blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
dc60cee322703e5b35e0f79b25a03572ec843277 | [
"if len(s) == 1:\n return 1\nelif len(s) == 0:\n return 0\nmax_count = 1\nres = []\nfor left in range(len(s)):\n for right in range(left, len(s)):\n if s[right] not in res:\n res.append(s[right])\n else:\n if len(res) > max_count:\n max_count = len(res)\n ... | <|body_start_0|>
if len(s) == 1:
return 1
elif len(s) == 0:
return 0
max_count = 1
res = []
for left in range(len(s)):
for right in range(left, len(s)):
if s[right] not in res:
res.append(s[right])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s: str) -> int:
"""常规做法,时间复杂度为O（n^2），空间复杂度为O（n）"""
<|body_0|>
def lengthOfLongestSubstring_2(self, s: str) -> int:
"""优化上诉代码,使用滑动窗口,时间复杂度为O（n）"""
<|body_1|>
def lengthOfLongestSubstring_3(self, s: str) -> int:... | stack_v2_sparse_classes_36k_train_024100 | 2,931 | no_license | [
{
"docstring": "常规做法,时间复杂度为O（n^2），空间复杂度为O（n）",
"name": "lengthOfLongestSubstring",
"signature": "def lengthOfLongestSubstring(self, s: str) -> int"
},
{
"docstring": "优化上诉代码,使用滑动窗口,时间复杂度为O（n）",
"name": "lengthOfLongestSubstring_2",
"signature": "def lengthOfLongestSubstring_2(self, s: st... | 3 | stack_v2_sparse_classes_30k_train_007109 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s: str) -> int: 常规做法,时间复杂度为O（n^2），空间复杂度为O（n）
- def lengthOfLongestSubstring_2(self, s: str) -> int: 优化上诉代码,使用滑动窗口,时间复杂度为O（n）
- def lengthOfLong... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s: str) -> int: 常规做法,时间复杂度为O（n^2），空间复杂度为O（n）
- def lengthOfLongestSubstring_2(self, s: str) -> int: 优化上诉代码,使用滑动窗口,时间复杂度为O（n）
- def lengthOfLong... | 13e7ec9fe7a92ab13b247bd4edeb1ada5de81a08 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s: str) -> int:
"""常规做法,时间复杂度为O（n^2），空间复杂度为O（n）"""
<|body_0|>
def lengthOfLongestSubstring_2(self, s: str) -> int:
"""优化上诉代码,使用滑动窗口,时间复杂度为O（n）"""
<|body_1|>
def lengthOfLongestSubstring_3(self, s: str) -> int:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLongestSubstring(self, s: str) -> int:
"""常规做法,时间复杂度为O（n^2），空间复杂度为O（n）"""
if len(s) == 1:
return 1
elif len(s) == 0:
return 0
max_count = 1
res = []
for left in range(len(s)):
for right in range(left, len... | the_stack_v2_python_sparse | Algorithms/3_Longest_Substring_Without_Repeating_Characters/Longest_Substring_Without_Repeating_Characters.py | lirui-ML/my_leetcode | train | 1 | |
57e1e5413180d717ac9677d49a89ebf17f99fafc | [
"super().__init__(**kwargs)\nself.batch = batch\nself.targets = list()\nif not (self.user and self.password):\n msg = 'A ClickSend user/pass was not provided.'\n self.logger.warning(msg)\n raise TypeError(msg)\nfor target in parse_phone_no(targets):\n result = is_phone_no(target)\n if not result:\n ... | <|body_start_0|>
super().__init__(**kwargs)
self.batch = batch
self.targets = list()
if not (self.user and self.password):
msg = 'A ClickSend user/pass was not provided.'
self.logger.warning(msg)
raise TypeError(msg)
for target in parse_phone_n... | A wrapper for ClickSend Notifications | NotifyClickSend | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotifyClickSend:
"""A wrapper for ClickSend Notifications"""
def __init__(self, targets=None, batch=False, **kwargs):
"""Initialize ClickSend Object"""
<|body_0|>
def send(self, body, title='', notify_type=NotifyType.INFO, **kwargs):
"""Perform ClickSend Notifica... | stack_v2_sparse_classes_36k_train_024101 | 11,434 | permissive | [
{
"docstring": "Initialize ClickSend Object",
"name": "__init__",
"signature": "def __init__(self, targets=None, batch=False, **kwargs)"
},
{
"docstring": "Perform ClickSend Notification",
"name": "send",
"signature": "def send(self, body, title='', notify_type=NotifyType.INFO, **kwargs)... | 5 | stack_v2_sparse_classes_30k_train_003761 | Implement the Python class `NotifyClickSend` described below.
Class description:
A wrapper for ClickSend Notifications
Method signatures and docstrings:
- def __init__(self, targets=None, batch=False, **kwargs): Initialize ClickSend Object
- def send(self, body, title='', notify_type=NotifyType.INFO, **kwargs): Perfo... | Implement the Python class `NotifyClickSend` described below.
Class description:
A wrapper for ClickSend Notifications
Method signatures and docstrings:
- def __init__(self, targets=None, batch=False, **kwargs): Initialize ClickSend Object
- def send(self, body, title='', notify_type=NotifyType.INFO, **kwargs): Perfo... | be3baed7e3d33bae973f1714df4ebbf65aa33f85 | <|skeleton|>
class NotifyClickSend:
"""A wrapper for ClickSend Notifications"""
def __init__(self, targets=None, batch=False, **kwargs):
"""Initialize ClickSend Object"""
<|body_0|>
def send(self, body, title='', notify_type=NotifyType.INFO, **kwargs):
"""Perform ClickSend Notifica... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotifyClickSend:
"""A wrapper for ClickSend Notifications"""
def __init__(self, targets=None, batch=False, **kwargs):
"""Initialize ClickSend Object"""
super().__init__(**kwargs)
self.batch = batch
self.targets = list()
if not (self.user and self.password):
... | the_stack_v2_python_sparse | apprise/plugins/NotifyClickSend.py | caronc/apprise | train | 8,426 |
1873e840c22c5678876bad7ad8f4cce71d8de4fd | [
"try:\n result = service.JobStateLoader().set_request_time(nnid, json.loads(request.body))\n return_data = {'status': '200', 'result': str(result)}\n return Response(json.dumps(return_data))\nexcept Exception as e:\n return_data = {'status': '400', 'result': str(e)}\n return Response(json.dumps(retur... | <|body_start_0|>
try:
result = service.JobStateLoader().set_request_time(nnid, json.loads(request.body))
return_data = {'status': '200', 'result': str(result)}
return Response(json.dumps(return_data))
except Exception as e:
return_data = {'status': '400', ... | 1. POST : 2. GET : 3. PUT : 4. DELETE : | CommonJobInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommonJobInfo:
"""1. POST : 2. GET : 3. PUT : 4. DELETE :"""
def post(self, request, nnid):
"""set the time on the job :param request: :return:"""
<|body_0|>
def get(self, request):
"""get all job list :param request: :return:"""
<|body_1|>
def put(s... | stack_v2_sparse_classes_36k_train_024102 | 2,335 | no_license | [
{
"docstring": "set the time on the job :param request: :return:",
"name": "post",
"signature": "def post(self, request, nnid)"
},
{
"docstring": "get all job list :param request: :return:",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "set the time on t... | 4 | stack_v2_sparse_classes_30k_train_011956 | Implement the Python class `CommonJobInfo` described below.
Class description:
1. POST : 2. GET : 3. PUT : 4. DELETE :
Method signatures and docstrings:
- def post(self, request, nnid): set the time on the job :param request: :return:
- def get(self, request): get all job list :param request: :return:
- def put(self,... | Implement the Python class `CommonJobInfo` described below.
Class description:
1. POST : 2. GET : 3. PUT : 4. DELETE :
Method signatures and docstrings:
- def post(self, request, nnid): set the time on the job :param request: :return:
- def get(self, request): get all job list :param request: :return:
- def put(self,... | 17216fd58619b56b6a397178d327687c274c238c | <|skeleton|>
class CommonJobInfo:
"""1. POST : 2. GET : 3. PUT : 4. DELETE :"""
def post(self, request, nnid):
"""set the time on the job :param request: :return:"""
<|body_0|>
def get(self, request):
"""get all job list :param request: :return:"""
<|body_1|>
def put(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommonJobInfo:
"""1. POST : 2. GET : 3. PUT : 4. DELETE :"""
def post(self, request, nnid):
"""set the time on the job :param request: :return:"""
try:
result = service.JobStateLoader().set_request_time(nnid, json.loads(request.body))
return_data = {'status': '200'... | the_stack_v2_python_sparse | tfmsarest/views/common_job.py | TensorMSA/tensormsa_server_old | train | 0 |
d59c5bcbf86acd4fe52fa3f4d700dfa09fb8783a | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Run()",
"from ..entity import Entity\nfrom .lifecycle_workflow_processing_status import LifecycleWorkflowProcessingStatus\nfrom .task_processing_result import TaskProcessingResult\nfrom .user_processing_result import UserProcessingResu... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Run()
<|end_body_0|>
<|body_start_1|>
from ..entity import Entity
from .lifecycle_workflow_processing_status import LifecycleWorkflowProcessingStatus
from .task_processing_result... | Run | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Run:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Run:
"""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: Run"""
<|b... | stack_v2_sparse_classes_36k_train_024103 | 7,160 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Run",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse_nod... | 3 | stack_v2_sparse_classes_30k_train_007087 | Implement the Python class `Run` described below.
Class description:
Implement the Run class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Run: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse n... | Implement the Python class `Run` described below.
Class description:
Implement the Run class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Run: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse n... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Run:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Run:
"""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: Run"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Run:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Run:
"""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: Run"""
if not parse_node... | the_stack_v2_python_sparse | msgraph/generated/models/identity_governance/run.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
d7d574cfedebdc55b5c0059f62bf0aa2b3f973fd | [
"output = []\ntemp = []\nfor i in range(1, n):\n temp.append(i)\n for j in range(i + 1, n + 1):\n temp.append(j)\n for k in range(j + 1, n + 1):\n temp.append(k)\n output.append(temp[:])\n temp.pop()\n temp.pop()\n temp.pop()\nreturn output",
"output ... | <|body_start_0|>
output = []
temp = []
for i in range(1, n):
temp.append(i)
for j in range(i + 1, n + 1):
temp.append(j)
for k in range(j + 1, n + 1):
temp.append(k)
output.append(temp[:])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combination(self, n):
"""Example of how to arrange combinations of 3 with numbers 1 -> n"""
<|body_0|>
def combine(self, n, k):
"""Creates all combos of size k using numbers 1 -> n. Does so by starting with lowest possible values in each slot. Increase ... | stack_v2_sparse_classes_36k_train_024104 | 1,918 | no_license | [
{
"docstring": "Example of how to arrange combinations of 3 with numbers 1 -> n",
"name": "combination",
"signature": "def combination(self, n)"
},
{
"docstring": "Creates all combos of size k using numbers 1 -> n. Does so by starting with lowest possible values in each slot. Increase last slot ... | 3 | stack_v2_sparse_classes_30k_train_004992 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combination(self, n): Example of how to arrange combinations of 3 with numbers 1 -> n
- def combine(self, n, k): Creates all combos of size k using numbers 1 -> n. Does so by... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combination(self, n): Example of how to arrange combinations of 3 with numbers 1 -> n
- def combine(self, n, k): Creates all combos of size k using numbers 1 -> n. Does so by... | f33d004d7629d46fbc5670f5b384f8a604d7f1e7 | <|skeleton|>
class Solution:
def combination(self, n):
"""Example of how to arrange combinations of 3 with numbers 1 -> n"""
<|body_0|>
def combine(self, n, k):
"""Creates all combos of size k using numbers 1 -> n. Does so by starting with lowest possible values in each slot. Increase ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def combination(self, n):
"""Example of how to arrange combinations of 3 with numbers 1 -> n"""
output = []
temp = []
for i in range(1, n):
temp.append(i)
for j in range(i + 1, n + 1):
temp.append(j)
for k in ran... | the_stack_v2_python_sparse | Combinations.py | aulee888/LeetCode | train | 0 | |
cd8bef09dad13b5d09caf15c25b217c00d78559d | [
"self.response.set_status(code, message)\nself.response.out.write(message)\nreturn",
"self.response.headers['Content-Type'] = self.JSON_MIMETYPE\nif obj is not None:\n if isinstance(obj, basestring):\n self.response.out.write(obj)\n else:\n self.response.out.write(json.dumps(obj, cls=model.Jso... | <|body_start_0|>
self.response.set_status(code, message)
self.response.out.write(message)
return
<|end_body_0|>
<|body_start_1|>
self.response.headers['Content-Type'] = self.JSON_MIMETYPE
if obj is not None:
if isinstance(obj, basestring):
self.respon... | Base RequestHandler type which provides convenience methods for writing JSON HTTP responses. | JsonRestHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JsonRestHandler:
"""Base RequestHandler type which provides convenience methods for writing JSON HTTP responses."""
def send_error(self, code, message):
"""Convenience method to format an HTTP error response in a standard format."""
<|body_0|>
def send_success(self, obj=... | stack_v2_sparse_classes_36k_train_024105 | 32,317 | no_license | [
{
"docstring": "Convenience method to format an HTTP error response in a standard format.",
"name": "send_error",
"signature": "def send_error(self, code, message)"
},
{
"docstring": "Convenience method to format a PhotoHunt JSON HTTP response in a standard format.",
"name": "send_success",
... | 2 | stack_v2_sparse_classes_30k_train_016768 | Implement the Python class `JsonRestHandler` described below.
Class description:
Base RequestHandler type which provides convenience methods for writing JSON HTTP responses.
Method signatures and docstrings:
- def send_error(self, code, message): Convenience method to format an HTTP error response in a standard forma... | Implement the Python class `JsonRestHandler` described below.
Class description:
Base RequestHandler type which provides convenience methods for writing JSON HTTP responses.
Method signatures and docstrings:
- def send_error(self, code, message): Convenience method to format an HTTP error response in a standard forma... | f236a8cd20af89e889caf1049217fdbb5c45e536 | <|skeleton|>
class JsonRestHandler:
"""Base RequestHandler type which provides convenience methods for writing JSON HTTP responses."""
def send_error(self, code, message):
"""Convenience method to format an HTTP error response in a standard format."""
<|body_0|>
def send_success(self, obj=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JsonRestHandler:
"""Base RequestHandler type which provides convenience methods for writing JSON HTTP responses."""
def send_error(self, code, message):
"""Convenience method to format an HTTP error response in a standard format."""
self.response.set_status(code, message)
self.res... | the_stack_v2_python_sparse | handlers.py | creationexus/django-x | train | 0 |
d0d6c82a0961feb100260b07864f0f72deb5dd69 | [
"N = len(a0)\nself.N = N\nself.nt = [[None] * N for i in range(M.bit_length() + 1)]\nfor i, a in enumerate(a0):\n self.nt[0][i] = a\nfor i in range(1, len(self.nt)):\n for j in range(N):\n if self.nt[i - 1][j] is None:\n self.nt[i][j] = None\n else:\n self.nt[i][j] = self.n... | <|body_start_0|>
N = len(a0)
self.N = N
self.nt = [[None] * N for i in range(M.bit_length() + 1)]
for i, a in enumerate(a0):
self.nt[0][i] = a
for i in range(1, len(self.nt)):
for j in range(N):
if self.nt[i - 1][j] is None:
... | Doubling | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Doubling:
def __init__(self, a0, M):
"""a0 is an array-like object which contains ai, 0 <= i < N. ai is the next value of i."""
<|body_0|>
def apply(self, i, n):
"""Apply n times from i"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
N = len(a0)
... | stack_v2_sparse_classes_36k_train_024106 | 4,141 | permissive | [
{
"docstring": "a0 is an array-like object which contains ai, 0 <= i < N. ai is the next value of i.",
"name": "__init__",
"signature": "def __init__(self, a0, M)"
},
{
"docstring": "Apply n times from i",
"name": "apply",
"signature": "def apply(self, i, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016973 | Implement the Python class `Doubling` described below.
Class description:
Implement the Doubling class.
Method signatures and docstrings:
- def __init__(self, a0, M): a0 is an array-like object which contains ai, 0 <= i < N. ai is the next value of i.
- def apply(self, i, n): Apply n times from i | Implement the Python class `Doubling` described below.
Class description:
Implement the Doubling class.
Method signatures and docstrings:
- def __init__(self, a0, M): a0 is an array-like object which contains ai, 0 <= i < N. ai is the next value of i.
- def apply(self, i, n): Apply n times from i
<|skeleton|>
class ... | 79a16474a8f21310e0fb47e536d527dd5dc6d655 | <|skeleton|>
class Doubling:
def __init__(self, a0, M):
"""a0 is an array-like object which contains ai, 0 <= i < N. ai is the next value of i."""
<|body_0|>
def apply(self, i, n):
"""Apply n times from i"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Doubling:
def __init__(self, a0, M):
"""a0 is an array-like object which contains ai, 0 <= i < N. ai is the next value of i."""
N = len(a0)
self.N = N
self.nt = [[None] * N for i in range(M.bit_length() + 1)]
for i, a in enumerate(a0):
self.nt[0][i] = a
... | the_stack_v2_python_sparse | src/data/1224.py | NULLCT/LOMC | train | 0 | |
c504142bed01a0aa46a494aeb7782f110d64b957 | [
"attachment = super(ir_attachment, self).create(vals)\nif vals.get('res_model', '') == 'hr.travel.request' and vals.get('res_id', False):\n model_obj = self.env['hr.travel.request']\n model = model_obj.browse(vals['res_id'])\n model.attachments_count = model.attachments_count + 1\nreturn attachment",
"re... | <|body_start_0|>
attachment = super(ir_attachment, self).create(vals)
if vals.get('res_model', '') == 'hr.travel.request' and vals.get('res_id', False):
model_obj = self.env['hr.travel.request']
model = model_obj.browse(vals['res_id'])
model.attachments_count = model.... | ir_attachment | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ir_attachment:
def create(self, vals):
"""When a document of a travel request is attached, increase a counting field of documents of that travel request."""
<|body_0|>
def unlink(self):
"""When a document of a travel request is removed, decrease a counting field of d... | stack_v2_sparse_classes_36k_train_024107 | 2,682 | no_license | [
{
"docstring": "When a document of a travel request is attached, increase a counting field of documents of that travel request.",
"name": "create",
"signature": "def create(self, vals)"
},
{
"docstring": "When a document of a travel request is removed, decrease a counting field of documents of t... | 3 | null | Implement the Python class `ir_attachment` described below.
Class description:
Implement the ir_attachment class.
Method signatures and docstrings:
- def create(self, vals): When a document of a travel request is attached, increase a counting field of documents of that travel request.
- def unlink(self): When a docum... | Implement the Python class `ir_attachment` described below.
Class description:
Implement the ir_attachment class.
Method signatures and docstrings:
- def create(self, vals): When a document of a travel request is attached, increase a counting field of documents of that travel request.
- def unlink(self): When a docum... | 673dd0f2a7c0b69a984342b20f55164a97a00529 | <|skeleton|>
class ir_attachment:
def create(self, vals):
"""When a document of a travel request is attached, increase a counting field of documents of that travel request."""
<|body_0|>
def unlink(self):
"""When a document of a travel request is removed, decrease a counting field of d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ir_attachment:
def create(self, vals):
"""When a document of a travel request is attached, increase a counting field of documents of that travel request."""
attachment = super(ir_attachment, self).create(vals)
if vals.get('res_model', '') == 'hr.travel.request' and vals.get('res_id', F... | the_stack_v2_python_sparse | addons/app-trobz-hr/trobz_hr_travel_request/model/base/ir_attachment.py | TinPlusIT05/tms | train | 0 | |
7641f4b73688680421b09ed923321f641ef0eb81 | [
"class K:\n\n def __init__(self, obj, *args):\n self.obj = obj\n\n def __lt__(self, other):\n return mycmp(self.obj, other.obj) < 0\n\n def __gt__(self, other):\n return mycmp(self.obj, other.obj) > 0\n\n def __eq__(self, other):\n return mycmp(self.obj, other.obj) == 0\n\n ... | <|body_start_0|>
class K:
def __init__(self, obj, *args):
self.obj = obj
def __lt__(self, other):
return mycmp(self.obj, other.obj) < 0
def __gt__(self, other):
return mycmp(self.obj, other.obj) > 0
def __eq__(se... | Utilities for graph processing | NLPGraphProcessingUtils | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NLPGraphProcessingUtils:
"""Utilities for graph processing"""
def cmp_to_key(mycmp):
"""Convert a cmp= function into a key= function"""
<|body_0|>
def LoadGraphFromContents(graphStrContents):
"""Loads netwokx graph from json string"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k_train_024108 | 2,394 | no_license | [
{
"docstring": "Convert a cmp= function into a key= function",
"name": "cmp_to_key",
"signature": "def cmp_to_key(mycmp)"
},
{
"docstring": "Loads netwokx graph from json string",
"name": "LoadGraphFromContents",
"signature": "def LoadGraphFromContents(graphStrContents)"
},
{
"do... | 6 | stack_v2_sparse_classes_30k_train_017562 | Implement the Python class `NLPGraphProcessingUtils` described below.
Class description:
Utilities for graph processing
Method signatures and docstrings:
- def cmp_to_key(mycmp): Convert a cmp= function into a key= function
- def LoadGraphFromContents(graphStrContents): Loads netwokx graph from json string
- def Load... | Implement the Python class `NLPGraphProcessingUtils` described below.
Class description:
Utilities for graph processing
Method signatures and docstrings:
- def cmp_to_key(mycmp): Convert a cmp= function into a key= function
- def LoadGraphFromContents(graphStrContents): Loads netwokx graph from json string
- def Load... | fe4aba5b20169754b717b77b5197d589270ca09a | <|skeleton|>
class NLPGraphProcessingUtils:
"""Utilities for graph processing"""
def cmp_to_key(mycmp):
"""Convert a cmp= function into a key= function"""
<|body_0|>
def LoadGraphFromContents(graphStrContents):
"""Loads netwokx graph from json string"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NLPGraphProcessingUtils:
"""Utilities for graph processing"""
def cmp_to_key(mycmp):
"""Convert a cmp= function into a key= function"""
class K:
def __init__(self, obj, *args):
self.obj = obj
def __lt__(self, other):
return mycmp(s... | the_stack_v2_python_sparse | PrefabOptimizationServer/NLPDataProcessing/NLPGraphProcessingUtils.py | waterbooo/Crane-optimization | train | 3 |
99a87cf4dd8dec1c60589536347e0d301d593081 | [
"super().__init__()\nif not isinstance(filename, str):\n raise RuntimeError(\"'{}' is not a valid file name.\".format(filename))\nif not os.path.isfile(filename):\n raise RuntimeError('File not found: {}'.format(filename))\nself._filename = filename",
"name_map = {}\nwith open(self._filename, 'r') as f:\n ... | <|body_start_0|>
super().__init__()
if not isinstance(filename, str):
raise RuntimeError("'{}' is not a valid file name.".format(filename))
if not os.path.isfile(filename):
raise RuntimeError('File not found: {}'.format(filename))
self._filename = filename
<|end_b... | DOE case generator that reads cases from a CSV file. This DOE case generator will accept an existing data set in the form of a CSV file containing DOE cases. The CSV file should have one column per design variable and the header row should have the names of the design variables. Attributes ---------- _filename : str th... | CSVGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSVGenerator:
"""DOE case generator that reads cases from a CSV file. This DOE case generator will accept an existing data set in the form of a CSV file containing DOE cases. The CSV file should have one column per design variable and the header row should have the names of the design variables. ... | stack_v2_sparse_classes_36k_train_024109 | 21,019 | no_license | [
{
"docstring": "Initialize the CSVGenerator. Parameters ---------- filename : str the name of the file from which to read cases",
"name": "__init__",
"signature": "def __init__(self, filename)"
},
{
"docstring": "Generate case. Parameters ---------- design_vars : OrderedDict Dictionary of design... | 2 | stack_v2_sparse_classes_30k_train_000968 | Implement the Python class `CSVGenerator` described below.
Class description:
DOE case generator that reads cases from a CSV file. This DOE case generator will accept an existing data set in the form of a CSV file containing DOE cases. The CSV file should have one column per design variable and the header row should h... | Implement the Python class `CSVGenerator` described below.
Class description:
DOE case generator that reads cases from a CSV file. This DOE case generator will accept an existing data set in the form of a CSV file containing DOE cases. The CSV file should have one column per design variable and the header row should h... | d9e89fe017f1131d554599c248247f73bb9b534d | <|skeleton|>
class CSVGenerator:
"""DOE case generator that reads cases from a CSV file. This DOE case generator will accept an existing data set in the form of a CSV file containing DOE cases. The CSV file should have one column per design variable and the header row should have the names of the design variables. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CSVGenerator:
"""DOE case generator that reads cases from a CSV file. This DOE case generator will accept an existing data set in the form of a CSV file containing DOE cases. The CSV file should have one column per design variable and the header row should have the names of the design variables. Attributes --... | the_stack_v2_python_sparse | venv/Lib/site-packages/openmdao/drivers/doe_generators.py | ManojDjs/Heart-rate-estimation | train | 1 |
b3a45ba5dce18927329522e664da80e338f76f77 | [
"import copy\nh = head\nl = []\nwhile h:\n l.append(h.val)\n h = h.next\nl_re = copy.copy(l)\nl_re.reverse()\nreturn l == l_re",
"if not head:\n return True\nfast = head\nslow = head\nwhile fast and fast.next:\n fast = fast.next.next\n slow = slow.next\npre = None\nif fast:\n slow = slow.next\nw... | <|body_start_0|>
import copy
h = head
l = []
while h:
l.append(h.val)
h = h.next
l_re = copy.copy(l)
l_re.reverse()
return l == l_re
<|end_body_0|>
<|body_start_1|>
if not head:
return True
fast = head
s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def isPalindrome_fs(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
import copy
h = head
l =... | stack_v2_sparse_classes_36k_train_024110 | 1,397 | no_license | [
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "isPalindrome_fs",
"signature": "def isPalindrome_fs(self, head)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head): :type head: ListNode :rtype: bool
- def isPalindrome_fs(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 isPalindrome(self, head): :type head: ListNode :rtype: bool
- def isPalindrome_fs(self, head): :type head: ListNode :rtype: bool
<|skeleton|>
class Solution:
def isPali... | 9f949ae6b5ee178c7153f1c402a92accbf710111 | <|skeleton|>
class Solution:
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def isPalindrome_fs(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
import copy
h = head
l = []
while h:
l.append(h.val)
h = h.next
l_re = copy.copy(l)
l_re.reverse()
return l == l_re
def isPalindrome_fs(s... | the_stack_v2_python_sparse | 算法题/判断回文链表.py | yllzxzyq/Nick-life-of-code | train | 1 | |
dbda750097e52195b1c42f6dffb73a604189bf48 | [
"ans = collections.defaultdict(list)\nfor s in strs:\n ans[tuple(sorted(s))].append(s)\nreturn list(ans.values())",
"ans = collections.defaultdict(list)\nfor s in strs:\n count = [0] * 26\n for c in s:\n count[ord(c) - ord('a')] += 1\n ans[tuple(count)].append(s)\nreturn list(ans.values())"
] | <|body_start_0|>
ans = collections.defaultdict(list)
for s in strs:
ans[tuple(sorted(s))].append(s)
return list(ans.values())
<|end_body_0|>
<|body_start_1|>
ans = collections.defaultdict(list)
for s in strs:
count = [0] * 26
for c in s:
... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def groupAnagrams_1(self, strs: List[str]) -> List[List[str]]:
"""时间复杂度：OO(NKlogK) 空间复杂度：O(NK) :param strs: :return:"""
<|body_0|>
def groupAnagrams_2(self, strs: List[str]) -> List[List[str]]:
"""时间复杂度：O(NK) 空间复杂度：O(NK) :param strs: :return:"""
<|b... | stack_v2_sparse_classes_36k_train_024111 | 1,552 | permissive | [
{
"docstring": "时间复杂度：OO(NKlogK) 空间复杂度：O(NK) :param strs: :return:",
"name": "groupAnagrams_1",
"signature": "def groupAnagrams_1(self, strs: List[str]) -> List[List[str]]"
},
{
"docstring": "时间复杂度：O(NK) 空间复杂度：O(NK) :param strs: :return:",
"name": "groupAnagrams_2",
"signature": "def gro... | 2 | stack_v2_sparse_classes_30k_train_006319 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams_1(self, strs: List[str]) -> List[List[str]]: 时间复杂度：OO(NKlogK) 空间复杂度：O(NK) :param strs: :return:
- def groupAnagrams_2(self, strs: List[str]) -> List[List[str]]:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams_1(self, strs: List[str]) -> List[List[str]]: 时间复杂度：OO(NKlogK) 空间复杂度：O(NK) :param strs: :return:
- def groupAnagrams_2(self, strs: List[str]) -> List[List[str]]:... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def groupAnagrams_1(self, strs: List[str]) -> List[List[str]]:
"""时间复杂度：OO(NKlogK) 空间复杂度：O(NK) :param strs: :return:"""
<|body_0|>
def groupAnagrams_2(self, strs: List[str]) -> List[List[str]]:
"""时间复杂度：O(NK) 空间复杂度：O(NK) :param strs: :return:"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def groupAnagrams_1(self, strs: List[str]) -> List[List[str]]:
"""时间复杂度：OO(NKlogK) 空间复杂度：O(NK) :param strs: :return:"""
ans = collections.defaultdict(list)
for s in strs:
ans[tuple(sorted(s))].append(s)
return list(ans.values())
def groupAnagrams_2(se... | the_stack_v2_python_sparse | LeetCode 热题 HOT 100/groupAnagrams.py | MaoningGuan/LeetCode | train | 3 | |
c64def0f7699e1cad3a372b3efada128e44e97ec | [
"self._old_layer = old_layer\nself._new_layer = new_layer\nif filter_fn is None:\n self._filter_fn = lambda s: True\nelse:\n self._filter_fn = filter_fn",
"del meta_state\nshould_change = [self._filter_fn(s) for s in state[self._old_layer]]\nchange_inds = np.argwhere(should_change)[:, 0]\ncount_changed_alre... | <|body_start_0|>
self._old_layer = old_layer
self._new_layer = new_layer
if filter_fn is None:
self._filter_fn = lambda s: True
else:
self._filter_fn = filter_fn
<|end_body_0|>
<|body_start_1|>
del meta_state
should_change = [self._filter_fn(s) fo... | ChangeLayer rule. This rule is used to change the layer of a sprite based on a filter of the sprite. For example, it could be used to change a sprite's layer if the sprite has changed to a new color. | ChangeLayer | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChangeLayer:
"""ChangeLayer rule. This rule is used to change the layer of a sprite based on a filter of the sprite. For example, it could be used to change a sprite's layer if the sprite has changed to a new color."""
def __init__(self, old_layer, new_layer, filter_fn=None):
"""Cons... | stack_v2_sparse_classes_36k_train_024112 | 1,651 | permissive | [
{
"docstring": "Constructor. Args: old_layer: String. Must be a key in the environment state. Sprites in this layer will be considered for the layer change. new_layer: String. Must be a key in the environment state. Layer to which sprites in old_layer may be moved. filter_fn: Function sprite -> bool. Whether to... | 2 | stack_v2_sparse_classes_30k_train_003984 | Implement the Python class `ChangeLayer` described below.
Class description:
ChangeLayer rule. This rule is used to change the layer of a sprite based on a filter of the sprite. For example, it could be used to change a sprite's layer if the sprite has changed to a new color.
Method signatures and docstrings:
- def _... | Implement the Python class `ChangeLayer` described below.
Class description:
ChangeLayer rule. This rule is used to change the layer of a sprite based on a filter of the sprite. For example, it could be used to change a sprite's layer if the sprite has changed to a new color.
