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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
bfdeb5361db702beebbe017c4450f5f4e094b533 | [
"if logdir is None:\n raise ValueError('A logdir is required')\nif directory_loader_factory is None:\n raise ValueError('A directory loader factory is required')\nself._logdir = logdir\nself._directory_loader_factory = directory_loader_factory\nself._directory_loaders = {}",
"logger.info('Starting logdir tr... | <|body_start_0|>
if logdir is None:
raise ValueError('A logdir is required')
if directory_loader_factory is None:
raise ValueError('A directory loader factory is required')
self._logdir = logdir
self._directory_loader_factory = directory_loader_factory
sel... | Loader for a root log directory, maintaining multiple DirectoryLoaders. This class takes a root log directory and a factory for DirectoryLoaders, and maintains one DirectoryLoader per "logdir subdirectory" of the root logdir. Note that this class is not thread-safe. | LogdirLoader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogdirLoader:
"""Loader for a root log directory, maintaining multiple DirectoryLoaders. This class takes a root log directory and a factory for DirectoryLoaders, and maintains one DirectoryLoader per "logdir subdirectory" of the root logdir. Note that this class is not thread-safe."""
def _... | stack_v2_sparse_classes_10k_train_007700 | 4,418 | permissive | [
{
"docstring": "Constructs a new LogdirLoader. Args: logdir: The root log directory to load from. directory_loader_factory: A factory for creating DirectoryLoaders. The factory should take a path and return a DirectoryLoader. Raises: ValueError: If logdir or directory_loader_factory are None.",
"name": "__i... | 4 | null | Implement the Python class `LogdirLoader` described below.
Class description:
Loader for a root log directory, maintaining multiple DirectoryLoaders. This class takes a root log directory and a factory for DirectoryLoaders, and maintains one DirectoryLoader per "logdir subdirectory" of the root logdir. Note that this ... | Implement the Python class `LogdirLoader` described below.
Class description:
Loader for a root log directory, maintaining multiple DirectoryLoaders. This class takes a root log directory and a factory for DirectoryLoaders, and maintains one DirectoryLoader per "logdir subdirectory" of the root logdir. Note that this ... | 5961c76dca0fb9bb40d146f5ce13834ac29d8ddb | <|skeleton|>
class LogdirLoader:
"""Loader for a root log directory, maintaining multiple DirectoryLoaders. This class takes a root log directory and a factory for DirectoryLoaders, and maintains one DirectoryLoader per "logdir subdirectory" of the root logdir. Note that this class is not thread-safe."""
def _... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LogdirLoader:
"""Loader for a root log directory, maintaining multiple DirectoryLoaders. This class takes a root log directory and a factory for DirectoryLoaders, and maintains one DirectoryLoader per "logdir subdirectory" of the root logdir. Note that this class is not thread-safe."""
def __init__(self,... | the_stack_v2_python_sparse | tensorboard/uploader/logdir_loader.py | tensorflow/tensorboard | train | 6,766 |
d8b37a686ef9e8dad507b9c0e276acbd212d1e67 | [
"try:\n resource, authorized, user = view_utils.authorize(request, pk, needed_permission=ACTION_TO_AUTHORIZE.VIEW_RESOURCE, raises_exception=False)\nexcept NotFound as ex:\n return Response(str(ex), status=status.HTTP_404_NOT_FOUND)\nif not authorized:\n return Response('Insufficient permission', status=st... | <|body_start_0|>
try:
resource, authorized, user = view_utils.authorize(request, pk, needed_permission=ACTION_TO_AUTHORIZE.VIEW_RESOURCE, raises_exception=False)
except NotFound as ex:
return Response(str(ex), status=status.HTTP_404_NOT_FOUND)
if not authorized:
... | list or delete a ticket Methods: GET, DELETE Returns: HTTP 200, 400, 403, 403 Example of a correct list request: GET /hsapi/resource/28f87079ceaf440588e7866a0f4b6c57/ticket/info/pwYwPanpnwdDZa9/ This returns HTTP_200_OK with content: {u'expires': u'2017-07-26.00:17:00', u'filename': u'28f87079ceaf440588e7866a0f4b6c57.z... | ManageResourceTicket | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageResourceTicket:
"""list or delete a ticket Methods: GET, DELETE Returns: HTTP 200, 400, 403, 403 Example of a correct list request: GET /hsapi/resource/28f87079ceaf440588e7866a0f4b6c57/ticket/info/pwYwPanpnwdDZa9/ This returns HTTP_200_OK with content: {u'expires': u'2017-07-26.00:17:00', u... | stack_v2_sparse_classes_10k_train_007701 | 9,855 | permissive | [
{
"docstring": "list a ticket",
"name": "get",
"signature": "def get(self, request, pk, ticket)"
},
{
"docstring": "Delete a ticket.",
"name": "delete",
"signature": "def delete(self, request, pk, ticket)"
}
] | 2 | null | Implement the Python class `ManageResourceTicket` described below.
Class description:
list or delete a ticket Methods: GET, DELETE Returns: HTTP 200, 400, 403, 403 Example of a correct list request: GET /hsapi/resource/28f87079ceaf440588e7866a0f4b6c57/ticket/info/pwYwPanpnwdDZa9/ This returns HTTP_200_OK with content:... | Implement the Python class `ManageResourceTicket` described below.
Class description:
list or delete a ticket Methods: GET, DELETE Returns: HTTP 200, 400, 403, 403 Example of a correct list request: GET /hsapi/resource/28f87079ceaf440588e7866a0f4b6c57/ticket/info/pwYwPanpnwdDZa9/ This returns HTTP_200_OK with content:... | 69855813052243c702c9b0108d2eac3f4f1a768f | <|skeleton|>
class ManageResourceTicket:
"""list or delete a ticket Methods: GET, DELETE Returns: HTTP 200, 400, 403, 403 Example of a correct list request: GET /hsapi/resource/28f87079ceaf440588e7866a0f4b6c57/ticket/info/pwYwPanpnwdDZa9/ This returns HTTP_200_OK with content: {u'expires': u'2017-07-26.00:17:00', u... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ManageResourceTicket:
"""list or delete a ticket Methods: GET, DELETE Returns: HTTP 200, 400, 403, 403 Example of a correct list request: GET /hsapi/resource/28f87079ceaf440588e7866a0f4b6c57/ticket/info/pwYwPanpnwdDZa9/ This returns HTTP_200_OK with content: {u'expires': u'2017-07-26.00:17:00', u'filename': u... | the_stack_v2_python_sparse | hs_core/views/resource_ticket_rest_api.py | hydroshare/hydroshare | train | 207 |
da3e17185f9575429b96e8f1cd541f1bc9a45d9f | [
"mini, maxa = (0, len(S))\nret = []\nfor c in S:\n if c == 'I':\n ret.append(mini)\n mini += 1\n else:\n ret.append(maxa)\n maxa -= 1\nret.append(mini)\nreturn ret",
"ret = [0]\nfor c in S:\n if c == 'I':\n ret.append(ret[-1] + 1)\n else:\n ret.append(ret[-1] ... | <|body_start_0|>
mini, maxa = (0, len(S))
ret = []
for c in S:
if c == 'I':
ret.append(mini)
mini += 1
else:
ret.append(maxa)
maxa -= 1
ret.append(mini)
return ret
<|end_body_0|>
<|body_start... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def diStringMatch(self, S: str) -> List[int]:
"""Looking at prev rather than cur If "I", then put smallest as prev. Increase from the min If "D", then put the largest as prev. Decrese from the max"""
<|body_0|>
def diStringMatchErrror(self, S: str) -> List[int]:
... | stack_v2_sparse_classes_10k_train_007702 | 1,464 | no_license | [
{
"docstring": "Looking at prev rather than cur If \"I\", then put smallest as prev. Increase from the min If \"D\", then put the largest as prev. Decrese from the max",
"name": "diStringMatch",
"signature": "def diStringMatch(self, S: str) -> List[int]"
},
{
"docstring": "start with 0, then add... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def diStringMatch(self, S: str) -> List[int]: Looking at prev rather than cur If "I", then put smallest as prev. Increase from the min If "D", then put the largest as prev. Decre... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def diStringMatch(self, S: str) -> List[int]: Looking at prev rather than cur If "I", then put smallest as prev. Increase from the min If "D", then put the largest as prev. Decre... | 929dde1723fb2f54870c8a9badc80fc23e8400d3 | <|skeleton|>
class Solution:
def diStringMatch(self, S: str) -> List[int]:
"""Looking at prev rather than cur If "I", then put smallest as prev. Increase from the min If "D", then put the largest as prev. Decrese from the max"""
<|body_0|>
def diStringMatchErrror(self, S: str) -> List[int]:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def diStringMatch(self, S: str) -> List[int]:
"""Looking at prev rather than cur If "I", then put smallest as prev. Increase from the min If "D", then put the largest as prev. Decrese from the max"""
mini, maxa = (0, len(S))
ret = []
for c in S:
if c == 'I... | the_stack_v2_python_sparse | _algorithms_challenges/leetcode/LeetCode/942 DI String Match.py | syurskyi/Algorithms_and_Data_Structure | train | 4 | |
1889934b14d1cee0ce13c5c48692522caac2fe78 | [
"ws = set(wordDict)\nif s in ws:\n return True\ndp = [False for _ in range(len(s) + 1)]\ndp[0] = True\nfor end in range(len(dp)):\n for start in range(end):\n if dp[start] and s[start:end] in ws:\n dp[end] = True\nreturn dp[-1]",
"ws = set(wordDict)\nif s in ws:\n return True\nstack = [... | <|body_start_0|>
ws = set(wordDict)
if s in ws:
return True
dp = [False for _ in range(len(s) + 1)]
dp[0] = True
for end in range(len(dp)):
for start in range(end):
if dp[start] and s[start:end] in ws:
dp[end] = True
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wordBreak2(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_0|>
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_007703 | 2,198 | no_license | [
{
"docstring": ":type s: str :type wordDict: List[str] :rtype: bool",
"name": "wordBreak2",
"signature": "def wordBreak2(self, s, wordDict)"
},
{
"docstring": ":type s: str :type wordDict: List[str] :rtype: bool",
"name": "wordBreak",
"signature": "def wordBreak(self, s, wordDict)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001416 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak2(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak2(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
<|... | b4da922c4e8406c486760639b71e3ec50283ca43 | <|skeleton|>
class Solution:
def wordBreak2(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_0|>
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def wordBreak2(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
ws = set(wordDict)
if s in ws:
return True
dp = [False for _ in range(len(s) + 1)]
dp[0] = True
for end in range(len(dp)):
for start in... | the_stack_v2_python_sparse | current_session/python/139_redo2.py | YJL33/LeetCode | train | 3 | |
b5256b0fe198c2c8832405b53ac4a10fd5b8be39 | [
"from core.tracing import get_tracer\nself.__tracer = get_tracer('CSVDevice')\nself.__tracer.info('Initializing CSVDevice')\nself.name = name\nself.core = core_services\nself.tracer = get_tracer(name)\nself.tdict = {}\nself.prop_names = []\nself.dm = self.core.get_service('device_driver_manager')\nself.channel_mana... | <|body_start_0|>
from core.tracing import get_tracer
self.__tracer = get_tracer('CSVDevice')
self.__tracer.info('Initializing CSVDevice')
self.name = name
self.core = core_services
self.tracer = get_tracer(name)
self.tdict = {}
self.prop_names = []
... | - name: CSVDevice driver: devices.csv_device:CSVDevice settings: channel_pattern: "*.csv_input" delimiter: ',' column_names: - "timestamp" - "status" - "error_msg" CSVDevice is a virtual device that parsed a delimited stream of data. The delimited data is then returned to the source's parent driver as new properties na... | CSVDevice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSVDevice:
"""- name: CSVDevice driver: devices.csv_device:CSVDevice settings: channel_pattern: "*.csv_input" delimiter: ',' column_names: - "timestamp" - "status" - "error_msg" CSVDevice is a virtual device that parsed a delimited stream of data. The delimited data is then returned to the source... | stack_v2_sparse_classes_10k_train_007704 | 9,108 | no_license | [
{
"docstring": "Standard device init function.",
"name": "__init__",
"signature": "def __init__(self, name, core_services)"
},
{
"docstring": "This procedure processes that match the pattern, then subscribes to those channels to continue processing upon updates.",
"name": "start",
"signa... | 5 | null | Implement the Python class `CSVDevice` described below.
Class description:
- name: CSVDevice driver: devices.csv_device:CSVDevice settings: channel_pattern: "*.csv_input" delimiter: ',' column_names: - "timestamp" - "status" - "error_msg" CSVDevice is a virtual device that parsed a delimited stream of data. The delimi... | Implement the Python class `CSVDevice` described below.
Class description:
- name: CSVDevice driver: devices.csv_device:CSVDevice settings: channel_pattern: "*.csv_input" delimiter: ',' column_names: - "timestamp" - "status" - "error_msg" CSVDevice is a virtual device that parsed a delimited stream of data. The delimi... | f36ba29ef883d70f94b8609ff734b5dcde786c66 | <|skeleton|>
class CSVDevice:
"""- name: CSVDevice driver: devices.csv_device:CSVDevice settings: channel_pattern: "*.csv_input" delimiter: ',' column_names: - "timestamp" - "status" - "error_msg" CSVDevice is a virtual device that parsed a delimited stream of data. The delimited data is then returned to the source... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CSVDevice:
"""- name: CSVDevice driver: devices.csv_device:CSVDevice settings: channel_pattern: "*.csv_input" delimiter: ',' column_names: - "timestamp" - "status" - "error_msg" CSVDevice is a virtual device that parsed a delimited stream of data. The delimited data is then returned to the source's parent dri... | the_stack_v2_python_sparse | src/devices/csv_device.py | bernhara/DigiGateway4Raph | train | 0 |
8f364b2151b821d8ce85ebe1ce3a3d4ffed67940 | [
"n = len(arr)\nleft = [float('inf') for _ in range(n)]\nright = [float('inf') for _ in range(n)]\npresum = {0: -1}\ncurr = 0\nfor i in range(n):\n curr += arr[i]\n if i > 0:\n left[i] = left[i - 1]\n if curr - target in presum:\n left[i] = min(left[i], i - presum[curr - target])\n presum[c... | <|body_start_0|>
n = len(arr)
left = [float('inf') for _ in range(n)]
right = [float('inf') for _ in range(n)]
presum = {0: -1}
curr = 0
for i in range(n):
curr += arr[i]
if i > 0:
left[i] = left[i - 1]
if curr - target ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minSumOfLengths(self, arr: List[int], target: int) -> int:
"""left: left[i] is min subarr len to the left of i right: right[i] is min subarr len to the right of i return min(left[i] + right[i + 1] for i: 0 to n - 2)"""
<|body_0|>
def minSumOfLengths(self, arr: ... | stack_v2_sparse_classes_10k_train_007705 | 3,270 | no_license | [
{
"docstring": "left: left[i] is min subarr len to the left of i right: right[i] is min subarr len to the right of i return min(left[i] + right[i + 1] for i: 0 to n - 2)",
"name": "minSumOfLengths",
"signature": "def minSumOfLengths(self, arr: List[int], target: int) -> int"
},
{
"docstring": "d... | 2 | stack_v2_sparse_classes_30k_train_006202 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minSumOfLengths(self, arr: List[int], target: int) -> int: left: left[i] is min subarr len to the left of i right: right[i] is min subarr len to the right of i return min(lef... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minSumOfLengths(self, arr: List[int], target: int) -> int: left: left[i] is min subarr len to the left of i right: right[i] is min subarr len to the right of i return min(lef... | 6ff1941ff213a843013100ac7033e2d4f90fbd6a | <|skeleton|>
class Solution:
def minSumOfLengths(self, arr: List[int], target: int) -> int:
"""left: left[i] is min subarr len to the left of i right: right[i] is min subarr len to the right of i return min(left[i] + right[i + 1] for i: 0 to n - 2)"""
<|body_0|>
def minSumOfLengths(self, arr: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def minSumOfLengths(self, arr: List[int], target: int) -> int:
"""left: left[i] is min subarr len to the left of i right: right[i] is min subarr len to the right of i return min(left[i] + right[i + 1] for i: 0 to n - 2)"""
n = len(arr)
left = [float('inf') for _ in range(n)]
... | the_stack_v2_python_sparse | Leetcode 1477. Find Two Non-overlapping Sub-arrays Each With Target Sum.py | Chaoran-sjsu/leetcode | train | 0 | |
a314e9d42e749bc9a4413b8e445c96c4ab1a3ace | [
"super(InTriggerDistanceToVehicle, self).__init__(name)\nself.logger.debug('%s.__init__()' % self.__class__.__name__)\nself._other_actor = other_actor\nself._actor = actor\nself._distance = distance",
"new_status = py_trees.common.Status.RUNNING\nego_location = CarlaDataProvider.get_location(self._actor)\nother_l... | <|body_start_0|>
super(InTriggerDistanceToVehicle, self).__init__(name)
self.logger.debug('%s.__init__()' % self.__class__.__name__)
self._other_actor = other_actor
self._actor = actor
self._distance = distance
<|end_body_0|>
<|body_start_1|>
new_status = py_trees.common... | This class contains the trigger distance (condition) between to actors of a scenario Important parameters: - actor: CARLA actor to execute the behavior - other_actor: Reference CARLA actor - name: Name of the condition - distance: Trigger distance between the two actors in meters The condition terminates with SUCCESS, ... | InTriggerDistanceToVehicle | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InTriggerDistanceToVehicle:
"""This class contains the trigger distance (condition) between to actors of a scenario Important parameters: - actor: CARLA actor to execute the behavior - other_actor: Reference CARLA actor - name: Name of the condition - distance: Trigger distance between the two ac... | stack_v2_sparse_classes_10k_train_007706 | 18,494 | permissive | [
{
"docstring": "Setup trigger distance",
"name": "__init__",
"signature": "def __init__(self, other_actor, actor, distance, name='TriggerDistanceToVehicle')"
},
{
"docstring": "Check if the ego vehicle is within trigger distance to other actor",
"name": "update",
"signature": "def update... | 2 | stack_v2_sparse_classes_30k_train_000985 | Implement the Python class `InTriggerDistanceToVehicle` described below.
Class description:
This class contains the trigger distance (condition) between to actors of a scenario Important parameters: - actor: CARLA actor to execute the behavior - other_actor: Reference CARLA actor - name: Name of the condition - distan... | Implement the Python class `InTriggerDistanceToVehicle` described below.
Class description:
This class contains the trigger distance (condition) between to actors of a scenario Important parameters: - actor: CARLA actor to execute the behavior - other_actor: Reference CARLA actor - name: Name of the condition - distan... | 8ab0894b92e1f994802a218002021ee075c405bf | <|skeleton|>
class InTriggerDistanceToVehicle:
"""This class contains the trigger distance (condition) between to actors of a scenario Important parameters: - actor: CARLA actor to execute the behavior - other_actor: Reference CARLA actor - name: Name of the condition - distance: Trigger distance between the two ac... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InTriggerDistanceToVehicle:
"""This class contains the trigger distance (condition) between to actors of a scenario Important parameters: - actor: CARLA actor to execute the behavior - other_actor: Reference CARLA actor - name: Name of the condition - distance: Trigger distance between the two actors in meter... | the_stack_v2_python_sparse | carla_rllib/carla_rllib-prak_evaluator-carla_rllib-prak_evaluator/carla_rllib/prak_evaluator/srunner/scenarioconfigs/scenariomanager/scenarioatomics/atomic_trigger_conditions.py | TinaMenke/Deep-Reinforcement-Learning | train | 9 |
cc17d071b4a5186f64619792d23a41a1018ffd9c | [
"self.clustering = clustering\nself.cluster_stabilities = cluster_stabilities\nself._descendant_cache = dict()",
"cache_id = (cluster_id_1, cluster_id_2)\nif cache_id in self._descendant_cache:\n return self._descendant_cache[cache_id]\ncluster_intersection = self.clustering[cluster_id_1] & self.clustering[clu... | <|body_start_0|>
self.clustering = clustering
self.cluster_stabilities = cluster_stabilities
self._descendant_cache = dict()
<|end_body_0|>
<|body_start_1|>
cache_id = (cluster_id_1, cluster_id_2)
if cache_id in self._descendant_cache:
return self._descendant_cache[c... | Finds child-parent relationships and removes children if parent is better than worse child, otherwise it removes parent. | ClusterDeduper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClusterDeduper:
"""Finds child-parent relationships and removes children if parent is better than worse child, otherwise it removes parent."""
def __init__(self, clustering, cluster_stabilities):
""":param clustering: cluster_id -> set of points :type clustering: dict[int, set[collec... | stack_v2_sparse_classes_10k_train_007707 | 4,546 | permissive | [
{
"docstring": ":param clustering: cluster_id -> set of points :type clustering: dict[int, set[collections.Hashable]] :param cluster_stabilities: :type cluster_stabilities: dict[int, numbers.Real]",
"name": "__init__",
"signature": "def __init__(self, clustering, cluster_stabilities)"
},
{
"docs... | 3 | stack_v2_sparse_classes_30k_train_001207 | Implement the Python class `ClusterDeduper` described below.
Class description:
Finds child-parent relationships and removes children if parent is better than worse child, otherwise it removes parent.
Method signatures and docstrings:
- def __init__(self, clustering, cluster_stabilities): :param clustering: cluster_i... | Implement the Python class `ClusterDeduper` described below.
Class description:
Finds child-parent relationships and removes children if parent is better than worse child, otherwise it removes parent.
Method signatures and docstrings:
- def __init__(self, clustering, cluster_stabilities): :param clustering: cluster_i... | bbf24fa7b80d32fae4b8c973a8fc3654eb63cadf | <|skeleton|>
class ClusterDeduper:
"""Finds child-parent relationships and removes children if parent is better than worse child, otherwise it removes parent."""
def __init__(self, clustering, cluster_stabilities):
""":param clustering: cluster_id -> set of points :type clustering: dict[int, set[collec... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ClusterDeduper:
"""Finds child-parent relationships and removes children if parent is better than worse child, otherwise it removes parent."""
def __init__(self, clustering, cluster_stabilities):
""":param clustering: cluster_id -> set of points :type clustering: dict[int, set[collections.Hashabl... | the_stack_v2_python_sparse | python/analysis/ClusterDeduper.py | nog642/himag-release-asonam | train | 0 |
eb640963f9ed25f83d8df1698d6f0f5713419449 | [
"if 'modifier' in kwargs:\n self.modifier = kwargs['modifier']\nelif len(args) > 2:\n self.modifier = args[2]\n args = args[:2]\nelse:\n self.modifier = lambda x: x\nif not six.callable(self.modifier):\n raise TypeError('itermod(o, modifier): modifier must be callable')\nsuper(itermod, self).__init__... | <|body_start_0|>
if 'modifier' in kwargs:
self.modifier = kwargs['modifier']
elif len(args) > 2:
self.modifier = args[2]
args = args[:2]
else:
self.modifier = lambda x: x
if not six.callable(self.modifier):
raise TypeError('iter... | An iterator object that supports modifying items as they are returned. >>> a = [" A list ", ... " of strings ", ... " with ", ... " extra ", ... " whitespace. "] >>> modifier = lambda s: s.strip().replace('with', 'without') >>> for s in itermod(a, modifier=modifier): ... print('"%s"' % s) "A list" "of strings" "without... | itermod | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class itermod:
"""An iterator object that supports modifying items as they are returned. >>> a = [" A list ", ... " of strings ", ... " with ", ... " extra ", ... " whitespace. "] >>> modifier = lambda s: s.strip().replace('with', 'without') >>> for s in itermod(a, modifier=modifier): ... print('"%s"' ... | stack_v2_sparse_classes_10k_train_007708 | 8,468 | permissive | [
{
"docstring": "__init__(o, sentinel=None, modifier=lambda x: x)",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Cache `n` modified items. If `n` is 0 or None, 1 item is cached. Each item returned by the iterator is passed through the `itermod.modified... | 2 | null | Implement the Python class `itermod` described below.
Class description:
An iterator object that supports modifying items as they are returned. >>> a = [" A list ", ... " of strings ", ... " with ", ... " extra ", ... " whitespace. "] >>> modifier = lambda s: s.strip().replace('with', 'without') >>> for s in itermod(a... | Implement the Python class `itermod` described below.
Class description:
An iterator object that supports modifying items as they are returned. >>> a = [" A list ", ... " of strings ", ... " with ", ... " extra ", ... " whitespace. "] >>> modifier = lambda s: s.strip().replace('with', 'without') >>> for s in itermod(a... | 05dbd4575d01a213f3f4d69aa4968473f2536142 | <|skeleton|>
class itermod:
"""An iterator object that supports modifying items as they are returned. >>> a = [" A list ", ... " of strings ", ... " with ", ... " extra ", ... " whitespace. "] >>> modifier = lambda s: s.strip().replace('with', 'without') >>> for s in itermod(a, modifier=modifier): ... print('"%s"' ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class itermod:
"""An iterator object that supports modifying items as they are returned. >>> a = [" A list ", ... " of strings ", ... " with ", ... " extra ", ... " whitespace. "] >>> modifier = lambda s: s.strip().replace('with', 'without') >>> for s in itermod(a, modifier=modifier): ... print('"%s"' % s) "A list"... | the_stack_v2_python_sparse | python/helpers/pockets/iterators.py | JetBrains/intellij-community | train | 16,288 |
d4bf322be501cd9bfbf4c71d03cc1afaa6da019b | [
"self._path = path\nself._summary_dirs: List[Path] = []\nevent_files = self._discover_event_files(self._path)\ncb_summaries = self._discover_cerebras_summary_dirs(event_files)\nself._summary_dirs = self._discover_tensor_summary_dirs(cb_summaries)\nif not self._summary_dirs:\n logging.warning(f'Could not find any... | <|body_start_0|>
self._path = path
self._summary_dirs: List[Path] = []
event_files = self._discover_event_files(self._path)
cb_summaries = self._discover_cerebras_summary_dirs(event_files)
self._summary_dirs = self._discover_tensor_summary_dirs(cb_summaries)
if not self._... | Class for reading summarized tensors. This class works in tandem with `TensorSummary` defined above. It provides general convenience APIs for inspecting tensor summaries produced by a run. Currently this class does not do any caching. So it can be used to inspect a live run. As more data becomes available, calling the ... | TensorSummaryReader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TensorSummaryReader:
"""Class for reading summarized tensors. This class works in tandem with `TensorSummary` defined above. It provides general convenience APIs for inspecting tensor summaries produced by a run. Currently this class does not do any caching. So it can be used to inspect a live ru... | stack_v2_sparse_classes_10k_train_007709 | 16,325 | permissive | [
{
"docstring": "Constructs a `TensorSummaryReader` instance. Args: path: Path to a Tensorboard events file or a directory containing Tensorboard events files. Location of tensor summaries are inferred from these events files as there is a one-to-one mapping from Tensorboard events files and tensor summary direc... | 6 | stack_v2_sparse_classes_30k_train_005550 | Implement the Python class `TensorSummaryReader` described below.
Class description:
Class for reading summarized tensors. This class works in tandem with `TensorSummary` defined above. It provides general convenience APIs for inspecting tensor summaries produced by a run. Currently this class does not do any caching.... | Implement the Python class `TensorSummaryReader` described below.
Class description:
Class for reading summarized tensors. This class works in tandem with `TensorSummary` defined above. It provides general convenience APIs for inspecting tensor summaries produced by a run. Currently this class does not do any caching.... | 97bdaf4460ace1681ad437b07ba33f0e179f5ca4 | <|skeleton|>
class TensorSummaryReader:
"""Class for reading summarized tensors. This class works in tandem with `TensorSummary` defined above. It provides general convenience APIs for inspecting tensor summaries produced by a run. Currently this class does not do any caching. So it can be used to inspect a live ru... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TensorSummaryReader:
"""Class for reading summarized tensors. This class works in tandem with `TensorSummary` defined above. It provides general convenience APIs for inspecting tensor summaries produced by a run. Currently this class does not do any caching. So it can be used to inspect a live run. As more da... | the_stack_v2_python_sparse | modelzoo/common/pytorch/summaries/tensor_summary.py | Cerebras/modelzoo | train | 644 |
dafeb5ffc6685f724a581d5e9d23054b7d161d71 | [
"self.bbox_roi_extractor = build_roi_extractor(bbox_roi_extractor)\nif bbox_head.type == 'Shared2FCBBoxHead':\n bbox_head.type = 'CustomConvFCBBoxHead'\nself.bbox_head = build_head(bbox_head)",
"rois = bbox2roi([res.bboxes for res in sampling_results])\nbbox_results = self._bbox_forward(x, rois)\nlabels, label... | <|body_start_0|>
self.bbox_roi_extractor = build_roi_extractor(bbox_roi_extractor)
if bbox_head.type == 'Shared2FCBBoxHead':
bbox_head.type = 'CustomConvFCBBoxHead'
self.bbox_head = build_head(bbox_head)
<|end_body_0|>
<|body_start_1|>
rois = bbox2roi([res.bboxes for res in ... | CustomROIHead class for OTX. | CustomRoIHead | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomRoIHead:
"""CustomROIHead class for OTX."""
def init_bbox_head(self, bbox_roi_extractor, bbox_head):
"""Initialize ``bbox_head``."""
<|body_0|>
def _bbox_forward_train(self, x, sampling_results, gt_bboxes, gt_labels, img_metas):
"""Run forward function and ... | stack_v2_sparse_classes_10k_train_007710 | 8,559 | permissive | [
{
"docstring": "Initialize ``bbox_head``.",
"name": "init_bbox_head",
"signature": "def init_bbox_head(self, bbox_roi_extractor, bbox_head)"
},
{
"docstring": "Run forward function and calculate loss for box head in training.",
"name": "_bbox_forward_train",
"signature": "def _bbox_forwa... | 2 | null | Implement the Python class `CustomRoIHead` described below.
Class description:
CustomROIHead class for OTX.
Method signatures and docstrings:
- def init_bbox_head(self, bbox_roi_extractor, bbox_head): Initialize ``bbox_head``.
- def _bbox_forward_train(self, x, sampling_results, gt_bboxes, gt_labels, img_metas): Run ... | Implement the Python class `CustomRoIHead` described below.
Class description:
CustomROIHead class for OTX.
Method signatures and docstrings:
- def init_bbox_head(self, bbox_roi_extractor, bbox_head): Initialize ``bbox_head``.
- def _bbox_forward_train(self, x, sampling_results, gt_bboxes, gt_labels, img_metas): Run ... | 80454808b38727e358e8b880043eeac0f18152fb | <|skeleton|>
class CustomRoIHead:
"""CustomROIHead class for OTX."""
def init_bbox_head(self, bbox_roi_extractor, bbox_head):
"""Initialize ``bbox_head``."""
