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 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8bfb89f555e4c86c8fcb3d7a40f5e305e55e39ab | [
"has_lot_seq = lot_num is not None and sequence_num is not None\nowner_entropy = _Bip38EcUtils.OwnerEntropyWithLotSeq(lot_num, sequence_num) if has_lot_seq else _Bip38EcUtils.OwnerEntropyNoLotSeq()\npassfactor = _Bip38EcUtils.PassFactor(passphrase, owner_entropy, has_lot_seq)\npasspoint = _Bip38EcUtils.PassPoint(pa... | <|body_start_0|>
has_lot_seq = lot_num is not None and sequence_num is not None
owner_entropy = _Bip38EcUtils.OwnerEntropyWithLotSeq(lot_num, sequence_num) if has_lot_seq else _Bip38EcUtils.OwnerEntropyNoLotSeq()
passfactor = _Bip38EcUtils.PassFactor(passphrase, owner_entropy, has_lot_seq)
... | BIP38 keys generator class. It generates intermediate codes and private keys using the algorithm specified in BIP38 with EC multiplication. | Bip38EcKeysGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bip38EcKeysGenerator:
"""BIP38 keys generator class. It generates intermediate codes and private keys using the algorithm specified in BIP38 with EC multiplication."""
def GenerateIntermediatePassphrase(passphrase: str, lot_num: Optional[int]=None, sequence_num: Optional[int]=None) -> str:
... | stack_v2_sparse_classes_75kplus_train_000900 | 20,821 | permissive | [
{
"docstring": "Generate an intermediate passphrase from the user passphrase as specified in BIP38. Args: passphrase (str) : Passphrase lot_num (int, optional) : Lot number sequence_num (int, optional): Sequence number Returns: str: Intermediate passphrase encoded in base58",
"name": "GenerateIntermediatePa... | 4 | stack_v2_sparse_classes_30k_train_051064 | Implement the Python class `Bip38EcKeysGenerator` described below.
Class description:
BIP38 keys generator class. It generates intermediate codes and private keys using the algorithm specified in BIP38 with EC multiplication.
Method signatures and docstrings:
- def GenerateIntermediatePassphrase(passphrase: str, lot_... | Implement the Python class `Bip38EcKeysGenerator` described below.
Class description:
BIP38 keys generator class. It generates intermediate codes and private keys using the algorithm specified in BIP38 with EC multiplication.
Method signatures and docstrings:
- def GenerateIntermediatePassphrase(passphrase: str, lot_... | d15c75ddd74e4838c396a0d036ef6faf11b06a4b | <|skeleton|>
class Bip38EcKeysGenerator:
"""BIP38 keys generator class. It generates intermediate codes and private keys using the algorithm specified in BIP38 with EC multiplication."""
def GenerateIntermediatePassphrase(passphrase: str, lot_num: Optional[int]=None, sequence_num: Optional[int]=None) -> str:
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Bip38EcKeysGenerator:
"""BIP38 keys generator class. It generates intermediate codes and private keys using the algorithm specified in BIP38 with EC multiplication."""
def GenerateIntermediatePassphrase(passphrase: str, lot_num: Optional[int]=None, sequence_num: Optional[int]=None) -> str:
"""Gen... | the_stack_v2_python_sparse | bip_utils/bip/bip38/bip38_ec.py | ebellocchia/bip_utils | train | 244 |
056976f8bdf1d4dfa3e0c2c25b3932d3f4a73a6b | [
"audiofiletype_serializer = self.serializer_class(data=self.request.data)\naudiofiletype_serializer.is_valid(raise_exception=True)\naudiofiletype = audiofiletype_serializer.validated_data['audiofiletype']\nreturn self.audio_type_serializer_model_mapping[audiofiletype]['serializer']",
"serializer_class = self.get_... | <|body_start_0|>
audiofiletype_serializer = self.serializer_class(data=self.request.data)
audiofiletype_serializer.is_valid(raise_exception=True)
audiofiletype = audiofiletype_serializer.validated_data['audiofiletype']
return self.audio_type_serializer_model_mapping[audiofiletype]['seria... | Create an Audio File Record in the specified audio type | AudioFileCreateAPIView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AudioFileCreateAPIView:
"""Create an Audio File Record in the specified audio type"""
def get_serializer_class(self):
"""Check which audiofiletype is passed and choose a serializer for the same from the defined mapping"""
<|body_0|>
def create(self, request, *args, **kwa... | stack_v2_sparse_classes_75kplus_train_000901 | 2,418 | no_license | [
{
"docstring": "Check which audiofiletype is passed and choose a serializer for the same from the defined mapping",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "Create a record in table of the deduced audiofiletype",
"name": "create",
"... | 2 | stack_v2_sparse_classes_30k_train_000355 | Implement the Python class `AudioFileCreateAPIView` described below.
Class description:
Create an Audio File Record in the specified audio type
Method signatures and docstrings:
- def get_serializer_class(self): Check which audiofiletype is passed and choose a serializer for the same from the defined mapping
- def cr... | Implement the Python class `AudioFileCreateAPIView` described below.
Class description:
Create an Audio File Record in the specified audio type
Method signatures and docstrings:
- def get_serializer_class(self): Check which audiofiletype is passed and choose a serializer for the same from the defined mapping
- def cr... | 55ebdc0ae27f3e1dbf2be98ec8b8248a23111d4a | <|skeleton|>
class AudioFileCreateAPIView:
"""Create an Audio File Record in the specified audio type"""
def get_serializer_class(self):
"""Check which audiofiletype is passed and choose a serializer for the same from the defined mapping"""
<|body_0|>
def create(self, request, *args, **kwa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AudioFileCreateAPIView:
"""Create an Audio File Record in the specified audio type"""
def get_serializer_class(self):
"""Check which audiofiletype is passed and choose a serializer for the same from the defined mapping"""
audiofiletype_serializer = self.serializer_class(data=self.request.... | the_stack_v2_python_sparse | src/core/views.py | vishaltanwar96/audio-file-api | train | 1 |
2fea7567d11e9044b1ac6cf5d4bc9abb56cd4536 | [
"if cls.app is None:\n cls.app = lux.App(cls.config_file, **cls.config_params)\nreturn cls.app",
"out = out or Stream()\napp = self.application()\ncmd = app.get_command(command, stdout=out)\nself.assertTrue(cmd.logger)\nself.assertEqual(cmd.name, command)\nreturn cmd"
] | <|body_start_0|>
if cls.app is None:
cls.app = lux.App(cls.config_file, **cls.config_params)
return cls.app
<|end_body_0|>
<|body_start_1|>
out = out or Stream()
app = self.application()
cmd = app.get_command(command, stdout=out)
self.assertTrue(cmd.logger)
... | TestCase class for lux tests. It provides several utilities methods. | TestCase | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCase:
"""TestCase class for lux tests. It provides several utilities methods."""
def application(cls):
"""Return an application for testing. Override if needed."""
<|body_0|>
def fetch_command(self, command, out=None):
"""Fetch a command."""
<|body_1|... | stack_v2_sparse_classes_75kplus_train_000902 | 1,586 | permissive | [
{
"docstring": "Return an application for testing. Override if needed.",
"name": "application",
"signature": "def application(cls)"
},
{
"docstring": "Fetch a command.",
"name": "fetch_command",
"signature": "def fetch_command(self, command, out=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_023092 | Implement the Python class `TestCase` described below.
Class description:
TestCase class for lux tests. It provides several utilities methods.
Method signatures and docstrings:
- def application(cls): Return an application for testing. Override if needed.
- def fetch_command(self, command, out=None): Fetch a command. | Implement the Python class `TestCase` described below.
Class description:
TestCase class for lux tests. It provides several utilities methods.
Method signatures and docstrings:
- def application(cls): Return an application for testing. Override if needed.
- def fetch_command(self, command, out=None): Fetch a command.... | b30062268104bc9350b5ed36a6f5fe070eca4cf7 | <|skeleton|>
class TestCase:
"""TestCase class for lux tests. It provides several utilities methods."""
def application(cls):
"""Return an application for testing. Override if needed."""
<|body_0|>
def fetch_command(self, command, out=None):
"""Fetch a command."""
<|body_1|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestCase:
"""TestCase class for lux tests. It provides several utilities methods."""
def application(cls):
"""Return an application for testing. Override if needed."""
if cls.app is None:
cls.app = lux.App(cls.config_file, **cls.config_params)
return cls.app
def f... | the_stack_v2_python_sparse | lux/utils/test.py | pombredanne/lux | train | 0 |
9f44765518ce70b7b0adc98269f254e02d652436 | [
"if request.user.has_perm(VIEW_TEAMTYPE):\n group_types = TeamType.objects.all()\n serializer = TeamTypeSerializer(group_types, many=True)\n return Response(serializer.data)\nelse:\n return Response(status=status.HTTP_401_UNAUTHORIZED)",
"if request.user.has_perm(ADD_TEAMTYPE):\n serializer = TeamT... | <|body_start_0|>
if request.user.has_perm(VIEW_TEAMTYPE):
group_types = TeamType.objects.all()
serializer = TeamTypeSerializer(group_types, many=True)
return Response(serializer.data)
else:
return Response(status=status.HTTP_401_UNAUTHORIZED)
<|end_body_0|... | # List all the team types or create a new one. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : list all team types and return the data POST request : - create a new team type, send HTTP 201. If the request is not valid, send HTTP 400. ... | TeamTypesList | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeamTypesList:
"""# List all the team types or create a new one. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : list all team types and return the data POST request : - create a new team type, send HTTP 201. If ... | stack_v2_sparse_classes_75kplus_train_000903 | 6,650 | permissive | [
{
"docstring": "docstring.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "docstring.",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_032186 | Implement the Python class `TeamTypesList` described below.
Class description:
# List all the team types or create a new one. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : list all team types and return the data POST request : - cre... | Implement the Python class `TeamTypesList` described below.
Class description:
# List all the team types or create a new one. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : list all team types and return the data POST request : - cre... | 56511ebac83a5dc1fb8768a98bc675e88530a447 | <|skeleton|>
class TeamTypesList:
"""# List all the team types or create a new one. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : list all team types and return the data POST request : - create a new team type, send HTTP 201. If ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TeamTypesList:
"""# List all the team types or create a new one. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : list all team types and return the data POST request : - create a new team type, send HTTP 201. If the request i... | the_stack_v2_python_sparse | usersmanagement/views/views_teamtypes.py | Open-CMMS/openCMMS_backend | train | 4 |
21958b9c814a63786afc44eaccdbcdff6ffead09 | [
"store = []\n\ndef inorder(node):\n if not node:\n return\n store.append(str(node.val))\n if node.left:\n inorder(node.left)\n if node.right:\n inorder(node.right)\ninorder(root)\nprint(store)\nreturn '-'.join(store)",
"def insert(root, node):\n if not root:\n return Tre... | <|body_start_0|>
store = []
def inorder(node):
if not node:
return
store.append(str(node.val))
if node.left:
inorder(node.left)
if node.right:
inorder(node.right)
inorder(root)
print(store)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
store = []
... | stack_v2_sparse_classes_75kplus_train_000904 | 1,550 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_050926 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | f273c655f37da643a605cc5bebcda6660e702445 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
store = []
def inorder(node):
if not node:
return
store.append(str(node.val))
if node.left:
inorder(node.left)
if... | the_stack_v2_python_sparse | Tree/449. Serialize and Deserialize BST(Med).py | nerohuang/LeetCode | train | 0 | |
59b209d85e5b7893cfc6be2d95712108abe8f813 | [
"node_list = []\nnode = head\nwhile node:\n if node:\n node_list.append(node)\n node = node.next\nreturn node_list[len(node_list) // 2]",
"slow = fast = head\nwhile fast and fast.next:\n slow = slow.next\n fast = fast.next.next\nreturn slow"
] | <|body_start_0|>
node_list = []
node = head
while node:
if node:
node_list.append(node)
node = node.next
return node_list[len(node_list) // 2]
<|end_body_0|>
<|body_start_1|>
slow = fast = head
while fast and fast.next:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def middleNodeArray(self, head: ListNode) -> ListNode:
"""链表转换数组"""
<|body_0|>
def middleNode(self, head: ListNode) -> List:
"""快慢指针"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
node_list = []
node = head
while node:
... | stack_v2_sparse_classes_75kplus_train_000905 | 1,239 | no_license | [
{
"docstring": "链表转换数组",
"name": "middleNodeArray",
"signature": "def middleNodeArray(self, head: ListNode) -> ListNode"
},
{
"docstring": "快慢指针",
"name": "middleNode",
"signature": "def middleNode(self, head: ListNode) -> List"
}
] | 2 | stack_v2_sparse_classes_30k_train_007640 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def middleNodeArray(self, head: ListNode) -> ListNode: 链表转换数组
- def middleNode(self, head: ListNode) -> List: 快慢指针 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def middleNodeArray(self, head: ListNode) -> ListNode: 链表转换数组
- def middleNode(self, head: ListNode) -> List: 快慢指针
<|skeleton|>
class Solution:
def middleNodeArray(self, he... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def middleNodeArray(self, head: ListNode) -> ListNode:
"""链表转换数组"""
<|body_0|>
def middleNode(self, head: ListNode) -> List:
"""快慢指针"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def middleNodeArray(self, head: ListNode) -> ListNode:
"""链表转换数组"""
node_list = []
node = head
while node:
if node:
node_list.append(node)
node = node.next
return node_list[len(node_list) // 2]
def middleNode(self, ... | the_stack_v2_python_sparse | 876.链表的中间结点/solution.py | QtTao/daily_leetcode | train | 0 | |
42bd1fe6b96b363bee615d27a24cc645cfa427fe | [
"super(TaskBundleManager, self).__init__()\nself.getters.update({'name': 'get_general', 'description': 'get_general', 'tasks': 'get_tasks_from_task_bundle'})\nself.setters.update({'name': 'set_general', 'description': 'set_general', 'tasks': 'set_tasks_for_task_bundle'})\nself.my_django_model = facade.models.TaskBu... | <|body_start_0|>
super(TaskBundleManager, self).__init__()
self.getters.update({'name': 'get_general', 'description': 'get_general', 'tasks': 'get_tasks_from_task_bundle'})
self.setters.update({'name': 'set_general', 'description': 'set_general', 'tasks': 'set_tasks_for_task_bundle'})
se... | Manage Task Bundles in the Power Reg system | TaskBundleManager | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskBundleManager:
"""Manage Task Bundles in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, name, description, tasks):
"""Creates a new task bundle :param name: user-visible name of the task bundle :type name... | stack_v2_sparse_classes_75kplus_train_000906 | 2,310 | permissive | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Creates a new task bundle :param name: user-visible name of the task bundle :type name: string :param description: description of the task bundle :type description: string :param tasks: list of... | 2 | stack_v2_sparse_classes_30k_train_032899 | Implement the Python class `TaskBundleManager` described below.
Class description:
Manage Task Bundles in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, name, description, tasks): Creates a new task bundle :param name: user-visible name of the t... | Implement the Python class `TaskBundleManager` described below.
Class description:
Manage Task Bundles in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, name, description, tasks): Creates a new task bundle :param name: user-visible name of the t... | a59457bc37f0501aea1f54d006a6de94ff80511c | <|skeleton|>
class TaskBundleManager:
"""Manage Task Bundles in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, name, description, tasks):
"""Creates a new task bundle :param name: user-visible name of the task bundle :type name... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TaskBundleManager:
"""Manage Task Bundles in the Power Reg system"""
def __init__(self):
"""constructor"""
super(TaskBundleManager, self).__init__()
self.getters.update({'name': 'get_general', 'description': 'get_general', 'tasks': 'get_tasks_from_task_bundle'})
self.sette... | the_stack_v2_python_sparse | pr_services/credential_system/task_bundle_manager.py | ninemoreminutes/openassign-server | train | 0 |
6886fba10bdf115c4faf2c56c6f7f24405dd76dc | [
"self.all_under_hierarchy = all_under_hierarchy\nself.compact_version = compact_version\nself.consecutive_failures = consecutive_failures\nself.environment = environment\nself.exclude_users_within_alert_threshold = exclude_users_within_alert_threshold\nself.group_by = group_by\nself.health_status = health_status\ns... | <|body_start_0|>
self.all_under_hierarchy = all_under_hierarchy
self.compact_version = compact_version
self.consecutive_failures = consecutive_failures
self.environment = environment
self.exclude_users_within_alert_threshold = exclude_users_within_alert_threshold
self.gro... | Implementation of the 'SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters' model. TODO: type description here. Attributes: all_under_hierarchy (bool): Specifies if subtenants of the given tenants should be considered for report generation. compact_version (string): Specifies the Cohe... | SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters:
"""Implementation of the 'SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters' model. TODO: type description here. Attributes: all_under_hierarchy (bool): Specifies if subten... | stack_v2_sparse_classes_75kplus_train_000907 | 8,990 | permissive | [
{
"docstring": "Constructor for the SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters class",
"name": "__init__",
"signature": "def __init__(self, all_under_hierarchy=None, compact_version=None, consecutive_failures=None, environment=None, exclude_users_within_alert_... | 2 | stack_v2_sparse_classes_30k_train_046576 | Implement the Python class `SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters` described below.
Class description:
Implementation of the 'SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters' model. TODO: type description here. Attributes: all_unde... | Implement the Python class `SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters` described below.
Class description:
Implementation of the 'SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters' model. TODO: type description here. Attributes: all_unde... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters:
"""Implementation of the 'SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters' model. TODO: type description here. Attributes: all_under_hierarchy (bool): Specifies if subten... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters:
"""Implementation of the 'SchedulerProto_SchedulerJob_ScheduleJobParameters_ReportJobParameter_Report_Parameters' model. TODO: type description here. Attributes: all_under_hierarchy (bool): Specifies if subtenants of the g... | the_stack_v2_python_sparse | cohesity_management_sdk/models/scheduler_proto_scheduler_job_schedule_job_parameters_report_job_parameter_report_parameters.py | cohesity/management-sdk-python | train | 24 |
1e355e32f09d4aaeb7f755e55e7c95da330b3f70 | [
"try:\n tree = ast.parse(expr)\nexcept SyntaxError:\n raise ValueError(_('Illegal syntax in equation'))\nself.visit(tree)",
"if node.func.id in allowedFunctions:\n super().generic_visit(node)\nelse:\n raise ValueError(_('Illegal function present: {0}').format(node.func.id))",
"if type(node).__name__... | <|body_start_0|>
try:
tree = ast.parse(expr)
except SyntaxError:
raise ValueError(_('Illegal syntax in equation'))
self.visit(tree)
<|end_body_0|>
<|body_start_1|>
if node.func.id in allowedFunctions:
super().generic_visit(node)
else:
... | Class to check that only safe functions are used in an eval expression. Raises a ValueError if unsafe or non-numeric operations are present. Ref. stackoverflow.com questions 10661079 and 12523516 | SafeEvalChecker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SafeEvalChecker:
"""Class to check that only safe functions are used in an eval expression. Raises a ValueError if unsafe or non-numeric operations are present. Ref. stackoverflow.com questions 10661079 and 12523516"""
def check(self, expr):
"""Check the given expression for non-nume... | stack_v2_sparse_classes_75kplus_train_000908 | 21,625 | no_license | [
{
"docstring": "Check the given expression for non-numeric operations. Arguments: expr -- the expression string to check",
"name": "check",
"signature": "def check(self, expr)"
},
{
"docstring": "Check for allowed functions only. Arguments: node -- the ast node being checked",
"name": "visit... | 3 | stack_v2_sparse_classes_30k_train_037720 | Implement the Python class `SafeEvalChecker` described below.
Class description:
Class to check that only safe functions are used in an eval expression. Raises a ValueError if unsafe or non-numeric operations are present. Ref. stackoverflow.com questions 10661079 and 12523516
Method signatures and docstrings:
- def c... | Implement the Python class `SafeEvalChecker` described below.
Class description:
Class to check that only safe functions are used in an eval expression. Raises a ValueError if unsafe or non-numeric operations are present. Ref. stackoverflow.com questions 10661079 and 12523516
Method signatures and docstrings:
- def c... | c9429496e8ed15116746a23f3a90f262cf54f755 | <|skeleton|>
class SafeEvalChecker:
"""Class to check that only safe functions are used in an eval expression. Raises a ValueError if unsafe or non-numeric operations are present. Ref. stackoverflow.com questions 10661079 and 12523516"""
def check(self, expr):
"""Check the given expression for non-nume... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SafeEvalChecker:
"""Class to check that only safe functions are used in an eval expression. Raises a ValueError if unsafe or non-numeric operations are present. Ref. stackoverflow.com questions 10661079 and 12523516"""
def check(self, expr):
"""Check the given expression for non-numeric operation... | the_stack_v2_python_sparse | source/matheval.py | doug-101/TreeLine | train | 121 |
82f08ea102e9fdd8022048f6cca8fbabbf4324f3 | [
"n = len(nums)\nif n == 0:\n return 0\ndp = [0] * n\ndp[0] = 1\nmax_len = 1\nfor i in range(1, n):\n max_val = 0\n for j in range(i):\n if nums[i] > nums[j]:\n max_val = max(max_val, dp[j])\n dp[i] = max_val + 1\n max_len = max(max_len, dp[i])\nreturn max_len",
"n = len(nums)\nif ... | <|body_start_0|>
n = len(nums)
if n == 0:
return 0
dp = [0] * n
dp[0] = 1
max_len = 1
for i in range(1, n):
max_val = 0
for j in range(i):
if nums[i] > nums[j]:
max_val = max(max_val, dp[j])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
"""input| nums: List[int] output| int"""
<|body_0|>
def lengthOfLIS_bisec(self, nums):
"""input| nums: List[int] output| int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
if n == 0:
... | stack_v2_sparse_classes_75kplus_train_000909 | 1,740 | no_license | [
{
"docstring": "input| nums: List[int] output| int",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums)"
},
{
"docstring": "input| nums: List[int] output| int",
"name": "lengthOfLIS_bisec",
"signature": "def lengthOfLIS_bisec(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_053167 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): input| nums: List[int] output| int
- def lengthOfLIS_bisec(self, nums): input| nums: List[int] output| int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): input| nums: List[int] output| int
- def lengthOfLIS_bisec(self, nums): input| nums: List[int] output| int
<|skeleton|>
class Solution:
def len... | 8290ad1c763d9f7c7f7bed63426b4769b34fd2fc | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
"""input| nums: List[int] output| int"""
<|body_0|>
def lengthOfLIS_bisec(self, nums):
"""input| nums: List[int] output| int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def lengthOfLIS(self, nums):
"""input| nums: List[int] output| int"""
n = len(nums)
if n == 0:
return 0
dp = [0] * n
dp[0] = 1
max_len = 1
for i in range(1, n):
max_val = 0
for j in range(i):
... | the_stack_v2_python_sparse | dp_300_lengthOfLIS.py | screnary/Algorithm_python | train | 0 | |
a79e5de7854b46710b57fcd83a8dabe7b0b69fe7 | [
"self.user = user\nself.auth = passwordMD5\nself.enc = passwordDES\nself.host = host\nself.port = port",
"if number:\n oid += '.' + str(number)\ntry:\n errorIndication, errorStatus, errorIndex, varBinds = next(getCmd(SnmpEngine(), UsmUserData(self.user, self.auth, self.enc), UdpTransportTarget((self.host, s... | <|body_start_0|>
self.user = user
self.auth = passwordMD5
self.enc = passwordDES
self.host = host
self.port = port
<|end_body_0|>
<|body_start_1|>
if number:
oid += '.' + str(number)
try:
errorIndication, errorStatus, errorIndex, varBinds ... | SnmpWrapper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnmpWrapper:
def __init__(self, host, user, passwordMD5, passwordDES, port=161):
"""Create a new snmp connection wrapper for a host. This wrapper uses SNMPv3 with MD for authentification and DES for encryption. :param host: Host or IP to connect to :param host: str :param port: Port used... | stack_v2_sparse_classes_75kplus_train_000910 | 7,826 | permissive | [
{
"docstring": "Create a new snmp connection wrapper for a host. This wrapper uses SNMPv3 with MD for authentification and DES for encryption. :param host: Host or IP to connect to :param host: str :param port: Port used for the snmp connection :type port: int :param user: User used for the snmp connection :typ... | 3 | stack_v2_sparse_classes_30k_test_000975 | Implement the Python class `SnmpWrapper` described below.
Class description:
Implement the SnmpWrapper class.
Method signatures and docstrings:
- def __init__(self, host, user, passwordMD5, passwordDES, port=161): Create a new snmp connection wrapper for a host. This wrapper uses SNMPv3 with MD for authentification a... | Implement the Python class `SnmpWrapper` described below.
Class description:
Implement the SnmpWrapper class.
Method signatures and docstrings:
- def __init__(self, host, user, passwordMD5, passwordDES, port=161): Create a new snmp connection wrapper for a host. This wrapper uses SNMPv3 with MD for authentification a... | e4c552023334f709b9586f664b7e049036133d33 | <|skeleton|>
class SnmpWrapper:
def __init__(self, host, user, passwordMD5, passwordDES, port=161):
"""Create a new snmp connection wrapper for a host. This wrapper uses SNMPv3 with MD for authentification and DES for encryption. :param host: Host or IP to connect to :param host: str :param port: Port used... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SnmpWrapper:
def __init__(self, host, user, passwordMD5, passwordDES, port=161):
"""Create a new snmp connection wrapper for a host. This wrapper uses SNMPv3 with MD for authentification and DES for encryption. :param host: Host or IP to connect to :param host: str :param port: Port used for the snmp ... | the_stack_v2_python_sparse | src/insalata/helper/SnmpWrapper.py | tumi8/INSALATA | train | 6 | |
f2ab0baafcf21bf6dc1e3bfda234c637c301cbf3 | [
"tag_slug = slug.capitalize()\ntry:\n tag = Tag.objects.get(TagSlug=tag_slug)\nexcept:\n self.NOT_FOUND_RESP = Response({tag_slug: 'Tag Not Found'}, status=status.HTTP_404_NOT_FOUND)\n return None\nreturn tag",
"tag = self.get_object(slug)\nif tag is None:\n return self.NOT_FOUND_RESP\nserializer = Ta... | <|body_start_0|>
tag_slug = slug.capitalize()
try:
tag = Tag.objects.get(TagSlug=tag_slug)
except:
self.NOT_FOUND_RESP = Response({tag_slug: 'Tag Not Found'}, status=status.HTTP_404_NOT_FOUND)
return None
return tag
<|end_body_0|>
<|body_start_1|>
... | Inhereits APIView class to encapsulate Read(GET), Update(PUT) and Delete(DELETE) operations on the model/table Tag given a specific tag id(unique) or tag name (unique). | TagViewForSlug | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagViewForSlug:
"""Inhereits APIView class to encapsulate Read(GET), Update(PUT) and Delete(DELETE) operations on the model/table Tag given a specific tag id(unique) or tag name (unique)."""
def get_object(self, slug):
"""Fetch an instance based on its primary key ie slug from the Ta... | stack_v2_sparse_classes_75kplus_train_000911 | 20,756 | no_license | [
{
"docstring": "Fetch an instance based on its primary key ie slug from the Tag table If not found return None :param id: slug of the instance which needs to be fetched :return: Tag instance with given tag_slug. If not found returns None",
"name": "get_object",
"signature": "def get_object(self, slug)"
... | 4 | null | Implement the Python class `TagViewForSlug` described below.
Class description:
Inhereits APIView class to encapsulate Read(GET), Update(PUT) and Delete(DELETE) operations on the model/table Tag given a specific tag id(unique) or tag name (unique).
Method signatures and docstrings:
- def get_object(self, slug): Fetch... | Implement the Python class `TagViewForSlug` described below.
Class description:
Inhereits APIView class to encapsulate Read(GET), Update(PUT) and Delete(DELETE) operations on the model/table Tag given a specific tag id(unique) or tag name (unique).
Method signatures and docstrings:
- def get_object(self, slug): Fetch... | 83d4abe6966f0ed51b288b3910b4dc28e564af0a | <|skeleton|>
class TagViewForSlug:
"""Inhereits APIView class to encapsulate Read(GET), Update(PUT) and Delete(DELETE) operations on the model/table Tag given a specific tag id(unique) or tag name (unique)."""
def get_object(self, slug):
"""Fetch an instance based on its primary key ie slug from the Ta... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TagViewForSlug:
"""Inhereits APIView class to encapsulate Read(GET), Update(PUT) and Delete(DELETE) operations on the model/table Tag given a specific tag id(unique) or tag name (unique)."""
def get_object(self, slug):
"""Fetch an instance based on its primary key ie slug from the Tag table If no... | the_stack_v2_python_sparse | NGKARTAPI/product/views.py | SmrutiRanjan-Ai/django | train | 0 |
d5604ada7e78e07f2205c8a5118f62c18e8075e2 | [
"interpolation = EnvironmentAwareInterpolation()\nkwargs['interpolation'] = interpolation\nConfigParser.__init__(self, *args, **kwargs)",
"result = ConfigParser.read(self, filenames)\nfor section in self.sections():\n original_section = section\n matches = self.r.search(section)\n while matches:\n ... | <|body_start_0|>
interpolation = EnvironmentAwareInterpolation()
kwargs['interpolation'] = interpolation
ConfigParser.__init__(self, *args, **kwargs)
<|end_body_0|>
<|body_start_1|>
result = ConfigParser.read(self, filenames)
for section in self.sections():
original_... | A subclass of ConfigParser which allows %env:VAR% interpolation via the get method. | EnvironmentAwareConfigParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnvironmentAwareConfigParser:
"""A subclass of ConfigParser which allows %env:VAR% interpolation via the get method."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Init with our specific interpolation class (for Python 3)"""
<|body_0|>
def read(self, filena... | stack_v2_sparse_classes_75kplus_train_000912 | 2,766 | permissive | [
{
"docstring": "Init with our specific interpolation class (for Python 3)",
"name": "__init__",
"signature": "def __init__(self, *args: Any, **kwargs: Any) -> None"
},
{
"docstring": "Load a config file and do environment variable interpolation on the section names.",
"name": "read",
"si... | 2 | stack_v2_sparse_classes_30k_train_010639 | Implement the Python class `EnvironmentAwareConfigParser` described below.
Class description:
A subclass of ConfigParser which allows %env:VAR% interpolation via the get method.
Method signatures and docstrings:
- def __init__(self, *args: Any, **kwargs: Any) -> None: Init with our specific interpolation class (for P... | Implement the Python class `EnvironmentAwareConfigParser` described below.
Class description:
A subclass of ConfigParser which allows %env:VAR% interpolation via the get method.
