__init__",
"signature": "def __init__(self, count=None, environment=None, size=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of ... | 2 | null | Implement the Python class `VaultProviderStatsByEnv` described below.
Class description:
Implementation of the 'VaultProviderStatsByEnv' model. Specifies the Vault stats by environments. Attributes: count (long|int): Specifies the count of the objects of the specified environment. environment (EnvironmentVaultProvider... | Implement the Python class `VaultProviderStatsByEnv` described below.
Class description:
Implementation of the 'VaultProviderStatsByEnv' model. Specifies the Vault stats by environments. Attributes: count (long|int): Specifies the count of the objects of the specified environment. environment (EnvironmentVaultProvider... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class VaultProviderStatsByEnv:
"""Implementation of the 'VaultProviderStatsByEnv' model. Specifies the Vault stats by environments. Attributes: count (long|int): Specifies the count of the objects of the specified environment. environment (EnvironmentVaultProviderStatsByEnvEnum): Specifies the environm... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VaultProviderStatsByEnv:
"""Implementation of the 'VaultProviderStatsByEnv' model. Specifies the Vault stats by environments. Attributes: count (long|int): Specifies the count of the objects of the specified environment. environment (EnvironmentVaultProviderStatsByEnvEnum): Specifies the environment type. siz... | the_stack_v2_python_sparse | cohesity_management_sdk/models/vault_provider_stats_by_env.py | cohesity/management-sdk-python | train | 24 |
6544b630174ec46621b87b7fff5e3fddeef21266 | [
"url = self.trimUrlPrefix(urlTrait.url)\nif url and self.isTnsStyle(url):\n EMPTY = OracleTnsRecordParser.EMPTY\n obj = OracleTnsRecordParser().parse(url)\n uniqueHostCount = self._countUniqueHosts(obj)\n description = self._getDescription(obj)\n serviceName = description.connect_data.service_name\n ... | <|body_start_0|>
url = self.trimUrlPrefix(urlTrait.url)
if url and self.isTnsStyle(url):
EMPTY = OracleTnsRecordParser.EMPTY
obj = OracleTnsRecordParser().parse(url)
uniqueHostCount = self._countUniqueHosts(obj)
description = self._getDescription(obj)
... | OracleThinHasSidCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OracleThinHasSidCase:
def isApplicableUrlTrait(self, urlTrait):
"""@types: jdbc_url_parser.Trait -> bool"""
<|body_0|>
def parse(self, url):
"""@types: str -> tuple[db.DatabaseServer]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
url = self.trimUr... | stack_v2_sparse_classes_10k_train_000796 | 40,819 | no_license | [
{
"docstring": "@types: jdbc_url_parser.Trait -> bool",
"name": "isApplicableUrlTrait",
"signature": "def isApplicableUrlTrait(self, urlTrait)"
},
{
"docstring": "@types: str -> tuple[db.DatabaseServer]",
"name": "parse",
"signature": "def parse(self, url)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000154 | Implement the Python class `OracleThinHasSidCase` described below.
Class description:
Implement the OracleThinHasSidCase class.
Method signatures and docstrings:
- def isApplicableUrlTrait(self, urlTrait): @types: jdbc_url_parser.Trait -> bool
- def parse(self, url): @types: str -> tuple[db.DatabaseServer] | Implement the Python class `OracleThinHasSidCase` described below.
Class description:
Implement the OracleThinHasSidCase class.