<|body_0|>
def _bbox_forward_train(self, x, sampling_results, gt_bboxes, gt_labels, img_metas):
"""Run forward function and ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CustomRoIHead:
"""CustomROIHead class for OTX."""
def init_bbox_head(self, bbox_roi_extractor, bbox_head):
"""Initialize ``bbox_head``."""
self.bbox_roi_extractor = build_roi_extractor(bbox_roi_extractor)
if bbox_head.type == 'Shared2FCBBoxHead':
bbox_head.type = 'Cust... | the_stack_v2_python_sparse | src/otx/algorithms/detection/adapters/mmdet/models/heads/custom_roi_head.py | openvinotoolkit/training_extensions | train | 397 |
a6fd5a79e0892cbf08161f34eed2ade38d5f07fd | [
"v1 = Vector(v1, copy=False)\nv2 = Vector(v2, copy=False)\nn1 = v1.norm()\nn2 = v2.norm()\nif n1 == 0 or n2 == 0:\n raise ValueError(\"Can't calculate angle between zero length vectors !\")\ncos_a = v1.dot(v2) / (n1 * n2)\ncos_a = max(-1.0, min(1.0, cos_a))\nreturn math.acos(cos_a)",
"p1 = Vector(p1, copy=Fals... | <|body_start_0|>
v1 = Vector(v1, copy=False)
v2 = Vector(v2, copy=False)
n1 = v1.norm()
n2 = v2.norm()
if n1 == 0 or n2 == 0:
raise ValueError("Can't calculate angle between zero length vectors !")
cos_a = v1.dot(v2) / (n1 * n2)
cos_a = max(-1.0, min(1... | Represents a triangle constructed from different other geometrical entities. | Triangle | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Triangle:
"""Represents a triangle constructed from different other geometrical entities."""
def angle_between_vectors(v1, v2):
"""Calculates the angle between <v1> and <v2>. The result is in the range [0, pi] On degenerate input (any of the vectors of norm 0) will raise ValueError."... | stack_v2_sparse_classes_10k_train_007711 | 1,355 | permissive | [
{
"docstring": "Calculates the angle between <v1> and <v2>. The result is in the range [0, pi] On degenerate input (any of the vectors of norm 0) will raise ValueError.",
"name": "angle_between_vectors",
"signature": "def angle_between_vectors(v1, v2)"
},
{
"docstring": "Calculates the angle p1-... | 2 | stack_v2_sparse_classes_30k_train_006557 | Implement the Python class `Triangle` described below.
Class description:
Represents a triangle constructed from different other geometrical entities.
Method signatures and docstrings:
- def angle_between_vectors(v1, v2): Calculates the angle between <v1> and <v2>. The result is in the range [0, pi] On degenerate inp... | Implement the Python class `Triangle` described below.
Class description:
Represents a triangle constructed from different other geometrical entities.
Method signatures and docstrings:
- def angle_between_vectors(v1, v2): Calculates the angle between <v1> and <v2>. The result is in the range [0, pi] On degenerate inp... | 43cceabf5fd4ddf6dbfd8c6d5329b9a4bba4ecb7 | <|skeleton|>
class Triangle:
"""Represents a triangle constructed from different other geometrical entities."""
def angle_between_vectors(v1, v2):
"""Calculates the angle between <v1> and <v2>. The result is in the range [0, pi] On degenerate input (any of the vectors of norm 0) will raise ValueError."... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Triangle:
"""Represents a triangle constructed from different other geometrical entities."""
def angle_between_vectors(v1, v2):
"""Calculates the angle between <v1> and <v2>. The result is in the range [0, pi] On degenerate input (any of the vectors of norm 0) will raise ValueError."""
v1... | the_stack_v2_python_sparse | brlcad/vmath/triangle.py | kanzure/python-brlcad | train | 6 |
9290f3a963fc0ba881cc178c29b9f4bbc46c3b9d | [
"create_empty_db()\nadd_customer(**user_1)\nquery = Customer.get(Customer.customer_id == user_1['customer_id'])\nself.assertEqual(user_1['name'], query.customer_name)\nself.assertEqual(user_1['lastname'], query.customer_last_name)\nself.assertEqual(user_1['home_address'], query.customer_address)\nself.assertEqual(u... | <|body_start_0|>
create_empty_db()
add_customer(**user_1)
query = Customer.get(Customer.customer_id == user_1['customer_id'])
self.assertEqual(user_1['name'], query.customer_name)
self.assertEqual(user_1['lastname'], query.customer_last_name)
self.assertEqual(user_1['home... | Tests basic_operations program, along with customer_model | BasicOperationsTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicOperationsTest:
"""Tests basic_operations program, along with customer_model"""
def test_add_customer(self):
"""Tests if a new customer is added to database"""
<|body_0|>
def test_search_customer(self):
"""Tests customer search function"""
<|body_1|>... | stack_v2_sparse_classes_10k_train_007712 | 5,205 | no_license | [
{
"docstring": "Tests if a new customer is added to database",
"name": "test_add_customer",
"signature": "def test_add_customer(self)"
},
{
"docstring": "Tests customer search function",
"name": "test_search_customer",
"signature": "def test_search_customer(self)"
},
{
"docstring... | 6 | stack_v2_sparse_classes_30k_train_004233 | Implement the Python class `BasicOperationsTest` described below.
Class description:
Tests basic_operations program, along with customer_model
Method signatures and docstrings:
- def test_add_customer(self): Tests if a new customer is added to database
- def test_search_customer(self): Tests customer search function
... | Implement the Python class `BasicOperationsTest` described below.
Class description:
Tests basic_operations program, along with customer_model
Method signatures and docstrings:
- def test_add_customer(self): Tests if a new customer is added to database
- def test_search_customer(self): Tests customer search function
... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class BasicOperationsTest:
"""Tests basic_operations program, along with customer_model"""
def test_add_customer(self):
"""Tests if a new customer is added to database"""
<|body_0|>
def test_search_customer(self):
"""Tests customer search function"""
<|body_1|>... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BasicOperationsTest:
"""Tests basic_operations program, along with customer_model"""
def test_add_customer(self):
"""Tests if a new customer is added to database"""
create_empty_db()
add_customer(**user_1)
query = Customer.get(Customer.customer_id == user_1['customer_id'])... | the_stack_v2_python_sparse | students/njschafi/Lesson04/assignment/test_basic_operations.py | JavaRod/SP_Python220B_2019 | train | 1 |
de1a59e11cf5e04112c8a67b84e527ba273b8d34 | [
"if not nums:\n return 0\nmydict = {}\nres = 1\nfor num in nums:\n if num in mydict.keys():\n continue\n mydict[num] = 1\n ll = num\n rr = num\n val = 1\n if num - 1 in mydict.keys():\n ll = num - mydict[num - 1]\n val += mydict[num - 1]\n if num + 1 in mydict.keys():\n ... | <|body_start_0|>
if not nums:
return 0
mydict = {}
res = 1
for num in nums:
if num in mydict.keys():
continue
mydict[num] = 1
ll = num
rr = num
val = 1
if num - 1 in mydict.keys():
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestConsecutive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def longestConsecutive2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def longestConsecutive3(self, nums):
""":type nums: List[int]... | stack_v2_sparse_classes_10k_train_007713 | 2,537 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "longestConsecutive",
"signature": "def longestConsecutive(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "longestConsecutive2",
"signature": "def longestConsecutive2(self, nums)"
},
{
"docst... | 3 | stack_v2_sparse_classes_30k_val_000002 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestConsecutive(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive2(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive3(self, num... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestConsecutive(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive2(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive3(self, num... | 690b685048c8e89d26047b6bc48b5f9af7d59cbb | <|skeleton|>
class Solution:
def longestConsecutive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def longestConsecutive2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def longestConsecutive3(self, nums):
""":type nums: List[int]... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def longestConsecutive(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 0
mydict = {}
res = 1
for num in nums:
if num in mydict.keys():
continue
mydict[num] = 1
ll = num
... | the_stack_v2_python_sparse | 数组/128. 最长连续序列.py | SimmonsChen/LeetCode | train | 0 | |
620040f16423e947db1c5e7c291bb39f196554cf | [
"self.students = []\nself.grades = {}\nself.isSorted = True",
"if student in self.students:\n raise ValueError('Duplicate Error')\nself.students.append(student)\nself.grades[student.getIdNum()] = []\nself.isSorted = False",
"try:\n self.grades[student.getIdNum()].append(grade)\nexcept KeyError:\n raise... | <|body_start_0|>
self.students = []
self.grades = {}
self.isSorted = True
<|end_body_0|>
<|body_start_1|>
if student in self.students:
raise ValueError('Duplicate Error')
self.students.append(student)
self.grades[student.getIdNum()] = []
self.isSorted... | A mapping from students to a list of grades | Grades | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Grades:
"""A mapping from students to a list of grades"""
def __init__(self):
"""Creates empty grade book"""
<|body_0|>
def addStudent(self, student):
"""Assumes: student is of type student Add student to the grade book."""
<|body_1|>
def addGrades(s... | stack_v2_sparse_classes_10k_train_007714 | 2,545 | no_license | [
{
"docstring": "Creates empty grade book",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Assumes: student is of type student Add student to the grade book.",
"name": "addStudent",
"signature": "def addStudent(self, student)"
},
{
"docstring": "Assumes: ... | 6 | stack_v2_sparse_classes_30k_train_004679 | Implement the Python class `Grades` described below.
Class description:
A mapping from students to a list of grades
Method signatures and docstrings:
- def __init__(self): Creates empty grade book
- def addStudent(self, student): Assumes: student is of type student Add student to the grade book.
- def addGrades(self,... | Implement the Python class `Grades` described below.
Class description:
A mapping from students to a list of grades
Method signatures and docstrings:
- def __init__(self): Creates empty grade book
- def addStudent(self, student): Assumes: student is of type student Add student to the grade book.
- def addGrades(self,... | 93e5e2a5e9355b4dc94ce2071351ee4bf280b9a8 | <|skeleton|>
class Grades:
"""A mapping from students to a list of grades"""
def __init__(self):
"""Creates empty grade book"""
<|body_0|>
def addStudent(self, student):
"""Assumes: student is of type student Add student to the grade book."""
<|body_1|>
def addGrades(s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Grades:
"""A mapping from students to a list of grades"""
def __init__(self):
"""Creates empty grade book"""
self.students = []
self.grades = {}
self.isSorted = True
def addStudent(self, student):
"""Assumes: student is of type student Add student to the grade... | the_stack_v2_python_sparse | python_programming_exercise/classHierarchy/Grades.py | dskeshav/python_practise | train | 0 |
a3e8c17507840336812204f68276dbf8d6dbf2c0 | [
"intervals.append(new_interval)\nintervals = sorted(intervals, cmp_interval)\nreturn self.merge(intervals)",
"if len(intervals) <= 1:\n return intervals\ni = 0\nmerge_intervals = []\nwhile i < len(intervals) - 1:\n interval = intervals[i]\n interval_next = intervals[i + 1]\n start = interval.start\n ... | <|body_start_0|>
intervals.append(new_interval)
intervals = sorted(intervals, cmp_interval)
return self.merge(intervals)
<|end_body_0|>
<|body_start_1|>
if len(intervals) <= 1:
return intervals
i = 0
merge_intervals = []
while i < len(intervals) - 1:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def insert(self, intervals, new_interval):
""":param intervals: List[Interval] :param new_interval: Interval :return: List[Interval]"""
<|body_0|>
def merge(self, intervals):
""":param intervals: List[Interval] :return: List[Interval]"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_007715 | 1,647 | no_license | [
{
"docstring": ":param intervals: List[Interval] :param new_interval: Interval :return: List[Interval]",
"name": "insert",
"signature": "def insert(self, intervals, new_interval)"
},
{
"docstring": ":param intervals: List[Interval] :return: List[Interval]",
"name": "merge",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_004113 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def insert(self, intervals, new_interval): :param intervals: List[Interval] :param new_interval: Interval :return: List[Interval]
- def merge(self, intervals): :param intervals: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def insert(self, intervals, new_interval): :param intervals: List[Interval] :param new_interval: Interval :return: List[Interval]
- def merge(self, intervals): :param intervals: ... | c1c5ee72b8fe608b278ca20a58bc240fdc62b599 | <|skeleton|>
class Solution:
def insert(self, intervals, new_interval):
""":param intervals: List[Interval] :param new_interval: Interval :return: List[Interval]"""
<|body_0|>
def merge(self, intervals):
""":param intervals: List[Interval] :return: List[Interval]"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def insert(self, intervals, new_interval):
""":param intervals: List[Interval] :param new_interval: Interval :return: List[Interval]"""
intervals.append(new_interval)
intervals = sorted(intervals, cmp_interval)
return self.merge(intervals)
def merge(self, interva... | the_stack_v2_python_sparse | 57_insert_interval.py | eazow/leetcode | train | 5 | |
a8a14cc306ad15a2bec7353415321668c425c07c | [
"self.event_str = event_str\nself.date = calendar_util.convert_str_to_date(date_str)\nself.start_time_str = start_time_str\nself.end_time_str = end_time_str",
"date_str = datetime.datetime.strftime(self.date, calendar_util.DATE_STR_FMT)\nret = ' '.join([self.event_str, 'on', date_str])\nif self.start_time_str:\n ... | <|body_start_0|>
self.event_str = event_str
self.date = calendar_util.convert_str_to_date(date_str)
self.start_time_str = start_time_str
self.end_time_str = end_time_str
<|end_body_0|>
<|body_start_1|>
date_str = datetime.datetime.strftime(self.date, calendar_util.DATE_STR_FMT)
... | Class for storing calendar event information. | CalendarEvent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalendarEvent:
"""Class for storing calendar event information."""
def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''):
"""Initialize this CalendarEvent instance."""
<|body_0|>
def __str__(self):
"""Returns the st... | stack_v2_sparse_classes_10k_train_007716 | 1,047 | permissive | [
{
"docstring": "Initialize this CalendarEvent instance.",
"name": "__init__",
"signature": "def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str='')"
},
{
"docstring": "Returns the string representation of this CalendarEvent.",
"name": "__str__",
... | 2 | stack_v2_sparse_classes_30k_train_000284 | Implement the Python class `CalendarEvent` described below.
Class description:
Class for storing calendar event information.
Method signatures and docstrings:
- def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''): Initialize this CalendarEvent instance.
- def __str__(... | Implement the Python class `CalendarEvent` described below.
Class description:
Class for storing calendar event information.
Method signatures and docstrings:
- def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''): Initialize this CalendarEvent instance.
- def __str__(... | 9fdf2f2b4861450fbed64b90b8c7c69b0173e052 | <|skeleton|>
class CalendarEvent:
"""Class for storing calendar event information."""
def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''):
"""Initialize this CalendarEvent instance."""
<|body_0|>
def __str__(self):
"""Returns the st... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CalendarEvent:
"""Class for storing calendar event information."""
def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''):
"""Initialize this CalendarEvent instance."""
self.event_str = event_str
self.date = calendar_util.convert_str_... | the_stack_v2_python_sparse | LTUAssistantPlus/services/calendar/calendar_event.py | Xyaneon/LTUAssistantPlus | train | 0 |
7b96d74e4a927b8f9d62078d8796131a3efa8fad | [
"test_map = dict(working_map)\nabs_rooms = []\nfor i in range(100):\n generator_pos = GeneratorUtil.random_pos(map_size, False)\n room = RoomGenerator.__generate_room(map_size)\n abs_room = GeneratorUtil.offset(generator_pos, room)\n room_clear = GeneratorUtil.check_clearance(test_map, abs_room)\n if... | <|body_start_0|>
test_map = dict(working_map)
abs_rooms = []
for i in range(100):
generator_pos = GeneratorUtil.random_pos(map_size, False)
room = RoomGenerator.__generate_room(map_size)
abs_room = GeneratorUtil.offset(generator_pos, room)
room_cle... | RoomGenerator | [
"MIT",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoomGenerator:
def generate_rooms(working_map, map_size):
"""Generate a list of absoulte-positioned rooms"""
<|body_0|>
def __generate_room(map_size):
"""Generate a room, and return it. A room is defined as a 2D list with MapTileTypes.Floor."""
<|body_1|>
<|... | stack_v2_sparse_classes_10k_train_007717 | 1,518 | permissive | [
{
"docstring": "Generate a list of absoulte-positioned rooms",
"name": "generate_rooms",
"signature": "def generate_rooms(working_map, map_size)"
},
{
"docstring": "Generate a room, and return it. A room is defined as a 2D list with MapTileTypes.Floor.",
"name": "__generate_room",
"signa... | 2 | stack_v2_sparse_classes_30k_train_005851 | Implement the Python class `RoomGenerator` described below.
Class description:
Implement the RoomGenerator class.
Method signatures and docstrings:
- def generate_rooms(working_map, map_size): Generate a list of absoulte-positioned rooms
- def __generate_room(map_size): Generate a room, and return it. A room is defin... | Implement the Python class `RoomGenerator` described below.
Class description:
Implement the RoomGenerator class.
Method signatures and docstrings:
- def generate_rooms(working_map, map_size): Generate a list of absoulte-positioned rooms
- def __generate_room(map_size): Generate a room, and return it. A room is defin... | bce8c262bc80912045a9e5394447b937f9b08f83 | <|skeleton|>
class RoomGenerator:
def generate_rooms(working_map, map_size):
"""Generate a list of absoulte-positioned rooms"""
<|body_0|>
def __generate_room(map_size):
"""Generate a room, and return it. A room is defined as a 2D list with MapTileTypes.Floor."""
<|body_1|>
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RoomGenerator:
def generate_rooms(working_map, map_size):
"""Generate a list of absoulte-positioned rooms"""
test_map = dict(working_map)
abs_rooms = []
for i in range(100):
generator_pos = GeneratorUtil.random_pos(map_size, False)
room = RoomGenerator._... | the_stack_v2_python_sparse | ageofwinds/map/mapGenerator/roomGenerator.py | pbrn46/ageofwinds | train | 0 | |
e3f1e91a022165a526299378047d7249c65a6eaa | [
"username = request.GET.get('username', None)\nif username is not None:\n cm = get_object_or_404(CM, user__username=username)\n serializer = CMSerializer(cm)\n return JsonResponse({'cms': [serializer.data]}, safe=False)\nelse:\n cms = CM.objects.all()\n serializer = CMSerializer(cms, many=True)\n ... | <|body_start_0|>
username = request.GET.get('username', None)
if username is not None:
cm = get_object_or_404(CM, user__username=username)
serializer = CMSerializer(cm)
return JsonResponse({'cms': [serializer.data]}, safe=False)
else:
cms = CM.obje... | 课程负责人view | CMs | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CMs:
"""课程负责人view"""
def get(self, request):
"""查询课程负责人"""
<|body_0|>
def post(self, request):
"""增加课程负责人"""
<|body_1|>
def delete(self, request):
"""删除课程负责人"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
username = request... | stack_v2_sparse_classes_10k_train_007718 | 16,053 | permissive | [
{
"docstring": "查询课程负责人",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "增加课程负责人",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "删除课程负责人",
"name": "delete",
"signature": "def delete(self, request)"
}
] | 3 | stack_v2_sparse_classes_30k_train_006995 | Implement the Python class `CMs` described below.
Class description:
课程负责人view
Method signatures and docstrings:
- def get(self, request): 查询课程负责人
- def post(self, request): 增加课程负责人
- def delete(self, request): 删除课程负责人 | Implement the Python class `CMs` described below.
Class description:
课程负责人view
Method signatures and docstrings:
- def get(self, request): 查询课程负责人
- def post(self, request): 增加课程负责人
- def delete(self, request): 删除课程负责人
<|skeleton|>
class CMs:
"""课程负责人view"""
def get(self, request):
"""查询课程负责人"""
... | 7aaa1be773718de1beb3ce0080edca7c4114b7ad | <|skeleton|>
class CMs:
"""课程负责人view"""
def get(self, request):
"""查询课程负责人"""
<|body_0|>
def post(self, request):
"""增加课程负责人"""
<|body_1|>
def delete(self, request):
"""删除课程负责人"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CMs:
"""课程负责人view"""
def get(self, request):
"""查询课程负责人"""
username = request.GET.get('username', None)
if username is not None:
cm = get_object_or_404(CM, user__username=username)
serializer = CMSerializer(cm)
return JsonResponse({'cms': [seria... | the_stack_v2_python_sparse | user/views.py | MIXISAMA/MIS-backend | train | 0 |
85e805c14e8b7a3c966c67e06320c6e74c26b8cd | [
"self.dist = dist\nself.accel = accel\nself.decel = decel\nd0 = dist * decel / (accel + decel)\nd1 = 0\nt0 = sqrt(2 * d0 / accel)\nt1 = 0\nt2 = accel / decel * t0\nvc = accel * t0\nif vc > max_speed:\n t0 = max_speed / accel\n t2 = max_speed / decel\n d0 = max_speed * t0 / 2\n d1 = dist - 0.5 * (accel *... | <|body_start_0|>
self.dist = dist
self.accel = accel
self.decel = decel
d0 = dist * decel / (accel + decel)
d1 = 0
t0 = sqrt(2 * d0 / accel)
t1 = 0
t2 = accel / decel * t0
vc = accel * t0
if vc > max_speed:
t0 = max_speed / acce... | The model of movement from A to B. The speed at point A and B is 0. The rates of acceleration and deceleration are constant. | AToBConstAccel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AToBConstAccel:
"""The model of movement from A to B. The speed at point A and B is 0. The rates of acceleration and deceleration are constant."""
def __init__(self, dist, accel, decel, max_speed=inf):
"""dist: The distance between A to B; accel: The rate of acceleration; decel: The ... | stack_v2_sparse_classes_10k_train_007719 | 1,724 | no_license | [
{
"docstring": "dist: The distance between A to B; accel: The rate of acceleration; decel: The rate of deceleration; max_speed: Optional. The max speed of movement.",
"name": "__init__",
"signature": "def __init__(self, dist, accel, decel, max_speed=inf)"
},
{
"docstring": "Calculating the curre... | 2 | stack_v2_sparse_classes_30k_val_000021 | Implement the Python class `AToBConstAccel` described below.
Class description:
The model of movement from A to B. The speed at point A and B is 0. The rates of acceleration and deceleration are constant.
Method signatures and docstrings:
- def __init__(self, dist, accel, decel, max_speed=inf): dist: The distance bet... | Implement the Python class `AToBConstAccel` described below.
Class description:
The model of movement from A to B. The speed at point A and B is 0. The rates of acceleration and deceleration are constant.
Method signatures and docstrings:
- def __init__(self, dist, accel, decel, max_speed=inf): dist: The distance bet... | 3945ef235ac8e7a7a66fec018597aa9b34b0a4e6 | <|skeleton|>
class AToBConstAccel:
"""The model of movement from A to B. The speed at point A and B is 0. The rates of acceleration and deceleration are constant."""
def __init__(self, dist, accel, decel, max_speed=inf):
"""dist: The distance between A to B; accel: The rate of acceleration; decel: The ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AToBConstAccel:
"""The model of movement from A to B. The speed at point A and B is 0. The rates of acceleration and deceleration are constant."""
def __init__(self, dist, accel, decel, max_speed=inf):
"""dist: The distance between A to B; accel: The rate of acceleration; decel: The rate of decel... | the_stack_v2_python_sparse | wavesynlib/formulae/motion.py | xialulee/WaveSyn | train | 9 |
8bb053396bfc84bed1b2e1f9f358852fc1435138 | [
"super(LabelSmoothingLoss, self).__init__()\nself.confidence = 1.0 - smoothing\nself.smoothing = smoothing\nself.dim = dim",
"with torch.no_grad():\n true_dist = torch.zeros_like(pred)\n true_dist.fill_(self.smoothing / (pred.shape[-1] - 1))\n true_dist.scatter_(1, target.data.unsqueeze(1), self.confiden... | <|body_start_0|>
super(LabelSmoothingLoss, self).__init__()
self.confidence = 1.0 - smoothing
self.smoothing = smoothing
self.dim = dim
<|end_body_0|>
<|body_start_1|>
with torch.no_grad():
true_dist = torch.zeros_like(pred)
true_dist.fill_(self.smoothing... | Create a NLL loss but by employing label smoothing. Particularly useful when the data is not 100% reliable, and there is a probability that other labels can actually be the real one. Credits to github users @ https://github.com/pytorch/pytorch/issues/7455 | LabelSmoothingLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabelSmoothingLoss:
"""Create a NLL loss but by employing label smoothing. Particularly useful when the data is not 100% reliable, and there is a probability that other labels can actually be the real one. Credits to github users @ https://github.com/pytorch/pytorch/issues/7455"""
def __init... | stack_v2_sparse_classes_10k_train_007720 | 17,400 | permissive | [
{
"docstring": "Create the label smoothing loss :param smoothing: smooting probability (0 for no smoothing, 1 for full smoothing) :param dim: dimension to apply the loss sum",
"name": "__init__",
"signature": "def __init__(self, smoothing=0.0, dim=-1)"
},
{
"docstring": "Compute the forward pass... | 2 | stack_v2_sparse_classes_30k_train_003234 | Implement the Python class `LabelSmoothingLoss` described below.
Class description:
Create a NLL loss but by employing label smoothing. Particularly useful when the data is not 100% reliable, and there is a probability that other labels can actually be the real one. Credits to github users @ https://github.com/pytorch... | Implement the Python class `LabelSmoothingLoss` described below.
Class description:
Create a NLL loss but by employing label smoothing. Particularly useful when the data is not 100% reliable, and there is a probability that other labels can actually be the real one. Credits to github users @ https://github.com/pytorch... | 1b9fbe6c89c74dc706fd8d3b11ea08977ba2c1d3 | <|skeleton|>
class LabelSmoothingLoss:
"""Create a NLL loss but by employing label smoothing. Particularly useful when the data is not 100% reliable, and there is a probability that other labels can actually be the real one. Credits to github users @ https://github.com/pytorch/pytorch/issues/7455"""
def __init... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LabelSmoothingLoss:
"""Create a NLL loss but by employing label smoothing. Particularly useful when the data is not 100% reliable, and there is a probability that other labels can actually be the real one. Credits to github users @ https://github.com/pytorch/pytorch/issues/7455"""
def __init__(self, smoo... | the_stack_v2_python_sparse | models/interaction_modules/train_aux.py | pedro-mgb/pedestrian-arc-lstm-smf | train | 4 |
f9d783542e5f8bbbe8ab5d55bf4f8462eebf5804 | [
"left, right = (0, len(height) - 1)\narea_max = (right - left) * min(height[left], height[right])\nwhile left < right:\n if height[left] <= height[right]:\n index = left + 1\n while height[index] <= height[left]:\n index += 1\n if index >= right:\n return area_m... | <|body_start_0|>
left, right = (0, len(height) - 1)
area_max = (right - left) * min(height[left], height[right])
while left < right:
if height[left] <= height[right]:
index = left + 1
while height[index] <= height[left]:
index += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxArea1(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
left, right = (0, len(height) - 1)
a... | stack_v2_sparse_classes_10k_train_007721 | 3,634 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea1",
"signature": "def maxArea1(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea",
"signature": "def maxArea(self, height)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000646 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea1(self, height): :type height: List[int] :rtype: int
- def maxArea(self, height): :type height: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea1(self, height): :type height: List[int] :rtype: int
- def maxArea(self, height): :type height: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxArea1(s... | 4a1747b6497305f3821612d9c358a6795b1690da | <|skeleton|>
class Solution:
def maxArea1(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxArea1(self, height):
""":type height: List[int] :rtype: int"""
left, right = (0, len(height) - 1)
area_max = (right - left) * min(height[left], height[right])
while left < right:
if height[left] <= height[right]:
index = left + 1
... | the_stack_v2_python_sparse | TwoPointers/q011_container_with_most_water.py | sevenhe716/LeetCode | train | 0 | |
ecd2e3126d92251a593524cb4db28a282df66a96 | [
"n = len(g)\ndp = [0] * (1 << n)\nfor i in range(1 << n):\n s = 0\n for j in range(n):\n if i >> j & 1:\n s += g[j]\n for j in range(n):\n if i & 1 << j == 0:\n dp[i | 1 << j] = max(dp[i | 1 << j], dp[i] + int(s % b == 0))\nreturn dp[-1]",
"arr = [0] * b\nfor gg in g:\... | <|body_start_0|>
n = len(g)
dp = [0] * (1 << n)
for i in range(1 << n):
s = 0
for j in range(n):
if i >> j & 1:
s += g[j]
for j in range(n):
if i & 1 << j == 0:
dp[i | 1 << j] = max(dp[i |... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxHappyGroups(self, b: int, g: List[int]) -> int:
"""常规做法：二进制枚举（超时） 1. 本代码可帮助理解题目意思 @param b: @param g: @return:"""
<|body_0|>
def maxHappyGroups(self, b: int, g: List[int]) -> int:
"""如果用2进制枚举会超时，由于客户数量最多30组，采用31进制 @param b: @param g: @return:"""
... | stack_v2_sparse_classes_10k_train_007722 | 2,946 | no_license | [
{
"docstring": "常规做法：二进制枚举（超时） 1. 本代码可帮助理解题目意思 @param b: @param g: @return:",
"name": "maxHappyGroups",
"signature": "def maxHappyGroups(self, b: int, g: List[int]) -> int"
},
{
"docstring": "如果用2进制枚举会超时，由于客户数量最多30组，采用31进制 @param b: @param g: @return:",
"name": "maxHappyGroups",
"signatu... | 2 | stack_v2_sparse_classes_30k_train_002448 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxHappyGroups(self, b: int, g: List[int]) -> int: 常规做法：二进制枚举（超时） 1. 本代码可帮助理解题目意思 @param b: @param g: @return:
- def maxHappyGroups(self, b: int, g: List[int]) -> int: 如果用2进制... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxHappyGroups(self, b: int, g: List[int]) -> int: 常规做法：二进制枚举（超时） 1. 本代码可帮助理解题目意思 @param b: @param g: @return:
- def maxHappyGroups(self, b: int, g: List[int]) -> int: 如果用2进制... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def maxHappyGroups(self, b: int, g: List[int]) -> int:
"""常规做法：二进制枚举（超时） 1. 本代码可帮助理解题目意思 @param b: @param g: @return:"""
<|body_0|>
def maxHappyGroups(self, b: int, g: List[int]) -> int:
"""如果用2进制枚举会超时，由于客户数量最多30组，采用31进制 @param b: @param g: @return:"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxHappyGroups(self, b: int, g: List[int]) -> int:
"""常规做法：二进制枚举（超时） 1. 本代码可帮助理解题目意思 @param b: @param g: @return:"""
n = len(g)
dp = [0] * (1 << n)
for i in range(1 << n):
s = 0
for j in range(n):
if i >> j & 1:
... | the_stack_v2_python_sparse | LeetCode/动态规划法(dp)/状态压缩DP/1815. 得到新鲜甜甜圈的最多组数.py | yiming1012/MyLeetCode | train | 2 | |
c1a88f411645e2bf0ff79f37e8a793e670cd24df | [
"if grid[0][0] == 1 or grid[-1][-1] == 1 or (not grid):\n return -1\nqueue = [(0, 0, 1)]\ngrid[0][0] = 1\nn = len(grid)\nif n == 1:\n return 1\ndirections = [(-1, 0), (1, 0), (0, -1), (0, 1), (1, 1), (1, -1), (-1, 1), (-1, -1)]\nwhile len(queue) > 0:\n size = len(queue)\n for k in range(size):\n ... | <|body_start_0|>
if grid[0][0] == 1 or grid[-1][-1] == 1 or (not grid):
return -1
queue = [(0, 0, 1)]
grid[0][0] = 1
n = len(grid)
if n == 1:
return 1
directions = [(-1, 0), (1, 0), (0, -1), (0, 1), (1, 1), (1, -1), (-1, 1), (-1, -1)]
while... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shortestPathBinaryMatrix_standard(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def shortestPathBinaryMatrix(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_007723 | 4,024 | no_license | [
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "shortestPathBinaryMatrix_standard",
"signature": "def shortestPathBinaryMatrix_standard(self, grid)"
},
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "shortestPathBinaryMatrix",
"signature": "def short... | 2 | stack_v2_sparse_classes_30k_train_003901 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestPathBinaryMatrix_standard(self, grid): :type grid: List[List[int]] :rtype: int
- def shortestPathBinaryMatrix(self, grid): :type grid: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestPathBinaryMatrix_standard(self, grid): :type grid: List[List[int]] :rtype: int
- def shortestPathBinaryMatrix(self, grid): :type grid: List[List[int]] :rtype: int
<|... | d36655924edb9e364c956f912ba4797fb962be7e | <|skeleton|>
class Solution:
def shortestPathBinaryMatrix_standard(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def shortestPathBinaryMatrix(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def shortestPathBinaryMatrix_standard(self, grid):
""":type grid: List[List[int]] :rtype: int"""
if grid[0][0] == 1 or grid[-1][-1] == 1 or (not grid):
return -1
queue = [(0, 0, 1)]
grid[0][0] = 1
n = len(grid)
if n == 1:
return... | the_stack_v2_python_sparse | 1091.BfsShortestPath.py | casssie-zhang/LeetcodeNotes | train | 2 | |
7f92d059921dbd85a167d832d012e59feff551e9 | [
"if not email:\n raise ValueError('Users must have an email address')\nif not username:\n raise ValueError('Users must have an username')\nuser = self.model(username=username, email=self.normalize_email(email))\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(u... | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
if not username:
raise ValueError('Users must have an username')
user = self.model(username=username, email=self.normalize_email(email))
user.set_password(password)
user.sa... | CustomUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, username, email, password):
"""Creates and saves a superuser with the give... | stack_v2_sparse_classes_10k_train_007724 | 4,781 | no_license | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, username, email, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
"name"... | 2 | stack_v2_sparse_classes_30k_train_001930 | Implement the Python class `CustomUserManager` described below.