Method signatures and docstrings:
- def _... | 3e89e46a5918d59475851f9d4f1558956c110d38 | <|skeleton|>
class ChangeLayer:
"""ChangeLayer rule. This rule is used to change the layer of a sprite based on a filter of the sprite. For example, it could be used to change a sprite's layer if the sprite has changed to a new color."""
def __init__(self, old_layer, new_layer, filter_fn=None):
"""Cons... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChangeLayer:
"""ChangeLayer rule. This rule is used to change the layer of a sprite based on a filter of the sprite. For example, it could be used to change a sprite's layer if the sprite has changed to a new color."""
def __init__(self, old_layer, new_layer, filter_fn=None):
"""Constructor. Args... | the_stack_v2_python_sparse | moog/game_rules/change_layer.py | hokysung/moog.github.io | train | 0 |
53b585661ac092105f6e7ccf316db3a58239104a | [
"super().__init__(label='Start Plotting')\nself.protocol = linear_actuator_protocol\nself.plotters = plotters\nself.plotting = False\nself.interval = plotting_interval",
"if self.plotting:\n await self.stop_plotting()\nelse:\n await self.start_plotting()",
"if self.plotting:\n return\nawait self.protoc... | <|body_start_0|>
super().__init__(label='Start Plotting')
self.protocol = linear_actuator_protocol
self.plotters = plotters
self.plotting = False
self.interval = plotting_interval
<|end_body_0|>
<|body_start_1|>
if self.plotting:
await self.stop_plotting()
... | Linear actuator plotter functionality toggle, synchronized across documents. | ToggleStatePlottingButton | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ToggleStatePlottingButton:
"""Linear actuator plotter functionality toggle, synchronized across documents."""
def __init__(self, linear_actuator_protocol, plotters, plotting_interval=20):
"""Initialize member variables."""
<|body_0|>
async def toggle_plotting(self):
... | stack_v2_sparse_classes_36k_train_024113 | 23,462 | permissive | [
{
"docstring": "Initialize member variables.",
"name": "__init__",
"signature": "def __init__(self, linear_actuator_protocol, plotters, plotting_interval=20)"
},
{
"docstring": "Toggle plotting.",
"name": "toggle_plotting",
"signature": "async def toggle_plotting(self)"
},
{
"doc... | 5 | stack_v2_sparse_classes_30k_train_008339 | Implement the Python class `ToggleStatePlottingButton` described below.
Class description:
Linear actuator plotter functionality toggle, synchronized across documents.
Method signatures and docstrings:
- def __init__(self, linear_actuator_protocol, plotters, plotting_interval=20): Initialize member variables.
- async... | Implement the Python class `ToggleStatePlottingButton` described below.
Class description:
Linear actuator plotter functionality toggle, synchronized across documents.
Method signatures and docstrings:
- def __init__(self, linear_actuator_protocol, plotters, plotting_interval=20): Initialize member variables.
- async... | fc7043558072e77981206ae123dfd3a24ef89029 | <|skeleton|>
class ToggleStatePlottingButton:
"""Linear actuator plotter functionality toggle, synchronized across documents."""
def __init__(self, linear_actuator_protocol, plotters, plotting_interval=20):
"""Initialize member variables."""
<|body_0|>
async def toggle_plotting(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ToggleStatePlottingButton:
"""Linear actuator plotter functionality toggle, synchronized across documents."""
def __init__(self, linear_actuator_protocol, plotters, plotting_interval=20):
"""Initialize member variables."""
super().__init__(label='Start Plotting')
self.protocol = l... | the_stack_v2_python_sparse | lhrhost/dashboard/linear_actuator/plots.py | ethanjli/liquid-handling-robotics | train | 0 |
4f591ff1b4d2662d55479682e1cee2f827db8fb2 | [
"super().__init__(params=params, modelparams={'phases': {'start': [0, 5], 'on': [5, 50], 'end': [50, 55]}, 'times': [0, 20, 55], 'tstep': 1})\n'\\n Here addflow() takes as input a unique name for the flow \"flowname\", a type for the flow, \"flowtype\"\\n and either: a dict with the initial flow att... | <|body_start_0|>
super().__init__(params=params, modelparams={'phases': {'start': [0, 5], 'on': [5, 50], 'end': [50, 55]}, 'times': [0, 20, 55], 'tstep': 1})
'\n Here addflow() takes as input a unique name for the flow "flowname", a type for the flow, "flowtype"\n and either: a dict with... | This defines the pump model as a Model. Models take a dictionary of parameters as input defining any veriables and values to use in the model. | Pump | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pump:
"""This defines the pump model as a Model. Models take a dictionary of parameters as input defining any veriables and values to use in the model."""
def __init__(self, params={'cost': {'repair', 'water'}, 'delay': 10, 'units': 'hrs'}):
"""To sample the model, the timerange and ... | stack_v2_sparse_classes_36k_train_024114 | 13,659 | permissive | [
{
"docstring": "To sample the model, the timerange and operational phases need to be defined. Here we dod that by setting self.phases as a dictionary of each phase and its start and ending and self.times to the beginning and end time (and any times to sample in between in run_list() self.tstep is the timestep t... | 2 | null | Implement the Python class `Pump` described below.
Class description:
This defines the pump model as a Model. Models take a dictionary of parameters as input defining any veriables and values to use in the model.
Method signatures and docstrings:
- def __init__(self, params={'cost': {'repair', 'water'}, 'delay': 10, ... | Implement the Python class `Pump` described below.
Class description:
This defines the pump model as a Model. Models take a dictionary of parameters as input defining any veriables and values to use in the model.
Method signatures and docstrings:
- def __init__(self, params={'cost': {'repair', 'water'}, 'delay': 10, ... | 2d87c415c036f44fe10310500788f5ab697e618d | <|skeleton|>
class Pump:
"""This defines the pump model as a Model. Models take a dictionary of parameters as input defining any veriables and values to use in the model."""
def __init__(self, params={'cost': {'repair', 'water'}, 'delay': 10, 'units': 'hrs'}):
"""To sample the model, the timerange and ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Pump:
"""This defines the pump model as a Model. Models take a dictionary of parameters as input defining any veriables and values to use in the model."""
def __init__(self, params={'cost': {'repair', 'water'}, 'delay': 10, 'units': 'hrs'}):
"""To sample the model, the timerange and operational p... | the_stack_v2_python_sparse | pump example/ex_pump.py | DesignEngrLab/fmdtools | train | 10 |
c4fbda88dbcc6b8521e16ac7bc0ab7498e269952 | [
"self.__robot = robot\nself.__max_ang_speed = max_ang_speed\nself.__ang_speed_weight = ang_speed_weight\nself.__timer = 0\nself.__turn_around_delay = turn_around_delay",
"if time.time() - self.__timer < self.__turn_around_delay:\n return\nelif force['x'] == 0 and force['y'] == 0:\n self.stop()\nelse:\n f... | <|body_start_0|>
self.__robot = robot
self.__max_ang_speed = max_ang_speed
self.__ang_speed_weight = ang_speed_weight
self.__timer = 0
self.__turn_around_delay = turn_around_delay
<|end_body_0|>
<|body_start_1|>
if time.time() - self.__timer < self.__turn_around_delay:
... | Class that implements a Controller, used as an interface to communicate easily with the Robot object which communicates directly with the MRDS server. | Controller | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
"""Class that implements a Controller, used as an interface to communicate easily with the Robot object which communicates directly with the MRDS server."""
def __init__(self, robot, max_ang_speed=3, ang_speed_weight=0.8, turn_around_delay=8):
"""Instantiates a Controller... | stack_v2_sparse_classes_36k_train_024115 | 2,629 | permissive | [
{
"docstring": "Instantiates a Controller. :param robot: The robot to interface. :type robot: Robot :param max_ang_speed: The robot max angular speed. :type max_ang_speed: float :param ang_speed_weight: The weight to apply to the angular speed. :type ang_speed_weight: float :param turn_around_delay: The delay a... | 4 | stack_v2_sparse_classes_30k_train_005190 | Implement the Python class `Controller` described below.
Class description:
Class that implements a Controller, used as an interface to communicate easily with the Robot object which communicates directly with the MRDS server.
Method signatures and docstrings:
- def __init__(self, robot, max_ang_speed=3, ang_speed_we... | Implement the Python class `Controller` described below.
Class description:
Class that implements a Controller, used as an interface to communicate easily with the Robot object which communicates directly with the MRDS server.
Method signatures and docstrings:
- def __init__(self, robot, max_ang_speed=3, ang_speed_we... | e36ddcc7d5959957d83fae778d8ef715c79712e7 | <|skeleton|>
class Controller:
"""Class that implements a Controller, used as an interface to communicate easily with the Robot object which communicates directly with the MRDS server."""
def __init__(self, robot, max_ang_speed=3, ang_speed_weight=0.8, turn_around_delay=8):
"""Instantiates a Controller... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
"""Class that implements a Controller, used as an interface to communicate easily with the Robot object which communicates directly with the MRDS server."""
def __init__(self, robot, max_ang_speed=3, ang_speed_weight=0.8, turn_around_delay=8):
"""Instantiates a Controller. :param robo... | the_stack_v2_python_sparse | submission/controller.py | ThomasRanvier/map_maker | train | 0 |
a47b2c0f6588425e067a75aebcbe91888dfd2065 | [
"out = self.nanoutput()\nall = None\nfor cs in config.stimuli():\n trs = self.get_stimuli(date.runs('training'), cs, (0, 2), 'dff')\n all = trs if all is None else np.concatenate([all, (trs.T - np.nanmean(trs, axis=1)).T], axis=1)\n out['noisecorr_%s' % cs] = self.calc_noisecorr_cohen(trs)\nout['noisecorr_... | <|body_start_0|>
out = self.nanoutput()
all = None
for cs in config.stimuli():
trs = self.get_stimuli(date.runs('training'), cs, (0, 2), 'dff')
all = trs if all is None else np.concatenate([all, (trs.T - np.nanmean(trs, axis=1)).T], axis=1)
out['noisecorr_%s' ... | Noisecorr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Noisecorr:
def run(self, date):
"""Run all analyses and returns results in a dictionary. Parameters ---------- date : Date object Returns ------- dict All of the output values"""
<|body_0|>
def get_stimuli(runs, cs, trange=(0, 2), ttype='dff', nolick=False):
"""Get s... | stack_v2_sparse_classes_36k_train_024116 | 4,829 | no_license | [
{
"docstring": "Run all analyses and returns results in a dictionary. Parameters ---------- date : Date object Returns ------- dict All of the output values",
"name": "run",
"signature": "def run(self, date)"
},
{
"docstring": "Get stimulus responses from training runs Parameters ---------- runs... | 4 | stack_v2_sparse_classes_30k_train_000164 | Implement the Python class `Noisecorr` described below.
Class description:
Implement the Noisecorr class.
Method signatures and docstrings:
- def run(self, date): Run all analyses and returns results in a dictionary. Parameters ---------- date : Date object Returns ------- dict All of the output values
- def get_stim... | Implement the Python class `Noisecorr` described below.
Class description:
Implement the Noisecorr class.
Method signatures and docstrings:
- def run(self, date): Run all analyses and returns results in a dictionary. Parameters ---------- date : Date object Returns ------- dict All of the output values
- def get_stim... | c4e9699fb78db7bd7cc14bc1bd6bd7d2b4e3a16b | <|skeleton|>
class Noisecorr:
def run(self, date):
"""Run all analyses and returns results in a dictionary. Parameters ---------- date : Date object Returns ------- dict All of the output values"""
<|body_0|>
def get_stimuli(runs, cs, trange=(0, 2), ttype='dff', nolick=False):
"""Get s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Noisecorr:
def run(self, date):
"""Run all analyses and returns results in a dictionary. Parameters ---------- date : Date object Returns ------- dict All of the output values"""
out = self.nanoutput()
all = None
for cs in config.stimuli():
trs = self.get_stimuli(da... | the_stack_v2_python_sparse | pool/analyses/noisecorr.py | jzaremba/pool | train | 0 | |
1c0cc1bb98f5c0b5c05583975d459874cf8455b5 | [
"super(DiceLoss, self).__init__()\nself.register_buffer('weight', weight)\nself.weight = weight\nself.p = p\nself.epsilon = epsilon\nif activation is None:\n self.activation = None\nelse:\n self.activation = get_activation(activation)\nself.ignore_label = ignore_label",
"if self.activation is not None:\n ... | <|body_start_0|>
super(DiceLoss, self).__init__()
self.register_buffer('weight', weight)
self.weight = weight
self.p = p
self.epsilon = epsilon
if activation is None:
self.activation = None
else:
self.activation = get_activation(activation)... | Dice loss module. | DiceLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiceLoss:
"""Dice loss module."""
def __init__(self, weight=None, p=1.0, epsilon=1e-06, activation=None, ignore_label=-1):
"""Args: weight (Tensor, optional): tensor of the weight per class with shape (C,). Defaults to None. p (float): exponential to compute union term of dice coeff.... | stack_v2_sparse_classes_36k_train_024117 | 3,995 | permissive | [
{
"docstring": "Args: weight (Tensor, optional): tensor of the weight per class with shape (C,). Defaults to None. p (float): exponential to compute union term of dice coeff. Defaults to 1.0. epsilon (float, optional): parameter to avoid zero division. Defaults to 1e-6. ignore_label (int): label assigned to the... | 2 | stack_v2_sparse_classes_30k_train_017907 | Implement the Python class `DiceLoss` described below.
Class description:
Dice loss module.
Method signatures and docstrings:
- def __init__(self, weight=None, p=1.0, epsilon=1e-06, activation=None, ignore_label=-1): Args: weight (Tensor, optional): tensor of the weight per class with shape (C,). Defaults to None. p ... | Implement the Python class `DiceLoss` described below.
Class description:
Dice loss module.
Method signatures and docstrings:
- def __init__(self, weight=None, p=1.0, epsilon=1e-06, activation=None, ignore_label=-1): Args: weight (Tensor, optional): tensor of the weight per class with shape (C,). Defaults to None. p ... | 871a24eaad388b8da427e0ab3c95f951629e36d6 | <|skeleton|>
class DiceLoss:
"""Dice loss module."""
def __init__(self, weight=None, p=1.0, epsilon=1e-06, activation=None, ignore_label=-1):
"""Args: weight (Tensor, optional): tensor of the weight per class with shape (C,). Defaults to None. p (float): exponential to compute union term of dice coeff.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DiceLoss:
"""Dice loss module."""
def __init__(self, weight=None, p=1.0, epsilon=1e-06, activation=None, ignore_label=-1):
"""Args: weight (Tensor, optional): tensor of the weight per class with shape (C,). Defaults to None. p (float): exponential to compute union term of dice coeff. Defaults to ... | the_stack_v2_python_sparse | kits19_3d_segmentation/solvers/losses.py | rabbittuan/kits19_3d_segmentation | train | 0 |
4982f6b20effaba5362371199a3398b444700f96 | [
"self.ip = '0.0.0.0'\nself.mac = '00:00:00:00:00:00'\nself.iface = ''\nif entry_line != '':\n self.parse(entry_line)",
"i = entry_line.split()\nif len(i) == 3:\n pass\nelif len(i) != 5:\n output.warn('ARP entry line should have 5 items but ' + str(len(i)) + ' found', self.__class__.__name__)\nelse:\n ... | <|body_start_0|>
self.ip = '0.0.0.0'
self.mac = '00:00:00:00:00:00'
self.iface = ''
if entry_line != '':
self.parse(entry_line)
<|end_body_0|>
<|body_start_1|>
i = entry_line.split()
if len(i) == 3:
pass
elif len(i) != 5:
outpu... | ARP entry in table @author ykk @date May 2011 | arp_entry | [
"LicenseRef-scancode-x11-stanford"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class arp_entry:
"""ARP entry in table @author ykk @date May 2011"""
def __init__(self, entry_line=''):
"""Initalize"""
<|body_0|>
def parse(self, entry_line):
"""Parse line"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.ip = '0.0.0.0'
s... | stack_v2_sparse_classes_36k_train_024118 | 20,463 | permissive | [
{
"docstring": "Initalize",
"name": "__init__",
"signature": "def __init__(self, entry_line='')"
},
{
"docstring": "Parse line",
"name": "parse",
"signature": "def parse(self, entry_line)"
}
] | 2 | null | Implement the Python class `arp_entry` described below.
Class description:
ARP entry in table @author ykk @date May 2011
Method signatures and docstrings:
- def __init__(self, entry_line=''): Initalize
- def parse(self, entry_line): Parse line | Implement the Python class `arp_entry` described below.
Class description:
ARP entry in table @author ykk @date May 2011
Method signatures and docstrings:
- def __init__(self, entry_line=''): Initalize
- def parse(self, entry_line): Parse line
<|skeleton|>
class arp_entry:
"""ARP entry in table @author ykk @date... | c3f5a31b74d5587671329eea9582ac8aed0c58a4 | <|skeleton|>
class arp_entry:
"""ARP entry in table @author ykk @date May 2011"""
def __init__(self, entry_line=''):
"""Initalize"""
<|body_0|>
def parse(self, entry_line):
"""Parse line"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class arp_entry:
"""ARP entry in table @author ykk @date May 2011"""
def __init__(self, entry_line=''):
"""Initalize"""
self.ip = '0.0.0.0'
self.mac = '00:00:00:00:00:00'
self.iface = ''
if entry_line != '':
self.parse(entry_line)
def parse(self, entry_l... | the_stack_v2_python_sparse | yapc/local/netintf.py | yapkke/yapc | train | 1 |
fce9308830fc740cc28088e98204fa88fcf1297e | [
"assert os.path.isfile(filename)\nassert filename.endswith('.docx')\nself.__filename = filename",
"try:\n pythoncom.CoInitialize()\n gencache.EnsureModule('{00020905-0000-0000-C000-000000000046}', 0, 8, 4)\n w = Dispatch('Word.Application')\n try:\n doc = w.Documents.Open(self.__filename, ReadO... | <|body_start_0|>
assert os.path.isfile(filename)
assert filename.endswith('.docx')
self.__filename = filename
<|end_body_0|>
<|body_start_1|>
try:
pythoncom.CoInitialize()
gencache.EnsureModule('{00020905-0000-0000-C000-000000000046}', 0, 8, 4)
w = Di... | Word (.docx) File Object. | WordFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordFile:
"""Word (.docx) File Object."""
def __init__(self, filename):
"""Create a Word file (.docx) object. Parameters ---------- filename: str Word file's (.docx) name. Returns ------- WordFile Return its case. Raises ------ AssertionError If the file does not exist and the suffix... | stack_v2_sparse_classes_36k_train_024119 | 2,390 | no_license | [
{
"docstring": "Create a Word file (.docx) object. Parameters ---------- filename: str Word file's (.docx) name. Returns ------- WordFile Return its case. Raises ------ AssertionError If the file does not exist and the suffix is not '.docx', raise it.",
"name": "__init__",
"signature": "def __init__(sel... | 2 | stack_v2_sparse_classes_30k_train_020119 | Implement the Python class `WordFile` described below.
Class description:
Word (.docx) File Object.
Method signatures and docstrings:
- def __init__(self, filename): Create a Word file (.docx) object. Parameters ---------- filename: str Word file's (.docx) name. Returns ------- WordFile Return its case. Raises ------... | Implement the Python class `WordFile` described below.
Class description:
Word (.docx) File Object.
Method signatures and docstrings:
- def __init__(self, filename): Create a Word file (.docx) object. Parameters ---------- filename: str Word file's (.docx) name. Returns ------- WordFile Return its case. Raises ------... | dab562f762cd7abb87496bcae2e49f27179a417e | <|skeleton|>
class WordFile:
"""Word (.docx) File Object."""
def __init__(self, filename):
"""Create a Word file (.docx) object. Parameters ---------- filename: str Word file's (.docx) name. Returns ------- WordFile Return its case. Raises ------ AssertionError If the file does not exist and the suffix... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordFile:
"""Word (.docx) File Object."""
def __init__(self, filename):
"""Create a Word file (.docx) object. Parameters ---------- filename: str Word file's (.docx) name. Returns ------- WordFile Return its case. Raises ------ AssertionError If the file does not exist and the suffix is not '.doc... | the_stack_v2_python_sparse | Files/WordFile.py | zhangletao/Tools | train | 0 |
2723fb1ad8050a2b1f8a90964f12661e0e0ca92a | [
"super(EncoderBlock, self).__init__()\nself.mha = MultiHeadAttention(dm, h)\nself.dense_hidden = tf.keras.layers.Dense(units=hidden, activation='relu')\nself.dense_output = tf.keras.layers.Dense(units=dm)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernorm2 = tf.keras.layers.LayerNo... | <|body_start_0|>
super(EncoderBlock, self).__init__()
self.mha = MultiHeadAttention(dm, h)
self.dense_hidden = tf.keras.layers.Dense(units=hidden, activation='relu')
self.dense_output = tf.keras.layers.Dense(units=dm)
self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1... | Class MultiHeadAttention | EncoderBlock | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderBlock:
"""Class MultiHeadAttention"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in the fully connected layer drop_rate - the dropout rate S... | stack_v2_sparse_classes_36k_train_024120 | 2,302 | permissive | [
{
"docstring": "Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in the fully connected layer drop_rate - the dropout rate Sets the following public instance attributes: mha - a MultiHeadAttention layer dense_hidden - the hidden dense... | 2 | stack_v2_sparse_classes_30k_train_015856 | Implement the Python class `EncoderBlock` described below.
Class description:
Class MultiHeadAttention
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in... | Implement the Python class `EncoderBlock` described below.
Class description:
Class MultiHeadAttention
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in... | eaf23423ec0f412f103f5931d6610fdd67bcc5be | <|skeleton|>
class EncoderBlock:
"""Class MultiHeadAttention"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in the fully connected layer drop_rate - the dropout rate S... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderBlock:
"""Class MultiHeadAttention"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in the fully connected layer drop_rate - the dropout rate Sets the follo... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/7-transformer_encoder_block.py | ledbagholberton/holbertonschool-machine_learning | train | 1 |
1edfe8a06b3738d103b1616feb314d3f9b6a7878 | [
"q = collections.deque([root])\nresult = ['#']\nwhile q:\n node = q.popleft()\n if node:\n q.append(node.left)\n q.append(node.right)\n result.append(str(node.val))\n else:\n result.append('#')\nreturn ' '.join(result)",
"if data == '# #':\n return None\nnodes = data.split(... | <|body_start_0|>
q = collections.deque([root])
result = ['#']
while q:
node = q.popleft()
if node:
q.append(node.left)
q.append(node.right)
result.append(str(node.val))
else:
result.append('#')
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_024121 | 1,644 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 46c04e0f583d4c6ec4f51a24f19a373b173b3d5c | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
q = collections.deque([root])
result = ['#']
while q:
node = q.popleft()
if node:
q.append(node.left)
q.append(nod... | the_stack_v2_python_sparse | 코테.py | hyeokjinson/algorithm | train | 1 | |
2ccc503f8a9efd4aa08f95ef77e3b4988adb1420 | [
"comments = CommentsSongs.query.order_by(asc(CommentsSongs.SongID), asc(CommentsSongs.Created)).all()\ncontents = jsonify({'comments': [{'commentID': comment.CommentID, 'songID': comment.SongID, 'userID': comment.UserID, 'name': get_username(comment.UserID), 'comment': comment.Comment, 'createdAt': get_iso_format(c... | <|body_start_0|>
comments = CommentsSongs.query.order_by(asc(CommentsSongs.SongID), asc(CommentsSongs.Created)).all()
contents = jsonify({'comments': [{'commentID': comment.CommentID, 'songID': comment.SongID, 'userID': comment.UserID, 'name': get_username(comment.UserID), 'comment': comment.Comment, 'c... | SongCommentsView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SongCommentsView:
def index(self):
"""Return all comments for all songs."""
<|body_0|>
def get(self, song_id):
"""Return the comments for a specific song."""
<|body_1|>
def post(self):
"""Add a comment to a song specified in the payload."""
... | stack_v2_sparse_classes_36k_train_024122 | 26,847 | permissive | [
{
"docstring": "Return all comments for all songs.",
"name": "index",
"signature": "def index(self)"
},
{
"docstring": "Return the comments for a specific song.",
"name": "get",
"signature": "def get(self, song_id)"
},
{
"docstring": "Add a comment to a song specified in the payl... | 5 | stack_v2_sparse_classes_30k_train_011233 | Implement the Python class `SongCommentsView` described below.
Class description:
Implement the SongCommentsView class.
Method signatures and docstrings:
- def index(self): Return all comments for all songs.
- def get(self, song_id): Return the comments for a specific song.
- def post(self): Add a comment to a song s... | Implement the Python class `SongCommentsView` described below.
Class description:
Implement the SongCommentsView class.
Method signatures and docstrings:
- def index(self): Return all comments for all songs.
- def get(self, song_id): Return the comments for a specific song.
- def post(self): Add a comment to a song s... | 62f8e8e904e379541193f0cbb91a8434b47f538f | <|skeleton|>
class SongCommentsView:
def index(self):
"""Return all comments for all songs."""
<|body_0|>
def get(self, song_id):
"""Return the comments for a specific song."""
<|body_1|>
def post(self):
"""Add a comment to a song specified in the payload."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SongCommentsView:
def index(self):
"""Return all comments for all songs."""
comments = CommentsSongs.query.order_by(asc(CommentsSongs.SongID), asc(CommentsSongs.Created)).all()
contents = jsonify({'comments': [{'commentID': comment.CommentID, 'songID': comment.SongID, 'userID': comment... | the_stack_v2_python_sparse | apps/comments/views.py | Torniojaws/vortech-backend | train | 0 | |
0f4ca0ea5e83c4ea764f04cff625d2b01258e88f | [
"self._doc_class = doc_class\nself._cb = cb\nself._count_valid = False\nsuper(BaseQuery, self).__init__()\nself._total_results = 0",
"if self._count_valid:\n return self._total_results\nresult = self._cb.get_object(self._doc_class.urlobject.format(self._cb.credentials.org_key))\nresults = result.get('results',... | <|body_start_0|>
self._doc_class = doc_class
self._cb = cb
self._count_valid = False
super(BaseQuery, self).__init__()
self._total_results = 0
<|end_body_0|>
<|body_start_1|>
if self._count_valid:
return self._total_results
result = self._cb.get_objec... | Represents a query that is used to locate USBDeviceBlock objects. | USBDeviceBlockQuery | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class USBDeviceBlockQuery:
"""Represents a query that is used to locate USBDeviceBlock objects."""
def __init__(self, doc_class, cb):
"""Initialize the USBDeviceBlockQuery. Args: doc_class (class): The model class that will be returned by this query. cb (BaseAPI): Reference to API object u... | stack_v2_sparse_classes_36k_train_024123 | 31,170 | permissive | [
{
"docstring": "Initialize the USBDeviceBlockQuery. Args: doc_class (class): The model class that will be returned by this query. cb (BaseAPI): Reference to API object used to communicate with the server.",
"name": "__init__",
"signature": "def __init__(self, doc_class, cb)"
},
{
"docstring": "R... | 4 | stack_v2_sparse_classes_30k_train_003840 | Implement the Python class `USBDeviceBlockQuery` described below.
Class description:
Represents a query that is used to locate USBDeviceBlock objects.
Method signatures and docstrings:
- def __init__(self, doc_class, cb): Initialize the USBDeviceBlockQuery. Args: doc_class (class): The model class that will be return... | Implement the Python class `USBDeviceBlockQuery` described below.
Class description:
Represents a query that is used to locate USBDeviceBlock objects.
Method signatures and docstrings:
- def __init__(self, doc_class, cb): Initialize the USBDeviceBlockQuery. Args: doc_class (class): The model class that will be return... | a8a2ec8ff6b9985b4fb4700d9d566e8e2a297381 | <|skeleton|>
class USBDeviceBlockQuery:
"""Represents a query that is used to locate USBDeviceBlock objects."""
def __init__(self, doc_class, cb):
"""Initialize the USBDeviceBlockQuery. Args: doc_class (class): The model class that will be returned by this query. cb (BaseAPI): Reference to API object u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class USBDeviceBlockQuery:
"""Represents a query that is used to locate USBDeviceBlock objects."""
def __init__(self, doc_class, cb):
"""Initialize the USBDeviceBlockQuery. Args: doc_class (class): The model class that will be returned by this query. cb (BaseAPI): Reference to API object used to commun... | the_stack_v2_python_sparse | src/cbc_sdk/endpoint_standard/usb_device_control.py | fslds/carbon-black-cloud-sdk-python | train | 0 |
ffbcf06dfb4ca6f267808f4235baf87d86dcaf11 | [
"E0 = a0 * m_e * c ** 2 * k0 / e\nself.k0 = k0\nself.waist = waist\nself.inv_tau = 1.0 / tau\nself.t_peak = t_peak\nself.E0 = E0\nself.v_antenna = source_v\nself.boost = boost\nself.temporal_order = temporal_order\nself.theta_zx = theta_zx\nself.x_center = x_center\nself.geom_coeff = get_geometric_coeff(dim)",
"t... | <|body_start_0|>
E0 = a0 * m_e * c ** 2 * k0 / e
self.k0 = k0
self.waist = waist
self.inv_tau = 1.0 / tau
self.t_peak = t_peak
self.E0 = E0
self.v_antenna = source_v
self.boost = boost
self.temporal_order = temporal_order
self.theta_zx = th... | Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z. | JincGaussianAngleProfile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JincGaussianAngleProfile:
"""Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z."""
def __init__(self, k0, waist, tau, t_peak, a0, dim, temporal_order=2, boost=None, source_v=0, theta_zx=0.0,... | stack_v2_sparse_classes_36k_train_024124 | 34,589 | permissive | [
{
"docstring": "Define a laser profile with is a Jinc function transversely and a supergaussian function longitudinally. The antenna is orthogonal to z, but this profile supports a non-zero angle in the (z, x) plane, and is compatible with the boosted frame and a moving window. Note 1: The focal plane is the pl... | 2 | null | Implement the Python class `JincGaussianAngleProfile` described below.
Class description:
Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z.
Method signatures and docstrings:
- def __init__(self, k0, waist, tau, t_pe... | Implement the Python class `JincGaussianAngleProfile` described below.
Class description:
Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z.