Method signatures and docstrings:
- def __init__(self, *args: Any, **kwargs: Any) -> None: Init with our specific interpolation class (for P... | 925cb9802c55a6da1c75eb946c2cee47b9c522fc | <|skeleton|>
class EnvironmentAwareConfigParser:
"""A subclass of ConfigParser which allows %env:VAR% interpolation via the get method."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Init with our specific interpolation class (for Python 3)"""
<|body_0|>
def read(self, filena... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EnvironmentAwareConfigParser:
"""A subclass of ConfigParser which allows %env:VAR% interpolation via the get method."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Init with our specific interpolation class (for Python 3)"""
interpolation = EnvironmentAwareInterpolation()
... | the_stack_v2_python_sparse | simplemonitor/util/envconfig.py | jamesoff/simplemonitor | train | 412 |
88e125f438ae3090f38e8b5781fbac7aa9b9bb5a | [
"N = len(s)\nif N == 0:\n return ''\nP = [[False for _ in range(N)] for _ in range(N)]\nmaxLen = 1\nstart = 0\nfor i in range(N):\n if i + 1 < N and s[i] == s[i + 1]:\n P[i][i + 1] = True\n start = i\n maxLen = 2\n P[i][i] = True\ni = 0\nj = 2\nwhile j < N:\n ii, jj = (i, j)\n wh... | <|body_start_0|>
N = len(s)
if N == 0:
return ''
P = [[False for _ in range(N)] for _ in range(N)]
maxLen = 1
start = 0
for i in range(N):
if i + 1 < N and s[i] == s[i + 1]:
P[i][i + 1] = True
start = i
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome2(self, s):
"""中心扩展法"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
N = len(s)
if N == 0:
return ''
P = [[False for... | stack_v2_sparse_classes_75kplus_train_000913 | 1,978 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
},
{
"docstring": "中心扩展法",
"name": "longestPalindrome2",
"signature": "def longestPalindrome2(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_027701 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: str
- def longestPalindrome2(self, s): 中心扩展法 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: str
- def longestPalindrome2(self, s): 中心扩展法
<|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":t... | 837957ea22aa07ce28a6c23ea0419bd2011e1f88 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome2(self, s):
"""中心扩展法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
N = len(s)
if N == 0:
return ''
P = [[False for _ in range(N)] for _ in range(N)]
maxLen = 1
start = 0
for i in range(N):
if i + 1 < N and s[i] == s[i + 1]:
... | the_stack_v2_python_sparse | 字节/最长回文子串.py | 2226171237/Algorithmpractice | train | 0 | |
d8a8fff0da5e5825219ba76be5d2832f41b8caee | [
"self.master = master\nself.mode = Tk.StringVar()\nself.mode_list = ['Create Level', 'Edit Existing Level']\nself.mode_string = ''\nself.lw = Tk.StringVar()\nself.newFrame = None\nself.createWidgets()",
"textLabel = Tk.Label(self.master, text='Select Editor Mode:')\ndropDown = Tk.OptionMenu(self.master, self.mode... | <|body_start_0|>
self.master = master
self.mode = Tk.StringVar()
self.mode_list = ['Create Level', 'Edit Existing Level']
self.mode_string = ''
self.lw = Tk.StringVar()
self.newFrame = None
self.createWidgets()
<|end_body_0|>
<|body_start_1|>
textLabel = ... | mainGUI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class mainGUI:
def __init__(self, master):
"""Initialisation params: master -> root window"""
<|body_0|>
def createWidgets(self):
"""Create widgets for frontend. The widgets are: -> An OptionMenu for choosing between the NEW and EDIT modes -> A field for entering level wid... | stack_v2_sparse_classes_75kplus_train_000914 | 3,921 | no_license | [
{
"docstring": "Initialisation params: master -> root window",
"name": "__init__",
"signature": "def __init__(self, master)"
},
{
"docstring": "Create widgets for frontend. The widgets are: -> An OptionMenu for choosing between the NEW and EDIT modes -> A field for entering level width -> Variou... | 6 | stack_v2_sparse_classes_30k_train_025938 | Implement the Python class `mainGUI` described below.
Class description:
Implement the mainGUI class.
Method signatures and docstrings:
- def __init__(self, master): Initialisation params: master -> root window
- def createWidgets(self): Create widgets for frontend. The widgets are: -> An OptionMenu for choosing betw... | Implement the Python class `mainGUI` described below.
Class description:
Implement the mainGUI class.
Method signatures and docstrings:
- def __init__(self, master): Initialisation params: master -> root window
- def createWidgets(self): Create widgets for frontend. The widgets are: -> An OptionMenu for choosing betw... | b5ef6160b958ece204edf68bad21f8ae39441fa7 | <|skeleton|>
class mainGUI:
def __init__(self, master):
"""Initialisation params: master -> root window"""
<|body_0|>
def createWidgets(self):
"""Create widgets for frontend. The widgets are: -> An OptionMenu for choosing between the NEW and EDIT modes -> A field for entering level wid... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class mainGUI:
def __init__(self, master):
"""Initialisation params: master -> root window"""
self.master = master
self.mode = Tk.StringVar()
self.mode_list = ['Create Level', 'Edit Existing Level']
self.mode_string = ''
self.lw = Tk.StringVar()
self.newFrame ... | the_stack_v2_python_sparse | worldShifter/levelEditor/ed_GUI.py | sanskarchand/python-projects | train | 0 | |
1e12abe768d49dc83d9be7a54e613fd872dbd4dd | [
"idx: Dict[int, Dict[str, Union[int, List[int]]]] = {}\nfor i, v in enumerate(numbers):\n if v not in idx:\n idx[v] = {'count': 1, 'index': [i]}\n else:\n idx[v]['count'] += 1\n idx[v]['index'].append(i)\nindex1, index2 = (0, 0)\nfor k in idx.keys():\n dif = target - k\n if dif in i... | <|body_start_0|>
idx: Dict[int, Dict[str, Union[int, List[int]]]] = {}
for i, v in enumerate(numbers):
if v not in idx:
idx[v] = {'count': 1, 'index': [i]}
else:
idx[v]['count'] += 1
idx[v]['index'].append(i)
index1, index2 ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, numbers: List[int], target: int) -> List[int]:
"""哈希表。"""
<|body_0|>
def twoSum2(self, numbers: List[int], target: int) -> List[int]:
"""二分查找。"""
<|body_1|>
def twoSum3(self, numbers: List[int], target: int) -> List[int]:
... | stack_v2_sparse_classes_75kplus_train_000915 | 4,429 | no_license | [
{
"docstring": "哈希表。",
"name": "twoSum",
"signature": "def twoSum(self, numbers: List[int], target: int) -> List[int]"
},
{
"docstring": "二分查找。",
"name": "twoSum2",
"signature": "def twoSum2(self, numbers: List[int], target: int) -> List[int]"
},
{
"docstring": "双指针。",
"name"... | 3 | stack_v2_sparse_classes_30k_train_050025 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, numbers: List[int], target: int) -> List[int]: 哈希表。
- def twoSum2(self, numbers: List[int], target: int) -> List[int]: 二分查找。
- def twoSum3(self, numbers: List[in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, numbers: List[int], target: int) -> List[int]: 哈希表。
- def twoSum2(self, numbers: List[int], target: int) -> List[int]: 二分查找。
- def twoSum3(self, numbers: List[in... | 6932d69353b94ec824dd0ddc86a92453f6673232 | <|skeleton|>
class Solution:
def twoSum(self, numbers: List[int], target: int) -> List[int]:
"""哈希表。"""
<|body_0|>
def twoSum2(self, numbers: List[int], target: int) -> List[int]:
"""二分查找。"""
<|body_1|>
def twoSum3(self, numbers: List[int], target: int) -> List[int]:
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def twoSum(self, numbers: List[int], target: int) -> List[int]:
"""哈希表。"""
idx: Dict[int, Dict[str, Union[int, List[int]]]] = {}
for i, v in enumerate(numbers):
if v not in idx:
idx[v] = {'count': 1, 'index': [i]}
else:
... | the_stack_v2_python_sparse | 0167_two-sum-ii-input-array-is-sorted.py | Nigirimeshi/leetcode | train | 0 | |
f2263da1efa2f3c54374278435ca6b894b9a57de | [
"if not root:\n return 0\nnodes = [root.left, root.right]\nif not any(nodes):\n return 1\nmin_depth = float(inf)\nfor node in nodes:\n if node:\n min_depth = min(self.get_depth(node), min_depth)\nreturn min_depth",
"if not root:\n return 0\nelse:\n stack, min_depth = ([(root.left, root.right... | <|body_start_0|>
if not root:
return 0
nodes = [root.left, root.right]
if not any(nodes):
return 1
min_depth = float(inf)
for node in nodes:
if node:
min_depth = min(self.get_depth(node), min_depth)
return min_depth
<|en... | MinimumDepth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MinimumDepth:
def get_min_depth(self, root: TreeNode) -> int:
"""Approach: Recursion using DFS. Time Complexity: O(n) Space Complexity: O(log n) :param root: :return:"""
<|body_0|>
def get_min_depth_(self, root: TreeNode) -> int:
"""Approach: Iterative using DFS Time... | stack_v2_sparse_classes_75kplus_train_000916 | 1,967 | no_license | [
{
"docstring": "Approach: Recursion using DFS. Time Complexity: O(n) Space Complexity: O(log n) :param root: :return:",
"name": "get_min_depth",
"signature": "def get_min_depth(self, root: TreeNode) -> int"
},
{
"docstring": "Approach: Iterative using DFS Time Complexity: O(n) Space Complexity: ... | 3 | stack_v2_sparse_classes_30k_train_025814 | Implement the Python class `MinimumDepth` described below.
Class description:
Implement the MinimumDepth class.
Method signatures and docstrings:
- def get_min_depth(self, root: TreeNode) -> int: Approach: Recursion using DFS. Time Complexity: O(n) Space Complexity: O(log n) :param root: :return:
- def get_min_depth_... | Implement the Python class `MinimumDepth` described below.
Class description:
Implement the MinimumDepth class.
Method signatures and docstrings:
- def get_min_depth(self, root: TreeNode) -> int: Approach: Recursion using DFS. Time Complexity: O(n) Space Complexity: O(log n) :param root: :return:
- def get_min_depth_... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class MinimumDepth:
def get_min_depth(self, root: TreeNode) -> int:
"""Approach: Recursion using DFS. Time Complexity: O(n) Space Complexity: O(log n) :param root: :return:"""
<|body_0|>
def get_min_depth_(self, root: TreeNode) -> int:
"""Approach: Iterative using DFS Time... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MinimumDepth:
def get_min_depth(self, root: TreeNode) -> int:
"""Approach: Recursion using DFS. Time Complexity: O(n) Space Complexity: O(log n) :param root: :return:"""
if not root:
return 0
nodes = [root.left, root.right]
if not any(nodes):
return 1
... | the_stack_v2_python_sparse | data_structures/tree_node/min_depth_of_bt.py | Shiv2157k/leet_code | train | 1 | |
ecc3be5a2b181f74b4e1fe0bdcb3588478a0684f | [
"if isinstance(waitkeyval, tuple):\n waitkeyval = waitkeyval[0]\nif is_raw:\n i = waitkeyval & 255\nreturn KeyBoardInput._key_dic[i]",
"if isinstance(waitkeyval, (tuple, dict, set)):\n for x in waitkeyval:\n if isinstance(waitkeyval, int):\n waitkeyval = x\n break\nspecial = ... | <|body_start_0|>
if isinstance(waitkeyval, tuple):
waitkeyval = waitkeyval[0]
if is_raw:
i = waitkeyval & 255
return KeyBoardInput._key_dic[i]
<|end_body_0|>
<|body_start_1|>
if isinstance(waitkeyval, (tuple, dict, set)):
for x in waitkeyval:
... | user keyboard input key_dic is a dictionary containing numbers as keys with the ASCII character Also includes the special keys: 'return', 'backspace', 'escape', 'tab', 'space', 'unknowable', 'none' | KeyBoardInput | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KeyBoardInput:
"""user keyboard input key_dic is a dictionary containing numbers as keys with the ASCII character Also includes the special keys: 'return', 'backspace', 'escape', 'tab', 'space', 'unknowable', 'none'"""
def get_pressed_key(waitkeyval, is_raw=True):
"""(int, bool) -> s... | stack_v2_sparse_classes_75kplus_train_000917 | 2,605 | no_license | [
{
"docstring": "(int, bool) -> str Pass in waitkey result, returning the string representation of the key. i: return value of waitkey is_raw: if true, is the raw return value otherwise assumes already converted to the character ord value, e.g. from view.show() Returns: string representation of keypress, also: '... | 2 | stack_v2_sparse_classes_30k_train_051933 | Implement the Python class `KeyBoardInput` described below.
Class description:
user keyboard input key_dic is a dictionary containing numbers as keys with the ASCII character Also includes the special keys: 'return', 'backspace', 'escape', 'tab', 'space', 'unknowable', 'none'
Method signatures and docstrings:
- def g... | Implement the Python class `KeyBoardInput` described below.
Class description:
user keyboard input key_dic is a dictionary containing numbers as keys with the ASCII character Also includes the special keys: 'return', 'backspace', 'escape', 'tab', 'space', 'unknowable', 'none'
Method signatures and docstrings:
- def g... | 9123aa6baf538b662143b9098d963d55165e8409 | <|skeleton|>
class KeyBoardInput:
"""user keyboard input key_dic is a dictionary containing numbers as keys with the ASCII character Also includes the special keys: 'return', 'backspace', 'escape', 'tab', 'space', 'unknowable', 'none'"""
def get_pressed_key(waitkeyval, is_raw=True):
"""(int, bool) -> s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KeyBoardInput:
"""user keyboard input key_dic is a dictionary containing numbers as keys with the ASCII character Also includes the special keys: 'return', 'backspace', 'escape', 'tab', 'space', 'unknowable', 'none'"""
def get_pressed_key(waitkeyval, is_raw=True):
"""(int, bool) -> str Pass in wa... | the_stack_v2_python_sparse | opencvlib/display_utils.py | gmonkman/python | train | 0 |
aca94b38994dc8519c694dbc68e165ce2bad0d2b | [
"if not matrix or matrix == []:\n self.n = 0\n self.m = 0\n return\nn = len(matrix)\nm = len(matrix[0])\ns = [[0] * (m + 1) for i in xrange(n + 1)]\nfor i in xrange(n):\n for j in xrange(m):\n if i == 0 and j == 0:\n s[1][1] = matrix[0][0]\n elif i == 0:\n s[1][j + 1]... | <|body_start_0|>
if not matrix or matrix == []:
self.n = 0
self.m = 0
return
n = len(matrix)
m = len(matrix[0])
s = [[0] * (m + 1) for i in xrange(n + 1)]
for i in xrange(n):
for j in xrange(m):
if i == 0 and j == 0:... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :ty... | stack_v2_sparse_classes_75kplus_train_000918 | 2,158 | no_license | [
{
"docstring": "initialize your data structure here. :type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": "sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :type row2: int :type col2: int :rtyp... | 2 | stack_v2_sparse_classes_30k_train_038465 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): initialize your data structure here. :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): initialize your data structure here. :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)... | 588a86282b8cc74fa14d810eb3a532c5c3e6de81 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :ty... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
if not matrix or matrix == []:
self.n = 0
self.m = 0
return
n = len(matrix)
m = len(matrix[0])
s = [[0] * (m + 1) for i in... | the_stack_v2_python_sparse | solutions/RangeSumQuery2DImmutable.py | howardhe0329/leetcode | train | 0 | |
9e7198773e890ea71b2e20a49e20088106d647cc | [
"super(TargetGroup, self).__init__()\nself.arn = None\nself.region = vpc.region\nself.name = 'pkb-%s' % FLAGS.run_uri\nself.protocol = 'TCP'\nself.port = port\nself.vpc_id = vpc.id",
"create_cmd = util.AWS_PREFIX + ['--region', self.region, 'elbv2', 'create-target-group', '--target-type', 'ip', '--name', self.nam... | <|body_start_0|>
super(TargetGroup, self).__init__()
self.arn = None
self.region = vpc.region
self.name = 'pkb-%s' % FLAGS.run_uri
self.protocol = 'TCP'
self.port = port
self.vpc_id = vpc.id
<|end_body_0|>
<|body_start_1|>
create_cmd = util.AWS_PREFIX + [... | Class represeting an AWS target group. | TargetGroup | [
"Classpath-exception-2.0",
"BSD-3-Clause",
"AGPL-3.0-only",
"MIT",
"GPL-2.0-only",
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TargetGroup:
"""Class represeting an AWS target group."""
def __init__(self, vpc, port):
"""Initializes the TargetGroup object. Args: vpc: AwsVpc object which contains the targets for load balancing. port: The internal port that the load balancer connects to."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_000919 | 4,687 | permissive | [
{
"docstring": "Initializes the TargetGroup object. Args: vpc: AwsVpc object which contains the targets for load balancing. port: The internal port that the load balancer connects to.",
"name": "__init__",
"signature": "def __init__(self, vpc, port)"
},
{
"docstring": "Create the target group.",... | 3 | stack_v2_sparse_classes_30k_train_001873 | Implement the Python class `TargetGroup` described below.
Class description:
Class represeting an AWS target group.
Method signatures and docstrings:
- def __init__(self, vpc, port): Initializes the TargetGroup object. Args: vpc: AwsVpc object which contains the targets for load balancing. port: The internal port tha... | Implement the Python class `TargetGroup` described below.
Class description:
Class represeting an AWS target group.
Method signatures and docstrings:
- def __init__(self, vpc, port): Initializes the TargetGroup object. Args: vpc: AwsVpc object which contains the targets for load balancing. port: The internal port tha... | d0699f32998898757b036704fba39e5471641f01 | <|skeleton|>
class TargetGroup:
"""Class represeting an AWS target group."""
def __init__(self, vpc, port):
"""Initializes the TargetGroup object. Args: vpc: AwsVpc object which contains the targets for load balancing. port: The internal port that the load balancer connects to."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TargetGroup:
"""Class represeting an AWS target group."""
def __init__(self, vpc, port):
"""Initializes the TargetGroup object. Args: vpc: AwsVpc object which contains the targets for load balancing. port: The internal port that the load balancer connects to."""
super(TargetGroup, self)._... | the_stack_v2_python_sparse | perfkitbenchmarker/providers/aws/aws_load_balancer.py | GoogleCloudPlatform/PerfKitBenchmarker | train | 1,923 |
029f983c1c0e3a0df9262e61b26d7df8f58ca8b1 | [
"if window_size_in_steps < 1:\n raise ValueError('window_size_in_steps has to be >= 1.')\nif abs(x) <= window_size_in_steps / 2:\n return 1.0\nelse:\n return 0.0",
"if window_size_in_steps < 1:\n raise ValueError('window_size_in_steps has to be >= 1.')\nreturn max(0.0, window_size_in_steps / 2 - abs(x... | <|body_start_0|>
if window_size_in_steps < 1:
raise ValueError('window_size_in_steps has to be >= 1.')
if abs(x) <= window_size_in_steps / 2:
return 1.0
else:
return 0.0
<|end_body_0|>
<|body_start_1|>
if window_size_in_steps < 1:
raise Va... | Kernel function to use for smoothing. | SmoothingKernel | [
"CC-BY-4.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmoothingKernel:
"""Kernel function to use for smoothing."""
def rectangular_kernel(self, x, window_size_in_steps):
"""Rectangular kernel for moving window average. All values in window are equally weighted. Args: x: Distance to kernel center in steps. window_size_in_steps: Size of t... | stack_v2_sparse_classes_75kplus_train_000920 | 17,872 | permissive | [
{
"docstring": "Rectangular kernel for moving window average. All values in window are equally weighted. Args: x: Distance to kernel center in steps. window_size_in_steps: Size of the window to average over. Returns: Unnormalized weight to use for averaging, e.g. in `np.average()`. Raises: ValueError: If window... | 3 | null | Implement the Python class `SmoothingKernel` described below.
Class description:
Kernel function to use for smoothing.
Method signatures and docstrings:
- def rectangular_kernel(self, x, window_size_in_steps): Rectangular kernel for moving window average. All values in window are equally weighted. Args: x: Distance t... | Implement the Python class `SmoothingKernel` described below.
Class description:
Kernel function to use for smoothing.
Method signatures and docstrings:
- def rectangular_kernel(self, x, window_size_in_steps): Rectangular kernel for moving window average. All values in window are equally weighted. Args: x: Distance t... | 320a49f768cea27200044c0d12f394aa6c795feb | <|skeleton|>
class SmoothingKernel:
"""Kernel function to use for smoothing."""
def rectangular_kernel(self, x, window_size_in_steps):
"""Rectangular kernel for moving window average. All values in window are equally weighted. Args: x: Distance to kernel center in steps. window_size_in_steps: Size of t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SmoothingKernel:
"""Kernel function to use for smoothing."""
def rectangular_kernel(self, x, window_size_in_steps):
"""Rectangular kernel for moving window average. All values in window are equally weighted. Args: x: Distance to kernel center in steps. window_size_in_steps: Size of the window to ... | the_stack_v2_python_sparse | aqt/utils/report_utils.py | afcarl/google-research | train | 1 |
7bd87f386cc2cd3f38d1b8a78386c0c119b0db3c | [
"self.name = name\nself.account = account\nself.balance = Decimal(0)",
"if self.balance >= 0 and amount >= 0:\n self.balance = self.balance + Decimal(amount)\nelse:\n raise ValueError('balance and amount must be positive')",
"if amount <= self.balance:\n self.balance -= Decimal(amount)\nelse:\n rais... | <|body_start_0|>
self.name = name
self.account = account
self.balance = Decimal(0)
<|end_body_0|>
<|body_start_1|>
if self.balance >= 0 and amount >= 0:
self.balance = self.balance + Decimal(amount)
else:
raise ValueError('balance and amount must be posit... | A class that represents a customer (python docs follows Numpy/Scipy format) ... Attributes ---------- name: str customer name account: str customer's account balance: decimal.Decimal customer's balance Methods ------- deposit(amount) a customer deposits money withdraw(amount) a customer withdraw money | Customer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Customer:
"""A class that represents a customer (python docs follows Numpy/Scipy format) ... Attributes ---------- name: str customer name account: str customer's account balance: decimal.Decimal customer's balance Methods ------- deposit(amount) a customer deposits money withdraw(amount) a custo... | stack_v2_sparse_classes_75kplus_train_000921 | 1,891 | no_license | [
{
"docstring": "Parameters ---------- name: str customer name account: str customer's account balance: decimal.Decimal customer's balance",
"name": "__init__",
"signature": "def __init__(self, name, account)"
},
{
"docstring": "Deposit money Parameters ---------- amount: float amount of money th... | 3 | stack_v2_sparse_classes_30k_train_002694 | Implement the Python class `Customer` described below.
Class description:
A class that represents a customer (python docs follows Numpy/Scipy format) ... Attributes ---------- name: str customer name account: str customer's account balance: decimal.Decimal customer's balance Methods ------- deposit(amount) a customer ... | Implement the Python class `Customer` described below.
Class description:
A class that represents a customer (python docs follows Numpy/Scipy format) ... Attributes ---------- name: str customer name account: str customer's account balance: decimal.Decimal customer's balance Methods ------- deposit(amount) a customer ... | 11ef8a7885d1e5a1f16788a934f3bb8d62a01dc2 | <|skeleton|>
class Customer:
"""A class that represents a customer (python docs follows Numpy/Scipy format) ... Attributes ---------- name: str customer name account: str customer's account balance: decimal.Decimal customer's balance Methods ------- deposit(amount) a customer deposits money withdraw(amount) a custo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Customer:
"""A class that represents a customer (python docs follows Numpy/Scipy format) ... Attributes ---------- name: str customer name account: str customer's account balance: decimal.Decimal customer's balance Methods ------- deposit(amount) a customer deposits money withdraw(amount) a customer withdraw ... | the_stack_v2_python_sparse | exam/1/python-ci-gitlab/cathay/sample/customer.py | daniel-qa/Python | train | 0 |
326e9dc664a17bc35cf07a23e0cf61b8bc552c25 | [
"if not matrix or not matrix[0]:\n return False\nm, n = (len(matrix), len(matrix[0]))\n\ndef binary_search(matrix, target, start, vertical):\n low = start\n high = len(matrix[0]) - 1 if vertical else len(matrix) - 1\n while low <= high:\n mid = low + high >> 1\n if vertical:\n i... | <|body_start_0|>
if not matrix or not matrix[0]:
return False
m, n = (len(matrix), len(matrix[0]))
def binary_search(matrix, target, start, vertical):
low = start
high = len(matrix[0]) - 1 if vertical else len(matrix) - 1
while low <= high:
... | Solution | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def searchMatrix_v2(self, matrix, target):
"""Divide and conquer"""
<|body_1|>
def searchMatrix_v3(self, matrix, target):
... | stack_v2_sparse_classes_75kplus_train_000922 | 3,598 | permissive | [
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool",
"name": "searchMatrix",
"signature": "def searchMatrix(self, matrix, target)"
},
{
"docstring": "Divide and conquer",
"name": "searchMatrix_v2",
"signature": "def searchMatrix_v2(self, matrix, target)"
},
... | 3 | stack_v2_sparse_classes_30k_train_013066 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def searchMatrix_v2(self, matrix, target): Divide and conquer
- def searchM... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def searchMatrix_v2(self, matrix, target): Divide and conquer
- def searchM... | 226cecde136531341ce23cdf88529345be1912fc | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def searchMatrix_v2(self, matrix, target):
"""Divide and conquer"""
<|body_1|>
def searchMatrix_v3(self, matrix, target):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
if not matrix or not matrix[0]:
return False
m, n = (len(matrix), len(matrix[0]))
def binary_search(matrix, target, start, vertical):
lo... | the_stack_v2_python_sparse | Leetcode/Intermediate/Sort and search/240_Search_a_2D_Matrix_II.py | ZR-Huang/AlgorithmsPractices | train | 1 | |
cabcec521549e3ec11f22cad761fb02c2191fedf | [
"super().__init__(config=config, parent=tool, **kwargs)\nif self.output_path is None:\n raise ValueError('Please specify an output path to save pedestal file')\nself.ped_obj = TCPedestalMaker(self.n_tms, self.n_blocks, self.n_samples, self.diagnosis, self.std)\nself.ped_stats = None",
"telid = 0\nwaveforms = e... | <|body_start_0|>
super().__init__(config=config, parent=tool, **kwargs)
if self.output_path is None:
raise ValueError('Please specify an output path to save pedestal file')
self.ped_obj = TCPedestalMaker(self.n_tms, self.n_blocks, self.n_samples, self.diagnosis, self.std)
sel... | PedestalMaker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PedestalMaker:
def __init__(self, config, tool, **kwargs):
"""Generator of Pedestal files. Parameters ---------- config : traitlets.loader.Config Configuration specified by config file or cmdline arguments. Used to set traitlet values. Set to None if no configuration to pass. tool : ctap... | stack_v2_sparse_classes_75kplus_train_000923 | 7,556 | no_license | [
{
"docstring": "Generator of Pedestal files. Parameters ---------- config : traitlets.loader.Config Configuration specified by config file or cmdline arguments. Used to set traitlet values. Set to None if no configuration to pass. tool : ctapipe.core.Tool Tool executable that is calling this component. Passes t... | 3 | stack_v2_sparse_classes_30k_train_048960 | Implement the Python class `PedestalMaker` described below.
Class description:
Implement the PedestalMaker class.
Method signatures and docstrings:
- def __init__(self, config, tool, **kwargs): Generator of Pedestal files. Parameters ---------- config : traitlets.loader.Config Configuration specified by config file o... | Implement the Python class `PedestalMaker` described below.
Class description:
Implement the PedestalMaker class.
Method signatures and docstrings:
- def __init__(self, config, tool, **kwargs): Generator of Pedestal files. Parameters ---------- config : traitlets.loader.Config Configuration specified by config file o... | 7238646f0793f9d9b0544be6723152d540b061a3 | <|skeleton|>
class PedestalMaker:
def __init__(self, config, tool, **kwargs):
"""Generator of Pedestal files. Parameters ---------- config : traitlets.loader.Config Configuration specified by config file or cmdline arguments. Used to set traitlet values. Set to None if no configuration to pass. tool : ctap... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PedestalMaker:
def __init__(self, config, tool, **kwargs):
"""Generator of Pedestal files. Parameters ---------- config : traitlets.loader.Config Configuration specified by config file or cmdline arguments. Used to set traitlet values. Set to None if no configuration to pass. tool : ctapipe.core.Tool ... | the_stack_v2_python_sparse | targetpipe/calib/camera/makers.py | watsonjj/targetpipe | train | 0 | |
eae4089a43a2dcbe6b7c68a01ce7d96711c48aba | [
"self.bit = x\nfor i in range(len(x)):\n j = i | i + 1\n if j < len(x):\n x[j] += x[i]",
"while idx < len(self.bit):\n self.bit[idx] += x\n idx |= idx + 1",
"x = 0\nwhile end:\n x += self.bit[end - 1]\n end &= end - 1\nreturn x",
"idx = -1\nfor d in reversed(range(len(self.bit).bit_le... | <|body_start_0|>
self.bit = x
for i in range(len(x)):
j = i | i + 1
if j < len(x):
x[j] += x[i]
<|end_body_0|>
<|body_start_1|>
while idx < len(self.bit):
self.bit[idx] += x
idx |= idx + 1
<|end_body_1|>
<|body_start_2|>
x... | FenwickTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FenwickTree:
def __init__(self, x):
"""transform list into BIT"""
<|body_0|>
def update(self, idx, x):
"""updates bit[idx] += x"""
<|body_1|>
def query(self, end):
"""calc sum(bit[:end])"""
<|body_2|>
def find_kth_smallest(self, k):
... | stack_v2_sparse_classes_75kplus_train_000924 | 2,618 | no_license | [
{
"docstring": "transform list into BIT",
"name": "__init__",
"signature": "def __init__(self, x)"
},
{
"docstring": "updates bit[idx] += x",
"name": "update",
"signature": "def update(self, idx, x)"
},
{
"docstring": "calc sum(bit[:end])",
"name": "query",
"signature": "... | 4 | stack_v2_sparse_classes_30k_train_035322 | Implement the Python class `FenwickTree` described below.
Class description:
Implement the FenwickTree class.
Method signatures and docstrings:
- def __init__(self, x): transform list into BIT
- def update(self, idx, x): updates bit[idx] += x
- def query(self, end): calc sum(bit[:end])
- def find_kth_smallest(self, k... | Implement the Python class `FenwickTree` described below.
Class description:
Implement the FenwickTree class.
Method signatures and docstrings:
- def __init__(self, x): transform list into BIT
- def update(self, idx, x): updates bit[idx] += x
- def query(self, end): calc sum(bit[:end])
- def find_kth_smallest(self, k... | 57f473ca84735f9312913967e20a3ac0da32baa8 | <|skeleton|>
class FenwickTree:
def __init__(self, x):
"""transform list into BIT"""
<|body_0|>
def update(self, idx, x):
"""updates bit[idx] += x"""
<|body_1|>
def query(self, end):
"""calc sum(bit[:end])"""
<|body_2|>
def find_kth_smallest(self, k):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FenwickTree:
def __init__(self, x):
"""transform list into BIT"""
self.bit = x
for i in range(len(x)):
j = i | i + 1
if j < len(x):
x[j] += x[i]
def update(self, idx, x):
"""updates bit[idx] += x"""
while idx < len(self.bit):... | the_stack_v2_python_sparse | codeforces/current/c1354d/task.py | x3mka/code-contests-python | train | 0 | |
8fe039124424c07db37838c0d9e9b4cee4f1c452 | [
"base.Action.__init__(self, self.__loadColourMap)\nself.__overlayList = overlayList\nself.__displayCtx = displayCtx",
"import wx\napp = wx.GetApp()\nloadDir = fslsettings.read('fsleyes.loadcolourmapdir', os.getcwd())\ndlg = wx.FileDialog(app.GetTopWindow(), defaultDir=loadDir, message=strings.messages[self, 'load... | <|body_start_0|>
base.Action.__init__(self, self.__loadColourMap)
self.__overlayList = overlayList
self.__displayCtx = displayCtx
<|end_body_0|>
<|body_start_1|>
import wx
app = wx.GetApp()
loadDir = fslsettings.read('fsleyes.loadcolourmapdir', os.getcwd())
dlg =... | The ``LoadColourMapAction`` allows the user to select a colour map file and give it a name. The loaded colour map is then registered with the :mod:`.colourmaps` module. The user is also given the option to permanently save the loaded colour map in *FSLeyes*. | LoadColourMapAction | [
"BSD-3-Clause",
"CC-BY-3.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoadColourMapAction:
"""The ``LoadColourMapAction`` allows the user to select a colour map file and give it a name. The loaded colour map is then registered with the :mod:`.colourmaps` module. The user is also given the option to permanently save the loaded colour map in *FSLeyes*."""
def __... | stack_v2_sparse_classes_75kplus_train_000925 | 4,121 | permissive | [
{
"docstring": "Create a ``LoadColourMapAction``. :arg overlayList: The :class:`.OverlayList`. :arg displayCtx: The :class:`.DisplayContext`.",
"name": "__init__",
"signature": "def __init__(self, overlayList, displayCtx)"
},
{
"docstring": "This method does the following: 1. Prompts the user to... | 2 | stack_v2_sparse_classes_30k_train_034751 | Implement the Python class `LoadColourMapAction` described below.