Class description:
Implement the CustomUserManager class.
Method signatures and docstrings:
- def create_user(self, username, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, u... | Implement the Python class `CustomUserManager` described below.
Class description:
Implement the CustomUserManager class.
Method signatures and docstrings:
- def create_user(self, username, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, u... | 95c22374f42e8156e43e31de3b6062f41258824b | <|skeleton|>
class CustomUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, username, email, password):
"""Creates and saves a superuser with the give... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CustomUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
if not email:
raise ValueError('Users must have an email address')
if not username:
raise ValueError('Users... | the_stack_v2_python_sparse | core/models.py | josben/flo | train | 0 | |
7d7949773446700a155e07f6aa166ae5d99027da | [
"n = len(A)\ncmp = [0] * n\nm = 10 ** 6 + 1\nfor i in range(n - 1, -1, -1):\n cmp[i] = m = min(m, A[i])\nm = -1\nfor i, x in enumerate(A):\n m = max(m, x)\n if m <= cmp[i + 1]:\n return i + 1",
"lm = m = A[0]\nres = 0\nfor i in range(1, len(A)):\n m = max(m, A[i])\n if A[i] < lm:\n lm... | <|body_start_0|>
n = len(A)
cmp = [0] * n
m = 10 ** 6 + 1
for i in range(n - 1, -1, -1):
cmp[i] = m = min(m, A[i])
m = -1
for i, x in enumerate(A):
m = max(m, x)
if m <= cmp[i + 1]:
return i + 1
<|end_body_0|>
<|body_st... | [915. 分割数组](https://leetcode-cn.com/problems/partition-array-into-disjoint-intervals/) | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""[915. 分割数组](https://leetcode-cn.com/problems/partition-array-into-disjoint-intervals/)"""
def partitionDisjoint(self, A: List[int]) -> int:
"""思路：找到第一个max(left)<=min(right)位置"""
<|body_0|>
def partitionDisjoint2(self, A: List[int]) -> int:
"""思路：优化，保... | stack_v2_sparse_classes_10k_train_007725 | 1,343 | no_license | [
{
"docstring": "思路：找到第一个max(left)<=min(right)位置",
"name": "partitionDisjoint",
"signature": "def partitionDisjoint(self, A: List[int]) -> int"
},
{
"docstring": "思路：优化，保存一个左边最大值，后面的遍历过程中比这个值还小的，一定要被划分到left中，相等不用。",
"name": "partitionDisjoint2",
"signature": "def partitionDisjoint2(self, ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
[915. 分割数组](https://leetcode-cn.com/problems/partition-array-into-disjoint-intervals/)
Method signatures and docstrings:
- def partitionDisjoint(self, A: List[int]) -> int: 思路：找到第一个max(left)<=min(right)位置
- def partitionDisjoint2(self, A: List[... | Implement the Python class `Solution` described below.
Class description:
[915. 分割数组](https://leetcode-cn.com/problems/partition-array-into-disjoint-intervals/)
Method signatures and docstrings:
- def partitionDisjoint(self, A: List[int]) -> int: 思路：找到第一个max(left)<=min(right)位置
- def partitionDisjoint2(self, A: List[... | dbe8eb449e5b112a71bc1cd4eabfd138304de4a3 | <|skeleton|>
class Solution:
"""[915. 分割数组](https://leetcode-cn.com/problems/partition-array-into-disjoint-intervals/)"""
def partitionDisjoint(self, A: List[int]) -> int:
"""思路：找到第一个max(left)<=min(right)位置"""
<|body_0|>
def partitionDisjoint2(self, A: List[int]) -> int:
"""思路：优化，保... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
"""[915. 分割数组](https://leetcode-cn.com/problems/partition-array-into-disjoint-intervals/)"""
def partitionDisjoint(self, A: List[int]) -> int:
"""思路：找到第一个max(left)<=min(right)位置"""
n = len(A)
cmp = [0] * n
m = 10 ** 6 + 1
for i in range(n - 1, -1, -1):
... | the_stack_v2_python_sparse | leetcode/901-1200/915.py | Rivarrl/leetcode_python | train | 3 |
493dec1c31ec298c00c77ebc95713a1444c2314f | [
"if request.COOKIES.get('site_language'):\n if request.COOKIES['site_language'] == '':\n language = 'fr'\n else:\n language = request.COOKIES['site_language']\n translation.activate(language)\n request.LANGUAGE_CODE = translation.get_language()",
"if not request.COOKIES.get('site_languag... | <|body_start_0|>
if request.COOKIES.get('site_language'):
if request.COOKIES['site_language'] == '':
language = 'fr'
else:
language = request.COOKIES['site_language']
translation.activate(language)
request.LANGUAGE_CODE = translatio... | LanguageCookieMiddleware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LanguageCookieMiddleware:
def process_request(self, request):
"""Sets language from the cookie value."""
<|body_0|>
def process_response(self, request, response):
"""Create cookie if not there already. Also deactivates language. (See http://stackoverflow.com/a/130312... | stack_v2_sparse_classes_10k_train_007726 | 1,353 | no_license | [
{
"docstring": "Sets language from the cookie value.",
"name": "process_request",
"signature": "def process_request(self, request)"
},
{
"docstring": "Create cookie if not there already. Also deactivates language. (See http://stackoverflow.com/a/13031239/388835 )",
"name": "process_response"... | 2 | stack_v2_sparse_classes_30k_train_004691 | Implement the Python class `LanguageCookieMiddleware` described below.
Class description:
Implement the LanguageCookieMiddleware class.
Method signatures and docstrings:
- def process_request(self, request): Sets language from the cookie value.
- def process_response(self, request, response): Create cookie if not the... | Implement the Python class `LanguageCookieMiddleware` described below.
Class description:
Implement the LanguageCookieMiddleware class.
Method signatures and docstrings:
- def process_request(self, request): Sets language from the cookie value.
- def process_response(self, request, response): Create cookie if not the... | d5aff19e4557fe1eb9e0765e40337df99d5e1935 | <|skeleton|>
class LanguageCookieMiddleware:
def process_request(self, request):
"""Sets language from the cookie value."""
<|body_0|>
def process_response(self, request, response):
"""Create cookie if not there already. Also deactivates language. (See http://stackoverflow.com/a/130312... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LanguageCookieMiddleware:
def process_request(self, request):
"""Sets language from the cookie value."""
if request.COOKIES.get('site_language'):
if request.COOKIES['site_language'] == '':
language = 'fr'
else:
language = request.COOKIES[... | the_stack_v2_python_sparse | visualexpcode/visualexpcode/middleware/languages/language_cookie.py | mlemaire79/visualexp | train | 0 | |
41cf2a8a364fe9efc69f720ea53eee1bcea41def | [
"entries = self.model_cls.published.none()\nif self.request.GET:\n self.pattern = self.request.GET.get('q', '')\n if len(self.pattern) < 3:\n self.error = _('The pattern is too short')\n else:\n query_parsed = QUERY.parseString(self.pattern)\n entries = self.model_cls.published.filter(... | <|body_start_0|>
entries = self.model_cls.published.none()
if self.request.GET:
self.pattern = self.request.GET.get('q', '')
if len(self.pattern) < 3:
self.error = _('The pattern is too short')
else:
query_parsed = QUERY.parseString(sel... | Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern. | EntrySearchMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntrySearchMixin:
"""Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern."""
def get_queryset(self):
"""Overridde the ... | stack_v2_sparse_classes_10k_train_007727 | 3,025 | no_license | [
{
"docstring": "Overridde the get_queryset method to do some validations and build the search queryset.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Add error and pattern in context.",
"name": "get_context_data",
"signature": "def get_context_data(se... | 2 | stack_v2_sparse_classes_30k_train_003889 | Implement the Python class `EntrySearchMixin` described below.
Class description:
Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern.
Method signatures... | Implement the Python class `EntrySearchMixin` described below.
Class description:
Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern.
Method signatures... | 80e5a36154d1e2ffdc08c7f0563e8e887efb017d | <|skeleton|>
class EntrySearchMixin:
"""Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern."""
def get_queryset(self):
"""Overridde the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EntrySearchMixin:
"""Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern."""
def get_queryset(self):
"""Overridde the get_queryset ... | the_stack_v2_python_sparse | apps/mp_blog/views/mixins.py | ivansons/mp_cms | train | 0 |
7821c114132cad6bbbae204cb605867db2f677af | [
"PlotCanvas1D.__init__(self, parent, id, xlabel, ylabel, xscale, yscale)\nself.bank = FilterBank()\npub.subscribe(self.PostProcess, 'filter.change')\nself.Bind(wx.EVT_WINDOW_DESTROY, self.OnDelete)",
"PlotCanvas1D.OnDelete(self, event)\npub.unsubscribe(self.PostProcess, 'filter.change')\nevent.Skip()",
"event.S... | <|body_start_0|>
PlotCanvas1D.__init__(self, parent, id, xlabel, ylabel, xscale, yscale)
self.bank = FilterBank()
pub.subscribe(self.PostProcess, 'filter.change')
self.Bind(wx.EVT_WINDOW_DESTROY, self.OnDelete)
<|end_body_0|>
<|body_start_1|>
PlotCanvas1D.OnDelete(self, event)
... | Canvas class for 1D post-processed data plots Properties: is_data - False, canvas is not meant to display raw measurement data is_filter - True, canvas is meant to display post-processed data dim=1 - dimension of plots displayed on this canvas (int) name - name of canvas type (str) | PlotCanvasF | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlotCanvasF:
"""Canvas class for 1D post-processed data plots Properties: is_data - False, canvas is not meant to display raw measurement data is_filter - True, canvas is meant to display post-processed data dim=1 - dimension of plots displayed on this canvas (int) name - name of canvas type (str... | stack_v2_sparse_classes_10k_train_007728 | 5,257 | no_license | [
{
"docstring": "Initialization. Parameters: parent - parent window (wx.Window) id - id (int) xlabel - label and units of abscissa axis ([str,quantities]) ylabel - label and units of ordinate axis ([str,quantities]) xscale - abscissa scale type (linear or log) yscale - ordinate scale type (linear or log)",
"... | 6 | stack_v2_sparse_classes_30k_val_000296 | Implement the Python class `PlotCanvasF` described below.
Class description:
Canvas class for 1D post-processed data plots Properties: is_data - False, canvas is not meant to display raw measurement data is_filter - True, canvas is meant to display post-processed data dim=1 - dimension of plots displayed on this canva... | Implement the Python class `PlotCanvasF` described below.
Class description:
Canvas class for 1D post-processed data plots Properties: is_data - False, canvas is not meant to display raw measurement data is_filter - True, canvas is meant to display post-processed data dim=1 - dimension of plots displayed on this canva... | 712accd3534ca35ae4c5c7f1c9c33fc935552ca6 | <|skeleton|>
class PlotCanvasF:
"""Canvas class for 1D post-processed data plots Properties: is_data - False, canvas is not meant to display raw measurement data is_filter - True, canvas is meant to display post-processed data dim=1 - dimension of plots displayed on this canvas (int) name - name of canvas type (str... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PlotCanvasF:
"""Canvas class for 1D post-processed data plots Properties: is_data - False, canvas is not meant to display raw measurement data is_filter - True, canvas is meant to display post-processed data dim=1 - dimension of plots displayed on this canvas (int) name - name of canvas type (str)"""
def... | the_stack_v2_python_sparse | terapy_2/plot/canvasF.py | dawidgadziala/terapy | train | 0 |
24d5ddfd705fde1f8a464200e71837453262d8dd | [
"neuron.Neuron.__init__(self, size)\nself.tau_rc = tau_rc\nself.tau_ref = tau_ref",
"x = 1.0 / (1 - TT.exp((self.tau_ref - 1.0 / max_rates) / self.tau_rc))\nalpha = (1 - z2) / (intercepts - 1.0)\nj_bias = 1 - alpha * intercepts\nreturn (alpha, j_bias)",
"rate = self.tau_ref - self.tau_rc * TT.log(1 - 1.0 / TT.m... | <|body_start_0|>
neuron.Neuron.__init__(self, size)
self.tau_rc = tau_rc
self.tau_ref = tau_ref
<|end_body_0|>
<|body_start_1|>
x = 1.0 / (1 - TT.exp((self.tau_ref - 1.0 / max_rates) / self.tau_rc))
alpha = (1 - z2) / (intercepts - 1.0)
j_bias = 1 - alpha * intercepts
... | LIFRateNeuron | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LIFRateNeuron:
def __init__(self, size, tau_rc=0.02, tau_ref=0.002):
"""Constructor for a set of LIF rate neuron :param int size: number of neurons in set :param float t_rc: the RC time constant :param float tau_ref: refractory period length (s)"""
<|body_0|>
def make_alpha_... | stack_v2_sparse_classes_10k_train_007729 | 1,938 | permissive | [
{
"docstring": "Constructor for a set of LIF rate neuron :param int size: number of neurons in set :param float t_rc: the RC time constant :param float tau_ref: refractory period length (s)",
"name": "__init__",
"signature": "def __init__(self, size, tau_rc=0.02, tau_ref=0.002)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_train_007101 | Implement the Python class `LIFRateNeuron` described below.
Class description:
Implement the LIFRateNeuron class.
Method signatures and docstrings:
- def __init__(self, size, tau_rc=0.02, tau_ref=0.002): Constructor for a set of LIF rate neuron :param int size: number of neurons in set :param float t_rc: the RC time ... | Implement the Python class `LIFRateNeuron` described below.
Class description:
Implement the LIFRateNeuron class.
Method signatures and docstrings:
- def __init__(self, size, tau_rc=0.02, tau_ref=0.002): Constructor for a set of LIF rate neuron :param int size: number of neurons in set :param float t_rc: the RC time ... | 9067f897d4bf3d1a01ceb03e1b1f044cde580a19 | <|skeleton|>
class LIFRateNeuron:
def __init__(self, size, tau_rc=0.02, tau_ref=0.002):
"""Constructor for a set of LIF rate neuron :param int size: number of neurons in set :param float t_rc: the RC time constant :param float tau_ref: refractory period length (s)"""
<|body_0|>
def make_alpha_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LIFRateNeuron:
def __init__(self, size, tau_rc=0.02, tau_ref=0.002):
"""Constructor for a set of LIF rate neuron :param int size: number of neurons in set :param float t_rc: the RC time constant :param float tau_ref: refractory period length (s)"""
neuron.Neuron.__init__(self, size)
se... | the_stack_v2_python_sparse | nengo_theano/lif_rate.py | ctn-archive/nengo_theano | train | 0 | |
5dea14c4eaad8b138fdd760667df9439dee73689 | [
"super(ListWebhooks, cls).setUpClass()\nwebhook1_response = cls.autoscale_client.create_webhook(cls.group.id, cls.policy['id'], 'webhook1').entity\ncls.webhook1 = cls.autoscale_behaviors.get_webhooks_properties(webhook1_response)\nwebhook2_response = cls.autoscale_client.create_webhook(cls.group.id, cls.policy['id'... | <|body_start_0|>
super(ListWebhooks, cls).setUpClass()
webhook1_response = cls.autoscale_client.create_webhook(cls.group.id, cls.policy['id'], 'webhook1').entity
cls.webhook1 = cls.autoscale_behaviors.get_webhooks_properties(webhook1_response)
webhook2_response = cls.autoscale_client.cre... | Verify list webhooks | ListWebhooks | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListWebhooks:
"""Verify list webhooks"""
def setUpClass(cls):
"""Creates a scaling group with a policy and 3 webhooks on the policy"""
<|body_0|>
def test_list_webhooks(self):
"""Verify the list webhooks call for response code 201, headers and data"""
<|b... | stack_v2_sparse_classes_10k_train_007730 | 1,861 | permissive | [
{
"docstring": "Creates a scaling group with a policy and 3 webhooks on the policy",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Verify the list webhooks call for response code 201, headers and data",
"name": "test_list_webhooks",
"signature": "def test_li... | 2 | stack_v2_sparse_classes_30k_train_005628 | Implement the Python class `ListWebhooks` described below.
Class description:
Verify list webhooks
Method signatures and docstrings:
- def setUpClass(cls): Creates a scaling group with a policy and 3 webhooks on the policy
- def test_list_webhooks(self): Verify the list webhooks call for response code 201, headers an... | Implement the Python class `ListWebhooks` described below.
Class description:
Verify list webhooks
Method signatures and docstrings:
- def setUpClass(cls): Creates a scaling group with a policy and 3 webhooks on the policy
- def test_list_webhooks(self): Verify the list webhooks call for response code 201, headers an... | 7199cdd67255fe116dbcbedea660c13453671134 | <|skeleton|>
class ListWebhooks:
"""Verify list webhooks"""
def setUpClass(cls):
"""Creates a scaling group with a policy and 3 webhooks on the policy"""
<|body_0|>
def test_list_webhooks(self):
"""Verify the list webhooks call for response code 201, headers and data"""
<|b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ListWebhooks:
"""Verify list webhooks"""
def setUpClass(cls):
"""Creates a scaling group with a policy and 3 webhooks on the policy"""
super(ListWebhooks, cls).setUpClass()
webhook1_response = cls.autoscale_client.create_webhook(cls.group.id, cls.policy['id'], 'webhook1').entity
... | the_stack_v2_python_sparse | autoscale_cloudroast/test_repo/autoscale/functional/webhooks/test_list_webhooks.py | rackerlabs/otter | train | 20 |
a3d1f411e1f95b350666d1f935f0106b81a2ddf9 | [
"self.temp = arr[0]\nfor values in range(len(arr) - 1):\n arr[values] = arr[values + 1]\narr[-1] = self.temp",
"self.temp = arr[-1]\nfor values in range(len(arr) - 1, -1, -1):\n arr[values] = arr[values - 1]\narr[0] = self.temp",
"self.aux = len(arr) * [0]\nfor i in range(len(arr)):\n self.aux[(i + k) ... | <|body_start_0|>
self.temp = arr[0]
for values in range(len(arr) - 1):
arr[values] = arr[values + 1]
arr[-1] = self.temp
<|end_body_0|>
<|body_start_1|>
self.temp = arr[-1]
for values in range(len(arr) - 1, -1, -1):
arr[values] = arr[values - 1]
a... | Rotation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rotation:
def rotate_left_by_One(self, arr):
"""Rotate the array left by one"""
<|body_0|>
def rotate_right_by_One(self, arr):
"""Rotate the array right by one"""
<|body_1|>
def rotate_right(self, arr, k):
"""We use an extra array in which we pla... | stack_v2_sparse_classes_10k_train_007731 | 3,090 | no_license | [
{
"docstring": "Rotate the array left by one",
"name": "rotate_left_by_One",
"signature": "def rotate_left_by_One(self, arr)"
},
{
"docstring": "Rotate the array right by one",
"name": "rotate_right_by_One",
"signature": "def rotate_right_by_One(self, arr)"
},
{
"docstring": "We ... | 5 | null | Implement the Python class `Rotation` described below.
Class description:
Implement the Rotation class.
Method signatures and docstrings:
- def rotate_left_by_One(self, arr): Rotate the array left by one
- def rotate_right_by_One(self, arr): Rotate the array right by one
- def rotate_right(self, arr, k): We use an ex... | Implement the Python class `Rotation` described below.
Class description:
Implement the Rotation class.
Method signatures and docstrings:
- def rotate_left_by_One(self, arr): Rotate the array left by one
- def rotate_right_by_One(self, arr): Rotate the array right by one
- def rotate_right(self, arr, k): We use an ex... | 0892f41fe055de4361aae950fb60b0e3c2f96505 | <|skeleton|>
class Rotation:
def rotate_left_by_One(self, arr):
"""Rotate the array left by one"""
<|body_0|>
def rotate_right_by_One(self, arr):
"""Rotate the array right by one"""
<|body_1|>
def rotate_right(self, arr, k):
"""We use an extra array in which we pla... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Rotation:
def rotate_left_by_One(self, arr):
"""Rotate the array left by one"""
self.temp = arr[0]
for values in range(len(arr) - 1):
arr[values] = arr[values + 1]
arr[-1] = self.temp
def rotate_right_by_One(self, arr):
"""Rotate the array right by one"... | the_stack_v2_python_sparse | DataStructures/v1/code/Geeks/arrayRotation.py | acemodou/Working-Copy | train | 0 | |
2e75f3f70ab13799d3b163d4f2873035a0de5839 | [
"name = ''.join(filter(str.isalnum, label)).lower()\nif background_color is None:\n background_color = BACKGROUND_COLOR\nLabel.__init__(self, name, label, rect, background_color)\nself.left_click_callback = callback\nself.clicked_counter = 0\nself.redraw()\nreturn",
"Label.redraw(self)\nself.image.lock()\npyga... | <|body_start_0|>
name = ''.join(filter(str.isalnum, label)).lower()
if background_color is None:
background_color = BACKGROUND_COLOR
Label.__init__(self, name, label, rect, background_color)
self.left_click_callback = callback
self.clicked_counter = 0
self.red... | A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different color | Button | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Button:
"""A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different color"""
def __init__(self, label, ... | stack_v2_sparse_classes_10k_train_007732 | 27,668 | permissive | [
{
"docstring": "Initialise the Button. label is the Text to be written on the button. rect is an instance of pygame.Rect giving the dimensions. callback is the function to be called when the Button is clicked with the left mouse button.",
"name": "__init__",
"signature": "def __init__(self, label, rect,... | 4 | stack_v2_sparse_classes_30k_train_003429 | Implement the Python class `Button` described below.
Class description:
A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different c... | Implement the Python class `Button` described below.
Class description:
A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different c... | c2fc3d4e9beedb8487cfa4bfa13bdf55ec36af97 | <|skeleton|>
class Button:
"""A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different color"""
def __init__(self, label, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Button:
"""A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different color"""
def __init__(self, label, rect, callbac... | the_stack_v2_python_sparse | reference_scripts/clickndrag-0.4.1/clickndrag/gui.py | stivosaurus/rpi-snippets | train | 1 |
9361a03824c0138cb41ec7f82cabc2fc4137cdd2 | [
"dummy_head = ListNode(0)\ncurrent_node = dummy_head\nfor i in list:\n current_node.next = ListNode(i)\n current_node = current_node.next\nreturn dummy_head.next",
"curr = list\nans = []\nwhile curr:\n ans.append(curr.val)\n curr = curr.next\nreturn ans"
] | <|body_start_0|>
dummy_head = ListNode(0)
current_node = dummy_head
for i in list:
current_node.next = ListNode(i)
current_node = current_node.next
return dummy_head.next
<|end_body_0|>
<|body_start_1|>
curr = list
ans = []
while curr:
... | LinkListHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkListHelper:
def listToLinkList(self, list):
""":type list: List[int] :rtype: ListNode"""
<|body_0|>
def linkListToList(self, list):
""":type list: ListNode :rtype: List"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dummy_head = ListNode(0)
... | stack_v2_sparse_classes_10k_train_007733 | 3,744 | no_license | [
{
"docstring": ":type list: List[int] :rtype: ListNode",
"name": "listToLinkList",
"signature": "def listToLinkList(self, list)"
},
{
"docstring": ":type list: ListNode :rtype: List",
"name": "linkListToList",
"signature": "def linkListToList(self, list)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004280 | Implement the Python class `LinkListHelper` described below.
Class description:
Implement the LinkListHelper class.
Method signatures and docstrings:
- def listToLinkList(self, list): :type list: List[int] :rtype: ListNode
- def linkListToList(self, list): :type list: ListNode :rtype: List | Implement the Python class `LinkListHelper` described below.
Class description:
Implement the LinkListHelper class.
Method signatures and docstrings:
- def listToLinkList(self, list): :type list: List[int] :rtype: ListNode
- def linkListToList(self, list): :type list: ListNode :rtype: List
<|skeleton|>
class LinkLis... | a57282895fb213b68e5d81db301903721a92d80f | <|skeleton|>
class LinkListHelper:
def listToLinkList(self, list):
""":type list: List[int] :rtype: ListNode"""
<|body_0|>
def linkListToList(self, list):
""":type list: ListNode :rtype: List"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LinkListHelper:
def listToLinkList(self, list):
""":type list: List[int] :rtype: ListNode"""
dummy_head = ListNode(0)
current_node = dummy_head
for i in list:
current_node.next = ListNode(i)
current_node = current_node.next
return dummy_head.next... | the_stack_v2_python_sparse | Python/helper.py | antonylu/leetcode2 | train | 0 | |
dcad37a8101e1054ceb0404e5dcec42041a1f2a3 | [
"BaseController.__init__(self, veh_id, car_following_params, delay=delay, fail_safe=fail_safe, noise=noise)\nself.v_desired = v0\nself.acc = acc\nself.b = b\nself.b_l = b_l\nself.s0 = s0\nself.tau = tau",
"v = env.k.vehicle.get_speed(self.veh_id)\nh = env.k.vehicle.get_headway(self.veh_id)\nv_l = env.k.vehicle.ge... | <|body_start_0|>
BaseController.__init__(self, veh_id, car_following_params, delay=delay, fail_safe=fail_safe, noise=noise)
self.v_desired = v0
self.acc = acc
self.b = b
self.b_l = b_l
self.s0 = s0
self.tau = tau
<|end_body_0|>
<|body_start_1|>
v = env.k.... | Gipps' Model controller. For more information on this controller, see: Traffic Flow Dynamics written by M.Treiber and A.Kesting By courtesy of Springer publisher, http://www.springer.com http://www.traffic-flow-dynamics.org/res/SampleChapter11.pdf Usage ----- See BaseController for usage example. Attributes ---------- ... | GippsController | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GippsController:
"""Gipps' Model controller. For more information on this controller, see: Traffic Flow Dynamics written by M.Treiber and A.Kesting By courtesy of Springer publisher, http://www.springer.com http://www.traffic-flow-dynamics.org/res/SampleChapter11.pdf Usage ----- See BaseControlle... | stack_v2_sparse_classes_10k_train_007734 | 17,548 | permissive | [
{
"docstring": "Instantiate a Gipps' controller.",
"name": "__init__",
"signature": "def __init__(self, veh_id, car_following_params=None, v0=30, acc=1.5, b=-1, b_l=-1, s0=2, tau=1, delay=0, noise=0, fail_safe=None)"
},
{
"docstring": "See parent class.",
"name": "get_accel",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_006704 | Implement the Python class `GippsController` described below.
Class description:
Gipps' Model controller. For more information on this controller, see: Traffic Flow Dynamics written by M.Treiber and A.Kesting By courtesy of Springer publisher, http://www.springer.com http://www.traffic-flow-dynamics.org/res/SampleChap... | Implement the Python class `GippsController` described below.
Class description:
Gipps' Model controller. For more information on this controller, see: Traffic Flow Dynamics written by M.Treiber and A.Kesting By courtesy of Springer publisher, http://www.springer.com http://www.traffic-flow-dynamics.org/res/SampleChap... | badac3da17f04d8d8ae5691ee8ba2af9d56fac35 | <|skeleton|>
class GippsController:
"""Gipps' Model controller. For more information on this controller, see: Traffic Flow Dynamics written by M.Treiber and A.Kesting By courtesy of Springer publisher, http://www.springer.com http://www.traffic-flow-dynamics.org/res/SampleChapter11.pdf Usage ----- See BaseControlle... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GippsController:
"""Gipps' Model controller. For more information on this controller, see: Traffic Flow Dynamics written by M.Treiber and A.Kesting By courtesy of Springer publisher, http://www.springer.com http://www.traffic-flow-dynamics.org/res/SampleChapter11.pdf Usage ----- See BaseController for usage e... | the_stack_v2_python_sparse | flow/controllers/car_following_models.py | parthjaggi/flow | train | 6 |
91397f7ddc1e148835a57ddbc130e7cb8464f66f | [
"self.instance = instance\nself.schema = None\nif self.instance:\n self.schema = SurveySchema(self.instance.survey)",
"for name, field in self.fields.items():\n yield (field.verbose_name, getattr(self.instance, name))\nif self.schema:\n for field in self.schema:\n field_id = field.getFieldName()\n... | <|body_start_0|>
self.instance = instance
self.schema = None
if self.instance:
self.schema = SurveySchema(self.instance.survey)
<|end_body_0|>
<|body_start_1|>
for name, field in self.fields.items():
yield (field.verbose_name, getattr(self.instance, name))
... | A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model. | SurveyRecordReadOnlyTemplate | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SurveyRecordReadOnlyTemplate:
"""A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model."""
def __init__(self, instance=Non... | stack_v2_sparse_classes_10k_train_007735 | 6,916 | permissive | [
{
"docstring": "Constructor to initialize the model instance. The readonly template will be rendered for the data in this model instance.",
"name": "__init__",
"signature": "def __init__(self, instance=None)"
},
{
"docstring": "Iterator yielding groups of record instance's properties to be rende... | 3 | stack_v2_sparse_classes_30k_train_003171 | Implement the Python class `SurveyRecordReadOnlyTemplate` described below.
Class description:
A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model.
... | Implement the Python class `SurveyRecordReadOnlyTemplate` described below.
Class description:
A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model.