Method signatures and docstrings:
- def __init__(self, k0, waist, tau, t_pe... | 091c982f82788209017315e13eb7d0e743687d46 | <|skeleton|>
class JincGaussianAngleProfile:
"""Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z."""
def __init__(self, k0, waist, tau, t_peak, a0, dim, temporal_order=2, boost=None, source_v=0, theta_zx=0.0,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JincGaussianAngleProfile:
"""Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z."""
def __init__(self, k0, waist, tau, t_peak, a0, dim, temporal_order=2, boost=None, source_v=0, theta_zx=0.0, x_center=0.0... | the_stack_v2_python_sparse | scripts/field_solvers/laser/laser_profiles.py | giadarol/warp | train | 0 |
f8956b944efd1fa0f32cde7e248ea4a1a5f22f95 | [
"n = len(data)\ndp = [1] * (n + 1)\nfor i in range(2, n + 1):\n for j in range(i - 1):\n if data[i - 1] == data[j] + 1:\n dp[i] = max(dp[j + 1] + 1, dp[i])\nreturn n - max(dp)",
"if not data:\n return 0\nAList_map = []\nfor num in data:\n flag = 0\n if AList_map:\n for map_old... | <|body_start_0|>
n = len(data)
dp = [1] * (n + 1)
for i in range(2, n + 1):
for j in range(i - 1):
if data[i - 1] == data[j] + 1:
dp[i] = max(dp[j + 1] + 1, dp[i])
return n - max(dp)
<|end_body_0|>
<|body_start_1|>
if not data:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def moveStoneMinNum(self, data):
"""分析：保持原来数组中最长递增子序列不变，移动其他石子，再用序列长度减去最长子序列个数即得答案。 dp[i] 是以 A[i-1_最短回文串.py]为尾的最长序列数长度。 dp[i] = max(dp[j-1_最短回文串.py] + 1_最短回文串.py) if data[i-1_最短回文串.py]==data[j]+1_最短回文串.py j=0,1_最短回文串.py,...,i-2 dp[0] = 0 dp[1_最短回文串.py] = 1_最短回文串.py res = max(dp... | stack_v2_sparse_classes_36k_train_024125 | 1,613 | no_license | [
{
"docstring": "分析：保持原来数组中最长递增子序列不变，移动其他石子，再用序列长度减去最长子序列个数即得答案。 dp[i] 是以 A[i-1_最短回文串.py]为尾的最长序列数长度。 dp[i] = max(dp[j-1_最短回文串.py] + 1_最短回文串.py) if data[i-1_最短回文串.py]==data[j]+1_最短回文串.py j=0,1_最短回文串.py,...,i-2 dp[0] = 0 dp[1_最短回文串.py] = 1_最短回文串.py res = max(dp) T:O(n^2) M:O(n)",
"name": "moveStoneMinNum",
... | 2 | stack_v2_sparse_classes_30k_train_019878 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveStoneMinNum(self, data): 分析：保持原来数组中最长递增子序列不变，移动其他石子，再用序列长度减去最长子序列个数即得答案。 dp[i] 是以 A[i-1_最短回文串.py]为尾的最长序列数长度。 dp[i] = max(dp[j-1_最短回文串.py] + 1_最短回文串.py) if data[i-1_最短回文串.... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveStoneMinNum(self, data): 分析：保持原来数组中最长递增子序列不变，移动其他石子，再用序列长度减去最长子序列个数即得答案。 dp[i] 是以 A[i-1_最短回文串.py]为尾的最长序列数长度。 dp[i] = max(dp[j-1_最短回文串.py] + 1_最短回文串.py) if data[i-1_最短回文串.... | 57f303aa6e76f7c5292fa60bffdfddcb4ff9ddfb | <|skeleton|>
class Solution:
def moveStoneMinNum(self, data):
"""分析：保持原来数组中最长递增子序列不变，移动其他石子，再用序列长度减去最长子序列个数即得答案。 dp[i] 是以 A[i-1_最短回文串.py]为尾的最长序列数长度。 dp[i] = max(dp[j-1_最短回文串.py] + 1_最短回文串.py) if data[i-1_最短回文串.py]==data[j]+1_最短回文串.py j=0,1_最短回文串.py,...,i-2 dp[0] = 0 dp[1_最短回文串.py] = 1_最短回文串.py res = max(dp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def moveStoneMinNum(self, data):
"""分析：保持原来数组中最长递增子序列不变，移动其他石子，再用序列长度减去最长子序列个数即得答案。 dp[i] 是以 A[i-1_最短回文串.py]为尾的最长序列数长度。 dp[i] = max(dp[j-1_最短回文串.py] + 1_最短回文串.py) if data[i-1_最短回文串.py]==data[j]+1_最短回文串.py j=0,1_最短回文串.py,...,i-2 dp[0] = 0 dp[1_最短回文串.py] = 1_最短回文串.py res = max(dp) T:O(n^2) M:O... | the_stack_v2_python_sparse | 4_LEETCODE/11_Interview/浪潮/石头排序.py | fzingithub/SwordRefers2Offer | train | 1 | |
f6b190448cd9d756c127d35f070bb804392b84cd | [
"prefix = f'{slugify(prefix)}_' if prefix else ''\nextension = f'.{extension}' if extension else ''\nreturn f'{prefix}{slugify(title)}{extension}'",
"match = re.match('^(?P<title>.*)(\\\\.{extension_regex:s})$'.format(extension_regex=EXTENSION_REGEX), value)\nif match:\n return match.group('title')\nreturn val... | <|body_start_0|>
prefix = f'{slugify(prefix)}_' if prefix else ''
extension = f'.{extension}' if extension else ''
return f'{prefix}{slugify(title)}{extension}'
<|end_body_0|>
<|body_start_1|>
match = re.match('^(?P<title>.*)(\\.{extension_regex:s})$'.format(extension_regex=EXTENSION_RE... | Set of function used by uploadable files managing an extension. | UploadableFileWithExtensionSerializerMixin | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadableFileWithExtensionSerializerMixin:
"""Set of function used by uploadable files managing an extension."""
def _get_filename(self, title, extension=None, prefix=None):
"""Filename of an object. Parameters ---------- title : Type[string] The raw object title extension: Type[str... | stack_v2_sparse_classes_36k_train_024126 | 8,960 | permissive | [
{
"docstring": "Filename of an object. Parameters ---------- title : Type[string] The raw object title extension: Type[string] The file extension if any prefix: Type[string] The file prefix if any Returns ------- String The document's filename",
"name": "_get_filename",
"signature": "def _get_filename(s... | 2 | stack_v2_sparse_classes_30k_train_020683 | Implement the Python class `UploadableFileWithExtensionSerializerMixin` described below.
Class description:
Set of function used by uploadable files managing an extension.
Method signatures and docstrings:
- def _get_filename(self, title, extension=None, prefix=None): Filename of an object. Parameters ---------- titl... | Implement the Python class `UploadableFileWithExtensionSerializerMixin` described below.
Class description:
Set of function used by uploadable files managing an extension.
Method signatures and docstrings:
- def _get_filename(self, title, extension=None, prefix=None): Filename of an object. Parameters ---------- titl... | f767f1bdc12c9712f26ea17cb8b19f536389f0ed | <|skeleton|>
class UploadableFileWithExtensionSerializerMixin:
"""Set of function used by uploadable files managing an extension."""
def _get_filename(self, title, extension=None, prefix=None):
"""Filename of an object. Parameters ---------- title : Type[string] The raw object title extension: Type[str... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UploadableFileWithExtensionSerializerMixin:
"""Set of function used by uploadable files managing an extension."""
def _get_filename(self, title, extension=None, prefix=None):
"""Filename of an object. Parameters ---------- title : Type[string] The raw object title extension: Type[string] The file... | the_stack_v2_python_sparse | src/backend/marsha/core/serializers/base.py | openfun/marsha | train | 92 |
55360ed8fba6d345f30ad6b272172cf01ef7c9ca | [
"self.num_players = num_players\nself.total_num_marbles = total_num_marbles\nself.marbles = deque([0])\nself.player_in_turn = 1\nself.scores = Counter()",
"for marble_id in range(1, self.total_num_marbles + 1):\n if marble_id % 100000 == 0:\n print(marble_id)\n if marble_id % 23 == 0:\n self.m... | <|body_start_0|>
self.num_players = num_players
self.total_num_marbles = total_num_marbles
self.marbles = deque([0])
self.player_in_turn = 1
self.scores = Counter()
<|end_body_0|>
<|body_start_1|>
for marble_id in range(1, self.total_num_marbles + 1):
if marb... | class for the marbles game as defined in the problem statement | Marbles | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Marbles:
"""class for the marbles game as defined in the problem statement"""
def __init__(self, num_players: int, total_num_marbles: int):
"""input: how many players, how many marbles to play"""
<|body_0|>
def play(self):
"""Plays the game of marbles until finis... | stack_v2_sparse_classes_36k_train_024127 | 3,796 | no_license | [
{
"docstring": "input: how many players, how many marbles to play",
"name": "__init__",
"signature": "def __init__(self, num_players: int, total_num_marbles: int)"
},
{
"docstring": "Plays the game of marbles until finish. Returns scores Counter",
"name": "play",
"signature": "def play(s... | 2 | stack_v2_sparse_classes_30k_train_018589 | Implement the Python class `Marbles` described below.
Class description:
class for the marbles game as defined in the problem statement
Method signatures and docstrings:
- def __init__(self, num_players: int, total_num_marbles: int): input: how many players, how many marbles to play
- def play(self): Plays the game o... | Implement the Python class `Marbles` described below.
Class description:
class for the marbles game as defined in the problem statement
Method signatures and docstrings:
- def __init__(self, num_players: int, total_num_marbles: int): input: how many players, how many marbles to play
- def play(self): Plays the game o... | a249b7092a1ae9b54b79eb4425036f45c7e04d74 | <|skeleton|>
class Marbles:
"""class for the marbles game as defined in the problem statement"""
def __init__(self, num_players: int, total_num_marbles: int):
"""input: how many players, how many marbles to play"""
<|body_0|>
def play(self):
"""Plays the game of marbles until finis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Marbles:
"""class for the marbles game as defined in the problem statement"""
def __init__(self, num_players: int, total_num_marbles: int):
"""input: how many players, how many marbles to play"""
self.num_players = num_players
self.total_num_marbles = total_num_marbles
sel... | the_stack_v2_python_sparse | day09_marble_mania_v3.py | aleksiheikkila/AdventOfCode2018 | train | 0 |
73a08a944039b4fc8c0b18c7f70d89221dee9841 | [
"_id = request.args.get('id', None)\nif not _id:\n return ({'msg': 'params error !'}, 400)\ntry:\n result = mongo_algo.db.algo_info.find_one({'_id': bson.ObjectId(_id)}, {'data_section': 1})\n if not result:\n return ({'msg': 'id is not exist !'}, 200)\nexcept Exception as e:\n logging.error(e, e... | <|body_start_0|>
_id = request.args.get('id', None)
if not _id:
return ({'msg': 'params error !'}, 400)
try:
result = mongo_algo.db.algo_info.find_one({'_id': bson.ObjectId(_id)}, {'data_section': 1})
if not result:
return ({'msg': 'id is not e... | DataSectionViews | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataSectionViews:
def get(self):
"""get one data section through id :return:"""
<|body_0|>
def post(self):
"""add an data section record :return:"""
<|body_1|>
def put(self):
"""update data section record :return:"""
<|body_2|>
<|end_ske... | stack_v2_sparse_classes_36k_train_024128 | 20,183 | no_license | [
{
"docstring": "get one data section through id :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "add an data section record :return:",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "update data section record :return:",
"name": "put"... | 3 | stack_v2_sparse_classes_30k_train_021615 | Implement the Python class `DataSectionViews` described below.
Class description:
Implement the DataSectionViews class.
Method signatures and docstrings:
- def get(self): get one data section through id :return:
- def post(self): add an data section record :return:
- def put(self): update data section record :return: | Implement the Python class `DataSectionViews` described below.
Class description:
Implement the DataSectionViews class.
Method signatures and docstrings:
- def get(self): get one data section through id :return:
- def post(self): add an data section record :return:
- def put(self): update data section record :return:... | 054324b50e807d6f4e98f4a1b67afac9a0653b06 | <|skeleton|>
class DataSectionViews:
def get(self):
"""get one data section through id :return:"""
<|body_0|>
def post(self):
"""add an data section record :return:"""
<|body_1|>
def put(self):
"""update data section record :return:"""
<|body_2|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataSectionViews:
def get(self):
"""get one data section through id :return:"""
_id = request.args.get('id', None)
if not _id:
return ({'msg': 'params error !'}, 400)
try:
result = mongo_algo.db.algo_info.find_one({'_id': bson.ObjectId(_id)}, {'data_sect... | the_stack_v2_python_sparse | services/AlgoVersion/views.py | condilin/DMS | train | 0 | |
f9c5bcea20a8d0bdd41c3c6b3dbd4eb347316576 | [
"super().__init__()\nself.linear = LinearPolicy(inp_n, hidden_size, hidden_size, num_layers - 1, activation_fn)\nif num_layers > 1:\n self.linear = nn.Sequential(self.linear, activation_fn())\n last_in_n = hidden_size\nelse:\n last_in_n = inp_n\nself.mean = nn.Linear(last_in_n, out_n)\nself.log_std = nn.Li... | <|body_start_0|>
super().__init__()
self.linear = LinearPolicy(inp_n, hidden_size, hidden_size, num_layers - 1, activation_fn)
if num_layers > 1:
self.linear = nn.Sequential(self.linear, activation_fn())
last_in_n = hidden_size
else:
last_in_n = inp_n
... | A simple gaussian policy. | GaussianPolicy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaussianPolicy:
"""A simple gaussian policy."""
def __init__(self, inp_n: int, out_n: int, hidden_size: int, num_layers: int, activation_fn: nn.Module):
"""Creates the gaussian policy. Args: inp_n: The number of input units to the network. out_n: The number of output units from the n... | stack_v2_sparse_classes_36k_train_024129 | 6,947 | permissive | [
{
"docstring": "Creates the gaussian policy. Args: inp_n: The number of input units to the network. out_n: The number of output units from the network. hidden_size: The number of units in each hidden layer. num_layers: The number of layers before the gaussian layer. activation_fn: The activation function in bet... | 3 | null | Implement the Python class `GaussianPolicy` described below.
Class description:
A simple gaussian policy.
Method signatures and docstrings:
- def __init__(self, inp_n: int, out_n: int, hidden_size: int, num_layers: int, activation_fn: nn.Module): Creates the gaussian policy. Args: inp_n: The number of input units to ... | Implement the Python class `GaussianPolicy` described below.
Class description:
A simple gaussian policy.
Method signatures and docstrings:
- def __init__(self, inp_n: int, out_n: int, hidden_size: int, num_layers: int, activation_fn: nn.Module): Creates the gaussian policy. Args: inp_n: The number of input units to ... | cde3be1c69bfd76fe4a78fa529e851d0a78318c7 | <|skeleton|>
class GaussianPolicy:
"""A simple gaussian policy."""
def __init__(self, inp_n: int, out_n: int, hidden_size: int, num_layers: int, activation_fn: nn.Module):
"""Creates the gaussian policy. Args: inp_n: The number of input units to the network. out_n: The number of output units from the n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GaussianPolicy:
"""A simple gaussian policy."""
def __init__(self, inp_n: int, out_n: int, hidden_size: int, num_layers: int, activation_fn: nn.Module):
"""Creates the gaussian policy. Args: inp_n: The number of input units to the network. out_n: The number of output units from the network. hidde... | the_stack_v2_python_sparse | hlrl/torch/policies/distribution.py | Chainso/HLRL | train | 3 |
41fa99d6de5ae139cacd40bb2788d0d5a93a4391 | [
"if not root:\n return True\nreturn self.is_symmetric_recursive(root)",
"def recursion(node1, node2):\n if not node1 and (not node2):\n return True\n return bool(node1) and bool(node2) and (node1.val == node2.val) and recursion(node1.left, node2.right) and recursion(node1.right, node2.left)\nretur... | <|body_start_0|>
if not root:
return True
return self.is_symmetric_recursive(root)
<|end_body_0|>
<|body_start_1|>
def recursion(node1, node2):
if not node1 and (not node2):
return True
return bool(node1) and bool(node2) and (node1.val == node... | Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None"""
def is_symmetric(self, root):
"""Determine whether a given binary tree is left-right sym... | stack_v2_sparse_classes_36k_train_024130 | 3,129 | no_license | [
{
"docstring": "Determine whether a given binary tree is left-right symmetric. :type root: TreeNode :rtype: bool",
"name": "is_symmetric",
"signature": "def is_symmetric(self, root)"
},
{
"docstring": "Symmetric tree: recursive solution.",
"name": "is_symmetric_recursive",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_000332 | Implement the Python class `Solution` described below.
Class description:
Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None
Method signatures and docstrings:
- def is_symmetric(self, root)... | Implement the Python class `Solution` described below.
Class description:
Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None
Method signatures and docstrings:
- def is_symmetric(self, root)... | e11bfc454789e716055b80873af0817ec8588aea | <|skeleton|>
class Solution:
"""Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None"""
def is_symmetric(self, root):
"""Determine whether a given binary tree is left-right sym... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None"""
def is_symmetric(self, root):
"""Determine whether a given binary tree is left-right symmetric. :type... | the_stack_v2_python_sparse | p101/problem101.py | stanl3y/leetcode | train | 0 |
82a9f0351d5a2090536aa2ff868063a444b2a158 | [
"self.resnet_size = resnet_size\nself.data_format = data_format\nself.dtype = dtype\nself.is_classification = is_classification\nself.block_stride = [1, 2, 2, 2]\nself.num_classes = num_classes",
"choices = {18: [2, 2, 2, 2], 34: [3, 4, 6, 3], 50: [3, 4, 6, 3], 101: [3, 4, 23, 3], 152: [3, 8, 36, 3], 200: [3, 24,... | <|body_start_0|>
self.resnet_size = resnet_size
self.data_format = data_format
self.dtype = dtype
self.is_classification = is_classification
self.block_stride = [1, 2, 2, 2]
self.num_classes = num_classes
<|end_body_0|>
<|body_start_1|>
choices = {18: [2, 2, 2, 2... | ResNet_use | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResNet_use:
def __init__(self, resnet_size, data_format='channels_first', dtype='float32', is_classification=False, num_classes=None):
""":param inPuts: :param resnet_size: :param data_format: :param dtype: :param is_train: :param is_classification:"""
<|body_0|>
def size_2_... | stack_v2_sparse_classes_36k_train_024131 | 3,795 | no_license | [
{
"docstring": ":param inPuts: :param resnet_size: :param data_format: :param dtype: :param is_train: :param is_classification:",
"name": "__init__",
"signature": "def __init__(self, resnet_size, data_format='channels_first', dtype='float32', is_classification=False, num_classes=None)"
},
{
"doc... | 3 | stack_v2_sparse_classes_30k_train_009789 | Implement the Python class `ResNet_use` described below.
Class description:
Implement the ResNet_use class.
Method signatures and docstrings:
- def __init__(self, resnet_size, data_format='channels_first', dtype='float32', is_classification=False, num_classes=None): :param inPuts: :param resnet_size: :param data_form... | Implement the Python class `ResNet_use` described below.
Class description:
Implement the ResNet_use class.
Method signatures and docstrings:
- def __init__(self, resnet_size, data_format='channels_first', dtype='float32', is_classification=False, num_classes=None): :param inPuts: :param resnet_size: :param data_form... | 032cb39eb17f4ff4ec852027e0021031a3fc0433 | <|skeleton|>
class ResNet_use:
def __init__(self, resnet_size, data_format='channels_first', dtype='float32', is_classification=False, num_classes=None):
""":param inPuts: :param resnet_size: :param data_format: :param dtype: :param is_train: :param is_classification:"""
<|body_0|>
def size_2_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResNet_use:
def __init__(self, resnet_size, data_format='channels_first', dtype='float32', is_classification=False, num_classes=None):
""":param inPuts: :param resnet_size: :param data_format: :param dtype: :param is_train: :param is_classification:"""
self.resnet_size = resnet_size
se... | the_stack_v2_python_sparse | base/ResNet.py | YJHMITWEB/TensorBox | train | 0 | |
26c19746cde7be455a4386c1932ab17bc0a88507 | [
"nr = choice(range(150))\ninput_file = open(filename).readlines()\nfilename = self._input_filename = 'mfold_in%d.txt' % nr\ndata_file = open(filename, 'w')\ndata_to_file = '\\n'.join([str(d).strip('\\n') for d in input_file])\ndata_file.write(data_to_file)\ndata_file.close()\ndata = '='.join(['SEQ', filename])\nret... | <|body_start_0|>
nr = choice(range(150))
input_file = open(filename).readlines()
filename = self._input_filename = 'mfold_in%d.txt' % nr
data_file = open(filename, 'w')
data_to_file = '\n'.join([str(d).strip('\n') for d in input_file])
data_file.write(data_to_file)
... | Application controller for mfold 3.2 application | Mfold | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mfold:
"""Application controller for mfold 3.2 application"""
def _input_as_string(self, filename):
"""mfold dosen't take full paths so a tmp-file is created in the working dir for mfold to read."""
<|body_0|>
def _input_as_lines(self, data):
"""Uses a fixed tmp ... | stack_v2_sparse_classes_36k_train_024132 | 4,259 | permissive | [
{
"docstring": "mfold dosen't take full paths so a tmp-file is created in the working dir for mfold to read.",
"name": "_input_as_string",
"signature": "def _input_as_string(self, filename)"
},
{
"docstring": "Uses a fixed tmp filename since weird truncation of the generated filename sometimes o... | 3 | null | Implement the Python class `Mfold` described below.
Class description:
Application controller for mfold 3.2 application
Method signatures and docstrings:
- def _input_as_string(self, filename): mfold dosen't take full paths so a tmp-file is created in the working dir for mfold to read.
- def _input_as_lines(self, dat... | Implement the Python class `Mfold` described below.
Class description:
Application controller for mfold 3.2 application
Method signatures and docstrings:
- def _input_as_string(self, filename): mfold dosen't take full paths so a tmp-file is created in the working dir for mfold to read.
- def _input_as_lines(self, dat... | fe6f8c8dfed86d39c80f2804a753c05bb2e485b4 | <|skeleton|>
class Mfold:
"""Application controller for mfold 3.2 application"""
def _input_as_string(self, filename):
"""mfold dosen't take full paths so a tmp-file is created in the working dir for mfold to read."""
<|body_0|>
def _input_as_lines(self, data):
"""Uses a fixed tmp ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Mfold:
"""Application controller for mfold 3.2 application"""
def _input_as_string(self, filename):
"""mfold dosen't take full paths so a tmp-file is created in the working dir for mfold to read."""
nr = choice(range(150))
input_file = open(filename).readlines()
filename =... | the_stack_v2_python_sparse | scripts/venv/lib/python2.7/site-packages/cogent/app/mfold.py | sauloal/cnidaria | train | 3 |
f4dd25fd5a088594d76f78e65976977852745640 | [
"super().__init__()\nself.backbone_model = RobertaModel.from_cfg(backbone_cfg)\nif weight_initializer is None:\n weight_initializer = self.backbone_model.weight_initializer\nif bias_initializer is None:\n bias_initializer = self.backbone_model.bias_initializer\nself.units = self.backbone_model.units\nself.mlm... | <|body_start_0|>
super().__init__()
self.backbone_model = RobertaModel.from_cfg(backbone_cfg)
if weight_initializer is None:
weight_initializer = self.backbone_model.weight_initializer
if bias_initializer is None:
bias_initializer = self.backbone_model.bias_initia... | RobertaForMLM | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RobertaForMLM:
def __init__(self, backbone_cfg, weight_initializer=None, bias_initializer=None):
"""Parameters ---------- backbone_cfg weight_initializer bias_initializer"""
<|body_0|>
def forward(self, inputs, valid_length, masked_positions):
"""Getting the scores o... | stack_v2_sparse_classes_36k_train_024133 | 22,705 | permissive | [
{
"docstring": "Parameters ---------- backbone_cfg weight_initializer bias_initializer",
"name": "__init__",
"signature": "def __init__(self, backbone_cfg, weight_initializer=None, bias_initializer=None)"
},
{
"docstring": "Getting the scores of the masked positions. Parameters ---------- inputs... | 2 | stack_v2_sparse_classes_30k_train_005279 | Implement the Python class `RobertaForMLM` described below.
Class description:
Implement the RobertaForMLM class.
Method signatures and docstrings:
- def __init__(self, backbone_cfg, weight_initializer=None, bias_initializer=None): Parameters ---------- backbone_cfg weight_initializer bias_initializer
- def forward(s... | Implement the Python class `RobertaForMLM` described below.
Class description:
Implement the RobertaForMLM class.
Method signatures and docstrings:
- def __init__(self, backbone_cfg, weight_initializer=None, bias_initializer=None): Parameters ---------- backbone_cfg weight_initializer bias_initializer
- def forward(s... | 1df42c561ae9552960e3f8b5f22e74de812a29c6 | <|skeleton|>
class RobertaForMLM:
def __init__(self, backbone_cfg, weight_initializer=None, bias_initializer=None):
"""Parameters ---------- backbone_cfg weight_initializer bias_initializer"""
<|body_0|>
def forward(self, inputs, valid_length, masked_positions):
"""Getting the scores o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RobertaForMLM:
def __init__(self, backbone_cfg, weight_initializer=None, bias_initializer=None):
"""Parameters ---------- backbone_cfg weight_initializer bias_initializer"""
super().__init__()
self.backbone_model = RobertaModel.from_cfg(backbone_cfg)
if weight_initializer is No... | the_stack_v2_python_sparse | src/gluonnlp/models/roberta.py | akshatgui/gluon-nlp | train | 0 | |
b763c1f00360f50874b7c0565f4f64de8f386e5f | [
"self.value = value\nself.left = left\nself.right = right",
"sub = []\nif self.left:\n sub = sub + self.left.deconstruct(level + '@')\nif self.right:\n sub = sub + self.right.deconstruct(level + '@')\nreturn [level] + [self.value] + sub",
"treeInString = self.deconstruct()\nlayers = {}\nfor e in treeInStr... | <|body_start_0|>
self.value = value
self.left = left
self.right = right
<|end_body_0|>
<|body_start_1|>
sub = []
if self.left:
sub = sub + self.left.deconstruct(level + '@')
if self.right:
sub = sub + self.right.deconstruct(level + '@')
re... | Node class for a binary tree. | Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
"""Node class for a binary tree."""
def __init__(self, value, left=None, right=None):
"""Initialize the node."""
<|body_0|>
def deconstruct(self, level='@'):
"""Deconstruct the binary tree into a string."""
<|body_1|>
def printLevelWise(self):
... | stack_v2_sparse_classes_36k_train_024134 | 1,627 | no_license | [
{
"docstring": "Initialize the node.",
"name": "__init__",
"signature": "def __init__(self, value, left=None, right=None)"
},
{
"docstring": "Deconstruct the binary tree into a string.",
"name": "deconstruct",
"signature": "def deconstruct(self, level='@')"
},
{
"docstring": "Pri... | 3 | null | Implement the Python class `Node` described below.
Class description:
Node class for a binary tree.
Method signatures and docstrings:
- def __init__(self, value, left=None, right=None): Initialize the node.
- def deconstruct(self, level='@'): Deconstruct the binary tree into a string.
- def printLevelWise(self): Prin... | Implement the Python class `Node` described below.
Class description:
Node class for a binary tree.
Method signatures and docstrings:
- def __init__(self, value, left=None, right=None): Initialize the node.
- def deconstruct(self, level='@'): Deconstruct the binary tree into a string.
- def printLevelWise(self): Prin... | 97eae3ee806756f4d646d600f434b1e68164ad34 | <|skeleton|>
class Node:
"""Node class for a binary tree."""
def __init__(self, value, left=None, right=None):
"""Initialize the node."""
<|body_0|>
def deconstruct(self, level='@'):
"""Deconstruct the binary tree into a string."""
<|body_1|>
def printLevelWise(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Node:
"""Node class for a binary tree."""
def __init__(self, value, left=None, right=None):
"""Initialize the node."""
self.value = value
self.left = left
self.right = right
def deconstruct(self, level='@'):
"""Deconstruct the binary tree into a string."""
... | the_stack_v2_python_sparse | Python/2019_05_02_Problem_107_Print_Binary_Tree_Level_Wise.py | BaoCaiH/Daily_Coding_Problem | train | 0 |
bc98ad089e3c572c73f9786a3433f5e5beadd4c3 | [
"task = self.images_behavior.create_new_task()\nresponse = self.images_client.get_task(task.id_)\nself.assertEqual(response.status_code, 200)\nget_task = response.entity\nself._validate_get_task_response(task, get_task)",
"errors = []\nif get_task.status != TaskStatus.SUCCESS:\n errors.append(self.error_msg.fo... | <|body_start_0|>
task = self.images_behavior.create_new_task()
response = self.images_client.get_task(task.id_)
self.assertEqual(response.status_code, 200)
get_task = response.entity
self._validate_get_task_response(task, get_task)
<|end_body_0|>
<|body_start_1|>
errors ... | TestGetTask | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestGetTask:
def test_get_task(self):
"""@summary: Get task 1) Create task 2) Get task 3) Verify that the response code is 200 4) Verify that the task contains the expected data"""
<|body_0|>
def _validate_get_task_response(self, task, get_task):
"""@summary: Validat... | stack_v2_sparse_classes_36k_train_024135 | 3,923 | permissive | [
{
"docstring": "@summary: Get task 1) Create task 2) Get task 3) Verify that the response code is 200 4) Verify that the task contains the expected data",
"name": "test_get_task",
"signature": "def test_get_task(self)"
},
{
"docstring": "@summary: Validate that the task and get_task responses ma... | 2 | null | Implement the Python class `TestGetTask` described below.
Class description:
Implement the TestGetTask class.
Method signatures and docstrings:
- def test_get_task(self): @summary: Get task 1) Create task 2) Get task 3) Verify that the response code is 200 4) Verify that the task contains the expected data
- def _val... | Implement the Python class `TestGetTask` described below.
Class description:
Implement the TestGetTask class.
Method signatures and docstrings:
- def test_get_task(self): @summary: Get task 1) Create task 2) Get task 3) Verify that the response code is 200 4) Verify that the task contains the expected data
- def _val... | 30f0e64672676c3f90b4a582fe90fac6621475b3 | <|skeleton|>
class TestGetTask:
def test_get_task(self):
"""@summary: Get task 1) Create task 2) Get task 3) Verify that the response code is 200 4) Verify that the task contains the expected data"""
<|body_0|>
def _validate_get_task_response(self, task, get_task):
"""@summary: Validat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestGetTask:
def test_get_task(self):
"""@summary: Get task 1) Create task 2) Get task 3) Verify that the response code is 200 4) Verify that the task contains the expected data"""
task = self.images_behavior.create_new_task()
response = self.images_client.get_task(task.id_)
se... | the_stack_v2_python_sparse | cloudroast/images/v2/functional/test_get_task.py | RULCSoft/cloudroast | train | 1 | |
e51ea1e9cd9459421b9e5b847dc1dee6ceae7584 | [
"count = [0] * 32\nfor num in nums:\n k = 0\n while k < 32:\n count[k] += num >> k & 1\n k += 1\nres = 0\nfor i in range(32):\n res += count[i] % 3 * 2 ** i\nreturn res",
"ones, twos = (0, 0)\nfor num in nums:\n ones = (ones ^ num) & ~twos\n twos = (twos ^ num) & ~ones\nreturn ones"
] | <|body_start_0|>
count = [0] * 32
for num in nums:
k = 0
while k < 32:
count[k] += num >> k & 1
k += 1
res = 0
for i in range(32):
res += count[i] % 3 * 2 ** i
return res
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findNumberAppearingOnce(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findNumberAppearingOnce_2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
count = [0] * 32
... | stack_v2_sparse_classes_36k_train_024136 | 1,038 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findNumberAppearingOnce",
"signature": "def findNumberAppearingOnce(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findNumberAppearingOnce_2",
"signature": "def findNumberAppearingOnce_2(self, nums... | 2 | stack_v2_sparse_classes_30k_train_010275 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findNumberAppearingOnce(self, nums): :type nums: List[int] :rtype: int
- def findNumberAppearingOnce_2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findNumberAppearingOnce(self, nums): :type nums: List[int] :rtype: int
- def findNumberAppearingOnce_2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solu... | 967b0fbb40ae491b552bc3365a481e66324cb6f2 | <|skeleton|>
class Solution:
def findNumberAppearingOnce(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findNumberAppearingOnce_2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findNumberAppearingOnce(self, nums):
""":type nums: List[int] :rtype: int"""
count = [0] * 32
for num in nums:
k = 0
while k < 32:
count[k] += num >> k & 1
k += 1
res = 0
for i in range(32):
... | the_stack_v2_python_sparse | jianzhi_offer/52_数组中唯一只出现一次的数字.py | ryanatgz/data_structure_and_algorithm | train | 0 | |
58267d18ea74cf0511604d99e7ee5072d91dc4e8 | [
"QtCore.QObject.__init__(self)\nself.q = Queue()\nself.fit = fo.fit_object(self.q, options[3], options[0], options[1], options[2], data)\nname = 'run_' + str(run) + 'index_' + str(options[3]) + '.txt'\nself.savePath = os.path.join(path, name)\nself.data = data\nself.index = options[3]\nself.exp_data = exp_data",
... | <|body_start_0|>
QtCore.QObject.__init__(self)
self.q = Queue()
self.fit = fo.fit_object(self.q, options[3], options[0], options[1], options[2], data)
name = 'run_' + str(run) + 'index_' + str(options[3]) + '.txt'
self.savePath = os.path.join(path, name)
self.data = data
... | Processing object for threading purposes @parameters data: numpy array options: list of options for fit parameters [params, type_of_fit, ROI, index | ProcessImage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessImage:
"""Processing object for threading purposes @parameters data: numpy array options: list of options for fit parameters [params, type_of_fit, ROI, index"""
def __init__(self, data, exp_data, options, path, run):
"""initialize fit_object"""
<|body_0|>
def run(... | stack_v2_sparse_classes_36k_train_024137 | 3,400 | no_license | [
{
"docstring": "initialize fit_object",
"name": "__init__",
"signature": "def __init__(self, data, exp_data, options, path, run)"
},
{
"docstring": "process results using methods from fit process and emit",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012296 | Implement the Python class `ProcessImage` described below.
Class description:
Processing object for threading purposes @parameters data: numpy array options: list of options for fit parameters [params, type_of_fit, ROI, index
Method signatures and docstrings:
- def __init__(self, data, exp_data, options, path, run): ... | Implement the Python class `ProcessImage` described below.