Class description:
The ``LoadColourMapAction`` allows the user to select a colour map file and give it a name. The loaded colour map is then registered with the :mod:`.colourmaps` module. The user is also given the option to permanently save the loaded ... | Implement the Python class `LoadColourMapAction` described below.
Class description:
The ``LoadColourMapAction`` allows the user to select a colour map file and give it a name. The loaded colour map is then registered with the :mod:`.colourmaps` module. The user is also given the option to permanently save the loaded ... | 46ccb4fe2b2346eb57576247f49714032b61307a | <|skeleton|>
class LoadColourMapAction:
"""The ``LoadColourMapAction`` allows the user to select a colour map file and give it a name. The loaded colour map is then registered with the :mod:`.colourmaps` module. The user is also given the option to permanently save the loaded colour map in *FSLeyes*."""
def __... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LoadColourMapAction:
"""The ``LoadColourMapAction`` allows the user to select a colour map file and give it a name. The loaded colour map is then registered with the :mod:`.colourmaps` module. The user is also given the option to permanently save the loaded colour map in *FSLeyes*."""
def __init__(self, ... | the_stack_v2_python_sparse | fsleyes/actions/loadcolourmap.py | sanjayankur31/fsleyes | train | 1 |
2fec4ee9ce3ded47e52c00c37b63a97f8cc07fe4 | [
"from .search import AsyncSearch\ns = AsyncSearch(client=self, index_name=index_name)\nreturn s",
"from .graph import AsyncGraph\ng = AsyncGraph(client=self, name=index_name)\nreturn g"
] | <|body_start_0|>
from .search import AsyncSearch
s = AsyncSearch(client=self, index_name=index_name)
return s
<|end_body_0|>
<|body_start_1|>
from .graph import AsyncGraph
g = AsyncGraph(client=self, name=index_name)
return g
<|end_body_1|>
| AsyncRedisModuleCommands | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsyncRedisModuleCommands:
def ft(self, index_name='idx'):
"""Access the search namespace, providing support for redis search."""
<|body_0|>
def graph(self, index_name='idx'):
"""Access the graph namespace, providing support for redis graph data."""
<|body_1|>... | stack_v2_sparse_classes_75kplus_train_000926 | 2,454 | permissive | [
{
"docstring": "Access the search namespace, providing support for redis search.",
"name": "ft",
"signature": "def ft(self, index_name='idx')"
},
{
"docstring": "Access the graph namespace, providing support for redis graph data.",
"name": "graph",
"signature": "def graph(self, index_nam... | 2 | stack_v2_sparse_classes_30k_train_053666 | Implement the Python class `AsyncRedisModuleCommands` described below.
Class description:
Implement the AsyncRedisModuleCommands class.
Method signatures and docstrings:
- def ft(self, index_name='idx'): Access the search namespace, providing support for redis search.
- def graph(self, index_name='idx'): Access the g... | Implement the Python class `AsyncRedisModuleCommands` described below.
Class description:
Implement the AsyncRedisModuleCommands class.
Method signatures and docstrings:
- def ft(self, index_name='idx'): Access the search namespace, providing support for redis search.
- def graph(self, index_name='idx'): Access the g... | e3de026a90ef2cc35a5b68934029a0ef2a5b2f53 | <|skeleton|>
class AsyncRedisModuleCommands:
def ft(self, index_name='idx'):
"""Access the search namespace, providing support for redis search."""
<|body_0|>
def graph(self, index_name='idx'):
"""Access the graph namespace, providing support for redis graph data."""
<|body_1|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AsyncRedisModuleCommands:
def ft(self, index_name='idx'):
"""Access the search namespace, providing support for redis search."""
from .search import AsyncSearch
s = AsyncSearch(client=self, index_name=index_name)
return s
def graph(self, index_name='idx'):
"""Acces... | the_stack_v2_python_sparse | redis/commands/redismodules.py | redis/redis-py | train | 2,213 | |
efbc6c26430848fcfa68f46bfd4e68c41043a680 | [
"self.client.login(username=TEST_LOGIN_USERNAME, password=TEST_LOGIN_PASSWORD)\nresponse = self.client.post(reverse('edit_request_priority'), {'request_path': reverse('home'), 'request_priority': 1}, HTTP_X_REQUESTED_WITH='XMLHttpRequest')\npriority_entry = RequestPriorityEntry.objects.get(pk=1)\nself.client.get(re... | <|body_start_0|>
self.client.login(username=TEST_LOGIN_USERNAME, password=TEST_LOGIN_PASSWORD)
response = self.client.post(reverse('edit_request_priority'), {'request_path': reverse('home'), 'request_priority': 1}, HTTP_X_REQUESTED_WITH='XMLHttpRequest')
priority_entry = RequestPriorityEntry.obj... | TestChangeRequestPriority | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestChangeRequestPriority:
def test_ajax_edition_priority_valid(self):
"""Test for valid data submission"""
<|body_0|>
def test_ajax_edition_priority_invalid(self):
"""Test for invalid data submission"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_000927 | 11,236 | no_license | [
{
"docstring": "Test for valid data submission",
"name": "test_ajax_edition_priority_valid",
"signature": "def test_ajax_edition_priority_valid(self)"
},
{
"docstring": "Test for invalid data submission",
"name": "test_ajax_edition_priority_invalid",
"signature": "def test_ajax_edition_p... | 2 | stack_v2_sparse_classes_30k_train_012828 | Implement the Python class `TestChangeRequestPriority` described below.
Class description:
Implement the TestChangeRequestPriority class.
Method signatures and docstrings:
- def test_ajax_edition_priority_valid(self): Test for valid data submission
- def test_ajax_edition_priority_invalid(self): Test for invalid data... | Implement the Python class `TestChangeRequestPriority` described below.
Class description:
Implement the TestChangeRequestPriority class.
Method signatures and docstrings:
- def test_ajax_edition_priority_valid(self): Test for valid data submission
- def test_ajax_edition_priority_invalid(self): Test for invalid data... | ad157bc53f250959daca5f100fc746cbe8e94193 | <|skeleton|>
class TestChangeRequestPriority:
def test_ajax_edition_priority_valid(self):
"""Test for valid data submission"""
<|body_0|>
def test_ajax_edition_priority_invalid(self):
"""Test for invalid data submission"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestChangeRequestPriority:
def test_ajax_edition_priority_valid(self):
"""Test for valid data submission"""
self.client.login(username=TEST_LOGIN_USERNAME, password=TEST_LOGIN_PASSWORD)
response = self.client.post(reverse('edit_request_priority'), {'request_path': reverse('home'), 'req... | the_stack_v2_python_sparse | pyta/tests.py | TTask/cups42 | train | 0 | |
1a7f0598d93ab83e7cac77ffa0c7c811e0bab141 | [
"tests = ('AAPL', 'AMZN', 'CSCO', 'GOOGL', 'IBM', 'MSFT', 'ORCL')\nfor test in tests:\n fundamentals = Fundamentals(test)\n self.assertTrue(isinstance(fundamentals, Fundamentals))",
"Test = collections.namedtuple('Test', 'date field expected_value')\ntests = (Test('2013-05-03', 'total_debt', 14460465000), T... | <|body_start_0|>
tests = ('AAPL', 'AMZN', 'CSCO', 'GOOGL', 'IBM', 'MSFT', 'ORCL')
for test in tests:
fundamentals = Fundamentals(test)
self.assertTrue(isinstance(fundamentals, Fundamentals))
<|end_body_0|>
<|body_start_1|>
Test = collections.namedtuple('Test', 'date fiel... | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
def test_construction_and_file_layouts(self):
"""test all issuers"""
<|body_0|>
def test_get_ok(self):
"""test just AAPL"""
<|body_1|>
def test_get_bad(self):
"""test just AAPL"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_000928 | 4,022 | no_license | [
{
"docstring": "test all issuers",
"name": "test_construction_and_file_layouts",
"signature": "def test_construction_and_file_layouts(self)"
},
{
"docstring": "test just AAPL",
"name": "test_get_ok",
"signature": "def test_get_ok(self)"
},
{
"docstring": "test just AAPL",
"na... | 3 | stack_v2_sparse_classes_30k_test_002387 | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def test_construction_and_file_layouts(self): test all issuers
- def test_get_ok(self): test just AAPL
- def test_get_bad(self): test just AAPL | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def test_construction_and_file_layouts(self): test all issuers
- def test_get_ok(self): test just AAPL
- def test_get_bad(self): test just AAPL
<|skeleton|>
class Test:
def test_co... | 3535bd46bff602fc3ba35c080d38b30e75a97fe7 | <|skeleton|>
class Test:
def test_construction_and_file_layouts(self):
"""test all issuers"""
<|body_0|>
def test_get_ok(self):
"""test just AAPL"""
<|body_1|>
def test_get_bad(self):
"""test just AAPL"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test:
def test_construction_and_file_layouts(self):
"""test all issuers"""
tests = ('AAPL', 'AMZN', 'CSCO', 'GOOGL', 'IBM', 'MSFT', 'ORCL')
for test in tests:
fundamentals = Fundamentals(test)
self.assertTrue(isinstance(fundamentals, Fundamentals))
def test... | the_stack_v2_python_sparse | seven/Fundamentals.py | rlowrance/test7 | train | 2 | |
a36dc2e0645ab9f77162c1f386572ee23bd06ed7 | [
"visit = set()\nwhile head:\n if head not in visit:\n visit.add(head)\n else:\n return True\n head = head.next\nreturn False",
"pslow = head\npfast = head\nwhile pfast and pfast.next:\n pslow = pslow.next\n pfast = pfast.next.next\n if pslow == pfast:\n return True\nreturn F... | <|body_start_0|>
visit = set()
while head:
if head not in visit:
visit.add(head)
else:
return True
head = head.next
return False
<|end_body_0|>
<|body_start_1|>
pslow = head
pfast = head
while pfast and ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasCycle(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def hasCycle2(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
visit = set()
while head:
if h... | stack_v2_sparse_classes_75kplus_train_000929 | 3,101 | no_license | [
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "hasCycle",
"signature": "def hasCycle(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "hasCycle2",
"signature": "def hasCycle2(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_037734 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasCycle(self, head): :type head: ListNode :rtype: bool
- def hasCycle2(self, head): :type head: ListNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasCycle(self, head): :type head: ListNode :rtype: bool
- def hasCycle2(self, head): :type head: ListNode :rtype: bool
<|skeleton|>
class Solution:
def hasCycle(self, h... | fcf79f4f7354454a28b60ef3c845dd6defddbf42 | <|skeleton|>
class Solution:
def hasCycle(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def hasCycle2(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def hasCycle(self, head):
""":type head: ListNode :rtype: bool"""
visit = set()
while head:
if head not in visit:
visit.add(head)
else:
return True
head = head.next
return False
def hasCycle2(sel... | the_stack_v2_python_sparse | python_data_structure/python_List/leetcode.py | liunlll/LiuLeetCode | train | 0 | |
7c3f55e49c21ef73190fc2778eb1d36ff10ffde9 | [
"def dfs(i, remains: List[int]):\n if i == n + 1:\n return 1\n cnt = 0\n for j in range(1, n + 1):\n if remains[j] is None and (i % j == 0 or j % i == 0):\n remains[j] = i\n cnt += dfs(i + 1, remains)\n remains[j] = None\n return cnt\nreturn dfs(1, [None] *... | <|body_start_0|>
def dfs(i, remains: List[int]):
if i == n + 1:
return 1
cnt = 0
for j in range(1, n + 1):
if remains[j] is None and (i % j == 0 or j % i == 0):
remains[j] = i
cnt += dfs(i + 1, remains)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countArrangement(self, n: int) -> int:
"""DFS using a list"""
<|body_0|>
def countArrangement(self, n: int) -> int:
"""DFS using a binary number to make argument hashable for caching"""
<|body_1|>
def countArrangement(self, n: int) -> int:
... | stack_v2_sparse_classes_75kplus_train_000930 | 2,867 | no_license | [
{
"docstring": "DFS using a list",
"name": "countArrangement",
"signature": "def countArrangement(self, n: int) -> int"
},
{
"docstring": "DFS using a binary number to make argument hashable for caching",
"name": "countArrangement",
"signature": "def countArrangement(self, n: int) -> int... | 3 | stack_v2_sparse_classes_30k_train_026368 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countArrangement(self, n: int) -> int: DFS using a list
- def countArrangement(self, n: int) -> int: DFS using a binary number to make argument hashable for caching
- def cou... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countArrangement(self, n: int) -> int: DFS using a list
- def countArrangement(self, n: int) -> int: DFS using a binary number to make argument hashable for caching
- def cou... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def countArrangement(self, n: int) -> int:
"""DFS using a list"""
<|body_0|>
def countArrangement(self, n: int) -> int:
"""DFS using a binary number to make argument hashable for caching"""
<|body_1|>
def countArrangement(self, n: int) -> int:
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countArrangement(self, n: int) -> int:
"""DFS using a list"""
def dfs(i, remains: List[int]):
if i == n + 1:
return 1
cnt = 0
for j in range(1, n + 1):
if remains[j] is None and (i % j == 0 or j % i == 0):
... | the_stack_v2_python_sparse | leetcode/solved/526_Beautiful_Arrangement/solution.py | sungminoh/algorithms | train | 0 | |
2704c06c675e5399e382153e58b1c61b38180c88 | [
"self.sleeptime = sleep_param\nself.looplimit = looplimit\nself.temperatureTask = TempSensorEmulatorTask.TempSensorEmulator()",
"i = 0\nif self.sleeptime < 0 or self.looplimit < 0:\n logging.error('looplimit or sleeptime is less than 0')\n return False\nif self.enableTempEmulatorAdapter == True:\n while ... | <|body_start_0|>
self.sleeptime = sleep_param
self.looplimit = looplimit
self.temperatureTask = TempSensorEmulatorTask.TempSensorEmulator()
<|end_body_0|>
<|body_start_1|>
i = 0
if self.sleeptime < 0 or self.looplimit < 0:
logging.error('looplimit or sleeptime is les... | This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations | TempEmulatorAdapter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TempEmulatorAdapter:
"""This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations"""
def __init__(self, sleep_param=sleepDefault, looplimit=loopDefault):
"""Constructor which sets... | stack_v2_sparse_classes_75kplus_train_000931 | 1,894 | no_license | [
{
"docstring": "Constructor which sets the sleep timer for the thread, and a looplimit if needed.",
"name": "__init__",
"signature": "def __init__(self, sleep_param=sleepDefault, looplimit=loopDefault)"
},
{
"docstring": "This method runs the emulation if enableTempEmulatorAdapter is set to True... | 2 | stack_v2_sparse_classes_30k_train_048324 | Implement the Python class `TempEmulatorAdapter` described below.
Class description:
This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations
Method signatures and docstrings:
- def __init__(self, sleep_param=sle... | Implement the Python class `TempEmulatorAdapter` described below.
Class description:
This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations
Method signatures and docstrings:
- def __init__(self, sleep_param=sle... | dfd5fd8c757cae8b1306ae3e4eb2cfc9bf124fee | <|skeleton|>
class TempEmulatorAdapter:
"""This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations"""
def __init__(self, sleep_param=sleepDefault, looplimit=loopDefault):
"""Constructor which sets... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TempEmulatorAdapter:
"""This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations"""
def __init__(self, sleep_param=sleepDefault, looplimit=loopDefault):
"""Constructor which sets the sleep ti... | the_stack_v2_python_sparse | apps/labs/module02/TempEmulatorAdapter.py | mnk400/iot-device | train | 0 |
b7e74093c18b7634df7dea95aec4fa6b204e422f | [
"stop_words = read_stop_words(stop_word_file) if stop_word_file is not None else []\nself.input_fields = frozenset(input_fields)\nself.nlp = SpacyTextParser(model_name, stop_words=stop_words, remove_punct=remove_punct, sent_split=False, keep_only_alpha_num=keep_only_alpha_num, lower_case=lower_case, enable_pos=enab... | <|body_start_0|>
stop_words = read_stop_words(stop_word_file) if stop_word_file is not None else []
self.input_fields = frozenset(input_fields)
self.nlp = SpacyTextParser(model_name, stop_words=stop_words, remove_punct=remove_punct, sent_split=False, keep_only_alpha_num=keep_only_alpha_num, lowe... | SpacyTextProcessor | [
"BSD-2-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpacyTextProcessor:
def __init__(self, input_fields: list, model_name, stop_word_file=None, remove_punct=True, keep_only_alpha_num=False, lower_case=True, enable_pos=True):
"""Constructor. :param input_fields: a list of field names to process :param model_name a name of the spacy model t... | stack_v2_sparse_classes_75kplus_train_000932 | 3,075 | permissive | [
{
"docstring": "Constructor. :param input_fields: a list of field names to process :param model_name a name of the spacy model to use, e.g., en_core_web_sm :param stop_word_file the name of the stop word file :param remove_punct a bool flag indicating if the punctuation tokens need to be removed :param keep_onl... | 2 | null | Implement the Python class `SpacyTextProcessor` described below.
Class description:
Implement the SpacyTextProcessor class.
Method signatures and docstrings:
- def __init__(self, input_fields: list, model_name, stop_word_file=None, remove_punct=True, keep_only_alpha_num=False, lower_case=True, enable_pos=True): Const... | Implement the Python class `SpacyTextProcessor` described below.
Class description:
Implement the SpacyTextProcessor class.
Method signatures and docstrings:
- def __init__(self, input_fields: list, model_name, stop_word_file=None, remove_punct=True, keep_only_alpha_num=False, lower_case=True, enable_pos=True): Const... | 0bd3e06735ff705731fb6cee62d3486276beccdf | <|skeleton|>
class SpacyTextProcessor:
def __init__(self, input_fields: list, model_name, stop_word_file=None, remove_punct=True, keep_only_alpha_num=False, lower_case=True, enable_pos=True):
"""Constructor. :param input_fields: a list of field names to process :param model_name a name of the spacy model t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SpacyTextProcessor:
def __init__(self, input_fields: list, model_name, stop_word_file=None, remove_punct=True, keep_only_alpha_num=False, lower_case=True, enable_pos=True):
"""Constructor. :param input_fields: a list of field names to process :param model_name a name of the spacy model to use, e.g., e... | the_stack_v2_python_sparse | flexneuart/ir_datasets/spacy.py | oaqa/FlexNeuART | train | 156 | |
3fc43052b05e733fc669cfd053336b2825dc65f9 | [
"version_url = self._get_base_version_url()\nresp, body = self.raw_request(version_url, 'GET')\nself._error_checker(resp, body)\nself.expected_success(300, resp.status)\nbody = json.loads(body)\nreturn rest_client.ResponseBody(resp, body)",
"version = 'v%s' % version\nsupported = ['SUPPORTED', 'CURRENT']\nversion... | <|body_start_0|>
version_url = self._get_base_version_url()
resp, body = self.raw_request(version_url, 'GET')
self._error_checker(resp, body)
self.expected_success(300, resp.status)
body = json.loads(body)
return rest_client.ResponseBody(resp, body)
<|end_body_0|>
<|body... | VersionsClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VersionsClient:
def list_versions(self):
"""List API versions"""
<|body_0|>
def has_version(self, version):
"""Return True if a version is supported."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
version_url = self._get_base_version_url()
... | stack_v2_sparse_classes_75kplus_train_000933 | 1,531 | permissive | [
{
"docstring": "List API versions",
"name": "list_versions",
"signature": "def list_versions(self)"
},
{
"docstring": "Return True if a version is supported.",
"name": "has_version",
"signature": "def has_version(self, version)"
}
] | 2 | stack_v2_sparse_classes_30k_train_042348 | Implement the Python class `VersionsClient` described below.
Class description:
Implement the VersionsClient class.
Method signatures and docstrings:
- def list_versions(self): List API versions
- def has_version(self, version): Return True if a version is supported. | Implement the Python class `VersionsClient` described below.
Class description:
Implement the VersionsClient class.
Method signatures and docstrings:
- def list_versions(self): List API versions
- def has_version(self, version): Return True if a version is supported.
<|skeleton|>
class VersionsClient:
def list_... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class VersionsClient:
def list_versions(self):
"""List API versions"""
<|body_0|>
def has_version(self, version):
"""Return True if a version is supported."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VersionsClient:
def list_versions(self):
"""List API versions"""
version_url = self._get_base_version_url()
resp, body = self.raw_request(version_url, 'GET')
self._error_checker(resp, body)
self.expected_success(300, resp.status)
body = json.loads(body)
... | the_stack_v2_python_sparse | tempest/lib/services/image/v2/versions_client.py | openstack/tempest | train | 270 | |
d1adea77ae57d3868dbe4b890712420fb8cda2cd | [
"self.max_proba = max_proba\nself.confident_threshold = confident_threshold\nself.top_n = top_n",
"if self.confident_threshold:\n return [list(np.where(np.array(d) > self.confident_threshold)[0]) for d in data]\nelif self.max_proba:\n return [np.argmax(d) for d in data]\nelif self.top_n:\n return [np.arg... | <|body_start_0|>
self.max_proba = max_proba
self.confident_threshold = confident_threshold
self.top_n = top_n
<|end_body_0|>
<|body_start_1|>
if self.confident_threshold:
return [list(np.where(np.array(d) > self.confident_threshold)[0]) for d in data]
elif self.max_p... | Class implements probability to labels processing using the following ways: choosing one or top_n indices with maximal probability or choosing any number of indices which probabilities to belong with are higher than given confident threshold Args: max_proba: whether to choose label with maximal probability confident_th... | Proba2Labels | [
"Python-2.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Proba2Labels:
"""Class implements probability to labels processing using the following ways: choosing one or top_n indices with maximal probability or choosing any number of indices which probabilities to belong with are higher than given confident threshold Args: max_proba: whether to choose lab... | stack_v2_sparse_classes_75kplus_train_000934 | 3,194 | permissive | [
{
"docstring": "Initialize class with given parameters",
"name": "__init__",
"signature": "def __init__(self, max_proba: bool=None, confident_threshold: float=None, top_n: int=None, **kwargs) -> None"
},
{
"docstring": "Process probabilities to labels Args: data: list of vectors with probability... | 2 | stack_v2_sparse_classes_30k_train_053696 | Implement the Python class `Proba2Labels` described below.
Class description:
Class implements probability to labels processing using the following ways: choosing one or top_n indices with maximal probability or choosing any number of indices which probabilities to belong with are higher than given confident threshold... | Implement the Python class `Proba2Labels` described below.
Class description:
Class implements probability to labels processing using the following ways: choosing one or top_n indices with maximal probability or choosing any number of indices which probabilities to belong with are higher than given confident threshold... | 65f69dfb898f5444cc2c98ae03ec7b3f44266df2 | <|skeleton|>
class Proba2Labels:
"""Class implements probability to labels processing using the following ways: choosing one or top_n indices with maximal probability or choosing any number of indices which probabilities to belong with are higher than given confident threshold Args: max_proba: whether to choose lab... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Proba2Labels:
"""Class implements probability to labels processing using the following ways: choosing one or top_n indices with maximal probability or choosing any number of indices which probabilities to belong with are higher than given confident threshold Args: max_proba: whether to choose label with maxim... | the_stack_v2_python_sparse | deeppavlov/models/classifiers/proba2labels.py | vintagexav/DeepPavlov | train | 2 |
9499948812698af51adb743a2b7d7b81c35dc7ea | [
"super(MultiTverskyLoss, self).__init__()\nself.alpha = alpha\nself.beta = beta\nself.gamma = gamma\nself.weights = weights",
"targets = targets.unsqueeze(1)\nnum_class = inputs.size(1)\nweight_losses = 0.0\nif self.weights is not None:\n assert len(self.weights) == num_class, 'number of classes should be equa... | <|body_start_0|>
super(MultiTverskyLoss, self).__init__()
self.alpha = alpha
self.beta = beta
self.gamma = gamma
self.weights = weights
<|end_body_0|>
<|body_start_1|>
targets = targets.unsqueeze(1)
num_class = inputs.size(1)
weight_losses = 0.0
i... | Tversky Loss for segmentation adaptive with multi class segmentation | MultiTverskyLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiTverskyLoss:
"""Tversky Loss for segmentation adaptive with multi class segmentation"""
def __init__(self, alpha=0.5, beta=0.5, gamma=1.0, weights=None):
""":param alpha (Tensor, float, optional): controls the penalty for false positives. :param beta (Tensor, float, optional): c... | stack_v2_sparse_classes_75kplus_train_000935 | 10,977 | permissive | [
{
"docstring": ":param alpha (Tensor, float, optional): controls the penalty for false positives. :param beta (Tensor, float, optional): controls the penalty for false negative. :param gamma (Tensor, float, optional): focal coefficient :param weights (Tensor, optional): a manual rescaling weight given to each c... | 2 | stack_v2_sparse_classes_30k_train_013794 | Implement the Python class `MultiTverskyLoss` described below.
Class description:
Tversky Loss for segmentation adaptive with multi class segmentation
Method signatures and docstrings:
- def __init__(self, alpha=0.5, beta=0.5, gamma=1.0, weights=None): :param alpha (Tensor, float, optional): controls the penalty for ... | Implement the Python class `MultiTverskyLoss` described below.
Class description:
Tversky Loss for segmentation adaptive with multi class segmentation
Method signatures and docstrings:
- def __init__(self, alpha=0.5, beta=0.5, gamma=1.0, weights=None): :param alpha (Tensor, float, optional): controls the penalty for ... | d83c9f6dfcfe36573fe77fbdfec4fda23ded9180 | <|skeleton|>
class MultiTverskyLoss:
"""Tversky Loss for segmentation adaptive with multi class segmentation"""
def __init__(self, alpha=0.5, beta=0.5, gamma=1.0, weights=None):
""":param alpha (Tensor, float, optional): controls the penalty for false positives. :param beta (Tensor, float, optional): c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiTverskyLoss:
"""Tversky Loss for segmentation adaptive with multi class segmentation"""
def __init__(self, alpha=0.5, beta=0.5, gamma=1.0, weights=None):
""":param alpha (Tensor, float, optional): controls the penalty for false positives. :param beta (Tensor, float, optional): controls the p... | the_stack_v2_python_sparse | utils/criterions.py | thanhhau097/brats-dmf-bifpn | train | 4 |
3c377f2d4253f4f70d94bd3d010c48886e8edddf | [
"redis_conn = get_redis_connection(settings.HISTORY_CACHE_ALIAS)\nuser_id = request.user.id\nhistory_browse_key = RedisKey.HISTORY_BROWSE_KEY.format(user_id=user_id)\nsku_ids = redis_conn.lrange(history_browse_key, 0, -1)\nskus = []\nfor sku_id in sku_ids:\n sku = SKU.objects.get(id=sku_id)\n skus.append({'id... | <|body_start_0|>
redis_conn = get_redis_connection(settings.HISTORY_CACHE_ALIAS)
user_id = request.user.id
history_browse_key = RedisKey.HISTORY_BROWSE_KEY.format(user_id=user_id)
sku_ids = redis_conn.lrange(history_browse_key, 0, -1)
skus = []
for sku_id in sku_ids:
... | 用户浏览记录 | UserBrowseHistory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserBrowseHistory:
"""用户浏览记录"""
def get(self, request):
"""获取用户浏览记录"""
<|body_0|>
def post(self, request):
"""保存用户浏览记录"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
redis_conn = get_redis_connection(settings.HISTORY_CACHE_ALIAS)
user_i... | stack_v2_sparse_classes_75kplus_train_000936 | 21,636 | permissive | [
{
"docstring": "获取用户浏览记录",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "保存用户浏览记录",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_046215 | Implement the Python class `UserBrowseHistory` described below.
Class description:
用户浏览记录
Method signatures and docstrings:
- def get(self, request): 获取用户浏览记录
- def post(self, request): 保存用户浏览记录 | Implement the Python class `UserBrowseHistory` described below.
Class description:
用户浏览记录
Method signatures and docstrings:
- def get(self, request): 获取用户浏览记录
- def post(self, request): 保存用户浏览记录
<|skeleton|>
class UserBrowseHistory:
"""用户浏览记录"""
def get(self, request):
"""获取用户浏览记录"""
<|body_... | b1aa6da9e3d0af3e6aa7ff2587148845469aefad | <|skeleton|>
class UserBrowseHistory:
"""用户浏览记录"""
def get(self, request):
"""获取用户浏览记录"""
<|body_0|>
def post(self, request):
"""保存用户浏览记录"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserBrowseHistory:
"""用户浏览记录"""
def get(self, request):
"""获取用户浏览记录"""
redis_conn = get_redis_connection(settings.HISTORY_CACHE_ALIAS)
user_id = request.user.id
history_browse_key = RedisKey.HISTORY_BROWSE_KEY.format(user_id=user_id)
sku_ids = redis_conn.lrange(his... | the_stack_v2_python_sparse | meiduo_mall/meiduo_mall/apps/users/views.py | HuiDBK/meiduo_project | train | 0 |
ea3f3eaec893a324aea469678def793c22ab8495 | [
"self.parser = templateparser.Parser()\nself.parse = self.parser.ParseString\nself.tmpl = templateparser.Template",
"self.parser['template'] = self.tmpl('This is a subtemplate by [name].')\ntemplate = '{{ inline template }}'\nexpected = 'This is a subtemplate by Elmer.'\nself.assertEqual(self.parse(template, name... | <|body_start_0|>
self.parser = templateparser.Parser()
self.parse = self.parser.ParseString
self.tmpl = templateparser.Template
<|end_body_0|>
<|body_start_1|>
self.parser['template'] = self.tmpl('This is a subtemplate by [name].')
template = '{{ inline template }}'
expe... | TemplateParser properly handles the include statement. | TemplateInlining | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplateInlining:
"""TemplateParser properly handles the include statement."""
def setUp(self):
"""Sets up a testbed."""
<|body_0|>
def testInlineExisting(self):
"""{{ inline }} Parser will inline an already existing template reference"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_000937 | 37,443 | permissive | [
{
"docstring": "Sets up a testbed.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "{{ inline }} Parser will inline an already existing template reference",
"name": "testInlineExisting",
"signature": "def testInlineExisting(self)"
},
{
"docstring": "{{ inline ... | 3 | stack_v2_sparse_classes_30k_train_047376 | Implement the Python class `TemplateInlining` described below.
Class description:
TemplateParser properly handles the include statement.
Method signatures and docstrings:
- def setUp(self): Sets up a testbed.
- def testInlineExisting(self): {{ inline }} Parser will inline an already existing template reference
- def ... | Implement the Python class `TemplateInlining` described below.
Class description:
TemplateParser properly handles the include statement.
Method signatures and docstrings:
- def setUp(self): Sets up a testbed.
- def testInlineExisting(self): {{ inline }} Parser will inline an already existing template reference
- def ... | 6ee9b512b9a42ef313032e7b79f779b44da3c319 | <|skeleton|>
class TemplateInlining:
"""TemplateParser properly handles the include statement."""
def setUp(self):
"""Sets up a testbed."""