... | 6bbd1674c99fe285596e46e738856a82afe036af | <|skeleton|>
class SurveyRecordReadOnlyTemplate:
"""A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model."""
def __init__(self, instance=Non... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SurveyRecordReadOnlyTemplate:
"""A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model."""
def __init__(self, instance=None):
"... | the_stack_v2_python_sparse | app/soc/views/readonly_template.py | adviti/melange | train | 0 |
dc3a85c1ac874b68486994abf0ab05a85bfb7b50 | [
"memo = {coins: 0}\nfor cost in costs:\n _memo = {}\n for coin, n in memo.items():\n _memo.setdefault(coin, 0)\n _memo[coin] = max(_memo[coin], n)\n if coin >= cost:\n _memo.setdefault(coin - cost, 0)\n _memo[coin - cost] = max(_memo[coin - cost], n + 1)\n memo = ... | <|body_start_0|>
memo = {coins: 0}
for cost in costs:
_memo = {}
for coin, n in memo.items():
_memo.setdefault(coin, 0)
_memo[coin] = max(_memo[coin], n)
if coin >= cost:
_memo.setdefault(coin - cost, 0)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxIceCream(self, costs: List[int], coins: int) -> int:
"""Mar 04, 2023 21:28 TLE"""
<|body_0|>
def maxIceCream(self, costs: List[int], coins: int) -> int:
"""Mar 04, 2023 21:31"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
memo = {c... | stack_v2_sparse_classes_10k_train_007736 | 6,815 | no_license | [
{
"docstring": "Mar 04, 2023 21:28 TLE",
"name": "maxIceCream",
"signature": "def maxIceCream(self, costs: List[int], coins: int) -> int"
},
{
"docstring": "Mar 04, 2023 21:31",
"name": "maxIceCream",
"signature": "def maxIceCream(self, costs: List[int], coins: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxIceCream(self, costs: List[int], coins: int) -> int: Mar 04, 2023 21:28 TLE
- def maxIceCream(self, costs: List[int], coins: int) -> int: Mar 04, 2023 21:31 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxIceCream(self, costs: List[int], coins: int) -> int: Mar 04, 2023 21:28 TLE
- def maxIceCream(self, costs: List[int], coins: int) -> int: Mar 04, 2023 21:31
<|skeleton|>
... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def maxIceCream(self, costs: List[int], coins: int) -> int:
"""Mar 04, 2023 21:28 TLE"""
<|body_0|>
def maxIceCream(self, costs: List[int], coins: int) -> int:
"""Mar 04, 2023 21:31"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxIceCream(self, costs: List[int], coins: int) -> int:
"""Mar 04, 2023 21:28 TLE"""
memo = {coins: 0}
for cost in costs:
_memo = {}
for coin, n in memo.items():
_memo.setdefault(coin, 0)
_memo[coin] = max(_memo[coin... | the_stack_v2_python_sparse | leetcode/solved/1961_Maximum_Ice_Cream_Bars/solution.py | sungminoh/algorithms | train | 0 | |
5176b32a3cd5a6a151c5f0076d5d9e4e5946c101 | [
"if not isinstance(data, np.ndarray) or len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nif data.shape[1] < 2:\n raise ValueError('data must contain multiple data points')\nself.mean = np.mean(data, axis=1).reshape((data.shape[0], 1))\ndata_t = data.T\nmean = np.mean(data_t, axis=0)... | <|body_start_0|>
if not isinstance(data, np.ndarray) or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
if data.shape[1] < 2:
raise ValueError('data must contain multiple data points')
self.mean = np.mean(data, axis=1).reshape((data.shape[0], 1))
... | class | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""class"""
def __init__(self, data):
"""initializer"""
<|body_0|>
def pdf(self, x):
"""method"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not isinstance(data, np.ndarray) or len(data.shape) != 2:
raise TypeError(... | stack_v2_sparse_classes_10k_train_007737 | 1,296 | no_license | [
{
"docstring": "initializer",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "method",
"name": "pdf",
"signature": "def pdf(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000353 | Implement the Python class `MultiNormal` described below.
Class description:
class
Method signatures and docstrings:
- def __init__(self, data): initializer
- def pdf(self, x): method | Implement the Python class `MultiNormal` described below.
Class description:
class
Method signatures and docstrings:
- def __init__(self, data): initializer
- def pdf(self, x): method
<|skeleton|>
class MultiNormal:
"""class"""
def __init__(self, data):
"""initializer"""
<|body_0|>
def ... | b5e8f1253309567ca7be71b9575a150de1be3820 | <|skeleton|>
class MultiNormal:
"""class"""
def __init__(self, data):
"""initializer"""
<|body_0|>
def pdf(self, x):
"""method"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""class"""
def __init__(self, data):
"""initializer"""
if not isinstance(data, np.ndarray) or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
if data.shape[1] < 2:
raise ValueError('data must contain multiple data poin... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | jadsm98/holbertonschool-machine_learning | train | 0 |
2d71d5032e29b772e4a23624cd052d97ef8f7248 | [
"super(Application, self).__init__(master)\nself.grid()\nself.create_widgets()",
"self.inst_lbl = Label(self, text='Input password to longevity secret.')\nself.inst_lbl.grid(row=0, column=0, columnspan=2, sticky=W)\nself.pw_lbl = Label(self, text='Password: ')\nself.pw_lbl.grid(row=1, column=0, sticky=W)\nself.pw... | <|body_start_0|>
super(Application, self).__init__(master)
self.grid()
self.create_widgets()
<|end_body_0|>
<|body_start_1|>
self.inst_lbl = Label(self, text='Input password to longevity secret.')
self.inst_lbl.grid(row=0, column=0, columnspan=2, sticky=W)
self.pw_lbl = ... | Application with GUI, which can revealed secret of longevity. | Application | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Application:
"""Application with GUI, which can revealed secret of longevity."""
def __init__(self, master):
"""Initialize frame."""
<|body_0|>
def create_widgets(self):
"""Create widgets Button, Text and Entry."""
<|body_1|>
def reveal(self):
... | stack_v2_sparse_classes_10k_train_007738 | 2,625 | no_license | [
{
"docstring": "Initialize frame.",
"name": "__init__",
"signature": "def __init__(self, master)"
},
{
"docstring": "Create widgets Button, Text and Entry.",
"name": "create_widgets",
"signature": "def create_widgets(self)"
},
{
"docstring": "Print message depends of password val... | 3 | stack_v2_sparse_classes_30k_train_004535 | Implement the Python class `Application` described below.
Class description:
Application with GUI, which can revealed secret of longevity.
Method signatures and docstrings:
- def __init__(self, master): Initialize frame.
- def create_widgets(self): Create widgets Button, Text and Entry.
- def reveal(self): Print mess... | Implement the Python class `Application` described below.
Class description:
Application with GUI, which can revealed secret of longevity.
Method signatures and docstrings:
- def __init__(self, master): Initialize frame.
- def create_widgets(self): Create widgets Button, Text and Entry.
- def reveal(self): Print mess... | 120e2d62468a085424ec71a22effe27d6b38b548 | <|skeleton|>
class Application:
"""Application with GUI, which can revealed secret of longevity."""
def __init__(self, master):
"""Initialize frame."""
<|body_0|>
def create_widgets(self):
"""Create widgets Button, Text and Entry."""
<|body_1|>
def reveal(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Application:
"""Application with GUI, which can revealed secret of longevity."""
def __init__(self, master):
"""Initialize frame."""
super(Application, self).__init__(master)
self.grid()
self.create_widgets()
def create_widgets(self):
"""Create widgets Button,... | the_stack_v2_python_sparse | Chapter 10/longevity.py | MartaSzuran/Python-for-the-Absolute-Beginner-M.Dawson | train | 1 |
12dcd5f7096e4684a91a188a73df5dbe52febc66 | [
"self.name = name\nself.desired_species = desired_species\nself.feared_species = feared_species",
"adopter_score = float(adoption_center.get_number_of_species(self.desired_species))\nnum_feared = float(adoption_center.get_number_of_species(self.feared_species))\nresult = adopter_score - 0.3 * num_feared\nif resul... | <|body_start_0|>
self.name = name
self.desired_species = desired_species
self.feared_species = feared_species
<|end_body_0|>
<|body_start_1|>
adopter_score = float(adoption_center.get_number_of_species(self.desired_species))
num_feared = float(adoption_center.get_number_of_speci... | A FearfulAdopter is afraid of a particular species of animal. If the adoption center has one or more of those animals in it, they will be a bit more reluctant to go there due to the presence of the feared species. Their score should be 1x number of desired species - .3x the number of feared species | FearfulAdopter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FearfulAdopter:
"""A FearfulAdopter is afraid of a particular species of animal. If the adoption center has one or more of those animals in it, they will be a bit more reluctant to go there due to the presence of the feared species. Their score should be 1x number of desired species - .3x the num... | stack_v2_sparse_classes_10k_train_007739 | 4,359 | no_license | [
{
"docstring": "Initializes FearfulAdopter, a subclass of Adopter object class feared_species - a string that is the name of the feared species. All of the inputs are the same as the Adopter",
"name": "__init__",
"signature": "def __init__(self, name, desired_species, feared_species)"
},
{
"docs... | 2 | stack_v2_sparse_classes_30k_train_001863 | Implement the Python class `FearfulAdopter` described below.
Class description:
A FearfulAdopter is afraid of a particular species of animal. If the adoption center has one or more of those animals in it, they will be a bit more reluctant to go there due to the presence of the feared species. Their score should be 1x ... | Implement the Python class `FearfulAdopter` described below.
Class description:
A FearfulAdopter is afraid of a particular species of animal. If the adoption center has one or more of those animals in it, they will be a bit more reluctant to go there due to the presence of the feared species. Their score should be 1x ... | d8750a5d78f042477f6577af67cc46d584f4aede | <|skeleton|>
class FearfulAdopter:
"""A FearfulAdopter is afraid of a particular species of animal. If the adoption center has one or more of those animals in it, they will be a bit more reluctant to go there due to the presence of the feared species. Their score should be 1x number of desired species - .3x the num... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FearfulAdopter:
"""A FearfulAdopter is afraid of a particular species of animal. If the adoption center has one or more of those animals in it, they will be a bit more reluctant to go there due to the presence of the feared species. Their score should be 1x number of desired species - .3x the number of feared... | the_stack_v2_python_sparse | ProblemSets/ProblemSet07c.py | Greatdane/MITx-6.00.1x | train | 0 |
ac8f1088a3937cca7f7feb9fd92e28771525e2c8 | [
"super(ResetServerStateTests, cls).setUpClass()\nkey_resp = cls.keypairs_client.create_keypair(rand_name('key'))\nassert key_resp.status_code is 200\ncls.key = key_resp.entity\ncls.resources.add(cls.key.name, cls.keypairs_client.delete_keypair)\ncls.server = cls.server_behaviors.create_active_server(key_name=cls.ke... | <|body_start_0|>
super(ResetServerStateTests, cls).setUpClass()
key_resp = cls.keypairs_client.create_keypair(rand_name('key'))
assert key_resp.status_code is 200
cls.key = key_resp.entity
cls.resources.add(cls.key.name, cls.keypairs_client.delete_keypair)
cls.server = cl... | ResetServerStateTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResetServerStateTests:
def setUpClass(cls):
"""Perform actions that setup the necessary resources for testing. The following resources are created during the setup: - Create a server in active state."""
<|body_0|>
def test_set_server_state(self):
"""Verify that the s... | stack_v2_sparse_classes_10k_train_007740 | 2,988 | permissive | [
{
"docstring": "Perform actions that setup the necessary resources for testing. The following resources are created during the setup: - Create a server in active state.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Verify that the state of a server can be set manu... | 2 | null | Implement the Python class `ResetServerStateTests` described below.
Class description:
Implement the ResetServerStateTests class.
Method signatures and docstrings:
- def setUpClass(cls): Perform actions that setup the necessary resources for testing. The following resources are created during the setup: - Create a se... | Implement the Python class `ResetServerStateTests` described below.
Class description:
Implement the ResetServerStateTests class.
Method signatures and docstrings:
- def setUpClass(cls): Perform actions that setup the necessary resources for testing. The following resources are created during the setup: - Create a se... | 30f0e64672676c3f90b4a582fe90fac6621475b3 | <|skeleton|>
class ResetServerStateTests:
def setUpClass(cls):
"""Perform actions that setup the necessary resources for testing. The following resources are created during the setup: - Create a server in active state."""
<|body_0|>
def test_set_server_state(self):
"""Verify that the s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ResetServerStateTests:
def setUpClass(cls):
"""Perform actions that setup the necessary resources for testing. The following resources are created during the setup: - Create a server in active state."""
super(ResetServerStateTests, cls).setUpClass()
key_resp = cls.keypairs_client.creat... | the_stack_v2_python_sparse | cloudroast/compute/instance_actions/admin_api/test_reset_server_state.py | RULCSoft/cloudroast | train | 1 | |
2a10f57ed56afdc6547a2676766c68e3f2b2e074 | [
"query = query.strip().lower().replace(' ', '+')\nsoup = self.get_soup(search_url % query)\nresults = []\nfor div in soup.select('#list-page .archive .list-truyen > .row'):\n a = div.select_one('.truyen-title a')\n info = div.select_one('.text-info a .chapter-text')\n results.append({'title': a.text.strip(... | <|body_start_0|>
query = query.strip().lower().replace(' ', '+')
soup = self.get_soup(search_url % query)
results = []
for div in soup.select('#list-page .archive .list-truyen > .row'):
a = div.select_one('.truyen-title a')
info = div.select_one('.text-info a .cha... | NovelFullCrawler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NovelFullCrawler:
def search_novel(self, query):
"""Gets a list of (title, url) matching the given query"""
<|body_0|>
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
<|body_1|>
def download_chapter_list(self, page):
"""Downloa... | stack_v2_sparse_classes_10k_train_007741 | 4,420 | permissive | [
{
"docstring": "Gets a list of (title, url) matching the given query",
"name": "search_novel",
"signature": "def search_novel(self, query)"
},
{
"docstring": "Get novel title, autor, cover etc",
"name": "read_novel_info",
"signature": "def read_novel_info(self)"
},
{
"docstring":... | 4 | stack_v2_sparse_classes_30k_train_006196 | Implement the Python class `NovelFullCrawler` described below.
Class description:
Implement the NovelFullCrawler class.
Method signatures and docstrings:
- def search_novel(self, query): Gets a list of (title, url) matching the given query
- def read_novel_info(self): Get novel title, autor, cover etc
- def download_... | Implement the Python class `NovelFullCrawler` described below.
Class description:
Implement the NovelFullCrawler class.
Method signatures and docstrings:
- def search_novel(self, query): Gets a list of (title, url) matching the given query
- def read_novel_info(self): Get novel title, autor, cover etc
- def download_... | 451e816ab03c8466be90f6f0b3eaa52d799140ce | <|skeleton|>
class NovelFullCrawler:
def search_novel(self, query):
"""Gets a list of (title, url) matching the given query"""
<|body_0|>
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
<|body_1|>
def download_chapter_list(self, page):
"""Downloa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NovelFullCrawler:
def search_novel(self, query):
"""Gets a list of (title, url) matching the given query"""
query = query.strip().lower().replace(' ', '+')
soup = self.get_soup(search_url % query)
results = []
for div in soup.select('#list-page .archive .list-truyen > .... | the_stack_v2_python_sparse | lncrawl/sources/novelfull.py | NNTin/lightnovel-crawler | train | 2 | |
64535387923dab6c9b6dd9b235680647e52ff975 | [
"Thread.__init__(self)\nself.command = command\nself.process = None",
"self.process = subprocess.Popen(self.command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\ntry:\n _stream_output(self.process)\nexcept RuntimeError as e:\n msg = 'Failed to run: %s, %s' % (self.command, str(e))\n raise RuntimeErro... | <|body_start_0|>
Thread.__init__(self)
self.command = command
self.process = None
<|end_body_0|>
<|body_start_1|>
self.process = subprocess.Popen(self.command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
try:
_stream_output(self.process)
except RuntimeErr... | Placeholder docstring. | _HostingContainer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _HostingContainer:
"""Placeholder docstring."""
def __init__(self, command):
"""Creates a new threaded hosting container. Args: command:"""
<|body_0|>
def run(self):
"""Placeholder docstring"""
<|body_1|>
def down(self):
"""Placeholder docstr... | stack_v2_sparse_classes_10k_train_007742 | 43,196 | permissive | [
{
"docstring": "Creates a new threaded hosting container. Args: command:",
"name": "__init__",
"signature": "def __init__(self, command)"
},
{
"docstring": "Placeholder docstring",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "Placeholder docstring",
"name": ... | 3 | stack_v2_sparse_classes_30k_test_000100 | Implement the Python class `_HostingContainer` described below.
Class description:
Placeholder docstring.
Method signatures and docstrings:
- def __init__(self, command): Creates a new threaded hosting container. Args: command:
- def run(self): Placeholder docstring
- def down(self): Placeholder docstring | Implement the Python class `_HostingContainer` described below.
Class description:
Placeholder docstring.
Method signatures and docstrings:
- def __init__(self, command): Creates a new threaded hosting container. Args: command:
- def run(self): Placeholder docstring
- def down(self): Placeholder docstring
<|skeleton... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class _HostingContainer:
"""Placeholder docstring."""
def __init__(self, command):
"""Creates a new threaded hosting container. Args: command:"""
<|body_0|>
def run(self):
"""Placeholder docstring"""
<|body_1|>
def down(self):
"""Placeholder docstr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _HostingContainer:
"""Placeholder docstring."""
def __init__(self, command):
"""Creates a new threaded hosting container. Args: command:"""
Thread.__init__(self)
self.command = command
self.process = None
def run(self):
"""Placeholder docstring"""
self... | the_stack_v2_python_sparse | src/sagemaker/local/image.py | aws/sagemaker-python-sdk | train | 2,050 |
8fcbeecd123fec46ddf01cd121c7407624b27954 | [
"request_user = User.get_by_id(token_auth.current_user())\nif request_user.role != 1:\n return ({'Error': 'Only admin users can create organisations.', 'SubCode': 'OnlyAdminAccess'}, 403)\ntry:\n organisation_dto = NewOrganisationDTO(request.get_json())\n if request_user.username not in organisation_dto.ma... | <|body_start_0|>
request_user = User.get_by_id(token_auth.current_user())
if request_user.role != 1:
return ({'Error': 'Only admin users can create organisations.', 'SubCode': 'OnlyAdminAccess'}, 403)
try:
organisation_dto = NewOrganisationDTO(request.get_json())
... | OrganisationsRestAPI | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganisationsRestAPI:
def post(self):
"""Creates a new organisation --- tags: - organisations produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - in: body name:... | stack_v2_sparse_classes_10k_train_007743 | 15,215 | permissive | [
{
"docstring": "Creates a new organisation --- tags: - organisations produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - in: body name: body required: true description: JSON object for... | 4 | stack_v2_sparse_classes_30k_train_004435 | Implement the Python class `OrganisationsRestAPI` described below.
Class description:
Implement the OrganisationsRestAPI class.
Method signatures and docstrings:
- def post(self): Creates a new organisation --- tags: - organisations produces: - application/json parameters: - in: header name: Authorization description... | Implement the Python class `OrganisationsRestAPI` described below.
Class description:
Implement the OrganisationsRestAPI class.
Method signatures and docstrings:
- def post(self): Creates a new organisation --- tags: - organisations produces: - application/json parameters: - in: header name: Authorization description... | 45bf3937c74902226096aee5b49e7abea62df524 | <|skeleton|>
class OrganisationsRestAPI:
def post(self):
"""Creates a new organisation --- tags: - organisations produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - in: body name:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OrganisationsRestAPI:
def post(self):
"""Creates a new organisation --- tags: - organisations produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - in: body name: body required... | the_stack_v2_python_sparse | backend/api/organisations/resources.py | hotosm/tasking-manager | train | 526 | |
c965cb91f7b05716a5d80b4568d14490f75c0b48 | [
"try:\n logger.info('测试登录用户的信息是否正确')\n self.login()\n self.click(self.userbtn)\n self.assertEqual(self.gettext(self.user_name), 'admin')\n self.assertEqual(self.gettext(self.user_type), '管理员')\nexcept Exception as msg:\n logger.error(u'异常原因：%s' % msg)\n self.driver.get_screenshot_as_file(os.pat... | <|body_start_0|>
try:
logger.info('测试登录用户的信息是否正确')
self.login()
self.click(self.userbtn)
self.assertEqual(self.gettext(self.user_name), 'admin')
self.assertEqual(self.gettext(self.user_type), '管理员')
except Exception as msg:
logger.e... | 首页的相关测试 | ManageTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageTest:
"""首页的相关测试"""
def test1_check_user(self):
"""测试登录用户的信息是否正确"""
<|body_0|>
def test2_logout(self):
"""退出系统测试"""
<|body_1|>
def test5_interaction_constraints1(self):
"""在录制过程中限制进入互动模块的测试"""
<|body_2|>
def test6_interacti... | stack_v2_sparse_classes_10k_train_007744 | 4,309 | no_license | [
{
"docstring": "测试登录用户的信息是否正确",
"name": "test1_check_user",
"signature": "def test1_check_user(self)"
},
{
"docstring": "退出系统测试",
"name": "test2_logout",
"signature": "def test2_logout(self)"
},
{
"docstring": "在录制过程中限制进入互动模块的测试",
"name": "test5_interaction_constraints1",
... | 4 | stack_v2_sparse_classes_30k_train_006620 | Implement the Python class `ManageTest` described below.
Class description:
首页的相关测试
Method signatures and docstrings:
- def test1_check_user(self): 测试登录用户的信息是否正确
- def test2_logout(self): 退出系统测试
- def test5_interaction_constraints1(self): 在录制过程中限制进入互动模块的测试
- def test6_interaction_constraints2(self): 在直播过程中限制进入互动模块的测试 | Implement the Python class `ManageTest` described below.
Class description:
首页的相关测试
Method signatures and docstrings:
- def test1_check_user(self): 测试登录用户的信息是否正确
- def test2_logout(self): 退出系统测试
- def test5_interaction_constraints1(self): 在录制过程中限制进入互动模块的测试
- def test6_interaction_constraints2(self): 在直播过程中限制进入互动模块的测试... | fd552eeb47fd4838c2c5caef4deea7480ab75ce9 | <|skeleton|>
class ManageTest:
"""首页的相关测试"""
def test1_check_user(self):
"""测试登录用户的信息是否正确"""
<|body_0|>
def test2_logout(self):
"""退出系统测试"""
<|body_1|>
def test5_interaction_constraints1(self):
"""在录制过程中限制进入互动模块的测试"""
<|body_2|>
def test6_interacti... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ManageTest:
"""首页的相关测试"""
def test1_check_user(self):
"""测试登录用户的信息是否正确"""
try:
logger.info('测试登录用户的信息是否正确')
self.login()
self.click(self.userbtn)
self.assertEqual(self.gettext(self.user_name), 'admin')
self.assertEqual(self.gette... | the_stack_v2_python_sparse | test_case/D001_manage_test.py | luhuifnag/AVA_UIauto_test | train | 0 |
536850eb042f24c979af6e9d0d2d5ca5597fd22f | [
"purls = request.data.get('purls', []) or []\npurl_only = request.data.get('purl_only', False)\nplain_purl = request.data.get('plain_purl', False)\nif not purls or not isinstance(purls, list):\n return Response(status=400, data={'Error': \"A non-empty 'purls' list of PURLs is required.\"})\nif plain_purl:\n p... | <|body_start_0|>
purls = request.data.get('purls', []) or []
purl_only = request.data.get('purl_only', False)
plain_purl = request.data.get('plain_purl', False)
if not purls or not isinstance(purls, list):
return Response(status=400, data={'Error': "A non-empty 'purls' list o... | Lookup for vulnerable packages by Package URL. | PackageViewSet | [
"Apache-2.0",
"CC-BY-SA-4.0",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PackageViewSet:
"""Lookup for vulnerable packages by Package URL."""
def bulk_search(self, request):
"""Lookup for vulnerable packages using many Package URLs at once."""
<|body_0|>
def all(self, request):
"""Return the Package URLs of all packages known to be vu... | stack_v2_sparse_classes_10k_train_007745 | 13,956 | permissive | [
{
"docstring": "Lookup for vulnerable packages using many Package URLs at once.",
"name": "bulk_search",
"signature": "def bulk_search(self, request)"
},
{
"docstring": "Return the Package URLs of all packages known to be vulnerable.",
"name": "all",
"signature": "def all(self, request)"... | 2 | stack_v2_sparse_classes_30k_train_002816 | Implement the Python class `PackageViewSet` described below.
Class description:
Lookup for vulnerable packages by Package URL.
Method signatures and docstrings:
- def bulk_search(self, request): Lookup for vulnerable packages using many Package URLs at once.
- def all(self, request): Return the Package URLs of all pa... | Implement the Python class `PackageViewSet` described below.
Class description:
Lookup for vulnerable packages by Package URL.
Method signatures and docstrings:
- def bulk_search(self, request): Lookup for vulnerable packages using many Package URLs at once.
- def all(self, request): Return the Package URLs of all pa... | eec05bb0f796d743e408a1b402df8abfc8344669 | <|skeleton|>
class PackageViewSet:
"""Lookup for vulnerable packages by Package URL."""
def bulk_search(self, request):
"""Lookup for vulnerable packages using many Package URLs at once."""
<|body_0|>
def all(self, request):
"""Return the Package URLs of all packages known to be vu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PackageViewSet:
"""Lookup for vulnerable packages by Package URL."""
def bulk_search(self, request):
"""Lookup for vulnerable packages using many Package URLs at once."""
purls = request.data.get('purls', []) or []
purl_only = request.data.get('purl_only', False)
plain_pur... | the_stack_v2_python_sparse | vulnerabilities/api.py | nexB/vulnerablecode | train | 371 |
f5629e682fd4bc02a02a90ffed28960461a4f6c6 | [
"event = rdfvalue.AuditEvent(user=self.token.username, action='CLIENT_APPROVAL_BREAK_GLASS_REQUEST', client=self.client_id, description=self.args.reason)\nflow.Events.PublishEvent('Audit', event, token=self.token)\nreturn self.ApprovalUrnBuilder(self.client_id.Path(), self.token.username, self.args.reason)",
"cli... | <|body_start_0|>
event = rdfvalue.AuditEvent(user=self.token.username, action='CLIENT_APPROVAL_BREAK_GLASS_REQUEST', client=self.client_id, description=self.args.reason)
flow.Events.PublishEvent('Audit', event, token=self.token)
return self.ApprovalUrnBuilder(self.client_id.Path(), self.token.us... | Grant an approval in an emergency. | BreakGlassGrantClientApprovalFlow | [
"Apache-2.0",
"DOC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BreakGlassGrantClientApprovalFlow:
"""Grant an approval in an emergency."""
def BuildApprovalUrn(self):
"""Builds approval object urn."""
<|body_0|>
def BuildSubjectTitle(self):
"""Returns the string with subject's title."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_10k_train_007746 | 28,119 | permissive | [
{
"docstring": "Builds approval object urn.",
"name": "BuildApprovalUrn",
"signature": "def BuildApprovalUrn(self)"
},
{
"docstring": "Returns the string with subject's title.",
"name": "BuildSubjectTitle",
"signature": "def BuildSubjectTitle(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005473 | Implement the Python class `BreakGlassGrantClientApprovalFlow` described below.
Class description:
Grant an approval in an emergency.
Method signatures and docstrings:
- def BuildApprovalUrn(self): Builds approval object urn.
- def BuildSubjectTitle(self): Returns the string with subject's title. | Implement the Python class `BreakGlassGrantClientApprovalFlow` described below.
Class description:
Grant an approval in an emergency.
Method signatures and docstrings:
- def BuildApprovalUrn(self): Builds approval object urn.
- def BuildSubjectTitle(self): Returns the string with subject's title.
<|skeleton|>
class ... | ba1648b97a76f844ffb8e1891cc9e2680f9b1c6e | <|skeleton|>
class BreakGlassGrantClientApprovalFlow:
"""Grant an approval in an emergency."""
def BuildApprovalUrn(self):
"""Builds approval object urn."""
<|body_0|>
def BuildSubjectTitle(self):
"""Returns the string with subject's title."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BreakGlassGrantClientApprovalFlow:
"""Grant an approval in an emergency."""
def BuildApprovalUrn(self):
"""Builds approval object urn."""
event = rdfvalue.AuditEvent(user=self.token.username, action='CLIENT_APPROVAL_BREAK_GLASS_REQUEST', client=self.client_id, description=self.args.reason... | the_stack_v2_python_sparse | lib/aff4_objects/security.py | defaultnamehere/grr | train | 3 |
88c10e162d8c9e4f32954becb73f9742e39f2479 | [
"super(AdbShellConnectionBuilder, self).__init__()\nself._connection = None\nreturn",
"if self._connection is None:\n self.logger.debug('Creating the adb shell connection')\n self._connection = adbconnection.ADBShellConnection()\nreturn self._connection"
] | <|body_start_0|>
super(AdbShellConnectionBuilder, self).__init__()
self._connection = None
return
<|end_body_0|>
<|body_start_1|>
if self._connection is None:
self.logger.debug('Creating the adb shell connection')
self._connection = adbconnection.ADBShellConnecti... | Use this to get an adb shell connection | AdbShellConnectionBuilder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdbShellConnectionBuilder:
"""Use this to get an adb shell connection"""
def __init__(self, parameters=None):
"""AdbShellConnectionBuilder Constructor :param: - `parameters`: Not used, just here to keep the interface uniform"""
<|body_0|>
def connection(self):
""... | stack_v2_sparse_classes_10k_train_007747 | 10,538 | permissive | [
{
"docstring": "AdbShellConnectionBuilder Constructor :param: - `parameters`: Not used, just here to keep the interface uniform",
"name": "__init__",
"signature": "def __init__(self, parameters=None)"
},
{
"docstring": "The ADB Shell Connection :rtype: ADBShellConnection :return: A built ADB she... | 2 | stack_v2_sparse_classes_30k_train_000702 | Implement the Python class `AdbShellConnectionBuilder` described below.
Class description:
Use this to get an adb shell connection
Method signatures and docstrings:
- def __init__(self, parameters=None): AdbShellConnectionBuilder Constructor :param: - `parameters`: Not used, just here to keep the interface uniform
- ... | Implement the Python class `AdbShellConnectionBuilder` described below.
Class description:
Use this to get an adb shell connection
Method signatures and docstrings:
- def __init__(self, parameters=None): AdbShellConnectionBuilder Constructor :param: - `parameters`: Not used, just here to keep the interface uniform
- ... | b4d1c77e1d611fe2b30768b42bdc7493afb0ea95 | <|skeleton|>
class AdbShellConnectionBuilder:
"""Use this to get an adb shell connection"""
def __init__(self, parameters=None):
"""AdbShellConnectionBuilder Constructor :param: - `parameters`: Not used, just here to keep the interface uniform"""
<|body_0|>
def connection(self):
""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AdbShellConnectionBuilder:
"""Use this to get an adb shell connection"""
def __init__(self, parameters=None):
"""AdbShellConnectionBuilder Constructor :param: - `parameters`: Not used, just here to keep the interface uniform"""
super(AdbShellConnectionBuilder, self).__init__()
sel... | the_stack_v2_python_sparse | apetools/builders/subbuilders/connectionbuilder.py | russell-n/oldape | train | 0 |
538d445e457171953756acf0f1e21677ba0b26a1 | [
"self.width, self.height = dim\nself.width = self.width // 2\nself.height = self.height // 2\nself.ruleset = ruleset\nself.surface = pygame.Surface(dim)\nself.generation = [0] + [random.randint(0, 1) for i in range(self.width - 1)] + [0]",
"number = left * 4 + center * 2 + right\nif number == 7:\n if self.rule... | <|body_start_0|>
self.width, self.height = dim
self.width = self.width // 2
self.height = self.height // 2
self.ruleset = ruleset
self.surface = pygame.Surface(dim)
self.generation = [0] + [random.randint(0, 1) for i in range(self.width - 1)] + [0]
<|end_body_0|>
<|body_... | simple Cellular Automata - Wolfram Elementary | WolframElementary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WolframElementary:
"""simple Cellular Automata - Wolfram Elementary"""
def __init__(self, dim: tuple, ruleset: int):
""":param dim: dimension of surface to draw on :param ruleset: ruleset to use"""
<|body_0|>
def rule(self, left: int, center: int, right: int) -> int:
... | stack_v2_sparse_classes_10k_train_007748 | 3,015 | no_license | [
{
"docstring": ":param dim: dimension of surface to draw on :param ruleset: ruleset to use",
"name": "__init__",
"signature": "def __init__(self, dim: tuple, ruleset: int)"
},
{
"docstring": "apply ruleset",
"name": "rule",
"signature": "def rule(self, left: int, center: int, right: int)... | 3 | stack_v2_sparse_classes_30k_train_000792 | Implement the Python class `WolframElementary` described below.
Class description:
simple Cellular Automata - Wolfram Elementary
Method signatures and docstrings:
- def __init__(self, dim: tuple, ruleset: int): :param dim: dimension of surface to draw on :param ruleset: ruleset to use
- def rule(self, left: int, cent... | Implement the Python class `WolframElementary` described below.