Class description:
Processing object for threading purposes @parameters data: numpy array options: list of options for fit parameters [params, type_of_fit, ROI, index
Method signatures and docstrings:
- def __init__(self, data, exp_data, options, path, run): ... | 788fb964cdf7a5cfd747aa6e064ee31a4ffc3518 | <|skeleton|>
class ProcessImage:
"""Processing object for threading purposes @parameters data: numpy array options: list of options for fit parameters [params, type_of_fit, ROI, index"""
def __init__(self, data, exp_data, options, path, run):
"""initialize fit_object"""
<|body_0|>
def run(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProcessImage:
"""Processing object for threading purposes @parameters data: numpy array options: list of options for fit parameters [params, type_of_fit, ROI, index"""
def __init__(self, data, exp_data, options, path, run):
"""initialize fit_object"""
QtCore.QObject.__init__(self)
... | the_stack_v2_python_sparse | BECMonitor/Image.py | ZachGlassman/BECMonitor | train | 1 |
452536988a1cb2311d0aa37ba05d1021bea91f2e | [
"if not host1:\n raise ValueError('No first host given for the disease')\nif not host2:\n raise ValueError('No second host given for the disease')\nif not disease_name:\n raise ValueError('No name given to the disease')\nself.host1 = host1\nself.host2 = host2\nself.disease_name = disease_name\nself.host1.d... | <|body_start_0|>
if not host1:
raise ValueError('No first host given for the disease')
if not host2:
raise ValueError('No second host given for the disease')
if not disease_name:
raise ValueError('No name given to the disease')
self.host1 = host1
... | BaseTwoSpeciesDisease | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseTwoSpeciesDisease:
def __init__(self, disease_name='', host1=None, host2=None):
"""todo :param host:"""
<|body_0|>
def count_nb_status_per_vertex(self, host, target_status, attribute_position='position'):
"""Count the number of agent having the targeted status in... | stack_v2_sparse_classes_36k_train_024138 | 1,818 | no_license | [
{
"docstring": "todo :param host:",
"name": "__init__",
"signature": "def __init__(self, disease_name='', host1=None, host2=None)"
},
{
"docstring": "Count the number of agent having the targeted status in each vertex. :param host: :param target_status: string in ['inf', 'con', 'imm'] :param att... | 2 | stack_v2_sparse_classes_30k_train_013759 | Implement the Python class `BaseTwoSpeciesDisease` described below.
Class description:
Implement the BaseTwoSpeciesDisease class.
Method signatures and docstrings:
- def __init__(self, disease_name='', host1=None, host2=None): todo :param host:
- def count_nb_status_per_vertex(self, host, target_status, attribute_pos... | Implement the Python class `BaseTwoSpeciesDisease` described below.
Class description:
Implement the BaseTwoSpeciesDisease class.
Method signatures and docstrings:
- def __init__(self, disease_name='', host1=None, host2=None): todo :param host:
- def count_nb_status_per_vertex(self, host, target_status, attribute_pos... | b12aa0e546e51a2cd751d6c08a34250a3bfe9607 | <|skeleton|>
class BaseTwoSpeciesDisease:
def __init__(self, disease_name='', host1=None, host2=None):
"""todo :param host:"""
<|body_0|>
def count_nb_status_per_vertex(self, host, target_status, attribute_position='position'):
"""Count the number of agent having the targeted status in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseTwoSpeciesDisease:
def __init__(self, disease_name='', host1=None, host2=None):
"""todo :param host:"""
if not host1:
raise ValueError('No first host given for the disease')
if not host2:
raise ValueError('No second host given for the disease')
if no... | the_stack_v2_python_sparse | sampy/disease/two_species/base.py | em-ach/sampy | train | 0 | |
30fb8651d31439ce3ecb27f1ff145e505262f949 | [
"if not root:\n self.stack = []\n return\nself.stack = [root]\np = root\nwhile self.stack and self.stack[-1].left:\n self.stack.append(self.stack[-1].left)",
"popNode = self.stack.pop()\nif popNode.right:\n self.stack.append(popNode.right)\n while self.stack and self.stack[-1].left:\n self.s... | <|body_start_0|>
if not root:
self.stack = []
return
self.stack = [root]
p = root
while self.stack and self.stack[-1].left:
self.stack.append(self.stack[-1].left)
<|end_body_0|>
<|body_start_1|>
popNode = self.stack.pop()
if popNode.ri... | BSTIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def next(self):
"""@return the next smallest number :rtype: int"""
<|body_1|>
def hasNext(self):
"""@return whether we have a next smallest number :rtype: bool"""
... | stack_v2_sparse_classes_36k_train_024139 | 1,317 | no_license | [
{
"docstring": ":type root: TreeNode",
"name": "__init__",
"signature": "def __init__(self, root)"
},
{
"docstring": "@return the next smallest number :rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": "@return whether we have a next smallest number :rt... | 3 | stack_v2_sparse_classes_30k_val_000833 | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def next(self): @return the next smallest number :rtype: int
- def hasNext(self): @return whether we have a next smallest n... | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def next(self): @return the next smallest number :rtype: int
- def hasNext(self): @return whether we have a next smallest n... | 1d8821da01c9c200732a6b7037b8631689e2f7e7 | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def next(self):
"""@return the next smallest number :rtype: int"""
<|body_1|>
def hasNext(self):
"""@return whether we have a next smallest number :rtype: bool"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
if not root:
self.stack = []
return
self.stack = [root]
p = root
while self.stack and self.stack[-1].left:
self.stack.append(self.stack[-1].left)
def next(self):
... | the_stack_v2_python_sparse | Leetcode0173_InorderWithStack.py | xiaojinghu/Leetcode | train | 0 | |
72db73186aa0138166b0537ede5aa682abd29efc | [
"self.n = n\nself.k = k\nvar_list = []\nfor i in range(k, n + 1):\n num_cliques = comb(i, self.k, exact=True)\n for j in range(comb(i, k, exact=True) + 1):\n var_list.append((i, j))\nself.lp = lp_helper.LP_Helper(var_list)",
"self.lp.add_constraint([((self.k, 0), 1.0)], '>', 0.0)\nself.lp.add_constra... | <|body_start_0|>
self.n = n
self.k = k
var_list = []
for i in range(k, n + 1):
num_cliques = comb(i, self.k, exact=True)
for j in range(comb(i, k, exact=True) + 1):
var_list.append((i, j))
self.lp = lp_helper.LP_Helper(var_list)
<|end_body_... | Computes a bound on the number of gates for finding cliques. Here, we zero out a vertex at a time (as zeroing out edges seems complicated). | LpBound | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LpBound:
"""Computes a bound on the number of gates for finding cliques. Here, we zero out a vertex at a time (as zeroing out edges seems complicated)."""
def __init__(self, n, k):
"""Constructor. ??? should I rename these? n: number of vertices k: size of clique we're looking for"""... | stack_v2_sparse_classes_36k_train_024140 | 10,652 | permissive | [
{
"docstring": "Constructor. ??? should I rename these? n: number of vertices k: size of clique we're looking for",
"name": "__init__",
"signature": "def __init__(self, n, k)"
},
{
"docstring": "Adds constraints based on zeroing out a vertex. This says that if a function finds some set of clique... | 6 | stack_v2_sparse_classes_30k_train_006890 | Implement the Python class `LpBound` described below.
Class description:
Computes a bound on the number of gates for finding cliques. Here, we zero out a vertex at a time (as zeroing out edges seems complicated).
Method signatures and docstrings:
- def __init__(self, n, k): Constructor. ??? should I rename these? n: ... | Implement the Python class `LpBound` described below.
Class description:
Computes a bound on the number of gates for finding cliques. Here, we zero out a vertex at a time (as zeroing out edges seems complicated).
Method signatures and docstrings:
- def __init__(self, n, k): Constructor. ??? should I rename these? n: ... | ae7b736d5199085e6b4d0aadd7c05467920cc20e | <|skeleton|>
class LpBound:
"""Computes a bound on the number of gates for finding cliques. Here, we zero out a vertex at a time (as zeroing out edges seems complicated)."""
def __init__(self, n, k):
"""Constructor. ??? should I rename these? n: number of vertices k: size of clique we're looking for"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LpBound:
"""Computes a bound on the number of gates for finding cliques. Here, we zero out a vertex at a time (as zeroing out edges seems complicated)."""
def __init__(self, n, k):
"""Constructor. ??? should I rename these? n: number of vertices k: size of clique we're looking for"""
self... | the_stack_v2_python_sparse | countingBound/py/lp_gate_bound_2a.py | joshtburdick/misc | train | 0 |
292b6152824f32b105728d4c1dc9e42c666eca79 | [
"task_schema = TaskSchema()\ntask_data = request.get_json()\nvalidated_task_data, errors = task_schema.load(task_data)\nif errors:\n return (dict(status='fail', message=errors), 400)\ntask = Task(**validated_task_data)\nsaved_task = task.save()\nif not saved_task:\n return (dict(status='fail', message='Intern... | <|body_start_0|>
task_schema = TaskSchema()
task_data = request.get_json()
validated_task_data, errors = task_schema.load(task_data)
if errors:
return (dict(status='fail', message=errors), 400)
task = Task(**validated_task_data)
saved_task = task.save()
... | TaskView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskView:
def post(self):
"""Creating an Task ad"""
<|body_0|>
def get(self):
"""Getting All tasks"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
task_schema = TaskSchema()
task_data = request.get_json()
validated_task_data, errors ... | stack_v2_sparse_classes_36k_train_024141 | 2,917 | no_license | [
{
"docstring": "Creating an Task ad",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Getting All tasks",
"name": "get",
"signature": "def get(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002500 | Implement the Python class `TaskView` described below.
Class description:
Implement the TaskView class.
Method signatures and docstrings:
- def post(self): Creating an Task ad
- def get(self): Getting All tasks | Implement the Python class `TaskView` described below.
Class description:
Implement the TaskView class.
Method signatures and docstrings:
- def post(self): Creating an Task ad
- def get(self): Getting All tasks
<|skeleton|>
class TaskView:
def post(self):
"""Creating an Task ad"""
<|body_0|>
... | 015d70b8f79df6c1a5629add35767cee52f424f5 | <|skeleton|>
class TaskView:
def post(self):
"""Creating an Task ad"""
<|body_0|>
def get(self):
"""Getting All tasks"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaskView:
def post(self):
"""Creating an Task ad"""
task_schema = TaskSchema()
task_data = request.get_json()
validated_task_data, errors = task_schema.load(task_data)
if errors:
return (dict(status='fail', message=errors), 400)
task = Task(**validat... | the_stack_v2_python_sparse | app/controllers/task.py | MutegekiHenry/project-cohort-backend | train | 0 | |
b9cd4e1ab9cb30bf63b8487027b548f0388e16b0 | [
"super().__init__()\nself.out_channels = query_dim\nself.num_heads = num_heads\nproj_dim = head_dim * num_heads\nif cross_attention_dim is None:\n cross_attention_dim = query_dim\nself.to_q = nn.Linear(query_dim, proj_dim, bias=bias)\nself.to_k = nn.Linear(cross_attention_dim, proj_dim, bias=bias)\nself.to_v = n... | <|body_start_0|>
super().__init__()
self.out_channels = query_dim
self.num_heads = num_heads
proj_dim = head_dim * num_heads
if cross_attention_dim is None:
cross_attention_dim = query_dim
self.to_q = nn.Linear(query_dim, proj_dim, bias=bias)
self.to_k... | SelfAttention | [
"MIT",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAttention:
def __init__(self, query_dim: int, name: str='exact', how: str='basic', cross_attention_dim: int=None, num_heads: int=8, head_dim: int=64, dropout: float=0.0, bias: bool=False, slice_size: int=4, **kwargs) -> None:
"""Compute self-attention. Includes all the data wrangling... | stack_v2_sparse_classes_36k_train_024142 | 10,093 | permissive | [
{
"docstring": "Compute self-attention. Includes all the data wrangling on the input before attention computation. Input Shape: (B, H'*W', query_dim). Output Shape: (B, H'*W', query_dim). Parameters ---------- query_dim : int The number of channels in the query. Typically: num_heads*head_dim name : str Name of ... | 5 | stack_v2_sparse_classes_30k_train_020502 | Implement the Python class `SelfAttention` described below.
Class description:
Implement the SelfAttention class.
Method signatures and docstrings:
- def __init__(self, query_dim: int, name: str='exact', how: str='basic', cross_attention_dim: int=None, num_heads: int=8, head_dim: int=64, dropout: float=0.0, bias: boo... | Implement the Python class `SelfAttention` described below.
Class description:
Implement the SelfAttention class.
Method signatures and docstrings:
- def __init__(self, query_dim: int, name: str='exact', how: str='basic', cross_attention_dim: int=None, num_heads: int=8, head_dim: int=64, dropout: float=0.0, bias: boo... | 7f79405012eb934b419bbdba8de23f35e840ca85 | <|skeleton|>
class SelfAttention:
def __init__(self, query_dim: int, name: str='exact', how: str='basic', cross_attention_dim: int=None, num_heads: int=8, head_dim: int=64, dropout: float=0.0, bias: bool=False, slice_size: int=4, **kwargs) -> None:
"""Compute self-attention. Includes all the data wrangling... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelfAttention:
def __init__(self, query_dim: int, name: str='exact', how: str='basic', cross_attention_dim: int=None, num_heads: int=8, head_dim: int=64, dropout: float=0.0, bias: bool=False, slice_size: int=4, **kwargs) -> None:
"""Compute self-attention. Includes all the data wrangling on the input ... | the_stack_v2_python_sparse | cellseg_models_pytorch/modules/self_attention_modules.py | okunator/cellseg_models.pytorch | train | 43 | |
986c9ee24b0f0fa54c77baaf71d188c6f623bef1 | [
"for i in range(replays):\n lists = [states[:-1], states[1:], actions, rewards, list(range(len(actions)))]\n if update_order == 'forward':\n zipped = zip(*lists)\n elif update_order == 'reverse':\n zipped = zip(*[reversed(x) for x in lists])\n elif update_order == 'random':\n inds =... | <|body_start_0|>
for i in range(replays):
lists = [states[:-1], states[1:], actions, rewards, list(range(len(actions)))]
if update_order == 'forward':
zipped = zip(*lists)
elif update_order == 'reverse':
zipped = zip(*[reversed(x) for x in list... | QLearning | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QLearning:
def update(self, states, actions, rewards, replays=1, alpha=0.05, gamma=1, update_order='forward'):
"""update Q function based on trajectory of states, actions, and rewards"""
<|body_0|>
def step_update(self, epsilon=0, alpha=0.05, gamma=1):
"""take a step... | stack_v2_sparse_classes_36k_train_024143 | 7,134 | no_license | [
{
"docstring": "update Q function based on trajectory of states, actions, and rewards",
"name": "update",
"signature": "def update(self, states, actions, rewards, replays=1, alpha=0.05, gamma=1, update_order='forward')"
},
{
"docstring": "take a step while updating Q for online learning",
"n... | 3 | stack_v2_sparse_classes_30k_train_015942 | Implement the Python class `QLearning` described below.
Class description:
Implement the QLearning class.
Method signatures and docstrings:
- def update(self, states, actions, rewards, replays=1, alpha=0.05, gamma=1, update_order='forward'): update Q function based on trajectory of states, actions, and rewards
- def ... | Implement the Python class `QLearning` described below.
Class description:
Implement the QLearning class.
Method signatures and docstrings:
- def update(self, states, actions, rewards, replays=1, alpha=0.05, gamma=1, update_order='forward'): update Q function based on trajectory of states, actions, and rewards
- def ... | ab6216a00f30cb5c3ea896b7a0fda7f01845c206 | <|skeleton|>
class QLearning:
def update(self, states, actions, rewards, replays=1, alpha=0.05, gamma=1, update_order='forward'):
"""update Q function based on trajectory of states, actions, and rewards"""
<|body_0|>
def step_update(self, epsilon=0, alpha=0.05, gamma=1):
"""take a step... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QLearning:
def update(self, states, actions, rewards, replays=1, alpha=0.05, gamma=1, update_order='forward'):
"""update Q function based on trajectory of states, actions, and rewards"""
for i in range(replays):
lists = [states[:-1], states[1:], actions, rewards, list(range(len(act... | the_stack_v2_python_sparse | gridworld/rickgrid/Agents.py | richard-warren/rl_sandbox | train | 0 | |
b297989a217f7aab4e59bbb4b52079f08a7e04d4 | [
"self.client_id = client_id\nself.client_secret = client_secret\nself.project_key = project_key",
"encoded = base64.b64encode('{}:{}'.format(self.client_id, self.client_secret))\nheaders = {'Authorization': 'Basic {}'.format(encoded), 'Content-Type': 'application/x-www-form-urlencoded'}\nbody = 'grant_type=client... | <|body_start_0|>
self.client_id = client_id
self.client_secret = client_secret
self.project_key = project_key
<|end_body_0|>
<|body_start_1|>
encoded = base64.b64encode('{}:{}'.format(self.client_id, self.client_secret))
headers = {'Authorization': 'Basic {}'.format(encoded), 'C... | SphereAPIAuthenticator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SphereAPIAuthenticator:
def __init__(self, client_id, client_secret, project_key):
""":type client_id: unicode :type client_secret: unicode :type project_key: unicode"""
<|body_0|>
def auth(self):
"""BÄÄÄM BÄ BÄÄÄÄÄMMMMMMM :returns Access token :rtype: dict"""
... | stack_v2_sparse_classes_36k_train_024144 | 2,676 | no_license | [
{
"docstring": ":type client_id: unicode :type client_secret: unicode :type project_key: unicode",
"name": "__init__",
"signature": "def __init__(self, client_id, client_secret, project_key)"
},
{
"docstring": "BÄÄÄM BÄ BÄÄÄÄÄMMMMMMM :returns Access token :rtype: dict",
"name": "auth",
"... | 2 | stack_v2_sparse_classes_30k_train_002410 | Implement the Python class `SphereAPIAuthenticator` described below.
Class description:
Implement the SphereAPIAuthenticator class.
Method signatures and docstrings:
- def __init__(self, client_id, client_secret, project_key): :type client_id: unicode :type client_secret: unicode :type project_key: unicode
- def auth... | Implement the Python class `SphereAPIAuthenticator` described below.
Class description:
Implement the SphereAPIAuthenticator class.
Method signatures and docstrings:
- def __init__(self, client_id, client_secret, project_key): :type client_id: unicode :type client_secret: unicode :type project_key: unicode
- def auth... | 0199789b2e2b0a9be8e3b00887e187b2ac97ea47 | <|skeleton|>
class SphereAPIAuthenticator:
def __init__(self, client_id, client_secret, project_key):
""":type client_id: unicode :type client_secret: unicode :type project_key: unicode"""
<|body_0|>
def auth(self):
"""BÄÄÄM BÄ BÄÄÄÄÄMMMMMMM :returns Access token :rtype: dict"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SphereAPIAuthenticator:
def __init__(self, client_id, client_secret, project_key):
""":type client_id: unicode :type client_secret: unicode :type project_key: unicode"""
self.client_id = client_id
self.client_secret = client_secret
self.project_key = project_key
def auth(s... | the_stack_v2_python_sparse | faces/lib/sphere_api/api.py | bartoszhernas/ecommhack.api | train | 0 | |
cc4f29a161eab13f9418823efcdea37e9c449c29 | [
"from apps.users.serializers import FollowModelSerializer\nview = self.context.get('view', None)\nfields = ('email', 'username', 'phone_number', 'first_name', 'last_name')\nif view is not None:\n if view.view_name == 'users' and view.action in view.fields_to_return:\n fields = view.fields_to_return[view.a... | <|body_start_0|>
from apps.users.serializers import FollowModelSerializer
view = self.context.get('view', None)
fields = ('email', 'username', 'phone_number', 'first_name', 'last_name')
if view is not None:
if view.view_name == 'users' and view.action in view.fields_to_return... | User model serializer. | UserModelSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserModelSerializer:
"""User model serializer."""
def get_followers(self, obj):
"""Return followers information."""
<|body_0|>
def get_followeds(self, obj):
"""Return followers information."""
<|body_1|>
def get_follow_requests(self, obj):
""... | stack_v2_sparse_classes_36k_train_024145 | 10,085 | no_license | [
{
"docstring": "Return followers information.",
"name": "get_followers",
"signature": "def get_followers(self, obj)"
},
{
"docstring": "Return followers information.",
"name": "get_followeds",
"signature": "def get_followeds(self, obj)"
},
{
"docstring": "Return follow requests."... | 4 | null | Implement the Python class `UserModelSerializer` described below.
Class description:
User model serializer.
Method signatures and docstrings:
- def get_followers(self, obj): Return followers information.
- def get_followeds(self, obj): Return followers information.
- def get_follow_requests(self, obj): Return follow ... | Implement the Python class `UserModelSerializer` described below.
Class description:
User model serializer.
Method signatures and docstrings:
- def get_followers(self, obj): Return followers information.
- def get_followeds(self, obj): Return followers information.
- def get_follow_requests(self, obj): Return follow ... | e2f4557e2a85405838c6c9f65f1cb8a5f60a35ba | <|skeleton|>
class UserModelSerializer:
"""User model serializer."""
def get_followers(self, obj):
"""Return followers information."""
<|body_0|>
def get_followeds(self, obj):
"""Return followers information."""
<|body_1|>
def get_follow_requests(self, obj):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserModelSerializer:
"""User model serializer."""
def get_followers(self, obj):
"""Return followers information."""
from apps.users.serializers import FollowModelSerializer
view = self.context.get('view', None)
fields = ('email', 'username', 'phone_number', 'first_name', '... | the_stack_v2_python_sparse | apps/users/serializers/users.py | HebertFerrer/WebMaster-back-end | train | 0 |
dac48cb07221cd71d02e6381d08eea2b33a0ed82 | [
"self.use_wget = use_wget\nself.quic_binary_dir = quic_binary_dir\nself.quic_server_address = quic_server_address\nself.quic_server_port = quic_server_port\nif not use_wget and (not os.path.isfile(quic_binary_dir + '/quic_client')):\n raise IOError('There is no quic_client in the given dir: %s.' % quic_binary_di... | <|body_start_0|>
self.use_wget = use_wget
self.quic_binary_dir = quic_binary_dir
self.quic_server_address = quic_server_address
self.quic_server_port = quic_server_port
if not use_wget and (not os.path.isfile(quic_binary_dir + '/quic_client')):
raise IOError('There is... | PageloadExperiment | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PageloadExperiment:
def __init__(self, use_wget, quic_binary_dir, quic_server_address, quic_server_port):
"""Initialize PageloadExperiment. Args: use_wget: Whether to use wget. quic_binary_dir: Directory for quic_binary. quic_server_address: IP address of quic server. quic_server_port: P... | stack_v2_sparse_classes_36k_train_024146 | 6,722 | permissive | [
{
"docstring": "Initialize PageloadExperiment. Args: use_wget: Whether to use wget. quic_binary_dir: Directory for quic_binary. quic_server_address: IP address of quic server. quic_server_port: Port of the quic server.",
"name": "__init__",
"signature": "def __init__(self, use_wget, quic_binary_dir, qui... | 4 | stack_v2_sparse_classes_30k_train_000719 | Implement the Python class `PageloadExperiment` described below.
Class description:
Implement the PageloadExperiment class.
Method signatures and docstrings:
- def __init__(self, use_wget, quic_binary_dir, quic_server_address, quic_server_port): Initialize PageloadExperiment. Args: use_wget: Whether to use wget. quic... | Implement the Python class `PageloadExperiment` described below.
Class description:
Implement the PageloadExperiment class.
Method signatures and docstrings:
- def __init__(self, use_wget, quic_binary_dir, quic_server_address, quic_server_port): Initialize PageloadExperiment. Args: use_wget: Whether to use wget. quic... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class PageloadExperiment:
def __init__(self, use_wget, quic_binary_dir, quic_server_address, quic_server_port):
"""Initialize PageloadExperiment. Args: use_wget: Whether to use wget. quic_binary_dir: Directory for quic_binary. quic_server_address: IP address of quic server. quic_server_port: P... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PageloadExperiment:
def __init__(self, use_wget, quic_binary_dir, quic_server_address, quic_server_port):
"""Initialize PageloadExperiment. Args: use_wget: Whether to use wget. quic_binary_dir: Directory for quic_binary. quic_server_address: IP address of quic server. quic_server_port: Port of the qui... | the_stack_v2_python_sparse | net/tools/quic/benchmark/run_client.py | chromium/chromium | train | 17,408 | |
d4797833a63681f1bacdd7b62fbb1864f21e5ddf | [
"if not options['username'] or not options['case'] or (not options['target']):\n print('Options -t (target), -c (case id) and -u (username) are mandatory. Exiting.')\n sys.exit(1)\nuser = Profile.objects.get(username=options['username'].strip())\ncase = Case.objects.get(pk=options['case'].strip())\nif os.path... | <|body_start_0|>
if not options['username'] or not options['case'] or (not options['target']):
print('Options -t (target), -c (case id) and -u (username) are mandatory. Exiting.')
sys.exit(1)
user = Profile.objects.get(username=options['username'].strip())
case = Case.obj... | Image submission via command line. | Command | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
"""Image submission via command line."""
def handle(self, *args, **options):
"""Runs command."""
<|body_0|>
def _add_task(self, target, case, user):
"""Wraps add_task() to catch errors."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if... | stack_v2_sparse_classes_36k_train_024147 | 2,584 | no_license | [
{
"docstring": "Runs command.",
"name": "handle",
"signature": "def handle(self, *args, **options)"
},
{
"docstring": "Wraps add_task() to catch errors.",
"name": "_add_task",
"signature": "def _add_task(self, target, case, user)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016090 | Implement the Python class `Command` described below.
Class description:
Image submission via command line.
Method signatures and docstrings:
- def handle(self, *args, **options): Runs command.
- def _add_task(self, target, case, user): Wraps add_task() to catch errors. | Implement the Python class `Command` described below.
Class description:
Image submission via command line.
Method signatures and docstrings:
- def handle(self, *args, **options): Runs command.
- def _add_task(self, target, case, user): Wraps add_task() to catch errors.
<|skeleton|>
class Command:
"""Image submi... | c9ff33b6ed16eb1cd960822b8031baf9b84a8636 | <|skeleton|>
class Command:
"""Image submission via command line."""
def handle(self, *args, **options):
"""Runs command."""
<|body_0|>
def _add_task(self, target, case, user):
"""Wraps add_task() to catch errors."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Command:
"""Image submission via command line."""
def handle(self, *args, **options):
"""Runs command."""
if not options['username'] or not options['case'] or (not options['target']):
print('Options -t (target), -c (case id) and -u (username) are mandatory. Exiting.')
... | the_stack_v2_python_sparse | analyses/management/commands/submit.py | DanielKorsa/ghiro | train | 1 |
8dfb7f8de3f494afcd16305f24e03775c9499a4f | [
"followers_users_list = [relationship.from_user for relationship in self.filter(to_user=user)]\nfriend_list = self.filter(from_user=user, to_user__in=followers_users_list)\nfriends_users_list = [relationship.to_user for relationship in friend_list]\nfollower_list = self.filter(to_user=user).exclude(from_user__in=fr... | <|body_start_0|>
followers_users_list = [relationship.from_user for relationship in self.filter(to_user=user)]
friend_list = self.filter(from_user=user, to_user__in=followers_users_list)
friends_users_list = [relationship.to_user for relationship in friend_list]
follower_list = self.filt... | RelationshipManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelationshipManager:
def relationships_for_user(self, user):
"""Relationships for user Returns a list of friends, people you are following, and followers, people that are following you but you are not following."""
<|body_0|>
def is_following(self, you, them):
"""Ans... | stack_v2_sparse_classes_36k_train_024148 | 1,799 | no_license | [
{
"docstring": "Relationships for user Returns a list of friends, people you are following, and followers, people that are following you but you are not following.",
"name": "relationships_for_user",
"signature": "def relationships_for_user(self, user)"
},
{
"docstring": "Answers the question, a... | 3 | stack_v2_sparse_classes_30k_train_003298 | Implement the Python class `RelationshipManager` described below.
Class description:
Implement the RelationshipManager class.
Method signatures and docstrings:
- def relationships_for_user(self, user): Relationships for user Returns a list of friends, people you are following, and followers, people that are following... | Implement the Python class `RelationshipManager` described below.
Class description:
Implement the RelationshipManager class.
Method signatures and docstrings:
- def relationships_for_user(self, user): Relationships for user Returns a list of friends, people you are following, and followers, people that are following... | 08f4210e3de77c4564fcc8c1a2e9b47a0088249f | <|skeleton|>
class RelationshipManager:
def relationships_for_user(self, user):
"""Relationships for user Returns a list of friends, people you are following, and followers, people that are following you but you are not following."""
<|body_0|>
def is_following(self, you, them):
"""Ans... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RelationshipManager:
def relationships_for_user(self, user):
"""Relationships for user Returns a list of friends, people you are following, and followers, people that are following you but you are not following."""
followers_users_list = [relationship.from_user for relationship in self.filter(... | the_stack_v2_python_sparse | ninetyseven/apps/relationships/managers.py | syncopated/97bottles | train | 0 | |
3d08d16c6b89726d5f23fc621a41a929a9851002 | [
"if args[0] is None or gfapy.is_placeholder(args[0]):\n return gfapy.AlignmentPlaceholder()\nif len(args) > 1:\n raise gfapy.ArgumentError('The Alignment() constructor requires ' + 'a single positional argument, {} found'.format(len(args)))\nif isinstance(args[0], gfapy.CIGAR) or isinstance(args[0], gfapy.Tra... | <|body_start_0|>
if args[0] is None or gfapy.is_placeholder(args[0]):
return gfapy.AlignmentPlaceholder()
if len(args) > 1:
raise gfapy.ArgumentError('The Alignment() constructor requires ' + 'a single positional argument, {} found'.format(len(args)))
if isinstance(args[0... | Factory for instances of classes which represent alignments in GFA fields. Args: initializer (string, list): the alignment field content version (str): GFA version, either ``'gfa1'`` or ``'gfa2'`` (default: ``'gfa2'``) valid (bool): if ``True``, validation is skipped, when possible (default: ``False``) Returns: :class:... | Alignment | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Alignment:
"""Factory for instances of classes which represent alignments in GFA fields. Args: initializer (string, list): the alignment field content version (str): GFA version, either ``'gfa1'`` or ``'gfa2'`` (default: ``'gfa2'``) valid (bool): if ``True``, validation is skipped, when possible ... | stack_v2_sparse_classes_36k_train_024149 | 5,360 | permissive | [
{
"docstring": "Create an instance of an alignment field class.",
"name": "__new__",
"signature": "def __new__(cls, *args, **kargs)"
},
{
"docstring": "Parses an alignment field Parameters ---------- string : str The string to parse. version : str GFA version (gfa1 or gfa2) If *gfa1*, then CIGAR... | 3 | stack_v2_sparse_classes_30k_train_012805 | Implement the Python class `Alignment` described below.
Class description:
Factory for instances of classes which represent alignments in GFA fields. Args: initializer (string, list): the alignment field content version (str): GFA version, either ``'gfa1'`` or ``'gfa2'`` (default: ``'gfa2'``) valid (bool): if ``True``... | Implement the Python class `Alignment` described below.