<|body_0|>
def testInlineExisting(self):
"""{{ inline }} Parser will inline an already existing template reference"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TemplateInlining:
"""TemplateParser properly handles the include statement."""
def setUp(self):
"""Sets up a testbed."""
self.parser = templateparser.Parser()
self.parse = self.parser.ParseString
self.tmpl = templateparser.Template
def testInlineExisting(self):
... | the_stack_v2_python_sparse | newweb/test_templateparser.py | edelooff/newWeb | train | 0 |
31dea531356445cca76fdb37e2fad0f7969500ab | [
"date = timezone.now()\norder = BuyProduct(full_name='Full Name Test', phone_number='123', country='TheCountry', postcode='902180', town_or_city='TheCity', street_address1='TheStreet', street_address2='TheStreetPart2', county='TheCounty', date=date)\nself.assertEqual(order.full_name, 'Full Name Test')\nself.assertE... | <|body_start_0|>
date = timezone.now()
order = BuyProduct(full_name='Full Name Test', phone_number='123', country='TheCountry', postcode='902180', town_or_city='TheCity', street_address1='TheStreet', street_address2='TheStreetPart2', county='TheCounty', date=date)
self.assertEqual(order.full_nam... | TestCheckoutModels | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCheckoutModels:
def test_buy_product(self):
"""Tests if the BuyProduct model really takes in the correct user information for an order"""
<|body_0|>
def test_order_as_string(self):
"""Tests if the string function of the BuyProduct model returns the right output""... | stack_v2_sparse_classes_75kplus_train_000938 | 3,582 | no_license | [
{
"docstring": "Tests if the BuyProduct model really takes in the correct user information for an order",
"name": "test_buy_product",
"signature": "def test_buy_product(self)"
},
{
"docstring": "Tests if the string function of the BuyProduct model returns the right output",
"name": "test_ord... | 4 | stack_v2_sparse_classes_30k_val_001122 | Implement the Python class `TestCheckoutModels` described below.
Class description:
Implement the TestCheckoutModels class.
Method signatures and docstrings:
- def test_buy_product(self): Tests if the BuyProduct model really takes in the correct user information for an order
- def test_order_as_string(self): Tests if... | Implement the Python class `TestCheckoutModels` described below.
Class description:
Implement the TestCheckoutModels class.
Method signatures and docstrings:
- def test_buy_product(self): Tests if the BuyProduct model really takes in the correct user information for an order
- def test_order_as_string(self): Tests if... | 4b2d560b4df459f36bb804f28eb488391a99b514 | <|skeleton|>
class TestCheckoutModels:
def test_buy_product(self):
"""Tests if the BuyProduct model really takes in the correct user information for an order"""
<|body_0|>
def test_order_as_string(self):
"""Tests if the string function of the BuyProduct model returns the right output""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestCheckoutModels:
def test_buy_product(self):
"""Tests if the BuyProduct model really takes in the correct user information for an order"""
date = timezone.now()
order = BuyProduct(full_name='Full Name Test', phone_number='123', country='TheCountry', postcode='902180', town_or_city='... | the_stack_v2_python_sparse | checkout/test_models.py | Code-Institute-Submissions/Milestone4-6 | train | 0 | |
fd200e4e0a8447a13e13fca06c73fd5904729cb0 | [
"departments = Department.query.join(Employee, isouter=True).group_by(Department.id).with_entities(func.round(func.ifnull(func.avg(Employee.salary), 0), 2).label('avg')).add_columns(Department.id.label('id'), Department.name.label('name')).all()\nlogger.info('List of departments: %s', departments)\nresponse = make_... | <|body_start_0|>
departments = Department.query.join(Employee, isouter=True).group_by(Department.id).with_entities(func.round(func.ifnull(func.avg(Employee.salary), 0), 2).label('avg')).add_columns(Department.id.label('id'), Department.name.label('name')).all()
logger.info('List of departments: %s', dep... | Resource class | DepartmentsResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DepartmentsResource:
"""Resource class"""
def get():
"""This static method exposes GET HTTP method. Request processing include select existing record from the database :return: response with HTML content"""
<|body_0|>
def post():
"""This static method exposes POS... | stack_v2_sparse_classes_75kplus_train_000939 | 1,994 | permissive | [
{
"docstring": "This static method exposes GET HTTP method. Request processing include select existing record from the database :return: response with HTML content",
"name": "get",
"signature": "def get()"
},
{
"docstring": "This static method exposes POST HTTP method. Request processing include... | 2 | stack_v2_sparse_classes_30k_train_048548 | Implement the Python class `DepartmentsResource` described below.
Class description:
Resource class
Method signatures and docstrings:
- def get(): This static method exposes GET HTTP method. Request processing include select existing record from the database :return: response with HTML content
- def post(): This stat... | Implement the Python class `DepartmentsResource` described below.
Class description:
Resource class
Method signatures and docstrings:
- def get(): This static method exposes GET HTTP method. Request processing include select existing record from the database :return: response with HTML content
- def post(): This stat... | 5e6e1620179f70dd13fbdaf2cabbefe5fac95aeb | <|skeleton|>
class DepartmentsResource:
"""Resource class"""
def get():
"""This static method exposes GET HTTP method. Request processing include select existing record from the database :return: response with HTML content"""
<|body_0|>
def post():
"""This static method exposes POS... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DepartmentsResource:
"""Resource class"""
def get():
"""This static method exposes GET HTTP method. Request processing include select existing record from the database :return: response with HTML content"""
departments = Department.query.join(Employee, isouter=True).group_by(Department.id... | the_stack_v2_python_sparse | department-app/service/department/departments.py | V1ckeyR/department | train | 2 |
98db11a1656cd611de44141938d7b25bbca452eb | [
"num_fractions = 16\nBED = np.array([range(num_fractions + 1)])\nx = BEDPredictorUpperBoundCorrect(BED)\nestimated = x.estimate(granularity=4)\nself.assertEqual(np.all(np.equal(estimated[0], range(num_fractions + 1))), True)",
"BED = np.array([[0, 20, 38, 54, 68, 80, 90, 98, 104, 108, 110, 111, 111, 111, 111, 111... | <|body_start_0|>
num_fractions = 16
BED = np.array([range(num_fractions + 1)])
x = BEDPredictorUpperBoundCorrect(BED)
estimated = x.estimate(granularity=4)
self.assertEqual(np.all(np.equal(estimated[0], range(num_fractions + 1))), True)
<|end_body_0|>
<|body_start_1|>
BE... | BEDPredictorUpperBoundCorrectTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BEDPredictorUpperBoundCorrectTest:
def test_case_BED_linear(self):
"""Testing BED approximation when BED values are linear."""
<|body_0|>
def test_case_BED_concave(self):
"""Testing BED approximation when BED values are arbitrary convex."""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus_train_000940 | 1,700 | no_license | [
{
"docstring": "Testing BED approximation when BED values are linear.",
"name": "test_case_BED_linear",
"signature": "def test_case_BED_linear(self)"
},
{
"docstring": "Testing BED approximation when BED values are arbitrary convex.",
"name": "test_case_BED_concave",
"signature": "def te... | 2 | stack_v2_sparse_classes_30k_train_048749 | Implement the Python class `BEDPredictorUpperBoundCorrectTest` described below.
Class description:
Implement the BEDPredictorUpperBoundCorrectTest class.
Method signatures and docstrings:
- def test_case_BED_linear(self): Testing BED approximation when BED values are linear.
- def test_case_BED_concave(self): Testing... | Implement the Python class `BEDPredictorUpperBoundCorrectTest` described below.
Class description:
Implement the BEDPredictorUpperBoundCorrectTest class.
Method signatures and docstrings:
- def test_case_BED_linear(self): Testing BED approximation when BED values are linear.
- def test_case_BED_concave(self): Testing... | 413b9e4aaea5a641aa36ab7f29528468a0c13196 | <|skeleton|>
class BEDPredictorUpperBoundCorrectTest:
def test_case_BED_linear(self):
"""Testing BED approximation when BED values are linear."""
<|body_0|>
def test_case_BED_concave(self):
"""Testing BED approximation when BED values are arbitrary convex."""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BEDPredictorUpperBoundCorrectTest:
def test_case_BED_linear(self):
"""Testing BED approximation when BED values are linear."""
num_fractions = 16
BED = np.array([range(num_fractions + 1)])
x = BEDPredictorUpperBoundCorrect(BED)
estimated = x.estimate(granularity=4)
... | the_stack_v2_python_sparse | proton/test_estimator.py | IDmy/proton | train | 0 | |
e1b1fc79abd30b449f2ffe706df43fdaf35f4d2d | [
"self.num_intentions = num_intentions\nself.alpha = alpha\nself.logger = logger",
"assert Q.dim() == action_log_prob.dim()\nif self.logger is not None:\n self.logger.add_scalar(tag='Loss/entropy', scalar_value=(self.alpha * action_log_prob).mean())\n self.logger.add_scalar(tag='Loss/Q', scalar_value=(-Q).me... | <|body_start_0|>
self.num_intentions = num_intentions
self.alpha = alpha
self.logger = logger
<|end_body_0|>
<|body_start_1|>
assert Q.dim() == action_log_prob.dim()
if self.logger is not None:
self.logger.add_scalar(tag='Loss/entropy', scalar_value=(self.alpha * act... | ActorLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActorLoss:
def __init__(self, num_intentions, alpha=0, logger=None):
"""Loss function for the actor. Args: alpha: entropy regularization parameter."""
<|body_0|>
def __call__(self, Q, action_log_prob):
"""Computes the loss of the actor according to L = 𝔼_π [Q(a,s) -... | stack_v2_sparse_classes_75kplus_train_000941 | 4,656 | no_license | [
{
"docstring": "Loss function for the actor. Args: alpha: entropy regularization parameter.",
"name": "__init__",
"signature": "def __init__(self, num_intentions, alpha=0, logger=None)"
},
{
"docstring": "Computes the loss of the actor according to L = 𝔼_π [Q(a,s) - α log(π(a|s)] Args: Q: Q(a,s... | 2 | stack_v2_sparse_classes_30k_test_002964 | Implement the Python class `ActorLoss` described below.
Class description:
Implement the ActorLoss class.
Method signatures and docstrings:
- def __init__(self, num_intentions, alpha=0, logger=None): Loss function for the actor. Args: alpha: entropy regularization parameter.
- def __call__(self, Q, action_log_prob): ... | Implement the Python class `ActorLoss` described below.
Class description:
Implement the ActorLoss class.
Method signatures and docstrings:
- def __init__(self, num_intentions, alpha=0, logger=None): Loss function for the actor. Args: alpha: entropy regularization parameter.
- def __call__(self, Q, action_log_prob): ... | 99c99c952bdf9997f240cf0fb7637a327c81424e | <|skeleton|>
class ActorLoss:
def __init__(self, num_intentions, alpha=0, logger=None):
"""Loss function for the actor. Args: alpha: entropy regularization parameter."""
<|body_0|>
def __call__(self, Q, action_log_prob):
"""Computes the loss of the actor according to L = 𝔼_π [Q(a,s) -... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ActorLoss:
def __init__(self, num_intentions, alpha=0, logger=None):
"""Loss function for the actor. Args: alpha: entropy regularization parameter."""
self.num_intentions = num_intentions
self.alpha = alpha
self.logger = logger
def __call__(self, Q, action_log_prob):
... | the_stack_v2_python_sparse | sac_x/loss_fn.py | DenisBless/ScheduledAuxiliaryControl | train | 1 | |
9805039ed80b415f06348d2180c36158d26ca0d2 | [
"self.rerank_top = rerank_top\nself.duoBERT_score_transform = DuoBERT_Scorer_Transform(checkpoint_dir, **kwargs)\nself.doc_resolver_transform = Document_Resolver_Transform(get_doc_fn, fields=[('d_idA', 'docA'), ('d_idB', 'docB')])\nself.duoBERT_numericalise_transform = DuoBERT_Numericalise_Transform(**kwargs)",
"... | <|body_start_0|>
self.rerank_top = rerank_top
self.duoBERT_score_transform = DuoBERT_Scorer_Transform(checkpoint_dir, **kwargs)
self.doc_resolver_transform = Document_Resolver_Transform(get_doc_fn, fields=[('d_idA', 'docA'), ('d_idB', 'docB')])
self.duoBERT_numericalise_transform = DuoBE... | DuoBERT_ReRanker_Transform | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DuoBERT_ReRanker_Transform:
def __init__(self, checkpoint_dir, get_doc_fn, rerank_top=10, **kwargs):
"""A Transform that reorders a list pairwise. checkpoint_path: str: path to only the state dict of the model, loaded with load_state_dict"""
<|body_0|>
def __call__(self, sam... | stack_v2_sparse_classes_75kplus_train_000942 | 24,876 | no_license | [
{
"docstring": "A Transform that reorders a list pairwise. checkpoint_path: str: path to only the state dict of the model, loaded with load_state_dict",
"name": "__init__",
"signature": "def __init__(self, checkpoint_dir, get_doc_fn, rerank_top=10, **kwargs)"
},
{
"docstring": "samples: [dict]: ... | 2 | stack_v2_sparse_classes_30k_train_036724 | Implement the Python class `DuoBERT_ReRanker_Transform` described below.
Class description:
Implement the DuoBERT_ReRanker_Transform class.
Method signatures and docstrings:
- def __init__(self, checkpoint_dir, get_doc_fn, rerank_top=10, **kwargs): A Transform that reorders a list pairwise. checkpoint_path: str: path... | Implement the Python class `DuoBERT_ReRanker_Transform` described below.
Class description:
Implement the DuoBERT_ReRanker_Transform class.
Method signatures and docstrings:
- def __init__(self, checkpoint_dir, get_doc_fn, rerank_top=10, **kwargs): A Transform that reorders a list pairwise. checkpoint_path: str: path... | 92dd4d41ad6f2be5b5c4e296e2a355bb14b9a1db | <|skeleton|>
class DuoBERT_ReRanker_Transform:
def __init__(self, checkpoint_dir, get_doc_fn, rerank_top=10, **kwargs):
"""A Transform that reorders a list pairwise. checkpoint_path: str: path to only the state dict of the model, loaded with load_state_dict"""
<|body_0|>
def __call__(self, sam... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DuoBERT_ReRanker_Transform:
def __init__(self, checkpoint_dir, get_doc_fn, rerank_top=10, **kwargs):
"""A Transform that reorders a list pairwise. checkpoint_path: str: path to only the state dict of the model, loaded with load_state_dict"""
self.rerank_top = rerank_top
self.duoBERT_sc... | the_stack_v2_python_sparse | notebooks/src/models_and_transforms/complex_transforms.py | carlos-gemmell/Glasgow-NLP | train | 0 | |
eedd648db0b8811eaf7d67435b4645201ef1cee8 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | DocumentAnnotatorServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DocumentAnnotatorServicer:
"""Missing associated documentation comment in .proto file."""
def AnnotateDocument(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def AnswerDocumentQuestion(self, request, context):
"... | stack_v2_sparse_classes_75kplus_train_000943 | 4,705 | no_license | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "AnnotateDocument",
"signature": "def AnnotateDocument(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "AnswerDocumentQuestion",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_054272 | Implement the Python class `DocumentAnnotatorServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def AnnotateDocument(self, request, context): Missing associated documentation comment in .proto file.
- def AnswerDocumentQuestion(se... | Implement the Python class `DocumentAnnotatorServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def AnnotateDocument(self, request, context): Missing associated documentation comment in .proto file.
- def AnswerDocumentQuestion(se... | 8de6749dd32ee2ff84f16780fdb7669a534e6f67 | <|skeleton|>
class DocumentAnnotatorServicer:
"""Missing associated documentation comment in .proto file."""
def AnnotateDocument(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def AnswerDocumentQuestion(self, request, context):
"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DocumentAnnotatorServicer:
"""Missing associated documentation comment in .proto file."""
def AnnotateDocument(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | the_stack_v2_python_sparse | gen/python/ssn/annotator/v1/annotator_pb2_grpc.py | e-conomic/vmlapis | train | 1 |
2e77eb4d29fe1c87b52b1f9a05decb4429463b58 | [
"assert not np.isinf(domain[1])\nx_pts, self.dx = get_asymmetric_interval_points(domain, max_nof_coefficients, interval_type=interval_type, get_spacing=True, **kwargs)\nself.mid = (x_pts[:-1] + x_pts[1:]) / 2\nself.J = J\ntry:\n self.ignore_zeros = kwargs['ignore_zeros']\nexcept KeyError:\n self.ignore_zeros ... | <|body_start_0|>
assert not np.isinf(domain[1])
x_pts, self.dx = get_asymmetric_interval_points(domain, max_nof_coefficients, interval_type=interval_type, get_spacing=True, **kwargs)
self.mid = (x_pts[:-1] + x_pts[1:]) / 2
self.J = J
try:
self.ignore_zeros = kwargs['i... | GKQuadDiscretizedAsymmetricBath | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GKQuadDiscretizedAsymmetricBath:
def __init__(self, J, domain, max_nof_coefficients=100, interval_type='lin', **kwargs):
"""Generates direct discretization coefficients from a spectral density J, by computing the integrals: gamma_i = sqrt(int_i^i+1 J(x) dx) xi_i = int_i^i+1 J(x) * x dx/ ... | stack_v2_sparse_classes_75kplus_train_000944 | 3,938 | permissive | [
{
"docstring": "Generates direct discretization coefficients from a spectral density J, by computing the integrals: gamma_i = sqrt(int_i^i+1 J(x) dx) xi_i = int_i^i+1 J(x) * x dx/ gamma_i^2 :param J: Spectral density. A function defined on 'domain', must be >0 in the inner part of domain :param domain: List/tup... | 2 | stack_v2_sparse_classes_30k_train_023661 | Implement the Python class `GKQuadDiscretizedAsymmetricBath` described below.
Class description:
Implement the GKQuadDiscretizedAsymmetricBath class.
Method signatures and docstrings:
- def __init__(self, J, domain, max_nof_coefficients=100, interval_type='lin', **kwargs): Generates direct discretization coefficients... | Implement the Python class `GKQuadDiscretizedAsymmetricBath` described below.
Class description:
Implement the GKQuadDiscretizedAsymmetricBath class.
Method signatures and docstrings:
- def __init__(self, J, domain, max_nof_coefficients=100, interval_type='lin', **kwargs): Generates direct discretization coefficients... | daf37f522f8acb6af2285d44f39cab31f34b01a4 | <|skeleton|>
class GKQuadDiscretizedAsymmetricBath:
def __init__(self, J, domain, max_nof_coefficients=100, interval_type='lin', **kwargs):
"""Generates direct discretization coefficients from a spectral density J, by computing the integrals: gamma_i = sqrt(int_i^i+1 J(x) dx) xi_i = int_i^i+1 J(x) * x dx/ ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GKQuadDiscretizedAsymmetricBath:
def __init__(self, J, domain, max_nof_coefficients=100, interval_type='lin', **kwargs):
"""Generates direct discretization coefficients from a spectral density J, by computing the integrals: gamma_i = sqrt(int_i^i+1 J(x) dx) xi_i = int_i^i+1 J(x) * x dx/ gamma_i^2 :par... | the_stack_v2_python_sparse | mapping/star/discretized_bath/asymmetric_gk_quad.py | fhoeb/py-mapping | train | 2 | |
a34f3ccf39e26284b732ad07ab7b06e28eb89808 | [
"if estimate and self.mol_obj is None:\n raise CgbindCritical('Cannot estimate charges without a rdkit molecule object')\nif estimate:\n try:\n rdPartialCharges.ComputeGasteigerCharges(self.mol_obj)\n charges = [float(self.mol_obj.GetAtomWithIdx(i).GetProp('_GasteigerCharge')) for i in range(sel... | <|body_start_0|>
if estimate and self.mol_obj is None:
raise CgbindCritical('Cannot estimate charges without a rdkit molecule object')
if estimate:
try:
rdPartialCharges.ComputeGasteigerCharges(self.mol_obj)
charges = [float(self.mol_obj.GetAtomWit... | Molecule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Molecule:
def get_charges(self, estimate=False):
"""Get the partial atomic charges using either XTB or estimate with RDKit using the Gasteiger charge scheme :param estimate: (bool) :param guess: (bool) :return:"""
<|body_0|>
def _init_smiles(self, smiles, use_etdg_confs=Fals... | stack_v2_sparse_classes_75kplus_train_000945 | 11,350 | permissive | [
{
"docstring": "Get the partial atomic charges using either XTB or estimate with RDKit using the Gasteiger charge scheme :param estimate: (bool) :param guess: (bool) :return:",
"name": "get_charges",
"signature": "def get_charges(self, estimate=False)"
},
{
"docstring": "Initialise a Molecule ob... | 3 | stack_v2_sparse_classes_30k_train_045553 | Implement the Python class `Molecule` described below.
Class description:
Implement the Molecule class.
Method signatures and docstrings:
- def get_charges(self, estimate=False): Get the partial atomic charges using either XTB or estimate with RDKit using the Gasteiger charge scheme :param estimate: (bool) :param gue... | Implement the Python class `Molecule` described below.
Class description:
Implement the Molecule class.
Method signatures and docstrings:
- def get_charges(self, estimate=False): Get the partial atomic charges using either XTB or estimate with RDKit using the Gasteiger charge scheme :param estimate: (bool) :param gue... | cfa47c06a42cd63bef8a9ac6af9c3403773c47ca | <|skeleton|>
class Molecule:
def get_charges(self, estimate=False):
"""Get the partial atomic charges using either XTB or estimate with RDKit using the Gasteiger charge scheme :param estimate: (bool) :param guess: (bool) :return:"""
<|body_0|>
def _init_smiles(self, smiles, use_etdg_confs=Fals... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Molecule:
def get_charges(self, estimate=False):
"""Get the partial atomic charges using either XTB or estimate with RDKit using the Gasteiger charge scheme :param estimate: (bool) :param guess: (bool) :return:"""
if estimate and self.mol_obj is None:
raise CgbindCritical('Cannot e... | the_stack_v2_python_sparse | cgbind/molecule.py | duartegroup/cgbind | train | 9 | |
cadc0cbca54d1d8bb1e933ece189bf032ada710d | [
"super(MTLSTM, self).__init__()\nself.word_embedding = word_embedding\nself.rnn = nn.LSTM(300, 300, num_layers=2, bidirectional=True, batch_first=True)\ndata_handler = DataHandler(cache_path=CachePath.PRETRAINED_VECTOR)\ncove_weight_path = data_handler.read(pretrained_path, return_path=True)\nif torch.cuda.is_avail... | <|body_start_0|>
super(MTLSTM, self).__init__()
self.word_embedding = word_embedding
self.rnn = nn.LSTM(300, 300, num_layers=2, bidirectional=True, batch_first=True)
data_handler = DataHandler(cache_path=CachePath.PRETRAINED_VECTOR)
cove_weight_path = data_handler.read(pretrained... | MTLSTM | [
"MIT",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MTLSTM:
def __init__(self, word_embedding, pretrained_path=None, requires_grad=False, residual_embeddings=False):
"""Initialize an MTLSTM. Arguments: n_vocab (bool): If not None, initialize MTLSTM with an embedding matrix with n_vocab vectors vectors (Float Tensor): If not None, initiapi... | stack_v2_sparse_classes_75kplus_train_000946 | 2,325 | permissive | [
{
"docstring": "Initialize an MTLSTM. Arguments: n_vocab (bool): If not None, initialize MTLSTM with an embedding matrix with n_vocab vectors vectors (Float Tensor): If not None, initiapize embedding matrix with specified vectors residual_embedding (bool): If True, concatenate the input embeddings with MTLSTM o... | 2 | null | Implement the Python class `MTLSTM` described below.
Class description:
Implement the MTLSTM class.
Method signatures and docstrings:
- def __init__(self, word_embedding, pretrained_path=None, requires_grad=False, residual_embeddings=False): Initialize an MTLSTM. Arguments: n_vocab (bool): If not None, initialize MTL... | Implement the Python class `MTLSTM` described below.
Class description:
Implement the MTLSTM class.
Method signatures and docstrings:
- def __init__(self, word_embedding, pretrained_path=None, requires_grad=False, residual_embeddings=False): Initialize an MTLSTM. Arguments: n_vocab (bool): If not None, initialize MTL... | 89b3e5c5ec0486886876ea3bac381508c6a6bf58 | <|skeleton|>
class MTLSTM:
def __init__(self, word_embedding, pretrained_path=None, requires_grad=False, residual_embeddings=False):
"""Initialize an MTLSTM. Arguments: n_vocab (bool): If not None, initialize MTLSTM with an embedding matrix with n_vocab vectors vectors (Float Tensor): If not None, initiapi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MTLSTM:
def __init__(self, word_embedding, pretrained_path=None, requires_grad=False, residual_embeddings=False):
"""Initialize an MTLSTM. Arguments: n_vocab (bool): If not None, initialize MTLSTM with an embedding matrix with n_vocab vectors vectors (Float Tensor): If not None, initiapize embedding m... | the_stack_v2_python_sparse | claf/tokens/cove.py | srlee-ai/claf | train | 0 | |
0229bec03ca65c0881390e7ec44f22405501cb91 | [
"WHITE, GREY, BLACK = (0, 1, 2)\nstack = [course]\ncolor_mapping = {}\nseen = []\nwhile stack:\n course = stack.pop()\n seen.append(course)\n if course not in graph or course in explored:\n continue\n if color_mapping[course] == GREY:\n color_mapping[course] = BLACK\n else:\n col... | <|body_start_0|>
WHITE, GREY, BLACK = (0, 1, 2)
stack = [course]
color_mapping = {}
seen = []
while stack:
course = stack.pop()
seen.append(course)
if course not in graph or course in explored:
continue
if color_mapp... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def detect_cycle(self, graph, course, explored):
""">>> s = Solution() # >>> graph = {0: [1], 1:[0]} # >>> s.detect_cycle(graph, 0, []) # True # >>> s.detect_cycle(graph, 1, []) # True # >>> graph = {0:[1]} # >>> s.detect_cycle(graph, 0, []) # False # >>> s.detect_cycle(graph, ... | stack_v2_sparse_classes_75kplus_train_000947 | 3,567 | no_license | [
{
"docstring": ">>> s = Solution() # >>> graph = {0: [1], 1:[0]} # >>> s.detect_cycle(graph, 0, []) # True # >>> s.detect_cycle(graph, 1, []) # True # >>> graph = {0:[1]} # >>> s.detect_cycle(graph, 0, []) # False # >>> s.detect_cycle(graph, 1, []) # False # >>> graph = {0:[1], 1:[2]} # >>> s.detect_cycle(graph... | 2 | stack_v2_sparse_classes_30k_train_007636 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def detect_cycle(self, graph, course, explored): >>> s = Solution() # >>> graph = {0: [1], 1:[0]} # >>> s.detect_cycle(graph, 0, []) # True # >>> s.detect_cycle(graph, 1, []) # T... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def detect_cycle(self, graph, course, explored): >>> s = Solution() # >>> graph = {0: [1], 1:[0]} # >>> s.detect_cycle(graph, 0, []) # True # >>> s.detect_cycle(graph, 1, []) # T... | 3b13a02f9c8273f9794a57b948d2655792707f37 | <|skeleton|>
class Solution:
def detect_cycle(self, graph, course, explored):
""">>> s = Solution() # >>> graph = {0: [1], 1:[0]} # >>> s.detect_cycle(graph, 0, []) # True # >>> s.detect_cycle(graph, 1, []) # True # >>> graph = {0:[1]} # >>> s.detect_cycle(graph, 0, []) # False # >>> s.detect_cycle(graph, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def detect_cycle(self, graph, course, explored):
""">>> s = Solution() # >>> graph = {0: [1], 1:[0]} # >>> s.detect_cycle(graph, 0, []) # True # >>> s.detect_cycle(graph, 1, []) # True # >>> graph = {0:[1]} # >>> s.detect_cycle(graph, 0, []) # False # >>> s.detect_cycle(graph, 1, []) # False... | the_stack_v2_python_sparse | course_schedule.py | gsy/leetcode | train | 1 | |
a7c6de54e0b4448064476e07c284c9ace13e00fd | [
"cnt = [0] * 2\nleft, right = (0, 0)\nres = 0\nwhile right < len(nums):\n cnt[nums[right]] += 1\n if nums[right] == 0:\n while cnt[0] > k:\n cnt[nums[left]] -= 1\n left += 1\n if cnt[0] <= k:\n while right + 1 < len(nums) and nums[right + 1] == 1:\n right += 1... | <|body_start_0|>
cnt = [0] * 2
left, right = (0, 0)
res = 0
while right < len(nums):
cnt[nums[right]] += 1
if nums[right] == 0:
while cnt[0] > k:
cnt[nums[left]] -= 1
left += 1
if cnt[0] <= k:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestOnes(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def longestOnes2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cnt = [0] * ... | stack_v2_sparse_classes_75kplus_train_000948 | 1,278 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "longestOnes",
"signature": "def longestOnes(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "longestOnes2",
"signature": "def longestOnes2(self, nums, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_033624 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestOnes(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def longestOnes2(self, nums, k): :type nums: List[int] :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestOnes(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def longestOnes2(self, nums, k): :type nums: List[int] :type k: int :rtype: int
<|skeleton|>
cla... | a32a1add8720de35e0ddc0c51efe781fb04c9d4a | <|skeleton|>
class Solution:
def longestOnes(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def longestOnes2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longestOnes(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
cnt = [0] * 2
left, right = (0, 0)
res = 0
while right < len(nums):
cnt[nums[right]] += 1
if nums[right] == 0:
while cnt[0] > k:
... | the_stack_v2_python_sparse | 双指针/leetcode_1004_Max_Consecutive_Ones_III.py | cleverer123/Algorithm | train | 0 | |
ee7e731ea65d9247b90afcf0268e36a468e7415e | [
"self.size = 0\nself.capacity = capacity\nself.node = dict()\nself.freq = collections.defaultdict(DLinkedList)\nself.minfreq = 0",
"freq = node.freq\nself.freq[freq].pop(node)\nif self.minfreq == freq and (not self.freq[freq]):\n self.minfreq += 1\nnode.freq += 1\nfreq = node.freq\nself.freq[freq].append(node)... | <|body_start_0|>
self.size = 0
self.capacity = capacity
self.node = dict()
self.freq = collections.defaultdict(DLinkedList)
self.minfreq = 0
<|end_body_0|>
<|body_start_1|>
freq = node.freq
self.freq[freq].pop(node)
if self.minfreq == freq and (not self.f... | LFUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
"""Three things to maintain: 1. a dict, named as `self.node`, for the reference of all nodes given key. That is, O(1) time to retrieve node given a key. 2. Each frequency has a doubly linked list, store in `self.freq`, where key is the frequency, a... | stack_v2_sparse_classes_75kplus_train_000949 | 13,553 | no_license | [
{
"docstring": "Three things to maintain: 1. a dict, named as `self.node`, for the reference of all nodes given key. That is, O(1) time to retrieve node given a key. 2. Each frequency has a doubly linked list, store in `self.freq`, where key is the frequency, and value is an object of `DLinkedList` 3. The min f... | 4 | stack_v2_sparse_classes_30k_train_048835 | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): Three things to maintain: 1. a dict, named as `self.node`, for the reference of all nodes given key. That is, O(1) time to retrieve node given a key... | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): Three things to maintain: 1. a dict, named as `self.node`, for the reference of all nodes given key. That is, O(1) time to retrieve node given a key... | a4d8b54d3004866fd304e732707eef4401dfdb0a | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
"""Three things to maintain: 1. a dict, named as `self.node`, for the reference of all nodes given key. That is, O(1) time to retrieve node given a key. 2. Each frequency has a doubly linked list, store in `self.freq`, where key is the frequency, a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LFUCache:
def __init__(self, capacity):
"""Three things to maintain: 1. a dict, named as `self.node`, for the reference of all nodes given key. That is, O(1) time to retrieve node given a key. 2. Each frequency has a doubly linked list, store in `self.freq`, where key is the frequency, and value is an... | the_stack_v2_python_sparse | LeetcodeNew/python/LC_460.py | derrickweiruluo/OptimizedLeetcode-1 | train | 0 | |
57cf1e5d65824b638cdc1ce852ebc3591192e864 | [
"levels = sorted(box_outputs.keys())\nbox_losses = []\nfor level in levels:\n box_losses.append(self._rpn_box_loss(box_outputs[level], labels[level], delta=self.delta))\nrpn_box_loss = jnp.sum(jnp.array(box_losses))\nreturn rpn_box_loss",
"mask = box_targets != 0.0\nbox_loss = huber_loss(box_outputs, box_targe... | <|body_start_0|>
levels = sorted(box_outputs.keys())
box_losses = []
for level in levels:
box_losses.append(self._rpn_box_loss(box_outputs[level], labels[level], delta=self.delta))
rpn_box_loss = jnp.sum(jnp.array(box_losses))
return rpn_box_loss
<|end_body_0|>
<|bod... | Region Proposal Network box regression loss function. Attributes: delta: The delta of box Huber loss. | RpnBoxLoss | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RpnBoxLoss:
"""Region Proposal Network box regression loss function. Attributes: delta: The delta of box Huber loss."""
def __call__(self, box_outputs, labels):
"""Computes and gathers RPN box losses from all levels. Args: box_outputs: A dictionary with keys representing levels and v... | stack_v2_sparse_classes_75kplus_train_000950 | 20,333 | permissive | [
{
"docstring": "Computes and gathers RPN box losses from all levels. Args: box_outputs: A dictionary with keys representing levels and values representing box regression targets in [batch_size, height, width, num_anchors * 4]. labels: A dictionary returned from dataloader with keys representing levels and value... | 2 | stack_v2_sparse_classes_30k_val_002692 | Implement the Python class `RpnBoxLoss` described below.