Class description:
simple Cellular Automata - Wolfram Elementary
Method signatures and docstrings:
- def __init__(self, dim: tuple, ruleset: int): :param dim: dimension of surface to draw on :param ruleset: ruleset to use
- def rule(self, left: int, cent... | 1fd421195a2888c0588a49f5a043a1110eedcdbf | <|skeleton|>
class WolframElementary:
"""simple Cellular Automata - Wolfram Elementary"""
def __init__(self, dim: tuple, ruleset: int):
""":param dim: dimension of surface to draw on :param ruleset: ruleset to use"""
<|body_0|>
def rule(self, left: int, center: int, right: int) -> int:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WolframElementary:
"""simple Cellular Automata - Wolfram Elementary"""
def __init__(self, dim: tuple, ruleset: int):
""":param dim: dimension of surface to draw on :param ruleset: ruleset to use"""
self.width, self.height = dim
self.width = self.width // 2
self.height = se... | the_stack_v2_python_sparse | effects/WolframElementary.py | gunny26/pygame | train | 5 |
d63fbf23d3fc1c8e3be519a34145c3ddfcc26580 | [
"if x <= 1:\n return x\nlow, high = (0, x)\nprint('low\\tmid\\thigh')\nwhile low <= high:\n mid = low + (high - low) // 2\n est = mid ** 2\n if est > x:\n print('{}\\t{}\\t{}, 答案比 mid 小, 要往左邊走'.format(low, mid, high))\n high = mid - 1\n else:\n print('{}\\t{}\\t{}, 答案比 mid 大, 要往右... | <|body_start_0|>
if x <= 1:
return x
low, high = (0, x)
print('low\tmid\thigh')
while low <= high:
mid = low + (high - low) // 2
est = mid ** 2
if est > x:
print('{}\t{}\t{}, 答案比 mid 小, 要往左邊走'.format(low, mid, high))
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mySqrt(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def mySqrtOld(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if x <= 1:
return x
low, high = (0, x)
print('lo... | stack_v2_sparse_classes_10k_train_007749 | 1,320 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "mySqrt",
"signature": "def mySqrt(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "mySqrtOld",
"signature": "def mySqrtOld(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005467 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mySqrt(self, x): :type x: int :rtype: int
- def mySqrtOld(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mySqrt(self, x): :type x: int :rtype: int
- def mySqrtOld(self, x): :type x: int :rtype: int
<|skeleton|>
class Solution:
def mySqrt(self, x):
""":type x: int :... | ac53dd9bf2c4c9d17c9dc5f7fdda32e386658fdd | <|skeleton|>
class Solution:
def mySqrt(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def mySqrtOld(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def mySqrt(self, x):
""":type x: int :rtype: int"""
if x <= 1:
return x
low, high = (0, x)
print('low\tmid\thigh')
while low <= high:
mid = low + (high - low) // 2
est = mid ** 2
if est > x:
print... | the_stack_v2_python_sparse | cs_notes/binary_search/sqrt_x.py | hwc1824/LeetCodeSolution | train | 0 | |
3667aa5cec6bbab2d040f4484ac3839be9397ce7 | [
"super(DGCNNCls, self).__init__()\nself.cfg = cfg\nself.k = cfg.get('k')\nself.emb_dims = cfg.get('emb_dims')\nself.dropout = cfg.get('dropout', 0.5)\nself.bn1 = nn.BatchNorm2d(64)\nself.bn2 = nn.BatchNorm2d(64)\nself.bn3 = nn.BatchNorm2d(128)\nself.bn4 = nn.BatchNorm2d(256)\nself.bn5 = nn.BatchNorm1d(self.emb_dims... | <|body_start_0|>
super(DGCNNCls, self).__init__()
self.cfg = cfg
self.k = cfg.get('k')
self.emb_dims = cfg.get('emb_dims')
self.dropout = cfg.get('dropout', 0.5)
self.bn1 = nn.BatchNorm2d(64)
self.bn2 = nn.BatchNorm2d(64)
self.bn3 = nn.BatchNorm2d(128)
... | DGCNNCls | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DGCNNCls:
def __init__(self, cfg, output_channels=40):
"""Author: shi.xian dgcnn classification network Args: k (int): [Num of nearest neighbors] emb_dims (int): [Dimension of embeddings] dropout (List[int], optional): [layers to apply dropout]"""
<|body_0|>
def forward(self... | stack_v2_sparse_classes_10k_train_007750 | 4,296 | permissive | [
{
"docstring": "Author: shi.xian dgcnn classification network Args: k (int): [Num of nearest neighbors] emb_dims (int): [Dimension of embeddings] dropout (List[int], optional): [layers to apply dropout]",
"name": "__init__",
"signature": "def __init__(self, cfg, output_channels=40)"
},
{
"docstr... | 2 | stack_v2_sparse_classes_30k_train_005705 | Implement the Python class `DGCNNCls` described below.
Class description:
Implement the DGCNNCls class.
Method signatures and docstrings:
- def __init__(self, cfg, output_channels=40): Author: shi.xian dgcnn classification network Args: k (int): [Num of nearest neighbors] emb_dims (int): [Dimension of embeddings] dro... | Implement the Python class `DGCNNCls` described below.
Class description:
Implement the DGCNNCls class.
Method signatures and docstrings:
- def __init__(self, cfg, output_channels=40): Author: shi.xian dgcnn classification network Args: k (int): [Num of nearest neighbors] emb_dims (int): [Dimension of embeddings] dro... | 9987806185a4e1619bc15ceecb8a1755e764ff68 | <|skeleton|>
class DGCNNCls:
def __init__(self, cfg, output_channels=40):
"""Author: shi.xian dgcnn classification network Args: k (int): [Num of nearest neighbors] emb_dims (int): [Dimension of embeddings] dropout (List[int], optional): [layers to apply dropout]"""
<|body_0|>
def forward(self... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DGCNNCls:
def __init__(self, cfg, output_channels=40):
"""Author: shi.xian dgcnn classification network Args: k (int): [Num of nearest neighbors] emb_dims (int): [Dimension of embeddings] dropout (List[int], optional): [layers to apply dropout]"""
super(DGCNNCls, self).__init__()
self.... | the_stack_v2_python_sparse | gorilla3d/nn/models/dgcnn/dgcnn_cls.py | SijanNeupane49/gorilla-3d | train | 0 | |
af6a21cd3f5eaa521ebc79959376af218c55a2e0 | [
"sql = ['-- Insert State Seed Data ({})'.format(country.alpha_2_code), 'INSERT INTO postaddr.states(code, country, alpha_code,' + 'subdivision_category, name)', 'VALUES']\nstates_sql = [(\"('{code}', '{country}', '{alpha_2_code}', \" + \"'{subdivision_category}', '{name}')\").format(code=s.code, country=s.country.a... | <|body_start_0|>
sql = ['-- Insert State Seed Data ({})'.format(country.alpha_2_code), 'INSERT INTO postaddr.states(code, country, alpha_code,' + 'subdivision_category, name)', 'VALUES']
states_sql = [("('{code}', '{country}', '{alpha_2_code}', " + "'{subdivision_category}', '{name}')").format(code=s.co... | Use a SQL generator to produce Cooper SQL commands from data objects. | CooperSqlGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CooperSqlGenerator:
"""Use a SQL generator to produce Cooper SQL commands from data objects."""
def states(self, country: Country) -> SqlOutput:
"""Generate a cooper SQL statement for a set of states. :param country: the country for which you want to generate the States SQL INSERT co... | stack_v2_sparse_classes_10k_train_007751 | 11,561 | permissive | [
{
"docstring": "Generate a cooper SQL statement for a set of states. :param country: the country for which you want to generate the States SQL INSERT command :return: a SQL INSERT command string",
"name": "states",
"signature": "def states(self, country: Country) -> SqlOutput"
},
{
"docstring": ... | 6 | stack_v2_sparse_classes_30k_train_006162 | Implement the Python class `CooperSqlGenerator` described below.
Class description:
Use a SQL generator to produce Cooper SQL commands from data objects.
Method signatures and docstrings:
- def states(self, country: Country) -> SqlOutput: Generate a cooper SQL statement for a set of states. :param country: the countr... | Implement the Python class `CooperSqlGenerator` described below.
Class description:
Use a SQL generator to produce Cooper SQL commands from data objects.
Method signatures and docstrings:
- def states(self, country: Country) -> SqlOutput: Generate a cooper SQL statement for a set of states. :param country: the countr... | f0750799eade79405e3f52e1a2a61dfd4e88dd4f | <|skeleton|>
class CooperSqlGenerator:
"""Use a SQL generator to produce Cooper SQL commands from data objects."""
def states(self, country: Country) -> SqlOutput:
"""Generate a cooper SQL statement for a set of states. :param country: the country for which you want to generate the States SQL INSERT co... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CooperSqlGenerator:
"""Use a SQL generator to produce Cooper SQL commands from data objects."""
def states(self, country: Country) -> SqlOutput:
"""Generate a cooper SQL statement for a set of states. :param country: the country for which you want to generate the States SQL INSERT command :return... | the_stack_v2_python_sparse | Python_lib/cliff/sql.py | mndarren/Code-Lib | train | 8 |
e03bb58b24774d695efaaa1e9efd72944748a01d | [
"if environment is not None and utils.version_lt(self._version, '1.25'):\n raise errors.InvalidVersion('Setting environment for exec is not supported in API < 1.25')\nif isinstance(cmd, str):\n cmd = utils.split_command(cmd)\nif isinstance(environment, dict):\n environment = utils.utils.format_environment(... | <|body_start_0|>
if environment is not None and utils.version_lt(self._version, '1.25'):
raise errors.InvalidVersion('Setting environment for exec is not supported in API < 1.25')
if isinstance(cmd, str):
cmd = utils.split_command(cmd)
if isinstance(environment, dict):
... | ExecApiMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExecApiMixin:
def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None):
"""Sets up an exec instance in a running container. Args: container (str): Target container where exec insta... | stack_v2_sparse_classes_10k_train_007752 | 6,224 | permissive | [
{
"docstring": "Sets up an exec instance in a running container. Args: container (str): Target container where exec instance will be created cmd (str or list): Command to be executed stdout (bool): Attach to stdout. Default: ``True`` stderr (bool): Attach to stderr. Default: ``True`` stdin (bool): Attach to std... | 4 | stack_v2_sparse_classes_30k_train_001238 | Implement the Python class `ExecApiMixin` described below.
Class description:
Implement the ExecApiMixin class.
Method signatures and docstrings:
- def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None): Sets... | Implement the Python class `ExecApiMixin` described below.
Class description:
Implement the ExecApiMixin class.
Method signatures and docstrings:
- def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None): Sets... | c38656dc7894363f32317affecc3e4279e1163f8 | <|skeleton|>
class ExecApiMixin:
def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None):
"""Sets up an exec instance in a running container. Args: container (str): Target container where exec insta... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExecApiMixin:
def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None):
"""Sets up an exec instance in a running container. Args: container (str): Target container where exec instance will be cr... | the_stack_v2_python_sparse | docker/api/exec_api.py | docker/docker-py | train | 6,473 | |
efc4e932b29cfe6f5458d8f2b041269ce01a64e7 | [
"returnSql = ''\nif filter:\n grouptype = ''\n grouptype, list = SearchFilter.GetSearchList(filter)\n if urlDecode:\n returnSql = SearchFilter.ToSql(list, grouptype)\n returnSql = urllib.parse.unquote(returnSql)\n else:\n returnSql = SearchFilter.ToSql(list, grouptype)\nreturn retur... | <|body_start_0|>
returnSql = ''
if filter:
grouptype = ''
grouptype, list = SearchFilter.GetSearchList(filter)
if urlDecode:
returnSql = SearchFilter.ToSql(list, grouptype)
returnSql = urllib.parse.unquote(returnSql)
else:
... | SearchFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchFilter:
def TransfromFilterToSql(filter, urlDecode=True):
"""转换EasyUi分页时的条件Filters为Sql Args: filter (string): Filters urlDecode (bool): Returns: returnValue (string): 字段值字符串"""
<|body_0|>
def GetSearchList(jsons):
"""将JSON字符串转换为LIST Args: jsons (string): json 串... | stack_v2_sparse_classes_10k_train_007753 | 3,094 | no_license | [
{
"docstring": "转换EasyUi分页时的条件Filters为Sql Args: filter (string): Filters urlDecode (bool): Returns: returnValue (string): 字段值字符串",
"name": "TransfromFilterToSql",
"signature": "def TransfromFilterToSql(filter, urlDecode=True)"
},
{
"docstring": "将JSON字符串转换为LIST Args: jsons (string): json 串 Retur... | 3 | stack_v2_sparse_classes_30k_train_000504 | Implement the Python class `SearchFilter` described below.
Class description:
Implement the SearchFilter class.
Method signatures and docstrings:
- def TransfromFilterToSql(filter, urlDecode=True): 转换EasyUi分页时的条件Filters为Sql Args: filter (string): Filters urlDecode (bool): Returns: returnValue (string): 字段值字符串
- def G... | Implement the Python class `SearchFilter` described below.
Class description:
Implement the SearchFilter class.
Method signatures and docstrings:
- def TransfromFilterToSql(filter, urlDecode=True): 转换EasyUi分页时的条件Filters为Sql Args: filter (string): Filters urlDecode (bool): Returns: returnValue (string): 字段值字符串
- def G... | 24689b359ee225c8678b33766e51a045fa5d50c9 | <|skeleton|>
class SearchFilter:
def TransfromFilterToSql(filter, urlDecode=True):
"""转换EasyUi分页时的条件Filters为Sql Args: filter (string): Filters urlDecode (bool): Returns: returnValue (string): 字段值字符串"""
<|body_0|>
def GetSearchList(jsons):
"""将JSON字符串转换为LIST Args: jsons (string): json 串... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SearchFilter:
def TransfromFilterToSql(filter, urlDecode=True):
"""转换EasyUi分页时的条件Filters为Sql Args: filter (string): Filters urlDecode (bool): Returns: returnValue (string): 字段值字符串"""
returnSql = ''
if filter:
grouptype = ''
grouptype, list = SearchFilter.GetSear... | the_stack_v2_python_sparse | apps/utilities/publiclibrary/SearchFilter.py | seesky/hpwf | train | 32 | |
d5b188cf33941b0f248c596f975c6cc85397fcd9 | [
"self.nums = {}\nfor i, v in enumerate(nums):\n self.nums[i] = v",
"sum = 0\nfor x in range(i, j + 1):\n sum += self.nums[x]\nreturn sum"
] | <|body_start_0|>
self.nums = {}
for i, v in enumerate(nums):
self.nums[i] = v
<|end_body_0|>
<|body_start_1|>
sum = 0
for x in range(i, j + 1):
sum += self.nums[x]
return sum
<|end_body_1|>
| NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
"""sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_10k_train_007754 | 1,287 | no_license | [
{
"docstring": "initialize your data structure here. :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": "sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtype: int",
"name": "sumRange",
"signature": "def sumRange(self, ... | 2 | stack_v2_sparse_classes_30k_train_004622 | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): initialize your data structure here. :type nums: List[int]
- def sumRange(self, i, j): sum of elements nums[i..j], inclusive. :type i: int :type j: int ... | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): initialize your data structure here. :type nums: List[int]
- def sumRange(self, i, j): sum of elements nums[i..j], inclusive. :type i: int :type j: int ... | 6de551327f96ec4d4b63d0045281b65bbb4f5d0f | <|skeleton|>
class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
"""sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
self.nums = {}
for i, v in enumerate(nums):
self.nums[i] = v
def sumRange(self, i, j):
"""sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtyp... | the_stack_v2_python_sparse | sumRange.py | JingweiTu/leetcode | train | 0 | |
edba1402e44e984f36352b564538403c60656216 | [
"from collections import Counter\ncounter = Counter(nums)\ni = 0\nfor color in range(3):\n for _ in range(counter[color]):\n nums[i] = color\n i += 1",
"\"\"\"https://leetcode.com/problems/sort-colors/discuss/26481/Python-O(n)-1-pass-in-place-solution-with-explanation\"\"\"\nn = len(nums)\nl, r =... | <|body_start_0|>
from collections import Counter
counter = Counter(nums)
i = 0
for color in range(3):
for _ in range(counter[color]):
nums[i] = color
i += 1
<|end_body_0|>
<|body_start_1|>
"""https://leetcode.com/problems/sort-colors/d... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortColors(self, nums: List[int]) -> None:
"""Counting Sort, Time: O(n), Space: O(n)"""
<|body_0|>
def sortColors(self, nums: List[int]) -> None:
"""Two Pointer, Time: O(n), Space: O(1)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
f... | stack_v2_sparse_classes_10k_train_007755 | 1,275 | no_license | [
{
"docstring": "Counting Sort, Time: O(n), Space: O(n)",
"name": "sortColors",
"signature": "def sortColors(self, nums: List[int]) -> None"
},
{
"docstring": "Two Pointer, Time: O(n), Space: O(1)",
"name": "sortColors",
"signature": "def sortColors(self, nums: List[int]) -> None"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums: List[int]) -> None: Counting Sort, Time: O(n), Space: O(n)
- def sortColors(self, nums: List[int]) -> None: Two Pointer, Time: O(n), Space: O(1) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums: List[int]) -> None: Counting Sort, Time: O(n), Space: O(n)
- def sortColors(self, nums: List[int]) -> None: Two Pointer, Time: O(n), Space: O(1)
<|ske... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def sortColors(self, nums: List[int]) -> None:
"""Counting Sort, Time: O(n), Space: O(n)"""
<|body_0|>
def sortColors(self, nums: List[int]) -> None:
"""Two Pointer, Time: O(n), Space: O(1)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def sortColors(self, nums: List[int]) -> None:
"""Counting Sort, Time: O(n), Space: O(n)"""
from collections import Counter
counter = Counter(nums)
i = 0
for color in range(3):
for _ in range(counter[color]):
nums[i] = color
... | the_stack_v2_python_sparse | python/75-Sort Colors.py | cwza/leetcode | train | 0 | |
029fd7c4aabe1ebcfd683db2b9668d059f5f4785 | [
"B = []\nlength = len(A)\nfor i in range(length):\n B.append(int(str(A[i])[-k]))\nreturn B",
"C = []\nB = _deepcopy(A)\nk = 27\nfor i in range(k):\n C.append(0)\nlength = len(A)\nfor j in range(length):\n C[A[j]] = C[A[j]] + 1\nfor i in range(1, k):\n C[i] = C[i] + C[i - 1]\nfor i in range(length):\n ... | <|body_start_0|>
B = []
length = len(A)
for i in range(length):
B.append(int(str(A[i])[-k]))
return B
<|end_body_0|>
<|body_start_1|>
C = []
B = _deepcopy(A)
k = 27
for i in range(k):
C.append(0)
length = len(A)
for... | chpater8.3 note and function | Chapter8_3 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Chapter8_3:
"""chpater8.3 note and function"""
def getarraystr_subarray(self, A, k):
"""取一个数组中每个元素第k位构成的子数组 Args === `A` : 待取子数组的数组 `k` : 第1位是最低位，第d位是最高位 Return === `subarray` : 取好的子数组 Example === ```python Chapter8_3().getarraystr_subarray(['ABC', 'DEF', 'OPQ'], 1) ['C', 'F', 'Q'] `... | stack_v2_sparse_classes_10k_train_007756 | 18,569 | permissive | [
{
"docstring": "取一个数组中每个元素第k位构成的子数组 Args === `A` : 待取子数组的数组 `k` : 第1位是最低位，第d位是最高位 Return === `subarray` : 取好的子数组 Example === ```python Chapter8_3().getarraystr_subarray(['ABC', 'DEF', 'OPQ'], 1) ['C', 'F', 'Q'] ```",
"name": "getarraystr_subarray",
"signature": "def getarraystr_subarray(self, A, k)"
}... | 4 | stack_v2_sparse_classes_30k_train_006857 | Implement the Python class `Chapter8_3` described below.
Class description:
chpater8.3 note and function
Method signatures and docstrings:
- def getarraystr_subarray(self, A, k): 取一个数组中每个元素第k位构成的子数组 Args === `A` : 待取子数组的数组 `k` : 第1位是最低位，第d位是最高位 Return === `subarray` : 取好的子数组 Example === ```python Chapter8_3().getarra... | Implement the Python class `Chapter8_3` described below.
Class description:
chpater8.3 note and function
Method signatures and docstrings:
- def getarraystr_subarray(self, A, k): 取一个数组中每个元素第k位构成的子数组 Args === `A` : 待取子数组的数组 `k` : 第1位是最低位，第d位是最高位 Return === `subarray` : 取好的子数组 Example === ```python Chapter8_3().getarra... | 33662f46dc346203b220d7481d1a4439feda05d2 | <|skeleton|>
class Chapter8_3:
"""chpater8.3 note and function"""
def getarraystr_subarray(self, A, k):
"""取一个数组中每个元素第k位构成的子数组 Args === `A` : 待取子数组的数组 `k` : 第1位是最低位，第d位是最高位 Return === `subarray` : 取好的子数组 Example === ```python Chapter8_3().getarraystr_subarray(['ABC', 'DEF', 'OPQ'], 1) ['C', 'F', 'Q'] `... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Chapter8_3:
"""chpater8.3 note and function"""
def getarraystr_subarray(self, A, k):
"""取一个数组中每个元素第k位构成的子数组 Args === `A` : 待取子数组的数组 `k` : 第1位是最低位，第d位是最高位 Return === `subarray` : 取好的子数组 Example === ```python Chapter8_3().getarraystr_subarray(['ABC', 'DEF', 'OPQ'], 1) ['C', 'F', 'Q'] ```"""
... | the_stack_v2_python_sparse | src/chapter8/chapter8note.py | HideLakitu/IntroductionToAlgorithm.Python | train | 1 |
716598e54713fde901b3625461d59204dc4e9cb7 | [
"self.input_size = input_size\nself.output_size = output_size\nself.X = tf.placeholder(tf.float32, shape=[None, self.input_size])\nself.Y = tf.placeholder(tf.float32, shape=[None, self.output_size])\nself.weights = tf.Variable(tf.glorot_uniform_initializer()((self.input_size, self.output_size)))\nself.biases = tf.V... | <|body_start_0|>
self.input_size = input_size
self.output_size = output_size
self.X = tf.placeholder(tf.float32, shape=[None, self.input_size])
self.Y = tf.placeholder(tf.float32, shape=[None, self.output_size])
self.weights = tf.Variable(tf.glorot_uniform_initializer()((self.inp... | SoftmaxRegression | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SoftmaxRegression:
def __init__(self, input_size, output_size, dropout=False, BN=False):
"""Function: Initialization of all variables"""
<|body_0|>
def Regression(self):
"""Function: Define softmax function as y = sigmoid(A * x + b) Using tf function tf.layers.BatchN... | stack_v2_sparse_classes_10k_train_007757 | 19,475 | no_license | [
{
"docstring": "Function: Initialization of all variables",
"name": "__init__",
"signature": "def __init__(self, input_size, output_size, dropout=False, BN=False)"
},
{
"docstring": "Function: Define softmax function as y = sigmoid(A * x + b) Using tf function tf.layers.BatchNormalization()",
... | 5 | stack_v2_sparse_classes_30k_train_001853 | Implement the Python class `SoftmaxRegression` described below.
Class description:
Implement the SoftmaxRegression class.
Method signatures and docstrings:
- def __init__(self, input_size, output_size, dropout=False, BN=False): Function: Initialization of all variables
- def Regression(self): Function: Define softmax... | Implement the Python class `SoftmaxRegression` described below.
Class description:
Implement the SoftmaxRegression class.
Method signatures and docstrings:
- def __init__(self, input_size, output_size, dropout=False, BN=False): Function: Initialization of all variables
- def Regression(self): Function: Define softmax... | 929e28c3ea5aec63bc655035c48d96d2d3cff5bc | <|skeleton|>
class SoftmaxRegression:
def __init__(self, input_size, output_size, dropout=False, BN=False):
"""Function: Initialization of all variables"""
<|body_0|>
def Regression(self):
"""Function: Define softmax function as y = sigmoid(A * x + b) Using tf function tf.layers.BatchN... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SoftmaxRegression:
def __init__(self, input_size, output_size, dropout=False, BN=False):
"""Function: Initialization of all variables"""
self.input_size = input_size
self.output_size = output_size
self.X = tf.placeholder(tf.float32, shape=[None, self.input_size])
self.Y... | the_stack_v2_python_sparse | Ao_Zhang/assignment2/assignment2_question3.py | ZhangAoCanada/CSI5138_Assignments | train | 1 | |
879ffbc10241dc43f05e36ca9cfd1218cf97d636 | [
"self._recursive = recursive\nnop = lambda: None\nskip = lambda arg: None\nself.link_callback = skip\nself.link_content_callback = skip\nself.ext_link_callback = skip\nself.redirect_callback = skip\nself.error_callback = skip\nself.nonhtml_callback = skip\nself.stop_callback = nop\nself.ext_link_test = have_same_ba... | <|body_start_0|>
self._recursive = recursive
nop = lambda: None
skip = lambda arg: None
self.link_callback = skip
self.link_content_callback = skip
self.ext_link_callback = skip
self.redirect_callback = skip
self.error_callback = skip
self.nonhtml_... | URL-redirects crawler | LinkCrawler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkCrawler:
"""URL-redirects crawler"""
def __init__(self, recursive=True):
"""Constructor"""
<|body_0|>
def process(self, url):
"""Iterate the external links from url"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self._recursive = recursive
... | stack_v2_sparse_classes_10k_train_007758 | 2,502 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, recursive=True)"
},
{
"docstring": "Iterate the external links from url",
"name": "process",
"signature": "def process(self, url)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002157 | Implement the Python class `LinkCrawler` described below.
Class description:
URL-redirects crawler
Method signatures and docstrings:
- def __init__(self, recursive=True): Constructor
- def process(self, url): Iterate the external links from url | Implement the Python class `LinkCrawler` described below.
Class description:
URL-redirects crawler
Method signatures and docstrings:
- def __init__(self, recursive=True): Constructor
- def process(self, url): Iterate the external links from url
<|skeleton|>
class LinkCrawler:
"""URL-redirects crawler"""
def... | aab6927de8424f0a8e9eb9b9a462a775555a80d5 | <|skeleton|>
class LinkCrawler:
"""URL-redirects crawler"""
def __init__(self, recursive=True):
"""Constructor"""
<|body_0|>
def process(self, url):
"""Iterate the external links from url"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LinkCrawler:
"""URL-redirects crawler"""
def __init__(self, recursive=True):
"""Constructor"""
self._recursive = recursive
nop = lambda: None
skip = lambda arg: None
self.link_callback = skip
self.link_content_callback = skip
self.ext_link_callback ... | the_stack_v2_python_sparse | lib/core/crawler.py | Silentsoul04/gtta-scripts | train | 0 |
86367a1d88a19de1f9555d5703d705fba9ca793d | [
"try:\n with transaction.atomic():\n self.create(user=user, group=group, project=group.project, is_active=True, reason=reason)\nexcept IntegrityError:\n pass",
"from sentry.models import User, UserOption, UserOptionValue\nusers = User.objects.filter(sentry_orgmember_set__teams=group.project.team, is_... | <|body_start_0|>
try:
with transaction.atomic():
self.create(user=user, group=group, project=group.project, is_active=True, reason=reason)
except IntegrityError:
pass
<|end_body_0|>
<|body_start_1|>
from sentry.models import User, UserOption, UserOptionVa... | GroupSubscriptionManager | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupSubscriptionManager:
def subscribe(self, group, user, reason=GroupSubscriptionReason.unknown):
"""Subscribe a user to an issue, but only if the user has not explicitly unsubscribed."""
<|body_0|>
def get_participants(self, group):
"""Identify all users who are p... | stack_v2_sparse_classes_10k_train_007759 | 5,262 | permissive | [
{
"docstring": "Subscribe a user to an issue, but only if the user has not explicitly unsubscribed.",
"name": "subscribe",
"signature": "def subscribe(self, group, user, reason=GroupSubscriptionReason.unknown)"
},
{
"docstring": "Identify all users who are participating with a given issue.",
... | 2 | stack_v2_sparse_classes_30k_train_003809 | Implement the Python class `GroupSubscriptionManager` described below.
Class description:
Implement the GroupSubscriptionManager class.
Method signatures and docstrings:
- def subscribe(self, group, user, reason=GroupSubscriptionReason.unknown): Subscribe a user to an issue, but only if the user has not explicitly un... | Implement the Python class `GroupSubscriptionManager` described below.
Class description:
Implement the GroupSubscriptionManager class.
Method signatures and docstrings:
- def subscribe(self, group, user, reason=GroupSubscriptionReason.unknown): Subscribe a user to an issue, but only if the user has not explicitly un... | b937615079d7b24dc225a83b99b1b65da932fc66 | <|skeleton|>
class GroupSubscriptionManager:
def subscribe(self, group, user, reason=GroupSubscriptionReason.unknown):
"""Subscribe a user to an issue, but only if the user has not explicitly unsubscribed."""
<|body_0|>
def get_participants(self, group):
"""Identify all users who are p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GroupSubscriptionManager:
def subscribe(self, group, user, reason=GroupSubscriptionReason.unknown):
"""Subscribe a user to an issue, but only if the user has not explicitly unsubscribed."""
try:
with transaction.atomic():
self.create(user=user, group=group, project=... | the_stack_v2_python_sparse | src/sentry/models/groupsubscription.py | atlassian/sentry | train | 1 | |
f03440f4918b1cf3bddc4044ae371b24da2e5d5b | [
"username = attrs['username']\npassword = attrs['password']\ntry:\n user = User.objects.get(username=username, is_staff=True)\nexcept User.DoesNotExit:\n raise serializers.ValidationError('手机号或密码错误')\nif not user.check_password(password):\n raise serializers.ValidationError('手机号或密码错误')\nattrs['user'] = use... | <|body_start_0|>
username = attrs['username']
password = attrs['password']
try:
user = User.objects.get(username=username, is_staff=True)
except User.DoesNotExit:
raise serializers.ValidationError('手机号或密码错误')
if not user.check_password(password):
... | 验证序列化器类 | AuthorizationSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthorizationSerializer:
"""验证序列化器类"""
def validate(self, attrs):
"""自定义验证用户名和密码"""
<|body_0|>
def create(self, validated_data):
"""重新增加一个jwt"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
username = attrs['username']
password = attrs['... | stack_v2_sparse_classes_10k_train_007760 | 3,173 | permissive | [
{
"docstring": "自定义验证用户名和密码",
"name": "validate",
"signature": "def validate(self, attrs)"
},
{
"docstring": "重新增加一个jwt",
"name": "create",
"signature": "def create(self, validated_data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003602 | Implement the Python class `AuthorizationSerializer` described below.
Class description:
验证序列化器类
Method signatures and docstrings:
- def validate(self, attrs): 自定义验证用户名和密码
- def create(self, validated_data): 重新增加一个jwt | Implement the Python class `AuthorizationSerializer` described below.