Class description:
Factory for instances of classes which represent alignments in GFA fields. Args: initializer (string, list): the alignment field content version (str): GFA version, either ``'gfa1'`` or ``'gfa2'`` (default: ``'gfa2'``) valid (bool): if ``True``... | 12b31daac26ab137b6ee4a29b4f14554ba962dcb | <|skeleton|>
class Alignment:
"""Factory for instances of classes which represent alignments in GFA fields. Args: initializer (string, list): the alignment field content version (str): GFA version, either ``'gfa1'`` or ``'gfa2'`` (default: ``'gfa2'``) valid (bool): if ``True``, validation is skipped, when possible ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Alignment:
"""Factory for instances of classes which represent alignments in GFA fields. Args: initializer (string, list): the alignment field content version (str): GFA version, either ``'gfa1'`` or ``'gfa2'`` (default: ``'gfa2'``) valid (bool): if ``True``, validation is skipped, when possible (default: ``F... | the_stack_v2_python_sparse | gfapy/alignment/alignment.py | ggonnella/gfapy | train | 63 |
93ef74251ab544831a373fcdcb802fb71b1ec59a | [
"raw = cls.validate_payload(payload)\ntry:\n return cls.SUPPORTED_MODES[raw[0]]\nexcept KeyError:\n raise ConversionError(f'Payload not supported for {cls.__name__}', raw=raw)",
"for knx_value, mode in cls.SUPPORTED_MODES.items():\n if mode == value:\n return DPTArray(knx_value)\nraise ConversionE... | <|body_start_0|>
raw = cls.validate_payload(payload)
try:
return cls.SUPPORTED_MODES[raw[0]]
except KeyError:
raise ConversionError(f'Payload not supported for {cls.__name__}', raw=raw)
<|end_body_0|>
<|body_start_1|>
for knx_value, mode in cls.SUPPORTED_MODES.it... | Base class for KNX Climate modes. | _DPTClimateMode | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _DPTClimateMode:
"""Base class for KNX Climate modes."""
def from_knx(cls, payload: DPTArray | DPTBinary) -> HVACModeT:
"""Parse/deserialize from KNX/IP raw data."""
<|body_0|>
def to_knx(cls, value: HVACModeT) -> DPTArray:
"""Serialize to KNX/IP raw data."""
... | stack_v2_sparse_classes_36k_train_024150 | 4,263 | permissive | [
{
"docstring": "Parse/deserialize from KNX/IP raw data.",
"name": "from_knx",
"signature": "def from_knx(cls, payload: DPTArray | DPTBinary) -> HVACModeT"
},
{
"docstring": "Serialize to KNX/IP raw data.",
"name": "to_knx",
"signature": "def to_knx(cls, value: HVACModeT) -> DPTArray"
}... | 2 | stack_v2_sparse_classes_30k_train_006814 | Implement the Python class `_DPTClimateMode` described below.
Class description:
Base class for KNX Climate modes.
Method signatures and docstrings:
- def from_knx(cls, payload: DPTArray | DPTBinary) -> HVACModeT: Parse/deserialize from KNX/IP raw data.
- def to_knx(cls, value: HVACModeT) -> DPTArray: Serialize to KN... | Implement the Python class `_DPTClimateMode` described below.
Class description:
Base class for KNX Climate modes.
Method signatures and docstrings:
- def from_knx(cls, payload: DPTArray | DPTBinary) -> HVACModeT: Parse/deserialize from KNX/IP raw data.
- def to_knx(cls, value: HVACModeT) -> DPTArray: Serialize to KN... | 48d4e31365c15e632b275f0d129cd9f2b2b5717d | <|skeleton|>
class _DPTClimateMode:
"""Base class for KNX Climate modes."""
def from_knx(cls, payload: DPTArray | DPTBinary) -> HVACModeT:
"""Parse/deserialize from KNX/IP raw data."""
<|body_0|>
def to_knx(cls, value: HVACModeT) -> DPTArray:
"""Serialize to KNX/IP raw data."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _DPTClimateMode:
"""Base class for KNX Climate modes."""
def from_knx(cls, payload: DPTArray | DPTBinary) -> HVACModeT:
"""Parse/deserialize from KNX/IP raw data."""
raw = cls.validate_payload(payload)
try:
return cls.SUPPORTED_MODES[raw[0]]
except KeyError:
... | the_stack_v2_python_sparse | xknx/dpt/dpt_hvac_mode.py | XKNX/xknx | train | 248 |
b7255f0e985453353a583103119cfe29c6bd2f8a | [
"Spectrum.__init__(self, *args, **kwargs)\nself._filename = filename\nself._separator = separator\nself._header = header\nif filename:\n wave = []\n flux = []\n with open(filename, 'r') as txt:\n for i in range(skip_lines):\n txt.readline()\n for line in txt:\n if line[0... | <|body_start_0|>
Spectrum.__init__(self, *args, **kwargs)
self._filename = filename
self._separator = separator
self._header = header
if filename:
wave = []
flux = []
with open(filename, 'r') as txt:
for i in range(skip_lines):
... | Handles spectra stored in ASCII files. | SpectrumAscii | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpectrumAscii:
"""Handles spectra stored in ASCII files."""
def __init__(self, filename: str=None, separator: str=',', skip_lines: int=0, comment: str='#', wave_column: int=0, flux_column: int=1, header: bool=True, *args, **kwargs):
"""Reads spectrum from ASCII file. Args: filename: ... | stack_v2_sparse_classes_36k_train_024151 | 46,205 | permissive | [
{
"docstring": "Reads spectrum from ASCII file. Args: filename: Filename to load spectrum from. separator: Separator in file. skip_lines: Number of lines to skip while reading file. comment: Character indicating a comment line. header: Whether to write a header.",
"name": "__init__",
"signature": "def _... | 2 | null | Implement the Python class `SpectrumAscii` described below.
Class description:
Handles spectra stored in ASCII files.
Method signatures and docstrings:
- def __init__(self, filename: str=None, separator: str=',', skip_lines: int=0, comment: str='#', wave_column: int=0, flux_column: int=1, header: bool=True, *args, **... | Implement the Python class `SpectrumAscii` described below.
Class description:
Handles spectra stored in ASCII files.
Method signatures and docstrings:
- def __init__(self, filename: str=None, separator: str=',', skip_lines: int=0, comment: str='#', wave_column: int=0, flux_column: int=1, header: bool=True, *args, **... | 648eb1758e3744d9e3d6669edc4a0c4753559f17 | <|skeleton|>
class SpectrumAscii:
"""Handles spectra stored in ASCII files."""
def __init__(self, filename: str=None, separator: str=',', skip_lines: int=0, comment: str='#', wave_column: int=0, flux_column: int=1, header: bool=True, *args, **kwargs):
"""Reads spectrum from ASCII file. Args: filename: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpectrumAscii:
"""Handles spectra stored in ASCII files."""
def __init__(self, filename: str=None, separator: str=',', skip_lines: int=0, comment: str='#', wave_column: int=0, flux_column: int=1, header: bool=True, *args, **kwargs):
"""Reads spectrum from ASCII file. Args: filename: Filename to l... | the_stack_v2_python_sparse | spexxy/data/spectrum.py | thusser/spexxy | train | 4 |
93d60f57cc66f9ce94190e5d6f34dcefa500a527 | [
"self.srv_addr = (srv_host, srv_port)\nself.cli_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\nself.cli_sock.connect(self.srv_addr)",
"while True:\n try:\n data = input('> ')\n assert data\n except (EOFError, KeyboardInterrupt, AssertionError) as e:\n print('用户输入异常或为空, 退出...'... | <|body_start_0|>
self.srv_addr = (srv_host, srv_port)
self.cli_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.cli_sock.connect(self.srv_addr)
<|end_body_0|>
<|body_start_1|>
while True:
try:
data = input('> ')
assert data
... | 基于TCP协议的回声客户端. | TCPEchoClient | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TCPEchoClient:
"""基于TCP协议的回声客户端."""
def __init__(self, srv_host='127.0.0.1', srv_port=12345):
"""Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号"""
<|body_0|>
def mainloop(self):
"""主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异常(EOFError: UNIX上为Ctr... | stack_v2_sparse_classes_36k_train_024152 | 1,296 | no_license | [
{
"docstring": "Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号",
"name": "__init__",
"signature": "def __init__(self, srv_host='127.0.0.1', srv_port=12345)"
},
{
"docstring": "主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异常(EOFError: UNIX上为Ctrl+d,Windows上为Ctrl+Z+Enter), 跳出循环 - 关闭s... | 2 | stack_v2_sparse_classes_30k_train_016195 | Implement the Python class `TCPEchoClient` described below.
Class description:
基于TCP协议的回声客户端.
Method signatures and docstrings:
- def __init__(self, srv_host='127.0.0.1', srv_port=12345): Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号
- def mainloop(self): 主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异... | Implement the Python class `TCPEchoClient` described below.
Class description:
基于TCP协议的回声客户端.
Method signatures and docstrings:
- def __init__(self, srv_host='127.0.0.1', srv_port=12345): Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号
- def mainloop(self): 主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异... | 43d2f943c703fe99966688c22de2d4493383feb9 | <|skeleton|>
class TCPEchoClient:
"""基于TCP协议的回声客户端."""
def __init__(self, srv_host='127.0.0.1', srv_port=12345):
"""Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号"""
<|body_0|>
def mainloop(self):
"""主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异常(EOFError: UNIX上为Ctr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TCPEchoClient:
"""基于TCP协议的回声客户端."""
def __init__(self, srv_host='127.0.0.1', srv_port=12345):
"""Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号"""
self.srv_addr = (srv_host, srv_port)
self.cli_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.cli_sock.connect(sel... | the_stack_v2_python_sparse | day14/tcp_echo_client.py | east4ming/pyEdu | train | 0 |
31a4a12b348e3837db43254aff922a8ad4447f1c | [
"self.face_detector = face_detector\nself.face_generator = face_generator\nself.save_all = save_all\nself.config = config\nself.video_converter = None\nif 'video_smooth_filter' in self.config:\n self.video_converter = video_utils.VideoConverter(use_kalman_filter=self.config['video_smooth_filter'] == 'kalman', bb... | <|body_start_0|>
self.face_detector = face_detector
self.face_generator = face_generator
self.save_all = save_all
self.config = config
self.video_converter = None
if 'video_smooth_filter' in self.config:
self.video_converter = video_utils.VideoConverter(use_ka... | Swapper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Swapper:
def __init__(self, face_detector: FaceDetector, face_generator: FaceGenerator, config, save_all=False):
"""Utility object that holds and manages the components necessary for swapping faces in a picture. :param face_detector: :param face_generator: :param config: :param save_all:... | stack_v2_sparse_classes_36k_train_024153 | 14,636 | permissive | [
{
"docstring": "Utility object that holds and manages the components necessary for swapping faces in a picture. :param face_detector: :param face_generator: :param config: :param save_all:",
"name": "__init__",
"signature": "def __init__(self, face_detector: FaceDetector, face_generator: FaceGenerator, ... | 2 | stack_v2_sparse_classes_30k_train_002535 | Implement the Python class `Swapper` described below.
Class description:
Implement the Swapper class.
Method signatures and docstrings:
- def __init__(self, face_detector: FaceDetector, face_generator: FaceGenerator, config, save_all=False): Utility object that holds and manages the components necessary for swapping ... | Implement the Python class `Swapper` described below.
Class description:
Implement the Swapper class.
Method signatures and docstrings:
- def __init__(self, face_detector: FaceDetector, face_generator: FaceGenerator, config, save_all=False): Utility object that holds and manages the components necessary for swapping ... | ada4803d4f1d53233ba4592beec75271254e5182 | <|skeleton|>
class Swapper:
def __init__(self, face_detector: FaceDetector, face_generator: FaceGenerator, config, save_all=False):
"""Utility object that holds and manages the components necessary for swapping faces in a picture. :param face_detector: :param face_generator: :param config: :param save_all:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Swapper:
def __init__(self, face_detector: FaceDetector, face_generator: FaceGenerator, config, save_all=False):
"""Utility object that holds and manages the components necessary for swapping faces in a picture. :param face_detector: :param face_generator: :param config: :param save_all:"""
se... | the_stack_v2_python_sparse | face_swap/deep_swap.py | brahimbellahcen/face-swap | train | 0 | |
3a44b3761413c880fe481fb0de764ba1ff5b3464 | [
"service_type = self.request.query_params.get('service_type')\nif service_type:\n service_type_validator(service_type)\n queryset = self.queryset.filter(service_type=service_type)\nelse:\n queryset = super(StatusTransitViewSet, self).get_queryset()\nreturn queryset",
"queryset = self.get_queryset()\nauto... | <|body_start_0|>
service_type = self.request.query_params.get('service_type')
if service_type:
service_type_validator(service_type)
queryset = self.queryset.filter(service_type=service_type)
else:
queryset = super(StatusTransitViewSet, self).get_queryset()
... | StatusTransitViewSet | [
"MIT",
"LGPL-2.1-or-later",
"LGPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StatusTransitViewSet:
def get_queryset(self):
"""支持额外过滤参数[service_type]"""
<|body_0|>
def is_auto(self, request, *args, **kwargs):
"""工单状态是否自动转换"""
<|body_1|>
def get_auto_detail(self, request, *args, **kwargs):
"""获取工单状态自动流转的详细信息"""
<|bo... | stack_v2_sparse_classes_36k_train_024154 | 11,791 | permissive | [
{
"docstring": "支持额外过滤参数[service_type]",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "工单状态是否自动转换",
"name": "is_auto",
"signature": "def is_auto(self, request, *args, **kwargs)"
},
{
"docstring": "获取工单状态自动流转的详细信息",
"name": "get_auto_detail",... | 4 | stack_v2_sparse_classes_30k_train_003040 | Implement the Python class `StatusTransitViewSet` described below.
Class description:
Implement the StatusTransitViewSet class.
Method signatures and docstrings:
- def get_queryset(self): 支持额外过滤参数[service_type]
- def is_auto(self, request, *args, **kwargs): 工单状态是否自动转换
- def get_auto_detail(self, request, *args, **kwa... | Implement the Python class `StatusTransitViewSet` described below.
Class description:
Implement the StatusTransitViewSet class.
Method signatures and docstrings:
- def get_queryset(self): 支持额外过滤参数[service_type]
- def is_auto(self, request, *args, **kwargs): 工单状态是否自动转换
- def get_auto_detail(self, request, *args, **kwa... | 2d708bd0d869d391456e0fb8d644af3b9f031acf | <|skeleton|>
class StatusTransitViewSet:
def get_queryset(self):
"""支持额外过滤参数[service_type]"""
<|body_0|>
def is_auto(self, request, *args, **kwargs):
"""工单状态是否自动转换"""
<|body_1|>
def get_auto_detail(self, request, *args, **kwargs):
"""获取工单状态自动流转的详细信息"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StatusTransitViewSet:
def get_queryset(self):
"""支持额外过滤参数[service_type]"""
service_type = self.request.query_params.get('service_type')
if service_type:
service_type_validator(service_type)
queryset = self.queryset.filter(service_type=service_type)
else:... | the_stack_v2_python_sparse | itsm/ticket_status/views.py | TencentBlueKing/bk-itsm | train | 100 | |
e0b24a068772e232fa25343576440fe06d19e39c | [
"self.content_type = CONTENT_TYPE\nself.root = partition_type\nself.headers_obj = HmcHeaders.HmcHeaders('web')\ndirectory_path = os.path.dirname(__file__)\nself.input = open(directory_path + '/data/poweron_lpar.xml', 'r').read()",
"super().__init__(ip, self.root, self.content_type, session_id)\nlog_object.log_deb... | <|body_start_0|>
self.content_type = CONTENT_TYPE
self.root = partition_type
self.headers_obj = HmcHeaders.HmcHeaders('web')
directory_path = os.path.dirname(__file__)
self.input = open(directory_path + '/data/poweron_lpar.xml', 'r').read()
<|end_body_0|>
<|body_start_1|>
... | PowerOnPartition | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PowerOnPartition:
def __init__(self, partition_type):
"""initializes root and content_type Args: partition_type : type of object Logical Partition or VirtualIOServer"""
<|body_0|>
def poweron_Partition(self, ip, logicalpartition_object, session_id):
"""performs power... | stack_v2_sparse_classes_36k_train_024155 | 2,956 | permissive | [
{
"docstring": "initializes root and content_type Args: partition_type : type of object Logical Partition or VirtualIOServer",
"name": "__init__",
"signature": "def __init__(self, partition_type)"
},
{
"docstring": "performs poweron operation for the provided LogicalPartition object Args: ip : i... | 2 | null | Implement the Python class `PowerOnPartition` described below.
Class description:
Implement the PowerOnPartition class.
Method signatures and docstrings:
- def __init__(self, partition_type): initializes root and content_type Args: partition_type : type of object Logical Partition or VirtualIOServer
- def poweron_Par... | Implement the Python class `PowerOnPartition` described below.
Class description:
Implement the PowerOnPartition class.
Method signatures and docstrings:
- def __init__(self, partition_type): initializes root and content_type Args: partition_type : type of object Logical Partition or VirtualIOServer
- def poweron_Par... | 8e46a5a25a57d07f0612404f4b978234d6d2cd4b | <|skeleton|>
class PowerOnPartition:
def __init__(self, partition_type):
"""initializes root and content_type Args: partition_type : type of object Logical Partition or VirtualIOServer"""
<|body_0|>
def poweron_Partition(self, ip, logicalpartition_object, session_id):
"""performs power... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PowerOnPartition:
def __init__(self, partition_type):
"""initializes root and content_type Args: partition_type : type of object Logical Partition or VirtualIOServer"""
self.content_type = CONTENT_TYPE
self.root = partition_type
self.headers_obj = HmcHeaders.HmcHeaders('web')
... | the_stack_v2_python_sparse | src/partition_operation_util/PowerOnPartition.py | Python3pkg/HmcRestClient | train | 0 | |
d3d068312c27744b34f3ed645696066683375e20 | [
"self.minh, self.maxh, self.total = ([], [], 0)\nheapq.heapify(self.minh)\nheapq.heapify(self.maxh)",
"heapq.heappush(self.maxh, num)\nheapq.heappush(self.minh, -heapq.heappop(self.maxh))\nif len(self.minh) > len(self.maxh):\n heapq.heappush(self.maxh, -heapq.heappop(self.minh))",
"if len(self.maxh) > len(se... | <|body_start_0|>
self.minh, self.maxh, self.total = ([], [], 0)
heapq.heapify(self.minh)
heapq.heapify(self.maxh)
<|end_body_0|>
<|body_start_1|>
heapq.heappush(self.maxh, num)
heapq.heappush(self.minh, -heapq.heappop(self.maxh))
if len(self.minh) > len(self.maxh):
... | MedianFinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: None"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_36k_train_024156 | 1,889 | no_license | [
{
"docstring": "initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type num: int :rtype: None",
"name": "addNum",
"signature": "def addNum(self, num)"
},
{
"docstring": ":rtype: float",
"name": "findMedian",
"s... | 3 | null | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: None
- def findMedian(self): :rtype: float | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: None
- def findMedian(self): :rtype: float
<|skeleton|>
class Me... | 6d012496b7f0279b3e2c31c1f444eebb7a7a20b9 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: None"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
self.minh, self.maxh, self.total = ([], [], 0)
heapq.heapify(self.minh)
heapq.heapify(self.maxh)
def addNum(self, num):
""":type num: int :rtype: None"""
heapq.heappush(self.maxh, ... | the_stack_v2_python_sparse | FindMedianFromDataStream.py | xmy7080/leetcode | train | 0 | |
e899bd664307d40bb06ca0eff4da0ade00d38689 | [
"self.datetimestamp = kwargs.get('datetimestamp') or datetime.datetime.now().strftime('%Y%m%d%H%M%S')\nself.identifier = None\nself.force_no_cloudshell = bool(kwargs.get('no_cloudshell'))\nself.project_id = kwargs.get('project_id')\nif kwargs.get('composite_root_resources'):\n tmpcrr = kwargs.get('composite_root... | <|body_start_0|>
self.datetimestamp = kwargs.get('datetimestamp') or datetime.datetime.now().strftime('%Y%m%d%H%M%S')
self.identifier = None
self.force_no_cloudshell = bool(kwargs.get('no_cloudshell'))
self.project_id = kwargs.get('project_id')
if kwargs.get('composite_root_resou... | Forseti installer config object. | Config | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Config:
"""Forseti installer config object."""
def __init__(self, **kwargs):
"""Initialize. Args: kwargs (dict): The kwargs."""
<|body_0|>
def generate_identifier(self, organization_id):
"""Generate resource unique identifier. Hash the timestamp and organization ... | stack_v2_sparse_classes_36k_train_024157 | 2,847 | permissive | [
{
"docstring": "Initialize. Args: kwargs (dict): The kwargs.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Generate resource unique identifier. Hash the timestamp and organization id and take the first 7 characters. Lowercase is needed because some resource... | 2 | null | Implement the Python class `Config` described below.
Class description:
Forseti installer config object.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialize. Args: kwargs (dict): The kwargs.
- def generate_identifier(self, organization_id): Generate resource unique identifier. Hash the timest... | Implement the Python class `Config` described below.
Class description:
Forseti installer config object.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialize. Args: kwargs (dict): The kwargs.
- def generate_identifier(self, organization_id): Generate resource unique identifier. Hash the timest... | d4421afa50a17ed47cbebe942044ebab3720e0f5 | <|skeleton|>
class Config:
"""Forseti installer config object."""
def __init__(self, **kwargs):
"""Initialize. Args: kwargs (dict): The kwargs."""
<|body_0|>
def generate_identifier(self, organization_id):
"""Generate resource unique identifier. Hash the timestamp and organization ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Config:
"""Forseti installer config object."""
def __init__(self, **kwargs):
"""Initialize. Args: kwargs (dict): The kwargs."""
self.datetimestamp = kwargs.get('datetimestamp') or datetime.datetime.now().strftime('%Y%m%d%H%M%S')
self.identifier = None
self.force_no_cloudsh... | the_stack_v2_python_sparse | install/gcp/installer/configs/config.py | kevensen/forseti-security | train | 1 |
05e58d44db8f43cc9ff77601bb92ffce8223cdfd | [
"KratosMultiphysics.Process.__init__(self)\ndefault_settings = KratosMultiphysics.Parameters('\\n {\\n \"model_part_name\":\"\",\\n \"center_of_rotation\":[0.0,0.0,0.0],\\n \"calculate_torque\":false,\\n \"torque_model_part_name\":\"\",\\n ... | <|body_start_0|>
KratosMultiphysics.Process.__init__(self)
default_settings = KratosMultiphysics.Parameters('\n {\n "model_part_name":"",\n "center_of_rotation":[0.0,0.0,0.0],\n "calculate_torque":false,\n "torque_model_part_name":"",\n ... | This process applies a rotation to a given modelpart or a submodelpart Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings. | ApplyRotateRegionProcess | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApplyRotateRegionProcess:
"""This process applies a rotation to a given modelpart or a submodelpart Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings."""
def __init__(self, Model, settings):
"""The d... | stack_v2_sparse_classes_36k_train_024158 | 4,517 | permissive | [
{
"docstring": "The default constructor of the class Keyword arguments: self -- It signifies an instance of a class. Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings.",
"name": "__init__",
"signature": "def __init__(self, Model, settings)"
}... | 3 | null | Implement the Python class `ApplyRotateRegionProcess` described below.
Class description:
This process applies a rotation to a given modelpart or a submodelpart Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings.
Method signatures and... | Implement the Python class `ApplyRotateRegionProcess` described below.
Class description:
This process applies a rotation to a given modelpart or a submodelpart Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings.
Method signatures and... | 366949ec4e3651702edc6ac3061d2988f10dd271 | <|skeleton|>
class ApplyRotateRegionProcess:
"""This process applies a rotation to a given modelpart or a submodelpart Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings."""
def __init__(self, Model, settings):
"""The d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApplyRotateRegionProcess:
"""This process applies a rotation to a given modelpart or a submodelpart Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings."""
def __init__(self, Model, settings):
"""The default constr... | the_stack_v2_python_sparse | applications/ChimeraApplication/python_scripts/rotate_region_process.py | KratosMultiphysics/Kratos | train | 994 |
b6d477d862bd615f44e6299546155d82a5331d40 | [
"with tf.variable_scope('generator'):\n encoder_layers, encoder_layer_channels = self._encoder(images)\n decoder_layers = self._decoder(encoder_layers, encoder_layer_channels)\n output = decoder_layers[-1]\n output = tf.identity(output, name='generated_images')\n return output",
"layers = []\nlayer... | <|body_start_0|>
with tf.variable_scope('generator'):
encoder_layers, encoder_layer_channels = self._encoder(images)
decoder_layers = self._decoder(encoder_layers, encoder_layer_channels)
output = decoder_layers[-1]
output = tf.identity(output, name='generated_ima... | Generator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Generator:
def create(self, images):
"""Generates fake images based off the input images. Uses a "U-net" architecture, an encoder-decoder with skip connections @images: A set of images normalized to [-1, 1], with shape [batch_size, img_size, img_size, input_channels] @returns: A set of g... | stack_v2_sparse_classes_36k_train_024159 | 5,008 | no_license | [
{
"docstring": "Generates fake images based off the input images. Uses a \"U-net\" architecture, an encoder-decoder with skip connections @images: A set of images normalized to [-1, 1], with shape [batch_size, img_size, img_size, input_channels] @returns: A set of generated images in range [-1, 1], with shape [... | 3 | stack_v2_sparse_classes_30k_train_003508 | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def create(self, images): Generates fake images based off the input images. Uses a "U-net" architecture, an encoder-decoder with skip connections @images: A set of images norma... | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def create(self, images): Generates fake images based off the input images. Uses a "U-net" architecture, an encoder-decoder with skip connections @images: A set of images norma... | 0d5c75877eecda2f812afa0576c0b947e3818b73 | <|skeleton|>
class Generator:
def create(self, images):
"""Generates fake images based off the input images. Uses a "U-net" architecture, an encoder-decoder with skip connections @images: A set of images normalized to [-1, 1], with shape [batch_size, img_size, img_size, input_channels] @returns: A set of g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Generator:
def create(self, images):
"""Generates fake images based off the input images. Uses a "U-net" architecture, an encoder-decoder with skip connections @images: A set of images normalized to [-1, 1], with shape [batch_size, img_size, img_size, input_channels] @returns: A set of generated image... | the_stack_v2_python_sparse | trainer/generator.py | 3a1b2c3/Image-to-Image-Translation | train | 0 | |
6f1f1b7cabf9af3b280400c866d29246dced6d20 | [
"if docs.from_date and docs.to_date:\n rec = self.env['account.analytic.line'].search([('user_id', '=', docs.employee[0].id), ('date', '>=', docs.from_date), ('date', '<=', docs.to_date)])\nelif docs.from_date:\n rec = self.env['account.analytic.line'].search([('user_id', '=', docs.employee[0].id), ('date', '... | <|body_start_0|>
if docs.from_date and docs.to_date:
rec = self.env['account.analytic.line'].search([('user_id', '=', docs.employee[0].id), ('date', '>=', docs.from_date), ('date', '<=', docs.to_date)])
elif docs.from_date:
rec = self.env['account.analytic.line'].search([('user_i... | ReportTimesheet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReportTimesheet:
def get_timesheets(self, docs):
"""input : name of employee and the starting date and ending date output: timesheets by that particular employee within that period and the total duration"""
<|body_0|>
def _get_report_values(self, docids, data=None):
... | stack_v2_sparse_classes_36k_train_024160 | 4,467 | no_license | [
{
"docstring": "input : name of employee and the starting date and ending date output: timesheets by that particular employee within that period and the total duration",
"name": "get_timesheets",
"signature": "def get_timesheets(self, docs)"
},
{
"docstring": "we are overwriting this function be... | 2 | null | Implement the Python class `ReportTimesheet` described below.
Class description:
Implement the ReportTimesheet class.
Method signatures and docstrings:
- def get_timesheets(self, docs): input : name of employee and the starting date and ending date output: timesheets by that particular employee within that period and... | Implement the Python class `ReportTimesheet` described below.
Class description:
Implement the ReportTimesheet class.
Method signatures and docstrings:
- def get_timesheets(self, docs): input : name of employee and the starting date and ending date output: timesheets by that particular employee within that period and... | bb6453404e4f28060643f23c1c6311587f7d2925 | <|skeleton|>
class ReportTimesheet:
def get_timesheets(self, docs):
"""input : name of employee and the starting date and ending date output: timesheets by that particular employee within that period and the total duration"""
<|body_0|>
def _get_report_values(self, docids, data=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReportTimesheet:
def get_timesheets(self, docs):
"""input : name of employee and the starting date and ending date output: timesheets by that particular employee within that period and the total duration"""
if docs.from_date and docs.to_date:
rec = self.env['account.analytic.line']... | the_stack_v2_python_sparse | timesheets_by_employee/report/report_timesheets.py | aaltinisik/CybroAddons | train | 1 | |
6f91d47659a9ec242d4cb42f02a6de6f1b296116 | [
"form = TagForm()\ntags = Tag.query.filter().all()\nif not tags:\n tags = None\ntemplate_return = flask.render_template('tags.html', table_data=tags, form=form)\nreturn flask.Response(template_return, mimetype='text/html')",
"form = TagForm()\nif form.validate_on_submit():\n name = form.name.data\n tag_o... | <|body_start_0|>
form = TagForm()
tags = Tag.query.filter().all()
if not tags:
tags = None
template_return = flask.render_template('tags.html', table_data=tags, form=form)
return flask.Response(template_return, mimetype='text/html')
<|end_body_0|>
<|body_start_1|>
... | TagResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagResource:
def get(self):
"""Handles the showing or not of the tags on the system. Returns: flask template."""
<|body_0|>
def post(self):
"""Handles the showing or not of the tags on the system. Returns: flask template."""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_36k_train_024161 | 3,873 | no_license | [
{
"docstring": "Handles the showing or not of the tags on the system. Returns: flask template.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Handles the showing or not of the tags on the system. Returns: flask template.",
"name": "post",
"signature": "def post(self)"
... | 2 | stack_v2_sparse_classes_30k_train_019526 | Implement the Python class `TagResource` described below.
Class description:
Implement the TagResource class.
Method signatures and docstrings:
- def get(self): Handles the showing or not of the tags on the system. Returns: flask template.
- def post(self): Handles the showing or not of the tags on the system. Return... | Implement the Python class `TagResource` described below.
Class description:
Implement the TagResource class.
Method signatures and docstrings:
- def get(self): Handles the showing or not of the tags on the system. Returns: flask template.
- def post(self): Handles the showing or not of the tags on the system. Return... | 865403e3b1717226b25c9d64aeb4c35c7220e7e3 | <|skeleton|>
class TagResource:
def get(self):
"""Handles the showing or not of the tags on the system. Returns: flask template."""
<|body_0|>
def post(self):
"""Handles the showing or not of the tags on the system. Returns: flask template."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TagResource:
def get(self):
"""Handles the showing or not of the tags on the system. Returns: flask template."""
form = TagForm()
tags = Tag.query.filter().all()
if not tags:
tags = None
template_return = flask.render_template('tags.html', table_data=tags, f... | the_stack_v2_python_sparse | things_organizer/web_app/tags/resources.py | yeyeto2788/Things-Organizer | train | 11 | |
90e08401cf50ef80d42fcfa6c388650e5fc09d54 | [
"favorite_nodes = UserFavoriteNode.get_favorite_nodes(get_jwt_identity())\nschema = GenericNodeSchema(many=True)\nresponse = json.loads(schema.dumps(favorite_nodes).data)\nreturn jsonify_response(response, 200)",
"user_id = get_jwt_identity()\ndata = json.loads(request.data)\nif 'nodeId' not in data or 'nodeType'... | <|body_start_0|>
favorite_nodes = UserFavoriteNode.get_favorite_nodes(get_jwt_identity())
schema = GenericNodeSchema(many=True)
response = json.loads(schema.dumps(favorite_nodes).data)
return jsonify_response(response, 200)
<|end_body_0|>
<|body_start_1|>
user_id = get_jwt_ident... | Container for the LIST and CREATE endpoints for favorite nodes | ListCreateFavoriteNodes | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListCreateFavoriteNodes:
"""Container for the LIST and CREATE endpoints for favorite nodes"""
def get(self):
"""Returns all of the user's favorite nodes that he has access to UNTESTED"""
<|body_0|>
def post(self):
"""Endpoint used for favoriting a node for the cu... | stack_v2_sparse_classes_36k_train_024162 | 44,865 | no_license | [
{
"docstring": "Returns all of the user's favorite nodes that he has access to UNTESTED",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Endpoint used for favoriting a node for the currently authenticated user",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015044 | Implement the Python class `ListCreateFavoriteNodes` described below.
Class description:
Container for the LIST and CREATE endpoints for favorite nodes
Method signatures and docstrings:
- def get(self): Returns all of the user's favorite nodes that he has access to UNTESTED
- def post(self): Endpoint used for favorit... | Implement the Python class `ListCreateFavoriteNodes` described below.