Class description:
Region Proposal Network box regression loss function. Attributes: delta: The delta of box Huber loss.
Method signatures and docstrings:
- def __call__(self, box_outputs, labels): Computes and gathers RPN box losses from all levels. Args: box_... | Implement the Python class `RpnBoxLoss` described below.
Class description:
Region Proposal Network box regression loss function. Attributes: delta: The delta of box Huber loss.
Method signatures and docstrings:
- def __call__(self, box_outputs, labels): Computes and gathers RPN box losses from all levels. Args: box_... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class RpnBoxLoss:
"""Region Proposal Network box regression loss function. Attributes: delta: The delta of box Huber loss."""
def __call__(self, box_outputs, labels):
"""Computes and gathers RPN box losses from all levels. Args: box_outputs: A dictionary with keys representing levels and v... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RpnBoxLoss:
"""Region Proposal Network box regression loss function. Attributes: delta: The delta of box Huber loss."""
def __call__(self, box_outputs, labels):
"""Computes and gathers RPN box losses from all levels. Args: box_outputs: A dictionary with keys representing levels and values represe... | the_stack_v2_python_sparse | moe_mtl/losses/maskrcnn_losses.py | Jimmy-INL/google-research | train | 1 |
cfbb3e99d6a2bb48aa8f8cbf643127e85bb5aa2a | [
"super(Sim_Attn, self).__init__()\nself.encoder_size = encoder_size\nself.decoder_size = decoder_size\nself.num_labels = num_labels\nself.hidden_size = hidden_size\nself.e_mlp = nn.Sequential(nn.Linear(encoder_size, hidden_size), nn.SELU(), nn.Linear(hidden_size, K), nn.SELU()) if MLP_Layer == 2 else nn.Sequential(... | <|body_start_0|>
super(Sim_Attn, self).__init__()
self.encoder_size = encoder_size
self.decoder_size = decoder_size
self.num_labels = num_labels
self.hidden_size = hidden_size
self.e_mlp = nn.Sequential(nn.Linear(encoder_size, hidden_size), nn.SELU(), nn.Linear(hidden_siz... | Sim_Attn | [
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sim_Attn:
def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE):
"""num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即可，一组标量的 soft_max 概率即 为边界标签的选择结果。 if LAYER_NORM_USE: edus = self.edu_norm(edus)"""
<|body_... | stack_v2_sparse_classes_75kplus_train_000951 | 16,149 | permissive | [
{
"docstring": "num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即可，一组标量的 soft_max 概率即 为边界标签的选择结果。 if LAYER_NORM_USE: edus = self.edu_norm(edus)",
"name": "__init__",
"signature": "def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SI... | 2 | stack_v2_sparse_classes_30k_train_052622 | Implement the Python class `Sim_Attn` described below.
Class description:
Implement the Sim_Attn class.
Method signatures and docstrings:
- def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE): num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即... | Implement the Python class `Sim_Attn` described below.
Class description:
Implement the Sim_Attn class.
Method signatures and docstrings:
- def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE): num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即... | fd71b353c59bcb82ec2cd0bebf943040756faa63 | <|skeleton|>
class Sim_Attn:
def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE):
"""num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即可，一组标量的 soft_max 概率即 为边界标签的选择结果。 if LAYER_NORM_USE: edus = self.edu_norm(edus)"""
<|body_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Sim_Attn:
def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE):
"""num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即可，一组标量的 soft_max 概率即 为边界标签的选择结果。 if LAYER_NORM_USE: edus = self.edu_norm(edus)"""
super(Sim_Attn, self)... | the_stack_v2_python_sparse | CDTB_Seg/model/ENC_DEC_GCN/model.py | NLP-Discourse-SoochowU/segmenter2020 | train | 0 | |
19823ae82390e2d9123df87592f349b979b727e1 | [
"if len(seed_bytes) != CardanoByronLegacyMstKeyGeneratorConst.SEED_BYTE_LEN:\n raise ValueError(f'Invalid seed length ({len(seed_bytes)})')\nreturn cls.__HashRepeatedly(cbor2.dumps(seed_bytes), 1)",
"il_bytes, ir_bytes = HmacSha512.QuickDigestHalves(data_bytes, CardanoByronLegacyMstKeyGeneratorConst.HMAC_MESSA... | <|body_start_0|>
if len(seed_bytes) != CardanoByronLegacyMstKeyGeneratorConst.SEED_BYTE_LEN:
raise ValueError(f'Invalid seed length ({len(seed_bytes)})')
return cls.__HashRepeatedly(cbor2.dumps(seed_bytes), 1)
<|end_body_0|>
<|body_start_1|>
il_bytes, ir_bytes = HmacSha512.QuickDige... | Cardano Byron legacy master key generator class. It allows master keys generation in according to Cardano Byron (legacy, used by old versions of Daedalus). | CardanoByronLegacyMstKeyGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CardanoByronLegacyMstKeyGenerator:
"""Cardano Byron legacy master key generator class. It allows master keys generation in according to Cardano Byron (legacy, used by old versions of Daedalus)."""
def GenerateFromSeed(cls, seed_bytes: bytes) -> Tuple[bytes, bytes]:
"""Generate a mast... | stack_v2_sparse_classes_75kplus_train_000952 | 4,310 | permissive | [
{
"docstring": "Generate a master key from the specified seed. Args: seed_bytes (bytes): Seed bytes Returns: tuple[bytes, bytes]: Private key bytes (index 0) and chain code bytes (index 1) Raises: Bip32KeyError: If the seed is not suitable for master key generation ValueError: If seed length is not valid",
... | 3 | stack_v2_sparse_classes_30k_train_025721 | Implement the Python class `CardanoByronLegacyMstKeyGenerator` described below.
Class description:
Cardano Byron legacy master key generator class. It allows master keys generation in according to Cardano Byron (legacy, used by old versions of Daedalus).
Method signatures and docstrings:
- def GenerateFromSeed(cls, s... | Implement the Python class `CardanoByronLegacyMstKeyGenerator` described below.
Class description:
Cardano Byron legacy master key generator class. It allows master keys generation in according to Cardano Byron (legacy, used by old versions of Daedalus).
Method signatures and docstrings:
- def GenerateFromSeed(cls, s... | d15c75ddd74e4838c396a0d036ef6faf11b06a4b | <|skeleton|>
class CardanoByronLegacyMstKeyGenerator:
"""Cardano Byron legacy master key generator class. It allows master keys generation in according to Cardano Byron (legacy, used by old versions of Daedalus)."""
def GenerateFromSeed(cls, seed_bytes: bytes) -> Tuple[bytes, bytes]:
"""Generate a mast... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CardanoByronLegacyMstKeyGenerator:
"""Cardano Byron legacy master key generator class. It allows master keys generation in according to Cardano Byron (legacy, used by old versions of Daedalus)."""
def GenerateFromSeed(cls, seed_bytes: bytes) -> Tuple[bytes, bytes]:
"""Generate a master key from t... | the_stack_v2_python_sparse | bip_utils/cardano/bip32/cardano_byron_legacy_mst_key_generator.py | ebellocchia/bip_utils | train | 244 |
70cd8bfedc35afc1d79db5e2748d10e634c70261 | [
"if self.get_argument('type', None) == 'province':\n ret = {'status': True, 'rows': '', 'summary': ''}\n try:\n province_id = self.get_argument('province_id', None)\n if not province_id:\n ret['status'] = False\n ret['summary'] = '请指定省份ID'\n else:\n region... | <|body_start_0|>
if self.get_argument('type', None) == 'province':
ret = {'status': True, 'rows': '', 'summary': ''}
try:
province_id = self.get_argument('province_id', None)
if not province_id:
ret['status'] = False
... | CityHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CityHandler:
def get(self, *args, **kwargs):
"""获取 :param args: :param kwargs: :return:"""
<|body_0|>
def post(self, *args, **kwargs):
"""添加 :param args: :param kwargs: :return:"""
<|body_1|>
def put(self, *args, **kwargs):
"""更新 :param args: :pa... | stack_v2_sparse_classes_75kplus_train_000953 | 13,334 | no_license | [
{
"docstring": "获取 :param args: :param kwargs: :return:",
"name": "get",
"signature": "def get(self, *args, **kwargs)"
},
{
"docstring": "添加 :param args: :param kwargs: :return:",
"name": "post",
"signature": "def post(self, *args, **kwargs)"
},
{
"docstring": "更新 :param args: :p... | 4 | stack_v2_sparse_classes_30k_train_010654 | Implement the Python class `CityHandler` described below.
Class description:
Implement the CityHandler class.
Method signatures and docstrings:
- def get(self, *args, **kwargs): 获取 :param args: :param kwargs: :return:
- def post(self, *args, **kwargs): 添加 :param args: :param kwargs: :return:
- def put(self, *args, **... | Implement the Python class `CityHandler` described below.
Class description:
Implement the CityHandler class.
Method signatures and docstrings:
- def get(self, *args, **kwargs): 获取 :param args: :param kwargs: :return:
- def post(self, *args, **kwargs): 添加 :param args: :param kwargs: :return:
- def put(self, *args, **... | 0056d8edb9b8912e28b0332b3202e8a8d50f7157 | <|skeleton|>
class CityHandler:
def get(self, *args, **kwargs):
"""获取 :param args: :param kwargs: :return:"""
<|body_0|>
def post(self, *args, **kwargs):
"""添加 :param args: :param kwargs: :return:"""
<|body_1|>
def put(self, *args, **kwargs):
"""更新 :param args: :pa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CityHandler:
def get(self, *args, **kwargs):
"""获取 :param args: :param kwargs: :return:"""
if self.get_argument('type', None) == 'province':
ret = {'status': True, 'rows': '', 'summary': ''}
try:
province_id = self.get_argument('province_id', None)
... | the_stack_v2_python_sparse | UIAdmin/Controllers/Region.py | kevin-light/Jd-shop | train | 0 | |
e0ae544a730e81eee7ecc97803ee144a586ce760 | [
"self.graph = graph\nif not self._is_eulerian():\n raise ValueError('the graph is not eulerian')\nself.eulerian_cycle = list()\nself._graph_copy = self.graph.copy()",
"if source is None:\n source = next(self.graph.iternodes())\nnode = source\nself.eulerian_cycle.append(node)\nwhile self._graph_copy.outdegre... | <|body_start_0|>
self.graph = graph
if not self._is_eulerian():
raise ValueError('the graph is not eulerian')
self.eulerian_cycle = list()
self._graph_copy = self.graph.copy()
<|end_body_0|>
<|body_start_1|>
if source is None:
source = next(self.graph.ite... | Fleury's algorithm for finding an Eulerian cycle (multigraphs). Complexity O(V*E). Attributes ---------- graph : input graph eulerian_cycle : list of nodes (length |E|+1) _graph_copy : graph, private Notes ----- Based on the description from: https://en.wikipedia.org/wiki/Eulerian_path | FleuryDFS | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FleuryDFS:
"""Fleury's algorithm for finding an Eulerian cycle (multigraphs). Complexity O(V*E). Attributes ---------- graph : input graph eulerian_cycle : list of nodes (length |E|+1) _graph_copy : graph, private Notes ----- Based on the description from: https://en.wikipedia.org/wiki/Eulerian_p... | stack_v2_sparse_classes_75kplus_train_000954 | 9,406 | permissive | [
{
"docstring": "The algorithm initialization.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self, source=None)"
},
{
"docstring": "Bridge test.",
"name": "_is_bridge",
"signa... | 4 | stack_v2_sparse_classes_30k_train_011113 | Implement the Python class `FleuryDFS` described below.
Class description:
Fleury's algorithm for finding an Eulerian cycle (multigraphs). Complexity O(V*E). Attributes ---------- graph : input graph eulerian_cycle : list of nodes (length |E|+1) _graph_copy : graph, private Notes ----- Based on the description from: h... | Implement the Python class `FleuryDFS` described below.
Class description:
Fleury's algorithm for finding an Eulerian cycle (multigraphs). Complexity O(V*E). Attributes ---------- graph : input graph eulerian_cycle : list of nodes (length |E|+1) _graph_copy : graph, private Notes ----- Based on the description from: h... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class FleuryDFS:
"""Fleury's algorithm for finding an Eulerian cycle (multigraphs). Complexity O(V*E). Attributes ---------- graph : input graph eulerian_cycle : list of nodes (length |E|+1) _graph_copy : graph, private Notes ----- Based on the description from: https://en.wikipedia.org/wiki/Eulerian_p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FleuryDFS:
"""Fleury's algorithm for finding an Eulerian cycle (multigraphs). Complexity O(V*E). Attributes ---------- graph : input graph eulerian_cycle : list of nodes (length |E|+1) _graph_copy : graph, private Notes ----- Based on the description from: https://en.wikipedia.org/wiki/Eulerian_path"""
d... | the_stack_v2_python_sparse | graphtheory/eulerian/fleury.py | kgashok/graphs-dict | train | 0 |
7db13e19468a4ea79509d8a6f317fba0d86beff2 | [
"self.n_cv_flt = n_cv_flt\nself.n_cv_ln = n_cv_ln\nself.cv_activation = cv_activation\nsuper().__init__(l=l)",
"n_cv_flt, n_cv_ln = (self.n_cv_flt, self.n_cv_ln)\ncv_activation = self.cv_activation\nmodel = Sequential()\nprint('n_cv_flt, n_cv_ln, cv_activation', n_cv_flt, n_cv_ln, cv_activation)\nmodel.add(Convol... | <|body_start_0|>
self.n_cv_flt = n_cv_flt
self.n_cv_ln = n_cv_ln
self.cv_activation = cv_activation
super().__init__(l=l)
<|end_body_0|>
<|body_start_1|>
n_cv_flt, n_cv_ln = (self.n_cv_flt, self.n_cv_ln)
cv_activation = self.cv_activation
model = Sequential()
... | CNNC | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CNNC:
def __init__(self, n_cv_flt=2, n_cv_ln=3, cv_activation='relu', l=[49, 30, 10, 3]):
"""Convolutional neural networks"""
<|body_0|>
def modeling(self, l=[49, 30, 10, 3]):
"""generate model"""
<|body_1|>
def X_reshape(self, X_train_2D, X_val_2D=None)... | stack_v2_sparse_classes_75kplus_train_000955 | 7,760 | permissive | [
{
"docstring": "Convolutional neural networks",
"name": "__init__",
"signature": "def __init__(self, n_cv_flt=2, n_cv_ln=3, cv_activation='relu', l=[49, 30, 10, 3])"
},
{
"docstring": "generate model",
"name": "modeling",
"signature": "def modeling(self, l=[49, 30, 10, 3])"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_008848 | Implement the Python class `CNNC` described below.
Class description:
Implement the CNNC class.
Method signatures and docstrings:
- def __init__(self, n_cv_flt=2, n_cv_ln=3, cv_activation='relu', l=[49, 30, 10, 3]): Convolutional neural networks
- def modeling(self, l=[49, 30, 10, 3]): generate model
- def X_reshape(... | Implement the Python class `CNNC` described below.
Class description:
Implement the CNNC class.
Method signatures and docstrings:
- def __init__(self, n_cv_flt=2, n_cv_ln=3, cv_activation='relu', l=[49, 30, 10, 3]): Convolutional neural networks
- def modeling(self, l=[49, 30, 10, 3]): generate model
- def X_reshape(... | b7e3c860280581e37c7b5254e18ff4b19c112ded | <|skeleton|>
class CNNC:
def __init__(self, n_cv_flt=2, n_cv_ln=3, cv_activation='relu', l=[49, 30, 10, 3]):
"""Convolutional neural networks"""
<|body_0|>
def modeling(self, l=[49, 30, 10, 3]):
"""generate model"""
<|body_1|>
def X_reshape(self, X_train_2D, X_val_2D=None)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CNNC:
def __init__(self, n_cv_flt=2, n_cv_ln=3, cv_activation='relu', l=[49, 30, 10, 3]):
"""Convolutional neural networks"""
self.n_cv_flt = n_cv_flt
self.n_cv_ln = n_cv_ln
self.cv_activation = cv_activation
super().__init__(l=l)
def modeling(self, l=[49, 30, 10, ... | the_stack_v2_python_sparse | repository/_kkeras_r0.py | jskDr/jamespy_py3 | train | 5 | |
82f669b07bba9c834ad75fb19995066f081cbb86 | [
"if not isinstance(personRepo, PersonRepository):\n raise NABException('The given repository of people is not valid.')\nif not isinstance(activityRepo, ActivityRepository):\n raise NABException('The given repository of activities is not valid.')\nself.__personRepo = personRepo\nself.__activityRepo = activityR... | <|body_start_0|>
if not isinstance(personRepo, PersonRepository):
raise NABException('The given repository of people is not valid.')
if not isinstance(activityRepo, ActivityRepository):
raise NABException('The given repository of activities is not valid.')
self.__personRe... | Class used for handling the operations regarding statistics. | StatsController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StatsController:
"""Class used for handling the operations regarding statistics."""
def __init__(self, personRepo, activityRepo):
"""Constructor for the class StatsController. :param personRepo: PersonRepository - repository containing people :param activityRepo: ActivityRepository- ... | stack_v2_sparse_classes_75kplus_train_000956 | 4,851 | no_license | [
{
"docstring": "Constructor for the class StatsController. :param personRepo: PersonRepository - repository containing people :param activityRepo: ActivityRepository- repository containing activities :exception NABException: if one of the parameters is not valid",
"name": "__init__",
"signature": "def _... | 6 | null | Implement the Python class `StatsController` described below.
Class description:
Class used for handling the operations regarding statistics.
Method signatures and docstrings:
- def __init__(self, personRepo, activityRepo): Constructor for the class StatsController. :param personRepo: PersonRepository - repository co... | Implement the Python class `StatsController` described below.
Class description:
Class used for handling the operations regarding statistics.
Method signatures and docstrings:
- def __init__(self, personRepo, activityRepo): Constructor for the class StatsController. :param personRepo: PersonRepository - repository co... | fc0f59ae78a6000d0fc1f63edb52ca7e3b840548 | <|skeleton|>
class StatsController:
"""Class used for handling the operations regarding statistics."""
def __init__(self, personRepo, activityRepo):
"""Constructor for the class StatsController. :param personRepo: PersonRepository - repository containing people :param activityRepo: ActivityRepository- ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StatsController:
"""Class used for handling the operations regarding statistics."""
def __init__(self, personRepo, activityRepo):
"""Constructor for the class StatsController. :param personRepo: PersonRepository - repository containing people :param activityRepo: ActivityRepository- repository co... | the_stack_v2_python_sparse | sem1/fp/labs/lab12-13/NABManagement/controller/StatsController.py | mirceadino/CollegeAssignments | train | 1 |
634f4bdc8758b11a597d8affefd13e27a1b2636a | [
"title = rs_track.get('title', '')\nif not title:\n return []\nartist, track = re.match(\"^(.+)\\\\,\\\\s'?(.+)'?$\", title).groups()\nreturn [artist, track.rstrip(\"'\")]",
"tracks = []\nresp = requests.get(page_url, headers=self.headers, cookies=cookies)\nitems = json.loads(resp.text).get('items', [])\nfor i... | <|body_start_0|>
title = rs_track.get('title', '')
if not title:
return []
artist, track = re.match("^(.+)\\,\\s'?(.+)'?$", title).groups()
return [artist, track.rstrip("'")]
<|end_body_0|>
<|body_start_1|>
tracks = []
resp = requests.get(page_url, headers=se... | Rolling stone 5000 greatest songs requestor | RS500Requestor | [
"Unlicense",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RS500Requestor:
"""Rolling stone 5000 greatest songs requestor"""
def normalize_item(rs_track):
"""Normalize track name"""
<|body_0|>
def get_tracks(self, page_url, cookies):
"""Get tracks from single page"""
<|body_1|>
def get_all(self):
"""... | stack_v2_sparse_classes_75kplus_train_000957 | 7,415 | permissive | [
{
"docstring": "Normalize track name",
"name": "normalize_item",
"signature": "def normalize_item(rs_track)"
},
{
"docstring": "Get tracks from single page",
"name": "get_tracks",
"signature": "def get_tracks(self, page_url, cookies)"
},
{
"docstring": "Get tracks from all pages"... | 3 | stack_v2_sparse_classes_30k_train_033170 | Implement the Python class `RS500Requestor` described below.
Class description:
Rolling stone 5000 greatest songs requestor
Method signatures and docstrings:
- def normalize_item(rs_track): Normalize track name
- def get_tracks(self, page_url, cookies): Get tracks from single page
- def get_all(self): Get tracks from... | Implement the Python class `RS500Requestor` described below.
Class description:
Rolling stone 5000 greatest songs requestor
Method signatures and docstrings:
- def normalize_item(rs_track): Normalize track name
- def get_tracks(self, page_url, cookies): Get tracks from single page
- def get_all(self): Get tracks from... | 3e35a25cfcf982a3871cf0d819bae4374ee31ecf | <|skeleton|>
class RS500Requestor:
"""Rolling stone 5000 greatest songs requestor"""
def normalize_item(rs_track):
"""Normalize track name"""
<|body_0|>
def get_tracks(self, page_url, cookies):
"""Get tracks from single page"""
<|body_1|>
def get_all(self):
"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RS500Requestor:
"""Rolling stone 5000 greatest songs requestor"""
def normalize_item(rs_track):
"""Normalize track name"""
title = rs_track.get('title', '')
if not title:
return []
artist, track = re.match("^(.+)\\,\\s'?(.+)'?$", title).groups()
return ... | the_stack_v2_python_sparse | voiceplay/player/tasks/top.py | tb0hdan/voiceplay | train | 4 |
f44b0c8b93a32cde2118a066c67f5afc252dcf27 | [
"def recursive(i, j):\n if i > j:\n return 0\n count = Counter(s[i:j + 1])\n for m in range(i, j + 1):\n if count[s[m]] >= k:\n continue\n n = m + 1\n while n <= j and count[s[n]] < k:\n n += 1\n return max(recursive(i, m - 1), recursive(n, j))\n ... | <|body_start_0|>
def recursive(i, j):
if i > j:
return 0
count = Counter(s[i:j + 1])
for m in range(i, j + 1):
if count[s[m]] >= k:
continue
n = m + 1
while n <= j and count[s[n]] < k:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_0|>
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def recursive(i, j):
... | stack_v2_sparse_classes_75kplus_train_000958 | 1,891 | no_license | [
{
"docstring": ":type s: str :type k: int :rtype: int",
"name": "longestSubstring",
"signature": "def longestSubstring(self, s, k)"
},
{
"docstring": ":type s: str :type k: int :rtype: int",
"name": "longestSubstring",
"signature": "def longestSubstring(self, s, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008717 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestSubstring(self, s, k): :type s: str :type k: int :rtype: int
- def longestSubstring(self, s, k): :type s: str :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestSubstring(self, s, k): :type s: str :type k: int :rtype: int
- def longestSubstring(self, s, k): :type s: str :type k: int :rtype: int
<|skeleton|>
class Solution:
... | 63b7eedc720c1ce14880b80744dcd5ef7107065c | <|skeleton|>
class Solution:
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_0|>
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
def recursive(i, j):
if i > j:
return 0
count = Counter(s[i:j + 1])
for m in range(i, j + 1):
if count[s[m]] >= k:
con... | the_stack_v2_python_sparse | problems/longestSubstring.py | joddiy/leetcode | train | 1 | |
8720ec9c64c995aaabc54db0c0d4ead0ac61a467 | [
"if isinstance(key, int):\n return CGAType(key)\nif key not in CGAType._member_map_:\n return extend_enum(CGAType, key, default)\nreturn CGAType[key]",
"if not (isinstance(value, int) and 0 <= value <= 340282366920938463463374607431768211455):\n raise ValueError('%r is not a valid %s' % (value, cls.__nam... | <|body_start_0|>
if isinstance(key, int):
return CGAType(key)
if key not in CGAType._member_map_:
return extend_enum(CGAType, key, default)
return CGAType[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and 0 <= value <= 3402823669209384634633... | [CGAType] CGA Extension Type Tags | CGAType | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CGAType:
"""[CGAType] CGA Extension Type Tags"""
def get(key: 'int | str', default: 'int'=-1) -> 'CGAType':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>
def _missing_(cls, value... | stack_v2_sparse_classes_75kplus_train_000959 | 2,568 | permissive | [
{
"docstring": "Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:",
"name": "get",
"signature": "def get(key: 'int | str', default: 'int'=-1) -> 'CGAType'"
},
{
"docstring": "Lookup function used when value is not found. Arg... | 2 | stack_v2_sparse_classes_30k_val_001533 | Implement the Python class `CGAType` described below.
Class description:
[CGAType] CGA Extension Type Tags
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'CGAType': Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta pri... | Implement the Python class `CGAType` described below.
Class description:
[CGAType] CGA Extension Type Tags
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'CGAType': Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta pri... | a6fe49ec58f09e105bec5a00fb66d9b3f22730d9 | <|skeleton|>
class CGAType:
"""[CGAType] CGA Extension Type Tags"""
def get(key: 'int | str', default: 'int'=-1) -> 'CGAType':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>
def _missing_(cls, value... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CGAType:
"""[CGAType] CGA Extension Type Tags"""
def get(key: 'int | str', default: 'int'=-1) -> 'CGAType':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
if isinstance(key, int):
return CGAType(k... | the_stack_v2_python_sparse | pcapkit/const/mh/cga_type.py | JarryShaw/PyPCAPKit | train | 204 |
7ac523f9bdaf166d52b283394f60a78bc912ef30 | [
"visited = set()\nwhile p:\n visited.add(p)\n p = p.parent\nwhile q:\n if q in visited:\n return q\n q = q.parent\nreturn None",
"n1, n2 = (p, q)\nwhile n1 != n2:\n n1 = n1.parent if n1.parent else p\n n2 = n2.parent if n2.parent else q\nreturn n1"
] | <|body_start_0|>
visited = set()
while p:
visited.add(p)
p = p.parent
while q:
if q in visited:
return q
q = q.parent
return None
<|end_body_0|>
<|body_start_1|>
n1, n2 = (p, q)
while n1 != n2:
n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lowestCommonAncestor_1(self, p: 'Node', q: 'Node') -> 'Node':
"""방문한 노드를 기록 O(H) / O(H)"""
<|body_0|>
def lowestCommonAncestor(self, p: 'Node', q: 'Node') -> 'Node':
"""Cycle 찾듯이 반복하면, LCA에서 겹치게됨. LCA보다 위에서 겹치는 경우는 없다. O(H) / O(1)"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_000960 | 952 | no_license | [
{
"docstring": "방문한 노드를 기록 O(H) / O(H)",
"name": "lowestCommonAncestor_1",
"signature": "def lowestCommonAncestor_1(self, p: 'Node', q: 'Node') -> 'Node'"
},
{
"docstring": "Cycle 찾듯이 반복하면, LCA에서 겹치게됨. LCA보다 위에서 겹치는 경우는 없다. O(H) / O(1)",
"name": "lowestCommonAncestor",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_051367 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor_1(self, p: 'Node', q: 'Node') -> 'Node': 방문한 노드를 기록 O(H) / O(H)
- def lowestCommonAncestor(self, p: 'Node', q: 'Node') -> 'Node': Cycle 찾듯이 반복하면, LCA에서 겹... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor_1(self, p: 'Node', q: 'Node') -> 'Node': 방문한 노드를 기록 O(H) / O(H)
- def lowestCommonAncestor(self, p: 'Node', q: 'Node') -> 'Node': Cycle 찾듯이 반복하면, LCA에서 겹... | c26aef2a59e5cc2d9b0658b9c7386a43267ff8a1 | <|skeleton|>
class Solution:
def lowestCommonAncestor_1(self, p: 'Node', q: 'Node') -> 'Node':
"""방문한 노드를 기록 O(H) / O(H)"""
<|body_0|>
def lowestCommonAncestor(self, p: 'Node', q: 'Node') -> 'Node':
"""Cycle 찾듯이 반복하면, LCA에서 겹치게됨. LCA보다 위에서 겹치는 경우는 없다. O(H) / O(1)"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def lowestCommonAncestor_1(self, p: 'Node', q: 'Node') -> 'Node':
"""방문한 노드를 기록 O(H) / O(H)"""
visited = set()
while p:
visited.add(p)
p = p.parent
while q:
if q in visited:
return q
q = q.parent
... | the_stack_v2_python_sparse | Leetcode/1650.py | hanwgyu/algorithm_problem_solving | train | 5 | |
df88bf0fac6811b2ea391a48114f5f1b06af83c6 | [
"super().__init__()\nself.bias = bias\nself.win_len = window_size\nself.channels = channels\nself.average = False\nif reduction == 'mean':\n self.average = True\nwin1d = gaussian(window_size, 1.5).unsqueeze(1)\nwin2d = win1d.mm(win1d.t()).float().unsqueeze(0).unsqueeze(0)\nself.window = torch.Tensor(win2d.expand... | <|body_start_0|>
super().__init__()
self.bias = bias
self.win_len = window_size
self.channels = channels
self.average = False
if reduction == 'mean':
self.average = True
win1d = gaussian(window_size, 1.5).unsqueeze(1)
win2d = win1d.mm(win1d.t()... | SSimLoss. This is an implementation of structural similarity (SSIM) loss. This code is modified from https://github.com/Po-Hsun-Su/pytorch-ssim. | SSimLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSimLoss:
"""SSimLoss. This is an implementation of structural similarity (SSIM) loss. This code is modified from https://github.com/Po-Hsun-Su/pytorch-ssim."""
def __init__(self, bias: float=6.0, window_size: int=11, channels: int=1, reduction: str='none'):
"""Initialization. Args: ... | stack_v2_sparse_classes_75kplus_train_000961 | 9,540 | permissive | [
{
"docstring": "Initialization. Args: bias (float, optional): value of the bias. Defaults to 6.0. window_size (int, optional): Window size. Defaults to 11. channels (int, optional): Number of channels. Defaults to 1. reduction (str, optional): Type of reduction during the loss calculation. Defaults to \"none\".... | 3 | null | Implement the Python class `SSimLoss` described below.
Class description:
SSimLoss. This is an implementation of structural similarity (SSIM) loss. This code is modified from https://github.com/Po-Hsun-Su/pytorch-ssim.
Method signatures and docstrings:
- def __init__(self, bias: float=6.0, window_size: int=11, channe... | Implement the Python class `SSimLoss` described below.
Class description:
SSimLoss. This is an implementation of structural similarity (SSIM) loss. This code is modified from https://github.com/Po-Hsun-Su/pytorch-ssim.