Class description:
验证序列化器类
Method signatures and docstrings:
- def validate(self, attrs): 自定义验证用户名和密码
- def create(self, validated_data): 重新增加一个jwt
<|skeleton|>
class AuthorizationSerializer:
"""验证序列化器类"""
def validate(self, attrs):
... | d3ce2185ec3c68325e8becddce07d0a9da144325 | <|skeleton|>
class AuthorizationSerializer:
"""验证序列化器类"""
def validate(self, attrs):
"""自定义验证用户名和密码"""
<|body_0|>
def create(self, validated_data):
"""重新增加一个jwt"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AuthorizationSerializer:
"""验证序列化器类"""
def validate(self, attrs):
"""自定义验证用户名和密码"""
username = attrs['username']
password = attrs['password']
try:
user = User.objects.get(username=username, is_staff=True)
except User.DoesNotExit:
raise seria... | the_stack_v2_python_sparse | meiduo_mall/meiduo_mall/apps/meiduo_admin/serializers/users.py | qls7/dianshanghoutai | train | 0 |
53e6f621be4a62d35f4dbc3298cbb5842d8bf325 | [
"super(PdCateInput, self).__init__(parent=parent)\nself.mainEngine = mainEngine\nself.eventEngine = eventEngine\nself.initUi()",
"self.setWindowTitle('输入协存项目')\nself.setMinimumSize(500, 200)\nself.setFont(BASIC_FONT)\nself.initInput()",
"pd_project_name_Label = QLabel('协存项目名称')\npd_project_rate_Label = QLabel('... | <|body_start_0|>
super(PdCateInput, self).__init__(parent=parent)
self.mainEngine = mainEngine
self.eventEngine = eventEngine
self.initUi()
<|end_body_0|>
<|body_start_1|>
self.setWindowTitle('输入协存项目')
self.setMinimumSize(500, 200)
self.setFont(BASIC_FONT)
... | 协存输入 | PdCateInput | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PdCateInput:
"""协存输入"""
def __init__(self, mainEngine, eventEngine=None, parent=None):
"""Constructor"""
<|body_0|>
def initUi(self):
"""初始化界面"""
<|body_1|>
def initInput(self):
"""设置输入框"""
<|body_2|>
def insertDB(self):
... | stack_v2_sparse_classes_10k_train_007761 | 3,686 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, mainEngine, eventEngine=None, parent=None)"
},
{
"docstring": "初始化界面",
"name": "initUi",
"signature": "def initUi(self)"
},
{
"docstring": "设置输入框",
"name": "initInput",
"signature": "def in... | 4 | stack_v2_sparse_classes_30k_train_002156 | Implement the Python class `PdCateInput` described below.
Class description:
协存输入
Method signatures and docstrings:
- def __init__(self, mainEngine, eventEngine=None, parent=None): Constructor
- def initUi(self): 初始化界面
- def initInput(self): 设置输入框
- def insertDB(self): 增加数据 | Implement the Python class `PdCateInput` described below.
Class description:
协存输入
Method signatures and docstrings:
- def __init__(self, mainEngine, eventEngine=None, parent=None): Constructor
- def initUi(self): 初始化界面
- def initInput(self): 设置输入框
- def insertDB(self): 增加数据
<|skeleton|>
class PdCateInput:
"""协存输... | aa0274650a6f16ee52dfac491eb520029d3dd846 | <|skeleton|>
class PdCateInput:
"""协存输入"""
def __init__(self, mainEngine, eventEngine=None, parent=None):
"""Constructor"""
<|body_0|>
def initUi(self):
"""初始化界面"""
<|body_1|>
def initInput(self):
"""设置输入框"""
<|body_2|>
def insertDB(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PdCateInput:
"""协存输入"""
def __init__(self, mainEngine, eventEngine=None, parent=None):
"""Constructor"""
super(PdCateInput, self).__init__(parent=parent)
self.mainEngine = mainEngine
self.eventEngine = eventEngine
self.initUi()
def initUi(self):
"""初始化... | the_stack_v2_python_sparse | view/protocolView/PdCateInput.py | zhnlk/feeCalculate | train | 0 |
784ba2c982c389a3f7ca834225c5691aae21508b | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119. Th... | StorageRegistryServiceServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StorageRegistryServiceServicer:
"""Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this d... | stack_v2_sparse_classes_10k_train_007762 | 5,403 | no_license | [
{
"docstring": "Returns the storage provider that is reponsible for the given resource reference. MUST return CODE_NOT_FOUND if the reference does not exist.",
"name": "GetStorageProvider",
"signature": "def GetStorageProvider(self, request, context)"
},
{
"docstring": "Returns a list of the ava... | 3 | stack_v2_sparse_classes_30k_train_000365 | Implement the Python class `StorageRegistryServiceServicer` described below.
Class description:
Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMM... | Implement the Python class `StorageRegistryServiceServicer` described below.
Class description:
Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMM... | dad1a042b38db5f8bedcac3b6af25066f4d6eef9 | <|skeleton|>
class StorageRegistryServiceServicer:
"""Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StorageRegistryServiceServicer:
"""Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are t... | the_stack_v2_python_sparse | cs3/storageregistry/v0alpha/storageregistry_pb2_grpc.py | SamuAlfageme/python-cs3apis | train | 0 |
e450095e7de6421b5f6d3828ebbdc25a03ee1493 | [
"[teams] = valuelist\nteams = [team.splitlines() for team in re.split('(?:\\r\\n|\\n){2,}', teams.strip())]\nif len(teams) == 1:\n teams = [[trainer] for trainer in teams[0]]\nself.data = teams",
"if not self.data:\n return ''\nelif all((len(team) == 1 for team in self.data)):\n return '\\n'.join((traine... | <|body_start_0|>
[teams] = valuelist
teams = [team.splitlines() for team in re.split('(?:\r\n|\n){2,}', teams.strip())]
if len(teams) == 1:
teams = [[trainer] for trainer in teams[0]]
self.data = teams
<|end_body_0|>
<|body_start_1|>
if not self.data:
ret... | A field for entering trainers who will participate in a battle. | BattleTrainerField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BattleTrainerField:
"""A field for entering trainers who will participate in a battle."""
def process_formdata(self, valuelist):
"""Split the input into lists of names."""
<|body_0|>
def _value(self):
"""Re-join all the lists of names into one string."""
... | stack_v2_sparse_classes_10k_train_007763 | 21,218 | no_license | [
{
"docstring": "Split the input into lists of names.",
"name": "process_formdata",
"signature": "def process_formdata(self, valuelist)"
},
{
"docstring": "Re-join all the lists of names into one string.",
"name": "_value",
"signature": "def _value(self)"
},
{
"docstring": "Do som... | 4 | stack_v2_sparse_classes_30k_train_003651 | Implement the Python class `BattleTrainerField` described below.
Class description:
A field for entering trainers who will participate in a battle.
Method signatures and docstrings:
- def process_formdata(self, valuelist): Split the input into lists of names.
- def _value(self): Re-join all the lists of names into on... | Implement the Python class `BattleTrainerField` described below.
Class description:
A field for entering trainers who will participate in a battle.
Method signatures and docstrings:
- def process_formdata(self, valuelist): Split the input into lists of names.
- def _value(self): Re-join all the lists of names into on... | 872c0b21ed8d45a4c88d51969d3531b8b7913e71 | <|skeleton|>
class BattleTrainerField:
"""A field for entering trainers who will participate in a battle."""
def process_formdata(self, valuelist):
"""Split the input into lists of names."""
<|body_0|>
def _value(self):
"""Re-join all the lists of names into one string."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BattleTrainerField:
"""A field for entering trainers who will participate in a battle."""
def process_formdata(self, valuelist):
"""Split the input into lists of names."""
[teams] = valuelist
teams = [team.splitlines() for team in re.split('(?:\r\n|\n){2,}', teams.strip())]
... | the_stack_v2_python_sparse | asb/views/battle.py | CatTrinket/tcod-asb | train | 1 |
dfc5681b10b8d6eb3b321d6b91ff592ee23f1880 | [
"if amount < 1:\n return 0\nreturn self.coin_change(coins, amount, [0] * (amount + 1))",
"if remainder < 0:\n return -1\n'\\n NOTE: BASE CASE\\n The minimum coins needed to make change for 0 is always 0\\n coins no matter what coins we have.\\n '\nif remainder == 0:\n return 0... | <|body_start_0|>
if amount < 1:
return 0
return self.coin_change(coins, amount, [0] * (amount + 1))
<|end_body_0|>
<|body_start_1|>
if remainder < 0:
return -1
'\n NOTE: BASE CASE\n The minimum coins needed to make change for 0 is always 0\n ... | TopDownSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopDownSolution:
def leastCoins(self, coins, amount):
"""Interface ---- :type coins: list of int :type amount: int :rtype: int Approach ---- 1. We use a recursive approach 2. At each stack frame we consider what choices do we have to make and how does this get us to our goal 3. What are ... | stack_v2_sparse_classes_10k_train_007764 | 5,135 | no_license | [
{
"docstring": "Interface ---- :type coins: list of int :type amount: int :rtype: int Approach ---- 1. We use a recursive approach 2. At each stack frame we consider what choices do we have to make and how does this get us to our goal 3. What are the base cases? - When the remainder is less then 0 - When the re... | 2 | null | Implement the Python class `TopDownSolution` described below.
Class description:
Implement the TopDownSolution class.
Method signatures and docstrings:
- def leastCoins(self, coins, amount): Interface ---- :type coins: list of int :type amount: int :rtype: int Approach ---- 1. We use a recursive approach 2. At each s... | Implement the Python class `TopDownSolution` described below.
Class description:
Implement the TopDownSolution class.
Method signatures and docstrings:
- def leastCoins(self, coins, amount): Interface ---- :type coins: list of int :type amount: int :rtype: int Approach ---- 1. We use a recursive approach 2. At each s... | c0d49423885832b616ae3c7cd58e8f24c17cfd4d | <|skeleton|>
class TopDownSolution:
def leastCoins(self, coins, amount):
"""Interface ---- :type coins: list of int :type amount: int :rtype: int Approach ---- 1. We use a recursive approach 2. At each stack frame we consider what choices do we have to make and how does this get us to our goal 3. What are ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TopDownSolution:
def leastCoins(self, coins, amount):
"""Interface ---- :type coins: list of int :type amount: int :rtype: int Approach ---- 1. We use a recursive approach 2. At each stack frame we consider what choices do we have to make and how does this get us to our goal 3. What are the base cases... | the_stack_v2_python_sparse | dynamicProgramming/min_coins_make_change.py | miaviles/Data-Structures-Algorithms-Python | train | 0 | |
ad5481e9b26a8ea9f9d56a19ed369ce6fad3ce59 | [
"user = request.user\ncheck_user_status(user)\nuser_id = user.id\nvalidate(instance=request.data, schema=schemas.food_insert_edit_schema)\nbody = request.data\nPendingFood.field_validate(body)\nrestaurant = PendingRestaurant.get_by_owner(user_id)\ndish = PendingFood.edit_dish(dish_id, body, restaurant._id)\nreturn ... | <|body_start_0|>
user = request.user
check_user_status(user)
user_id = user.id
validate(instance=request.data, schema=schemas.food_insert_edit_schema)
body = request.data
PendingFood.field_validate(body)
restaurant = PendingRestaurant.get_by_owner(user_id)
... | PendingDish view for updating or deleting | PendingDishModifyDeleteView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PendingDishModifyDeleteView:
"""PendingDish view for updating or deleting"""
def put(self, request, dish_id):
"""Updates dish data"""
<|body_0|>
def delete(self, request, dish_id):
"""Deletes dish from database"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_10k_train_007765 | 19,356 | no_license | [
{
"docstring": "Updates dish data",
"name": "put",
"signature": "def put(self, request, dish_id)"
},
{
"docstring": "Deletes dish from database",
"name": "delete",
"signature": "def delete(self, request, dish_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003026 | Implement the Python class `PendingDishModifyDeleteView` described below.
Class description:
PendingDish view for updating or deleting
Method signatures and docstrings:
- def put(self, request, dish_id): Updates dish data
- def delete(self, request, dish_id): Deletes dish from database | Implement the Python class `PendingDishModifyDeleteView` described below.
Class description:
PendingDish view for updating or deleting
Method signatures and docstrings:
- def put(self, request, dish_id): Updates dish data
- def delete(self, request, dish_id): Deletes dish from database
<|skeleton|>
class PendingDish... | 2707062c9a9a8bb4baca955e8a60ba08cc9f8953 | <|skeleton|>
class PendingDishModifyDeleteView:
"""PendingDish view for updating or deleting"""
def put(self, request, dish_id):
"""Updates dish data"""
<|body_0|>
def delete(self, request, dish_id):
"""Deletes dish from database"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PendingDishModifyDeleteView:
"""PendingDish view for updating or deleting"""
def put(self, request, dish_id):
"""Updates dish data"""
user = request.user
check_user_status(user)
user_id = user.id
validate(instance=request.data, schema=schemas.food_insert_edit_schem... | the_stack_v2_python_sparse | backend/restaurant/views.py | MochiTarts/Find-Dining-The-Bridge | train | 1 |
c1dc2f0df073027de820071920a43badb81bb84d | [
"super().__init__(dynamic=True, **kwargs)\nself.max_edge = maximum_edge_length\nself.dimensions = homology_dimensions\nself.min_persistence = min_persistence if min_persistence is not None else [0.0 for _ in range(len(self.dimensions))]\nself.hcf = homology_coeff_field\nassert len(self.min_persistence) == len(self.... | <|body_start_0|>
super().__init__(dynamic=True, **kwargs)
self.max_edge = maximum_edge_length
self.dimensions = homology_dimensions
self.min_persistence = min_persistence if min_persistence is not None else [0.0 for _ in range(len(self.dimensions))]
self.hcf = homology_coeff_fiel... | TensorFlow layer for computing Rips persistence out of a point cloud | RipsLayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RipsLayer:
"""TensorFlow layer for computing Rips persistence out of a point cloud"""
def __init__(self, homology_dimensions, maximum_edge_length=np.inf, min_persistence=None, homology_coeff_field=11, **kwargs):
"""Constructor for the RipsLayer class Parameters: maximum_edge_length (... | stack_v2_sparse_classes_10k_train_007766 | 4,886 | permissive | [
{
"docstring": "Constructor for the RipsLayer class Parameters: maximum_edge_length (float): maximum edge length for the Rips complex homology_dimensions (List[int]): list of homology dimensions min_persistence (List[float]): minimum distance-to-diagonal of the points in the output persistence diagrams (default... | 2 | stack_v2_sparse_classes_30k_train_003124 | Implement the Python class `RipsLayer` described below.
Class description:
TensorFlow layer for computing Rips persistence out of a point cloud
Method signatures and docstrings:
- def __init__(self, homology_dimensions, maximum_edge_length=np.inf, min_persistence=None, homology_coeff_field=11, **kwargs): Constructor ... | Implement the Python class `RipsLayer` described below.
Class description:
TensorFlow layer for computing Rips persistence out of a point cloud
Method signatures and docstrings:
- def __init__(self, homology_dimensions, maximum_edge_length=np.inf, min_persistence=None, homology_coeff_field=11, **kwargs): Constructor ... | 2f76d9416e145282adcd8264438480008bd59f77 | <|skeleton|>
class RipsLayer:
"""TensorFlow layer for computing Rips persistence out of a point cloud"""
def __init__(self, homology_dimensions, maximum_edge_length=np.inf, min_persistence=None, homology_coeff_field=11, **kwargs):
"""Constructor for the RipsLayer class Parameters: maximum_edge_length (... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RipsLayer:
"""TensorFlow layer for computing Rips persistence out of a point cloud"""
def __init__(self, homology_dimensions, maximum_edge_length=np.inf, min_persistence=None, homology_coeff_field=11, **kwargs):
"""Constructor for the RipsLayer class Parameters: maximum_edge_length (float): maxim... | the_stack_v2_python_sparse | src/python/gudhi/tensorflow/rips_layer.py | GUDHI/gudhi-devel | train | 212 |
f1fee2d533d9cfda0b03ba19ff00cf989b7c1732 | [
"if not prices:\n return 0\nmax_profit, min_price = (0, prices[0])\nfor i in range(1, len(prices)):\n if prices[i] < min_price:\n min_price = prices[i]\n else:\n max_profit = max(max_profit, prices[i] - min_price)\nreturn max_profit",
"max_profit, max_curr = (0, 0)\nfor i in range(1, len(pr... | <|body_start_0|>
if not prices:
return 0
max_profit, min_price = (0, prices[0])
for i in range(1, len(prices)):
if prices[i] < min_price:
min_price = prices[i]
else:
max_profit = max(max_profit, prices[i] - min_price)
re... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit_MK1(self, prices: List[int]) -> int:
"""Solution.md Approach 2: One pass Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def maxProfit_MK2(self, prices: List[int]) -> int:
"""My solution. Time complexity: O(n). Space complexity: O(1... | stack_v2_sparse_classes_10k_train_007767 | 1,295 | no_license | [
{
"docstring": "Solution.md Approach 2: One pass Time complexity: O(n) Space complexity: O(1)",
"name": "maxProfit_MK1",
"signature": "def maxProfit_MK1(self, prices: List[int]) -> int"
},
{
"docstring": "My solution. Time complexity: O(n). Space complexity: O(1). Calculate the difference array ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit_MK1(self, prices: List[int]) -> int: Solution.md Approach 2: One pass Time complexity: O(n) Space complexity: O(1)
- def maxProfit_MK2(self, prices: List[int]) -> i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit_MK1(self, prices: List[int]) -> int: Solution.md Approach 2: One pass Time complexity: O(n) Space complexity: O(1)
- def maxProfit_MK2(self, prices: List[int]) -> i... | d7ba416d22becfa8f2a2ae4eee04c86617cd9332 | <|skeleton|>
class Solution:
def maxProfit_MK1(self, prices: List[int]) -> int:
"""Solution.md Approach 2: One pass Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def maxProfit_MK2(self, prices: List[int]) -> int:
"""My solution. Time complexity: O(n). Space complexity: O(1... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit_MK1(self, prices: List[int]) -> int:
"""Solution.md Approach 2: One pass Time complexity: O(n) Space complexity: O(1)"""
if not prices:
return 0
max_profit, min_price = (0, prices[0])
for i in range(1, len(prices)):
if prices[i] <... | the_stack_v2_python_sparse | 0121. Best Time to Buy and Sell Stock/Solution.py | faterazer/LeetCode | train | 4 | |
681706c9b63dfeea3a60d738a3f91124a7691063 | [
"super().__init__(**kwargs)\nself._model_directory = self._options['model_directory']\nself._half_precision_model = self._options.get('half_precision_model', False)\nself._model = BertModel.from_pretrained(self._model_directory)\nif self._half_precision_model:\n self._model = self._model.half()\nself._model = se... | <|body_start_0|>
super().__init__(**kwargs)
self._model_directory = self._options['model_directory']
self._half_precision_model = self._options.get('half_precision_model', False)
self._model = BertModel.from_pretrained(self._model_directory)
if self._half_precision_model:
... | ProtTrans-Bert-BFD Embedder (ProtBert-BFD) Elnaggar, Ahmed, et al. "ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing." arXiv preprint arXiv:2007.06225 (2020). https://arxiv.org/abs/2007.06225 | ProtTransBertBFDEmbedder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtTransBertBFDEmbedder:
"""ProtTrans-Bert-BFD Embedder (ProtBert-BFD) Elnaggar, Ahmed, et al. "ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing." arXiv preprint arXiv:2007.06225 (2020). https://arxiv.org/abs/2007.06225"... | stack_v2_sparse_classes_10k_train_007768 | 1,793 | permissive | [
{
"docstring": "Initialize Bert embedder. :param model_directory: :param half_precision_model:",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Returns the CPU model",
"name": "_get_fallback_model",
"signature": "def _get_fallback_model(self) -> BertMo... | 2 | stack_v2_sparse_classes_30k_train_003039 | Implement the Python class `ProtTransBertBFDEmbedder` described below.
Class description:
ProtTrans-Bert-BFD Embedder (ProtBert-BFD) Elnaggar, Ahmed, et al. "ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing." arXiv preprint arXiv:2007.06225 (2... | Implement the Python class `ProtTransBertBFDEmbedder` described below.
Class description:
ProtTrans-Bert-BFD Embedder (ProtBert-BFD) Elnaggar, Ahmed, et al. "ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing." arXiv preprint arXiv:2007.06225 (2... | efb9801f0de9b9d51d19b741088763a7d2d0c3a2 | <|skeleton|>
class ProtTransBertBFDEmbedder:
"""ProtTrans-Bert-BFD Embedder (ProtBert-BFD) Elnaggar, Ahmed, et al. "ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing." arXiv preprint arXiv:2007.06225 (2020). https://arxiv.org/abs/2007.06225"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProtTransBertBFDEmbedder:
"""ProtTrans-Bert-BFD Embedder (ProtBert-BFD) Elnaggar, Ahmed, et al. "ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing." arXiv preprint arXiv:2007.06225 (2020). https://arxiv.org/abs/2007.06225"""
def _... | the_stack_v2_python_sparse | bio_embeddings/embed/prottrans_bert_bfd_embedder.py | sacdallago/bio_embeddings | train | 383 |
538c0e52ddba115234f80f951a8bc2548f169540 | [
"super(NewlineSentenceSplitter, self).__init__(**kwargs)\nif 'create_empty' in kwargs:\n self.create_empty = True\nelse:\n self.create_empty = False\nif kwargs.get('use_universal_newline', 'true').lower() == 'true':\n self.use_universal_newline = True\nelse:\n self.use_universal_newline = False",
"add... | <|body_start_0|>
super(NewlineSentenceSplitter, self).__init__(**kwargs)
if 'create_empty' in kwargs:
self.create_empty = True
else:
self.create_empty = False
if kwargs.get('use_universal_newline', 'true').lower() == 'true':
self.use_universal_newline ... | This should be used when each sentence is on a separate line of document -- useful for converting pre-tokenized corpora to serifxml via pipeline | NewlineSentenceSplitter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewlineSentenceSplitter:
"""This should be used when each sentence is on a separate line of document -- useful for converting pre-tokenized corpora to serifxml via pipeline"""
def __init__(self, **kwargs):
""":param kwargs: create_empty: This is very useful if you want to strictly as... | stack_v2_sparse_classes_10k_train_007769 | 2,412 | permissive | [
{
"docstring": ":param kwargs: create_empty: This is very useful if you want to strictly assume number of sentences matches with your input for alignment purpose. When specified, it will create empty sentence as place holders for empty lines. Usage: ``` SENTENCE_SPLITTING_MODEL NewlineSentenceSplitter create_em... | 2 | null | Implement the Python class `NewlineSentenceSplitter` described below.
Class description:
This should be used when each sentence is on a separate line of document -- useful for converting pre-tokenized corpora to serifxml via pipeline
Method signatures and docstrings:
- def __init__(self, **kwargs): :param kwargs: cre... | Implement the Python class `NewlineSentenceSplitter` described below.
Class description:
This should be used when each sentence is on a separate line of document -- useful for converting pre-tokenized corpora to serifxml via pipeline
Method signatures and docstrings:
- def __init__(self, **kwargs): :param kwargs: cre... | b486a66339a330e94d81850e6acb3a7e34df746e | <|skeleton|>
class NewlineSentenceSplitter:
"""This should be used when each sentence is on a separate line of document -- useful for converting pre-tokenized corpora to serifxml via pipeline"""
def __init__(self, **kwargs):
""":param kwargs: create_empty: This is very useful if you want to strictly as... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NewlineSentenceSplitter:
"""This should be used when each sentence is on a separate line of document -- useful for converting pre-tokenized corpora to serifxml via pipeline"""
def __init__(self, **kwargs):
""":param kwargs: create_empty: This is very useful if you want to strictly assume number o... | the_stack_v2_python_sparse | src/python/serif/model/impl/sentence_splitter/newline_sentence_splitter.py | BBN-E/text-open | train | 2 |
2a0f4c5cb475a8861c8564158531d8a211415176 | [
"paginator = client.get_paginator('describe_load_balancers')\nload_balancers = {}\nfor resp in paginator.paginate():\n for lb in resp.get('LoadBalancers', []):\n resource_arn = lb['LoadBalancerArn']\n try:\n lb_attrs = cls.get_lb_attrs(client, resource_arn)\n lb.update(lb_attr... | <|body_start_0|>
paginator = client.get_paginator('describe_load_balancers')
load_balancers = {}
for resp in paginator.paginate():
for lb in resp.get('LoadBalancers', []):
resource_arn = lb['LoadBalancerArn']
try:
lb_attrs = cls.get... | Resource for load balancer | LoadBalancerResourceSpec | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoadBalancerResourceSpec:
"""Resource for load balancer"""
def list_from_aws(cls: Type['LoadBalancerResourceSpec'], client: BaseClient, account_id: str, region: str) -> ListFromAWSResult:
"""Return a dict of dicts of the format: {'lb_1_arn': {lb_1_dict}, 'lb_2_arn': {lb_2_dict}, ...}... | stack_v2_sparse_classes_10k_train_007770 | 4,379 | permissive | [
{
"docstring": "Return a dict of dicts of the format: {'lb_1_arn': {lb_1_dict}, 'lb_2_arn': {lb_2_dict}, ...} Where the dicts represent results from describe_load_balancers.",
"name": "list_from_aws",
"signature": "def list_from_aws(cls: Type['LoadBalancerResourceSpec'], client: BaseClient, account_id: ... | 2 | stack_v2_sparse_classes_30k_train_003174 | Implement the Python class `LoadBalancerResourceSpec` described below.
Class description:
Resource for load balancer
Method signatures and docstrings:
- def list_from_aws(cls: Type['LoadBalancerResourceSpec'], client: BaseClient, account_id: str, region: str) -> ListFromAWSResult: Return a dict of dicts of the format... | Implement the Python class `LoadBalancerResourceSpec` described below.
Class description:
Resource for load balancer
Method signatures and docstrings:
- def list_from_aws(cls: Type['LoadBalancerResourceSpec'], client: BaseClient, account_id: str, region: str) -> ListFromAWSResult: Return a dict of dicts of the format... | eb7d5d18f3d177973c4105c21be9d251250ca8d6 | <|skeleton|>
class LoadBalancerResourceSpec:
"""Resource for load balancer"""
def list_from_aws(cls: Type['LoadBalancerResourceSpec'], client: BaseClient, account_id: str, region: str) -> ListFromAWSResult:
"""Return a dict of dicts of the format: {'lb_1_arn': {lb_1_dict}, 'lb_2_arn': {lb_2_dict}, ...}... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LoadBalancerResourceSpec:
"""Resource for load balancer"""
def list_from_aws(cls: Type['LoadBalancerResourceSpec'], client: BaseClient, account_id: str, region: str) -> ListFromAWSResult:
"""Return a dict of dicts of the format: {'lb_1_arn': {lb_1_dict}, 'lb_2_arn': {lb_2_dict}, ...} Where the di... | the_stack_v2_python_sparse | altimeter/aws/resource/elbv2/load_balancer.py | tableau/altimeter | train | 75 |
2b5718603423712bade7ba9528f3b40731036501 | [
"acting_user = UserFactory.create()\norder = OrderFactory.create()\noriginal_before_json = serialize_model_object(order)\noriginal_before_json['lines'] = []\nassert OrderAudit.objects.count() == 0\norder.save_and_log(acting_user)\nassert OrderAudit.objects.count() == 1\noriginal_after_json = serialize_model_object(... | <|body_start_0|>
acting_user = UserFactory.create()
order = OrderFactory.create()
original_before_json = serialize_model_object(order)
original_before_json['lines'] = []
assert OrderAudit.objects.count() == 0
order.save_and_log(acting_user)
assert OrderAudit.objec... | Tests for abstract models | ModelsTests | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelsTests:
"""Tests for abstract models"""
def test_save_and_log(self):
"""Tests that save_and_log() creates an audit record with the correct information."""
<|body_0|>
def test_to_dict(self):
"""assert output of to_dict"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_10k_train_007771 | 2,214 | permissive | [
{
"docstring": "Tests that save_and_log() creates an audit record with the correct information.",
"name": "test_save_and_log",
"signature": "def test_save_and_log(self)"
},
{
"docstring": "assert output of to_dict",
"name": "test_to_dict",
"signature": "def test_to_dict(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004457 | Implement the Python class `ModelsTests` described below.
Class description:
Tests for abstract models
Method signatures and docstrings:
- def test_save_and_log(self): Tests that save_and_log() creates an audit record with the correct information.
- def test_to_dict(self): assert output of to_dict | Implement the Python class `ModelsTests` described below.
Class description:
Tests for abstract models
Method signatures and docstrings:
- def test_save_and_log(self): Tests that save_and_log() creates an audit record with the correct information.
- def test_to_dict(self): assert output of to_dict
<|skeleton|>
class... | 339c67b84b661a37ffe32580da72383d95666c5c | <|skeleton|>
class ModelsTests:
"""Tests for abstract models"""
def test_save_and_log(self):
"""Tests that save_and_log() creates an audit record with the correct information."""
<|body_0|>
def test_to_dict(self):
"""assert output of to_dict"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ModelsTests:
"""Tests for abstract models"""
def test_save_and_log(self):
"""Tests that save_and_log() creates an audit record with the correct information."""
acting_user = UserFactory.create()
order = OrderFactory.create()
original_before_json = serialize_model_object(or... | the_stack_v2_python_sparse | main/models_test.py | mitodl/bootcamp-ecommerce | train | 6 |
5c72bb73dea124923ef1165d8cb06029ae08a7d9 | [
"sleep(2)\ndriver.find_element_by_id('qqLoginTab').click()\nsleep(1)\ndriver.switch_to.frame('login_frame')\nsleep(1)\ndriver.find_element_by_id('switcher_plogin').click()\nsleep(1)\ndriver.find_element_by_name('u').clear()\ndriver.find_element_by_name('u').send_keys(username)\ndriver.find_element_by_name('p').clea... | <|body_start_0|>
sleep(2)
driver.find_element_by_id('qqLoginTab').click()
sleep(1)
driver.switch_to.frame('login_frame')
sleep(1)
driver.find_element_by_id('switcher_plogin').click()
sleep(1)
driver.find_element_by_name('u').clear()
driver.find_ele... | def __int__(self, driver): self.driver = driver | Mail | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mail:
"""def __int__(self, driver): self.driver = driver"""
def login(self, username, password):
"""登录"""
<|body_0|>
def logout(self):
"""退出"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sleep(2)
driver.find_element_by_id('qqLoginTab')... | stack_v2_sparse_classes_10k_train_007772 | 1,085 | no_license | [
{
"docstring": "登录",
"name": "login",
"signature": "def login(self, username, password)"
},
{
"docstring": "退出",
"name": "logout",
"signature": "def logout(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005258 | Implement the Python class `Mail` described below.
Class description:
def __int__(self, driver): self.driver = driver
Method signatures and docstrings:
- def login(self, username, password): 登录
- def logout(self): 退出 | Implement the Python class `Mail` described below.
Class description:
def __int__(self, driver): self.driver = driver
Method signatures and docstrings:
- def login(self, username, password): 登录
- def logout(self): 退出
<|skeleton|>
class Mail:
"""def __int__(self, driver): self.driver = driver"""
def login(se... | e6d51de7fbb08b69e7985a0e9b962cae7def7844 | <|skeleton|>
class Mail:
"""def __int__(self, driver): self.driver = driver"""
def login(self, username, password):
"""登录"""
<|body_0|>
def logout(self):
"""退出"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Mail:
"""def __int__(self, driver): self.driver = driver"""
def login(self, username, password):
"""登录"""
sleep(2)
driver.find_element_by_id('qqLoginTab').click()
sleep(1)
driver.switch_to.frame('login_frame')
sleep(1)
driver.find_element_by_id('swi... | the_stack_v2_python_sparse | selenium_20190727/test_day_02/module.py | wangcaicai-666/PythonDemo | train | 0 |
8bcd795a9f88132501d8b487be49fe075728c5c6 | [
"if not flags.FLAGS.is_parsed():\n flags.FLAGS.mark_as_parsed()\nself.fake_data_dir = os.path.join(platforms_util.get_test_data_dir(), 'fake_tf_record_data')\nself.output_dir = output_dir\nif root_data_dir is None:\n self.data_dir = '/readahead/200M/placer/prod/home/distbelief/imagenet-tensorflow/imagenet-201... | <|body_start_0|>
if not flags.FLAGS.is_parsed():
flags.FLAGS.mark_as_parsed()
self.fake_data_dir = os.path.join(platforms_util.get_test_data_dir(), 'fake_tf_record_data')
self.output_dir = output_dir
if root_data_dir is None:
self.data_dir = '/readahead/200M/place... | Base class for all benchmarks in this file. | BenchmarkBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BenchmarkBase:
"""Base class for all benchmarks in this file."""
def __init__(self, output_dir=None, root_data_dir=None, **kwargs):
"""Base class for all benchmarks in this file. Args: output_dir: directory where to output e.g. log files root_data_dir: directory under which to look f... | stack_v2_sparse_classes_10k_train_007773 | 36,235 | permissive | [
{
"docstring": "Base class for all benchmarks in this file. Args: output_dir: directory where to output e.g. log files root_data_dir: directory under which to look for dataset **kwargs: arbitrary named arguments. This is needed to make the constructor forward compatible in case PerfZero provides more named argu... | 4 | stack_v2_sparse_classes_30k_train_000746 | Implement the Python class `BenchmarkBase` described below.