Class description:
Container for the LIST and CREATE endpoints for favorite nodes
Method signatures and docstrings:
- def get(self): Returns all of the user's favorite nodes that he has access to UNTESTED
- def post(self): Endpoint used for favorit... | 00434985013b65fe45b0a8c8a7f0b50bb727087a | <|skeleton|>
class ListCreateFavoriteNodes:
"""Container for the LIST and CREATE endpoints for favorite nodes"""
def get(self):
"""Returns all of the user's favorite nodes that he has access to UNTESTED"""
<|body_0|>
def post(self):
"""Endpoint used for favoriting a node for the cu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListCreateFavoriteNodes:
"""Container for the LIST and CREATE endpoints for favorite nodes"""
def get(self):
"""Returns all of the user's favorite nodes that he has access to UNTESTED"""
favorite_nodes = UserFavoriteNode.get_favorite_nodes(get_jwt_identity())
schema = GenericNodeS... | the_stack_v2_python_sparse | core/views.py | gingerComms/gingerCommsAPIs | train | 0 |
0ec1ac4d4c9d60181fa0bcb9f9d23fe783a20444 | [
"self.nums = collections.deque(maxlen=size)\nself.curr_sum = 0\nself.size = size",
"self.curr_sum += val\nif len(self.nums) == self.size:\n self.curr_sum -= self.nums[0]\nself.nums.append(val)\nreturn self.curr_sum / len(self.nums)"
] | <|body_start_0|>
self.nums = collections.deque(maxlen=size)
self.curr_sum = 0
self.size = size
<|end_body_0|>
<|body_start_1|>
self.curr_sum += val
if len(self.nums) == self.size:
self.curr_sum -= self.nums[0]
self.nums.append(val)
return self.curr_su... | MovingAverage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.nums = collections.deque(maxlen=... | stack_v2_sparse_classes_36k_train_024163 | 1,524 | no_license | [
{
"docstring": "Initialize your data structure here. :type size: int",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": ":type val: int :rtype: float",
"name": "next",
"signature": "def next(self, val)"
}
] | 2 | null | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float
<|skeleton|>
class MovingAverage:
... | 98fb752c574a6ec5961a274e41a44275b56da194 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
self.nums = collections.deque(maxlen=size)
self.curr_sum = 0
self.size = size
def next(self, val):
""":type val: int :rtype: float"""
self.curr_sum += val
... | the_stack_v2_python_sparse | Challenges/movingAverageDataStream.py | AusCommsteam/Algorithm-and-Data-Structures-and-Coding-Challenges | train | 0 | |
153bb61a97bdc6de811aff603ebbe2318fcb5571 | [
"if not os.path.exists(path):\n return {}\nRequestFileCom.mutex.acquire()\nwith open(path, 'r') as f:\n content = f.readlines()\n request_dict = {}\n for line in content:\n try:\n key = line.split('::')[0]\n value = line.split('::')[1]\n if value.endswith('\\n'):\... | <|body_start_0|>
if not os.path.exists(path):
return {}
RequestFileCom.mutex.acquire()
with open(path, 'r') as f:
content = f.readlines()
request_dict = {}
for line in content:
try:
key = line.split('::')[0]
... | This class allows supplies methods to handle the request file. | RequestFileCom | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RequestFileCom:
"""This class allows supplies methods to handle the request file."""
def file_to_dict(path='current_request.txt'):
"""The function reads the file and return a dict as follow: {key, value}."""
<|body_0|>
def get_value(key):
"""The function returns ... | stack_v2_sparse_classes_36k_train_024164 | 2,224 | no_license | [
{
"docstring": "The function reads the file and return a dict as follow: {key, value}.",
"name": "file_to_dict",
"signature": "def file_to_dict(path='current_request.txt')"
},
{
"docstring": "The function returns the value of the current title in request file.",
"name": "get_value",
"sig... | 3 | stack_v2_sparse_classes_30k_train_003388 | Implement the Python class `RequestFileCom` described below.
Class description:
This class allows supplies methods to handle the request file.
Method signatures and docstrings:
- def file_to_dict(path='current_request.txt'): The function reads the file and return a dict as follow: {key, value}.
- def get_value(key): ... | Implement the Python class `RequestFileCom` described below.
Class description:
This class allows supplies methods to handle the request file.
Method signatures and docstrings:
- def file_to_dict(path='current_request.txt'): The function reads the file and return a dict as follow: {key, value}.
- def get_value(key): ... | f97386d7ba9ec639083c150706429b832fd288eb | <|skeleton|>
class RequestFileCom:
"""This class allows supplies methods to handle the request file."""
def file_to_dict(path='current_request.txt'):
"""The function reads the file and return a dict as follow: {key, value}."""
<|body_0|>
def get_value(key):
"""The function returns ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RequestFileCom:
"""This class allows supplies methods to handle the request file."""
def file_to_dict(path='current_request.txt'):
"""The function reads the file and return a dict as follow: {key, value}."""
if not os.path.exists(path):
return {}
RequestFileCom.mutex.a... | the_stack_v2_python_sparse | Project/Code/Client/client2/RequestFileCom.py | Maor2871/CodeDup | train | 0 |
5a250a9ec313c3bd3678d44488730090ffa54a43 | [
"super(ProcessRecipeInput, self).__init__('process_recipe_input')\nself.recipe_id = None\nself.forced_nodes = None",
"json_dict = {'recipe_id': self.recipe_id}\nif self.forced_nodes:\n json_dict['forced_nodes'] = convert_forced_nodes_to_v6(self.forced_nodes).get_dict()\nreturn json_dict",
"message = ProcessR... | <|body_start_0|>
super(ProcessRecipeInput, self).__init__('process_recipe_input')
self.recipe_id = None
self.forced_nodes = None
<|end_body_0|>
<|body_start_1|>
json_dict = {'recipe_id': self.recipe_id}
if self.forced_nodes:
json_dict['forced_nodes'] = convert_forced... | Command message that processes the input for a recipes | ProcessRecipeInput | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessRecipeInput:
"""Command message that processes the input for a recipes"""
def __init__(self):
"""Constructor"""
<|body_0|>
def to_json(self):
"""See :meth:`messaging.messages.message.CommandMessage.to_json`"""
<|body_1|>
def from_json(json_dic... | stack_v2_sparse_classes_36k_train_024165 | 4,614 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "See :meth:`messaging.messages.message.CommandMessage.to_json`",
"name": "to_json",
"signature": "def to_json(self)"
},
{
"docstring": "See :meth:`messaging.messages.message.Comm... | 5 | null | Implement the Python class `ProcessRecipeInput` described below.
Class description:
Command message that processes the input for a recipes
Method signatures and docstrings:
- def __init__(self): Constructor
- def to_json(self): See :meth:`messaging.messages.message.CommandMessage.to_json`
- def from_json(json_dict): ... | Implement the Python class `ProcessRecipeInput` described below.
Class description:
Command message that processes the input for a recipes
Method signatures and docstrings:
- def __init__(self): Constructor
- def to_json(self): See :meth:`messaging.messages.message.CommandMessage.to_json`
- def from_json(json_dict): ... | 28618aee07ceed9e4a6eb7b8d0e6f05b31d8fd6b | <|skeleton|>
class ProcessRecipeInput:
"""Command message that processes the input for a recipes"""
def __init__(self):
"""Constructor"""
<|body_0|>
def to_json(self):
"""See :meth:`messaging.messages.message.CommandMessage.to_json`"""
<|body_1|>
def from_json(json_dic... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProcessRecipeInput:
"""Command message that processes the input for a recipes"""
def __init__(self):
"""Constructor"""
super(ProcessRecipeInput, self).__init__('process_recipe_input')
self.recipe_id = None
self.forced_nodes = None
def to_json(self):
"""See :me... | the_stack_v2_python_sparse | scale/recipe/messages/process_recipe_input.py | kfconsultant/scale | train | 0 |
2734a228aad4fffd4d748a1fb02dded9c9b287cd | [
"metadata = deepcopy(cube.metadata)\ncube += 273.15\ncube.metadata = metadata\nreturn cube",
"cube = self.get_cube_from_list(cubes)\ncube.standard_name = 'sea_surface_temperature'\nreturn cubes"
] | <|body_start_0|>
metadata = deepcopy(cube.metadata)
cube += 273.15
cube.metadata = metadata
return cube
<|end_body_0|>
<|body_start_1|>
cube = self.get_cube_from_list(cubes)
cube.standard_name = 'sea_surface_temperature'
return cubes
<|end_body_1|>
| Fixes for tos. | Tos | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tos:
"""Fixes for tos."""
def fix_data(self, cube):
"""Fix data. Fixes discrepancy between declared units and real units Parameters ---------- cube: iris.cube.Cube Returns ------- iris.cube.Cube"""
<|body_0|>
def fix_metadata(self, cubes):
"""Fix metadata. Fixes ... | stack_v2_sparse_classes_36k_train_024166 | 2,948 | permissive | [
{
"docstring": "Fix data. Fixes discrepancy between declared units and real units Parameters ---------- cube: iris.cube.Cube Returns ------- iris.cube.Cube",
"name": "fix_data",
"signature": "def fix_data(self, cube)"
},
{
"docstring": "Fix metadata. Fixes wrong standard_name. Parameters -------... | 2 | null | Implement the Python class `Tos` described below.
Class description:
Fixes for tos.
Method signatures and docstrings:
- def fix_data(self, cube): Fix data. Fixes discrepancy between declared units and real units Parameters ---------- cube: iris.cube.Cube Returns ------- iris.cube.Cube
- def fix_metadata(self, cubes):... | Implement the Python class `Tos` described below.
Class description:
Fixes for tos.
Method signatures and docstrings:
- def fix_data(self, cube): Fix data. Fixes discrepancy between declared units and real units Parameters ---------- cube: iris.cube.Cube Returns ------- iris.cube.Cube
- def fix_metadata(self, cubes):... | d5187438fea2928644cb53ecb26c6adb1e4cc947 | <|skeleton|>
class Tos:
"""Fixes for tos."""
def fix_data(self, cube):
"""Fix data. Fixes discrepancy between declared units and real units Parameters ---------- cube: iris.cube.Cube Returns ------- iris.cube.Cube"""
<|body_0|>
def fix_metadata(self, cubes):
"""Fix metadata. Fixes ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tos:
"""Fixes for tos."""
def fix_data(self, cube):
"""Fix data. Fixes discrepancy between declared units and real units Parameters ---------- cube: iris.cube.Cube Returns ------- iris.cube.Cube"""
metadata = deepcopy(cube.metadata)
cube += 273.15
cube.metadata = metadata
... | the_stack_v2_python_sparse | esmvalcore/cmor/_fixes/cmip5/gfdl_cm2p1.py | ESMValGroup/ESMValCore | train | 41 |
ec07f6fa25e8536bc98f276fcf3f6582056efbc2 | [
"flags.AddParentFlagsToParser(parser)\nparser.add_argument('RECOMMENDATION', type=str, help='Recommendation id which will be marked as active')\nparser.add_argument('--location', metavar='LOCATION', required=True, help='Location')\nparser.add_argument('--recommender', metavar='RECOMMENDER', required=True, help='Rec... | <|body_start_0|>
flags.AddParentFlagsToParser(parser)
parser.add_argument('RECOMMENDATION', type=str, help='Recommendation id which will be marked as active')
parser.add_argument('--location', metavar='LOCATION', required=True, help='Location')
parser.add_argument('--recommender', metava... | Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organization. ## EXAMPLES To mark a recommenation as ACTIVE: $ {command} RECOMMENDATION... | MarkActive | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MarkActive:
"""Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organization. ## EXAMPLES To mark a recommenation... | stack_v2_sparse_classes_36k_train_024167 | 2,733 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "Run 'gcloud recommender recomme... | 2 | stack_v2_sparse_classes_30k_train_000758 | Implement the Python class `MarkActive` described below.
Class description:
Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organizati... | Implement the Python class `MarkActive` described below.
Class description:
Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organizati... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class MarkActive:
"""Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organization. ## EXAMPLES To mark a recommenation... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MarkActive:
"""Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organization. ## EXAMPLES To mark a recommenation as ACTIVE: $... | the_stack_v2_python_sparse | lib/surface/recommender/recommendations/mark_active.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
b1d217c48da1f80ffbbea6749dd6d83afb775db1 | [
"include_inactive = request.args.get('include_inactive', '0') != '0'\nget_users_response = InternalApi().get(url_for('flexmeasures_api_v2_0.get_users', include_inactive=include_inactive))\nusers = [process_internal_api_response(user, make_obj=True) for user in get_users_response.json()]\nreturn render_flexmeasures_... | <|body_start_0|>
include_inactive = request.args.get('include_inactive', '0') != '0'
get_users_response = InternalApi().get(url_for('flexmeasures_api_v2_0.get_users', include_inactive=include_inactive))
users = [process_internal_api_response(user, make_obj=True) for user in get_users_response.js... | UserCrudUI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserCrudUI:
def index(self):
"""/users"""
<|body_0|>
def get(self, id: str):
"""GET from /users/<id>"""
<|body_1|>
def toggle_active(self, id: str):
"""Toggle activation status via /users/toggle_active/<id>"""
<|body_2|>
def reset_pa... | stack_v2_sparse_classes_36k_train_024168 | 4,885 | permissive | [
{
"docstring": "/users",
"name": "index",
"signature": "def index(self)"
},
{
"docstring": "GET from /users/<id>",
"name": "get",
"signature": "def get(self, id: str)"
},
{
"docstring": "Toggle activation status via /users/toggle_active/<id>",
"name": "toggle_active",
"si... | 4 | stack_v2_sparse_classes_30k_train_020559 | Implement the Python class `UserCrudUI` described below.
Class description:
Implement the UserCrudUI class.
Method signatures and docstrings:
- def index(self): /users
- def get(self, id: str): GET from /users/<id>
- def toggle_active(self, id: str): Toggle activation status via /users/toggle_active/<id>
- def reset_... | Implement the Python class `UserCrudUI` described below.
Class description:
Implement the UserCrudUI class.
Method signatures and docstrings:
- def index(self): /users
- def get(self, id: str): GET from /users/<id>
- def toggle_active(self, id: str): Toggle activation status via /users/toggle_active/<id>
- def reset_... | 6ba518bae7e9b8a715b9a05f6fae19f5e4ade791 | <|skeleton|>
class UserCrudUI:
def index(self):
"""/users"""
<|body_0|>
def get(self, id: str):
"""GET from /users/<id>"""
<|body_1|>
def toggle_active(self, id: str):
"""Toggle activation status via /users/toggle_active/<id>"""
<|body_2|>
def reset_pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserCrudUI:
def index(self):
"""/users"""
include_inactive = request.args.get('include_inactive', '0') != '0'
get_users_response = InternalApi().get(url_for('flexmeasures_api_v2_0.get_users', include_inactive=include_inactive))
users = [process_internal_api_response(user, make_... | the_stack_v2_python_sparse | flexmeasures/ui/crud/users.py | meeseeksmachine/flexmeasures | train | 0 | |
873e7a28777a59b3626c9ae980a8ab124615f827 | [
"self.x_driver = driver\nself.name = name\nself.x_elem_id = elem_id",
"logging.info('Determine if ' + self.name + ' is enabled.')\nelement = self.x_driver.find_element(self.x_elem_id[0], self.x_elem_id[1])\nenabled = element.is_enabled()\nlogging.info('Enabled state of ' + self.name + ' is: ' + str(enabled))\nret... | <|body_start_0|>
self.x_driver = driver
self.name = name
self.x_elem_id = elem_id
<|end_body_0|>
<|body_start_1|>
logging.info('Determine if ' + self.name + ' is enabled.')
element = self.x_driver.find_element(self.x_elem_id[0], self.x_elem_id[1])
enabled = element.is_en... | Common base class for al widgets/elements | BaseElement | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseElement:
"""Common base class for al widgets/elements"""
def __init__(self, driver, name, elem_id):
"""Common code for all elements/widgets. :param driver: Interface to Website :param elem_id: Unique ID related to the element :return: None"""
<|body_0|>
def is_enable... | stack_v2_sparse_classes_36k_train_024169 | 1,411 | no_license | [
{
"docstring": "Common code for all elements/widgets. :param driver: Interface to Website :param elem_id: Unique ID related to the element :return: None",
"name": "__init__",
"signature": "def __init__(self, driver, name, elem_id)"
},
{
"docstring": "Determine if the element is enabled. :return:... | 3 | stack_v2_sparse_classes_30k_train_004711 | Implement the Python class `BaseElement` described below.
Class description:
Common base class for al widgets/elements
Method signatures and docstrings:
- def __init__(self, driver, name, elem_id): Common code for all elements/widgets. :param driver: Interface to Website :param elem_id: Unique ID related to the eleme... | Implement the Python class `BaseElement` described below.
Class description:
Common base class for al widgets/elements
Method signatures and docstrings:
- def __init__(self, driver, name, elem_id): Common code for all elements/widgets. :param driver: Interface to Website :param elem_id: Unique ID related to the eleme... | c7ae5cd1c14defdbff57c2ed5e4a447c7799c495 | <|skeleton|>
class BaseElement:
"""Common base class for al widgets/elements"""
def __init__(self, driver, name, elem_id):
"""Common code for all elements/widgets. :param driver: Interface to Website :param elem_id: Unique ID related to the element :return: None"""
<|body_0|>
def is_enable... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseElement:
"""Common base class for al widgets/elements"""
def __init__(self, driver, name, elem_id):
"""Common code for all elements/widgets. :param driver: Interface to Website :param elem_id: Unique ID related to the element :return: None"""
self.x_driver = driver
self.name =... | the_stack_v2_python_sparse | support/common_controls/__base_element.py | chrisaroy/proj_selenium_python_dev | train | 0 |
368f3d65b3dcbbfb9b9ff08b82a8748cb8826381 | [
"super().setUp()\nself.signup(self.CURRICULUM_ADMIN_EMAIL, self.CURRICULUM_ADMIN_USERNAME)\nself.signup(self.ALBERT_EMAIL, self.ALBERT_NAME)\nself.admin_id = self.get_user_id_from_email(self.CURRICULUM_ADMIN_EMAIL)\nself.albert_id = self.get_user_id_from_email(self.ALBERT_EMAIL)\nself.albert = user_services.get_use... | <|body_start_0|>
super().setUp()
self.signup(self.CURRICULUM_ADMIN_EMAIL, self.CURRICULUM_ADMIN_USERNAME)
self.signup(self.ALBERT_EMAIL, self.ALBERT_NAME)
self.admin_id = self.get_user_id_from_email(self.CURRICULUM_ADMIN_EMAIL)
self.albert_id = self.get_user_id_from_email(self.AL... | Test functions for getting displayable recently published exploration summary dicts. | RecentlyPublishedExplorationDisplayableSummariesTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecentlyPublishedExplorationDisplayableSummariesTest:
"""Test functions for getting displayable recently published exploration summary dicts."""
def setUp(self) -> None:
"""Populate the database of explorations and their summaries. The sequence of events is: - (1) Albert creates EXP_... | stack_v2_sparse_classes_36k_train_024170 | 47,358 | permissive | [
{
"docstring": "Populate the database of explorations and their summaries. The sequence of events is: - (1) Albert creates EXP_ID_1. - (2) Albert creates EXP_ID_2. - (3) Albert creates EXP_ID_3. - (4) Albert publishes EXP_ID_1. - (5) Albert publishes EXP_ID_2. - (6) Albert publishes EXP_ID_3. - (7) Admin user i... | 2 | stack_v2_sparse_classes_30k_train_002718 | Implement the Python class `RecentlyPublishedExplorationDisplayableSummariesTest` described below.
Class description:
Test functions for getting displayable recently published exploration summary dicts.
Method signatures and docstrings:
- def setUp(self) -> None: Populate the database of explorations and their summar... | Implement the Python class `RecentlyPublishedExplorationDisplayableSummariesTest` described below.
Class description:
Test functions for getting displayable recently published exploration summary dicts.
Method signatures and docstrings:
- def setUp(self) -> None: Populate the database of explorations and their summar... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class RecentlyPublishedExplorationDisplayableSummariesTest:
"""Test functions for getting displayable recently published exploration summary dicts."""
def setUp(self) -> None:
"""Populate the database of explorations and their summaries. The sequence of events is: - (1) Albert creates EXP_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RecentlyPublishedExplorationDisplayableSummariesTest:
"""Test functions for getting displayable recently published exploration summary dicts."""
def setUp(self) -> None:
"""Populate the database of explorations and their summaries. The sequence of events is: - (1) Albert creates EXP_ID_1. - (2) A... | the_stack_v2_python_sparse | core/domain/summary_services_test.py | oppia/oppia | train | 6,172 |
f33a67fdfde8e4cf4cac95ab408652096b51a5df | [
"id_d = id(d)\nsc = self.manager.displayable_map.get(id_d, None)\nif sc is None:\n d = renpy.easy.displayable(d)\n sc = SpriteCache()\n sc.render = None\n sc.child = d\n sc.st = None\n if d._duplicatable:\n sc.child_copy = d._duplicate(None)\n sc.child_copy._unique()\n else:\n ... | <|body_start_0|>
id_d = id(d)
sc = self.manager.displayable_map.get(id_d, None)
if sc is None:
d = renpy.easy.displayable(d)
sc = SpriteCache()
sc.render = None
sc.child = d
sc.st = None
if d._duplicatable:
s... | :doc: sprites class This represents a sprite that is managed by the SpriteManager. It contains fields that control the placement of the sprite on the screen. Sprites should not be created directly. Instead, they should be created by calling :meth:`SpriteManager.create`. The fields of a sprite object are: `x`, `y` The x... | Sprite | [
"GPL-1.0-or-later",
"LGPL-2.0-or-later",
"LGPL-2.1-or-later",
"IJG",
"WxWindows-exception-3.1",
"Zlib",
"bzip2-1.0.6",
"LicenseRef-scancode-proprietary-license",
"LicenseRef-scancode-other-copyleft",
"BSD-3-Clause",
"Artistic-2.0",
"LGPL-2.1-only",
"Python-2.0",
"LicenseRef-scancode-warran... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sprite:
""":doc: sprites class This represents a sprite that is managed by the SpriteManager. It contains fields that control the placement of the sprite on the screen. Sprites should not be created directly. Instead, they should be created by calling :meth:`SpriteManager.create`. The fields of a... | stack_v2_sparse_classes_36k_train_024171 | 18,129 | permissive | [
{
"docstring": ":doc: sprites method Changes the Displayable associated with this sprite to `d`.",
"name": "set_child",
"signature": "def set_child(self, d)"
},
{
"docstring": ":doc: sprites method Destroys this sprite, preventing it from being displayed and removing it from the SpriteManager.",... | 2 | null | Implement the Python class `Sprite` described below.
Class description:
:doc: sprites class This represents a sprite that is managed by the SpriteManager. It contains fields that control the placement of the sprite on the screen. Sprites should not be created directly. Instead, they should be created by calling :meth:... | Implement the Python class `Sprite` described below.
Class description:
:doc: sprites class This represents a sprite that is managed by the SpriteManager. It contains fields that control the placement of the sprite on the screen. Sprites should not be created directly. Instead, they should be created by calling :meth:... | e365b474e7df3f76ccc0853fd1665f6529a59304 | <|skeleton|>
class Sprite:
""":doc: sprites class This represents a sprite that is managed by the SpriteManager. It contains fields that control the placement of the sprite on the screen. Sprites should not be created directly. Instead, they should be created by calling :meth:`SpriteManager.create`. The fields of a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sprite:
""":doc: sprites class This represents a sprite that is managed by the SpriteManager. It contains fields that control the placement of the sprite on the screen. Sprites should not be created directly. Instead, they should be created by calling :meth:`SpriteManager.create`. The fields of a sprite objec... | the_stack_v2_python_sparse | TEST_PROJET-1.0-pc/renpy/display/particle.py | Dune0lyn/otome | train | 0 |
bf432d82d93968be576231dfed80bdc5018d2a13 | [
"dt_fpaths = list(self.dt_root_fpath.glob('*/per_sweep_annotations_amodal/*.json'))\ngt_fpaths = list(self.gt_root_fpath.glob('*/per_sweep_annotations_amodal/*.json'))\nassert len(dt_fpaths) == len(gt_fpaths)\ndata: DefaultDict[str, np.ndarray] = defaultdict(list)\ncls_to_ninst: DefaultDict[str, int] = defaultdict(... | <|body_start_0|>
dt_fpaths = list(self.dt_root_fpath.glob('*/per_sweep_annotations_amodal/*.json'))
gt_fpaths = list(self.gt_root_fpath.glob('*/per_sweep_annotations_amodal/*.json'))
assert len(dt_fpaths) == len(gt_fpaths)
data: DefaultDict[str, np.ndarray] = defaultdict(list)
cl... | Instantiates a DetectionEvaluator object for evaluation. Args: dt_fpath_root: Path to the folder which contains the detections. gt_fpath_root: Path to the folder which contains the split of logs. figs_fpath: Path to the folder which will contain the output figures. cfg: Detection configuration settings. | DetectionEvaluator | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DetectionEvaluator:
"""Instantiates a DetectionEvaluator object for evaluation. Args: dt_fpath_root: Path to the folder which contains the detections. gt_fpath_root: Path to the folder which contains the split of logs. figs_fpath: Path to the folder which will contain the output figures. cfg: Det... | stack_v2_sparse_classes_36k_train_024172 | 8,609 | permissive | [
{
"docstring": "Evaluate detection output and return metrics. The multiprocessing library is used for parallel assignment between detections and ground truth annotations. Returns: Evaluation metrics of shape (C + 1, K) where C + 1 is the number of classes. plus a row for their means. K refers to the number of e... | 2 | null | Implement the Python class `DetectionEvaluator` described below.
Class description:
Instantiates a DetectionEvaluator object for evaluation. Args: dt_fpath_root: Path to the folder which contains the detections. gt_fpath_root: Path to the folder which contains the split of logs. figs_fpath: Path to the folder which wi... | Implement the Python class `DetectionEvaluator` described below.
Class description:
Instantiates a DetectionEvaluator object for evaluation. Args: dt_fpath_root: Path to the folder which contains the detections. gt_fpath_root: Path to the folder which contains the split of logs. figs_fpath: Path to the folder which wi... | 2e2aed64d4a286821aece806134054c6d6e1d3cb | <|skeleton|>
class DetectionEvaluator:
"""Instantiates a DetectionEvaluator object for evaluation. Args: dt_fpath_root: Path to the folder which contains the detections. gt_fpath_root: Path to the folder which contains the split of logs. figs_fpath: Path to the folder which will contain the output figures. cfg: Det... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DetectionEvaluator:
"""Instantiates a DetectionEvaluator object for evaluation. Args: dt_fpath_root: Path to the folder which contains the detections. gt_fpath_root: Path to the folder which contains the split of logs. figs_fpath: Path to the folder which will contain the output figures. cfg: Detection config... | the_stack_v2_python_sparse | argoverse/evaluation/detection/eval.py | ChenChenGith/argoverse-api-ccuse | train | 1 |
1de468463bf8668cad8b622775669e28a42dd12d | [
"Fiscal = self.env['account.fiscalyear']\nSeq = self.env['ir.sequence']\nfiscalyear_id = self._context.get('fiscalyear_id', False)\nfor rec in self:\n if rec.code:\n continue\n if not fiscalyear_id:\n fiscalyear_id = rec.fiscalyear_id.id or Fiscal.find()\n ctx = {'fiscalyear_id': fiscalyear_i... | <|body_start_0|>
Fiscal = self.env['account.fiscalyear']
Seq = self.env['ir.sequence']
fiscalyear_id = self._context.get('fiscalyear_id', False)
for rec in self:
if rec.code:
continue
if not fiscalyear_id:
fiscalyear_id = rec.fiscal... | ResInvestAsset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResInvestAsset:
def generate_code(self):
"""Generate Asset Code based on context fiscalyear_id"""
<|body_0|>
def _add_name_search_domain(self):
"""only asset not being used in other budget control"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Fisc... | stack_v2_sparse_classes_36k_train_024173 | 1,727 | no_license | [
{
"docstring": "Generate Asset Code based on context fiscalyear_id",
"name": "generate_code",
"signature": "def generate_code(self)"
},
{
"docstring": "only asset not being used in other budget control",
"name": "_add_name_search_domain",
"signature": "def _add_name_search_domain(self)"
... | 2 | null | Implement the Python class `ResInvestAsset` described below.
Class description:
Implement the ResInvestAsset class.
Method signatures and docstrings:
- def generate_code(self): Generate Asset Code based on context fiscalyear_id
- def _add_name_search_domain(self): only asset not being used in other budget control | Implement the Python class `ResInvestAsset` described below.
Class description:
Implement the ResInvestAsset class.
Method signatures and docstrings:
- def generate_code(self): Generate Asset Code based on context fiscalyear_id
- def _add_name_search_domain(self): only asset not being used in other budget control
<|... | e8c21082c187f4639373b29a7a0905d069d770f2 | <|skeleton|>
class ResInvestAsset:
def generate_code(self):
"""Generate Asset Code based on context fiscalyear_id"""
<|body_0|>
def _add_name_search_domain(self):
"""only asset not being used in other budget control"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResInvestAsset:
def generate_code(self):
"""Generate Asset Code based on context fiscalyear_id"""
Fiscal = self.env['account.fiscalyear']
Seq = self.env['ir.sequence']
fiscalyear_id = self._context.get('fiscalyear_id', False)
for rec in self:
if rec.code:
... | the_stack_v2_python_sparse | pabi_budget_plan/models/res_invest_asset.py | pabi2/pb2_addons | train | 6 | |
2c7435e8268949ff0043dbaa385c93202378089e | [
"@lru_cache(None)\ndef f(i, cur_sum):\n if i == len(nums):\n if target == cur_sum:\n return 1\n return 0\n return f(i + 1, cur_sum + nums[i]) + f(i + 1, cur_sum - nums[i])\nreturn f(0, 0)",
"if (sum(nums) + target) % 2 == 1:\n return 0\nt = (sum(nums) + target) // 2\ndp = [[0] * ... | <|body_start_0|>
@lru_cache(None)
def f(i, cur_sum):
if i == len(nums):
if target == cur_sum:
return 1
return 0
return f(i + 1, cur_sum + nums[i]) + f(i + 1, cur_sum - nums[i])
return f(0, 0)
<|end_body_0|>
<|body_start... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findTargetSumWays(self, nums: List[int], target: int) -> int:
"""method 1 recursion + memoize"""
<|body_0|>
def findTargetSumWays2(self, nums: List[int], target: int) -> int:
"""method 2 2D DP"""
<|body_1|>
def findTargetSumWays3(self, nums... | stack_v2_sparse_classes_36k_train_024174 | 2,087 | no_license | [
{
"docstring": "method 1 recursion + memoize",
"name": "findTargetSumWays",
"signature": "def findTargetSumWays(self, nums: List[int], target: int) -> int"
},
{
"docstring": "method 2 2D DP",
"name": "findTargetSumWays2",
"signature": "def findTargetSumWays2(self, nums: List[int], target... | 3 | stack_v2_sparse_classes_30k_train_008535 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTargetSumWays(self, nums: List[int], target: int) -> int: method 1 recursion + memoize
- def findTargetSumWays2(self, nums: List[int], target: int) -> int: method 2 2D DP... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTargetSumWays(self, nums: List[int], target: int) -> int: method 1 recursion + memoize
- def findTargetSumWays2(self, nums: List[int], target: int) -> int: method 2 2D DP... | 3a5649357e0f21cbbc5e238351300cd706d533b3 | <|skeleton|>
class Solution:
def findTargetSumWays(self, nums: List[int], target: int) -> int:
"""method 1 recursion + memoize"""
<|body_0|>
def findTargetSumWays2(self, nums: List[int], target: int) -> int:
"""method 2 2D DP"""
<|body_1|>
def findTargetSumWays3(self, nums... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findTargetSumWays(self, nums: List[int], target: int) -> int:
"""method 1 recursion + memoize"""
@lru_cache(None)
def f(i, cur_sum):
if i == len(nums):
if target == cur_sum:
return 1
return 0
retu... | the_stack_v2_python_sparse | leetcode-py/leetcode494.py | cicihou/LearningProject | train | 0 | |
bd9bb501880bef1c80ebdb23285789fbc0d31007 | [
"if pos < 2 or steps < 1 or start < 1 or (start > pos) or (target < 1) or (target > pos):\n return 0\nreturn self.process_a(pos, start, steps, target)",
"if rest == 0:\n return 1 if cur == target else 0\nif cur == 1:\n return self.process_a(pos, cur + 1, rest - 1, target)\nif cur == pos:\n return self... | <|body_start_0|>
if pos < 2 or steps < 1 or start < 1 or (start > pos) or (target < 1) or (target > pos):
return 0
return self.process_a(pos, start, steps, target)
<|end_body_0|>
<|body_start_1|>
if rest == 0:
return 1 if cur == target else 0
if cur == 1:
... | RobotWalk | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RobotWalk:
def ways_a(self, pos, steps, start, target):
""":param pos: 总共有pos个位置 :param steps: 可以走的步数 :param start: 开始位置 :param target: 目标位置 :return:"""
<|body_0|>
def process_a(self, pos, cur, rest, target):
""":param pos: 总共有pos个位置 :param cur: 当前来到的位置 :param rest: ... | stack_v2_sparse_classes_36k_train_024175 | 4,456 | no_license | [
{
"docstring": ":param pos: 总共有pos个位置 :param steps: 可以走的步数 :param start: 开始位置 :param target: 目标位置 :return:",
"name": "ways_a",
"signature": "def ways_a(self, pos, steps, start, target)"
},
{
"docstring": ":param pos: 总共有pos个位置 :param cur: 当前来到的位置 :param rest: 还剩下的步数 :param target: 目标位置 :return: ... | 5 | stack_v2_sparse_classes_30k_train_012389 | Implement the Python class `RobotWalk` described below.