Method signatures and docstrings:
- def __init__(self, bias: float=6.0, window_size: int=11, channe... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class SSimLoss:
"""SSimLoss. This is an implementation of structural similarity (SSIM) loss. This code is modified from https://github.com/Po-Hsun-Su/pytorch-ssim."""
def __init__(self, bias: float=6.0, window_size: int=11, channels: int=1, reduction: str='none'):
"""Initialization. Args: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SSimLoss:
"""SSimLoss. This is an implementation of structural similarity (SSIM) loss. This code is modified from https://github.com/Po-Hsun-Su/pytorch-ssim."""
def __init__(self, bias: float=6.0, window_size: int=11, channels: int=1, reduction: str='none'):
"""Initialization. Args: bias (float, ... | the_stack_v2_python_sparse | espnet2/tts/prodiff/loss.py | espnet/espnet | train | 7,242 |
0c348a6fed32245193be6c23da985a8aa4b701d1 | [
"self.timeline = timeline\nif not now:\n self.now = today.as_seconds\nelse:\n try:\n self.now = self.timeline[str(now)].as_seconds\n except KeyError:\n self.now = int(now)",
"for pattern in parser.patterns:\n m = pattern.match(expression)\n if m:\n return datetime.from_seconds(... | <|body_start_0|>
self.timeline = timeline
if not now:
self.now = today.as_seconds
else:
try:
self.now = self.timeline[str(now)].as_seconds
except KeyError:
self.now = int(now)
<|end_body_0|>
<|body_start_1|>
for pattern... | A lexical date expression parser that can understand various relative dates. Some examples: 2 days before 3.3206.3.36 11 spans later than now yesterday tomorrow 2 days after tomorrow 11 spans later than now yesterday 1000 years ago on 1.193.1.1 at 2.4839.7.22 If initialized with a timeline, the parser will also support... | parser | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class parser:
"""A lexical date expression parser that can understand various relative dates. Some examples: 2 days before 3.3206.3.36 11 spans later than now yesterday tomorrow 2 days after tomorrow 11 spans later than now yesterday 1000 years ago on 1.193.1.1 at 2.4839.7.22 If initialized with a time... | stack_v2_sparse_classes_75kplus_train_000962 | 26,385 | permissive | [
{
"docstring": "Constructor Args: now (datetime): the date against which calculate the relative date timeline (dict): a dictionary of event datetimes keyed by description",
"name": "__init__",
"signature": "def __init__(self, now=None, timeline={})"
},
{
"docstring": "Parse an expression and ret... | 6 | null | Implement the Python class `parser` described below.
Class description:
A lexical date expression parser that can understand various relative dates. Some examples: 2 days before 3.3206.3.36 11 spans later than now yesterday tomorrow 2 days after tomorrow 11 spans later than now yesterday 1000 years ago on 1.193.1.1 at... | Implement the Python class `parser` described below.
Class description:
A lexical date expression parser that can understand various relative dates. Some examples: 2 days before 3.3206.3.36 11 spans later than now yesterday tomorrow 2 days after tomorrow 11 spans later than now yesterday 1000 years ago on 1.193.1.1 at... | 4152de28ed03afecb579c6065414439146b8b169 | <|skeleton|>
class parser:
"""A lexical date expression parser that can understand various relative dates. Some examples: 2 days before 3.3206.3.36 11 spans later than now yesterday tomorrow 2 days after tomorrow 11 spans later than now yesterday 1000 years ago on 1.193.1.1 at 2.4839.7.22 If initialized with a time... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class parser:
"""A lexical date expression parser that can understand various relative dates. Some examples: 2 days before 3.3206.3.36 11 spans later than now yesterday tomorrow 2 days after tomorrow 11 spans later than now yesterday 1000 years ago on 1.193.1.1 at 2.4839.7.22 If initialized with a timeline, the par... | the_stack_v2_python_sparse | telisar/reckoning/telisaran.py | evilchili/telisar | train | 1 |
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_75kplus_train_000963 | 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_006899 | 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_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | 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 | |
c77345d5ba511683f93e85e494bf18806faf1002 | [
"C = self.COEFFS[imt]\nmag = rup.mag - 6\nd = np.sqrt(dists.rjb ** 2 + C['c7'] ** 2)\nmean = np.zeros_like(d)\nmean += C['c1'] + C['c2'] * mag + C['c3'] * mag ** 2 + C['c6']\nidx = d <= 100.0\nmean[idx] = mean[idx] + C['c5'] * np.log10(d[idx])\nidx = d > 100.0\nmean[idx] = mean[idx] + C['c5'] * np.log10(100.0) - np... | <|body_start_0|>
C = self.COEFFS[imt]
mag = rup.mag - 6
d = np.sqrt(dists.rjb ** 2 + C['c7'] ** 2)
mean = np.zeros_like(d)
mean += C['c1'] + C['c2'] * mag + C['c3'] * mag ** 2 + C['c6']
idx = d <= 100.0
mean[idx] = mean[idx] + C['c5'] * np.log10(d[idx])
id... | Implement equation used by the Geological Survey of Canada (GSC) for the 2010 Western Canada National Seismic Hazard Model. The class implements the model of David M. Boore, William B. Joyner, and Thomas E. Fumal ("Estimation of Response Spectra and Peak Accelerations from Western North American Earthquakes: An Interim... | BooreEtAl1993GSCBest | [
"BSD-3-Clause",
"AGPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BooreEtAl1993GSCBest:
"""Implement equation used by the Geological Survey of Canada (GSC) for the 2010 Western Canada National Seismic Hazard Model. The class implements the model of David M. Boore, William B. Joyner, and Thomas E. Fumal ("Estimation of Response Spectra and Peak Accelerations fro... | stack_v2_sparse_classes_75kplus_train_000964 | 7,227 | permissive | [
{
"docstring": "See :meth:`superclass method <.base.GroundShakingIntensityModel.get_mean_and_stddevs>` for spec of input and result values.",
"name": "get_mean_and_stddevs",
"signature": "def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types)"
},
{
"docstring": "Return total standa... | 2 | stack_v2_sparse_classes_30k_train_001754 | Implement the Python class `BooreEtAl1993GSCBest` described below.
Class description:
Implement equation used by the Geological Survey of Canada (GSC) for the 2010 Western Canada National Seismic Hazard Model. The class implements the model of David M. Boore, William B. Joyner, and Thomas E. Fumal ("Estimation of Resp... | Implement the Python class `BooreEtAl1993GSCBest` described below.
Class description:
Implement equation used by the Geological Survey of Canada (GSC) for the 2010 Western Canada National Seismic Hazard Model. The class implements the model of David M. Boore, William B. Joyner, and Thomas E. Fumal ("Estimation of Resp... | 0da9ba5a575360081715e8b90c71d4b16c6687c8 | <|skeleton|>
class BooreEtAl1993GSCBest:
"""Implement equation used by the Geological Survey of Canada (GSC) for the 2010 Western Canada National Seismic Hazard Model. The class implements the model of David M. Boore, William B. Joyner, and Thomas E. Fumal ("Estimation of Response Spectra and Peak Accelerations fro... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BooreEtAl1993GSCBest:
"""Implement equation used by the Geological Survey of Canada (GSC) for the 2010 Western Canada National Seismic Hazard Model. The class implements the model of David M. Boore, William B. Joyner, and Thomas E. Fumal ("Estimation of Response Spectra and Peak Accelerations from Western Nor... | the_stack_v2_python_sparse | openquake/hazardlib/gsim/boore_1993.py | GFZ-Centre-for-Early-Warning/shakyground | train | 1 |
83d30966b61bc220354410a654bca38fd81de339 | [
"members = ctx.guild.members\nassert len(members) >= 4, 'Member count must be more than 4'\ngenerator = randint(0, len(members) - 1)\nself.members = ctx.guild.members[generator:generator + 4]\nmissing = (len(self.members) - 4) * -1\nfor i in range(missing):\n self.members.append(members[i])\ndel members\nself.ct... | <|body_start_0|>
members = ctx.guild.members
assert len(members) >= 4, 'Member count must be more than 4'
generator = randint(0, len(members) - 1)
self.members = ctx.guild.members[generator:generator + 4]
missing = (len(self.members) - 4) * -1
for i in range(missing):
... | GuessAvatar | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GuessAvatar:
def __init__(self, ctx) -> None:
"""Creates a 'guess what avatar this belongs to' game"""
<|body_0|>
async def start(self) -> bool:
"""begin"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
members = ctx.guild.members
assert len(... | stack_v2_sparse_classes_75kplus_train_000965 | 17,718 | permissive | [
{
"docstring": "Creates a 'guess what avatar this belongs to' game",
"name": "__init__",
"signature": "def __init__(self, ctx) -> None"
},
{
"docstring": "begin",
"name": "start",
"signature": "async def start(self) -> bool"
}
] | 2 | stack_v2_sparse_classes_30k_train_034059 | Implement the Python class `GuessAvatar` described below.
Class description:
Implement the GuessAvatar class.
Method signatures and docstrings:
- def __init__(self, ctx) -> None: Creates a 'guess what avatar this belongs to' game
- async def start(self) -> bool: begin | Implement the Python class `GuessAvatar` described below.
Class description:
Implement the GuessAvatar class.
Method signatures and docstrings:
- def __init__(self, ctx) -> None: Creates a 'guess what avatar this belongs to' game
- async def start(self) -> bool: begin
<|skeleton|>
class GuessAvatar:
def __init_... | b5309b91b9da49a2a5cee1596084d450b987c17a | <|skeleton|>
class GuessAvatar:
def __init__(self, ctx) -> None:
"""Creates a 'guess what avatar this belongs to' game"""
<|body_0|>
async def start(self) -> bool:
"""begin"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GuessAvatar:
def __init__(self, ctx) -> None:
"""Creates a 'guess what avatar this belongs to' game"""
members = ctx.guild.members
assert len(members) >= 4, 'Member count must be more than 4'
generator = randint(0, len(members) - 1)
self.members = ctx.guild.members[gene... | the_stack_v2_python_sparse | framework/games.py | alexshcer/username601 | train | 0 | |
a666a2fad9632507ee471472ecd54d77aa49bde7 | [
"super(PropertiesList, self).__init__(step_name, path, shape_name)\nself.shape_name = shape_name\nself.service_name = service_name\nself._items: Dict[Union[int, str], Properties] = dict()",
"if item not in self._items.keys():\n shape = Properties._shapes_map.get(self.service_name, {}).get(self.shape_name)\n ... | <|body_start_0|>
super(PropertiesList, self).__init__(step_name, path, shape_name)
self.shape_name = shape_name
self.service_name = service_name
self._items: Dict[Union[int, str], Properties] = dict()
<|end_body_0|>
<|body_start_1|>
if item not in self._items.keys():
... | PropertiesList for use in workflow expressions. | PropertiesList | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PropertiesList:
"""PropertiesList for use in workflow expressions."""
def __init__(self, step_name: str, path: str, shape_name: str=None, service_name: str='sagemaker'):
"""Create a PropertiesList instance representing the given shape. Args: step_name (str): The name of the Step this... | stack_v2_sparse_classes_75kplus_train_000966 | 8,233 | permissive | [
{
"docstring": "Create a PropertiesList instance representing the given shape. Args: step_name (str): The name of the Step this Property belongs to. path (str): The relative path of this Property value. shape_name (str): The botocore service model shape name. service_name (str): The botocore service name.",
... | 2 | stack_v2_sparse_classes_30k_train_032976 | Implement the Python class `PropertiesList` described below.
Class description:
PropertiesList for use in workflow expressions.
Method signatures and docstrings:
- def __init__(self, step_name: str, path: str, shape_name: str=None, service_name: str='sagemaker'): Create a PropertiesList instance representing the give... | Implement the Python class `PropertiesList` described below.
Class description:
PropertiesList for use in workflow expressions.
Method signatures and docstrings:
- def __init__(self, step_name: str, path: str, shape_name: str=None, service_name: str='sagemaker'): Create a PropertiesList instance representing the give... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class PropertiesList:
"""PropertiesList for use in workflow expressions."""
def __init__(self, step_name: str, path: str, shape_name: str=None, service_name: str='sagemaker'):
"""Create a PropertiesList instance representing the given shape. Args: step_name (str): The name of the Step this... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PropertiesList:
"""PropertiesList for use in workflow expressions."""
def __init__(self, step_name: str, path: str, shape_name: str=None, service_name: str='sagemaker'):
"""Create a PropertiesList instance representing the given shape. Args: step_name (str): The name of the Step this Property bel... | the_stack_v2_python_sparse | src/sagemaker/workflow/properties.py | aws/sagemaker-python-sdk | train | 2,050 |
3c745dcf5506eb16e0f79c6683374a25a18387a6 | [
"self.name = name + ':'\nself.fwd_lstm = LSTM(fwd_weight_tensors, activation=activation, activation_params=activation_params, name=self.name + 'fwd_lstm')\nself.bwd_lstm = LSTM(bwd_weight_tensors, activation=activation, activation_params=activation_params, name=self.name + 'bwd_lstm')",
"fwd_outputs, fwd_state = ... | <|body_start_0|>
self.name = name + ':'
self.fwd_lstm = LSTM(fwd_weight_tensors, activation=activation, activation_params=activation_params, name=self.name + 'fwd_lstm')
self.bwd_lstm = LSTM(bwd_weight_tensors, activation=activation, activation_params=activation_params, name=self.name + 'bwd_lst... | BidirectionalLSTM | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BidirectionalLSTM:
def __init__(self, fwd_weight_tensors, bwd_weight_tensors, activation='tanh', activation_params=dict(), name='bidir_lstm'):
"""A bidirectional LSTM layer. Args: fwd_weight_tensors: weights used for the forward LSTM. bwd_weight_tensors: weights used for the backward LST... | stack_v2_sparse_classes_75kplus_train_000967 | 6,227 | permissive | [
{
"docstring": "A bidirectional LSTM layer. Args: fwd_weight_tensors: weights used for the forward LSTM. bwd_weight_tensors: weights used for the backward LSTM. activation/activation_params: See in the LSTM class.",
"name": "__init__",
"signature": "def __init__(self, fwd_weight_tensors, bwd_weight_tens... | 2 | null | Implement the Python class `BidirectionalLSTM` described below.
Class description:
Implement the BidirectionalLSTM class.
Method signatures and docstrings:
- def __init__(self, fwd_weight_tensors, bwd_weight_tensors, activation='tanh', activation_params=dict(), name='bidir_lstm'): A bidirectional LSTM layer. Args: fw... | Implement the Python class `BidirectionalLSTM` described below.
Class description:
Implement the BidirectionalLSTM class.
Method signatures and docstrings:
- def __init__(self, fwd_weight_tensors, bwd_weight_tensors, activation='tanh', activation_params=dict(), name='bidir_lstm'): A bidirectional LSTM layer. Args: fw... | 01ef7892bb25cb08c13cea6125efc1528a8de260 | <|skeleton|>
class BidirectionalLSTM:
def __init__(self, fwd_weight_tensors, bwd_weight_tensors, activation='tanh', activation_params=dict(), name='bidir_lstm'):
"""A bidirectional LSTM layer. Args: fwd_weight_tensors: weights used for the forward LSTM. bwd_weight_tensors: weights used for the backward LST... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BidirectionalLSTM:
def __init__(self, fwd_weight_tensors, bwd_weight_tensors, activation='tanh', activation_params=dict(), name='bidir_lstm'):
"""A bidirectional LSTM layer. Args: fwd_weight_tensors: weights used for the forward LSTM. bwd_weight_tensors: weights used for the backward LSTM. activation/... | the_stack_v2_python_sparse | smaug/python/ops/recurrent.py | mrbeann/smaug | train | 0 | |
286ec5fbbed7a877cc04dff967dff3bc804d7a71 | [
"super(self.__class__, self).__init__()\nself.hash = hash_f\nself.key_len = key_len\nself.key = ''\nself.key_gen = key_gen",
"if self.key_gen is None:\n self.key = random_string(self.key_len)\nelse:\n self.key = self.key_gen()\nreturn self.key",
"x1, x2 = x\nif x1 == x2 or self.hash(self.key, x1) == None:... | <|body_start_0|>
super(self.__class__, self).__init__()
self.hash = hash_f
self.key_len = key_len
self.key = ''
self.key_gen = key_gen
<|end_body_0|>
<|body_start_1|>
if self.key_gen is None:
self.key = random_string(self.key_len)
else:
se... | This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function. | GameCR | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameCR:
"""This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function."""
def __init__(self, hash_f, key_len, key_gen=None):
""":param hash_f: T... | stack_v2_sparse_classes_75kplus_train_000968 | 1,745 | no_license | [
{
"docstring": ":param hash_f: This is the hash function that the adversary is playing against. It must take two parameters, a key of length key_len and a message. :param key_len: Length of key used by hash function.",
"name": "__init__",
"signature": "def __init__(self, hash_f, key_len, key_gen=None)"
... | 3 | stack_v2_sparse_classes_30k_train_053448 | Implement the Python class `GameCR` described below.
Class description:
This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function.
Method signatures and docstrings:
- def __init... | Implement the Python class `GameCR` described below.
Class description:
This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function.
Method signatures and docstrings:
- def __init... | 9014f5a9bf7021bef9f5cc4aa5b16424ca83dee9 | <|skeleton|>
class GameCR:
"""This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function."""
def __init__(self, hash_f, key_len, key_gen=None):
""":param hash_f: T... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GameCR:
"""This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function."""
def __init__(self, hash_f, key_len, key_gen=None):
""":param hash_f: This is the ha... | the_stack_v2_python_sparse | src/playcrypt/games/game_cr.py | UCSDCSE107/playcrypt | train | 2 |
27e37ed6be765abaa07ff4a912dfa1972a82dc2e | [
"self.end_time_usecs = end_time_usecs\nself.environment = environment\nself.job_uids = job_uids\nself.protection_source_id = protection_source_id\nself.start_time_usecs = start_time_usecs",
"if dictionary is None:\n return None\nend_time_usecs = dictionary.get('endTimeUsecs')\nenvironment = dictionary.get('env... | <|body_start_0|>
self.end_time_usecs = end_time_usecs
self.environment = environment
self.job_uids = job_uids
self.protection_source_id = protection_source_id
self.start_time_usecs = start_time_usecs
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
retu... | Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Timestamp (in microseconds). environment (EnvironmentRestorePointsForTimeRangeParamEnum): Specifies... | RestorePointsForTimeRangeParam | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestorePointsForTimeRangeParam:
"""Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Timestamp (in microseconds). environment ... | stack_v2_sparse_classes_75kplus_train_000969 | 6,957 | permissive | [
{
"docstring": "Constructor for the RestorePointsForTimeRangeParam class",
"name": "__init__",
"signature": "def __init__(self, end_time_usecs=None, environment=None, job_uids=None, protection_source_id=None, start_time_usecs=None)"
},
{
"docstring": "Creates an instance of this model from a dic... | 2 | stack_v2_sparse_classes_30k_train_025997 | Implement the Python class `RestorePointsForTimeRangeParam` described below.
Class description:
Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Ti... | Implement the Python class `RestorePointsForTimeRangeParam` described below.
Class description:
Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Ti... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestorePointsForTimeRangeParam:
"""Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Timestamp (in microseconds). environment ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RestorePointsForTimeRangeParam:
"""Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Timestamp (in microseconds). environment (EnvironmentR... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_points_for_time_range_param.py | cohesity/management-sdk-python | train | 24 |
15baddc4eac9f5b77a5e9bf7fdc2787716fa6825 | [
"self.latitude = latitude\nself.longitude = longitude\nself.headers = {USER_AGENT: HA_USER_AGENT}\nself.threshold = int(threshold)\nself.is_visible = None\nself.is_visible_text = None\nself.visibility_level = None",
"try:\n self.visibility_level = self.get_aurora_forecast()\n if int(self.visibility_level) >... | <|body_start_0|>
self.latitude = latitude
self.longitude = longitude
self.headers = {USER_AGENT: HA_USER_AGENT}
self.threshold = int(threshold)
self.is_visible = None
self.is_visible_text = None
self.visibility_level = None
<|end_body_0|>
<|body_start_1|>
... | Get aurora forecast. | AuroraData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuroraData:
"""Get aurora forecast."""
def __init__(self, latitude, longitude, threshold):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Get the latest data from the Aurora service."""
<|body_1|>
def get_aurora_forecast(self):
... | stack_v2_sparse_classes_75kplus_train_000970 | 4,922 | permissive | [
{
"docstring": "Initialize the data object.",
"name": "__init__",
"signature": "def __init__(self, latitude, longitude, threshold)"
},
{
"docstring": "Get the latest data from the Aurora service.",
"name": "update",
"signature": "def update(self)"
},
{
"docstring": "Get forecast ... | 3 | stack_v2_sparse_classes_30k_train_048739 | Implement the Python class `AuroraData` described below.
Class description:
Get aurora forecast.
Method signatures and docstrings:
- def __init__(self, latitude, longitude, threshold): Initialize the data object.
- def update(self): Get the latest data from the Aurora service.
- def get_aurora_forecast(self): Get for... | Implement the Python class `AuroraData` described below.
Class description:
Get aurora forecast.
Method signatures and docstrings:
- def __init__(self, latitude, longitude, threshold): Initialize the data object.
- def update(self): Get the latest data from the Aurora service.
- def get_aurora_forecast(self): Get for... | ed4ab403deaed9e8c95e0db728477fcb012bf4fa | <|skeleton|>
class AuroraData:
"""Get aurora forecast."""
def __init__(self, latitude, longitude, threshold):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Get the latest data from the Aurora service."""
<|body_1|>
def get_aurora_forecast(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuroraData:
"""Get aurora forecast."""
def __init__(self, latitude, longitude, threshold):
"""Initialize the data object."""
self.latitude = latitude
self.longitude = longitude
self.headers = {USER_AGENT: HA_USER_AGENT}
self.threshold = int(threshold)
self.... | the_stack_v2_python_sparse | homeassistant/components/aurora/binary_sensor.py | tchellomello/home-assistant | train | 8 |
5d31725e2e365272579c381749a397c815d54153 | [
"try:\n validate_email(email)\nexcept ValidationError:\n raise ValueError('Invalid email address, please try again.')\nuser = self.model(email=self.normalize_email(email))\nif password:\n user.set_password(password)\nelse:\n user.set_unusable_password()\nuser.save(using=self._db)\nreturn user",
"user ... | <|body_start_0|>
try:
validate_email(email)
except ValidationError:
raise ValueError('Invalid email address, please try again.')
user = self.model(email=self.normalize_email(email))
if password:
user.set_password(password)
else:
use... | RinkUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RinkUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email and password."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the given email and password."""
<|bo... | stack_v2_sparse_classes_75kplus_train_000971 | 9,151 | no_license | [
{
"docstring": "Creates and saves a User with the given email and password.",
"name": "create_user",
"signature": "def create_user(self, email, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email and password.",
"name": "create_superuser",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_005685 | Implement the Python class `RinkUserManager` described below.
Class description:
Implement the RinkUserManager class.
Method signatures and docstrings:
- def create_user(self, email, password=None): Creates and saves a User with the given email and password.
- def create_superuser(self, email, password): Creates and ... | Implement the Python class `RinkUserManager` described below.
Class description:
Implement the RinkUserManager class.
Method signatures and docstrings:
- def create_user(self, email, password=None): Creates and saves a User with the given email and password.
- def create_superuser(self, email, password): Creates and ... | e3eebf1a9bce85616df698f7e33a01688929fe53 | <|skeleton|>
class RinkUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email and password."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the given email and password."""
<|bo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RinkUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email and password."""
try:
validate_email(email)
except ValidationError:
raise ValueError('Invalid email address, please try again.')
user = self.mo... | the_stack_v2_python_sparse | rink/users/models.py | MadisonRollerDerby/rink | train | 0 | |
da1d1184ef77c3d4f4f8389cdd4213f0d1aaac29 | [
"self.num_points = num_points\nself.x_values = [0]\nself.y_values = [0]",
"while len(self.x_values) < self.num_points:\n x_step = self.get_step()\n y_step = self.get_step()\n if x_step == 0 and y_step == 0:\n continue\n next_x = self.x_values[-1] + x_step\n next_y = self.y_values[-1] + y_ste... | <|body_start_0|>
self.num_points = num_points
self.x_values = [0]
self.y_values = [0]
<|end_body_0|>
<|body_start_1|>
while len(self.x_values) < self.num_points:
x_step = self.get_step()
y_step = self.get_step()
if x_step == 0 and y_step == 0:
... | 一个生产随机漫步数据的类 | RandomWalk | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomWalk:
"""一个生产随机漫步数据的类"""
def __init__(self, num_points=5000):
"""初始化随机漫步的属性"""
<|body_0|>
def fill_walk(self):
"""计算随机漫步包含的所有点"""
<|body_1|>
def get_step(self):
"""获取每次漫步的距离和方向"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_000972 | 1,452 | no_license | [
{
"docstring": "初始化随机漫步的属性",
"name": "__init__",
"signature": "def __init__(self, num_points=5000)"
},
{
"docstring": "计算随机漫步包含的所有点",
"name": "fill_walk",
"signature": "def fill_walk(self)"
},
{
"docstring": "获取每次漫步的距离和方向",
"name": "get_step",
"signature": "def get_step(s... | 3 | stack_v2_sparse_classes_30k_train_039731 | Implement the Python class `RandomWalk` described below.
Class description:
一个生产随机漫步数据的类
Method signatures and docstrings:
- def __init__(self, num_points=5000): 初始化随机漫步的属性
- def fill_walk(self): 计算随机漫步包含的所有点
- def get_step(self): 获取每次漫步的距离和方向 | Implement the Python class `RandomWalk` described below.
Class description:
一个生产随机漫步数据的类
Method signatures and docstrings:
- def __init__(self, num_points=5000): 初始化随机漫步的属性
- def fill_walk(self): 计算随机漫步包含的所有点
- def get_step(self): 获取每次漫步的距离和方向
<|skeleton|>
class RandomWalk:
"""一个生产随机漫步数据的类"""
def __init__(s... | 6f91fe5e7cbedcdf4b8f7baa7641fd615b4d6141 | <|skeleton|>
class RandomWalk:
"""一个生产随机漫步数据的类"""
def __init__(self, num_points=5000):
"""初始化随机漫步的属性"""
<|body_0|>
def fill_walk(self):
"""计算随机漫步包含的所有点"""
<|body_1|>
def get_step(self):
"""获取每次漫步的距离和方向"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RandomWalk:
"""一个生产随机漫步数据的类"""
def __init__(self, num_points=5000):
"""初始化随机漫步的属性"""
self.num_points = num_points
self.x_values = [0]
self.y_values = [0]
def fill_walk(self):
"""计算随机漫步包含的所有点"""
while len(self.x_values) < self.num_points:
x_... | the_stack_v2_python_sparse | demos/data-analysis/data_visual_by_generate/random_walk.py | romanticair/python | train | 0 |
cd35bc9d28049344fd3cfaaf3b6885ad02ac5583 | [
"profile.addListsToCraftTypeRepository('skeinforge_tools.craft_plugins.feed.html', self)\nself.fileNameInput = settings.FileNameInput().getFromFileName(interpret.getGNUTranslatorGcodeFileTypeTuples(), 'Open File for Feed', self, '')\nself.activateFeed = settings.BooleanSetting().getFromValue('Activate Feed:', self,... | <|body_start_0|>
profile.addListsToCraftTypeRepository('skeinforge_tools.craft_plugins.feed.html', self)
self.fileNameInput = settings.FileNameInput().getFromFileName(interpret.getGNUTranslatorGcodeFileTypeTuples(), 'Open File for Feed', self, '')
self.activateFeed = settings.BooleanSetting().ge... | A class to handle the feed settings. | FeedRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeedRepository:
"""A class to handle the feed settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Feed button has been clicked."""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_75kplus_train_000973 | 8,389 | no_license | [
{
"docstring": "Set the default settings, execute title & settings fileName.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Feed button has been clicked.",
"name": "execute",
"signature": "def execute(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011266 | Implement the Python class `FeedRepository` described below.
Class description:
A class to handle the feed settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Feed button has been clicked. | Implement the Python class `FeedRepository` described below.
Class description:
A class to handle the feed settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Feed button has been clicked.
<|skeleton|>
class FeedRepositor... | fd69d8e856780c826386dc973ceabcc03623f3e8 | <|skeleton|>
class FeedRepository:
"""A class to handle the feed settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Feed button has been clicked."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FeedRepository:
"""A class to handle the feed settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
profile.addListsToCraftTypeRepository('skeinforge_tools.craft_plugins.feed.html', self)
self.fileNameInput = settings.FileNameInput().g... | the_stack_v2_python_sparse | skeinforge_tools/craft_plugins/feed.py | bmander/skeinforge | train | 34 |
7d1fac98740f1012214e7d7e9f6a51fc05d8a1c5 | [
"super(SimpleEncoderDecoder, self).__init__(params)\nself.max_length = params['max_length']\nself.input_voc_size = params['input_voc_size']\nself.hidden_size = params['hidden_size']\nself.encoder_bidirectional = params['encoder_bidirectional']\nself.encoder = EncoderRNN(input_voc_size=self.input_voc_size, hidden_si... | <|body_start_0|>
super(SimpleEncoderDecoder, self).__init__(params)
self.max_length = params['max_length']
self.input_voc_size = params['input_voc_size']
self.hidden_size = params['hidden_size']
self.encoder_bidirectional = params['encoder_bidirectional']
self.encoder = E... | Sequence to Sequence model based on EncoderRNN & DecoderRNN. | SimpleEncoderDecoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleEncoderDecoder:
"""Sequence to Sequence model based on EncoderRNN & DecoderRNN."""
def __init__(self, params):
"""Initializes the Encoder-Decoder network. :param params: dict containing the main parameters set: - max_length: maximal length of the input / output sequence of word... | stack_v2_sparse_classes_75kplus_train_000974 | 12,975 | permissive | [
{
"docstring": "Initializes the Encoder-Decoder network. :param params: dict containing the main parameters set: - max_length: maximal length of the input / output sequence of words: i.e, max length of the sentences to translate -> upper limit of seq_length - input_voc_size: should correspond to the length of t... | 3 | stack_v2_sparse_classes_30k_test_001788 | Implement the Python class `SimpleEncoderDecoder` described below.
Class description:
Sequence to Sequence model based on EncoderRNN & DecoderRNN.
Method signatures and docstrings:
- def __init__(self, params): Initializes the Encoder-Decoder network. :param params: dict containing the main parameters set: - max_leng... | Implement the Python class `SimpleEncoderDecoder` described below.
Class description:
Sequence to Sequence model based on EncoderRNN & DecoderRNN.
Method signatures and docstrings:
- def __init__(self, params): Initializes the Encoder-Decoder network. :param params: dict containing the main parameters set: - max_leng... | c655c88cc6aec4d0724c19ea95209f1c2dd6770d | <|skeleton|>
class SimpleEncoderDecoder:
"""Sequence to Sequence model based on EncoderRNN & DecoderRNN."""
def __init__(self, params):
"""Initializes the Encoder-Decoder network. :param params: dict containing the main parameters set: - max_length: maximal length of the input / output sequence of word... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleEncoderDecoder:
"""Sequence to Sequence model based on EncoderRNN & DecoderRNN."""
def __init__(self, params):
"""Initializes the Encoder-Decoder network. :param params: dict containing the main parameters set: - max_length: maximal length of the input / output sequence of words: i.e, max l... | the_stack_v2_python_sparse | models/text2text/simple_encoder_decoder.py | aasseman/mi-prometheus | train | 0 |
b8fba8cbe306db11fa935145005cf588ef4a9f39 | [
"self.user = get_object_or_404(User, username=kwargs['username'])\nself.profile = self.user.profile\nreturn super(ProfileView, self).dispatch(request, *args, **kwargs)",
"context = super(ProfileView, self).get_context_data(**kwargs)\ncontext['profile'] = self.profile\nreturn context",
"initial = super(ProfileVi... | <|body_start_0|>
self.user = get_object_or_404(User, username=kwargs['username'])
self.profile = self.user.profile
return super(ProfileView, self).dispatch(request, *args, **kwargs)
<|end_body_0|>
<|body_start_1|>
context = super(ProfileView, self).get_context_data(**kwargs)
con... | ProfileView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileView:
def dispatch(self, request, *args, **kwargs):
"""check if user is exist else raise 404 :param request: :param args: :param kwargs:"""
<|body_0|>
def get_context_data(self, **kwargs):
"""add the profile instance to the context data :param kwargs: :return:... | stack_v2_sparse_classes_75kplus_train_000975 | 2,780 | no_license | [
{
"docstring": "check if user is exist else raise 404 :param request: :param args: :param kwargs:",
"name": "dispatch",
"signature": "def dispatch(self, request, *args, **kwargs)"
},
{
"docstring": "add the profile instance to the context data :param kwargs: :return:",
"name": "get_context_d... | 5 | null | Implement the Python class `ProfileView` described below.