Class description:
Base class for all benchmarks in this file.
Method signatures and docstrings:
- def __init__(self, output_dir=None, root_data_dir=None, **kwargs): Base class for all benchmarks in this file. Args: output_dir: directory where to output e.g.... | Implement the Python class `BenchmarkBase` described below.
Class description:
Base class for all benchmarks in this file.
Method signatures and docstrings:
- def __init__(self, output_dir=None, root_data_dir=None, **kwargs): Base class for all benchmarks in this file. Args: output_dir: directory where to output e.g.... | c8e97df0d4d3d0c1020b98391c526df12371fc30 | <|skeleton|>
class BenchmarkBase:
"""Base class for all benchmarks in this file."""
def __init__(self, output_dir=None, root_data_dir=None, **kwargs):
"""Base class for all benchmarks in this file. Args: output_dir: directory where to output e.g. log files root_data_dir: directory under which to look f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BenchmarkBase:
"""Base class for all benchmarks in this file."""
def __init__(self, output_dir=None, root_data_dir=None, **kwargs):
"""Base class for all benchmarks in this file. Args: output_dir: directory where to output e.g. log files root_data_dir: directory under which to look for dataset **... | the_stack_v2_python_sparse | scripts/tf_cnn_benchmarks/leading_indicators_test.py | tensorflow/benchmarks | train | 1,182 |
5885c8fa06047d5b38e48bf7e02aaeec5e59840e | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn CalendarGroup()",
"from .calendar import Calendar\nfrom .entity import Entity\nfrom .calendar import Calendar\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'calendars': lambda n: setattr(self, 'calendars', n.... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return CalendarGroup()
<|end_body_0|>
<|body_start_1|>
from .calendar import Calendar
from .entity import Entity
from .calendar import Calendar
from .entity import Entity
... | CalendarGroup | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalendarGroup:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarGroup:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | stack_v2_sparse_classes_10k_train_007774 | 2,971 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: CalendarGroup",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value... | 3 | null | Implement the Python class `CalendarGroup` described below.
Class description:
Implement the CalendarGroup class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarGroup: Creates a new instance of the appropriate class based on discriminator value... | Implement the Python class `CalendarGroup` described below.
Class description:
Implement the CalendarGroup class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarGroup: Creates a new instance of the appropriate class based on discriminator value... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class CalendarGroup:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarGroup:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CalendarGroup:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarGroup:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: CalendarGrou... | the_stack_v2_python_sparse | msgraph/generated/models/calendar_group.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
d0565f83db422e3d3436761b64934a05366ebf17 | [
"value = '<div>'\nclase = 'actions'\nurl_cont = '/roles/'\nperm_mod = PoseePermiso('modificar rol')\nperm_del = PoseePermiso('eliminar rol')\nif perm_mod.is_met(request.environ):\n value += '<div>' + '<a href=\"' + url_cont + str(obj.id_rol) + '/edit' + '\" class=\"' + clase + '\">Modificar</a>' + '</div><br />'... | <|body_start_0|>
value = '<div>'
clase = 'actions'
url_cont = '/roles/'
perm_mod = PoseePermiso('modificar rol')
perm_del = PoseePermiso('eliminar rol')
if perm_mod.is_met(request.environ):
value += '<div>' + '<a href="' + url_cont + str(obj.id_rol) + '/edit' ... | RolTableFiller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RolTableFiller:
def __actions__(self, obj):
"""Links de acciones para un registro dado"""
<|body_0|>
def _do_get_provider_count_and_objs(self, **kw):
"""Se muestra la lista de rol si se tiene un permiso necesario. Caso contrario le muestra sus roles."""
<|bod... | stack_v2_sparse_classes_10k_train_007775 | 31,597 | no_license | [
{
"docstring": "Links de acciones para un registro dado",
"name": "__actions__",
"signature": "def __actions__(self, obj)"
},
{
"docstring": "Se muestra la lista de rol si se tiene un permiso necesario. Caso contrario le muestra sus roles.",
"name": "_do_get_provider_count_and_objs",
"si... | 2 | stack_v2_sparse_classes_30k_train_005415 | Implement the Python class `RolTableFiller` described below.
Class description:
Implement the RolTableFiller class.
Method signatures and docstrings:
- def __actions__(self, obj): Links de acciones para un registro dado
- def _do_get_provider_count_and_objs(self, **kw): Se muestra la lista de rol si se tiene un permi... | Implement the Python class `RolTableFiller` described below.
Class description:
Implement the RolTableFiller class.
Method signatures and docstrings:
- def __actions__(self, obj): Links de acciones para un registro dado
- def _do_get_provider_count_and_objs(self, **kw): Se muestra la lista de rol si se tiene un permi... | 997531e130d1951b483f4a6a67f2df7467cd9fd1 | <|skeleton|>
class RolTableFiller:
def __actions__(self, obj):
"""Links de acciones para un registro dado"""
<|body_0|>
def _do_get_provider_count_and_objs(self, **kw):
"""Se muestra la lista de rol si se tiene un permiso necesario. Caso contrario le muestra sus roles."""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RolTableFiller:
def __actions__(self, obj):
"""Links de acciones para un registro dado"""
value = '<div>'
clase = 'actions'
url_cont = '/roles/'
perm_mod = PoseePermiso('modificar rol')
perm_del = PoseePermiso('eliminar rol')
if perm_mod.is_met(request.e... | the_stack_v2_python_sparse | lpm/controllers/rol.py | jorgeramirez/LPM | train | 1 | |
a314e9d42e749bc9a4413b8e445c96c4ab1a3ace | [
"super(InTimeToArrivalToVehicle, self).__init__(name)\nself.logger.debug('%s.__init__()' % self.__class__.__name__)\nself._other_actor = other_actor\nself._actor = actor\nself._time = time",
"new_status = py_trees.common.Status.RUNNING\ncurrent_location = CarlaDataProvider.get_location(self._actor)\ntarget_locati... | <|body_start_0|>
super(InTimeToArrivalToVehicle, self).__init__(name)
self.logger.debug('%s.__init__()' % self.__class__.__name__)
self._other_actor = other_actor
self._actor = actor
self._time = time
<|end_body_0|>
<|body_start_1|>
new_status = py_trees.common.Status.RU... | This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is less than _time_ in seconds - other_actor: Reference actor used in this behavior The conditi... | InTimeToArrivalToVehicle | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InTimeToArrivalToVehicle:
"""This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is less than _time_ in seconds - other_acto... | stack_v2_sparse_classes_10k_train_007776 | 18,494 | permissive | [
{
"docstring": "Setup parameters",
"name": "__init__",
"signature": "def __init__(self, other_actor, actor, time, name='TimeToArrival')"
},
{
"docstring": "Check if the ego vehicle can arrive at other actor within time",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007330 | Implement the Python class `InTimeToArrivalToVehicle` described below.
Class description:
This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is l... | Implement the Python class `InTimeToArrivalToVehicle` described below.
Class description:
This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is l... | 8ab0894b92e1f994802a218002021ee075c405bf | <|skeleton|>
class InTimeToArrivalToVehicle:
"""This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is less than _time_ in seconds - other_acto... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InTimeToArrivalToVehicle:
"""This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is less than _time_ in seconds - other_actor: Reference ... | the_stack_v2_python_sparse | carla_rllib/carla_rllib-prak_evaluator-carla_rllib-prak_evaluator/carla_rllib/prak_evaluator/srunner/scenarioconfigs/scenariomanager/scenarioatomics/atomic_trigger_conditions.py | TinaMenke/Deep-Reinforcement-Learning | train | 9 |
a41d8b96ccdfb544605222bcef69cd6cb18564cd | [
"for key in params.keys():\n if key not in SequenceType:\n raise ValueError(f'{key} is not a supported SequenceType.')\nself._params = params",
"for key, transforms in self._params.items():\n data[key] = VideoAugmentor.MAP[key](data[key], transforms)\nreturn data"
] | <|body_start_0|>
for key in params.keys():
if key not in SequenceType:
raise ValueError(f'{key} is not a supported SequenceType.')
self._params = params
<|end_body_0|>
<|body_start_1|>
for key, transforms in self._params.items():
data[key] = VideoAugmento... | Data augmentation for videos. Augmentor consistently augments data across the time dimension (i.e. dim 0). In other words, the same transformation is applied to every single frame in a video sequence. Currently, only image frames, i.e. SequenceType.FRAMES in a video can be augmented. | VideoAugmentor | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VideoAugmentor:
"""Data augmentation for videos. Augmentor consistently augments data across the time dimension (i.e. dim 0). In other words, the same transformation is applied to every single frame in a video sequence. Currently, only image frames, i.e. SequenceType.FRAMES in a video can be augm... | stack_v2_sparse_classes_10k_train_007777 | 4,197 | permissive | [
{
"docstring": "Constructor. Args: params: Raises: ValueError: If params contains an unsupported data augmentation.",
"name": "__init__",
"signature": "def __init__(self, params)"
},
{
"docstring": "Iterate and transform the data values. Currently, data augmentation is only applied to video fram... | 2 | null | Implement the Python class `VideoAugmentor` described below.
Class description:
Data augmentation for videos. Augmentor consistently augments data across the time dimension (i.e. dim 0). In other words, the same transformation is applied to every single frame in a video sequence. Currently, only image frames, i.e. Seq... | Implement the Python class `VideoAugmentor` described below.
Class description:
Data augmentation for videos. Augmentor consistently augments data across the time dimension (i.e. dim 0). In other words, the same transformation is applied to every single frame in a video sequence. Currently, only image frames, i.e. Seq... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class VideoAugmentor:
"""Data augmentation for videos. Augmentor consistently augments data across the time dimension (i.e. dim 0). In other words, the same transformation is applied to every single frame in a video sequence. Currently, only image frames, i.e. SequenceType.FRAMES in a video can be augm... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VideoAugmentor:
"""Data augmentation for videos. Augmentor consistently augments data across the time dimension (i.e. dim 0). In other words, the same transformation is applied to every single frame in a video sequence. Currently, only image frames, i.e. SequenceType.FRAMES in a video can be augmented."""
... | the_stack_v2_python_sparse | xirl/xirl/transforms.py | Jimmy-INL/google-research | train | 1 |
2bf9372a29a8401b64bf725faf0bcf6e2811db27 | [
"with open(pkl_path, 'r') as f:\n dd = pickle.load(f)\nself.v_template = tf.Variable(undo_chumpy(dd['v_template']), name='v_template', dtype=dtype, trainable=False)\nself.size = [self.v_template.shape[0].value, 3]\nself.num_betas = dd['shapedirs'].shape[-1]\nshapedir = np.reshape(undo_chumpy(dd['shapedirs']), [-... | <|body_start_0|>
with open(pkl_path, 'r') as f:
dd = pickle.load(f)
self.v_template = tf.Variable(undo_chumpy(dd['v_template']), name='v_template', dtype=dtype, trainable=False)
self.size = [self.v_template.shape[0].value, 3]
self.num_betas = dd['shapedirs'].shape[-1]
... | SMPL | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SMPL:
def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32):
"""pkl_path is the path to a SMPL model"""
<|body_0|>
def __call__(self, beta, theta, get_skin=False, name=None):
"""Obtain SMPL with shape (beta) & pose (theta) inputs. Theta includes the g... | stack_v2_sparse_classes_10k_train_007778 | 5,935 | permissive | [
{
"docstring": "pkl_path is the path to a SMPL model",
"name": "__init__",
"signature": "def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32)"
},
{
"docstring": "Obtain SMPL with shape (beta) & pose (theta) inputs. Theta includes the global rotation. Args: beta: N x 10 theta: N ... | 2 | stack_v2_sparse_classes_30k_train_003857 | Implement the Python class `SMPL` described below.
Class description:
Implement the SMPL class.
Method signatures and docstrings:
- def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32): pkl_path is the path to a SMPL model
- def __call__(self, beta, theta, get_skin=False, name=None): Obtain SMPL with... | Implement the Python class `SMPL` described below.
Class description:
Implement the SMPL class.
Method signatures and docstrings:
- def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32): pkl_path is the path to a SMPL model
- def __call__(self, beta, theta, get_skin=False, name=None): Obtain SMPL with... | 6ff7fc867e9e185d547ada11713a60fbf3caa902 | <|skeleton|>
class SMPL:
def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32):
"""pkl_path is the path to a SMPL model"""
<|body_0|>
def __call__(self, beta, theta, get_skin=False, name=None):
"""Obtain SMPL with shape (beta) & pose (theta) inputs. Theta includes the g... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SMPL:
def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32):
"""pkl_path is the path to a SMPL model"""
with open(pkl_path, 'r') as f:
dd = pickle.load(f)
self.v_template = tf.Variable(undo_chumpy(dd['v_template']), name='v_template', dtype=dtype, trainable=... | the_stack_v2_python_sparse | src/tf_smpl/batch_smpl.py | akanazawa/motion_reconstruction | train | 297 | |
d8c3ec2856565c7c3d6dc5ffdb82bbc44b2bec8f | [
"self.students = []\nself.grades = {}\nself.isSorted = True",
"if student in self.students:\n raise ValueError('Duplicate student')\nself.students.append(student)\nself.grades[student.getNum()] = []\nself.isSorted = False",
"try:\n self.grades[student.getNum()].append(grade)\nexcept KeyError:\n raise V... | <|body_start_0|>
self.students = []
self.grades = {}
self.isSorted = True
<|end_body_0|>
<|body_start_1|>
if student in self.students:
raise ValueError('Duplicate student')
self.students.append(student)
self.grades[student.getNum()] = []
self.isSorted... | A mapping from students to a list of grades | Grades | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Grades:
"""A mapping from students to a list of grades"""
def __init__(self):
"""Creat empty grade book"""
<|body_0|>
def addStudent(self, student):
"""Assumes: student is of type Student Add student to the grade book"""
<|body_1|>
def addGrade(self,... | stack_v2_sparse_classes_10k_train_007779 | 4,596 | no_license | [
{
"docstring": "Creat empty grade book",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Assumes: student is of type Student Add student to the grade book",
"name": "addStudent",
"signature": "def addStudent(self, student)"
},
{
"docstring": "Assumes: gra... | 5 | stack_v2_sparse_classes_30k_train_003256 | Implement the Python class `Grades` described below.
Class description:
A mapping from students to a list of grades
Method signatures and docstrings:
- def __init__(self): Creat empty grade book
- def addStudent(self, student): Assumes: student is of type Student Add student to the grade book
- def addGrade(self, stu... | Implement the Python class `Grades` described below.
Class description:
A mapping from students to a list of grades
Method signatures and docstrings:
- def __init__(self): Creat empty grade book
- def addStudent(self, student): Assumes: student is of type Student Add student to the grade book
- def addGrade(self, stu... | b72144c258d07915936908214ec0a1bcd8a0c56a | <|skeleton|>
class Grades:
"""A mapping from students to a list of grades"""
def __init__(self):
"""Creat empty grade book"""
<|body_0|>
def addStudent(self, student):
"""Assumes: student is of type Student Add student to the grade book"""
<|body_1|>
def addGrade(self,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Grades:
"""A mapping from students to a list of grades"""
def __init__(self):
"""Creat empty grade book"""
self.students = []
self.grades = {}
self.isSorted = True
def addStudent(self, student):
"""Assumes: student is of type Student Add student to the grade b... | the_stack_v2_python_sparse | class_inheritance.py | aduxhi/learnpython | train | 0 |
446f93db141f6f425732417fb84e211bbd69465d | [
"super().__init__()\nself.mha1 = MultiHeadAttention(dm, h)\nself.mha2 = MultiHeadAttention(dm, h)\nself.ffn = point_wise_feed_forward_network(dm, hidden)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernorm2 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernorm3 = tf.ke... | <|body_start_0|>
super().__init__()
self.mha1 = MultiHeadAttention(dm, h)
self.mha2 = MultiHeadAttention(dm, h)
self.ffn = point_wise_feed_forward_network(dm, hidden)
self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)
self.layernorm2 = tf.keras.layers.Lay... | class DecoderBlock | DecoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderBlock:
"""class DecoderBlock"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public ins... | stack_v2_sparse_classes_10k_train_007780 | 18,002 | no_license | [
{
"docstring": "* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public instance attributes: * mha1 - the first MultiHeadAttention layer * mha2 - the second MultiHeadAttention lay... | 2 | stack_v2_sparse_classes_30k_train_006429 | Implement the Python class `DecoderBlock` described below.
Class description:
class DecoderBlock
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): * dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * d... | Implement the Python class `DecoderBlock` described below.
Class description:
class DecoderBlock
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): * dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * d... | 8ad4c2594ff78b345dbd92e9d54d2a143ac4071a | <|skeleton|>
class DecoderBlock:
"""class DecoderBlock"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public ins... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DecoderBlock:
"""class DecoderBlock"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public instance attribu... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/5-transformer.py | jorgezafra94/holbertonschool-machine_learning | train | 1 |
a6fe174c99fcd417755167f97fcddc8b3f87413e | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn DirectoryRole()",
"from .directory_object import DirectoryObject\nfrom .scoped_role_membership import ScopedRoleMembership\nfrom .directory_object import DirectoryObject\nfrom .scoped_role_membership import ScopedRoleMembership\nfields... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return DirectoryRole()
<|end_body_0|>
<|body_start_1|>
from .directory_object import DirectoryObject
from .scoped_role_membership import ScopedRoleMembership
from .directory_object impo... | DirectoryRole | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirectoryRole:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DirectoryRole:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | stack_v2_sparse_classes_10k_train_007781 | 3,845 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: DirectoryRole",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value... | 3 | null | Implement the Python class `DirectoryRole` described below.
Class description:
Implement the DirectoryRole class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DirectoryRole: Creates a new instance of the appropriate class based on discriminator value... | Implement the Python class `DirectoryRole` described below.
Class description:
Implement the DirectoryRole class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DirectoryRole: Creates a new instance of the appropriate class based on discriminator value... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class DirectoryRole:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DirectoryRole:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DirectoryRole:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DirectoryRole:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: DirectoryRol... | the_stack_v2_python_sparse | msgraph/generated/models/directory_role.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
06bdb34f3ffc77a71db13eed330ae21a129c0a1f | [
"self.body_spec = body_spec\nself.nn_spec = nn_spec\nself.body_decoder = BodyDecoder(body_spec)\nself.brain_decoder = NeuralNetworkDecoder(nn_spec, body_spec)",
"obj = yaml.load(stream)\nrobot = Robot()\nrobot.id = obj.get('id', 0)\nrobot.body.CopyFrom(self.body_decoder.decode(obj))\nrobot.brain.CopyFrom(self.bra... | <|body_start_0|>
self.body_spec = body_spec
self.nn_spec = nn_spec
self.body_decoder = BodyDecoder(body_spec)
self.brain_decoder = NeuralNetworkDecoder(nn_spec, body_spec)
<|end_body_0|>
<|body_start_1|>
obj = yaml.load(stream)
robot = Robot()
robot.id = obj.get(... | Sample converter creates a Robot protobuf message from a YAML stream and a body / neural net spec. | YamlToRobot | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YamlToRobot:
"""Sample converter creates a Robot protobuf message from a YAML stream and a body / neural net spec."""
def __init__(self, body_spec, nn_spec):
""":param body_spec: :type body_spec: BodyImplementation :param nn_spec: :type nn_spec: NeuralNetImplementation"""
<|b... | stack_v2_sparse_classes_10k_train_007782 | 3,202 | permissive | [
{
"docstring": ":param body_spec: :type body_spec: BodyImplementation :param nn_spec: :type nn_spec: NeuralNetImplementation",
"name": "__init__",
"signature": "def __init__(self, body_spec, nn_spec)"
},
{
"docstring": "Returns a protobuf `Robot` for the given stream. :param stream: :type stream... | 2 | stack_v2_sparse_classes_30k_train_000946 | Implement the Python class `YamlToRobot` described below.
Class description:
Sample converter creates a Robot protobuf message from a YAML stream and a body / neural net spec.
Method signatures and docstrings:
- def __init__(self, body_spec, nn_spec): :param body_spec: :type body_spec: BodyImplementation :param nn_sp... | Implement the Python class `YamlToRobot` described below.
Class description:
Sample converter creates a Robot protobuf message from a YAML stream and a body / neural net spec.
Method signatures and docstrings:
- def __init__(self, body_spec, nn_spec): :param body_spec: :type body_spec: BodyImplementation :param nn_sp... | 70e65320a28fe04e121145b2cdde289d3052728a | <|skeleton|>
class YamlToRobot:
"""Sample converter creates a Robot protobuf message from a YAML stream and a body / neural net spec."""
def __init__(self, body_spec, nn_spec):
""":param body_spec: :type body_spec: BodyImplementation :param nn_spec: :type nn_spec: NeuralNetImplementation"""
<|b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class YamlToRobot:
"""Sample converter creates a Robot protobuf message from a YAML stream and a body / neural net spec."""
def __init__(self, body_spec, nn_spec):
""":param body_spec: :type body_spec: BodyImplementation :param nn_spec: :type nn_spec: NeuralNetImplementation"""
self.body_spec =... | the_stack_v2_python_sparse | revolve/convert/yaml.py | ElteHupkes/revolve | train | 0 |
894afbec7420c31c65df42d3e367218c3ff39e16 | [
"self._momentum = momentum\nself._epsilon = epsilon\nself._trainable = trainable\nself._use_sync_bn = use_sync_bn\nif activation == 'relu':\n self._activation = tf.nn.relu\nelif activation == 'swish':\n self._activation = tf.nn.swish\nelse:\n raise ValueError('Activation {} not implemented.'.format(activat... | <|body_start_0|>
self._momentum = momentum
self._epsilon = epsilon
self._trainable = trainable
self._use_sync_bn = use_sync_bn
if activation == 'relu':
self._activation = tf.nn.relu
elif activation == 'swish':
self._activation = tf.nn.swish
... | Combined Batch Normalization and ReLU layers. | BatchNormActivation | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatchNormActivation:
"""Combined Batch Normalization and ReLU layers."""
def __init__(self, momentum=0.997, epsilon=0.0001, trainable=True, use_sync_bn=False, activation='relu'):
"""A class to construct layers for a batch normalization followed by a ReLU. Args: momentum: momentum for... | stack_v2_sparse_classes_10k_train_007783 | 26,918 | permissive | [
{
"docstring": "A class to construct layers for a batch normalization followed by a ReLU. Args: momentum: momentum for the moving average. epsilon: small float added to variance to avoid dividing by zero. trainable: `boolean`, if True also add variables to the graph collection GraphKeys.TRAINABLE_VARIABLES. If ... | 2 | null | Implement the Python class `BatchNormActivation` described below.
Class description:
Combined Batch Normalization and ReLU layers.
Method signatures and docstrings:
- def __init__(self, momentum=0.997, epsilon=0.0001, trainable=True, use_sync_bn=False, activation='relu'): A class to construct layers for a batch norma... | Implement the Python class `BatchNormActivation` described below.
Class description:
Combined Batch Normalization and ReLU layers.
Method signatures and docstrings:
- def __init__(self, momentum=0.997, epsilon=0.0001, trainable=True, use_sync_bn=False, activation='relu'): A class to construct layers for a batch norma... | 0f7adb97a93ec3e3485c261d030c507eb16b33e4 | <|skeleton|>
class BatchNormActivation:
"""Combined Batch Normalization and ReLU layers."""
def __init__(self, momentum=0.997, epsilon=0.0001, trainable=True, use_sync_bn=False, activation='relu'):
"""A class to construct layers for a batch normalization followed by a ReLU. Args: momentum: momentum for... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BatchNormActivation:
"""Combined Batch Normalization and ReLU layers."""
def __init__(self, momentum=0.997, epsilon=0.0001, trainable=True, use_sync_bn=False, activation='relu'):
"""A class to construct layers for a batch normalization followed by a ReLU. Args: momentum: momentum for the moving a... | the_stack_v2_python_sparse | models/official/detection/modeling/architecture/nn_ops.py | tensorflow/tpu | train | 5,627 |
363cfab6a7232de52da4615c8fe4e4366b11c20d | [
"if model is not None:\n try:\n return (get_framework_by_class_name(model=model), {})\n except mlrun.errors.MLRunInvalidArgumentError:\n return (get_framework_by_instance(model=model), {})\nif model_path is not None:\n model_file, model_artifact, extra_data = get_model(model_path)\n if mod... | <|body_start_0|>
if model is not None:
try:
return (get_framework_by_class_name(model=model), {})
except mlrun.errors.MLRunInvalidArgumentError:
return (get_framework_by_instance(model=model), {})
if model_path is not None:
model_file, ... | A library of automatic functions for managing models using MLRun's frameworks package. | AutoMLRun | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoMLRun:
"""A library of automatic functions for managing models using MLRun's frameworks package."""
def _get_framework(model: CommonTypes.ModelType=None, model_path: str=None) -> Union[Tuple[str, dict]]:
"""Try to get the framework from the model or model path provided. The frame... | stack_v2_sparse_classes_10k_train_007784 | 24,099 | permissive | [
{
"docstring": "Try to get the framework from the model or model path provided. The framework can be read from the model path only if the model path is of a logged model artifact (store object uri). :param model: The model instance to get its framework. :param model_path: The store object uri of a model artifac... | 3 | null | Implement the Python class `AutoMLRun` described below.
Class description:
A library of automatic functions for managing models using MLRun's frameworks package.
Method signatures and docstrings:
- def _get_framework(model: CommonTypes.ModelType=None, model_path: str=None) -> Union[Tuple[str, dict]]: Try to get the f... | Implement the Python class `AutoMLRun` described below.
Class description:
A library of automatic functions for managing models using MLRun's frameworks package.
Method signatures and docstrings:
- def _get_framework(model: CommonTypes.ModelType=None, model_path: str=None) -> Union[Tuple[str, dict]]: Try to get the f... | b5fe0c05ae7f5818a4a5a5a40245c851ff9b2c77 | <|skeleton|>
class AutoMLRun:
"""A library of automatic functions for managing models using MLRun's frameworks package."""
def _get_framework(model: CommonTypes.ModelType=None, model_path: str=None) -> Union[Tuple[str, dict]]:
"""Try to get the framework from the model or model path provided. The frame... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AutoMLRun:
"""A library of automatic functions for managing models using MLRun's frameworks package."""
def _get_framework(model: CommonTypes.ModelType=None, model_path: str=None) -> Union[Tuple[str, dict]]:
"""Try to get the framework from the model or model path provided. The framework can be r... | the_stack_v2_python_sparse | mlrun/frameworks/auto_mlrun/auto_mlrun.py | mlrun/mlrun | train | 1,093 |
3077088e5e3a6ce5ab65a0e1aaa97dc97975f27a | [
"super(TwoLayerNet, self).__init__()\nself.linear1 = torch.nn.Linear(D_in, H)\nself.linear2 = torch.nn.Linear(H, D_out)",
"h_relu = self.linear1(x).clamp(min=0)\ny_pred = self.linear2(h_relu)\nreturn y_pred"
] | <|body_start_0|>
super(TwoLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
<|end_body_0|>
<|body_start_1|>
h_relu = self.linear1(x).clamp(min=0)
y_pred = self.linear2(h_relu)
return y_pred
<|end_body_1|>
| TwoLayerNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。"""
<|body_0|>
def forward(self, x):
"""在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_10k_train_007785 | 16,194 | no_license | [
{
"docstring": "在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。",
"name": "__init__",
"signature": "def __init__(self, D_in, H, D_out)"
},
{
"docstring": "在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000671 | Implement the Python class `TwoLayerNet` described below.
Class description:
Implement the TwoLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。
- def forward(self, x): 在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。 | Implement the Python class `TwoLayerNet` described below.
Class description:
Implement the TwoLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。
- def forward(self, x): 在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。
<|... | 272e0b674f2d8ebdca9eea0a35909d2c420212ae | <|skeleton|>
class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。"""
<|body_0|>
def forward(self, x):
"""在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。"""
super(TwoLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
def forward(self, x):
"""在前向传播的函数中，我们接收一个输入的张量，也必须返回一个... | the_stack_v2_python_sparse | PyTorch/quick_start_2/function_try.py | StarkTan/Python | train | 0 | |
c71644522a117565d1d18ffb59609d832583402f | [
"paddle.set_device('cpu')\n[batch_size, d_model, n_head, dim_feedforward, dropout, _, _, source_length, target_length] = generate_basic_params(mode='decoder_layer')\ntgt = np.random.rand(batch_size, target_length, d_model).astype('float32')\nmemory = np.random.rand(batch_size, source_length, d_model).astype('float3... | <|body_start_0|>
paddle.set_device('cpu')
[batch_size, d_model, n_head, dim_feedforward, dropout, _, _, source_length, target_length] = generate_basic_params(mode='decoder_layer')
tgt = np.random.rand(batch_size, target_length, d_model).astype('float32')
memory = np.random.rand(batch_siz... | test | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
"""test"""
def test_decoder(self):
"""test_decoder"""
<|body_0|>
def test(self):
"""test"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
paddle.set_device('cpu')
[batch_size, d_model, n_head, dim_feedforward, dropout, _, _, source_... | stack_v2_sparse_classes_10k_train_007786 | 3,236 | no_license | [
{
"docstring": "test_decoder",
"name": "test_decoder",
"signature": "def test_decoder(self)"
},
{
"docstring": "test",
"name": "test",
"signature": "def test(self)"
}
] | 2 | null | Implement the Python class `Test` described below.
Class description:
test
Method signatures and docstrings:
- def test_decoder(self): test_decoder
- def test(self): test | Implement the Python class `Test` described below.
Class description:
test
Method signatures and docstrings:
- def test_decoder(self): test_decoder
- def test(self): test
<|skeleton|>
class Test:
"""test"""
def test_decoder(self):
"""test_decoder"""
<|body_0|>
def test(self):
""... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class Test:
"""test"""
def test_decoder(self):
"""test_decoder"""
<|body_0|>
def test(self):
"""test"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test:
"""test"""
def test_decoder(self):
"""test_decoder"""
paddle.set_device('cpu')
[batch_size, d_model, n_head, dim_feedforward, dropout, _, _, source_length, target_length] = generate_basic_params(mode='decoder_layer')
tgt = np.random.rand(batch_size, target_length, d_... | the_stack_v2_python_sparse | framework/api/nn/test_TransformerDecoder.py | PaddlePaddle/PaddleTest | train | 42 |
7bc1783af65e3191d92d49d03a6a53ff5acd504c | [
"super().__init__()\nself.pre_ln_attn = nn.LayerNorm(n_hidden)\nself.pre_ln_ffn = nn.LayerNorm(n_hidden)\nself.attention = AttentionLayer(n_hidden, n_heads)\nself.ffn = FFNLayer(n_hidden)",
"residual = x\nattn = self.attention(self.pre_ln_attn(x))\nffn = self.ffn(self.pre_ln_ffn(x))\nreturn attn + ffn + residual"... | <|body_start_0|>
super().__init__()
self.pre_ln_attn = nn.LayerNorm(n_hidden)
self.pre_ln_ffn = nn.LayerNorm(n_hidden)
self.attention = AttentionLayer(n_hidden, n_heads)
self.ffn = FFNLayer(n_hidden)
<|end_body_0|>
<|body_start_1|>
residual = x
attn = self.attent... | ## Transformer Layer | TransformerLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerLayer:
"""## Transformer Layer"""
def __init__(self, n_hidden: int=6144, n_heads: int=64):
""":param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*."""