Class description:
Implement the RobotWalk class.
Method signatures and docstrings:
- def ways_a(self, pos, steps, start, target): :param pos: 总共有pos个位置 :param steps: 可以走的步数 :param start: 开始位置 :param target: 目标位置 :return:
- def process_a(self, pos, cur, rest, ta... | Implement the Python class `RobotWalk` described below.
Class description:
Implement the RobotWalk class.
Method signatures and docstrings:
- def ways_a(self, pos, steps, start, target): :param pos: 总共有pos个位置 :param steps: 可以走的步数 :param start: 开始位置 :param target: 目标位置 :return:
- def process_a(self, pos, cur, rest, ta... | 45c26b4791fc95b19442b909b6744dbe07bf9a56 | <|skeleton|>
class RobotWalk:
def ways_a(self, pos, steps, start, target):
""":param pos: 总共有pos个位置 :param steps: 可以走的步数 :param start: 开始位置 :param target: 目标位置 :return:"""
<|body_0|>
def process_a(self, pos, cur, rest, target):
""":param pos: 总共有pos个位置 :param cur: 当前来到的位置 :param rest: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RobotWalk:
def ways_a(self, pos, steps, start, target):
""":param pos: 总共有pos个位置 :param steps: 可以走的步数 :param start: 开始位置 :param target: 目标位置 :return:"""
if pos < 2 or steps < 1 or start < 1 or (start > pos) or (target < 1) or (target > pos):
return 0
return self.process_a(p... | the_stack_v2_python_sparse | basic/动态规划/机器人走路.py | imlifeilong/MyAlgorithm | train | 0 | |
b8066e3fb1e3ec7236a3cb3027cd872401134acc | [
"self.gateway_url = config.get('gateway_url')\nself.username = config.get('username')\nself.password = config.get('password')\nself.smsc = config.get('smsc')\nself.charset = config.get('charset')\nself.coding = config.get('coding')\nself.sender = config.get('from', '')",
"gateway_params = {'username': self.userna... | <|body_start_0|>
self.gateway_url = config.get('gateway_url')
self.username = config.get('username')
self.password = config.get('password')
self.smsc = config.get('smsc')
self.charset = config.get('charset')
self.coding = config.get('coding')
self.sender = config.... | Kannel Gateway class | KannelGateway | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KannelGateway:
"""Kannel Gateway class"""
def __init__(self, config):
"""initializes the kannel gateway object :param config: The configuration object obtained from the app settings"""
<|body_0|>
def send(self, text, recipient, sender=''):
"""Sends the message to... | stack_v2_sparse_classes_36k_train_024176 | 3,492 | no_license | [
{
"docstring": "initializes the kannel gateway object :param config: The configuration object obtained from the app settings",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Sends the message to the specified recipients using this gateway :param text: Contents o... | 2 | null | Implement the Python class `KannelGateway` described below.
Class description:
Kannel Gateway class
Method signatures and docstrings:
- def __init__(self, config): initializes the kannel gateway object :param config: The configuration object obtained from the app settings
- def send(self, text, recipient, sender=''):... | Implement the Python class `KannelGateway` described below.
Class description:
Kannel Gateway class
Method signatures and docstrings:
- def __init__(self, config): initializes the kannel gateway object :param config: The configuration object obtained from the app settings
- def send(self, text, recipient, sender=''):... | e071b05b6122a756313c561643d343fa4d23b097 | <|skeleton|>
class KannelGateway:
"""Kannel Gateway class"""
def __init__(self, config):
"""initializes the kannel gateway object :param config: The configuration object obtained from the app settings"""
<|body_0|>
def send(self, text, recipient, sender=''):
"""Sends the message to... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KannelGateway:
"""Kannel Gateway class"""
def __init__(self, config):
"""initializes the kannel gateway object :param config: The configuration object obtained from the app settings"""
self.gateway_url = config.get('gateway_url')
self.username = config.get('username')
self... | the_stack_v2_python_sparse | apollo/messaging/outgoing.py | Ismail774403783/apollo | train | 0 |
e44d0d0dd9f43be503e69674f8adb506510a67bf | [
"parser = linux_software_parser.DebianPackagesStatusParser(deb822)\npath = os.path.join(self.base_path, 'dpkg_status')\nwith open(path, 'rb') as data:\n out = list(parser.ParseFile(None, None, data))\nself.assertLen(out, 1)\npackage_list = out[0]\nself.assertLen(package_list.packages, 2)\npackage0 = package_list... | <|body_start_0|>
parser = linux_software_parser.DebianPackagesStatusParser(deb822)
path = os.path.join(self.base_path, 'dpkg_status')
with open(path, 'rb') as data:
out = list(parser.ParseFile(None, None, data))
self.assertLen(out, 1)
package_list = out[0]
sel... | Test parsing of linux software collection. | LinuxSoftwareParserTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinuxSoftwareParserTest:
"""Test parsing of linux software collection."""
def testDebianPackagesStatusParser(self):
"""Test parsing of a status file."""
<|body_0|>
def testDebianPackagesStatusParserBadInput(self):
"""If the status file is broken, fail nicely."""
... | stack_v2_sparse_classes_36k_train_024177 | 1,633 | permissive | [
{
"docstring": "Test parsing of a status file.",
"name": "testDebianPackagesStatusParser",
"signature": "def testDebianPackagesStatusParser(self)"
},
{
"docstring": "If the status file is broken, fail nicely.",
"name": "testDebianPackagesStatusParserBadInput",
"signature": "def testDebia... | 2 | null | Implement the Python class `LinuxSoftwareParserTest` described below.
Class description:
Test parsing of linux software collection.
Method signatures and docstrings:
- def testDebianPackagesStatusParser(self): Test parsing of a status file.
- def testDebianPackagesStatusParserBadInput(self): If the status file is bro... | Implement the Python class `LinuxSoftwareParserTest` described below.
Class description:
Test parsing of linux software collection.
Method signatures and docstrings:
- def testDebianPackagesStatusParser(self): Test parsing of a status file.
- def testDebianPackagesStatusParserBadInput(self): If the status file is bro... | 44c0eb8c938302098ef7efae8cfd6b90bcfbb2d6 | <|skeleton|>
class LinuxSoftwareParserTest:
"""Test parsing of linux software collection."""
def testDebianPackagesStatusParser(self):
"""Test parsing of a status file."""
<|body_0|>
def testDebianPackagesStatusParserBadInput(self):
"""If the status file is broken, fail nicely."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinuxSoftwareParserTest:
"""Test parsing of linux software collection."""
def testDebianPackagesStatusParser(self):
"""Test parsing of a status file."""
parser = linux_software_parser.DebianPackagesStatusParser(deb822)
path = os.path.join(self.base_path, 'dpkg_status')
wit... | the_stack_v2_python_sparse | grr/core/grr_response_core/lib/parsers/linux_software_parser_test.py | google/grr | train | 4,683 |
972b4d292e87e9380d32036e27864d5ad6d31eaf | [
"group = self.context['group']\nuser = data\nmembership = Membership.objects.filter(group=group, user=user)\nif membership.exists():\n raise serializers.ValidationError('User has already been invited to this group.')\nreturn data",
"try:\n invitation = Invitation.objects.get(code=data, group=self.context['g... | <|body_start_0|>
group = self.context['group']
user = data
membership = Membership.objects.filter(group=group, user=user)
if membership.exists():
raise serializers.ValidationError('User has already been invited to this group.')
return data
<|end_body_0|>
<|body_start... | Add member serializer. Handle the addition of a new member to a group. | AddMemberSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddMemberSerializer:
"""Add member serializer. Handle the addition of a new member to a group."""
def validate_user(self, data):
"""Verify user is not already a member."""
<|body_0|>
def validate_invitation_code(self, data):
"""Verify code exists and that it is r... | stack_v2_sparse_classes_36k_train_024178 | 2,279 | no_license | [
{
"docstring": "Verify user is not already a member.",
"name": "validate_user",
"signature": "def validate_user(self, data)"
},
{
"docstring": "Verify code exists and that it is related to the group.",
"name": "validate_invitation_code",
"signature": "def validate_invitation_code(self, d... | 3 | stack_v2_sparse_classes_30k_train_017544 | Implement the Python class `AddMemberSerializer` described below.
Class description:
Add member serializer. Handle the addition of a new member to a group.
Method signatures and docstrings:
- def validate_user(self, data): Verify user is not already a member.
- def validate_invitation_code(self, data): Verify code ex... | Implement the Python class `AddMemberSerializer` described below.
Class description:
Add member serializer. Handle the addition of a new member to a group.
Method signatures and docstrings:
- def validate_user(self, data): Verify user is not already a member.
- def validate_invitation_code(self, data): Verify code ex... | fae5c0b2e388239e2e32a3fbf52aa7cfd48a7cbb | <|skeleton|>
class AddMemberSerializer:
"""Add member serializer. Handle the addition of a new member to a group."""
def validate_user(self, data):
"""Verify user is not already a member."""
<|body_0|>
def validate_invitation_code(self, data):
"""Verify code exists and that it is r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddMemberSerializer:
"""Add member serializer. Handle the addition of a new member to a group."""
def validate_user(self, data):
"""Verify user is not already a member."""
group = self.context['group']
user = data
membership = Membership.objects.filter(group=group, user=us... | the_stack_v2_python_sparse | facebook/app/groups/serializers/memberships.py | ricagome/Api-Facebook-Clone | train | 0 |
12677c6c07c58539c280d64698a3d3df35eb7da9 | [
"self.is_training = is_training\nif not is_training:\n batch_size = 1\n min_dimension = params['min_dimension']\n assert min_dimension % DIVISOR == 0\n self.min_dimension = min_dimension\nelse:\n batch_size = params['batch_size']\n width, height = params['image_size']\n assert height % DIVISOR ... | <|body_start_0|>
self.is_training = is_training
if not is_training:
batch_size = 1
min_dimension = params['min_dimension']
assert min_dimension % DIVISOR == 0
self.min_dimension = min_dimension
else:
batch_size = params['batch_size']
... | Input pipeline for training or evaluating networks for heatmaps regression. | KeypointPipeline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KeypointPipeline:
"""Input pipeline for training or evaluating networks for heatmaps regression."""
def __init__(self, filenames, is_training, params):
"""During the evaluation we resize images keeping aspect ratio. Arguments: filenames: a list of strings, paths to tfrecords files. i... | stack_v2_sparse_classes_36k_train_024179 | 17,983 | permissive | [
{
"docstring": "During the evaluation we resize images keeping aspect ratio. Arguments: filenames: a list of strings, paths to tfrecords files. is_training: a boolean. params: a dict.",
"name": "__init__",
"signature": "def __init__(self, filenames, is_training, params)"
},
{
"docstring": "All h... | 3 | stack_v2_sparse_classes_30k_train_006351 | Implement the Python class `KeypointPipeline` described below.
Class description:
Input pipeline for training or evaluating networks for heatmaps regression.
Method signatures and docstrings:
- def __init__(self, filenames, is_training, params): During the evaluation we resize images keeping aspect ratio. Arguments: ... | Implement the Python class `KeypointPipeline` described below.
Class description:
Input pipeline for training or evaluating networks for heatmaps regression.
Method signatures and docstrings:
- def __init__(self, filenames, is_training, params): During the evaluation we resize images keeping aspect ratio. Arguments: ... | 0a509a6f217e84342e54219e0ca8d2e4052127e9 | <|skeleton|>
class KeypointPipeline:
"""Input pipeline for training or evaluating networks for heatmaps regression."""
def __init__(self, filenames, is_training, params):
"""During the evaluation we resize images keeping aspect ratio. Arguments: filenames: a list of strings, paths to tfrecords files. i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KeypointPipeline:
"""Input pipeline for training or evaluating networks for heatmaps regression."""
def __init__(self, filenames, is_training, params):
"""During the evaluation we resize images keeping aspect ratio. Arguments: filenames: a list of strings, paths to tfrecords files. is_training: a... | the_stack_v2_python_sparse | detector/input_pipeline/keypoints_detector_pipeline.py | TropComplique/MultiPoseNet | train | 12 |
179059de3a08256bcbca884f8cb24c47066e7ea0 | [
"from GoogleDrive import files_list_command\nwith open('test_data/files_list_response.json', encoding='utf-8') as data:\n mock_response = json.load(data)\nmocker_http_request.return_value = mock_response\nargs = {'use_domain_admin_access': True}\nresult = files_list_command(gsuite_client, args)\nassert 'GoogleDr... | <|body_start_0|>
from GoogleDrive import files_list_command
with open('test_data/files_list_response.json', encoding='utf-8') as data:
mock_response = json.load(data)
mocker_http_request.return_value = mock_response
args = {'use_domain_admin_access': True}
result = fi... | TestFileMethods | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestFileMethods:
def test_files_list_command_success(self, mocker_http_request, gsuite_client):
"""Scenario: For google-drive-files-list command successful run. Given: - Command args. When: - Calling google-drive-files-list command with the parameters provided. Then: - Ensure command's r... | stack_v2_sparse_classes_36k_train_024180 | 33,071 | permissive | [
{
"docstring": "Scenario: For google-drive-files-list command successful run. Given: - Command args. When: - Calling google-drive-files-list command with the parameters provided. Then: - Ensure command's raw_response, outputs should be as expected.",
"name": "test_files_list_command_success",
"signature... | 4 | stack_v2_sparse_classes_30k_train_009729 | Implement the Python class `TestFileMethods` described below.
Class description:
Implement the TestFileMethods class.
Method signatures and docstrings:
- def test_files_list_command_success(self, mocker_http_request, gsuite_client): Scenario: For google-drive-files-list command successful run. Given: - Command args. ... | Implement the Python class `TestFileMethods` described below.
Class description:
Implement the TestFileMethods class.
Method signatures and docstrings:
- def test_files_list_command_success(self, mocker_http_request, gsuite_client): Scenario: For google-drive-files-list command successful run. Given: - Command args. ... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class TestFileMethods:
def test_files_list_command_success(self, mocker_http_request, gsuite_client):
"""Scenario: For google-drive-files-list command successful run. Given: - Command args. When: - Calling google-drive-files-list command with the parameters provided. Then: - Ensure command's r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestFileMethods:
def test_files_list_command_success(self, mocker_http_request, gsuite_client):
"""Scenario: For google-drive-files-list command successful run. Given: - Command args. When: - Calling google-drive-files-list command with the parameters provided. Then: - Ensure command's raw_response, o... | the_stack_v2_python_sparse | Packs/GoogleDrive/Integrations/GoogleDrive/GoogleDrive_test.py | demisto/content | train | 1,023 | |
a7f2cfc2a00feec3a4656898afc46df083090709 | [
"self.clerk = clerk\nself.fID = fID\nself.fclass = fclass",
"if name == 'ID' or isinstance(getattr(stub.__class__, name), linkset):\n pass\nelse:\n stub.removeInjector(self.inject)\n stub.removeObserver(self.inject)\n if hasattr(stub.private, 'isStub'):\n pri = stub.private\n raw = self.... | <|body_start_0|>
self.clerk = clerk
self.fID = fID
self.fclass = fclass
<|end_body_0|>
<|body_start_1|>
if name == 'ID' or isinstance(getattr(stub.__class__, name), linkset):
pass
else:
stub.removeInjector(self.inject)
stub.removeObserver(self... | LinkInjector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkInjector:
def __init__(self, clerk, fclass, fID):
"""Registers a callback so that when getattr(box, atr) is called, the object of box.atr's type with given ID is loaded from sto and injected into box. In other words, this provides lazy loading for strongboxen."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_024181 | 20,272 | no_license | [
{
"docstring": "Registers a callback so that when getattr(box, atr) is called, the object of box.atr's type with given ID is loaded from sto and injected into box. In other words, this provides lazy loading for strongboxen.",
"name": "__init__",
"signature": "def __init__(self, clerk, fclass, fID)"
},... | 2 | stack_v2_sparse_classes_30k_train_007266 | Implement the Python class `LinkInjector` described below.
Class description:
Implement the LinkInjector class.
Method signatures and docstrings:
- def __init__(self, clerk, fclass, fID): Registers a callback so that when getattr(box, atr) is called, the object of box.atr's type with given ID is loaded from sto and i... | Implement the Python class `LinkInjector` described below.
Class description:
Implement the LinkInjector class.
Method signatures and docstrings:
- def __init__(self, clerk, fclass, fID): Registers a callback so that when getattr(box, atr) is called, the object of box.atr's type with given ID is loaded from sto and i... | 1ea55a754a7568b8df2bab297a8036c0b3a671e0 | <|skeleton|>
class LinkInjector:
def __init__(self, clerk, fclass, fID):
"""Registers a callback so that when getattr(box, atr) is called, the object of box.atr's type with given ID is loaded from sto and injected into box. In other words, this provides lazy loading for strongboxen."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkInjector:
def __init__(self, clerk, fclass, fID):
"""Registers a callback so that when getattr(box, atr) is called, the object of box.atr's type with given ID is loaded from sto and injected into box. In other words, this provides lazy loading for strongboxen."""
self.clerk = clerk
... | the_stack_v2_python_sparse | code/clerks.py | tangentstorm/workshop | train | 0 | |
457892631cd8804366663db4c350ca395b81253f | [
"LDC_Info.__init__(self)\nself.setTitle(self.name)\nself.status = compat_res[0]\nui = Ui_soundFrame()\nui.setupUi(self.frame)\nself.__fill_frame(ui, info_res, compat_res, diag_res)",
"ui.productLineEdit.setText(QtGui.QApplication.translate('soundFrame', self._check_invalid_values(info_res.product[1]), None, QtGui... | <|body_start_0|>
LDC_Info.__init__(self)
self.setTitle(self.name)
self.status = compat_res[0]
ui = Ui_soundFrame()
ui.setupUi(self.frame)
self.__fill_frame(ui, info_res, compat_res, diag_res)
<|end_body_0|>
<|body_start_1|>
ui.productLineEdit.setText(QtGui.QAppli... | Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de som. | GUISound | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GUISound:
"""Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de som."""
def __init__(self, info_res, compat_res, diag_res):
"""Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResSound) compat_res... | stack_v2_sparse_classes_36k_train_024182 | 3,403 | no_license | [
{
"docstring": "Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResSound) compat_res -- Lista com as tuples de resultados de compatibilidade [(True, msg)] diag_res -- Lista com os resultados do diagnóstico (lista de 'DaigResSound')",
"name": "__init__",
"signature"... | 2 | null | Implement the Python class `GUISound` described below.
Class description:
Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de som.
Method signatures and docstrings:
- def __init__(self, info_res, compat_res, diag_res): Construtor Parâmetros: info_res -- lista com os re... | Implement the Python class `GUISound` described below.
Class description:
Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de som.
Method signatures and docstrings:
- def __init__(self, info_res, compat_res, diag_res): Construtor Parâmetros: info_res -- lista com os re... | bda0c2c8977dd1246339f1f0f4718d29e8795f21 | <|skeleton|>
class GUISound:
"""Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de som."""
def __init__(self, info_res, compat_res, diag_res):
"""Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResSound) compat_res... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GUISound:
"""Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de som."""
def __init__(self, info_res, compat_res, diag_res):
"""Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResSound) compat_res -- Lista com... | the_stack_v2_python_sparse | src/libs/sound/gui_sound.py | adrianomelo/ldc-desktop | train | 1 |
9fafc61f6afbe3ccff2e5c4383b9f0508327e8a1 | [
"super(JobWorker, self).__init__()\nself.cb = cb\nself.sensor_id = sensor_id\nself.job_queue = Queue()\nself.lr_session = None\nself.result_queue = result_queue",
"try:\n self.lr_session = self.cb.live_response.request_session(self.sensor_id)\n self.result_queue.put(WorkerStatus(self.sensor_id, status='read... | <|body_start_0|>
super(JobWorker, self).__init__()
self.cb = cb
self.sensor_id = sensor_id
self.job_queue = Queue()
self.lr_session = None
self.result_queue = result_queue
<|end_body_0|>
<|body_start_1|>
try:
self.lr_session = self.cb.live_response.re... | Thread object that executes individual Live Response jobs. | JobWorker | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobWorker:
"""Thread object that executes individual Live Response jobs."""
def __init__(self, cb, sensor_id, result_queue):
"""Initialize the JobWorker. Args: cb (BaseAPI): The CBAPI object reference. sensor_id (int): The ID of the sensor being used. result_queue (Queue): The queue ... | stack_v2_sparse_classes_36k_train_024183 | 44,074 | permissive | [
{
"docstring": "Initialize the JobWorker. Args: cb (BaseAPI): The CBAPI object reference. sensor_id (int): The ID of the sensor being used. result_queue (Queue): The queue where results are placed.",
"name": "__init__",
"signature": "def __init__(self, cb, sensor_id, result_queue)"
},
{
"docstri... | 3 | stack_v2_sparse_classes_30k_train_007855 | Implement the Python class `JobWorker` described below.
Class description:
Thread object that executes individual Live Response jobs.
Method signatures and docstrings:
- def __init__(self, cb, sensor_id, result_queue): Initialize the JobWorker. Args: cb (BaseAPI): The CBAPI object reference. sensor_id (int): The ID o... | Implement the Python class `JobWorker` described below.
Class description:
Thread object that executes individual Live Response jobs.
Method signatures and docstrings:
- def __init__(self, cb, sensor_id, result_queue): Initialize the JobWorker. Args: cb (BaseAPI): The CBAPI object reference. sensor_id (int): The ID o... | 32dd08d2185f7113f87834002e720db31c8c910e | <|skeleton|>
class JobWorker:
"""Thread object that executes individual Live Response jobs."""
def __init__(self, cb, sensor_id, result_queue):
"""Initialize the JobWorker. Args: cb (BaseAPI): The CBAPI object reference. sensor_id (int): The ID of the sensor being used. result_queue (Queue): The queue ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobWorker:
"""Thread object that executes individual Live Response jobs."""
def __init__(self, cb, sensor_id, result_queue):
"""Initialize the JobWorker. Args: cb (BaseAPI): The CBAPI object reference. sensor_id (int): The ID of the sensor being used. result_queue (Queue): The queue where results... | the_stack_v2_python_sparse | src/cbapi/live_response_api.py | carbonblack/cbapi-python | train | 158 |
03ffbfa0de3ec63b03a1a7b9f9545ab078637dec | [
"def adjmul(arr, i):\n ret = arr[i]\n if 0 < i:\n ret *= arr[i - 1]\n if i < len(arr) - 1:\n ret *= arr[i + 1]\n return ret\n\n@lru_cache(None)\ndef dp(nums):\n ret = 0\n for i in range(len(nums)):\n cur = adjmul(nums, i)\n sub = dp(tuple(nums[:i] + nums[i + 1:]))\n ... | <|body_start_0|>
def adjmul(arr, i):
ret = arr[i]
if 0 < i:
ret *= arr[i - 1]
if i < len(arr) - 1:
ret *= arr[i + 1]
return ret
@lru_cache(None)
def dp(nums):
ret = 0
for i in range(len(nums)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxCoins(self, nums: List[int]) -> int:
"""Brute-force TLE"""
<|body_0|>
def maxCoins(self, nums: List[int]) -> int:
"""Top-down DP, Recursive Time complexity: O(n^3) Space complexity: O(n^2)"""
<|body_1|>
def maxCoins(self, nums: List[int]... | stack_v2_sparse_classes_36k_train_024184 | 3,846 | no_license | [
{
"docstring": "Brute-force TLE",
"name": "maxCoins",
"signature": "def maxCoins(self, nums: List[int]) -> int"
},
{
"docstring": "Top-down DP, Recursive Time complexity: O(n^3) Space complexity: O(n^2)",
"name": "maxCoins",
"signature": "def maxCoins(self, nums: List[int]) -> int"
},
... | 4 | stack_v2_sparse_classes_30k_train_006113 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxCoins(self, nums: List[int]) -> int: Brute-force TLE
- def maxCoins(self, nums: List[int]) -> int: Top-down DP, Recursive Time complexity: O(n^3) Space complexity: O(n^2)
... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxCoins(self, nums: List[int]) -> int: Brute-force TLE
- def maxCoins(self, nums: List[int]) -> int: Top-down DP, Recursive Time complexity: O(n^3) Space complexity: O(n^2)
... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def maxCoins(self, nums: List[int]) -> int:
"""Brute-force TLE"""
<|body_0|>
def maxCoins(self, nums: List[int]) -> int:
"""Top-down DP, Recursive Time complexity: O(n^3) Space complexity: O(n^2)"""
<|body_1|>
def maxCoins(self, nums: List[int]... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxCoins(self, nums: List[int]) -> int:
"""Brute-force TLE"""
def adjmul(arr, i):
ret = arr[i]
if 0 < i:
ret *= arr[i - 1]
if i < len(arr) - 1:
ret *= arr[i + 1]
return ret
@lru_cache(None)
... | the_stack_v2_python_sparse | leetcode/solved/312_Burst_Balloons/solution.py | sungminoh/algorithms | train | 0 | |
34c0d5018b622d6ad02c691db28797eca484d3fa | [
"super(TwoLayerNet, self).__init__()\nself.linear1 = torch.nn.Linear(D_in, H)\nself.linear2 = torch.nn.Linear(H, D_out)",
"h_relu = self.linear1(x).clamp(min=0)\ny_pred = self.linear2(h_relu)\nreturn y_pred"
] | <|body_start_0|>
super(TwoLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
<|end_body_0|>
<|body_start_1|>
h_relu = self.linear1(x).clamp(min=0)
y_pred = self.linear2(h_relu)
return y_pred
<|end_body_1|>
| TwoLayerNet | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化了两个nn.Linear模块， 并将它们赋值为成员变量。"""
<|body_0|>
def forward(self, x):
"""在前馈函数中，我们接受一个输入数据的 Tensor， 并且我们必须返回输出数据的Tensor。在这里 我们可以使用造函数中已经定义好的Modules和 其他任意的Tensors上的算子来完成前馈函数的任务逻辑。"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_024185 | 2,326 | permissive | [
{
"docstring": "在构造函数中，我们实例化了两个nn.Linear模块， 并将它们赋值为成员变量。",
"name": "__init__",
"signature": "def __init__(self, D_in, H, D_out)"
},
{
"docstring": "在前馈函数中，我们接受一个输入数据的 Tensor， 并且我们必须返回输出数据的Tensor。在这里 我们可以使用造函数中已经定义好的Modules和 其他任意的Tensors上的算子来完成前馈函数的任务逻辑。",
"name": "forward",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_011734 | Implement the Python class `TwoLayerNet` described below.
Class description:
Implement the TwoLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们实例化了两个nn.Linear模块， 并将它们赋值为成员变量。
- def forward(self, x): 在前馈函数中，我们接受一个输入数据的 Tensor， 并且我们必须返回输出数据的Tensor。在这里 我们可以使用造函数中已经定义好的Modu... | Implement the Python class `TwoLayerNet` described below.
Class description:
Implement the TwoLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们实例化了两个nn.Linear模块， 并将它们赋值为成员变量。
- def forward(self, x): 在前馈函数中，我们接受一个输入数据的 Tensor， 并且我们必须返回输出数据的Tensor。在这里 我们可以使用造函数中已经定义好的Modu... | 631b817d2e98f351d1173b620d15c4a5efed11da | <|skeleton|>
class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化了两个nn.Linear模块， 并将它们赋值为成员变量。"""
<|body_0|>
def forward(self, x):
"""在前馈函数中，我们接受一个输入数据的 Tensor， 并且我们必须返回输出数据的Tensor。在这里 我们可以使用造函数中已经定义好的Modules和 其他任意的Tensors上的算子来完成前馈函数的任务逻辑。"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化了两个nn.Linear模块， 并将它们赋值为成员变量。"""
super(TwoLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
def forward(self, x):
"""在前馈函数中，我们接受一个输入数据的 Tensor， ... | the_stack_v2_python_sparse | build/_downloads/2e3e83652169c85c0c0972d072ffa8a2/two_layer_net_module.py | ScorpioDoctor/antares02 | train | 0 | |
2bcdf18d379125b37f40b408c478e927f4fea4e1 | [
"if fields is None:\n self._fields = []\nelse:\n self._fields = fields\nself.byte_order = byte_order",
"current_offset = offset\nfor field_name, field_size in self._fields:\n value = int.from_bytes(data[current_offset:current_offset + field_size], byteorder=self.byte_order)\n setattr(self, field_name,... | <|body_start_0|>
if fields is None:
self._fields = []
else:
self._fields = fields
self.byte_order = byte_order
<|end_body_0|>
<|body_start_1|>
current_offset = offset
for field_name, field_size in self._fields:
value = int.from_bytes(data[curr... | Base class for ELF headers. Provides methods for populating fields. | ElfEntry | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElfEntry:
"""Base class for ELF headers. Provides methods for populating fields."""
def __init__(self, byte_order, fields=None):
"""ElfEntry constructor. Args: byte_order: str. Either 'little' for little endian or 'big' for big endian. fields: List[Tuple[str, int]]. An ordered list o... | stack_v2_sparse_classes_36k_train_024186 | 14,032 | permissive | [
{
"docstring": "ElfEntry constructor. Args: byte_order: str. Either 'little' for little endian or 'big' for big endian. fields: List[Tuple[str, int]]. An ordered list of pairs of (attribute name, size in bytes). This list will be used for parsing data and automatically setting up those fields.",
"name": "__... | 6 | stack_v2_sparse_classes_30k_train_020693 | Implement the Python class `ElfEntry` described below.
Class description:
Base class for ELF headers. Provides methods for populating fields.
Method signatures and docstrings:
- def __init__(self, byte_order, fields=None): ElfEntry constructor. Args: byte_order: str. Either 'little' for little endian or 'big' for big... | Implement the Python class `ElfEntry` described below.
Class description:
Base class for ELF headers. Provides methods for populating fields.