Class description:
Implement the ProfileView class.
Method signatures and docstrings:
- def dispatch(self, request, *args, **kwargs): check if user is exist else raise 404 :param request: :param args: :param kwargs:
- def get_context_data(self, **kwargs): add ... | Implement the Python class `ProfileView` described below.
Class description:
Implement the ProfileView class.
Method signatures and docstrings:
- def dispatch(self, request, *args, **kwargs): check if user is exist else raise 404 :param request: :param args: :param kwargs:
- def get_context_data(self, **kwargs): add ... | de5e9e9887dee857e6169184aa9c7b74f31d32c4 | <|skeleton|>
class ProfileView:
def dispatch(self, request, *args, **kwargs):
"""check if user is exist else raise 404 :param request: :param args: :param kwargs:"""
<|body_0|>
def get_context_data(self, **kwargs):
"""add the profile instance to the context data :param kwargs: :return:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProfileView:
def dispatch(self, request, *args, **kwargs):
"""check if user is exist else raise 404 :param request: :param args: :param kwargs:"""
self.user = get_object_or_404(User, username=kwargs['username'])
self.profile = self.user.profile
return super(ProfileView, self).d... | the_stack_v2_python_sparse | todo/views/profile_views.py | AmrAnwar/ToDoList | train | 0 | |
06caf0cb733db96dfbba5c34355065cb61dd2747 | [
"self.db_url = _mask_uri(db_url)\nself.client = MDBClient(db_url)\nself.db = self.client.get()\nself._query_collection = self.db[CatalogConstants.catalog_collections['query']]\nself._feature_collection = self.db[CatalogConstants.catalog_collections['feature']]\nself._model_collection = self.db[CatalogConstants.cata... | <|body_start_0|>
self.db_url = _mask_uri(db_url)
self.client = MDBClient(db_url)
self.db = self.client.get()
self._query_collection = self.db[CatalogConstants.catalog_collections['query']]
self._feature_collection = self.db[CatalogConstants.catalog_collections['feature']]
... | Catalog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Catalog:
def __init__(self, db_url: str):
"""initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url"""
<|body_0|>
def save(self, dev_id: str, data_type: str, data: dict):
"""Args: def_id(str): dev identifier data_type(str): f... | stack_v2_sparse_classes_75kplus_train_000976 | 2,944 | no_license | [
{
"docstring": "initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url",
"name": "__init__",
"signature": "def __init__(self, db_url: str)"
},
{
"docstring": "Args: def_id(str): dev identifier data_type(str): feature, query or model object data(dict): ca... | 3 | stack_v2_sparse_classes_30k_train_005948 | Implement the Python class `Catalog` described below.
Class description:
Implement the Catalog class.
Method signatures and docstrings:
- def __init__(self, db_url: str): initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url
- def save(self, dev_id: str, data_type: str, data... | Implement the Python class `Catalog` described below.
Class description:
Implement the Catalog class.
Method signatures and docstrings:
- def __init__(self, db_url: str): initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url
- def save(self, dev_id: str, data_type: str, data... | d9b72831510b8a9e7004d3ccfac073e3ef3c1f52 | <|skeleton|>
class Catalog:
def __init__(self, db_url: str):
"""initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url"""
<|body_0|>
def save(self, dev_id: str, data_type: str, data: dict):
"""Args: def_id(str): dev identifier data_type(str): f... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Catalog:
def __init__(self, db_url: str):
"""initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url"""
self.db_url = _mask_uri(db_url)
self.client = MDBClient(db_url)
self.db = self.client.get()
self._query_collection = self.db[... | the_stack_v2_python_sparse | feature_store/catalog.py | miararoy/feature_store | train | 0 | |
aca5702934631c9b9d20219d191ff13ddee7b3ed | [
"role = db.Role.find_one(Role.role_id == roleId)\nif not role:\n return self.make_response('No such role found', HTTP.NOT_FOUND)\nreturn self.make_response({'role': role})",
"self.reqparse.add_argument('color', type=str, required=True)\nargs = self.reqparse.parse_args()\nrole = db.Role.find_one(Role.role_id ==... | <|body_start_0|>
role = db.Role.find_one(Role.role_id == roleId)
if not role:
return self.make_response('No such role found', HTTP.NOT_FOUND)
return self.make_response({'role': role})
<|end_body_0|>
<|body_start_1|>
self.reqparse.add_argument('color', type=str, required=True... | RoleGet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoleGet:
def get(self, roleId):
"""Get a specific role information"""
<|body_0|>
def put(self, roleId):
"""Update a user role"""
<|body_1|>
def delete(self, roleId):
"""Delete a user role"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_000977 | 3,193 | permissive | [
{
"docstring": "Get a specific role information",
"name": "get",
"signature": "def get(self, roleId)"
},
{
"docstring": "Update a user role",
"name": "put",
"signature": "def put(self, roleId)"
},
{
"docstring": "Delete a user role",
"name": "delete",
"signature": "def de... | 3 | null | Implement the Python class `RoleGet` described below.
Class description:
Implement the RoleGet class.
Method signatures and docstrings:
- def get(self, roleId): Get a specific role information
- def put(self, roleId): Update a user role
- def delete(self, roleId): Delete a user role | Implement the Python class `RoleGet` described below.
Class description:
Implement the RoleGet class.
Method signatures and docstrings:
- def get(self, roleId): Get a specific role information
- def put(self, roleId): Update a user role
- def delete(self, roleId): Delete a user role
<|skeleton|>
class RoleGet:
... | 29a26c705381fdba3538b4efedb25b9e09b387ed | <|skeleton|>
class RoleGet:
def get(self, roleId):
"""Get a specific role information"""
<|body_0|>
def put(self, roleId):
"""Update a user role"""
<|body_1|>
def delete(self, roleId):
"""Delete a user role"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RoleGet:
def get(self, roleId):
"""Get a specific role information"""
role = db.Role.find_one(Role.role_id == roleId)
if not role:
return self.make_response('No such role found', HTTP.NOT_FOUND)
return self.make_response({'role': role})
def put(self, roleId):
... | the_stack_v2_python_sparse | backend/cloud_inquisitor/plugins/views/roles.py | RiotGames/cloud-inquisitor | train | 468 | |
de36d7f1dd04276393eff0162a8fc4b9868748f5 | [
"currX = self.xcor()\ncurrY = self.ycor()\ndXactual = x - currX\ndYactual = y - currY\nlength = math.hypot(dXactual, dYactual)\ntry:\n self.dx = dXactual / length * speed\n self.dy = dYactual / length * speed\nexcept:\n self.dx, self.dy = (0, 0)",
"try:\n newX = self.xcor() + self.dx\n newY = self.... | <|body_start_0|>
currX = self.xcor()
currY = self.ycor()
dXactual = x - currX
dYactual = y - currY
length = math.hypot(dXactual, dYactual)
try:
self.dx = dXactual / length * speed
self.dy = dYactual / length * speed
except:
self... | Creature | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Creature:
def setNormalizedDirection(self, x, y, speed):
"""set turtle t's dx and dy to go towards x,y at the given speed The turtle t need not have dx and dy attributes already set. The cool thing is that turtles don't normally HAVE a dx and a dy attribute When you set them, though, the... | stack_v2_sparse_classes_75kplus_train_000978 | 3,726 | no_license | [
{
"docstring": "set turtle t's dx and dy to go towards x,y at the given speed The turtle t need not have dx and dy attributes already set. The cool thing is that turtles don't normally HAVE a dx and a dy attribute When you set them, though, they are there to use.",
"name": "setNormalizedDirection",
"sig... | 2 | stack_v2_sparse_classes_30k_train_030725 | Implement the Python class `Creature` described below.
Class description:
Implement the Creature class.
Method signatures and docstrings:
- def setNormalizedDirection(self, x, y, speed): set turtle t's dx and dy to go towards x,y at the given speed The turtle t need not have dx and dy attributes already set. The cool... | Implement the Python class `Creature` described below.
Class description:
Implement the Creature class.
Method signatures and docstrings:
- def setNormalizedDirection(self, x, y, speed): set turtle t's dx and dy to go towards x,y at the given speed The turtle t need not have dx and dy attributes already set. The cool... | 8b6875036dd0faa6607cfb9d02dd03bc33f6a8a4 | <|skeleton|>
class Creature:
def setNormalizedDirection(self, x, y, speed):
"""set turtle t's dx and dy to go towards x,y at the given speed The turtle t need not have dx and dy attributes already set. The cool thing is that turtles don't normally HAVE a dx and a dy attribute When you set them, though, the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Creature:
def setNormalizedDirection(self, x, y, speed):
"""set turtle t's dx and dy to go towards x,y at the given speed The turtle t need not have dx and dy attributes already set. The cool thing is that turtles don't normally HAVE a dx and a dy attribute When you set them, though, they are there to... | the_stack_v2_python_sparse | 32 - Turtle Creatures/Code before 2016-12-05/creature-2016-12-01.py | mars-wilson/mat2110 | train | 0 | |
bf9a09e222c6a89d94340b1ad4db3508fab709bd | [
"attachment_data = self.env['ir.attachment'].read_group([('res_model', '=', 'ocean.member.form1'), ('res_id', 'in', self.ids)], ['res_id'], ['res_id'])\nattachment = dict(((data['res_id'], data['res_id_count']) for data in attachment_data))\nfor expense in self:\n expense.attachment_number = attachment.get(expen... | <|body_start_0|>
attachment_data = self.env['ir.attachment'].read_group([('res_model', '=', 'ocean.member.form1'), ('res_id', 'in', self.ids)], ['res_id'], ['res_id'])
attachment = dict(((data['res_id'], data['res_id_count']) for data in attachment_data))
for expense in self:
expense... | MemberOceanMagazeum | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MemberOceanMagazeum:
def _compute_attachment_number(self):
"""附件上传"""
<|body_0|>
def action_get_attachment_view(self):
"""附件上传动作视图"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
attachment_data = self.env['ir.attachment'].read_group([('res_model', ... | stack_v2_sparse_classes_75kplus_train_000979 | 2,689 | no_license | [
{
"docstring": "附件上传",
"name": "_compute_attachment_number",
"signature": "def _compute_attachment_number(self)"
},
{
"docstring": "附件上传动作视图",
"name": "action_get_attachment_view",
"signature": "def action_get_attachment_view(self)"
}
] | 2 | null | Implement the Python class `MemberOceanMagazeum` described below.
Class description:
Implement the MemberOceanMagazeum class.
Method signatures and docstrings:
- def _compute_attachment_number(self): 附件上传
- def action_get_attachment_view(self): 附件上传动作视图 | Implement the Python class `MemberOceanMagazeum` described below.
Class description:
Implement the MemberOceanMagazeum class.
Method signatures and docstrings:
- def _compute_attachment_number(self): 附件上传
- def action_get_attachment_view(self): 附件上传动作视图
<|skeleton|>
class MemberOceanMagazeum:
def _compute_attac... | 9e55a72f988261fc937f305aa4a9e1687fab5052 | <|skeleton|>
class MemberOceanMagazeum:
def _compute_attachment_number(self):
"""附件上传"""
<|body_0|>
def action_get_attachment_view(self):
"""附件上传动作视图"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MemberOceanMagazeum:
def _compute_attachment_number(self):
"""附件上传"""
attachment_data = self.env['ir.attachment'].read_group([('res_model', '=', 'ocean.member.form1'), ('res_id', 'in', self.ids)], ['res_id'], ['res_id'])
attachment = dict(((data['res_id'], data['res_id_count']) for dat... | the_stack_v2_python_sparse | ocean_member_form/models/member_ocean_form1.py | A-you/myaddons | train | 1 | |
686136ad0690d407166c4d7614390e870668b8a5 | [
"record = {}\nvid = [bytes(row['id']).decode('utf-8')]\nrecord[self.alias] = vid\nreturn record",
"record = dict()\nrecord[self.alias] = []\nfor instance in batch:\n record[self.alias].extend(instance[self.alias])\nreturn record"
] | <|body_start_0|>
record = {}
vid = [bytes(row['id']).decode('utf-8')]
record[self.alias] = vid
return record
<|end_body_0|>
<|body_start_1|>
record = dict()
record[self.alias] = []
for instance in batch:
record[self.alias].extend(instance[self.alias])... | VidParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VidParser:
def parse(self, row, training=False):
""":param row: raw feature map {key1: raw_feature1, key2: raw_feature2, ...} :param training: training or not can behave different :return: id feature with {self.alias: feature}"""
<|body_0|>
def collate(self, batch):
... | stack_v2_sparse_classes_75kplus_train_000980 | 5,031 | no_license | [
{
"docstring": ":param row: raw feature map {key1: raw_feature1, key2: raw_feature2, ...} :param training: training or not can behave different :return: id feature with {self.alias: feature}",
"name": "parse",
"signature": "def parse(self, row, training=False)"
},
{
"docstring": ":param batch: l... | 2 | stack_v2_sparse_classes_30k_train_000309 | Implement the Python class `VidParser` described below.
Class description:
Implement the VidParser class.
Method signatures and docstrings:
- def parse(self, row, training=False): :param row: raw feature map {key1: raw_feature1, key2: raw_feature2, ...} :param training: training or not can behave different :return: i... | Implement the Python class `VidParser` described below.
Class description:
Implement the VidParser class.
Method signatures and docstrings:
- def parse(self, row, training=False): :param row: raw feature map {key1: raw_feature1, key2: raw_feature2, ...} :param training: training or not can behave different :return: i... | 6c28ee71417eb12e637ea362dfbc8057ba88c9c8 | <|skeleton|>
class VidParser:
def parse(self, row, training=False):
""":param row: raw feature map {key1: raw_feature1, key2: raw_feature2, ...} :param training: training or not can behave different :return: id feature with {self.alias: feature}"""
<|body_0|>
def collate(self, batch):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VidParser:
def parse(self, row, training=False):
""":param row: raw feature map {key1: raw_feature1, key2: raw_feature2, ...} :param training: training or not can behave different :return: id feature with {self.alias: feature}"""
record = {}
vid = [bytes(row['id']).decode('utf-8')]
... | the_stack_v2_python_sparse | module/feature_parser.py | jiyt17/qq_transformer | train | 1 | |
710fea9c8cb9ca215d255f212994b7883675edf2 | [
"self.__logger = get_logger(__name__)\nself.__logger.info('Creating decorator ')\nself.__topics_receive__ = []\nself.__topics_send__ = []\nself.__connection__ = None\nself.cls = None",
"self.__logger.info('Adding host')\nparent = self\n\ndef inner(cls):\n parent.__logger.info(f'Creating class: {cls}')\n\n c... | <|body_start_0|>
self.__logger = get_logger(__name__)
self.__logger.info('Creating decorator ')
self.__topics_receive__ = []
self.__topics_send__ = []
self.__connection__ = None
self.cls = None
<|end_body_0|>
<|body_start_1|>
self.__logger.info('Adding host')
... | Wrap pykafka functions. Define the decorators and hold the comunication data | KafkaDecorator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KafkaDecorator:
"""Wrap pykafka functions. Define the decorators and hold the comunication data"""
def __init__(self):
"""Create a KafkaDecorator."""
<|body_0|>
def host(self, *args, **kargs):
"""Set the conenction data. Create a new version of the decorated clas... | stack_v2_sparse_classes_75kplus_train_000981 | 5,207 | permissive | [
{
"docstring": "Create a KafkaDecorator.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Set the conenction data. Create a new version of the decorated class that inherits from kafka_client_decorators.client.Client class Parameters ---------- *args A list of arguments ... | 5 | stack_v2_sparse_classes_30k_train_017856 | Implement the Python class `KafkaDecorator` described below.
Class description:
Wrap pykafka functions. Define the decorators and hold the comunication data
Method signatures and docstrings:
- def __init__(self): Create a KafkaDecorator.
- def host(self, *args, **kargs): Set the conenction data. Create a new version ... | Implement the Python class `KafkaDecorator` described below.
Class description:
Wrap pykafka functions. Define the decorators and hold the comunication data
Method signatures and docstrings:
- def __init__(self): Create a KafkaDecorator.
- def host(self, *args, **kargs): Set the conenction data. Create a new version ... | f2c958df88c5698148aae4c5314dd39e31e995c3 | <|skeleton|>
class KafkaDecorator:
"""Wrap pykafka functions. Define the decorators and hold the comunication data"""
def __init__(self):
"""Create a KafkaDecorator."""
<|body_0|>
def host(self, *args, **kargs):
"""Set the conenction data. Create a new version of the decorated clas... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KafkaDecorator:
"""Wrap pykafka functions. Define the decorators and hold the comunication data"""
def __init__(self):
"""Create a KafkaDecorator."""
self.__logger = get_logger(__name__)
self.__logger.info('Creating decorator ')
self.__topics_receive__ = []
self.__... | the_stack_v2_python_sparse | kafka_client_decorators/decorators.py | cdsedson/kafka-decorator | train | 1 |
60d1b0c10846ca92121547c174e02f4cb035778b | [
"nin = self.observation_space.shape[0] + self.action_space.shape[0]\nself.fc1 = nn.Linear(nin, 32)\nself.fc2 = nn.Linear(32, 32)\nself.fc3 = nn.Linear(32, 32)\nself.qvalue = nn.Linear(32, 1)",
"x = F.relu(self.fc1(torch.cat([x, a], dim=1)))\nx = F.relu(self.fc2(x))\nx = F.relu(self.fc3(x))\nreturn self.qvalue(x)"... | <|body_start_0|>
nin = self.observation_space.shape[0] + self.action_space.shape[0]
self.fc1 = nn.Linear(nin, 32)
self.fc2 = nn.Linear(32, 32)
self.fc3 = nn.Linear(32, 32)
self.qvalue = nn.Linear(32, 1)
<|end_body_0|>
<|body_start_1|>
x = F.relu(self.fc1(torch.cat([x, a]... | Q network. | QFBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QFBase:
"""Q network."""
def build(self):
"""Build Network."""
<|body_0|>
def forward(self, x, a):
"""Forward."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nin = self.observation_space.shape[0] + self.action_space.shape[0]
self.fc1 = ... | stack_v2_sparse_classes_75kplus_train_000982 | 14,308 | no_license | [
{
"docstring": "Build Network.",
"name": "build",
"signature": "def build(self)"
},
{
"docstring": "Forward.",
"name": "forward",
"signature": "def forward(self, x, a)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000825 | Implement the Python class `QFBase` described below.
Class description:
Q network.
Method signatures and docstrings:
- def build(self): Build Network.
- def forward(self, x, a): Forward. | Implement the Python class `QFBase` described below.
Class description:
Q network.
Method signatures and docstrings:
- def build(self): Build Network.
- def forward(self, x, a): Forward.
<|skeleton|>
class QFBase:
"""Q network."""
def build(self):
"""Build Network."""
<|body_0|>
def for... | e71c4b12955b01bfb907aa31c91ded6bcd8aaec8 | <|skeleton|>
class QFBase:
"""Q network."""
def build(self):
"""Build Network."""
<|body_0|>
def forward(self, x, a):
"""Forward."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QFBase:
"""Q network."""
def build(self):
"""Build Network."""
nin = self.observation_space.shape[0] + self.action_space.shape[0]
self.fc1 = nn.Linear(nin, 32)
self.fc2 = nn.Linear(32, 32)
self.fc3 = nn.Linear(32, 32)
self.qvalue = nn.Linear(32, 1)
def... | the_stack_v2_python_sparse | dl/rl/algorithms/ddpg.py | cbschaff/dl | train | 1 |
d0ee64a91e7e9fd5c126afeef26dd6352f7f34c7 | [
"if fname:\n if not fname.endswith('.pkl'):\n fname = fname + '.pkl'\n ifile = open(fname, 'rb')\n self._archive = pkl.load(ifile)\n ifile.close()\nelse:\n self._archive = None\nself._fname = fname\nself._pulled = {}\nself._new = {}\nif kwds:\n for key, value in list(kwds.items(... | <|body_start_0|>
if fname:
if not fname.endswith('.pkl'):
fname = fname + '.pkl'
ifile = open(fname, 'rb')
self._archive = pkl.load(ifile)
ifile.close()
else:
self._archive = None
self._fname = fname
... | A container class that provides lazy persistance of instance attributes as a Python pickle. This is doubly lazy: attributes are not placed in the namespace until actually requested, and they are not saved to the archive until the AttrStore is explicitly saved. If only NumPy arrays are to be stored, ArrayStore may be mo... | AttrStore | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttrStore:
"""A container class that provides lazy persistance of instance attributes as a Python pickle. This is doubly lazy: attributes are not placed in the namespace until actually requested, and they are not saved to the archive until the AttrStore is explicitly saved. If only NumPy arrays a... | stack_v2_sparse_classes_75kplus_train_000983 | 14,154 | no_license | [
{
"docstring": "Prepare to load attributes from storage if a file name is provided; otherwise support saving of arrays assigned as attributes.",
"name": "__init__",
"signature": "def __init__(self, fname=None, **kwds)"
},
{
"docstring": "Catch references to attributes that have not yet been load... | 5 | stack_v2_sparse_classes_30k_train_048991 | Implement the Python class `AttrStore` described below.
Class description:
A container class that provides lazy persistance of instance attributes as a Python pickle. This is doubly lazy: attributes are not placed in the namespace until actually requested, and they are not saved to the archive until the AttrStore is e... | Implement the Python class `AttrStore` described below.
Class description:
A container class that provides lazy persistance of instance attributes as a Python pickle. This is doubly lazy: attributes are not placed in the namespace until actually requested, and they are not saved to the archive until the AttrStore is e... | 215de4e93b5cf79a1e9f380047b4db92bfeaf45c | <|skeleton|>
class AttrStore:
"""A container class that provides lazy persistance of instance attributes as a Python pickle. This is doubly lazy: attributes are not placed in the namespace until actually requested, and they are not saved to the archive until the AttrStore is explicitly saved. If only NumPy arrays a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AttrStore:
"""A container class that provides lazy persistance of instance attributes as a Python pickle. This is doubly lazy: attributes are not placed in the namespace until actually requested, and they are not saved to the archive until the AttrStore is explicitly saved. If only NumPy arrays are to be stor... | the_stack_v2_python_sparse | package/inference/utils/ioutils.py | tloredo/inference | train | 3 |
fff466408e2ab14ad9e2cf4db573eaba802fe930 | [
"self.logger = Log()\nself.logger.info('########################### TestWaybillConfirm START ###########################')\nconfig = ReadYaml(FileUtil.getProjectObsPath() + '/config/config.yaml').getValue()\napp_package = config['appPackage_chezhu']\napp_activity = config['appActivity_chezhu']\nself.mobile = config... | <|body_start_0|>
self.logger = Log()
self.logger.info('########################### TestWaybillConfirm START ###########################')
config = ReadYaml(FileUtil.getProjectObsPath() + '/config/config.yaml').getValue()
app_package = config['appPackage_chezhu']
app_activity = co... | 凯京车主APP 确认发车 | TestWaybillConfirm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestWaybillConfirm:
"""凯京车主APP 确认发车"""
def setUp(self):
"""前置条件准备"""
<|body_0|>
def tearDown(self):
"""测试环境重置"""
<|body_1|>
def test_bvt_waybill_confirm(self):
"""确认发车操作"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
self.l... | stack_v2_sparse_classes_75kplus_train_000984 | 2,925 | no_license | [
{
"docstring": "前置条件准备",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "测试环境重置",
"name": "tearDown",
"signature": "def tearDown(self)"
},
{
"docstring": "确认发车操作",
"name": "test_bvt_waybill_confirm",
"signature": "def test_bvt_waybill_confirm(self)"
}... | 3 | stack_v2_sparse_classes_30k_train_041491 | Implement the Python class `TestWaybillConfirm` described below.
Class description:
凯京车主APP 确认发车
Method signatures and docstrings:
- def setUp(self): 前置条件准备
- def tearDown(self): 测试环境重置
- def test_bvt_waybill_confirm(self): 确认发车操作 | Implement the Python class `TestWaybillConfirm` described below.
Class description:
凯京车主APP 确认发车
Method signatures and docstrings:
- def setUp(self): 前置条件准备
- def tearDown(self): 测试环境重置
- def test_bvt_waybill_confirm(self): 确认发车操作
<|skeleton|>
class TestWaybillConfirm:
"""凯京车主APP 确认发车"""
def setUp(self):
... | 4112ee34827a68289ba95a30518c4b1ecf38a3b2 | <|skeleton|>
class TestWaybillConfirm:
"""凯京车主APP 确认发车"""
def setUp(self):
"""前置条件准备"""
<|body_0|>
def tearDown(self):
"""测试环境重置"""
<|body_1|>
def test_bvt_waybill_confirm(self):
"""确认发车操作"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestWaybillConfirm:
"""凯京车主APP 确认发车"""
def setUp(self):
"""前置条件准备"""
self.logger = Log()
self.logger.info('########################### TestWaybillConfirm START ###########################')
config = ReadYaml(FileUtil.getProjectObsPath() + '/config/config.yaml').getValue()
... | the_stack_v2_python_sparse | BVT/chezhuAPP/driver_register/test_case/test_waybill_confirm_chezhu.py | penny1205/AppUI | train | 0 |
3b0b7ec40fab6545921022d0553699f6c2c6dbb1 | [
"super(Model, self).__init__()\nself.w2v_size = param['embedding'].shape[1]\nself.vocab_size = param['embedding'].shape[0]\nself.embedding_type = param['embedding_type']\nself.embedding_is_training = param['embedding_is_training']\nself.mode = param['mode']\nself.hidden_size = param['hidden_size']\nself.dropout_p =... | <|body_start_0|>
super(Model, self).__init__()
self.w2v_size = param['embedding'].shape[1]
self.vocab_size = param['embedding'].shape[0]
self.embedding_type = param['embedding_type']
self.embedding_is_training = param['embedding_is_training']
self.mode = param['mode']
... | match-lstm model for machine comprehension | Model | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
"""match-lstm model for machine comprehension"""
def __init__(self, param):
""":param param: embedding, hidden_size, dropout_p, encoder_dropout_p, encoder_direction_num, encoder_layer_num"""
<|body_0|>
def forward(self, batch):
""":param batch: [content, q... | stack_v2_sparse_classes_75kplus_train_000985 | 3,371 | no_license | [
{
"docstring": ":param param: embedding, hidden_size, dropout_p, encoder_dropout_p, encoder_direction_num, encoder_layer_num",
"name": "__init__",
"signature": "def __init__(self, param)"
},
{
"docstring": ":param batch: [content, question, answer_start, answer_end] :return: ans_range (2, batch_... | 2 | stack_v2_sparse_classes_30k_train_019771 | Implement the Python class `Model` described below.
Class description:
match-lstm model for machine comprehension
Method signatures and docstrings:
- def __init__(self, param): :param param: embedding, hidden_size, dropout_p, encoder_dropout_p, encoder_direction_num, encoder_layer_num
- def forward(self, batch): :par... | Implement the Python class `Model` described below.
Class description:
match-lstm model for machine comprehension
Method signatures and docstrings:
- def __init__(self, param): :param param: embedding, hidden_size, dropout_p, encoder_dropout_p, encoder_direction_num, encoder_layer_num
- def forward(self, batch): :par... | 4aaca6397c94ee62ef62e6436c649507ceb1e69b | <|skeleton|>
class Model:
"""match-lstm model for machine comprehension"""
def __init__(self, param):
""":param param: embedding, hidden_size, dropout_p, encoder_dropout_p, encoder_direction_num, encoder_layer_num"""
<|body_0|>
def forward(self, batch):
""":param batch: [content, q... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Model:
"""match-lstm model for machine comprehension"""
def __init__(self, param):
""":param param: embedding, hidden_size, dropout_p, encoder_dropout_p, encoder_direction_num, encoder_layer_num"""
super(Model, self).__init__()
self.w2v_size = param['embedding'].shape[1]
s... | the_stack_v2_python_sparse | modules/match_lstm.py | xy09Player/rd_opinion | train | 2 |
09ab232296c98b5313a90983234befc0750598ed | [
"self.__file = allel.read_vcf(filename, fields=VCFFile.LAYERS + VCFFile.ANNOTATIONS)\nself.sorting = None\nself.n_high_quality_variants = 0\nself.set_quality_threshold(quality_threshold)",
"if quality_threshold is not None:\n q = self.__file[self.QUAL]\n low_quality = q < quality_threshold\n self.n_high_... | <|body_start_0|>
self.__file = allel.read_vcf(filename, fields=VCFFile.LAYERS + VCFFile.ANNOTATIONS)
self.sorting = None
self.n_high_quality_variants = 0
self.set_quality_threshold(quality_threshold)
<|end_body_0|>
<|body_start_1|>
if quality_threshold is not None:
q... | Class representing vcf file | VCFFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VCFFile:
"""Class representing vcf file"""
def __init__(self, filename: str, quality_threshold: Optional[int]=None):
"""Representation for VCF gile Args: filename: path to the vcf file quality_threshold: when set, variants above this thresholds come first"""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus_train_000986 | 6,090 | no_license | [
{
"docstring": "Representation for VCF gile Args: filename: path to the vcf file quality_threshold: when set, variants above this thresholds come first",
"name": "__init__",
"signature": "def __init__(self, filename: str, quality_threshold: Optional[int]=None)"
},
{
"docstring": "Set quality thr... | 5 | null | Implement the Python class `VCFFile` described below.
Class description:
Class representing vcf file
Method signatures and docstrings:
- def __init__(self, filename: str, quality_threshold: Optional[int]=None): Representation for VCF gile Args: filename: path to the vcf file quality_threshold: when set, variants abov... | Implement the Python class `VCFFile` described below.
Class description:
Class representing vcf file
Method signatures and docstrings:
- def __init__(self, filename: str, quality_threshold: Optional[int]=None): Representation for VCF gile Args: filename: path to the vcf file quality_threshold: when set, variants abov... | a14dee58aaf96cb432bebe4003c12a7e32b7a6cc | <|skeleton|>
class VCFFile:
"""Class representing vcf file"""
def __init__(self, filename: str, quality_threshold: Optional[int]=None):
"""Representation for VCF gile Args: filename: path to the vcf file quality_threshold: when set, variants above this thresholds come first"""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VCFFile:
"""Class representing vcf file"""
def __init__(self, filename: str, quality_threshold: Optional[int]=None):
"""Representation for VCF gile Args: filename: path to the vcf file quality_threshold: when set, variants above this thresholds come first"""
self.__file = allel.read_vcf(f... | the_stack_v2_python_sparse | h5/create/dna.py | haochenz96/mosaic | train | 0 |
3d3fee05b3c34f18debfffdc3d62614041cf3ab4 | [
"BaseDbManager.__init__(self, db_connection)\nself.config_lock = BoundedSemaphore(1)\nself.config = self.get_config()",
"value = ''\nself.config_lock.acquire()\ntry:\n self.check_db()\n value = self.get_config()\nfinally:\n self.config_lock.release()\nreturn value",
"self.config_lock.acquire()\ntry:\n ... | <|body_start_0|>
BaseDbManager.__init__(self, db_connection)
self.config_lock = BoundedSemaphore(1)
self.config = self.get_config()
<|end_body_0|>
<|body_start_1|>
value = ''
self.config_lock.acquire()
try:
self.check_db()
value = self.get_config(... | Class that represents the handler object use to manage Alerts in MongoDB :param db_connection: DbConnection instance to handle MongoDb connection :type db_connection: data_manager.managers.DbConnection | ConfigDbManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigDbManager:
"""Class that represents the handler object use to manage Alerts in MongoDB :param db_connection: DbConnection instance to handle MongoDb connection :type db_connection: data_manager.managers.DbConnection"""
def __init__(self, db_connection):
"""Constructor"""
... | stack_v2_sparse_classes_75kplus_train_000987 | 3,170 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, db_connection)"
},
{
"docstring": "Getter for the config attribute :return: Current config in DB :rtype: dict",
"name": "config",
"signature": "def config(self)"
},
{
"docstring": "Setter for confi... | 5 | stack_v2_sparse_classes_30k_train_053449 | Implement the Python class `ConfigDbManager` described below.