Method signatures and docstrings:
- def isApplicableUrlTrait(self, urlTrait): @types: jdbc_url_parser.Trait -> bool
- def parse(self, url): @types: str -> tuple[db.DatabaseServer]
<|skeleto... | c431e809e8d0f82e1bca7e3429dd0245560b5680 | <|skeleton|>
class OracleThinHasSidCase:
def isApplicableUrlTrait(self, urlTrait):
"""@types: jdbc_url_parser.Trait -> bool"""
<|body_0|>
def parse(self, url):
"""@types: str -> tuple[db.DatabaseServer]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OracleThinHasSidCase:
def isApplicableUrlTrait(self, urlTrait):
"""@types: jdbc_url_parser.Trait -> bool"""
url = self.trimUrlPrefix(urlTrait.url)
if url and self.isTnsStyle(url):
EMPTY = OracleTnsRecordParser.EMPTY
obj = OracleTnsRecordParser().parse(url)
... | the_stack_v2_python_sparse | reference/ucmdb/discovery/jdbc_url_parser.py | madmonkyang/cda-record | train | 0 | |
cb88c5175ce1714d6e75bda08b33c25e19a3e474 | [
"self.end_time_msecs = end_time_msecs\nself.env_type = env_type\nself.job_id = job_id\nself.job_name = job_name\nself.job_run_id = job_run_id\nself.job_type = job_type\nself.start_time_msecs = start_time_msecs\nself.view_box_id = view_box_id",
"if dictionary is None:\n return None\nend_time_msecs = dictionary.... | <|body_start_0|>
self.end_time_msecs = end_time_msecs
self.env_type = env_type
self.job_id = job_id
self.job_name = job_name
self.job_run_id = job_run_id
self.job_type = job_type
self.start_time_msecs = start_time_msecs
self.view_box_id = view_box_id
<|end... | Implementation of the 'GetAllJobRunsResult' model. Specifies the common result structure of the response of all runs info ( protection, replication, archival etc.). Attributes: end_time_msecs (long|int): Specifies the end time of the run. env_type (EnvTypeEnum): Specifies the environment type of the job. Supported envi... | GetAllJobRunsResult | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetAllJobRunsResult:
"""Implementation of the 'GetAllJobRunsResult' model. Specifies the common result structure of the response of all runs info ( protection, replication, archival etc.). Attributes: end_time_msecs (long|int): Specifies the end time of the run. env_type (EnvTypeEnum): Specifies ... | stack_v2_sparse_classes_10k_train_000797 | 6,994 | permissive | [
{
"docstring": "Constructor for the GetAllJobRunsResult class",
"name": "__init__",
"signature": "def __init__(self, end_time_msecs=None, env_type=None, job_id=None, job_name=None, job_run_id=None, job_type=None, start_time_msecs=None, view_box_id=None)"
},
{
"docstring": "Creates an instance of... | 2 | null | Implement the Python class `GetAllJobRunsResult` described below.
Class description:
Implementation of the 'GetAllJobRunsResult' model. Specifies the common result structure of the response of all runs info ( protection, replication, archival etc.). Attributes: end_time_msecs (long|int): Specifies the end time of the ... | Implement the Python class `GetAllJobRunsResult` described below.
Class description:
Implementation of the 'GetAllJobRunsResult' model. Specifies the common result structure of the response of all runs info ( protection, replication, archival etc.). Attributes: end_time_msecs (long|int): Specifies the end time of the ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class GetAllJobRunsResult:
"""Implementation of the 'GetAllJobRunsResult' model. Specifies the common result structure of the response of all runs info ( protection, replication, archival etc.). Attributes: end_time_msecs (long|int): Specifies the end time of the run. env_type (EnvTypeEnum): Specifies ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GetAllJobRunsResult:
"""Implementation of the 'GetAllJobRunsResult' model. Specifies the common result structure of the response of all runs info ( protection, replication, archival etc.). Attributes: end_time_msecs (long|int): Specifies the end time of the run. env_type (EnvTypeEnum): Specifies the environme... | the_stack_v2_python_sparse | cohesity_management_sdk/models/get_all_job_runs_result.py | cohesity/management-sdk-python | train | 24 |
8d00f6f2379b4c050501c270cd78756fa3737ac7 | [
"filters = filters or {}\nif not is_user_action_allowed('manage_others_tokens'):\n filters['_user_fk'] = current_user.id\nsm = get_storage_manager()\nresult = sm.list(models.Token, filters=filters, pagination=pagination, sort=sort)\nreturn result",
"_purge_expired_user_tokens()\nrequest_dict = get_json_and_ver... | <|body_start_0|>
filters = filters or {}
if not is_user_action_allowed('manage_others_tokens'):
filters['_user_fk'] = current_user.id
sm = get_storage_manager()
result = sm.list(models.Token, filters=filters, pagination=pagination, sort=sort)
return result
<|end_body_... | Tokens | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tokens:
def get(self, filters=None, pagination=None, sort=None):
"""Get a list of tokens."""