<|body_0|>
def forward(self, x: torch.T... | stack_v2_sparse_classes_10k_train_007787 | 13,522 | no_license | [
{
"docstring": ":param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*.",
"name": "__init__",
"signature": "def __init__(self, n_hidden: int=6144, n_heads: int=64)"
},
{
"docstring": ":param x: are the embeddings of shape `[batc... | 3 | null | Implement the Python class `TransformerLayer` described below.
Class description:
## Transformer Layer
Method signatures and docstrings:
- def __init__(self, n_hidden: int=6144, n_heads: int=64): :param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*... | Implement the Python class `TransformerLayer` described below.
Class description:
## Transformer Layer
Method signatures and docstrings:
- def __init__(self, n_hidden: int=6144, n_heads: int=64): :param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class TransformerLayer:
"""## Transformer Layer"""
def __init__(self, n_hidden: int=6144, n_heads: int=64):
""":param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*."""
<|body_0|>
def forward(self, x: torch.T... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TransformerLayer:
"""## Transformer Layer"""
def __init__(self, n_hidden: int=6144, n_heads: int=64):
""":param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*."""
super().__init__()
self.pre_ln_attn = nn.LayerNor... | the_stack_v2_python_sparse | generated/test_labmlai_neox.py | jansel/pytorch-jit-paritybench | train | 35 |
5e7b52ecb441c4972fd4855ac4edcc1747d8f79f | [
"super(SegNet, self).__init__()\nself.layer_1 = SegnetLayer_Encoder(in_channels, 64, 2)\nself.layer_2 = SegnetLayer_Encoder(64, 128, 2)\nself.layer_3 = SegnetLayer_Encoder(128, 256, 3)\nself.layer_4 = SegnetLayer_Encoder(256, 512, 3)\nself.layer_5 = SegnetLayer_Encoder(512, 512, 3)\nself.layer_6 = SegnetLayer_Decod... | <|body_start_0|>
super(SegNet, self).__init__()
self.layer_1 = SegnetLayer_Encoder(in_channels, 64, 2)
self.layer_2 = SegnetLayer_Encoder(64, 128, 2)
self.layer_3 = SegnetLayer_Encoder(128, 256, 3)
self.layer_4 = SegnetLayer_Encoder(256, 512, 3)
self.layer_5 = SegnetLayer... | Derived Class to define a Segnet Architecture of NN Attributes ---------- in_channels : int The input size of the network. n_classes : int The output size of the network. References ---------- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan, Alex Kendall, Roberto Ci... | SegNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegNet:
"""Derived Class to define a Segnet Architecture of NN Attributes ---------- in_channels : int The input size of the network. n_classes : int The output size of the network. References ---------- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrin... | stack_v2_sparse_classes_10k_train_007788 | 20,094 | no_license | [
{
"docstring": "Sequential Instanciation of the different Layers",
"name": "__init__",
"signature": "def __init__(self, in_channels=3, n_classes=21)"
},
{
"docstring": "Sequential Computation, see nn.Module.forward methods PyTorch",
"name": "forward",
"signature": "def forward(self, inpu... | 3 | stack_v2_sparse_classes_30k_train_001399 | Implement the Python class `SegNet` described below.
Class description:
Derived Class to define a Segnet Architecture of NN Attributes ---------- in_channels : int The input size of the network. n_classes : int The output size of the network. References ---------- SegNet: A Deep Convolutional Encoder-Decoder Architect... | Implement the Python class `SegNet` described below.
Class description:
Derived Class to define a Segnet Architecture of NN Attributes ---------- in_channels : int The input size of the network. n_classes : int The output size of the network. References ---------- SegNet: A Deep Convolutional Encoder-Decoder Architect... | 3b63f360e67013d5962082e57fb36ebfb37d8920 | <|skeleton|>
class SegNet:
"""Derived Class to define a Segnet Architecture of NN Attributes ---------- in_channels : int The input size of the network. n_classes : int The output size of the network. References ---------- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SegNet:
"""Derived Class to define a Segnet Architecture of NN Attributes ---------- in_channels : int The input size of the network. n_classes : int The output size of the network. References ---------- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan, Ale... | the_stack_v2_python_sparse | segmentation/models/nn.py | Kivo0/vibotorch | train | 0 |
4f8053e55731d705a95bf665509f4fc40e187df0 | [
"status = ErrorCode.SUCCESS\ntry:\n tid = self.get_argument('tid')\nexcept Exception as e:\n status = ErrorCode.ILLEGAL_DATA_FORMAT\n self.write_ret(status)\ntry:\n res = QueryHelper.get_mileage_notification_by_tid(tid, self.db)\n self.write_ret(status, dict_=DotDict(res=res))\nexcept Exception as e:... | <|body_start_0|>
status = ErrorCode.SUCCESS
try:
tid = self.get_argument('tid')
except Exception as e:
status = ErrorCode.ILLEGAL_DATA_FORMAT
self.write_ret(status)
try:
res = QueryHelper.get_mileage_notification_by_tid(tid, self.db)
... | Mileage notification: distance of per day | MileageNotificationHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MileageNotificationHandler:
"""Mileage notification: distance of per day"""
def get(self):
"""Get mileage notifiction of a terminal. @params: tid, is required"""
<|body_0|>
def put(self):
"""Modify some settings about mileage notification."""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_007789 | 3,606 | no_license | [
{
"docstring": "Get mileage notifiction of a terminal. @params: tid, is required",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Modify some settings about mileage notification.",
"name": "put",
"signature": "def put(self)"
}
] | 2 | null | Implement the Python class `MileageNotificationHandler` described below.
Class description:
Mileage notification: distance of per day
Method signatures and docstrings:
- def get(self): Get mileage notifiction of a terminal. @params: tid, is required
- def put(self): Modify some settings about mileage notification. | Implement the Python class `MileageNotificationHandler` described below.
Class description:
Mileage notification: distance of per day
Method signatures and docstrings:
- def get(self): Get mileage notifiction of a terminal. @params: tid, is required
- def put(self): Modify some settings about mileage notification.
<... | 3b095a325581b1fc48497c234f0ad55e928586a1 | <|skeleton|>
class MileageNotificationHandler:
"""Mileage notification: distance of per day"""
def get(self):
"""Get mileage notifiction of a terminal. @params: tid, is required"""
<|body_0|>
def put(self):
"""Modify some settings about mileage notification."""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MileageNotificationHandler:
"""Mileage notification: distance of per day"""
def get(self):
"""Get mileage notifiction of a terminal. @params: tid, is required"""
status = ErrorCode.SUCCESS
try:
tid = self.get_argument('tid')
except Exception as e:
s... | the_stack_v2_python_sparse | apps/uweb/handlers/mileagenotification.py | jcsy521/ydws | train | 0 |
36b7d7396db6d1295406598de4598b75d73465db | [
"self.arduino = Serial(config)\nself.arduino.add_listener(self.parse_data)\nObservableComponent.__init__(self, self.arduino)",
"if len(reading) == 5:\n try:\n packet = TrollPacket.from_binary_packet(reading)\n self.update_listeners(packet)\n except KeyError as e:\n err_msg = 'Arduino me... | <|body_start_0|>
self.arduino = Serial(config)
self.arduino.add_listener(self.parse_data)
ObservableComponent.__init__(self, self.arduino)
<|end_body_0|>
<|body_start_1|>
if len(reading) == 5:
try:
packet = TrollPacket.from_binary_packet(reading)
... | Arduino layer for handling data inconsistensies. | Arduino | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Arduino:
"""Arduino layer for handling data inconsistensies."""
def __init__(self, config):
""":param config: Dictionary containing connection headers :type config: dict"""
<|body_0|>
def parse_data(self, reading):
"""Arduino sends data incosistently sometimes. T... | stack_v2_sparse_classes_10k_train_007790 | 10,572 | permissive | [
{
"docstring": ":param config: Dictionary containing connection headers :type config: dict",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Arduino sends data incosistently sometimes. This implementation assumes a format when receiving from arduino: - First byte... | 2 | stack_v2_sparse_classes_30k_train_000210 | Implement the Python class `Arduino` described below.
Class description:
Arduino layer for handling data inconsistensies.
Method signatures and docstrings:
- def __init__(self, config): :param config: Dictionary containing connection headers :type config: dict
- def parse_data(self, reading): Arduino sends data incos... | Implement the Python class `Arduino` described below.
Class description:
Arduino layer for handling data inconsistensies.
Method signatures and docstrings:
- def __init__(self, config): :param config: Dictionary containing connection headers :type config: dict
- def parse_data(self, reading): Arduino sends data incos... | d554403dc73e8de43e723c08994b3dae08ac0c1c | <|skeleton|>
class Arduino:
"""Arduino layer for handling data inconsistensies."""
def __init__(self, config):
""":param config: Dictionary containing connection headers :type config: dict"""
<|body_0|>
def parse_data(self, reading):
"""Arduino sends data incosistently sometimes. T... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Arduino:
"""Arduino layer for handling data inconsistensies."""
def __init__(self, config):
""":param config: Dictionary containing connection headers :type config: dict"""
self.arduino = Serial(config)
self.arduino.add_listener(self.parse_data)
ObservableComponent.__init_... | the_stack_v2_python_sparse | backend/endpoints.py | trolllabs/trollsim | train | 0 |
6a143293e3b168d679bc5c10d4ec7f30d379c03d | [
"super(FuncAwsGuarddutyPoller, self).__init__(opts)\nself.options = opts.get('fn_aws_guardduty', {})\nself.opts = opts\nif int(self.options.get('aws_gd_polling_interval', POLLING_INTERVAL_DEFAULT)) == 0:\n LOG.info('Polling for findings in AWS GuardDuty not enabled')\nelse:\n validate_fields(config.REQUIRED_C... | <|body_start_0|>
super(FuncAwsGuarddutyPoller, self).__init__(opts)
self.options = opts.get('fn_aws_guardduty', {})
self.opts = opts
if int(self.options.get('aws_gd_polling_interval', POLLING_INTERVAL_DEFAULT)) == 0:
LOG.info('Polling for findings in AWS GuardDuty not enabled... | Component that polls for new findings from AWS GuardDuty | FuncAwsGuarddutyPoller | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FuncAwsGuarddutyPoller:
"""Component that polls for new findings from AWS GuardDuty"""
def __init__(self, opts):
"""constructor provides access to the configuration options"""
<|body_0|>
def _reload(self, event, opts):
"""Configuration options have changed, save ... | stack_v2_sparse_classes_10k_train_007791 | 3,403 | permissive | [
{
"docstring": "constructor provides access to the configuration options",
"name": "__init__",
"signature": "def __init__(self, opts)"
},
{
"docstring": "Configuration options have changed, save new values",
"name": "_reload",
"signature": "def _reload(self, event, opts)"
},
{
"d... | 3 | null | Implement the Python class `FuncAwsGuarddutyPoller` described below.
Class description:
Component that polls for new findings from AWS GuardDuty
Method signatures and docstrings:
- def __init__(self, opts): constructor provides access to the configuration options
- def _reload(self, event, opts): Configuration option... | Implement the Python class `FuncAwsGuarddutyPoller` described below.
Class description:
Component that polls for new findings from AWS GuardDuty
Method signatures and docstrings:
- def __init__(self, opts): constructor provides access to the configuration options
- def _reload(self, event, opts): Configuration option... | 6878c78b94eeca407998a41ce8db2cc00f2b6758 | <|skeleton|>
class FuncAwsGuarddutyPoller:
"""Component that polls for new findings from AWS GuardDuty"""
def __init__(self, opts):
"""constructor provides access to the configuration options"""
<|body_0|>
def _reload(self, event, opts):
"""Configuration options have changed, save ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FuncAwsGuarddutyPoller:
"""Component that polls for new findings from AWS GuardDuty"""
def __init__(self, opts):
"""constructor provides access to the configuration options"""
super(FuncAwsGuarddutyPoller, self).__init__(opts)
self.options = opts.get('fn_aws_guardduty', {})
... | the_stack_v2_python_sparse | fn_aws_guardduty/fn_aws_guardduty/components/func_aws_guardduty_poller.py | ibmresilient/resilient-community-apps | train | 81 |
1c0620022b2b7864d4bff3526252bc6e5325886d | [
"if not nums or len(nums) <= 0:\n return\nres = 0\nfor i in nums:\n res = res ^ i\nindex = self.findFirstBit(res)\nres1 = 0\nres2 = 0\nfor j in nums:\n if j >> index & 1 == 1:\n res1 = res1 ^ j\n else:\n res2 = res2 ^ j\nreturn [res1, res2]",
"indexBit = 0\nwhile num & 1 == 0 and indexBi... | <|body_start_0|>
if not nums or len(nums) <= 0:
return
res = 0
for i in nums:
res = res ^ i
index = self.findFirstBit(res)
res1 = 0
res2 = 0
for j in nums:
if j >> index & 1 == 1:
res1 = res1 ^ j
else... | Solution1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def findNumsAppearOnce(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findFirstBit(self, num):
"""找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums or len... | stack_v2_sparse_classes_10k_train_007792 | 3,672 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findNumsAppearOnce",
"signature": "def findNumsAppearOnce(self, nums)"
},
{
"docstring": "找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return:",
"name": "findFirstBit",
"signature": "def findFirstBit(self, num)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001635 | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def findNumsAppearOnce(self, nums): :type nums: List[int] :rtype: List[int]
- def findFirstBit(self, num): 找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return: | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def findNumsAppearOnce(self, nums): :type nums: List[int] :rtype: List[int]
- def findFirstBit(self, num): 找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return:
<|skeleton|>
class So... | 1db60502acb208f22d2149a4824e1219d8938225 | <|skeleton|>
class Solution1:
def findNumsAppearOnce(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findFirstBit(self, num):
"""找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution1:
def findNumsAppearOnce(self, nums):
""":type nums: List[int] :rtype: List[int]"""
if not nums or len(nums) <= 0:
return
res = 0
for i in nums:
res = res ^ i
index = self.findFirstBit(res)
res1 = 0
res2 = 0
for j... | the_stack_v2_python_sparse | code_with_name/test55_prob56_数组中只出现一次的两个数字.py | Binjer/jianzhi_offer | train | 2 | |
0e68a2594dc66fa9cf8c9491b0f8d6dafc876ca6 | [
"extra = ctypes.c_ulong(0)\nii_ = Input_I()\nii_.ki = KeyBdInput(keyCode, 72, 0, 0, ctypes.pointer(extra))\nx = Input(ctypes.c_ulong(1), ii_)\nSendInput(1, ctypes.pointer(x), ctypes.sizeof(x))",
"extra = ctypes.c_ulong(0)\nii_ = Input_I()\nii_.ki = KeyBdInput(keyCode, 72, 2, 0, ctypes.pointer(extra))\nx = Input(c... | <|body_start_0|>
extra = ctypes.c_ulong(0)
ii_ = Input_I()
ii_.ki = KeyBdInput(keyCode, 72, 0, 0, ctypes.pointer(extra))
x = Input(ctypes.c_ulong(1), ii_)
SendInput(1, ctypes.pointer(x), ctypes.sizeof(x))
<|end_body_0|>
<|body_start_1|>
extra = ctypes.c_ulong(0)
... | Class Keyboard :author: Paradoxis <luke@paradoxis.nl> :description: Keyboard methods to trigger fake key events | Keyboard | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Keyboard:
"""Class Keyboard :author: Paradoxis <luke@paradoxis.nl> :description: Keyboard methods to trigger fake key events"""
def keyDown(keyCode):
"""Key down wrapper :param keyCode: int :return: void"""
<|body_0|>
def keyUp(keyCode):
"""Key up wrapper :param ... | stack_v2_sparse_classes_10k_train_007793 | 5,030 | no_license | [
{
"docstring": "Key down wrapper :param keyCode: int :return: void",
"name": "keyDown",
"signature": "def keyDown(keyCode)"
},
{
"docstring": "Key up wrapper :param keyCode: int :return: void",
"name": "keyUp",
"signature": "def keyUp(keyCode)"
},
{
"docstring": "Type a key :para... | 3 | stack_v2_sparse_classes_30k_train_003934 | Implement the Python class `Keyboard` described below.
Class description:
Class Keyboard :author: Paradoxis <luke@paradoxis.nl> :description: Keyboard methods to trigger fake key events
Method signatures and docstrings:
- def keyDown(keyCode): Key down wrapper :param keyCode: int :return: void
- def keyUp(keyCode): K... | Implement the Python class `Keyboard` described below.
Class description:
Class Keyboard :author: Paradoxis <luke@paradoxis.nl> :description: Keyboard methods to trigger fake key events
Method signatures and docstrings:
- def keyDown(keyCode): Key down wrapper :param keyCode: int :return: void
- def keyUp(keyCode): K... | 5c03f77893ae98a49805fb15fbf48fed688dc714 | <|skeleton|>
class Keyboard:
"""Class Keyboard :author: Paradoxis <luke@paradoxis.nl> :description: Keyboard methods to trigger fake key events"""
def keyDown(keyCode):
"""Key down wrapper :param keyCode: int :return: void"""
<|body_0|>
def keyUp(keyCode):
"""Key up wrapper :param ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Keyboard:
"""Class Keyboard :author: Paradoxis <luke@paradoxis.nl> :description: Keyboard methods to trigger fake key events"""
def keyDown(keyCode):
"""Key down wrapper :param keyCode: int :return: void"""
extra = ctypes.c_ulong(0)
ii_ = Input_I()
ii_.ki = KeyBdInput(keyC... | the_stack_v2_python_sparse | software/non_ai/systemcontrols/keyboard.py | SGNetworksIndia/J.A.R.V.I.S | train | 7 |
e7b498e474050ea71bdd96a303b23022c8f1da2a | [
"self.stack_size = stack_size\nself.arr = [None] * stack_size * 3\nself.bottoms = [i * stack_size for i in range(3)]\nself.tops = [i * stack_size for i in range(3)]",
"i = stackno - 1\nif self.tops[i] - self.bottoms[i] == self.stack_size:\n raise Exception('push called on full stack {stackno}')\nself.arr[self.... | <|body_start_0|>
self.stack_size = stack_size
self.arr = [None] * stack_size * 3
self.bottoms = [i * stack_size for i in range(3)]
self.tops = [i * stack_size for i in range(3)]
<|end_body_0|>
<|body_start_1|>
i = stackno - 1
if self.tops[i] - self.bottoms[i] == self.sta... | Class implementing three stacks with one array | ThreeStacks | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThreeStacks:
"""Class implementing three stacks with one array"""
def __init__(self, stack_size: int=10):
"""Init three stacks, each with initial allocated size `stack_size`"""
<|body_0|>
def push(self, stackno: int, val) -> None:
"""Push `val` onto stack number ... | stack_v2_sparse_classes_10k_train_007794 | 2,829 | no_license | [
{
"docstring": "Init three stacks, each with initial allocated size `stack_size`",
"name": "__init__",
"signature": "def __init__(self, stack_size: int=10)"
},
{
"docstring": "Push `val` onto stack number `stackno` (1, 2, or 3)",
"name": "push",
"signature": "def push(self, stackno: int,... | 3 | stack_v2_sparse_classes_30k_train_004916 | Implement the Python class `ThreeStacks` described below.
Class description:
Class implementing three stacks with one array
Method signatures and docstrings:
- def __init__(self, stack_size: int=10): Init three stacks, each with initial allocated size `stack_size`
- def push(self, stackno: int, val) -> None: Push `va... | Implement the Python class `ThreeStacks` described below.
Class description:
Class implementing three stacks with one array
Method signatures and docstrings:
- def __init__(self, stack_size: int=10): Init three stacks, each with initial allocated size `stack_size`
- def push(self, stackno: int, val) -> None: Push `va... | 12200cf58378bb858d1113a12c3f54054df91937 | <|skeleton|>
class ThreeStacks:
"""Class implementing three stacks with one array"""
def __init__(self, stack_size: int=10):
"""Init three stacks, each with initial allocated size `stack_size`"""
<|body_0|>
def push(self, stackno: int, val) -> None:
"""Push `val` onto stack number ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ThreeStacks:
"""Class implementing three stacks with one array"""
def __init__(self, stack_size: int=10):
"""Init three stacks, each with initial allocated size `stack_size`"""
self.stack_size = stack_size
self.arr = [None] * stack_size * 3
self.bottoms = [i * stack_size f... | the_stack_v2_python_sparse | chapter3/1_three_in_one.py | adityabads/cracking-coding-interview | train | 0 |
c32e53468161fbe3f4bbb7580d9b790278b22aeb | [
"super().__init__(name)\nself.reg_seqr = None\nself.adapter = None\nself.model = None\nself.parent_select = LOCAL\nself.upstream_parent = None",
"if self.m_sequencer is None:\n uvm_fatal('NO_SEQR', 'Sequence executing as translation sequence, ' + 'but is not associated with a sequencer (m_sequencer == null)')\... | <|body_start_0|>
super().__init__(name)
self.reg_seqr = None
self.adapter = None
self.model = None
self.parent_select = LOCAL
self.upstream_parent = None
<|end_body_0|>
<|body_start_1|>
if self.m_sequencer is None:
uvm_fatal('NO_SEQR', 'Sequence execu... | UVMRegSequence | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UVMRegSequence:
def __init__(self, name='uvm_reg_sequence_inst'):
"""Function: new Create a new instance, giving it the optional `name`. Args: name:"""
<|body_0|>
async def body(self):
"""Task: body Continually gets a register transaction from the configured upstream... | stack_v2_sparse_classes_10k_train_007795 | 21,775 | permissive | [
{
"docstring": "Function: new Create a new instance, giving it the optional `name`. Args: name:",
"name": "__init__",
"signature": "def __init__(self, name='uvm_reg_sequence_inst')"
},
{
"docstring": "Task: body Continually gets a register transaction from the configured upstream sequencer, `reg... | 3 | null | Implement the Python class `UVMRegSequence` described below.
Class description:
Implement the UVMRegSequence class.
Method signatures and docstrings:
- def __init__(self, name='uvm_reg_sequence_inst'): Function: new Create a new instance, giving it the optional `name`. Args: name:
- async def body(self): Task: body C... | Implement the Python class `UVMRegSequence` described below.
Class description:
Implement the UVMRegSequence class.
Method signatures and docstrings:
- def __init__(self, name='uvm_reg_sequence_inst'): Function: new Create a new instance, giving it the optional `name`. Args: name:
- async def body(self): Task: body C... | fc5f955701b2b56c1fddac195c70cb3ebb9139fe | <|skeleton|>
class UVMRegSequence:
def __init__(self, name='uvm_reg_sequence_inst'):
"""Function: new Create a new instance, giving it the optional `name`. Args: name:"""
<|body_0|>
async def body(self):
"""Task: body Continually gets a register transaction from the configured upstream... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UVMRegSequence:
def __init__(self, name='uvm_reg_sequence_inst'):
"""Function: new Create a new instance, giving it the optional `name`. Args: name:"""
super().__init__(name)
self.reg_seqr = None
self.adapter = None
self.model = None
self.parent_select = LOCAL
... | the_stack_v2_python_sparse | src/uvm/reg/uvm_reg_sequence.py | tpoikela/uvm-python | train | 199 | |
395894b682ece2b60e052c6f592624dfa651517f | [
"super().__init__(pool_size=pool_size)\nself.min_neg = min_neg\nself.batch_size_per_image = batch_size_per_image\nself.positive_fraction = positive_fraction",
"anchors_per_image = [anchors_in_image.shape[0] for anchors_in_image in target_labels]\nfg_probs = fg_probs.split(anchors_per_image, 0)\npos_idx = []\nneg_... | <|body_start_0|>
super().__init__(pool_size=pool_size)
self.min_neg = min_neg
self.batch_size_per_image = batch_size_per_image
self.positive_fraction = positive_fraction
<|end_body_0|>
<|body_start_1|>
anchors_per_image = [anchors_in_image.shape[0] for anchors_in_image in target... | HardNegativeSampler | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HardNegativeSampler:
def __init__(self, batch_size_per_image: int, positive_fraction: float, min_neg: int=0, pool_size: float=10):
"""Created a pool from the highest scoring false positives and sample defined number of negatives from it Args: batch_size_per_image (int): number of element... | stack_v2_sparse_classes_10k_train_007796 | 13,985 | permissive | [
{
"docstring": "Created a pool from the highest scoring false positives and sample defined number of negatives from it Args: batch_size_per_image (int): number of elements to be selected per image positive_fraction (float): percentage of positive elements per batch pool_size (float): hard negatives are sampled ... | 5 | stack_v2_sparse_classes_30k_train_005423 | Implement the Python class `HardNegativeSampler` described below.
Class description:
Implement the HardNegativeSampler class.
Method signatures and docstrings:
- def __init__(self, batch_size_per_image: int, positive_fraction: float, min_neg: int=0, pool_size: float=10): Created a pool from the highest scoring false ... | Implement the Python class `HardNegativeSampler` described below.
Class description:
Implement the HardNegativeSampler class.
Method signatures and docstrings:
- def __init__(self, batch_size_per_image: int, positive_fraction: float, min_neg: int=0, pool_size: float=10): Created a pool from the highest scoring false ... | 4f41faa7536dcef8fca7b647dcdca25360e5b58a | <|skeleton|>
class HardNegativeSampler:
def __init__(self, batch_size_per_image: int, positive_fraction: float, min_neg: int=0, pool_size: float=10):
"""Created a pool from the highest scoring false positives and sample defined number of negatives from it Args: batch_size_per_image (int): number of element... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HardNegativeSampler:
def __init__(self, batch_size_per_image: int, positive_fraction: float, min_neg: int=0, pool_size: float=10):
"""Created a pool from the highest scoring false positives and sample defined number of negatives from it Args: batch_size_per_image (int): number of elements to be select... | the_stack_v2_python_sparse | nndet/core/boxes/sampler.py | dboun/nnDetection | train | 1 | |
f8357c6e6d0b5a278efeee7f08179a117e68be88 | [
"self.big = big\nself.medium = medium\nself.small = small",
"if carType == 1:\n self.big = self.big - 1\n if self.big >= 0:\n return True\n else:\n return False\nelif carType == 2:\n self.medium = self.medium - 1\n if self.medium >= 0:\n return True\n else:\n return F... | <|body_start_0|>
self.big = big
self.medium = medium
self.small = small
<|end_body_0|>
<|body_start_1|>
if carType == 1:
self.big = self.big - 1
if self.big >= 0:
return True
else:
return False
elif carType == 2... | ParkingSystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParkingSystem:
def __init__(self, big, medium, small):
""":type big: int :type medium: int :type small: int"""
<|body_0|>
def addCar(self, carType):
""":type carType: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.big = big
... | stack_v2_sparse_classes_10k_train_007797 | 1,839 | no_license | [
{
"docstring": ":type big: int :type medium: int :type small: int",
"name": "__init__",
"signature": "def __init__(self, big, medium, small)"
},
{
"docstring": ":type carType: int :rtype: bool",
"name": "addCar",
"signature": "def addCar(self, carType)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006749 | Implement the Python class `ParkingSystem` described below.
Class description:
Implement the ParkingSystem class.
Method signatures and docstrings:
- def __init__(self, big, medium, small): :type big: int :type medium: int :type small: int
- def addCar(self, carType): :type carType: int :rtype: bool | Implement the Python class `ParkingSystem` described below.
Class description:
Implement the ParkingSystem class.
Method signatures and docstrings:
- def __init__(self, big, medium, small): :type big: int :type medium: int :type small: int
- def addCar(self, carType): :type carType: int :rtype: bool
<|skeleton|>
cla... | 6d6afba93d20665d033fe542c97e3eb50368bd3c | <|skeleton|>
class ParkingSystem:
def __init__(self, big, medium, small):
""":type big: int :type medium: int :type small: int"""
<|body_0|>
def addCar(self, carType):
""":type carType: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ParkingSystem:
def __init__(self, big, medium, small):
""":type big: int :type medium: int :type small: int"""
self.big = big
self.medium = medium
self.small = small
def addCar(self, carType):
""":type carType: int :rtype: bool"""
if carType == 1:
... | the_stack_v2_python_sparse | design_parking_system.py | naomi397liu/AlgorithmPactice | train | 1 | |
856601f7348d491c89af97d715f7e406504b0d1f | [
"tmp_file_name = 'test.json'\ntmp_dir_name = tempfile.gettempdir()\njson_file_path = tmp_dir_name + '/' + tmp_file_name\nwith open(json_file_path, 'w') as f:\n f.write(policy_json.strip())\ngrd_text = '\\n <grit base_dir=\".\" latest_public_release=\"0\" current_release=\"1\" source_lang_id=\"en\">\\n <r... | <|body_start_0|>
tmp_file_name = 'test.json'
tmp_dir_name = tempfile.gettempdir()
json_file_path = tmp_dir_name + '/' + tmp_file_name
with open(json_file_path, 'w') as f:
f.write(policy_json.strip())
grd_text = '\n <grit base_dir="." latest_public_release="0" curre... | Common class for unittesting writers. | WriterUnittestCommon | [
"BSD-3-Clause",
"LGPL-2.0-or-later",
"LicenseRef-scancode-unknown-license-reference",
"GPL-2.0-only",
"Apache-2.0",
"LicenseRef-scancode-unknown",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WriterUnittestCommon:
"""Common class for unittesting writers."""
def PrepareTest(self, policy_json):
"""Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in JSON format."""
<|body_0|>
def GetOutput(self... | stack_v2_sparse_classes_10k_train_007798 | 2,618 | permissive | [
{
"docstring": "Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in JSON format.",
"name": "PrepareTest",
"signature": "def PrepareTest(self, policy_json)"
},
{
"docstring": "Generates an output of a writer. Args: grd: The root... | 2 | null | Implement the Python class `WriterUnittestCommon` described below.
Class description:
Common class for unittesting writers.
Method signatures and docstrings:
- def PrepareTest(self, policy_json): Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in J... | Implement the Python class `WriterUnittestCommon` described below.
Class description:
Common class for unittesting writers.
Method signatures and docstrings:
- def PrepareTest(self, policy_json): Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in J... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class WriterUnittestCommon:
"""Common class for unittesting writers."""
def PrepareTest(self, policy_json):
"""Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in JSON format."""
<|body_0|>
def GetOutput(self... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WriterUnittestCommon:
"""Common class for unittesting writers."""
def PrepareTest(self, policy_json):
"""Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in JSON format."""
tmp_file_name = 'test.json'
tmp_dir_nam... | the_stack_v2_python_sparse | tools/grit/grit/format/policy_templates/writers/writer_unittest_common.py | metux/chromium-suckless | train | 5 |
99d4ca8e0e3a1e13e230611864ef6a98dac4c1a6 | [
"inSpec = super(SampleSelector, cls).getInputSpecification()\ninSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringType))\ncriterion = InputData.parameterInputFactory('criterion', contentType=InputTypes.StringType, strictMode=True)\ncriterion.addParam('value', InputTypes.IntegerType)... | <|body_start_0|>
inSpec = super(SampleSelector, cls).getInputSpecification()
inSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringType))
criterion = InputData.parameterInputFactory('criterion', contentType=InputTypes.StringType, strictMode=True)
criterion.... | This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return. | SampleSelector | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampleSelector:
"""This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return."""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the ... | stack_v2_sparse_classes_10k_train_007799 | 5,362 | permissive | [
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for which we are retrieving the specification @ Out, inputSpecification, InputData.ParameterInput, class to use for specifying input of cls.",
"name": "getInputSpecification",
"signatur... | 6 | null | Implement the Python class `SampleSelector` described below.
Class description:
This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return.
Method signatures and docstrings:
- def getInputSpecification(cls):... | Implement the Python class `SampleSelector` described below.
Class description:
This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return.
Method signatures and docstrings:
- def getInputSpecification(cls):... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class SampleSelector:
"""This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return."""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SampleSelector:
"""This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return."""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data fo... | the_stack_v2_python_sparse | ravenframework/Models/PostProcessors/SampleSelector.py | idaholab/raven | train | 201 |
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