Method signatures and docstrings:
- def __init__(self, byte_order, fields=None): ElfEntry constructor. Args: byte_order: str. Either 'little' for little endian or 'big' for big... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class ElfEntry:
"""Base class for ELF headers. Provides methods for populating fields."""
def __init__(self, byte_order, fields=None):
"""ElfEntry constructor. Args: byte_order: str. Either 'little' for little endian or 'big' for big endian. fields: List[Tuple[str, int]]. An ordered list o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElfEntry:
"""Base class for ELF headers. Provides methods for populating fields."""
def __init__(self, byte_order, fields=None):
"""ElfEntry constructor. Args: byte_order: str. Either 'little' for little endian or 'big' for big endian. fields: List[Tuple[str, int]]. An ordered list of pairs of (a... | the_stack_v2_python_sparse | tools/android/elf_compression/elf_headers.py | chromium/chromium | train | 17,408 |
ebc21112efdc108a7177ec13cc7119eb8c5e5ebd | [
"super(Mpstat, self).__init__(connection=connection, prompt=prompt, newline_chars=newline_chars, runner=runner)\nself.options = options\nself.ret_required = False\nself.current_ret['cpu'] = dict()",
"cmd = 'mpstat'\nif self.options:\n cmd = '{} {}'.format(cmd, self.options)\nreturn cmd",
"if is_full_line:\n ... | <|body_start_0|>
super(Mpstat, self).__init__(connection=connection, prompt=prompt, newline_chars=newline_chars, runner=runner)
self.options = options
self.ret_required = False
self.current_ret['cpu'] = dict()
<|end_body_0|>
<|body_start_1|>
cmd = 'mpstat'
if self.option... | Unix mpstat command | Mpstat | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mpstat:
"""Unix mpstat command"""
def __init__(self, connection, options=None, prompt=None, newline_chars=None, runner=None):
"""Unix mpstat command. :param connection: moler connection to device, terminal when command is executed. :param options: mpstat command options. :param promp... | stack_v2_sparse_classes_36k_train_024187 | 5,652 | permissive | [
{
"docstring": "Unix mpstat command. :param connection: moler connection to device, terminal when command is executed. :param options: mpstat command options. :param prompt: prompt on system where command is executed. :param newline_chars: characters to split lines. :param runner: Runner to run command.",
"... | 4 | null | Implement the Python class `Mpstat` described below.
Class description:
Unix mpstat command
Method signatures and docstrings:
- def __init__(self, connection, options=None, prompt=None, newline_chars=None, runner=None): Unix mpstat command. :param connection: moler connection to device, terminal when command is execu... | Implement the Python class `Mpstat` described below.
Class description:
Unix mpstat command
Method signatures and docstrings:
- def __init__(self, connection, options=None, prompt=None, newline_chars=None, runner=None): Unix mpstat command. :param connection: moler connection to device, terminal when command is execu... | 5a7bb06807b6e0124c77040367d0c20f42849a4c | <|skeleton|>
class Mpstat:
"""Unix mpstat command"""
def __init__(self, connection, options=None, prompt=None, newline_chars=None, runner=None):
"""Unix mpstat command. :param connection: moler connection to device, terminal when command is executed. :param options: mpstat command options. :param promp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Mpstat:
"""Unix mpstat command"""
def __init__(self, connection, options=None, prompt=None, newline_chars=None, runner=None):
"""Unix mpstat command. :param connection: moler connection to device, terminal when command is executed. :param options: mpstat command options. :param prompt: prompt on ... | the_stack_v2_python_sparse | moler/cmd/unix/mpstat.py | nokia/moler | train | 60 |
8243dc62af7c2886b31ace2716aedf2f78dec7e2 | [
"self.Wh = np.random.normal(size=(i + h, h))\nself.bh = np.zeros((1, h))\nself.Wy = np.random.normal(size=(h, o))\nself.by = np.zeros((1, o))",
"X = np.concatenate((h_prev, x_t), axis=1)\nh_next = np.tanh(np.matmul(X, self.Wh) + self.bh)\nz = np.matmul(h_next, self.Wy) + self.by\ny = np.exp(z) / np.sum(np.exp(z),... | <|body_start_0|>
self.Wh = np.random.normal(size=(i + h, h))
self.bh = np.zeros((1, h))
self.Wy = np.random.normal(size=(h, o))
self.by = np.zeros((1, o))
<|end_body_0|>
<|body_start_1|>
X = np.concatenate((h_prev, x_t), axis=1)
h_next = np.tanh(np.matmul(X, self.Wh) + s... | RNNCell class | RNNCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNCell:
"""RNNCell class"""
def __init__(self, i, h, o):
"""Initializer."""
<|body_0|>
def forward(self, h_prev, x_t):
"""performs forward propagation for one time step. Args: h_prev: (numpy.ndarray) contains the data input for the cell. x_t: (numpy.ndarray) con... | stack_v2_sparse_classes_36k_train_024188 | 986 | no_license | [
{
"docstring": "Initializer.",
"name": "__init__",
"signature": "def __init__(self, i, h, o)"
},
{
"docstring": "performs forward propagation for one time step. Args: h_prev: (numpy.ndarray) contains the data input for the cell. x_t: (numpy.ndarray) containing the previous hidden state. Returns:... | 2 | null | Implement the Python class `RNNCell` described below.
Class description:
RNNCell class
Method signatures and docstrings:
- def __init__(self, i, h, o): Initializer.
- def forward(self, h_prev, x_t): performs forward propagation for one time step. Args: h_prev: (numpy.ndarray) contains the data input for the cell. x_t... | Implement the Python class `RNNCell` described below.
Class description:
RNNCell class
Method signatures and docstrings:
- def __init__(self, i, h, o): Initializer.
- def forward(self, h_prev, x_t): performs forward propagation for one time step. Args: h_prev: (numpy.ndarray) contains the data input for the cell. x_t... | 75274394adb52d740f6cd4000cc00bbde44b9b72 | <|skeleton|>
class RNNCell:
"""RNNCell class"""
def __init__(self, i, h, o):
"""Initializer."""
<|body_0|>
def forward(self, h_prev, x_t):
"""performs forward propagation for one time step. Args: h_prev: (numpy.ndarray) contains the data input for the cell. x_t: (numpy.ndarray) con... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNCell:
"""RNNCell class"""
def __init__(self, i, h, o):
"""Initializer."""
self.Wh = np.random.normal(size=(i + h, h))
self.bh = np.zeros((1, h))
self.Wy = np.random.normal(size=(h, o))
self.by = np.zeros((1, o))
def forward(self, h_prev, x_t):
"""pe... | the_stack_v2_python_sparse | supervised_learning/0x0D-RNNs/0-rnn_cell.py | jdarangop/holbertonschool-machine_learning | train | 2 |
ff2131a0364047d8bb38793ebf1ef585e4d6afc8 | [
"self.pipeline_type = pipeline_type\nself.project = project\nself.location = location\nself.gcp_resources = gcp_resources\nself.client_options = client_options.ClientOptions(api_endpoint=location + '-aiplatform.googleapis.com')\nself.client_info = gapic_v1.client_info.ClientInfo(user_agent='google-cloud-pipeline-co... | <|body_start_0|>
self.pipeline_type = pipeline_type
self.project = project
self.location = location
self.gcp_resources = gcp_resources
self.client_options = client_options.ClientOptions(api_endpoint=location + '-aiplatform.googleapis.com')
self.client_info = gapic_v1.clie... | Common module for creating and polling pipelines on the Vertex Platform. | PipelineRemoteRunner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PipelineRemoteRunner:
"""Common module for creating and polling pipelines on the Vertex Platform."""
def __init__(self, pipeline_type: str, project: str, location: str, gcp_resources: str):
"""Initializes a pipeline client and other common attributes."""
<|body_0|>
def c... | stack_v2_sparse_classes_36k_train_024189 | 10,315 | permissive | [
{
"docstring": "Initializes a pipeline client and other common attributes.",
"name": "__init__",
"signature": "def __init__(self, pipeline_type: str, project: str, location: str, gcp_resources: str)"
},
{
"docstring": "Checks if the pipeline already exists. Returns: The pipeline name if the pipe... | 5 | null | Implement the Python class `PipelineRemoteRunner` described below.
Class description:
Common module for creating and polling pipelines on the Vertex Platform.
Method signatures and docstrings:
- def __init__(self, pipeline_type: str, project: str, location: str, gcp_resources: str): Initializes a pipeline client and ... | Implement the Python class `PipelineRemoteRunner` described below.
Class description:
Common module for creating and polling pipelines on the Vertex Platform.
Method signatures and docstrings:
- def __init__(self, pipeline_type: str, project: str, location: str, gcp_resources: str): Initializes a pipeline client and ... | 3fb199658f68e7debf4906d9ce32a9a307e39243 | <|skeleton|>
class PipelineRemoteRunner:
"""Common module for creating and polling pipelines on the Vertex Platform."""
def __init__(self, pipeline_type: str, project: str, location: str, gcp_resources: str):
"""Initializes a pipeline client and other common attributes."""
<|body_0|>
def c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PipelineRemoteRunner:
"""Common module for creating and polling pipelines on the Vertex Platform."""
def __init__(self, pipeline_type: str, project: str, location: str, gcp_resources: str):
"""Initializes a pipeline client and other common attributes."""
self.pipeline_type = pipeline_type... | the_stack_v2_python_sparse | components/google-cloud/google_cloud_pipeline_components/container/v1/gcp_launcher/pipeline_remote_runner.py | kubeflow/pipelines | train | 3,434 |
4938dcbf091290061db6406f50ab802edf3959a6 | [
"def search(node, total, current, output):\n if node and (not node.left) and (not node.right) and (total == node.val):\n output.append(current + [node.val])\n elif node:\n current.append(node.val)\n search(node.left, total - node.val, current, output)\n search(node.right, total - n... | <|body_start_0|>
def search(node, total, current, output):
if node and (not node.left) and (not node.right) and (total == node.val):
output.append(current + [node.val])
elif node:
current.append(node.val)
search(node.left, total - node.val,... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: List[List[int]]"""
<|body_0|>
def pathSum_verbose(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_024190 | 2,451 | no_license | [
{
"docstring": ":type root: TreeNode :type sum: int :rtype: List[List[int]]",
"name": "pathSum",
"signature": "def pathSum(self, root, sum)"
},
{
"docstring": ":type root: TreeNode :type sum: int :rtype: List[List[int]]",
"name": "pathSum_verbose",
"signature": "def pathSum_verbose(self,... | 2 | stack_v2_sparse_classes_30k_test_001163 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: List[List[int]]
- def pathSum_verbose(self, root, sum): :type root: TreeNode :type sum: int :rtype: List... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: List[List[int]]
- def pathSum_verbose(self, root, sum): :type root: TreeNode :type sum: int :rtype: List... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: List[List[int]]"""
<|body_0|>
def pathSum_verbose(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: List[List[int]]"""
def search(node, total, current, output):
if node and (not node.left) and (not node.right) and (total == node.val):
output.append(current + [node.val])
... | the_stack_v2_python_sparse | src/lt_113.py | oxhead/CodingYourWay | train | 0 | |
da84de39b7319616398549d32867c631cda8aa37 | [
"verify_records = VerifyCode.objects.filter(mobile=self.initial_data['username']).order_by('-add_time')\nif verify_records:\n if now() - verify_records[0].add_time > timedelta(hours=0, minutes=1, seconds=0):\n raise serializers.ValidationError('验证码过期')\n if verify_records[0].code != code:\n rais... | <|body_start_0|>
verify_records = VerifyCode.objects.filter(mobile=self.initial_data['username']).order_by('-add_time')
if verify_records:
if now() - verify_records[0].add_time > timedelta(hours=0, minutes=1, seconds=0):
raise serializers.ValidationError('验证码过期')
... | 这个例子比较特殊应为使用了ModelSerializer,用户提交了多余code的字段，也就是该字段没有出现在Model中 | UserRegSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRegSerializer:
"""这个例子比较特殊应为使用了ModelSerializer,用户提交了多余code的字段，也就是该字段没有出现在Model中"""
def validate_code(self, code):
"""验证单个字段， 可以选择是否返回该字段,此处不需要返回，应为user数据表中没有这个字段"""
<|body_0|>
def validate(self, attrs):
"""1. 可以取到所有字段，验证所有字段， 并返回字段 2. 可以按需添加和减少保存到model的字段 3. ... | stack_v2_sparse_classes_36k_train_024191 | 5,055 | no_license | [
{
"docstring": "验证单个字段， 可以选择是否返回该字段,此处不需要返回，应为user数据表中没有这个字段",
"name": "validate_code",
"signature": "def validate_code(self, code)"
},
{
"docstring": "1. 可以取到所有字段，验证所有字段， 并返回字段 2. 可以按需添加和减少保存到model的字段 3. 可以进行字段间的联合验证 4. 验证顺序，先验证单独的后验证联合的",
"name": "validate",
"signature": "def validate(... | 2 | stack_v2_sparse_classes_30k_train_000828 | Implement the Python class `UserRegSerializer` described below.
Class description:
这个例子比较特殊应为使用了ModelSerializer,用户提交了多余code的字段，也就是该字段没有出现在Model中
Method signatures and docstrings:
- def validate_code(self, code): 验证单个字段， 可以选择是否返回该字段,此处不需要返回，应为user数据表中没有这个字段
- def validate(self, attrs): 1. 可以取到所有字段，验证所有字段， 并返回字段 2. 可以按... | Implement the Python class `UserRegSerializer` described below.
Class description:
这个例子比较特殊应为使用了ModelSerializer,用户提交了多余code的字段，也就是该字段没有出现在Model中
Method signatures and docstrings:
- def validate_code(self, code): 验证单个字段， 可以选择是否返回该字段,此处不需要返回，应为user数据表中没有这个字段
- def validate(self, attrs): 1. 可以取到所有字段，验证所有字段， 并返回字段 2. 可以按... | 837fcae8fbbe4d0b8a665666eb6d81d85a1b205f | <|skeleton|>
class UserRegSerializer:
"""这个例子比较特殊应为使用了ModelSerializer,用户提交了多余code的字段，也就是该字段没有出现在Model中"""
def validate_code(self, code):
"""验证单个字段， 可以选择是否返回该字段,此处不需要返回，应为user数据表中没有这个字段"""
<|body_0|>
def validate(self, attrs):
"""1. 可以取到所有字段，验证所有字段， 并返回字段 2. 可以按需添加和减少保存到model的字段 3. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserRegSerializer:
"""这个例子比较特殊应为使用了ModelSerializer,用户提交了多余code的字段，也就是该字段没有出现在Model中"""
def validate_code(self, code):
"""验证单个字段， 可以选择是否返回该字段,此处不需要返回，应为user数据表中没有这个字段"""
verify_records = VerifyCode.objects.filter(mobile=self.initial_data['username']).order_by('-add_time')
if verify... | the_stack_v2_python_sparse | apps/users/serializers.py | 15051882416/MxShop | train | 0 |
82eae91903eae504f1c4ddfaa51d327d32a920a7 | [
"if s.count('A') > 1 or s.count('LLL') > 0:\n return False\nreturn True",
"count_absent = 0\nfor chr in s:\n if chr == 'A':\n count_absent += 1\n if count_absent > 1:\n return False\nfor i in range(0, len(s) - 2):\n if s[i] == 'L' and s[i + 1] == 'L' and (s[i + 2] == 'L'):\n ... | <|body_start_0|>
if s.count('A') > 1 or s.count('LLL') > 0:
return False
return True
<|end_body_0|>
<|body_start_1|>
count_absent = 0
for chr in s:
if chr == 'A':
count_absent += 1
if count_absent > 1:
return Fa... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkRecord(self, s):
""":type s: str :rtype: bool Time Complexity: O(N)"""
<|body_0|>
def checkRecord1(self, s):
""":type s: str :rtype: bool Time Complexity: O(N)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if s.count('A') > 1 or... | stack_v2_sparse_classes_36k_train_024192 | 1,263 | no_license | [
{
"docstring": ":type s: str :rtype: bool Time Complexity: O(N)",
"name": "checkRecord",
"signature": "def checkRecord(self, s)"
},
{
"docstring": ":type s: str :rtype: bool Time Complexity: O(N)",
"name": "checkRecord1",
"signature": "def checkRecord1(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012530 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkRecord(self, s): :type s: str :rtype: bool Time Complexity: O(N)
- def checkRecord1(self, s): :type s: str :rtype: bool Time Complexity: O(N) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkRecord(self, s): :type s: str :rtype: bool Time Complexity: O(N)
- def checkRecord1(self, s): :type s: str :rtype: bool Time Complexity: O(N)
<|skeleton|>
class Solutio... | 96dd15210bcf9efe1f8cf31ce0566a7eabb3e221 | <|skeleton|>
class Solution:
def checkRecord(self, s):
""":type s: str :rtype: bool Time Complexity: O(N)"""
<|body_0|>
def checkRecord1(self, s):
""":type s: str :rtype: bool Time Complexity: O(N)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def checkRecord(self, s):
""":type s: str :rtype: bool Time Complexity: O(N)"""
if s.count('A') > 1 or s.count('LLL') > 0:
return False
return True
def checkRecord1(self, s):
""":type s: str :rtype: bool Time Complexity: O(N)"""
count_absent =... | the_stack_v2_python_sparse | Python/Student_Attendance_Record_I.py | abhi-verma/LeetCode-Algo | train | 0 | |
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_36k_train_024193 | 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_018736 | 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_36k | data/stack_v2_sparse_classes_30k | 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 | |
f24d9e1202ce469f85a88fb6c7406b3303f43d27 | [
"if len(name) == 7 and name[0] == '#':\n self.set_hex(name)\nelse:\n value = Color.colors.get(name, None)\n if value is None:\n raise ValueError(\"Unknown color name '{}'.\".format(name))\n if len(value) == 7:\n self.set_hex(value)\n else:\n self.red, self.green, self.blue = valu... | <|body_start_0|>
if len(name) == 7 and name[0] == '#':
self.set_hex(name)
else:
value = Color.colors.get(name, None)
if value is None:
raise ValueError("Unknown color name '{}'.".format(name))
if len(value) == 7:
self.set_he... | Lists of known colors. | Color | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Color:
"""Lists of known colors."""
def __init__(self, name):
"""@param name hexadecimal or name"""
<|body_0|>
def set_hex(self, name):
"""Converts a string like ``#AABBCC`` into `(red, green, blue)`."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_024194 | 6,106 | permissive | [
{
"docstring": "@param name hexadecimal or name",
"name": "__init__",
"signature": "def __init__(self, name)"
},
{
"docstring": "Converts a string like ``#AABBCC`` into `(red, green, blue)`.",
"name": "set_hex",
"signature": "def set_hex(self, name)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002581 | Implement the Python class `Color` described below.
Class description:
Lists of known colors.
Method signatures and docstrings:
- def __init__(self, name): @param name hexadecimal or name
- def set_hex(self, name): Converts a string like ``#AABBCC`` into `(red, green, blue)`. | Implement the Python class `Color` described below.
Class description:
Lists of known colors.
Method signatures and docstrings:
- def __init__(self, name): @param name hexadecimal or name
- def set_hex(self, name): Converts a string like ``#AABBCC`` into `(red, green, blue)`.
<|skeleton|>
class Color:
"""Lists o... | 33af98adb093f525df7fac7c86613fa7cd181b44 | <|skeleton|>
class Color:
"""Lists of known colors."""
def __init__(self, name):
"""@param name hexadecimal or name"""
<|body_0|>
def set_hex(self, name):
"""Converts a string like ``#AABBCC`` into `(red, green, blue)`."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Color:
"""Lists of known colors."""
def __init__(self, name):
"""@param name hexadecimal or name"""
if len(name) == 7 and name[0] == '#':
self.set_hex(name)
else:
value = Color.colors.get(name, None)
if value is None:
raise Value... | the_stack_v2_python_sparse | src/pyensae/graphhelper/_colormap.py | sdpython/pyensae | train | 33 |
c2c9ce14160360a314affb15f2cb2182929fdbc9 | [
"form = EngineerAddForm(request.POST or None)\nif form.is_valid():\n instance = form.save(commit=False)\n instance.added_by = self.request.user\n instance.save()\n messages.add_message(request, messages.INFO, 'Success - Engineer added successfully')\n return redirect('engineers:engineer_view')\nmessa... | <|body_start_0|>
form = EngineerAddForm(request.POST or None)
if form.is_valid():
instance = form.save(commit=False)
instance.added_by = self.request.user
instance.save()
messages.add_message(request, messages.INFO, 'Success - Engineer added successfully')... | EngineerView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EngineerView:
def post(self, request):
"""Adds new engineer from engineer_list_view page modal"""
<|body_0|>
def get(self, request):
"""Returns list of all engineers"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
form = EngineerAddForm(request.POST... | stack_v2_sparse_classes_36k_train_024195 | 3,806 | no_license | [
{
"docstring": "Adds new engineer from engineer_list_view page modal",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "Returns list of all engineers",
"name": "get",
"signature": "def get(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017815 | Implement the Python class `EngineerView` described below.
Class description:
Implement the EngineerView class.
Method signatures and docstrings:
- def post(self, request): Adds new engineer from engineer_list_view page modal
- def get(self, request): Returns list of all engineers | Implement the Python class `EngineerView` described below.
Class description:
Implement the EngineerView class.
Method signatures and docstrings:
- def post(self, request): Adds new engineer from engineer_list_view page modal
- def get(self, request): Returns list of all engineers
<|skeleton|>
class EngineerView:
... | bdd7c5ca9f00ce33be31609e5be9c2ccfcd8743a | <|skeleton|>
class EngineerView:
def post(self, request):
"""Adds new engineer from engineer_list_view page modal"""
<|body_0|>
def get(self, request):
"""Returns list of all engineers"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EngineerView:
def post(self, request):
"""Adds new engineer from engineer_list_view page modal"""
form = EngineerAddForm(request.POST or None)
if form.is_valid():
instance = form.save(commit=False)
instance.added_by = self.request.user
instance.save(... | the_stack_v2_python_sparse | engineers/views.py | mrmaheshrajput/htscrm | train | 0 | |
90a9ed3c1e74272b231c151469c24e9cad6dbc83 | [
"if quadrant_letter == 'B' or quadrant_letter == 'C':\n return cls.left(parallel_size=parallel_size, serial_size=serial_size, serial_prescan_size=serial_prescan_size, parallel_overscan_size=parallel_overscan_size)\nelif quadrant_letter == 'A' or quadrant_letter == 'D':\n return cls.right(parallel_size=paralle... | <|body_start_0|>
if quadrant_letter == 'B' or quadrant_letter == 'C':
return cls.left(parallel_size=parallel_size, serial_size=serial_size, serial_prescan_size=serial_prescan_size, parallel_overscan_size=parallel_overscan_size)
elif quadrant_letter == 'A' or quadrant_letter == 'D':
... | Layout2DACS | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Layout2DACS:
def from_ccd(cls, quadrant_letter, parallel_size=2068, serial_size=2072, serial_prescan_size=24, parallel_overscan_size=20):
"""Using an input array of both quadrants in electrons, use the quadrant letter to extract the quadrant from the full CCD and perform the rotations re... | stack_v2_sparse_classes_36k_train_024196 | 13,170 | permissive | [
{
"docstring": "Using an input array of both quadrants in electrons, use the quadrant letter to extract the quadrant from the full CCD and perform the rotations required to give correct arctic. See the docstring of the `FrameACS` class for a complete description of the Euclid FPA, quadrants and rotations.",
... | 3 | stack_v2_sparse_classes_30k_test_000291 | Implement the Python class `Layout2DACS` described below.
Class description:
Implement the Layout2DACS class.
Method signatures and docstrings:
- def from_ccd(cls, quadrant_letter, parallel_size=2068, serial_size=2072, serial_prescan_size=24, parallel_overscan_size=20): Using an input array of both quadrants in elect... | Implement the Python class `Layout2DACS` described below.
Class description:
Implement the Layout2DACS class.
Method signatures and docstrings:
- def from_ccd(cls, quadrant_letter, parallel_size=2068, serial_size=2072, serial_prescan_size=24, parallel_overscan_size=20): Using an input array of both quadrants in elect... | c21e8859bdb20737352147b9904797ac99985b73 | <|skeleton|>
class Layout2DACS:
def from_ccd(cls, quadrant_letter, parallel_size=2068, serial_size=2072, serial_prescan_size=24, parallel_overscan_size=20):
"""Using an input array of both quadrants in electrons, use the quadrant letter to extract the quadrant from the full CCD and perform the rotations re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Layout2DACS:
def from_ccd(cls, quadrant_letter, parallel_size=2068, serial_size=2072, serial_prescan_size=24, parallel_overscan_size=20):
"""Using an input array of both quadrants in electrons, use the quadrant letter to extract the quadrant from the full CCD and perform the rotations required to give... | the_stack_v2_python_sparse | autoarray/instruments/acs.py | jonathanfrawley/PyAutoArray_copy | train | 0 | |
2c94347df29165ac2a5109083de89f3ed8cec80b | [
"try:\n customer, _created = Customer.get_or_create(subscriber=subscriber_request_callback(self.request))\n serializer = SubscriptionSerializer(customer.subscription)\n return Response(serializer.data)\nexcept:\n return Response(status=status.HTTP_204_NO_CONTENT)",
"serializer = CreateSubscriptionSeri... | <|body_start_0|>
try:
customer, _created = Customer.get_or_create(subscriber=subscriber_request_callback(self.request))
serializer = SubscriptionSerializer(customer.subscription)
return Response(serializer.data)
except:
return Response(status=status.HTTP_2... | API Endpoints for the Subscription object. | SubscriptionRestView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubscriptionRestView:
"""API Endpoints for the Subscription object."""
def get(self, request, **kwargs):
"""Return the customer's valid subscriptions. Returns with status code 200."""
<|body_0|>
def post(self, request, **kwargs):
"""Create a new current subscript... | stack_v2_sparse_classes_36k_train_024197 | 4,950 | permissive | [
{
"docstring": "Return the customer's valid subscriptions. Returns with status code 200.",
"name": "get",
"signature": "def get(self, request, **kwargs)"
},
{
"docstring": "Create a new current subscription for the user. Returns with status code 201.",
"name": "post",
"signature": "def p... | 3 | stack_v2_sparse_classes_30k_train_020253 | Implement the Python class `SubscriptionRestView` described below.
Class description:
API Endpoints for the Subscription object.
Method signatures and docstrings:
- def get(self, request, **kwargs): Return the customer's valid subscriptions. Returns with status code 200.
- def post(self, request, **kwargs): Create a ... | Implement the Python class `SubscriptionRestView` described below.
Class description:
API Endpoints for the Subscription object.
Method signatures and docstrings:
- def get(self, request, **kwargs): Return the customer's valid subscriptions. Returns with status code 200.
- def post(self, request, **kwargs): Create a ... | 325cc11fbc28eee7507778e387714e9465880d68 | <|skeleton|>
class SubscriptionRestView:
"""API Endpoints for the Subscription object."""
def get(self, request, **kwargs):
"""Return the customer's valid subscriptions. Returns with status code 200."""
<|body_0|>
def post(self, request, **kwargs):
"""Create a new current subscript... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubscriptionRestView:
"""API Endpoints for the Subscription object."""
def get(self, request, **kwargs):
"""Return the customer's valid subscriptions. Returns with status code 200."""
try:
customer, _created = Customer.get_or_create(subscriber=subscriber_request_callback(self.... | the_stack_v2_python_sparse | djstripe/contrib/rest_framework/views.py | talpor/dj-stripe | train | 1 |
cdd77d970a7410d0e667f5f9de62b8c45688df49 | [
"super().__init__(env, name, agent_seed)\nself.mpc_policy = StationaryActionMPCPolicy(env.physical_constituency_matrix, mpc_seed)\nself.method = method\nself.binary_action = binary_action",
"_, num_activities = self.constituency_matrix.shape\nz = cvx.Variable((num_activities, 1), boolean=self.binary_action)\ndiag... | <|body_start_0|>
super().__init__(env, name, agent_seed)
self.mpc_policy = StationaryActionMPCPolicy(env.physical_constituency_matrix, mpc_seed)
self.method = method
self.binary_action = binary_action
<|end_body_0|>
<|body_start_1|>
_, num_activities = self.constituency_matrix.s... | MaxWeightLpAgent | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaxWeightLpAgent:
def __init__(self, env: crw.ControlledRandomWalk, method: str='cvx.ECOS', name: str='MaxWeightLpAgent', binary_action: Optional[bool]=False, agent_seed: Optional[int]=None, mpc_seed: Optional[int]=None) -> None:
"""MaxWeight policy for general push models. :param env: C... | stack_v2_sparse_classes_36k_train_024198 | 5,659 | permissive | [
{
"docstring": "MaxWeight policy for general push models. :param env: CRW environment. :param method: Optimisation method/solver that CVXPY should use to solve the LP. :param name: Agent identifier. :param binary_action: where the problem is an MIP with binary variables or not. :param agent_seed: Agent random s... | 3 | stack_v2_sparse_classes_30k_train_000911 | Implement the Python class `MaxWeightLpAgent` described below.
Class description:
Implement the MaxWeightLpAgent class.
Method signatures and docstrings:
- def __init__(self, env: crw.ControlledRandomWalk, method: str='cvx.ECOS', name: str='MaxWeightLpAgent', binary_action: Optional[bool]=False, agent_seed: Optional[... | Implement the Python class `MaxWeightLpAgent` described below.
Class description:
Implement the MaxWeightLpAgent class.
Method signatures and docstrings:
- def __init__(self, env: crw.ControlledRandomWalk, method: str='cvx.ECOS', name: str='MaxWeightLpAgent', binary_action: Optional[bool]=False, agent_seed: Optional[... | b067eebaa5b57a96efdaed5796aca9f157d32214 | <|skeleton|>
class MaxWeightLpAgent:
def __init__(self, env: crw.ControlledRandomWalk, method: str='cvx.ECOS', name: str='MaxWeightLpAgent', binary_action: Optional[bool]=False, agent_seed: Optional[int]=None, mpc_seed: Optional[int]=None) -> None:
"""MaxWeight policy for general push models. :param env: C... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MaxWeightLpAgent:
def __init__(self, env: crw.ControlledRandomWalk, method: str='cvx.ECOS', name: str='MaxWeightLpAgent', binary_action: Optional[bool]=False, agent_seed: Optional[int]=None, mpc_seed: Optional[int]=None) -> None:
"""MaxWeight policy for general push models. :param env: CRW environment... | the_stack_v2_python_sparse | src/snc/agents/maxweight_variants/maxweight_lp.py | stochasticnetworkcontrol/snc | train | 9 | |
daa097f3dc119982264276f6744749f005b9cb91 | [
"msg = await self._state.fetch_user_csgo_profile(self.id)\nif not msg.account_profiles:\n raise ValueError\nreturn ProfileInfo(self, msg.account_profiles[0])",
"future = self._state.ws.gc_wait_for(cstrike.MatchList, check=lambda msg: msg.msgrequestid == cstrike.MatchListRequestRecentUserGames.MSG and msg.accou... | <|body_start_0|>
msg = await self._state.fetch_user_csgo_profile(self.id)
if not msg.account_profiles:
raise ValueError
return ProfileInfo(self, msg.account_profiles[0])
<|end_body_0|>
<|body_start_1|>
future = self._state.ws.gc_wait_for(cstrike.MatchList, check=lambda msg: ... | PartialUser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PartialUser:
async def csgo_profile(self) -> ProfileInfo[Self]:
"""Fetches this users CSGO profile info."""
<|body_0|>
async def recent_matches(self) -> Matches:
"""Fetches this user's recent games."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ms... | stack_v2_sparse_classes_36k_train_024199 | 7,623 | permissive | [
{
"docstring": "Fetches this users CSGO profile info.",
"name": "csgo_profile",
"signature": "async def csgo_profile(self) -> ProfileInfo[Self]"
},
{
"docstring": "Fetches this user's recent games.",
"name": "recent_matches",
"signature": "async def recent_matches(self) -> Matches"
}
] | 2 | stack_v2_sparse_classes_30k_train_005015 | Implement the Python class `PartialUser` described below.
Class description:
Implement the PartialUser class.
Method signatures and docstrings:
- async def csgo_profile(self) -> ProfileInfo[Self]: Fetches this users CSGO profile info.
- async def recent_matches(self) -> Matches: Fetches this user's recent games. | Implement the Python class `PartialUser` described below.
Class description:
Implement the PartialUser class.
Method signatures and docstrings:
- async def csgo_profile(self) -> ProfileInfo[Self]: Fetches this users CSGO profile info.
- async def recent_matches(self) -> Matches: Fetches this user's recent games.
<|s... | 3075c6065babcd8a67052593d4b31d10c20edabe | <|skeleton|>
class PartialUser:
async def csgo_profile(self) -> ProfileInfo[Self]:
"""Fetches this users CSGO profile info."""
<|body_0|>
async def recent_matches(self) -> Matches:
"""Fetches this user's recent games."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PartialUser:
async def csgo_profile(self) -> ProfileInfo[Self]:
"""Fetches this users CSGO profile info."""
msg = await self._state.fetch_user_csgo_profile(self.id)
if not msg.account_profiles:
raise ValueError
return ProfileInfo(self, msg.account_profiles[0])
... | the_stack_v2_python_sparse | steam/ext/csgo/models.py | Gobot1234/steam.py | train | 144 |
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