<|body_0|>
def post(self):
"""Create a new token."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
filters = filters or {}
if not is_user_action_allo... | stack_v2_sparse_classes_10k_train_000798 | 3,246 | permissive | [
{
"docstring": "Get a list of tokens.",
"name": "get",
"signature": "def get(self, filters=None, pagination=None, sort=None)"
},
{
"docstring": "Create a new token.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006784 | Implement the Python class `Tokens` described below.
Class description:
Implement the Tokens class.
Method signatures and docstrings:
- def get(self, filters=None, pagination=None, sort=None): Get a list of tokens.
- def post(self): Create a new token. | Implement the Python class `Tokens` described below.
Class description:
Implement the Tokens class.
Method signatures and docstrings:
- def get(self, filters=None, pagination=None, sort=None): Get a list of tokens.
- def post(self): Create a new token.
<|skeleton|>
class Tokens:
def get(self, filters=None, pagi... | c0de6442e1d7653fad824d75e571802a74eee605 | <|skeleton|>
class Tokens:
def get(self, filters=None, pagination=None, sort=None):
"""Get a list of tokens."""
<|body_0|>
def post(self):
"""Create a new token."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Tokens:
def get(self, filters=None, pagination=None, sort=None):
"""Get a list of tokens."""
filters = filters or {}
if not is_user_action_allowed('manage_others_tokens'):
filters['_user_fk'] = current_user.id
sm = get_storage_manager()
result = sm.list(mode... | the_stack_v2_python_sparse | rest-service/manager_rest/rest/resources_v3_1/tokens.py | cloudify-cosmo/cloudify-manager | train | 146 | |
d349de07b292bdeab635290cd1dfcd044933b896 | [
"res = 0\nfor i in range(len(nums)):\n res = max(res, nums[i] + self.rob(nums[i + 2:]))\nreturn res",
"if not nums:\n return 0\np_0 = nums[0]\nif len(nums) == 1:\n return p_0\np_1 = max(p_0, nums[1])\nfor i in range(2, len(nums)):\n p_2 = max(p_1, p_0 + nums[i])\n p_0 = p_1\n p_1 = p_2\nreturn p... | <|body_start_0|>
res = 0
for i in range(len(nums)):
res = max(res, nums[i] + self.rob(nums[i + 2:]))
return res
<|end_body_0|>
<|body_start_1|>
if not nums:
return 0
p_0 = nums[0]
if len(nums) == 1:
return p_0
p_1 = max(p_0, nu... | Solution | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob(self, nums):
"""Brute Force (Time Limit Exceeded)"""
<|body_0|>
def rob2(self, nums):
"""DP"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = 0
for i in range(len(nums)):
res = max(res, nums[i] + self.rob(nu... | stack_v2_sparse_classes_10k_train_000799 | 1,489 | permissive | [
{
"docstring": "Brute Force (Time Limit Exceeded)",
"name": "rob",
"signature": "def rob(self, nums)"
},
{
"docstring": "DP",
"name": "rob2",
"signature": "def rob2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): Brute Force (Time Limit Exceeded)
- def rob2(self, nums): DP | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): Brute Force (Time Limit Exceeded)
- def rob2(self, nums): DP
<|skeleton|>
class Solution:
def rob(self, nums):
"""Brute Force (Time Limit Excee... | 49a0b03c55d8a702785888d473ef96539265ce9c | <|skeleton|>
class Solution:
def rob(self, nums):
"""Brute Force (Time Limit Exceeded)"""
<|body_0|>
def rob2(self, nums):
"""DP"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def rob(self, nums):
"""Brute Force (Time Limit Exceeded)"""
res = 0
for i in range(len(nums)):
res = max(res, nums[i] + self.rob(nums[i + 2:]))
return res
def rob2(self, nums):
"""DP"""
if not nums:
return 0
p_0 = ... | the_stack_v2_python_sparse | leetcode/0198_house_robber.py | chaosWsF/Python-Practice | train | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.