Class description:
Class that represents the handler object use to manage Alerts in MongoDB :param db_connection: DbConnection instance to handle MongoDb connection :type db_connection: data_manager.managers.DbConnection
Method signatures and docstrings:
-... | Implement the Python class `ConfigDbManager` described below.
Class description:
Class that represents the handler object use to manage Alerts in MongoDB :param db_connection: DbConnection instance to handle MongoDb connection :type db_connection: data_manager.managers.DbConnection
Method signatures and docstrings:
-... | dc0d84e1f62be38868718410006fed98fb7763a5 | <|skeleton|>
class ConfigDbManager:
"""Class that represents the handler object use to manage Alerts in MongoDB :param db_connection: DbConnection instance to handle MongoDb connection :type db_connection: data_manager.managers.DbConnection"""
def __init__(self, db_connection):
"""Constructor"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConfigDbManager:
"""Class that represents the handler object use to manage Alerts in MongoDB :param db_connection: DbConnection instance to handle MongoDb connection :type db_connection: data_manager.managers.DbConnection"""
def __init__(self, db_connection):
"""Constructor"""
BaseDbManag... | the_stack_v2_python_sparse | data_manager/managers/db_managers/config_db_manager.py | victorgrubio/sonda-data-manager | train | 0 |
b3bd00e3ce0d3b73e80f4933b8d6187d3f90f8c3 | [
"facility = logging.handlers.SysLogHandler.LOG_DAEMON\nself.logger = logger.Logger(name='google-networking', debug=debug, facility=facility)\nself.ip_aliases = ip_aliases\nself.ip_forwarding_enabled = ip_forwarding_enabled\nself.network_setup_enabled = network_setup_enabled\nself.target_instance_ips = target_instan... | <|body_start_0|>
facility = logging.handlers.SysLogHandler.LOG_DAEMON
self.logger = logger.Logger(name='google-networking', debug=debug, facility=facility)
self.ip_aliases = ip_aliases
self.ip_forwarding_enabled = ip_forwarding_enabled
self.network_setup_enabled = network_setup_e... | Manage networking based on changes to network metadata. | NetworkDaemon | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkDaemon:
"""Manage networking based on changes to network metadata."""
def __init__(self, ip_forwarding_enabled, proto_id, ip_aliases, target_instance_ips, dhclient_script, dhcp_command, network_setup_enabled, debug=False):
"""Constructor. Args: ip_forwarding_enabled: bool, Tru... | stack_v2_sparse_classes_75kplus_train_000988 | 7,254 | permissive | [
{
"docstring": "Constructor. Args: ip_forwarding_enabled: bool, True if ip forwarding is enabled. proto_id: string, the routing protocol identifier for Google IP changes. ip_aliases: bool, True if the guest should configure IP alias routes. target_instance_ips: bool, True supports internal IP load balancing. dh... | 3 | stack_v2_sparse_classes_30k_train_040650 | Implement the Python class `NetworkDaemon` described below.
Class description:
Manage networking based on changes to network metadata.
Method signatures and docstrings:
- def __init__(self, ip_forwarding_enabled, proto_id, ip_aliases, target_instance_ips, dhclient_script, dhcp_command, network_setup_enabled, debug=Fa... | Implement the Python class `NetworkDaemon` described below.
Class description:
Manage networking based on changes to network metadata.
Method signatures and docstrings:
- def __init__(self, ip_forwarding_enabled, proto_id, ip_aliases, target_instance_ips, dhclient_script, dhcp_command, network_setup_enabled, debug=Fa... | cf4b33214f770da2299923a5fa73d3d95f66ec35 | <|skeleton|>
class NetworkDaemon:
"""Manage networking based on changes to network metadata."""
def __init__(self, ip_forwarding_enabled, proto_id, ip_aliases, target_instance_ips, dhclient_script, dhcp_command, network_setup_enabled, debug=False):
"""Constructor. Args: ip_forwarding_enabled: bool, Tru... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NetworkDaemon:
"""Manage networking based on changes to network metadata."""
def __init__(self, ip_forwarding_enabled, proto_id, ip_aliases, target_instance_ips, dhclient_script, dhcp_command, network_setup_enabled, debug=False):
"""Constructor. Args: ip_forwarding_enabled: bool, True if ip forwa... | the_stack_v2_python_sparse | packages/python-google-compute-engine/google_compute_engine/networking/network_daemon.py | GoogleCloudPlatform/compute-image-packages | train | 329 |
4cee7a401b7bf864752d86b0923e2a281bd8afbd | [
"self.board = Board(self, width, height)\nself.board.place_mines(num_mines)\nself.start = time.time()",
"while True:\n try:\n move = input(\"Move (col row, like 'ab' - %d left) > \" % self.board.left)\n col = ord(move[0].upper()) - ord('A')\n row = ord(move[1].upper()) - ord('A')\n ... | <|body_start_0|>
self.board = Board(self, width, height)
self.board.place_mines(num_mines)
self.start = time.time()
<|end_body_0|>
<|body_start_1|>
while True:
try:
move = input("Move (col row, like 'ab' - %d left) > " % self.board.left)
col =... | Minesweeper. | Game | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Game:
"""Minesweeper."""
def __init__(self, width=11, height=11, num_mines=11):
"""Initialize game. - Set up bord - Place mines - Note time (so at game end the delta can be shown)"""
<|body_0|>
def get_move(self):
"""Get a move, looping until we get a legal move"... | stack_v2_sparse_classes_75kplus_train_000989 | 5,366 | no_license | [
{
"docstring": "Initialize game. - Set up bord - Place mines - Note time (so at game end the delta can be shown)",
"name": "__init__",
"signature": "def __init__(self, width=11, height=11, num_mines=11)"
},
{
"docstring": "Get a move, looping until we get a legal move",
"name": "get_move",
... | 3 | stack_v2_sparse_classes_30k_train_041583 | Implement the Python class `Game` described below.
Class description:
Minesweeper.
Method signatures and docstrings:
- def __init__(self, width=11, height=11, num_mines=11): Initialize game. - Set up bord - Place mines - Note time (so at game end the delta can be shown)
- def get_move(self): Get a move, looping until... | Implement the Python class `Game` described below.
Class description:
Minesweeper.
Method signatures and docstrings:
- def __init__(self, width=11, height=11, num_mines=11): Initialize game. - Set up bord - Place mines - Note time (so at game end the delta can be shown)
- def get_move(self): Get a move, looping until... | 2244d63607be13c70c531a6e3064f85074111ca7 | <|skeleton|>
class Game:
"""Minesweeper."""
def __init__(self, width=11, height=11, num_mines=11):
"""Initialize game. - Set up bord - Place mines - Note time (so at game end the delta can be shown)"""
<|body_0|>
def get_move(self):
"""Get a move, looping until we get a legal move"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Game:
"""Minesweeper."""
def __init__(self, width=11, height=11, num_mines=11):
"""Initialize game. - Set up bord - Place mines - Note time (so at game end the delta can be shown)"""
self.board = Board(self, width, height)
self.board.place_mines(num_mines)
self.start = tim... | the_stack_v2_python_sparse | HARD/minesweeper/minesweeper.py | jenihuang/hb_challenges | train | 2 |
c4f7bf8753f15a3c51925286c32d8e47832015af | [
"if treeSize == 0:\n return (None, head)\nif treeSize == 1:\n return (TreeNode(head.val), head.next)\nleftTreeSize = treeSize // 2\nrightTreeSize = treeSize - 1 - leftTreeSize\nleftRoot, rootListNode = self.sortedListToBSTHelper(head, leftTreeSize)\nroot = TreeNode(rootListNode.val)\nrightHead = rootListNode.... | <|body_start_0|>
if treeSize == 0:
return (None, head)
if treeSize == 1:
return (TreeNode(head.val), head.next)
leftTreeSize = treeSize // 2
rightTreeSize = treeSize - 1 - leftTreeSize
leftRoot, rootListNode = self.sortedListToBSTHelper(head, leftTreeSize)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortedListToBSTHelper(self, head, treeSize):
"""Moves head forward, and build a balanced tree with the iterated list nodes return a pair (treeRoot, newHead)"""
<|body_0|>
def sortedListToBST(self, head):
""":type head: ListNode :rtype: TreeNode"""
... | stack_v2_sparse_classes_75kplus_train_000990 | 1,535 | no_license | [
{
"docstring": "Moves head forward, and build a balanced tree with the iterated list nodes return a pair (treeRoot, newHead)",
"name": "sortedListToBSTHelper",
"signature": "def sortedListToBSTHelper(self, head, treeSize)"
},
{
"docstring": ":type head: ListNode :rtype: TreeNode",
"name": "s... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortedListToBSTHelper(self, head, treeSize): Moves head forward, and build a balanced tree with the iterated list nodes return a pair (treeRoot, newHead)
- def sortedListToBS... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortedListToBSTHelper(self, head, treeSize): Moves head forward, and build a balanced tree with the iterated list nodes return a pair (treeRoot, newHead)
- def sortedListToBS... | 6e051eb554d9cf6f424f1e0a77f3072adf7f64c4 | <|skeleton|>
class Solution:
def sortedListToBSTHelper(self, head, treeSize):
"""Moves head forward, and build a balanced tree with the iterated list nodes return a pair (treeRoot, newHead)"""
<|body_0|>
def sortedListToBST(self, head):
""":type head: ListNode :rtype: TreeNode"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def sortedListToBSTHelper(self, head, treeSize):
"""Moves head forward, and build a balanced tree with the iterated list nodes return a pair (treeRoot, newHead)"""
if treeSize == 0:
return (None, head)
if treeSize == 1:
return (TreeNode(head.val), head... | the_stack_v2_python_sparse | 109. Convert Sorted List to Binary Search Tree.py | vincent-kangzhou/LeetCode-Python | train | 0 | |
761d059bc51ee29c9b235411e3002479972c7202 | [
"adm = ProjectAdministration()\nproposal = Grading.from_dict(api.payload)\nif proposal is not None:\n 'Wir verwenden Grading_id und Grade des Proposals für die Erzeugung eines Grading-Objektes.'\n grad = adm.create_grading(proposal.get_grade(), proposal.get_participation_id())\n return (grad, 200)\nelse:\n... | <|body_start_0|>
adm = ProjectAdministration()
proposal = Grading.from_dict(api.payload)
if proposal is not None:
'Wir verwenden Grading_id und Grade des Proposals für die Erzeugung eines Grading-Objektes.'
grad = adm.create_grading(proposal.get_grade(), proposal.get_part... | GradingOperations | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GradingOperations:
def post(self):
"""Anlegen eines neuen Grading-Objekts"""
<|body_0|>
def put(self):
"""Update eines bestimmten Grading-Objekts."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
adm = ProjectAdministration()
proposal = Gradi... | stack_v2_sparse_classes_75kplus_train_000991 | 44,493 | no_license | [
{
"docstring": "Anlegen eines neuen Grading-Objekts",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Update eines bestimmten Grading-Objekts.",
"name": "put",
"signature": "def put(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_037300 | Implement the Python class `GradingOperations` described below.
Class description:
Implement the GradingOperations class.
Method signatures and docstrings:
- def post(self): Anlegen eines neuen Grading-Objekts
- def put(self): Update eines bestimmten Grading-Objekts. | Implement the Python class `GradingOperations` described below.
Class description:
Implement the GradingOperations class.
Method signatures and docstrings:
- def post(self): Anlegen eines neuen Grading-Objekts
- def put(self): Update eines bestimmten Grading-Objekts.
<|skeleton|>
class GradingOperations:
def po... | 4b2826225525ae855e15e1174f5cf90466097021 | <|skeleton|>
class GradingOperations:
def post(self):
"""Anlegen eines neuen Grading-Objekts"""
<|body_0|>
def put(self):
"""Update eines bestimmten Grading-Objekts."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GradingOperations:
def post(self):
"""Anlegen eines neuen Grading-Objekts"""
adm = ProjectAdministration()
proposal = Grading.from_dict(api.payload)
if proposal is not None:
'Wir verwenden Grading_id und Grade des Proposals für die Erzeugung eines Grading-Objektes.'... | the_stack_v2_python_sparse | src/main.py | KieserChristian/SW_Praktikum_Gruppe1 | train | 0 | |
984fe6c68213718ea8a4b362e68067059b5680aa | [
"i = m - 1\nj = n - 1\nidx = len(nums1) - 1\nwhile i >= 0 or j >= 0:\n if i >= 0 and j >= 0:\n if nums1[i] < nums2[j]:\n nums1[idx] = nums2[j]\n idx -= 1\n j -= 1\n elif nums1[i] >= nums2[j]:\n nums1[idx] = nums1[i]\n idx -= 1\n i -=... | <|body_start_0|>
i = m - 1
j = n - 1
idx = len(nums1) - 1
while i >= 0 or j >= 0:
if i >= 0 and j >= 0:
if nums1[i] < nums2[j]:
nums1[idx] = nums2[j]
idx -= 1
j -= 1
elif nums1[i] >= n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def merge(self, nums1, m, nums2, n):
""":type nums1: List[int] :type m: int :type nums2: List[int] :type n: int :rtype: None Do not return anything, modify nums1 in-place instead."""
<|body_0|>
def merge(self, nums1: [int], m: int, nums2: [int], n: int) -> None:
... | stack_v2_sparse_classes_75kplus_train_000992 | 1,946 | no_license | [
{
"docstring": ":type nums1: List[int] :type m: int :type nums2: List[int] :type n: int :rtype: None Do not return anything, modify nums1 in-place instead.",
"name": "merge",
"signature": "def merge(self, nums1, m, nums2, n)"
},
{
"docstring": "Do not return anything, modify nums1 in-place inste... | 2 | stack_v2_sparse_classes_30k_train_049428 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, nums1, m, nums2, n): :type nums1: List[int] :type m: int :type nums2: List[int] :type n: int :rtype: None Do not return anything, modify nums1 in-place instead.
-... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, nums1, m, nums2, n): :type nums1: List[int] :type m: int :type nums2: List[int] :type n: int :rtype: None Do not return anything, modify nums1 in-place instead.
-... | ae8bb8bf4ae4026ccaf1dce323b4098547dd35ec | <|skeleton|>
class Solution:
def merge(self, nums1, m, nums2, n):
""":type nums1: List[int] :type m: int :type nums2: List[int] :type n: int :rtype: None Do not return anything, modify nums1 in-place instead."""
<|body_0|>
def merge(self, nums1: [int], m: int, nums2: [int], n: int) -> None:
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def merge(self, nums1, m, nums2, n):
""":type nums1: List[int] :type m: int :type nums2: List[int] :type n: int :rtype: None Do not return anything, modify nums1 in-place instead."""
i = m - 1
j = n - 1
idx = len(nums1) - 1
while i >= 0 or j >= 0:
... | the_stack_v2_python_sparse | leet_code/88. Merge Sorted Array.py | roiei/algo | train | 0 | |
d1318c0a4d41d52a0bb8be4bd0e6cc0b8ff99f4a | [
"if n < 2:\n return 0\nif n == 2:\n return 1\nif n == 3:\n return 2\nporduct = [0] * (n + 1)\nporduct[0] = 0\nporduct[1] = 1\nporduct[2] = 2\nporduct[3] = 3\nres = 0\nfor i in range(4, n + 1):\n maxs = 0\n for j in range(1, i // 2 + 1):\n pro = porduct[j] * porduct[i - j]\n maxs = max(m... | <|body_start_0|>
if n < 2:
return 0
if n == 2:
return 1
if n == 3:
return 2
porduct = [0] * (n + 1)
porduct[0] = 0
porduct[1] = 1
porduct[2] = 2
porduct[3] = 3
res = 0
for i in range(4, n + 1):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def cuttingRope1(self, n):
"""dp,f(n) = max(f(i)*f(n-i)) 由于必须剪一刀，所以对n<=3单独考虑"""
<|body_0|>
def cuttingRope2(self, n):
"""贪婪法，当"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n < 2:
return 0
if n == 2:
re... | stack_v2_sparse_classes_75kplus_train_000993 | 1,202 | no_license | [
{
"docstring": "dp,f(n) = max(f(i)*f(n-i)) 由于必须剪一刀，所以对n<=3单独考虑",
"name": "cuttingRope1",
"signature": "def cuttingRope1(self, n)"
},
{
"docstring": "贪婪法，当",
"name": "cuttingRope2",
"signature": "def cuttingRope2(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_030080 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cuttingRope1(self, n): dp,f(n) = max(f(i)*f(n-i)) 由于必须剪一刀，所以对n<=3单独考虑
- def cuttingRope2(self, n): 贪婪法，当 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cuttingRope1(self, n): dp,f(n) = max(f(i)*f(n-i)) 由于必须剪一刀，所以对n<=3单独考虑
- def cuttingRope2(self, n): 贪婪法，当
<|skeleton|>
class Solution:
def cuttingRope1(self, n):
... | 1c963f69d8542f7741f7a07ff28e4de18d0f1377 | <|skeleton|>
class Solution:
def cuttingRope1(self, n):
"""dp,f(n) = max(f(i)*f(n-i)) 由于必须剪一刀，所以对n<=3单独考虑"""
<|body_0|>
def cuttingRope2(self, n):
"""贪婪法，当"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def cuttingRope1(self, n):
"""dp,f(n) = max(f(i)*f(n-i)) 由于必须剪一刀，所以对n<=3单独考虑"""
if n < 2:
return 0
if n == 2:
return 1
if n == 3:
return 2
porduct = [0] * (n + 1)
porduct[0] = 0
porduct[1] = 1
porduct... | the_stack_v2_python_sparse | 14_CuttingRope.py | VCloser/CodingInterviewChinese2-python | train | 0 | |
51bf63a5476320866fe9b1a519617e8f602d86e0 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ConditionalAccessUsers()",
"from .conditional_access_guests_or_external_users import ConditionalAccessGuestsOrExternalUsers\nfrom .conditional_access_guests_or_external_users import ConditionalAccessGuestsOrExternalUsers\nfields: Dict[... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ConditionalAccessUsers()
<|end_body_0|>
<|body_start_1|>
from .conditional_access_guests_or_external_users import ConditionalAccessGuestsOrExternalUsers
from .conditional_access_guests_o... | ConditionalAccessUsers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConditionalAccessUsers:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessUsers:
"""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 ... | stack_v2_sparse_classes_75kplus_train_000994 | 5,400 | 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: ConditionalAccessUsers",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrimina... | 3 | stack_v2_sparse_classes_30k_train_053024 | Implement the Python class `ConditionalAccessUsers` described below.
Class description:
Implement the ConditionalAccessUsers class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessUsers: Creates a new instance of the appropriate class b... | Implement the Python class `ConditionalAccessUsers` described below.
Class description:
Implement the ConditionalAccessUsers class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessUsers: Creates a new instance of the appropriate class b... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ConditionalAccessUsers:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessUsers:
"""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 ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConditionalAccessUsers:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessUsers:
"""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 Ret... | the_stack_v2_python_sparse | msgraph/generated/models/conditional_access_users.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e45b19d283a19e1481e4bb4fd4799eb77dd719b0 | [
"self.full_course_name = full_course_name\nself.course_name = course_name\nself.course_visibility = course_visibility\nself.begin_day = begin_day\nself.begin_month = begin_month\nself.begin_year = begin_year\nself.end_day = end_day\nself.end_month = end_month\nself.end_year = end_year\nself.id_course = id_course\ns... | <|body_start_0|>
self.full_course_name = full_course_name
self.course_name = course_name
self.course_visibility = course_visibility
self.begin_day = begin_day
self.begin_month = begin_month
self.begin_year = begin_year
self.end_day = end_day
self.end_month... | CreateCourse | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateCourse:
def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_year=None, id_course=None, description_field=None, image_url=None, group_mode=None, forced_group_mode=None, tags_... | stack_v2_sparse_classes_75kplus_train_000995 | 2,824 | permissive | [
{
"docstring": "Construct data.",
"name": "__init__",
"signature": "def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_year=None, id_course=None, description_field=None, image_url=None, ... | 2 | stack_v2_sparse_classes_30k_train_007733 | Implement the Python class `CreateCourse` described below.
Class description:
Implement the CreateCourse class.
Method signatures and docstrings:
- def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_y... | Implement the Python class `CreateCourse` described below.
Class description:
Implement the CreateCourse class.
Method signatures and docstrings:
- def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_y... | 8cd0a53fffe797c47d3b14cc3300c610467432e3 | <|skeleton|>
class CreateCourse:
def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_year=None, id_course=None, description_field=None, image_url=None, group_mode=None, forced_group_mode=None, tags_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CreateCourse:
def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_year=None, id_course=None, description_field=None, image_url=None, group_mode=None, forced_group_mode=None, tags_courses=None):... | the_stack_v2_python_sparse | models/create_course.py | KKashpovski/test_moodle_project | train | 0 | |
69b1db7930589fd859762ce88faf24ad9f1f5254 | [
"if not image_key:\n image_key = 'image/encoded'\nsuper(Image, self).__init__([image_key])\nself._image_key = image_key\nself._shape = shape\nself._channels = channels\nself._dtype = dtype\nself._repeated = repeated",
"image_buffer = keys_to_tensors[self._image_key]\nif self._repeated:\n return functional_o... | <|body_start_0|>
if not image_key:
image_key = 'image/encoded'
super(Image, self).__init__([image_key])
self._image_key = image_key
self._shape = shape
self._channels = channels
self._dtype = dtype
self._repeated = repeated
<|end_body_0|>
<|body_start... | Image | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Image:
def __init__(self, image_key=None, format_key=None, shape=None, channels=3, dtype=tf.uint8, repeated=False):
"""Initializes the image. Args: image_key: the name of the TF-Example feature in which the encoded image is stored. shape: the output shape of the image as 1-D `Tensor` [he... | stack_v2_sparse_classes_75kplus_train_000996 | 5,647 | permissive | [
{
"docstring": "Initializes the image. Args: image_key: the name of the TF-Example feature in which the encoded image is stored. shape: the output shape of the image as 1-D `Tensor` [height, width, channels]. If provided, the image is reshaped accordingly. If left as None, no reshaping is done. A shape should b... | 3 | stack_v2_sparse_classes_30k_train_014329 | Implement the Python class `Image` described below.
Class description:
Implement the Image class.
Method signatures and docstrings:
- def __init__(self, image_key=None, format_key=None, shape=None, channels=3, dtype=tf.uint8, repeated=False): Initializes the image. Args: image_key: the name of the TF-Example feature ... | Implement the Python class `Image` described below.
Class description:
Implement the Image class.
Method signatures and docstrings:
- def __init__(self, image_key=None, format_key=None, shape=None, channels=3, dtype=tf.uint8, repeated=False): Initializes the image. Args: image_key: the name of the TF-Example feature ... | 5f7a17e527edb30480fb7c7783e968956b409b0b | <|skeleton|>
class Image:
def __init__(self, image_key=None, format_key=None, shape=None, channels=3, dtype=tf.uint8, repeated=False):
"""Initializes the image. Args: image_key: the name of the TF-Example feature in which the encoded image is stored. shape: the output shape of the image as 1-D `Tensor` [he... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Image:
def __init__(self, image_key=None, format_key=None, shape=None, channels=3, dtype=tf.uint8, repeated=False):
"""Initializes the image. Args: image_key: the name of the TF-Example feature in which the encoded image is stored. shape: the output shape of the image as 1-D `Tensor` [height, width, c... | the_stack_v2_python_sparse | script/dataset_debug/reader.py | ki-lm/blueoil | train | 0 | |
2cdf1cd40eb37da4cb5e9849beaabb1f2a35ea32 | [
"if max_subspace <= 2 or max_iterations <= 0 or eps <= 0:\n raise ValueError('Invalid values for max_subspace, max_iterations and/ or eps: ({}, {}, {}).'.format(max_subspace, max_iterations, eps))\nself.max_subspace = max_subspace\nself.max_iterations = max_iterations\nself.eps = eps\nself.real_only = real_only"... | <|body_start_0|>
if max_subspace <= 2 or max_iterations <= 0 or eps <= 0:
raise ValueError('Invalid values for max_subspace, max_iterations and/ or eps: ({}, {}, {}).'.format(max_subspace, max_iterations, eps))
self.max_subspace = max_subspace
self.max_iterations = max_iterations
... | Davidson algorithm iteration options. | DavidsonOptions | [
"LicenseRef-scancode-generic-cla",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DavidsonOptions:
"""Davidson algorithm iteration options."""
def __init__(self, max_subspace=100, max_iterations=300, eps=1e-06, real_only=False):
"""Args: max_subspace(int): Max number of vectors in the auxiliary subspace. max_iterations(int): Max number of iterations. eps(float): T... | stack_v2_sparse_classes_75kplus_train_000997 | 19,388 | permissive | [
{
"docstring": "Args: max_subspace(int): Max number of vectors in the auxiliary subspace. max_iterations(int): Max number of iterations. eps(float): The max error for eigen vector error's elements during iterations: linear_operator * v - v * lambda. real_only(bool): Desired eigenvectors are real only or not. Wh... | 2 | stack_v2_sparse_classes_30k_train_004497 | Implement the Python class `DavidsonOptions` described below.
Class description:
Davidson algorithm iteration options.
Method signatures and docstrings:
- def __init__(self, max_subspace=100, max_iterations=300, eps=1e-06, real_only=False): Args: max_subspace(int): Max number of vectors in the auxiliary subspace. max... | Implement the Python class `DavidsonOptions` described below.
Class description:
Davidson algorithm iteration options.
Method signatures and docstrings:
- def __init__(self, max_subspace=100, max_iterations=300, eps=1e-06, real_only=False): Args: max_subspace(int): Max number of vectors in the auxiliary subspace. max... | 788481753c798a72c5cb3aa9f2aa9da3ce3190b0 | <|skeleton|>
class DavidsonOptions:
"""Davidson algorithm iteration options."""
def __init__(self, max_subspace=100, max_iterations=300, eps=1e-06, real_only=False):
"""Args: max_subspace(int): Max number of vectors in the auxiliary subspace. max_iterations(int): Max number of iterations. eps(float): T... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DavidsonOptions:
"""Davidson algorithm iteration options."""
def __init__(self, max_subspace=100, max_iterations=300, eps=1e-06, real_only=False):
"""Args: max_subspace(int): Max number of vectors in the auxiliary subspace. max_iterations(int): Max number of iterations. eps(float): The max error ... | the_stack_v2_python_sparse | src/openfermion/linalg/davidson.py | quantumlib/OpenFermion | train | 1,481 |
78eb557cc6892e4804fda13c4dd94944f6d59141 | [
"max_len = 0\nfor i in range(len(string)):\n for j in range(i, len(string)):\n curr = string[i:j + 1]\n if len(curr) == len(set(curr)):\n max_len = max(max_len, j - i + 1)\nreturn max_len",
"letters = set()\nmax_len = 0\ni = 0\nfor j, char in enumerate(string):\n while letters and c... | <|body_start_0|>
max_len = 0
for i in range(len(string)):
for j in range(i, len(string)):
curr = string[i:j + 1]
if len(curr) == len(set(curr)):
max_len = max(max_len, j - i + 1)
return max_len
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longest_nonrepeat_brute(self, string):
"""Returns length of longest nonrepeating substring. Brute force algorithm. Time complexity: O(n ^ 2). Space complexity: O(1), n is len(string)."""
<|body_0|>
def longest_nonrepeat(self, string):
"""Returns length ... | stack_v2_sparse_classes_75kplus_train_000998 | 3,247 | no_license | [
{
"docstring": "Returns length of longest nonrepeating substring. Brute force algorithm. Time complexity: O(n ^ 2). Space complexity: O(1), n is len(string).",
"name": "longest_nonrepeat_brute",
"signature": "def longest_nonrepeat_brute(self, string)"
},
{
"docstring": "Returns length of longest... | 4 | stack_v2_sparse_classes_30k_train_007054 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longest_nonrepeat_brute(self, string): Returns length of longest nonrepeating substring. Brute force algorithm. Time complexity: O(n ^ 2). Space complexity: O(1), n is len(st... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longest_nonrepeat_brute(self, string): Returns length of longest nonrepeating substring. Brute force algorithm. Time complexity: O(n ^ 2). Space complexity: O(1), n is len(st... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def longest_nonrepeat_brute(self, string):
"""Returns length of longest nonrepeating substring. Brute force algorithm. Time complexity: O(n ^ 2). Space complexity: O(1), n is len(string)."""
<|body_0|>
def longest_nonrepeat(self, string):
"""Returns length ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longest_nonrepeat_brute(self, string):
"""Returns length of longest nonrepeating substring. Brute force algorithm. Time complexity: O(n ^ 2). Space complexity: O(1), n is len(string)."""
max_len = 0
for i in range(len(string)):
for j in range(i, len(string)):
... | the_stack_v2_python_sparse | Hashing/longest_nonrepeating_substring.py | vladn90/Algorithms | train | 0 | |
cf8e9badaf81b60e2599a5b52c4d28a36488f679 | [
"user_name = input('\\nEnter your email: ')\ndevice_name = input('Enter the name of your phone: ')\nreturn self.search(user_name, device_name)",
"while True:\n device_address = None\n print('Searching for device..')\n time.sleep(2)\n nearby_devices = bluetooth.discover_devices()\n for mac_address i... | <|body_start_0|>
user_name = input('\nEnter your email: ')
device_name = input('Enter the name of your phone: ')
return self.search(user_name, device_name)
<|end_body_0|>
<|body_start_1|>
while True:
device_address = None
print('Searching for device..')
... | Class to listen for mac address using bluetooth | BluetoothIOT | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BluetoothIOT:
"""Class to listen for mac address using bluetooth"""
def main(self):
"""Main function"""
<|body_0|>
def search(self, user_name, device_name):
"""Function to search for device with device_name"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_75kplus_train_000999 | 1,463 | no_license | [
{
"docstring": "Main function",
"name": "main",
"signature": "def main(self)"
},
{
"docstring": "Function to search for device with device_name",
"name": "search",
"signature": "def search(self, user_name, device_name)"
}
] | 2 | stack_v2_sparse_classes_30k_train_023991 | Implement the Python class `BluetoothIOT` described below.
Class description:
Class to listen for mac address using bluetooth
Method signatures and docstrings:
- def main(self): Main function
- def search(self, user_name, device_name): Function to search for device with device_name | Implement the Python class `BluetoothIOT` described below.
Class description:
Class to listen for mac address using bluetooth
Method signatures and docstrings:
- def main(self): Main function
- def search(self, user_name, device_name): Function to search for device with device_name
<|skeleton|>
class BluetoothIOT:
... | 8a54132766ce38a7e338218cc70fd58093edd820 | <|skeleton|>
class BluetoothIOT:
"""Class to listen for mac address using bluetooth"""
def main(self):
"""Main function"""
<|body_0|>
def search(self, user_name, device_name):
"""Function to search for device with device_name"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BluetoothIOT:
"""Class to listen for mac address using bluetooth"""
def main(self):
"""Main function"""
user_name = input('\nEnter your email: ')
device_name = input('Enter the name of your phone: ')
return self.search(user_name, device_name)
def search(self, user_nam... | the_stack_v2_python_sparse | AgentPi/bluetoothIOT.py | chrisho251/Car-Share-IoT-Application | train | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.